diff --git a/.github/workflows/soak.yaml b/.github/workflows/soak.yaml index b3c02dd11..ff0b3234e 100644 --- a/.github/workflows/soak.yaml +++ b/.github/workflows/soak.yaml @@ -15,7 +15,7 @@ jobs: SOAK_RATE_PER_SEC: "1000" MQTT_TOPIC: "mqtt/soak" KAFKA_TOPIC: "dev-robot-alerts" - LOSS_THRESHOLD_PCT: "1.0" # סף כשל: % אובדן מותר (שני לפי הצורך) + LOSS_THRESHOLD_PCT: "1.0" steps: - name: Checkout @@ -248,10 +248,7 @@ jobs: if: always() run: | set -euo pipefail - # ודא שהצרכן נעצר if [ -f kcat.pid ]; then kill -9 "$(cat kcat.pid)" 2>/dev/null || true; fi - # נקה את סביבת ה-compose docker compose down -v || true - # ניקוי נוסף למקרה של שאריות docker ps -aq | xargs -r docker rm -f || true docker network prune -f || true diff --git a/.gitignore b/.gitignore index 348249e4c..1f4c108c4 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,8 @@ +data/rover_samples/** +!data/rover_samples/.gitkeep + +# Ignore data payloads +/data/ # --- Secrets and Certificates --- *.env *.crt @@ -10,12 +15,22 @@ MQTT_IMAGES/secrets/ services/sounds/sounds_classifier/src/classification/data/ services/sounds/sounds_classifier/src/classification/models/panns_data/ +# Ignore environment and IDE files +.env + # --- Python --- __pycache__/ +*.py[cod] *.pyc *.pyo *.pyd *.pytest_cache/ +.pytest_cache/ +<<<<<<< HEAD +======= + + +>>>>>>> 4bb2e60fc0fd9a846955fa89533d661a56b1645a .venv/ venv/ .coverage @@ -38,3 +53,50 @@ venv/ .DS_Store Thumbs.db + +# ==== Training/experiment outputs (never version) ==== +# Any top-level or nested "runs" folders created by Ultralytics or notebooks +runs*/ +**/runs*/ + +# ==== Model weights from training (PyTorch checkpoints) ==== +# Keep weights out of Git; publish via Releases/Artifacts instead. +<<<<<<< HEAD +!services/inference_http/models/fence_hole_detector/weights/ +!services/inference_http/models/fence_hole_detector/weights/best.onnx + +# ==== Model weights from training (PyTorch checkpoints) ==== +# Keep weights out of Git; publish via Releases/Artifacts instead. +======= +!services/fence_hole_detector/weights/ +!services/fence_hole_detector/weights/best.onnx + +>>>>>>> 4bb2e60fc0fd9a846955fa89533d661a56b1645a +runs_fence/**/weights/*.pt + +# ==== Prediction artifacts (images + txt) ==== +# Generic preds folders created by `yolo predict` +runs_fence/**/preds/** +runs_fence/*_preds/** + +# Specific experiment outputs you listed (safe to ignore entirely) +runs_fence/y8n_baseline_no_roi/** +runs_fence/y8n_baseline_vote_soft/** +runs_fence/y8n_realtime_preds_no_roi/** +runs_fence/y8s_cpu_v1_preds/** + +# ==== Logs / plots (reproducible – don’t store) ==== +**/results.png +**/confusion_matrix.png +**/*.log + +# ==== Optional: large exported models (keep if you plan to ship them) ==== +# Uncomment to ignore ONNX as well; otherwise keep the single runtime ONNX in repo. +runs_fence/**/weights/*.onnx + +models/*.pt +<<<<<<< HEAD +======= + +.coverage +>>>>>>> 4bb2e60fc0fd9a846955fa89533d661a56b1645a diff --git 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+ b = json.dumps(body).encode() + self.send_response(200) + self.send_header("Content-Type", "application/json") + self.send_header("Content-Length", str(len(b))) + self.end_headers() + self.wfile.write(b) + + def log_message(self, *a): + pass + +if __name__ == "__main__": + print("[mock-db-api] listening on 127.0.0.1:8001") + HTTPServer(("127.0.0.1", 8001), H).serve_forever() diff --git a/GUI/requirements.txt b/GUI/requirements.txt index 96080bc7a..779d432a9 100644 --- a/GUI/requirements.txt +++ b/GUI/requirements.txt @@ -1,6 +1,9 @@ -PyQt6==6.7.1 -PyQt6-WebEngine==6.7.0 +PyQt6==6.9.1 +PyQt6-WebEngine==6.9.0 +PyQt6-Charts==6.9.0 +PyQt6-Qt6==6.9.1 +PyQt6-sip>=13.6 python-vlc @@ -29,9 +32,21 @@ shapely # ───── Async / misc ───── aiohttp + +folium plotly shapely PyJWT>=2.9.0 sip +SQLAlchemy>=2.0 +geoalchemy2>=0.15.0 + +tenacity>=8.2 +openai>=1.0.0 +python-dotenv>=1.0.0 +jsonschema>=4.0.0 +psycopg2-binary>=2.9.0 +matplotlib>=3.7.0 + diff --git a/GUI/src/vast/alerts/alert_service.py b/GUI/src/vast/alerts/alert_service.py index c6c28e50f..8014e0f86 100644 --- a/GUI/src/vast/alerts/alert_service.py +++ b/GUI/src/vast/alerts/alert_service.py @@ -1,4 +1,5 @@ import yaml +import json, ast from string import Template from PyQt6.QtCore import QObject, pyqtSignal from vast.alerts.alert_client import AlertClient @@ -39,7 +40,7 @@ def _load_templates(self, path): # ──────────────────────────────── def load_devices(self): try: - url = f"{self.api.base}/api/tables/devices" + url = f"{self.api.base}/api/tables/devices?limit=500" r = self.api.http.get(url, timeout=10) r.raise_for_status() data = r.json() @@ -58,7 +59,7 @@ def load_devices(self): # ──────────────────────────────── def load_initial(self): try: - url = f"{self.api.base}/api/tables/alerts" + url = f"{self.api.base}/api/tables/alerts?limit=500" r = self.api.http.get(url, timeout=10) r.raise_for_status() data = r.json() @@ -76,21 +77,49 @@ def load_initial(self): if not a.get("lon") and lon: a["lon"] = lon - # Apply template enrichment + # ───────────── ENRICH ALERT WITH TEMPLATE ───────────── tmpl = self.templates.get(alert_type) if tmpl: - a["category"] = tmpl.get("category") + raw_meta = a.get("meta", {}) or {} + meta = {} + + # FIX: correct meta parsing + if isinstance(raw_meta, dict): + meta = raw_meta + elif isinstance(raw_meta, str): + try: + meta = json.loads(raw_meta) + except Exception: + try: + meta = ast.literal_eval(raw_meta) + except Exception: + meta = {} + + subject = meta.get("subject", "animal") + severity = int(a.get("severity", meta.get("severity", 1))) + + # build context context = { "device_id": device_id, "area": a.get("area", "unknown area"), "confidence": a.get("confidence", "?"), "timestamp": a.get("started_at", ""), + "subject": subject, + "severity": severity, + "started_at": a.get("startsAt", ""), } - # Use Template.safe_substitute to avoid KeyErrors + + # enrich record + a["category"] = tmpl.get("category") + a["severity"] = severity + a["subject"] = subject a["summary"] = Template(tmpl.get("summary", "")).safe_substitute(context) a["recommendation"] = Template(tmpl.get("recommendation", "")).safe_substitute(context) self.alerts = alerts + self.alerts.sort( + key=lambda a: a.get("started_at") or a.get("startsAt") or "", + ) self.alertsUpdated.emit(self.alerts) print(f"[AlertService] Loaded {len(alerts)} enriched alerts.") except Exception as e: @@ -101,7 +130,6 @@ def load_initial(self): # ──────────────────────────────── def _on_realtime(self, alert_msg): alerts = alert_msg.get("alerts", []) - print("[AlertService] Realtime message:", alert_msg) for a in alerts: labels = a.get("labels", {}) @@ -112,25 +140,20 @@ def _on_realtime(self, alert_msg): ends_at = a.get("endsAt") is_resolved = ends_at and not ends_at.startswith("0001-01-01") - # Find existing alert in memory + # Find existing alert existing = next((al for al in self.alerts if al.get("alert_id") == alert_id), None) if is_resolved: - # ✅ Don't delete — update existing alert with endedAt timestamp if existing: existing["endedAt"] = ends_at self.alertRemoved.emit(alert_id) else: - # If not in memory (e.g. loaded from DB earlier) - # create a minimal record so the UI can update fake_alert = {"alert_id": alert_id, "endedAt": ends_at} self.alerts.append(fake_alert) self.alertRemoved.emit(alert_id) continue - # ──────────────────────────────── - # ACTIVE alert (new or ongoing) - # ──────────────────────────────── + # ACTIVE alert lat = ann.get("lat") lon = ann.get("lon") @@ -139,14 +162,44 @@ def _on_realtime(self, alert_msg): lat, lon = self.device_locations[device_id] print(f"[AlertService] Filled missing coords for {device_id}: ({lat}, {lon})") - # Enrich with template + # ──────────────────────────────── + # FIXED meta parsing + # ──────────────────────────────── tmpl = self.templates.get(alert_type, {}) + raw_meta = ann.get("meta", {}) or {} + meta = {} + + if isinstance(raw_meta, dict): + meta = raw_meta + elif isinstance(raw_meta, str): + try: + meta = json.loads(raw_meta) + except Exception: + try: + meta = ast.literal_eval(raw_meta) + except Exception: + meta = {} + + subject = meta.get("subject", "animal") + severity = int(ann.get("severity", 1)) + started_at = a.get("startsAt") or "" + summary = Template(tmpl.get("summary", "")).safe_substitute( device_id=device_id, area=ann.get("area", ""), confidence=ann.get("confidence", ""), + subject=subject, + severity=severity, + started_at=started_at, ) - recommendation = tmpl.get("recommendation", "") + + recommendation = Template(tmpl.get("recommendation", "")).safe_substitute( + device_id=device_id, + area=ann.get("area", ""), + subject=subject, + severity=severity, + ) + category = tmpl.get("category") normalized = { @@ -155,7 +208,7 @@ def _on_realtime(self, alert_msg): "device_id": device_id, "lat": lat, "lon": lon, - "severity": int(ann.get("severity", 1)), + "severity": severity, "summary": summary, "recommendation": recommendation, "category": category, @@ -165,29 +218,31 @@ def _on_realtime(self, alert_msg): "startsAt": a.get("startsAt"), } - # Update if it already exists, else append if existing: existing.update(normalized) else: self.alerts.append(normalized) + self.alerts.sort( + key=lambda a: a.get("started_at") or a.get("startsAt") or "", + ) + self.alertAdded.emit(normalized) - + # ──────────────────────────────── + # Mark all as acknowledged + # ──────────────────────────────── def mark_all_acknowledged(self): - """Mark all alerts as acknowledged both locally and in DB (PATCH /api/tables/alerts).""" unacked = [a for a in self.alerts if not a.get("ack", False)] if not unacked: return - # Update local memory first for a in unacked: a["ack"] = True - # Push updates asynchronously to DB def _patch_ack(alert): try: - url = f"{self.api.base}/api/tables/alerts" + url = f"{self.api.base}/api/tables/alerts?limit=500" payload = { "keys": {"alert_id": alert["alert_id"]}, "data": {"ack": True}, @@ -202,8 +257,4 @@ def _patch_ack(alert): pool.submit(_patch_ack, a) self.alertsUpdated.emit(self.alerts) - print(f"[AlertService] Marked {len(unacked)} alerts as acknowledged.") - - - - + print(f"[AlertService] Marked {len(unacked)} alerts as acknowledged.") \ No newline at end of file diff --git a/GUI/src/vast/dashboard_api.py b/GUI/src/vast/dashboard_api.py index 00a3b2de8..790605fa3 100644 --- a/GUI/src/vast/dashboard_api.py +++ b/GUI/src/vast/dashboard_api.py @@ -442,3 +442,373 @@ def get_phi_for_current_image(self) -> dict: return {"phi": None, "severity_avg": None, "density": None, "coverage": None, "trend": None} image_id = _image_id_from_object_key(key) return self.rdb.get_phi_for_image(image_id) + + + # ===================================================== + # ===== AUDIO ANALYTICS METHODS WITH SOUND FILTER ===== + # ===================================================== + + def get_audio_stats(self, time_range: str = 'all', sound_types: List[str] = None) -> Dict: + """Get aggregated audio classification statistics""" + time_filter = { + 'all': '', + 'hour': "AND r.started_at > NOW() - INTERVAL '1 hour'", + 'day': "AND r.started_at > NOW() - INTERVAL '24 hours'", + 'week': "AND r.started_at > NOW() - INTERVAL '7 days'", + 'month': "AND r.started_at > NOW() - INTERVAL '30 days'" + }.get(time_range, '') + + sound_filter = "" + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_list})" + + query = f""" + SELECT + COUNT(*) as total_files, + SUM(CASE WHEN head_is_another = true THEN 1 ELSE 0 END) as unknown_count, + AVG(head_pred_prob) as avg_confidence, + AVG(processing_ms) as avg_processing_ms + FROM agcloud_audio.file_aggregates fa + JOIN agcloud_audio.runs r ON fa.run_id = r.run_id + WHERE 1=1 {time_filter} {sound_filter} + """ + + results = self.run_query(query) + return results[0] if results else {} + + def get_audio_distribution(self, time_range: str = 'all', limit: int = 10, sound_types: List[str] = None) -> List[Dict]: + """Get distribution of audio classifications""" + time_filter = { + 'all': '', + 'hour': "AND r.started_at > NOW() - INTERVAL '1 hour'", + 'day': "AND r.started_at > NOW() - INTERVAL '24 hours'", + 'week': "AND r.started_at > NOW() - INTERVAL '7 days'", + 'month': "AND r.started_at > NOW() - INTERVAL '30 days'" + }.get(time_range, '') + + sound_filter = "" + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_list})" + + query = f""" + SELECT + head_pred_label, + COUNT(*) as count + FROM agcloud_audio.file_aggregates fa + JOIN agcloud_audio.runs r ON fa.run_id = r.run_id + WHERE head_pred_label IS NOT NULL {time_filter} {sound_filter} + GROUP BY head_pred_label + ORDER BY count DESC + LIMIT {limit} + """ + + return self.run_query(query) + + def get_audio_confidence_by_class(self, time_range: str = 'all', limit: int = 10, sound_types: List[str] = None) -> List[Dict]: + """Get average confidence levels by classification""" + time_filter = { + 'all': '', + 'hour': "AND r.started_at > NOW() - INTERVAL '1 hour'", + 'day': "AND r.started_at > NOW() - INTERVAL '24 hours'", + 'week': "AND r.started_at > NOW() - INTERVAL '7 days'", + 'month': "AND r.started_at > NOW() - INTERVAL '30 days'" + }.get(time_range, '') + + sound_filter = "" + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_list})" + + query = f""" + SELECT + head_pred_label, + AVG(head_pred_prob) as avg_confidence + FROM agcloud_audio.file_aggregates fa + JOIN agcloud_audio.runs r ON fa.run_id = r.run_id + WHERE head_pred_label IS NOT NULL + AND head_pred_prob IS NOT NULL + {time_filter} + {sound_filter} + GROUP BY head_pred_label + ORDER BY avg_confidence DESC + LIMIT {limit} + """ + + return self.run_query(query) + + def get_audio_detailed_table(self, time_range: str = 'all', limit: int = 20, sound_types: List[str] = None) -> List[Dict]: + """Get detailed table data with class probabilities""" + time_filter = { + 'all': '', + 'hour': "AND r.started_at > NOW() - INTERVAL '1 hour'", + 'day': "AND r.started_at > NOW() - INTERVAL '24 hours'", + 'week': "AND r.started_at > NOW() - INTERVAL '7 days'", + 'month': "AND r.started_at > NOW() - INTERVAL '30 days'" + }.get(time_range, '') + + sound_filter = "" + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_list})" + + query = f""" + SELECT + head_pred_label, + COUNT(*) as count, + AVG(head_pred_prob) as avg_prob, + AVG((head_probs_json->>'predatory_animals')::float) as p_predatory, + AVG((head_probs_json->>'birds')::float) as p_birds, + AVG((head_probs_json->>'fire')::float) as p_fire, + AVG((head_probs_json->>'screaming')::float) as p_screaming, + AVG((head_probs_json->>'shotgun')::float) as p_shotgun + FROM agcloud_audio.file_aggregates fa + JOIN agcloud_audio.runs r ON fa.run_id = r.run_id + WHERE head_pred_label IS NOT NULL {time_filter} {sound_filter} + GROUP BY head_pred_label + ORDER BY count DESC + LIMIT {limit} + """ + + return self.run_query(query) + + def get_audio_critical_events(self, time_range: str = 'day', limit: int = 100, sound_types: List[str] = None) -> List[Dict]: + """Get critical sound events""" + time_filter = { + 'hour': "AND r.started_at > NOW() - INTERVAL '1 hour'", + 'day': "AND r.started_at > NOW() - INTERVAL '24 hours'", + 'week': "AND r.started_at > NOW() - INTERVAL '7 days'", + 'month': "AND r.started_at > NOW() - INTERVAL '30 days'" + }.get(time_range, "AND r.started_at > NOW() - INTERVAL '24 hours'") + + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_list})" + else: + sound_filter = "AND fa.head_pred_label IN ('fire', 'screaming', 'shotgun', 'predatory_animals')" + + query = f""" + SELECT + r.run_id, + r.started_at, + f.path as file_path, + fa.head_pred_label as event_type, + fa.head_pred_prob as confidence, + fa.head_probs_json + FROM agcloud_audio.file_aggregates fa + JOIN agcloud_audio.runs r ON fa.run_id = r.run_id + JOIN agcloud_audio.files f ON fa.file_id = f.file_id + WHERE 1=1 + {time_filter} + {sound_filter} + ORDER BY r.started_at DESC, fa.head_pred_prob DESC + LIMIT {limit} + """ + + return self.run_query(query) + + def get_audio_timeline(self, time_range: str = 'day', sound_types: List[str] = None) -> List[Dict]: + """Get audio alert timeline data grouped by time buckets""" + bucket_interval = { + 'day': 1, + 'week': 6, + 'month': 24 + }.get(time_range, 1) + + time_filter_map = { + 'day': "AND r.started_at > NOW() - INTERVAL '24 hours'", + 'week': "AND r.started_at > NOW() - INTERVAL '7 days'", + 'month': "AND r.started_at > NOW() - INTERVAL '30 days'" + } + time_filter = time_filter_map.get(time_range, "AND r.started_at > NOW() - INTERVAL '24 hours'") + + sound_filter = "" + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_list})" + + query = f""" + SELECT + date_trunc('hour', r.started_at) + + INTERVAL '{bucket_interval} hours' * + (EXTRACT(hour FROM r.started_at)::int / {bucket_interval}) as time_bucket, + fa.head_pred_label, + COUNT(*) as count + FROM agcloud_audio.file_aggregates fa + JOIN agcloud_audio.runs r ON fa.run_id = r.run_id + WHERE fa.head_pred_label IS NOT NULL + {time_filter} + {sound_filter} + GROUP BY time_bucket, fa.head_pred_label + ORDER BY time_bucket ASC, count DESC + """ + + return self.run_query(query) + + def get_audio_heatmap(self, time_range: str = 'week', sound_types: List[str] = None) -> List[Dict]: + """Get audio detection heatmap data - hour of day vs day of week""" + time_filter_map = { + 'day': "AND r.started_at > NOW() - INTERVAL '24 hours'", + 'week': "AND r.started_at > NOW() - INTERVAL '7 days'", + 'month': "AND r.started_at > NOW() - INTERVAL '30 days'" + } + time_filter = time_filter_map.get(time_range, "AND r.started_at > NOW() - INTERVAL '7 days'") + + sound_filter = "" + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_list})" + + query = f""" + SELECT + EXTRACT(HOUR FROM r.started_at) as hour_of_day, + EXTRACT(DOW FROM r.started_at) as day_of_week, + fa.head_pred_label as sound_type, + COUNT(*) as count + FROM agcloud_audio.file_aggregates fa + JOIN agcloud_audio.runs r ON fa.run_id = r.run_id + WHERE fa.head_pred_label IS NOT NULL + {time_filter} + {sound_filter} + GROUP BY hour_of_day, day_of_week, fa.head_pred_label + ORDER BY day_of_week, hour_of_day + """ + + return self.run_query(query) + + def get_audio_correlations(self, time_range: str = 'day', sound_types: List[str] = None) -> List[Dict]: + """Get sound detection data for correlation analysis using linked_time from sound_new_sounds_connections""" + bucket_interval = { + 'day': 1, + 'week': 6, + 'month': 24 + }.get(time_range, 1) + + time_filter_map = { + 'day': "AND c.linked_time > NOW() - INTERVAL '24 hours'", + 'week': "AND c.linked_time > NOW() - INTERVAL '7 days'", + 'month': "AND c.linked_time > NOW() - INTERVAL '30 days'" + } + time_filter = time_filter_map.get(time_range, "AND c.linked_time > NOW() - INTERVAL '24 hours'") + + sound_filter = "" + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_list})" + + query = f""" + SELECT + (date_trunc('hour', c.linked_time) + - (INTERVAL '1 hour' * (EXTRACT(hour FROM c.linked_time)::int % {bucket_interval})) + ) AS time_bucket, + fa.head_pred_label AS sound_type, + COUNT(*) AS detection_count + FROM agcloud_audio.file_aggregates fa + JOIN public.sound_new_sounds_connections c + ON c.id = fa.file_id + WHERE fa.head_pred_label IS NOT NULL + {time_filter} + {sound_filter} + GROUP BY time_bucket, fa.head_pred_label + ORDER BY time_bucket ASC + """ + + return self.run_query(query) + + def get_model_health_metrics(self, time_range: str = 'day', sound_types: List[str] = None) -> List[Dict]: + """Get model health metrics over time""" + bucket_interval = { + 'day': 1, + 'week': 6, + 'month': 24 + }.get(time_range, 1) + + time_filter_map = { + 'day': "AND r.started_at > NOW() - INTERVAL '24 hours'", + 'week': "AND r.started_at > NOW() - INTERVAL '7 days'", + 'month': "AND r.started_at > NOW() - INTERVAL '30 days'" + } + time_filter = time_filter_map.get(time_range, "AND r.started_at > NOW() - INTERVAL '24 hours'") + + sound_filter = "" + if sound_types and len(sound_types) > 0: + sound_list = "'" + "','".join(sound_types) + "'" + sound_filter = f"AND fa.head_pred_label IN ({sound_filter})" + + query = f""" + SELECT + date_trunc('hour', r.started_at) + + INTERVAL '{bucket_interval} hours' * + (EXTRACT(hour FROM r.started_at)::int / {bucket_interval}) as time_bucket, + AVG(fa.head_pred_prob) as avg_confidence, + AVG(fa.processing_ms) as avg_processing_ms, + COUNT(*) as total_predictions, + SUM(CASE WHEN fa.head_is_another = true THEN 1 ELSE 0 END) as unknown_count, + (SUM(CASE WHEN fa.head_is_another = true THEN 1 ELSE 0 END)::float / + NULLIF(COUNT(*), 0)) * 100 as error_rate_pct + FROM agcloud_audio.file_aggregates fa + JOIN agcloud_audio.runs r ON fa.run_id = r.run_id + WHERE fa.head_pred_label IS NOT NULL + {time_filter} + {sound_filter} + GROUP BY time_bucket + ORDER BY time_bucket ASC + """ + + return self.run_query(query) + + + # ===================================================== + # ===== ADDED: HELPER METHODS FOR OTHER VIEWS ===== + # ===================================================== + def get_sensors(self) -> List[Dict]: + """Get all sensors from the sensors table""" + query = "SELECT * FROM sensors ORDER BY sensor_name" + return self.run_query(query) + def get_sensor_status(self, sensor_name: str) -> Dict: + """Get status of a specific sensor""" + query = "SELECT * FROM sensors WHERE sensor_name = %s" + results = self.run_query(query, (sensor_name,)) + return results[0] if results else {} + def get_alerts(self, limit: int = 50) -> List[Dict]: + """Get recent alerts""" + query = """ + SELECT * FROM alerts + ORDER BY started_at DESC + LIMIT %s + """ + return self.run_query(query, (limit,)) + + def acknowledge_alert(self, alert_id: str) -> bool: + """Mark an alert as acknowledged""" + conn = None + cursor = None + try: + conn = self._get_connection() + cursor = conn.cursor() + query = "UPDATE alerts SET ack = true WHERE alert_id = %s" + cursor.execute(query, (alert_id,)) + conn.commit() + print(f"[DashboardApi] Alert {alert_id} acknowledged", flush=True) + return True + except Exception as e: + print(f"[DashboardApi] Error acknowledging alert: {e}", flush=True) + return False + finally: + if cursor: + cursor.close() + if conn: + conn.close() + def get_ripeness_stats(self) -> Dict: + """Get ripeness prediction statistics""" + query = """ + SELECT + COUNT(*) as total_predictions, + SUM(CASE WHEN ripeness_label = 'ripe' THEN 1 ELSE 0 END) as ripe_count, + SUM(CASE WHEN ripeness_label = 'unripe' THEN 1 ELSE 0 END) as unripe_count, + SUM(CASE WHEN ripeness_label = 'overripe' THEN 1 ELSE 0 END) as overripe_count + FROM ripeness_predictions + """ + results = self.run_query(query) + return results[0] if results else {} diff --git a/GUI/src/vast/desktop/Dockerfile b/GUI/src/vast/desktop/Dockerfile index ec0cc9972..d60b2dc24 100644 --- a/GUI/src/vast/desktop/Dockerfile +++ b/GUI/src/vast/desktop/Dockerfile @@ -2,7 +2,7 @@ FROM python:3.11-slim ENV PYTHONDONTWRITEBYTECODE=1 PYTHONUNBUFFERED=1 WORKDIR /app -# ───────── system dependencies ───────── +# ───────────────────── system deps ───────────────────── RUN apt-get update && apt-get install -y --no-install-recommends \ libgl1 libegl1 libx11-6 libxcomposite1 libxext6 libxi6 libxtst6 libsm6 \ libxkbcommon0 libxkbcommon-x11-0 libxkbfile1 libxrender1 libxrandr2 \ @@ -13,27 +13,25 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ libnspr4 libdbus-1-3 libkrb5-3 libgssapi-krb5-2 libasound2 libpulse0 \ fluxbox x11vnc xvfb wget net-tools python3-tk ca-certificates \ procps iproute2 xauth git vlc libvlc5 libvlccore9 \ - fonts-dejavu-core fonts-noto-core fonts-noto-color-emoji\ - && rm -rf /var/lib/apt/lists/* + fonts-dejavu-core fonts-noto-core fonts-noto-color-emoji && \ + rm -rf /var/lib/apt/lists/* -# (optional) minimal extra XCB deps for PyQt +# Extra XCB deps for PyQt RUN apt-get update && apt-get install -y --no-install-recommends \ libxcb-xinerama0 libxcb-cursor0 libxcb-keysyms1 libxcb-render-util0 \ libxcb-randr0 && rm -rf /var/lib/apt/lists/* -# ───────── optional CA certs ───────── +# ───────────────────── optional CA certs ───────────────────── COPY certs /app/certs RUN if [ -d ./certs ] && [ "$(ls ./certs/*.crt 2>/dev/null)" ]; then \ - echo "Configuring NetFree certificates..."; \ - cp ./certs/*.crt /usr/local/share/ca-certificates/; \ - update-ca-certificates; \ + cp ./certs/*.crt /usr/local/share/ca-certificates/ && update-ca-certificates; \ fi ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt ENV PIP_CERT=/etc/ssl/certs/ca-certificates.crt -# ───────── noVNC for remote GUI ───────── +# ───────────────────── noVNC ───────────────────── RUN mkdir -p /opt && \ wget --tries=3 --timeout=30 -O /tmp/novnc.tar.gz https://github.com/novnc/noVNC/archive/refs/tags/v1.4.0.tar.gz && \ tar xzf /tmp/novnc.tar.gz -C /opt && \ @@ -41,37 +39,50 @@ RUN mkdir -p /opt && \ rm /tmp/novnc.tar.gz && \ git clone --depth 1 https://github.com/novnc/websockify /opt/noVNC/utils/websockify -# ───────── Python deps ───────── +# ───────────────────── PulseAudio FIX ───────────────────── +RUN apt-get update && apt-get install -y --no-install-recommends pulseaudio && \ + mkdir -p /etc/pulse && \ + echo "load-module module-native-protocol-unix" >> /etc/pulse/default.pa && \ + echo "load-module module-always-sink" >> /etc/pulse/default.pa && \ + echo "set-default-sink default" >> /etc/pulse/default.pa + +RUN mkdir -p /run/user/1000 && chmod -R 777 /run/user/1000 + +# ───────────────────── Python deps ───────────────────── COPY requirements.txt /app/requirements.txt RUN pip install --no-cache-dir -r requirements.txt -RUN pip install --no-cache-dir --upgrade pip \ - && pip install --no-cache-dir \ - "PyQt6==6.8.0" \ - "PyQt6-WebEngine==6.8.0" \ - "argon2-cffi" \ - "requests" \ - "numpy" \ - --extra-index-url https://pypi.org/simple \ - --prefer-binary \ - --break-system-packages \ +RUN pip install --no-cache-dir --upgrade pip && \ + pip install --no-cache-dir \ + "PyQt6==6.9.0" \ + "PyQt6-WebEngine==6.9.0" \ + "argon2-cffi" \ + "requests" \ + "numpy" \ + argon2-cffi requests numpy \ + --extra-index-url https://pypi.org/simple \ + --prefer-binary \ + --break-system-packages \ && pip show PyQt6 PyQt6-WebEngine argon2-cffi -RUN pip install plotly -RUN pip install PyJWT -# ───────── app setup ───────── -RUN useradd -m -s /bin/bash appuser \ - && mkdir -p /app /tmp/.X11-unix \ - && chown -R appuser:appuser /app /tmp /opt/noVNC /var/tmp + --prefer-binary --break-system-packages +RUN pip install plotly PyJWT -RUN apt-get update && apt-get install -y --no-install-recommends gosu && rm -rf /var/lib/apt/lists/* +# ───────────────────── App setup ───────────────────── +RUN useradd -m -s /bin/bash appuser && \ + mkdir -p /app /tmp/.X11-unix && chown -R appuser:appuser /app /tmp /opt/noVNC /var/tmp +RUN apt-get update && apt-get install -y --no-install-recommends gosu && rm -rf /var/lib/apt/lists/* +RUN pip install psycopg2-binary COPY src/vast /app/src/vast COPY src/vast/desktop/start.sh /app/start.sh RUN sed -i 's/\r$//' /app/start.sh && chmod +x /app/start.sh && chown -R appuser:appuser /app RUN mkdir -p /app/secrets && chmod -R 777 /app/secrets +RUN mkdir -p /run/user/1000 && chmod -R 777 /run/user/1000 + USER appuser -EXPOSE 5900 6080 + +EXPOSE 5900 6080 ENV PYTHONPATH=/app/src:/app ENV DISPLAY=:0 ENV NO_VNC_PORT=6080 @@ -79,6 +90,3 @@ ENV PORT=19100 ENV MEDIA_BASE=http://media-proxy:8080 CMD ["/app/start.sh"] - - - diff --git a/GUI/src/vast/desktop/start.sh b/GUI/src/vast/desktop/start.sh index 460dfcafe..12884fe5d 100644 --- a/GUI/src/vast/desktop/start.sh +++ b/GUI/src/vast/desktop/start.sh @@ -5,6 +5,10 @@ set -x export DISPLAY=:0 rm -f /tmp/.X0-lock +echo "[INFO] Starting PulseAudio..." +pulseaudio --start --exit-idle-time=-1 --log-target=stderr +sleep 1 + echo "[INFO] Starting Xvfb..." Xvfb :0 -screen 0 1920x1080x24 & sleep 3 @@ -22,10 +26,3 @@ echo "[INFO] Starting noVNC..." echo "[INFO] Starting PyQt application..." exec python /app/src/vast/main.py - - - -# # ------------------------------ -# # 🚀 Launch the main PyQt application -# # ------------------------------ -# exec /opt/venv/bin/python /app/src/vast/main.py diff --git a/GUI/src/vast/dsl/builder.py b/GUI/src/vast/dsl/builder.py index 93ab0785e..cf17cf985 100644 --- a/GUI/src/vast/dsl/builder.py +++ b/GUI/src/vast/dsl/builder.py @@ -24,13 +24,11 @@ class SQLState: source: str dialect: Dialect clauses: Dict[str, List[Clause]] = field(default_factory=lambda: defaultdict(list)) - CLAUSE_ORDER: List[str] = field(default_factory=lambda: ["select", "from", "where"]) # extend externally + CLAUSE_ORDER: List[str] = field(default_factory=lambda: [ + "select", "from", "where", "group_by", "having", "order_by", "limit", "offset" +]) + - # Helper methods to avoid importing Clause classes in ops - def add_select(self, columns: List[str]) -> None: - self.clauses["select"].append(SelectClause(columns)) - def add_where(self, cond) -> None: - self.clauses["where"].append(WhereClause(cond)) def add_clause(self, clause: Clause) -> None: self.clauses[clause.phase].append(clause) @@ -75,10 +73,19 @@ def compile(self, plan: Plan | Dict[str, Any]) -> tuple[str, List[Any]]: p = plan if isinstance(plan, Plan) else Plan.from_dict(plan) st = SQLState(source=p.source, dialect=self.dialect) for op in p._ops: - if set(op.keys()) - {"op", "columns", "cond"}: + if not isinstance(op, dict): + raise TypeError(f"Each operation must be a dict, got {type(op).__name__}: {op}") + + allowed_keys = {"op", "columns", "cond", "directions", "limit", "offset"} + extra = set(op.keys()) - allowed_keys + if extra: raise ValueError(f"Unknown keys in op: {op}") + op_type = op.get("op") if op_type not in Op.registry: raise ValueError(f"Unsupported op {op_type!r}. Allowed: {sorted(Op.registry)}") + + # Pass all keys except "op" as kwargs Op.registry[op_type](**{k: v for k, v in op.items() if k != "op"}).apply(st) - return st.build() \ No newline at end of file + + return st.build() diff --git a/GUI/src/vast/dsl/clauses.py b/GUI/src/vast/dsl/clauses.py index f2d0f225b..d2f2ecf48 100644 --- a/GUI/src/vast/dsl/clauses.py +++ b/GUI/src/vast/dsl/clauses.py @@ -27,12 +27,23 @@ def fragment(self, ctx: CompileCtx) -> str: ... @dataclass class SelectClause(Clause): columns: List[str] + @property - def phase(self) -> str: return "select" - def keyword(self) -> str: return "SELECT" - def joiner(self) -> str: return ", " + def phase(self) -> str: + return "select" + + def keyword(self) -> str: + return "SELECT" + + def joiner(self) -> str: + return ", " + def fragment(self, ctx: CompileCtx) -> str: def star_aware_quote(col: str) -> str: + # Skip quoting if expression or alias (COUNT(*), AVG(...), AS, etc.) + if any(token in col.upper() for token in ("(", ")", " AS ")): + return col # treat as SQL expression + # Support "*", "tbl.*", and dotted names that may end with * parts = col.split(".") quoted = [] @@ -42,11 +53,13 @@ def star_aware_quote(col: str) -> str: else: quoted.append(ctx.dialect.quote_ident(p)) return ".".join(quoted) + if not self.columns: return "*" # default return ", ".join(star_aware_quote(c) for c in self.columns) + @dataclass class FromClause(Clause): source: str @@ -65,4 +78,78 @@ def phase(self) -> str: return "where" def keyword(self) -> str: return "WHERE" def joiner(self) -> str: return " AND " def fragment(self, ctx: CompileCtx) -> str: - return self.cond.compile(ctx) \ No newline at end of file + return self.cond.compile(ctx) + + +@dataclass +class OrderByClause(Clause): + columns: list[str] + directions: list[str] + + @property + def phase(self): return "order_by" + def keyword(self): return "ORDER BY" + def joiner(self): return ", " + + def fragment(self, ctx): + def quote_or_passthrough(col: str) -> str: + # Skip quoting if it's clearly an SQL expression or aggregate + if "(" in col or ")" in col: + return col + return ctx.dialect.quote_ident(col) + + cols = [quote_or_passthrough(c) for c in self.columns] + dirs = self.directions or ["ASC"] * len(cols) + return ", ".join(f"{c} {d.upper()}" for c, d in zip(cols, dirs)) + + + +@dataclass +class LimitClause(Clause): + limit: int + @property + def phase(self): return "limit" + def keyword(self): return "LIMIT" + def joiner(self): return " " + def fragment(self, ctx): return str(self.limit) + + +@dataclass +class OffsetClause(Clause): + offset: int + @property + def phase(self): return "offset" + def keyword(self): return "OFFSET" + def joiner(self): return " " + def fragment(self, ctx): return str(self.offset) + + +@dataclass +class GroupByClause(Clause): + columns: list[str] + + @property + def phase(self): return "group_by" + def keyword(self): return "GROUP BY" + def joiner(self): return ", " + + def fragment(self, ctx): + def quote_or_passthrough(col: str) -> str: + # Skip quoting if it's a SQL expression or function call + if any(token in col.upper() for token in ( + "(", ")", " AS ", "COUNT", "AVG", "SUM", "MAX", "MIN", "DATE_TRUNC" + )): + return col + return ctx.dialect.quote_ident(col) + return ", ".join(quote_or_passthrough(c) for c in self.columns) + + + +@dataclass +class HavingClause(Clause): + cond: Cond + @property + def phase(self): return "having" + def keyword(self): return "HAVING" + def joiner(self): return " AND " + def fragment(self, ctx): return self.cond.compile(ctx) diff --git a/GUI/src/vast/dsl/dialects.py b/GUI/src/vast/dsl/dialects.py index 078ec65cc..b83ce6c9f 100644 --- a/GUI/src/vast/dsl/dialects.py +++ b/GUI/src/vast/dsl/dialects.py @@ -35,19 +35,33 @@ def placeholder(self, idx: int) -> str: return "?" # qmark style class PostgresDialect(Dialect): - def __init__(self, style: str = "psycopg"): - """style: - - 'psycopg' → %s style placeholders (psycopg2/3) - - 'numeric' → $1, $2, ... style placeholders (asyncpg) + def __init__(self, style: str = "named"): """ - - if style not in ("psycopg", "numeric"): - raise ValueError("PostgresDialect.style must be 'psycopg' or 'numeric'") + style: + - 'psycopg' → %s placeholders (for psycopg2) + - 'numeric' → $1, $2 placeholders (for asyncpg) + - 'named' → :p1, :p2 placeholders (for SQLAlchemy.text) + """ + if style not in ("psycopg", "numeric", "named"): + raise ValueError("PostgresDialect.style must be 'psycopg', 'numeric', or 'named'") self.style = style + def quote_ident(self, name: str) -> str: parts = name.split(".") - return ".".join('"' + p.replace('"', '""') + '"' for p in parts) + escaped = [] + for p in parts: + escaped_name = p.replace('"', '""') + escaped.append(f'"{escaped_name}"') + return ".".join(escaped) + + def normalize_bool(self, v: Any) -> Any: - return v # PostgreSQL has a real boolean type + return v + def placeholder(self, idx: int) -> str: - return "%s" if self.style == "psycopg" else f"${idx}" \ No newline at end of file + if self.style == "psycopg": + return "%s" + elif self.style == "numeric": + return f"${idx}" + else: # named + return f":p{idx}" diff --git a/GUI/src/vast/dsl/expr.py b/GUI/src/vast/dsl/expr.py index 03abf40d1..d9c41aff3 100644 --- a/GUI/src/vast/dsl/expr.py +++ b/GUI/src/vast/dsl/expr.py @@ -47,8 +47,37 @@ def to_ir(self) -> Dict[str, Any]: return {"col": self.name} class Literal(Expr): """A literal value that becomes a bound parameter (with a placeholder).""" value: Any - def compile(self, ctx: CompileCtx) -> str: return ctx.add_param(self.value) - def to_ir(self) -> Dict[str, Any]: return {"literal": self.value} + + def compile(self, ctx: CompileCtx) -> str: + # Detect SQL expressions that should be inlined (not parameterized) + if isinstance(self.value, str) and any( + kw in self.value.lower() + for kw in ("now()", "interval", "date_trunc", "current_date", "current_timestamp") + ): + return self.value # inline directly as SQL expression + + # Default: treat as bound parameter + return ctx.add_param(self.value) + + def to_ir(self) -> Dict[str, Any]: + return {"literal": self.value} + +@dataclass +class Func(Expr): + name: str + args: list[Expr] + + def compile(self, ctx: CompileCtx) -> str: + compiled = ", ".join(arg.compile(ctx) for arg in self.args) + return f"{self.name.upper()}({compiled})" + + def to_ir(self) -> Dict[str, Any]: + return { + "func": self.name, + "args": [arg.to_ir() for arg in self.args] + } + + def ensure_expr(x: Any) -> Expr: """Coerce Python values to Literal, leave Expr as-is.""" @@ -72,7 +101,7 @@ class Predicate(Cond): op: BinOp right: Expr def __post_init__(self): - if not isinstance(self.left, (Col, Literal)) or not isinstance(self.right, (Col, Literal)): + if not isinstance(self.left, (Col, Literal,Func)) or not isinstance(self.right, (Col, Literal,Func)): raise TypeError("Predicate must compare columns and/or literals only") def compile(self, ctx: CompileCtx) -> str: return f"({self.left.compile(ctx)} {self.op.value} {self.right.compile(ctx)})" @@ -96,34 +125,76 @@ def to_ir(self) -> Dict[str, Any]: return {"any": [p.to_ir() for p in self.parts # ---- Strict IR decoding ---- def expr_from_ir(d: Dict[str, Any]) -> Expr: - """Decode a strict Expr IR object into Expr.""" - if not isinstance(d, dict): raise TypeError("Expr leaf must be an object") + if not isinstance(d, dict): + raise TypeError("Expr leaf must be an object") + keys = set(d.keys()) - if keys == {"col"}: return Col(d["col"]) - if keys == {"literal"}: return Literal(d["literal"]) - raise ValueError("Expr leaf must be either {\"col\": name} or {\"literal\": value}") + + if keys == {"col"}: + return Col(d["col"]) + + if keys == {"literal"}: + return Literal(d["literal"]) + + if keys == {"func", "args"}: + return Func( + d["func"], + [expr_from_ir(arg) for arg in d["args"]] + ) + + raise ValueError(f"Invalid Expr IR: {d}") + def cond_from_ir(d: Dict[str, Any]) -> Cond: - """Decode a strict Cond IR object into Cond.""" - if not isinstance(d, dict): raise TypeError("Cond node must be an object") + """Decode a strict Cond IR object into Cond with defensive validation.""" + # ───────────── DEBUG LOG ───────────── + import traceback + print("\n[DEBUG cond_from_ir] called with:", repr(d)) + # Optional: print call stack to see which Op invoked this + # print("".join(traceback.format_stack(limit=3))) + + if not isinstance(d, dict): + raise TypeError(f"Cond node must be an object, got {type(d).__name__}: {d}") + keys = set(d.keys()) + + # ───── Logical AND if keys == {"all"}: arr = d["all"] - if not isinstance(arr, list): raise TypeError("all must be an array of Cond") + if not isinstance(arr, list): + raise TypeError(f"'all' must be a list of condition objects, got {type(arr).__name__}") + for i, item in enumerate(arr): + if not isinstance(item, dict): + raise TypeError(f"List argument at index {i} must be a dict, got {type(item).__name__}: {item}") return All(*[cond_from_ir(x) for x in arr]) + + # ───── Logical OR if keys == {"any"}: arr = d["any"] - if not isinstance(arr, list): raise TypeError("any must be an array of Cond") + if not isinstance(arr, list): + raise TypeError(f"'any' must be a list of condition objects, got {type(arr).__name__}") + for i, item in enumerate(arr): + if not isinstance(item, dict): + raise TypeError(f"List argument at index {i} must be a dict, got {type(item).__name__}: {item}") return Any(*[cond_from_ir(x) for x in arr]) + + # ───── Predicate if keys == {"op", "left", "right"}: try: - op = BinOp(d["op"]) # raises ValueError if unknown -> nice error + op = BinOp(d["op"]) except ValueError as e: allowed = ", ".join(o.value for o in BinOp) raise ValueError(f"Operator {d['op']!r} not allowed. Allowed: [{allowed}]") from e return Predicate(expr_from_ir(d["left"]), op, expr_from_ir(d["right"])) + if "col" in d and "literal" in d: + return Predicate(expr_from_ir({"col": d["col"]}), BinOp.EQ, expr_from_ir({"literal": d["literal"]})) + + raise ValueError(f"Invalid condition node: {d}") + + + # Convenience aliases AND = All -OR = Any \ No newline at end of file +OR = Any diff --git a/GUI/src/vast/dsl/ops.py b/GUI/src/vast/dsl/ops.py index 0cbc7678d..cc66239c0 100644 --- a/GUI/src/vast/dsl/ops.py +++ b/GUI/src/vast/dsl/ops.py @@ -7,7 +7,7 @@ from __future__ import annotations from typing import Any, Dict, List, Type from abc import ABC, abstractmethod -from .clauses import SelectClause, WhereClause +from .clauses import SelectClause, WhereClause,OrderByClause,LimitClause,HavingClause,OffsetClause,GroupByClause from .expr import cond_from_ir # from .builder import SQLState @@ -28,11 +28,55 @@ def apply(self, st: "SQLState") -> None: class SelectOp(Op): op_type = "select" def apply(self, st: "SQLState") -> None: - cols = self.payload.get("columns") - st.add_select(cols or []) + cols = self.payload.get("columns", []) + st.add_clause(SelectClause(cols)) + class WhereOp(Op): op_type = "where" def apply(self, st: "SQLState") -> None: - cond_ir: Dict[str, Any] = self.payload["cond"] - st.add_where(cond_from_ir(cond_ir)) + cond_ir = self.payload.get("cond") + if not isinstance(cond_ir, dict): + raise TypeError("Invalid WHERE condition") + expr = cond_from_ir(cond_ir) + st.add_clause(WhereClause(expr)) + + + +class HavingOp(Op): + op_type = "having" + def apply(self, st): + cond_ir = self.payload.get("cond") + if not isinstance(cond_ir, dict): + raise TypeError( + f"Invalid HAVING condition: expected dict, got {type(cond_ir).__name__} → {cond_ir}" + ) + st.add_clause(HavingClause(cond_from_ir(cond_ir))) + + + +class OrderByOp(Op): + op_type = "order_by" + def apply(self, st): + st.add_clause(OrderByClause( + self.payload.get("columns", []), + self.payload.get("directions", []) + )) + +class LimitOp(Op): + op_type = "limit" + def apply(self, st): + st.add_clause(LimitClause(self.payload["limit"])) + +class OffsetOp(Op): + op_type = "offset" + def apply(self, st): + st.add_clause(OffsetClause(self.payload["offset"])) + +class GroupByOp(Op): + op_type = "group_by" + def apply(self, st): + st.add_clause(GroupByClause(self.payload.get("columns", []))) + + + diff --git a/GUI/src/vast/dsl/query.py b/GUI/src/vast/dsl/query.py index 12d5457f7..b21965bae 100644 --- a/GUI/src/vast/dsl/query.py +++ b/GUI/src/vast/dsl/query.py @@ -26,6 +26,28 @@ def where(self, cond: Cond) -> "Query": self._plan._ops.append({"op": "where", "cond": cond.to_ir()}) return self + def order_by(self, *columns: str, directions: list[str] | None = None) -> "Query": + directions = directions or ["ASC"] * len(columns) + self._plan._ops.append({"op": "order_by", "columns": list(columns), "directions": directions}) + return self + + def limit(self, n: int) -> "Query": + self._plan._ops.append({"op": "limit", "limit": n}) + return self + + def offset(self, n: int) -> "Query": + self._plan._ops.append({"op": "offset", "offset": n}) + return self + + def group_by(self, *columns: str) -> "Query": + self._plan._ops.append({"op": "group_by", "columns": list(columns)}) + return self + + def having(self, cond: Cond) -> "Query": + self._plan._ops.append({"op": "having", "cond": cond.to_ir()}) + return self + + def to_plan(self) -> Plan: """Return the underlying Plan object (e.g., for transport).""" return self._plan diff --git a/GUI/src/vast/dsl/runtime.py b/GUI/src/vast/dsl/runtime.py index 20fcc8aef..15fdaefb8 100644 --- a/GUI/src/vast/dsl/runtime.py +++ b/GUI/src/vast/dsl/runtime.py @@ -9,10 +9,13 @@ class CompileCtx: def __init__(self, dialect: Dialect) -> None: - self.params: List[Any] = [] # Accumulated bound parameters in order of appearance. + self.params: dict[str, Any] = {} self.dialect = dialect def add_param(self, v: Any) -> str: - """Append a value (after dialect-specific normalization) and return its placeholder.""" - self.params.append(self.dialect.normalize_bool(v)) - return self.dialect.placeholder(len(self.params)) + """Append a value and return its dialect-specific placeholder.""" + idx = len(self.params) + 1 + name = f"p{idx}" + self.params[name] = self.dialect.normalize_bool(v) + return self.dialect.placeholder(idx) + diff --git a/GUI/src/vast/gateway/Dockerfile b/GUI/src/vast/gateway/Dockerfile index 745b58831..29549ecba 100644 --- a/GUI/src/vast/gateway/Dockerfile +++ b/GUI/src/vast/gateway/Dockerfile @@ -1,33 +1,54 @@ +# syntax=docker/dockerfile:1.6 + FROM python:3.11-slim -ENV PYTHONDONTWRITEBYTECODE=1 PYTHONUNBUFFERED=1 -WORKDIR /app +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 + +WORKDIR /app # build arg # ARG USE_NETFREE=true -RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates curl && rm -rf /var/lib/apt/lists/* -COPY certs /app/certs -# System CA + add NetFree certs -RUN if [ "$USE_NETFREE" = "true" ] && [ -d ./certs ] && [ "$(ls ./certs/*.crt 2>/dev/null)" ]; then \ - echo "Configuring NetFree certificates..."; \ - cp ./certs/*.crt /usr/local/share/ca-certificates/; \ - update-ca-certificates; \ +# Toggle NetFree handling at build time: +# docker build --build-arg USE_NETFREE=true -t image:netfree . +# docker build --build-arg USE_NETFREE=false -t image:default . +ARG USE_NETFREE=false + +# Base system tools (certificates + curl) +RUN apt-get update \ + && apt-get install -y --no-install-recommends ca-certificates curl \ + && rm -rf /var/lib/apt/lists/* + +# Optional extra CA certs (e.g. NetFree) from ./certs +COPY certs/ /tmp/certs + +RUN set -eux; \ + if [ "${USE_NETFREE}" = "true" ] \ + && [ -d /tmp/certs ] \ + && ls /tmp/certs/*.crt >/dev/null 2>&1; then \ + echo "Adding extra CA certs from /tmp/certs ..."; \ + cp /tmp/certs/*.crt /usr/local/share/ca-certificates/; \ + chmod 644 /usr/local/share/ca-certificates/*.crt; \ + update-ca-certificates; \ + else \ + echo "No extra CA certs configured (USE_NETFREE=${USE_NETFREE})."; \ fi -# SSL certs env +# System-wide SSL env (works with or without extra CAs) ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ PIP_CERT=/etc/ssl/certs/ca-certificates.crt +ENV PIP_DEFAULT_TIMEOUT=600 -# # System CA + add NetFree certs -RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates curl && rm -rf /var/lib/apt/lists/* -COPY certs/*.crt /usr/local/share/ca-certificates/ -RUN update-ca-certificates || true -ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ - REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ - PIP_CERT=/etc/ssl/certs/ca-certificates.crt +# # # System CA + add NetFree certs +# RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates curl && rm -rf /var/lib/apt/lists/* +# COPY certs/*.crt /usr/local/share/ca-certificates/ +# RUN update-ca-certificates || true +# ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ +# REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ +# PIP_CERT=/etc/ssl/certs/ca-certificates.crt # Python deps COPY requirements.txt /app/requirements.txt @@ -37,16 +58,17 @@ RUN pip install --no-cache-dir -r /app/requirements.txt \ --trusted-host pypi.python.org \ --trusted-host files.pythonhosted.org -# Copy source under /app/vast/* +# App code COPY src/vast/gateway /app/vast/gateway COPY src/vast/proto /app/vast/proto -# Generate stubs +# Generate gRPC stubs RUN python -m grpc_tools.protoc -I./vast/proto \ --python_out=. --grpc_python_out=. \ ./vast/proto/query.proto ENV PYTHONPATH=/app/vast/proto/generated:/app ENV RUNNER_ADDR=runner:50051 + EXPOSE 8000 -CMD ["uvicorn", "vast.gateway.gateway_main:app", "--host", "0.0.0.0", "--port", "8000"] \ No newline at end of file +CMD ["uvicorn", "vast.gateway.gateway_main:app", "--host", "0.0.0.0", "--port", "8000"] diff --git a/GUI/src/vast/home_view.py b/GUI/src/vast/home_view.py index ec2b41df2..b82ef2ef1 100644 --- a/GUI/src/vast/home_view.py +++ b/GUI/src/vast/home_view.py @@ -174,7 +174,3 @@ def _on_alert_realtime(self, alert: dict): print(f"[HomeView] Active alert: {normalized['alert_type']} " f"from {normalized['device_id']} ({normalized['lat']}, {normalized['lon']})") self.alert_layer.add_or_update_alert(normalized) - - - - diff --git a/GUI/src/vast/main.py b/GUI/src/vast/main.py index f302d3b81..4517b96d6 100644 --- a/GUI/src/vast/main.py +++ b/GUI/src/vast/main.py @@ -100,30 +100,31 @@ def main() -> int: print("[main] starting QApplication") app = QApplication(sys.argv) + # 1) create the auth shell but do NOT show it shell = AuthShell() shell.setWindowTitle("Sign in") # shell.show() # disabled to skip the login window + # 2) when login succeeds -> open MainWindow def open_main(user): api = DashboardApi() # create API instance (user not required) win = MainWindow(api) - # connect logout back to login win.logoutRequested.connect(lambda: on_logout(win)) - win.show() shell.hide() + def on_logout(win): win.close() shell.reset() shell.show() - # wire callback shell.on_login_success = open_main + # open the main window directly (skip login) open_main(None) @@ -131,7 +132,5 @@ def on_logout(win): rc = app.exec() print(f"[main] event loop exited with code {rc}") return rc - - if __name__ == "__main__": sys.exit(main()) diff --git a/GUI/src/vast/main_window.py b/GUI/src/vast/main_window.py index 0dfc7c1d9..726b129c6 100644 --- a/GUI/src/vast/main_window.py +++ b/GUI/src/vast/main_window.py @@ -1,3 +1,916 @@ +# # from PyQt6.QtCore import Qt, pyqtSignal, QSize +# # from PyQt6.QtWidgets import ( +# # QMainWindow, QDockWidget, QListWidget, QListWidgetItem, QStatusBar, +# # QStackedWidget, QToolButton, QLabel, QWidget, QHBoxLayout, QVBoxLayout, +# # QGraphicsDropShadowEffect, QPushButton, +# # QMainWindow, QDockWidget, QListWidget, QListWidgetItem, QStatusBar, +# # QStackedWidget, QToolButton, QLabel, QWidget, QHBoxLayout, QVBoxLayout, +# # QGraphicsDropShadowEffect, QPushButton +# # ) +# # from PyQt6.QtGui import QAction, QIcon, QFont, QColor +# # import os + +# # from PyQt6.QtGui import QAction, QIcon, QFont, QColor +# # import os + +# # from home_view import HomeView +# # from views.sensors_view import SensorsView +# # from views.alerts_panel import AlertsPanel +# # from views.notification_view import NotificationView +# # from views.fruits_view import FruitsView +# # from views.sound.sound_view import SoundView +# # from views.ground_view import GroundView +# # from views.auth_status_view import AuthStatusView +# # from views.ground_view import GroundView +# # from views.auth_status_view import AuthStatusView +# # from dashboard_api import DashboardApi +# # from vast.alerts.alert_service import AlertService +# # from views.leaf_diseases import LeafDiseaseView + + +# # # === New Sensors GUI imports === +# # from views.sensorsMainView import SensorsMainView +# # from views.sensorsMapView import SensorsMapView +# # from views.sensorDetailsTab import SensorDetailsTab +# # from views.sensors_status_summary import SensorsStatusSummary + +# # from views.security.incident_player_vlc import IncidentPlayerVLC +# # # === New Sensors GUI imports === +# # from views.sensorsMainView import SensorsMainView +# # from views.sensorsMapView import SensorsMapView +# # from views.sensorDetailsTab import SensorDetailsTab +# # from views.sensors_status_summary import SensorsStatusSummary + + +# # class MainWindow(QMainWindow): +# # logoutRequested = pyqtSignal() + +# # def __init__(self, api: DashboardApi, parent=None): +# # super().__init__(parent) +# # self.setWindowTitle("AgCloud – Dashboard") +# # self.resize(1280, 760) +# # self.setWindowTitle("AgCloud – Dashboard") +# # self.resize(1280, 760) +# # self.api = api + +# # # ─────────────────────────────── +# # # GLOBAL STYLE +# # # ─────────────────────────────── +# # self.setStyleSheet(""" +# # QMainWindow { background-color: #f9fafb; } +# # QMenuBar { background-color: #e5e7eb; font-size: 11.5pt; padding: 4px 10px; } +# # QToolBar { +# # background: qlineargradient(x1:0, y1:0, x2:0, y2:1, stop:0 #ffffff, stop:1 #f3f4f6); +# # border-bottom: 1px solid #d1d5db; padding: 2px 10px; min-height: 42px; +# # } +# # QToolButton { background-color: transparent; border: none; padding: 4px; border-radius: 8px; font-size: 20px; } +# # QToolButton:hover { background-color: #e5e7eb; } +# # QListWidget { background-color: #ffffff; border: none; font-size: 12pt; color: #111827; } +# # QListWidget::item { padding: 10px; border-radius: 6px; } +# # QListWidget::item:selected { background-color: #10b981; color: white; } +# # QStatusBar { background-color: #f3f4f6; font-size: 10pt; } +# # """) + +# # # ─────────────────────────────── +# # # MENU +# # # ─────────────────────────────── +# # # ─────────────────────────────── +# # # GLOBAL STYLE +# # # ─────────────────────────────── +# # self.setStyleSheet(""" +# # QMainWindow { background-color: #f9fafb; } +# # QMenuBar { background-color: #e5e7eb; font-size: 11.5pt; padding: 4px 10px; } +# # QToolBar { +# # background: qlineargradient(x1:0, y1:0, x2:0, y2:1, stop:0 #ffffff, stop:1 #f3f4f6); +# # border-bottom: 1px solid #d1d5db; padding: 2px 10px; min-height: 42px; +# # } +# # QToolButton { background-color: transparent; border: none; padding: 4px; border-radius: 8px; font-size: 20px; } +# # QToolButton:hover { background-color: #e5e7eb; } +# # QListWidget { background-color: #ffffff; border: none; font-size: 12pt; color: #111827; } +# # QListWidget::item { padding: 10px; border-radius: 6px; } +# # QListWidget::item:selected { background-color: #10b981; color: white; } +# # QStatusBar { background-color: #f3f4f6; font-size: 10pt; } +# # """) + +# # # ─────────────────────────────── +# # # MENU +# # # ─────────────────────────────── +# # file_menu = self.menuBar().addMenu("&File") +# # self.back_action = QAction(QIcon.fromTheme("go-previous"), "Back", self) +# # self.back_action.setShortcut("Alt+Left") +# # self.back_action.triggered.connect(self.go_back) +# # file_menu.addAction(self.back_action) +# # self.logout_action = QAction("Log out", self) +# # self.logout_action = QAction("Log out", self) +# # self.logout_action.triggered.connect(self._logout) +# # file_menu.addAction(self.logout_action) + +# # # ─────────────────────────────── +# # # TOP BAR (toolbar) +# # # ─────────────────────────────── +# # # ─────────────────────────────── +# # # TOP BAR (toolbar) +# # # ─────────────────────────────── +# # toolbar = self.addToolBar("Main Toolbar") +# # toolbar.setMovable(False) +# # toolbar.setFloatable(False) +# # toolbar.setIconSize(QSize(32, 32)) + +# # top_bar = QWidget() +# # top_bar_layout = QHBoxLayout(top_bar) +# # top_bar_layout.setContentsMargins(8, 0, 8, 0) +# # top_bar_layout.setSpacing(10) + +# # # Logout button +# # logout_btn = QPushButton("Logout") +# # logout_btn.setToolTip("Log out") +# # logout_btn.setCursor(Qt.CursorShape.PointingHandCursor) +# # logout_btn.setStyleSheet(""" +# # QPushButton { +# # background-color: #10b981; +# # color: white; +# # border: none; +# # border-radius: 8px; +# # padding: 6px 16px; +# # font-size: 11pt; +# # font-weight: 600; +# # } +# # QPushButton:hover { background-color: #059669; } +# # QPushButton:pressed { background-color: #047857; } +# # """) +# # logout_btn.clicked.connect(self._logout) + +# # # Alert bell +# # toolbar.setIconSize(QSize(32, 32)) + +# # top_bar = QWidget() +# # top_bar_layout = QHBoxLayout(top_bar) +# # top_bar_layout.setContentsMargins(8, 0, 8, 0) +# # top_bar_layout.setSpacing(10) + +# # # Logout button +# # logout_btn = QPushButton("Logout") +# # logout_btn.setToolTip("Log out") +# # logout_btn.setCursor(Qt.CursorShape.PointingHandCursor) +# # logout_btn.setStyleSheet(""" +# # QPushButton { +# # background-color: #10b981; +# # color: white; +# # border: none; +# # border-radius: 8px; +# # padding: 6px 16px; +# # font-size: 11pt; +# # font-weight: 600; +# # } +# # QPushButton:hover { background-color: #059669; } +# # QPushButton:pressed { background-color: #047857; } +# # """) +# # logout_btn.clicked.connect(self._logout) + +# # # Alert bell +# # self.alert_button = QToolButton() +# # self.alert_button.setToolTip("Show alerts") +# # self.alert_button.setText("🔔") +# # self.alert_button.setIconSize(QSize(40, 40)) +# # self.alert_button.setIconSize(QSize(40, 40)) +# # self.alert_button.setStyleSheet(""" +# # QToolButton { +# # font-size: 30px; +# # font-size: 30px; +# # border: none; +# # background: transparent; +# # padding: 4px; +# # border-radius: 8px; +# # border-radius: 8px; +# # } +# # QToolButton:hover { background-color: #e5e7eb; } +# # QToolButton:hover { background-color: #e5e7eb; } +# # """) + +# # # Alert badge +# # # Alert badge +# # self.alert_badge = QLabel("0", self.alert_button) +# # self.alert_badge.setAlignment(Qt.AlignmentFlag.AlignCenter) +# # self.alert_badge.setFixedSize(24, 24) +# # self.alert_badge.setFixedSize(24, 24) +# # self.alert_badge.setStyleSheet(""" +# # QLabel { +# # background-color: #3b82f6; +# # background-color: #3b82f6; +# # color: white; +# # font-size: 10pt; +# # font-size: 10pt; +# # font-weight: bold; +# # border-radius: 12px; +# # border: 2px solid white; +# # border-radius: 12px; +# # border: 2px solid white; +# # } +# # """) +# # self.alert_badge.hide() + +# # def reposition_badge(): +# # btn_w = self.alert_button.width() +# # self.alert_badge.move(btn_w - 22, 2) +# # self.alert_badge.move(btn_w - 22, 2) +# # self.alert_badge.raise_() + +# # self.alert_button.resizeEvent = lambda e: ( +# # QToolButton.resizeEvent(self.alert_button, e), +# # reposition_badge() +# # ) +# # reposition_badge() + +# # # ─────────────────────────────── +# # # TITLE AREA (Updated) +# # # ─────────────────────────────── +# # title_container = QWidget() +# # title_layout = QVBoxLayout(title_container) +# # title_layout.setContentsMargins(0, 0, 0, 0) +# # title_layout.setSpacing(0) + +# # main_title = QLabel("AgCloud") +# # main_title.setAlignment(Qt.AlignmentFlag.AlignCenter) +# # main_title.setStyleSheet(""" +# # QLabel { +# # font-size: 22pt; +# # font-weight: 700; +# # color: #047857; +# # letter-spacing: 1px; +# # } +# # """) + +# # subtitle = QLabel("The Smart Platform that Protects and Optimizes Your Field") +# # subtitle.setAlignment(Qt.AlignmentFlag.AlignCenter) +# # subtitle.setStyleSheet(""" +# # QLabel { +# # font-size: 11pt; +# # font-weight: 500; +# # color: #374151; +# # margin-top: 2px; +# # } +# # """) + +# # title_layout.addWidget(main_title) +# # title_layout.addWidget(subtitle) + +# # shadow = QGraphicsDropShadowEffect() +# # shadow.setBlurRadius(8) +# # shadow.setColor(QColor(0, 0, 0, 35)) +# # shadow.setOffset(0, 2) +# # top_bar.setGraphicsEffect(shadow) + +# # top_bar_layout.addWidget(logout_btn) +# # top_bar_layout.addWidget(self.alert_button) +# # top_bar_layout.addStretch() +# # top_bar_layout.addWidget(title_container) +# # top_bar_layout.addStretch() +# # toolbar.addWidget(top_bar) + +# # # ─────────────────────────────── +# # # NAVIGATION +# # # ─────────────────────────────── +# # # ─────────────────────────────── +# # # TITLE AREA (Updated) +# # # ─────────────────────────────── +# # title_container = QWidget() +# # title_layout = QVBoxLayout(title_container) +# # title_layout.setContentsMargins(0, 0, 0, 0) +# # title_layout.setSpacing(0) + +# # main_title = QLabel("AgCloud") +# # main_title.setAlignment(Qt.AlignmentFlag.AlignCenter) +# # main_title.setStyleSheet(""" +# # QLabel { +# # font-size: 22pt; +# # font-weight: 700; +# # color: #047857; +# # letter-spacing: 1px; +# # } +# # """) + +# # subtitle = QLabel("The Smart Platform that Protects and Optimizes Your Field") +# # subtitle.setAlignment(Qt.AlignmentFlag.AlignCenter) +# # subtitle.setStyleSheet(""" +# # QLabel { +# # font-size: 11pt; +# # font-weight: 500; +# # color: #374151; +# # margin-top: 2px; +# # } +# # """) + +# # title_layout.addWidget(main_title) +# # title_layout.addWidget(subtitle) + +# # shadow = QGraphicsDropShadowEffect() +# # shadow.setBlurRadius(8) +# # shadow.setColor(QColor(0, 0, 0, 35)) +# # shadow.setOffset(0, 2) +# # top_bar.setGraphicsEffect(shadow) + +# # top_bar_layout.addWidget(logout_btn) +# # top_bar_layout.addWidget(self.alert_button) +# # top_bar_layout.addStretch() +# # top_bar_layout.addWidget(title_container) +# # top_bar_layout.addStretch() +# # toolbar.addWidget(top_bar) + +# # # ─────────────────────────────── +# # # NAVIGATION +# # # ─────────────────────────────── +# # self.nav_dock = QDockWidget("Navigation", self) +# # self.nav_dock.setFeatures(QDockWidget.DockWidgetFeature.NoDockWidgetFeatures) +# # self.addDockWidget(Qt.DockWidgetArea.LeftDockWidgetArea, self.nav_dock) +# # self.nav_list = QListWidget(self.nav_dock) +# # self.nav_dock.setWidget(self.nav_list) +# # self.nav_dock.setMinimumWidth(220) +# # self.nav_dock.setMinimumWidth(220) + +# # font = QFont(); font.setPointSize(12) +# # self.nav_list.setFont(font) + +# # for main_item in ["Home", "Sensors", "Sound", "Ground Image", "Aerial Image", "Fruits", "Security", "Settings", "Notifications", "Auth", "Leaf Diseases"]: +# # item.setData(Qt.ItemDataRole.UserRole, {"type": "main"}) +# # self.nav_list.addItem(item) +# # if main_item == "Sensors": +# # for sub in ["Live Data", "Sensor Health", "Location Map"]: +# # sub_item = QListWidgetItem(f" ↳ {sub}") +# # sub_item.setData(Qt.ItemDataRole.UserRole, {"type": "sub", "parent": main_item, "name": sub}) +# # sub_item.setHidden(True) +# # self.nav_list.addItem(sub_item) + +# # font = QFont(); font.setPointSize(12) +# # self.nav_list.setFont(font) +# # for main_item in ["Home", "Sensors", "Sound", "Ground Image", "Aerial Image", "Fruits", "Security", "Settings", "Notifications", "Auth", "Leaf Diseases"]: +# # item = QListWidgetItem(main_item) +# # item.setData(Qt.ItemDataRole.UserRole, {"type": "main"}) +# # self.nav_list.addItem(item) +# # if main_item == "Sensors": +# # for sub in ["Live Data", "Sensor Health", "Location Map"]: +# # sub_item = QListWidgetItem(f" ↳ {sub}") +# # sub_item.setData(Qt.ItemDataRole.UserRole, {"type": "sub", "parent": main_item, "name": sub}) +# # sub_item.setHidden(True) +# # self.nav_list.addItem(sub_item) + +# # self.nav_list.currentRowChanged.connect(self._on_nav_change) +# # self.nav_list.itemClicked.connect(self._on_nav_click) +# # self.nav_list.itemClicked.connect(self._on_nav_click) + +# # # ─────────────────────────────── +# # # ALERT SERVICE + PANEL +# # # ─────────────────────────────── +# # # ─────────────────────────────── +# # # ALERT SERVICE + PANEL +# # # ─────────────────────────────── +# # ws_url = os.getenv("ALERTS_WS", "ws://alerts-gateway:8000/ws/alerts") +# # self.alert_service = AlertService(ws_url, api) +# # self.alert_service.alertsUpdated.connect(self.update_alert_badge) +# # self.alert_service.alertAdded.connect(lambda _: self.update_alert_badge()) + +# # self.alerts_panel = AlertsPanel(self.alert_service) +# # self.alerts_panel.setWindowFlags(Qt.WindowType.FramelessWindowHint | Qt.WindowType.Tool) +# # self.alerts_panel.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground) +# # self.alerts_panel.setStyleSheet(""" +# # QWidget { +# # background-color: #ffffff; +# # border: 1px solid #d1d5db; +# # border: 1px solid #d1d5db; +# # border-radius: 10px; +# # } +# # """) +# # self.alerts_panel.hide() +# # self.alert_button.clicked.connect(self.toggle_alert_panel) + +# # # ─────────────────────────────── +# # # CENTRAL STACKED VIEWS +# # # ─────────────────────────────── +# # # ─────────────────────────────── +# # # CENTRAL STACKED VIEWS +# # # ─────────────────────────────── +# # self.home = HomeView(api, self.alert_service, self) +# # self.sensors_view = SensorsView(api, self) +# # self.notification_view = NotificationView(self) +# # self.fruits_view = FruitsView(api, self) +# # self.sound_view = SoundView(api, self) +# # self.ground_view = GroundView(api, self) +# # self.auth_status = AuthStatusView(api, self) +# # self.leaf_diseases_view = LeafDiseaseView(api, self) +# # self.sensors_status_summary = SensorsStatusSummary(api, self) +# # self.sensors_health = SensorsView(api, self) +# # self.sensors_main = SensorsMainView(api, self) +# # self.security_view = IncidentPlayerVLC(api, self.alert_service, self) +# # self.ground_view = GroundView(api, self) +# # self.auth_status = AuthStatusView(api, self) + +# # self.sensors_status_summary = SensorsStatusSummary(api, self) +# # self.sensors_health = SensorsView(api, self) +# # self.sensors_main = SensorsMainView(api, self) + +# # self.stack = QStackedWidget() +# # self.setCentralWidget(self.stack) +# # self.views = { +# # "Home": self.home, +# # "Sensors": self.sensors_view, +# # "Sound": self.sound_view, +# # "Sensors - Live Data": self.sensors_status_summary, +# # "Sensors - Sensor Health": self.sensors_health, +# # "Sensors - Location Map": self.sensors_main, +# # "Notifications": self.notification_view, +# # "Leaf Diseases": self.leaf_diseases_view, +# # "Fruits": self.fruits_view, +# # "Ground Image": self.ground_view, +# # "Auth": self.auth_status, +# # "Security": self.security_view, +# # } + +# # for view in self.views.values(): +# # self.stack.addWidget(view) +# # self.stack.setCurrentWidget(self.home) +# # self.history = [] +# # self.history = [] + +# # # ─────────────────────────────── +# # # STATUS BAR +# # # ─────────────────────────────── +# # # ─────────────────────────────── +# # # STATUS BAR +# # # ─────────────────────────────── +# # sb = QStatusBar(self) +# # sb.setStyleSheet("QStatusBar { background-color: #f3f4f6; color: #374151; font-size: 10.5pt; }") +# # sb.setStyleSheet("QStatusBar { background-color: #f3f4f6; color: #374151; font-size: 10.5pt; }") +# # self.setStatusBar(sb) +# # sb.showMessage("Ready") + +# # # ─────────────────────────────── +# # # ALERT BADGE +# # # ─────────────────────────────── +# # # ─────────────────────────────── +# # # ALERT BADGE +# # # ─────────────────────────────── +# # def update_alert_badge(self): +# # unacked = sum(1 for a in self.alert_service.alerts if not a.get("ack", False)) +# # if unacked > 0: +# # self.alert_badge.setText(str(unacked)) +# # self.alert_badge.show() +# # else: +# # self.alert_badge.hide() + +# # def toggle_alert_panel(self): +# # if self.alerts_panel.isVisible(): +# # self.alerts_panel.hide() +# # return + +# # panel_width, panel_height = 420, 540 +# # panel_width, panel_height = 420, 540 +# # self.alerts_panel.resize(panel_width, panel_height) +# # rect = self.alert_button.geometry() +# # bottom_left = self.alert_button.mapToGlobal(rect.bottomLeft()) +# # bottom_right = self.alert_button.mapToGlobal(rect.bottomRight()) +# # center_x = (bottom_left.x() + bottom_right.x()) // 2 - (panel_width // 2) +# # pos_y = bottom_left.y() + 8 +# # pos_y = bottom_left.y() + 8 +# # self.alerts_panel.move(center_x, pos_y) +# # self.alerts_panel.show() +# # self.alerts_panel.raise_() + +# # if hasattr(self.alert_service, "mark_all_acknowledged"): +# # self.alert_service.mark_all_acknowledged() +# # self.update_alert_badge() + +# # # ─────────────────────────────── +# # # NAVIGATION +# # # ─────────────────────────────── +# # # ─────────────────────────────── +# # # NAVIGATION +# # # ─────────────────────────────── +# # def _on_nav_change(self, row: int) -> None: +# # name = self.nav_list.item(row).text().strip() +# # name = self.nav_list.item(row).text().strip() +# # if name in self.views: +# # self.navigate_to(self.views[name]) +# # else: +# # self.statusBar().showMessage(f"Section '{name}' not implemented yet.") + +# # def _on_nav_click(self, item): +# # data = item.data(Qt.ItemDataRole.UserRole) +# # if data and data.get("type") == "main": +# # parent = item.text() +# # expanded = False +# # for i in range(self.nav_list.count()): +# # sub_item = self.nav_list.item(i) +# # sub_data = sub_item.data(Qt.ItemDataRole.UserRole) +# # if sub_data and sub_data.get("type") == "sub" and sub_data.get("parent") == parent: +# # expanded = sub_item.isHidden() +# # break +# # for i in range(self.nav_list.count()): +# # sub_item = self.nav_list.item(i) +# # sub_data = sub_item.data(Qt.ItemDataRole.UserRole) +# # if sub_data and sub_data.get("type") == "sub" and sub_data.get("parent") == parent: +# # sub_item.setHidden(not expanded) +# # elif data and data.get("type") == "sub": +# # parent = data.get("parent") +# # sub_name = data.get("name") +# # key = f"{parent} - {sub_name}" +# # if key in self.views: +# # self.stack.setCurrentWidget(self.views[key]) + +# # def _on_nav_click(self, item): +# # data = item.data(Qt.ItemDataRole.UserRole) +# # if data and data.get("type") == "main": +# # parent = item.text() +# # expanded = False +# # for i in range(self.nav_list.count()): +# # sub_item = self.nav_list.item(i) +# # sub_data = sub_item.data(Qt.ItemDataRole.UserRole) +# # if sub_data and sub_data.get("type") == "sub" and sub_data.get("parent") == parent: +# # expanded = sub_item.isHidden() +# # break +# # for i in range(self.nav_list.count()): +# # sub_item = self.nav_list.item(i) +# # sub_data = sub_item.data(Qt.ItemDataRole.UserRole) +# # if sub_data and sub_data.get("type") == "sub" and sub_data.get("parent") == parent: +# # sub_item.setHidden(not expanded) +# # elif data and data.get("type") == "sub": +# # parent = data.get("parent") +# # sub_name = data.get("name") +# # key = f"{parent} - {sub_name}" +# # if key in self.views: +# # self.stack.setCurrentWidget(self.views[key]) + +# # def navigate_to(self, widget): +# # current = self.stack.currentWidget() +# # if current not in self.history: +# # self.history.append(current) +# # self.stack.setCurrentWidget(widget) + +# # def go_back(self): +# # if self.history: +# # last = self.history.pop() +# # self.stack.setCurrentWidget(last) +# # else: +# # self.statusBar().showMessage("No previous view to go back to.") + +# # def _logout(self) -> None: +# # self.statusBar().showMessage("Logged out (demo)") +# # self.logoutRequested.emit() + +# from PyQt6.QtCore import Qt, pyqtSignal, QSize +# from PyQt6.QtWidgets import ( +# QMainWindow, QDockWidget, QListWidget, QListWidgetItem, QStatusBar, +# QStackedWidget, QToolButton, QLabel, QWidget, QHBoxLayout, QVBoxLayout, +# QGraphicsDropShadowEffect, QPushButton +# ) +# from PyQt6.QtGui import QAction, QIcon, QFont, QColor +# import os + +# from home_view import HomeView +# from views.sensors_view import SensorsView +# from views.alerts_panel import AlertsPanel +# from views.notification_view import NotificationView +# from views.fruits_view import FruitsView +# from views.ground_view import GroundView +# from views.auth_status_view import AuthStatusView +# from dashboard_api import DashboardApi +# from vast.alerts.alert_service import AlertService + +# # === New Sensors GUI imports === +# from views.sensorsMainView import SensorsMainView +# from views.sensorsMapView import SensorsMapView +# from views.sensorDetailsTab import SensorDetailsTab +# from views.sensors_status_summary import SensorsStatusSummary + + +# class MainWindow(QMainWindow): +# logoutRequested = pyqtSignal() + +# def __init__(self, api: DashboardApi, parent=None): +# super().__init__(parent) +# self.setWindowTitle("AgCloud – Dashboard") +# self.resize(1280, 760) +# self.api = api + +# # ─────────────────────────────── +# # GLOBAL STYLE +# # ─────────────────────────────── +# self.setStyleSheet(""" +# QMainWindow { background-color: #f9fafb; } +# QMenuBar { background-color: #e5e7eb; font-size: 11.5pt; padding: 4px 10px; } +# QToolBar { +# background: qlineargradient(x1:0, y1:0, x2:0, y2:1, stop:0 #ffffff, stop:1 #f3f4f6); +# border-bottom: 1px solid #d1d5db; padding: 2px 10px; min-height: 42px; +# } +# QToolButton { background-color: transparent; border: none; padding: 4px; border-radius: 8px; font-size: 20px; } +# QToolButton:hover { background-color: #e5e7eb; } +# QListWidget { background-color: #ffffff; border: none; font-size: 12pt; color: #111827; } +# QListWidget::item { padding: 10px; border-radius: 6px; } +# QListWidget::item:selected { background-color: #10b981; color: white; } +# QStatusBar { background-color: #f3f4f6; font-size: 10pt; } +# """) + +# # ─────────────────────────────── +# # MENU +# # ─────────────────────────────── +# file_menu = self.menuBar().addMenu("&File") +# self.back_action = QAction(QIcon.fromTheme("go-previous"), "Back", self) +# self.back_action.setShortcut("Alt+Left") +# self.back_action.triggered.connect(self.go_back) +# file_menu.addAction(self.back_action) +# self.logout_action = QAction("Log out", self) +# self.logout_action.triggered.connect(self._logout) +# file_menu.addAction(self.logout_action) + +# # ─────────────────────────────── +# # TOP BAR (toolbar) +# # ─────────────────────────────── +# toolbar = self.addToolBar("Main Toolbar") +# toolbar.setMovable(False) +# toolbar.setFloatable(False) +# toolbar.setIconSize(QSize(32, 32)) + +# top_bar = QWidget() +# top_bar_layout = QHBoxLayout(top_bar) +# top_bar_layout.setContentsMargins(8, 0, 8, 0) +# top_bar_layout.setSpacing(10) + +# # Logout button +# logout_btn = QPushButton("Logout") +# logout_btn.setToolTip("Log out") +# logout_btn.setCursor(Qt.CursorShape.PointingHandCursor) +# logout_btn.setStyleSheet(""" +# QPushButton { +# background-color: #10b981; +# color: white; +# border: none; +# border-radius: 8px; +# padding: 6px 16px; +# font-size: 11pt; +# font-weight: 600; +# } +# QPushButton:hover { background-color: #059669; } +# QPushButton:pressed { background-color: #047857; } +# """) +# logout_btn.clicked.connect(self._logout) + +# # Alert bell +# self.alert_button = QToolButton() +# self.alert_button.setToolTip("Show alerts") +# self.alert_button.setText("🔔") +# self.alert_button.setIconSize(QSize(40, 40)) +# self.alert_button.setStyleSheet(""" +# QToolButton { +# font-size: 30px; +# border: none; +# background: transparent; +# padding: 4px; +# border-radius: 8px; +# } +# QToolButton:hover { background-color: #e5e7eb; } +# """) + +# # Alert badge +# self.alert_badge = QLabel("0", self.alert_button) +# self.alert_badge.setAlignment(Qt.AlignmentFlag.AlignCenter) +# self.alert_badge.setFixedSize(24, 24) +# self.alert_badge.setStyleSheet(""" +# QLabel { +# background-color: #3b82f6; +# color: white; +# font-size: 10pt; +# font-weight: bold; +# border-radius: 12px; +# border: 2px solid white; +# } +# """) +# self.alert_badge.hide() + +# def reposition_badge(): +# btn_w = self.alert_button.width() +# self.alert_badge.move(btn_w - 22, 2) +# self.alert_badge.raise_() + +# self.alert_button.resizeEvent = lambda e: ( +# QToolButton.resizeEvent(self.alert_button, e), +# reposition_badge() +# ) +# reposition_badge() + +# # ─────────────────────────────── +# # TITLE AREA (Updated) +# # ─────────────────────────────── +# title_container = QWidget() +# title_layout = QVBoxLayout(title_container) +# title_layout.setContentsMargins(0, 0, 0, 0) +# title_layout.setSpacing(0) + +# main_title = QLabel("AgCloud") +# main_title.setAlignment(Qt.AlignmentFlag.AlignCenter) +# main_title.setStyleSheet(""" +# QLabel { +# font-size: 22pt; +# font-weight: 700; +# color: #047857; +# letter-spacing: 1px; +# } +# """) + +# subtitle = QLabel("The Smart Platform that Protects and Optimizes Your Field") +# subtitle.setAlignment(Qt.AlignmentFlag.AlignCenter) +# subtitle.setStyleSheet(""" +# QLabel { +# font-size: 11pt; +# font-weight: 500; +# color: #374151; +# margin-top: 2px; +# } +# """) + +# title_layout.addWidget(main_title) +# title_layout.addWidget(subtitle) + +# shadow = QGraphicsDropShadowEffect() +# shadow.setBlurRadius(8) +# shadow.setColor(QColor(0, 0, 0, 35)) +# shadow.setOffset(0, 2) +# top_bar.setGraphicsEffect(shadow) + +# top_bar_layout.addWidget(logout_btn) +# top_bar_layout.addWidget(self.alert_button) +# top_bar_layout.addStretch() +# top_bar_layout.addWidget(title_container) +# top_bar_layout.addStretch() +# toolbar.addWidget(top_bar) + +# # ─────────────────────────────── +# # NAVIGATION +# # ─────────────────────────────── +# self.nav_dock = QDockWidget("Navigation", self) +# self.nav_dock.setFeatures(QDockWidget.DockWidgetFeature.NoDockWidgetFeatures) +# self.addDockWidget(Qt.DockWidgetArea.LeftDockWidgetArea, self.nav_dock) +# self.nav_list = QListWidget(self.nav_dock) +# self.nav_dock.setWidget(self.nav_list) +# self.nav_dock.setMinimumWidth(220) + +# font = QFont(); font.setPointSize(12) +# self.nav_list.setFont(font) + +# for main_item in ["Home", "Sensors", "Sound", "Ground Image", "Aerial Image", "Fruits", "Security", "Settings", "Notifications", "Auth"]: +# item = QListWidgetItem(main_item) +# item.setData(Qt.ItemDataRole.UserRole, {"type": "main"}) +# self.nav_list.addItem(item) +# if main_item == "Sensors": +# for sub in ["Live Data", "Sensor Health", "Location Map"]: +# sub_item = QListWidgetItem(f" ↳ {sub}") +# sub_item.setData(Qt.ItemDataRole.UserRole, {"type": "sub", "parent": main_item, "name": sub}) +# sub_item.setHidden(True) +# self.nav_list.addItem(sub_item) + +# self.nav_list.currentRowChanged.connect(self._on_nav_change) +# self.nav_list.itemClicked.connect(self._on_nav_click) + +# # ─────────────────────────────── +# # ALERT SERVICE + PANEL +# # ─────────────────────────────── +# ws_url = os.getenv("ALERTS_WS", "ws://alerts-gateway:8000/ws/alerts") +# self.alert_service = AlertService(ws_url, api) +# self.alert_service.alertsUpdated.connect(self.update_alert_badge) +# self.alert_service.alertAdded.connect(lambda _: self.update_alert_badge()) + +# self.alerts_panel = AlertsPanel(self.alert_service) +# self.alerts_panel.setWindowFlags(Qt.WindowType.FramelessWindowHint | Qt.WindowType.Tool) +# self.alerts_panel.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground) +# self.alerts_panel.setStyleSheet(""" +# QWidget { +# background-color: #ffffff; +# border: 1px solid #d1d5db; +# border-radius: 10px; +# } +# """) +# self.alerts_panel.hide() +# self.alert_button.clicked.connect(self.toggle_alert_panel) + +# # ─────────────────────────────── +# # CENTRAL STACKED VIEWS +# # ─────────────────────────────── +# self.home = HomeView(api, self.alert_service, self) +# self.sensors_view = SensorsView(api, self) +# self.notification_view = NotificationView(self) +# self.fruits_view = FruitsView(api, self) +# self.ground_view = GroundView(api, self) +# self.auth_status = AuthStatusView(api, self) + +# self.sensors_status_summary = SensorsStatusSummary(api, self) +# self.sensors_health = SensorsView(api, self) +# self.sensors_main = SensorsMainView(api, self) + +# self.stack = QStackedWidget() +# self.setCentralWidget(self.stack) +# self.views = { +# "Home": self.home, +# "Sensors": self.sensors_view, +# "Sensors - Live Data": self.sensors_status_summary, +# "Sensors - Sensor Health": self.sensors_health, +# "Sensors - Location Map": self.sensors_main, +# "Notifications": self.notification_view, +# "Fruits": self.fruits_view, +# "Ground Image": self.ground_view, +# "Auth": self.auth_status +# } + +# for view in self.views.values(): +# self.stack.addWidget(view) +# self.stack.setCurrentWidget(self.home) +# self.history = [] + +# # ─────────────────────────────── +# # STATUS BAR +# # ─────────────────────────────── +# sb = QStatusBar(self) +# sb.setStyleSheet("QStatusBar { background-color: #f3f4f6; color: #374151; font-size: 10.5pt; }") +# self.setStatusBar(sb) +# sb.showMessage("Ready") + +# # ─────────────────────────────── +# # ALERT BADGE +# # ─────────────────────────────── +# def update_alert_badge(self): +# unacked = sum(1 for a in self.alert_service.alerts if not a.get("ack", False)) +# if unacked > 0: +# self.alert_badge.setText(str(unacked)) +# self.alert_badge.show() +# else: +# self.alert_badge.hide() + +# def toggle_alert_panel(self): +# if self.alerts_panel.isVisible(): +# self.alerts_panel.hide() +# return + +# panel_width, panel_height = 420, 540 +# self.alerts_panel.resize(panel_width, panel_height) +# rect = self.alert_button.geometry() +# bottom_left = self.alert_button.mapToGlobal(rect.bottomLeft()) +# bottom_right = self.alert_button.mapToGlobal(rect.bottomRight()) +# center_x = (bottom_left.x() + bottom_right.x()) // 2 - (panel_width // 2) +# pos_y = bottom_left.y() + 8 +# self.alerts_panel.move(center_x, pos_y) +# self.alerts_panel.show() +# self.alerts_panel.raise_() + +# if hasattr(self.alert_service, "mark_all_acknowledged"): +# self.alert_service.mark_all_acknowledged() +# self.update_alert_badge() + +# # ─────────────────────────────── +# # NAVIGATION +# # ─────────────────────────────── +# def _on_nav_change(self, row: int) -> None: +# name = self.nav_list.item(row).text().strip() +# if name in self.views: +# self.navigate_to(self.views[name]) +# else: +# self.statusBar().showMessage(f"Section '{name}' not implemented yet.") + +# def _on_nav_click(self, item): +# data = item.data(Qt.ItemDataRole.UserRole) +# if data and data.get("type") == "main": +# parent = item.text() +# expanded = False +# for i in range(self.nav_list.count()): +# sub_item = self.nav_list.item(i) +# sub_data = sub_item.data(Qt.ItemDataRole.UserRole) +# if sub_data and sub_data.get("type") == "sub" and sub_data.get("parent") == parent: +# expanded = sub_item.isHidden() +# break +# for i in range(self.nav_list.count()): +# sub_item = self.nav_list.item(i) +# sub_data = sub_item.data(Qt.ItemDataRole.UserRole) +# if sub_data and sub_data.get("type") == "sub" and sub_data.get("parent") == parent: +# sub_item.setHidden(not expanded) +# elif data and data.get("type") == "sub": +# parent = data.get("parent") +# sub_name = data.get("name") +# key = f"{parent} - {sub_name}" +# if key in self.views: +# self.stack.setCurrentWidget(self.views[key]) + +# def navigate_to(self, widget): +# current = self.stack.currentWidget() +# if current not in self.history: +# self.history.append(current) +# self.stack.setCurrentWidget(widget) + +# def go_back(self): +# if self.history: +# last = self.history.pop() +# self.stack.setCurrentWidget(last) +# else: +# self.statusBar().showMessage("No previous view to go back to.") + +# def _logout(self) -> None: +# self.statusBar().showMessage("Logged out (demo)") +# self.logoutRequested.emit() + from PyQt6.QtCore import Qt, pyqtSignal, QSize from PyQt6.QtWidgets import ( QMainWindow, QDockWidget, QListWidget, QListWidgetItem, QStatusBar, @@ -9,19 +922,17 @@ from home_view import HomeView from views.sensors_view import SensorsView +from views.security.incident_player_vlc import IncidentPlayerVLC from views.alerts_panel import AlertsPanel from views.notification_view import NotificationView from views.fruits_view import FruitsView -from views.ground_view import GroundView -from views.auth_status_view import AuthStatusView from dashboard_api import DashboardApi from vast.alerts.alert_service import AlertService -# === New Sensors GUI imports === -from views.sensorsMainView import SensorsMainView -from views.sensorsMapView import SensorsMapView -from views.sensorDetailsTab import SensorDetailsTab -from views.sensors_status_summary import SensorsStatusSummary + + +# === Irrigation imports === +from views.irrigation.irrigation_view import IrrigationView class MainWindow(QMainWindow): @@ -37,18 +948,52 @@ def __init__(self, api: DashboardApi, parent=None): # GLOBAL STYLE # ─────────────────────────────── self.setStyleSheet(""" - QMainWindow { background-color: #f9fafb; } - QMenuBar { background-color: #e5e7eb; font-size: 11.5pt; padding: 4px 10px; } + QMainWindow { + background-color: #f9fafb; + } + QMenuBar { + background-color: #e5e7eb; + font-size: 11.5pt; + padding: 4px 10px; + } QToolBar { - background: qlineargradient(x1:0, y1:0, x2:0, y2:1, stop:0 #ffffff, stop:1 #f3f4f6); - border-bottom: 1px solid #d1d5db; padding: 2px 10px; min-height: 42px; + background: qlineargradient( + x1:0, y1:0, x2:0, y2:1, + stop:0 #ffffff, + stop:1 #f3f4f6 + ); + border-bottom: 1px solid #d1d5db; + padding: 2px 10px; + min-height: 42px; + } + QToolButton { + background-color: transparent; + border: none; + padding: 4px; + border-radius: 8px; + font-size: 20px; + } + QToolButton:hover { + background-color: #e5e7eb; + } + QListWidget { + background-color: #ffffff; + border: none; + font-size: 12pt; + color: #111827; + } + QListWidget::item { + padding: 10px; + border-radius: 6px; + } + QListWidget::item:selected { + background-color: #10b981; + color: white; + } + QStatusBar { + background-color: #f3f4f6; + font-size: 10pt; } - QToolButton { background-color: transparent; border: none; padding: 4px; border-radius: 8px; font-size: 20px; } - QToolButton:hover { background-color: #e5e7eb; } - QListWidget { background-color: #ffffff; border: none; font-size: 12pt; color: #111827; } - QListWidget::item { padding: 10px; border-radius: 6px; } - QListWidget::item:selected { background-color: #10b981; color: white; } - QStatusBar { background-color: #f3f4f6; font-size: 10pt; } """) # ─────────────────────────────── @@ -59,12 +1004,13 @@ def __init__(self, api: DashboardApi, parent=None): self.back_action.setShortcut("Alt+Left") self.back_action.triggered.connect(self.go_back) file_menu.addAction(self.back_action) + self.logout_action = QAction("Log out", self) self.logout_action.triggered.connect(self._logout) file_menu.addAction(self.logout_action) # ─────────────────────────────── - # TOP BAR (toolbar) + # TOP BAR # ─────────────────────────────── toolbar = self.addToolBar("Main Toolbar") toolbar.setMovable(False) @@ -76,6 +1022,13 @@ def __init__(self, api: DashboardApi, parent=None): top_bar_layout.setContentsMargins(8, 0, 8, 0) top_bar_layout.setSpacing(10) + # Back button + back_btn = QToolButton() + back_btn.setIcon(QIcon.fromTheme("go-previous")) + back_btn.setIconSize(QSize(28, 28)) + back_btn.setToolTip("Go back") + back_btn.clicked.connect(self.go_back) + # Logout button logout_btn = QPushButton("Logout") logout_btn.setToolTip("Log out") @@ -90,12 +1043,16 @@ def __init__(self, api: DashboardApi, parent=None): font-size: 11pt; font-weight: 600; } - QPushButton:hover { background-color: #059669; } - QPushButton:pressed { background-color: #047857; } + QPushButton:hover { + background-color: #059669; + } + QPushButton:pressed { + background-color: #047857; + } """) logout_btn.clicked.connect(self._logout) - # Alert bell + # Bell button self.alert_button = QToolButton() self.alert_button.setToolTip("Show alerts") self.alert_button.setText("🔔") @@ -108,16 +1065,18 @@ def __init__(self, api: DashboardApi, parent=None): padding: 4px; border-radius: 8px; } - QToolButton:hover { background-color: #e5e7eb; } + QToolButton:hover { + background-color: #e5e7eb; + } """) - # Alert badge + # Larger blue badge self.alert_badge = QLabel("0", self.alert_button) self.alert_badge.setAlignment(Qt.AlignmentFlag.AlignCenter) self.alert_badge.setFixedSize(24, 24) self.alert_badge.setStyleSheet(""" QLabel { - background-color: #3b82f6; + background-color: #3b82f6; /* blue */ color: white; font-size: 10pt; font-weight: bold; @@ -139,12 +1098,18 @@ def reposition_badge(): ) reposition_badge() + # Title title_label = QLabel("VAST Dashboard") title_label.setAlignment(Qt.AlignmentFlag.AlignCenter) title_label.setStyleSheet(""" - QLabel { font-size: 17pt; font-weight: 600; color: #111827; } + QLabel { + font-size: 17pt; + font-weight: 600; + color: #111827; + } """) + # Shadow shadow = QGraphicsDropShadowEffect() shadow.setBlurRadius(8) shadow.setColor(QColor(0, 0, 0, 35)) @@ -156,44 +1121,42 @@ def reposition_badge(): top_bar_layout.addStretch() top_bar_layout.addWidget(title_label) top_bar_layout.addStretch() + toolbar.addWidget(top_bar) # ─────────────────────────────── - # NAVIGATION + # NAVIGATION DOCK # ─────────────────────────────── self.nav_dock = QDockWidget("Navigation", self) self.nav_dock.setFeatures(QDockWidget.DockWidgetFeature.NoDockWidgetFeatures) self.addDockWidget(Qt.DockWidgetArea.LeftDockWidgetArea, self.nav_dock) + self.nav_list = QListWidget(self.nav_dock) self.nav_dock.setWidget(self.nav_list) self.nav_dock.setMinimumWidth(220) - font = QFont(); font.setPointSize(12) + font = QFont() + font.setPointSize(12) self.nav_list.setFont(font) - # Menu with expandable Sensors section - for main_item in ["Home", "Sensors", "Sound", "Ground Image", "Aerial Image", "Fruits", "Security", "Settings", "Notifications", "Auth"]: - item = QListWidgetItem(main_item) - item.setData(Qt.ItemDataRole.UserRole, {"type": "main"}) - self.nav_list.addItem(item) - if main_item == "Sensors": - for sub in ["Live Data", "Sensor Health", "Location Map"]: - sub_item = QListWidgetItem(f" ↳ {sub}") - sub_item.setData(Qt.ItemDataRole.UserRole, {"type": "sub", "parent": main_item, "name": sub}) - sub_item.setHidden(True) - self.nav_list.addItem(sub_item) + for name in [ + "Home", "Sensors", "Sound", "Ground Image", + "Aerial Image", "Fruits", "Security", "Settings", "Notifications", "Irrigation" + ]: + QListWidgetItem(f" {name}", self.nav_list) + self.nav_list.setCurrentRow(0) self.nav_list.currentRowChanged.connect(self._on_nav_change) - self.nav_list.itemClicked.connect(self._on_nav_click) # ─────────────────────────────── - # ALERT SERVICE + PANEL + # ALERT SERVICE # ─────────────────────────────── ws_url = os.getenv("ALERTS_WS", "ws://alerts-gateway:8000/ws/alerts") self.alert_service = AlertService(ws_url, api) self.alert_service.alertsUpdated.connect(self.update_alert_badge) self.alert_service.alertAdded.connect(lambda _: self.update_alert_badge()) + # Alerts panel self.alerts_panel = AlertsPanel(self.alert_service) self.alerts_panel.setWindowFlags(Qt.WindowType.FramelessWindowHint | Qt.WindowType.Tool) self.alerts_panel.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground) @@ -213,38 +1176,54 @@ def reposition_badge(): self.home = HomeView(api, self.alert_service, self) self.sensors_view = SensorsView(api, self) self.notification_view = NotificationView(self) + self.security_view = IncidentPlayerVLC(api, self.alert_service, self) self.fruits_view = FruitsView(api, self) self.ground_view = GroundView(api, self) self.auth_status = AuthStatusView(api, self) - # New Sensors views self.sensors_status_summary = SensorsStatusSummary(api, self) self.sensors_health = SensorsView(api, self) self.sensors_main = SensorsMainView(api, self) + print("[DEBUG] Creating IrrigationView...") + try: + self.irrigation_view = IrrigationView(api, self) + print("[DEBUG] IrrigationView created successfully") + except Exception as e: + print(f"[ERROR] Failed to create IrrigationView: {e}") + import traceback + traceback.print_exc() + self.irrigation_view = QWidget() # Fallback empty widget self.stack = QStackedWidget() self.setCentralWidget(self.stack) + self.views = { "Home": self.home, "Sensors": self.sensors_view, - "Sensors - Live Data": self.sensors_status_summary, - "Sensors - Sensor Health": self.sensors_health, - "Sensors - Location Map": self.sensors_main, "Notifications": self.notification_view, + "Security": self.security_view, "Fruits": self.fruits_view, - "Ground": self.ground_view, - "Auth": self.auth_status, + "Ground Image": self.ground_view, + "Irrigation": self.irrigation_view, + "Auth": self.auth_status + } for view in self.views.values(): self.stack.addWidget(view) self.stack.setCurrentWidget(self.home) - self.history = [] + self.history: list = [] # ─────────────────────────────── # STATUS BAR # ─────────────────────────────── sb = QStatusBar(self) - sb.setStyleSheet("QStatusBar { background-color: #f3f4f6; color: #374151; font-size: 10.5pt; }") + sb.setStyleSheet(""" + QStatusBar { + background-color: #f3f4f6; + color: #374151; + font-size: 10.5pt; + } + """) self.setStatusBar(sb) sb.showMessage("Ready") @@ -284,39 +1263,23 @@ def toggle_alert_panel(self): # ─────────────────────────────── def _on_nav_change(self, row: int) -> None: name = self.nav_list.item(row).text().strip() + print(f"[DEBUG] _on_nav_change: row={row}, name='{name}'") + print(f"[DEBUG] Available views: {list(self.views.keys())}") if name in self.views: + print(f"[DEBUG] Navigating to '{name}'") self.navigate_to(self.views[name]) else: + print(f"[DEBUG] Section '{name}' not found in views") self.statusBar().showMessage(f"Section '{name}' not implemented yet.") - def _on_nav_click(self, item): - data = item.data(Qt.ItemDataRole.UserRole) - if data and data.get("type") == "main": - parent = item.text() - expanded = False - for i in range(self.nav_list.count()): - sub_item = self.nav_list.item(i) - sub_data = sub_item.data(Qt.ItemDataRole.UserRole) - if sub_data and sub_data.get("type") == "sub" and sub_data.get("parent") == parent: - expanded = sub_item.isHidden() - break - for i in range(self.nav_list.count()): - sub_item = self.nav_list.item(i) - sub_data = sub_item.data(Qt.ItemDataRole.UserRole) - if sub_data and sub_data.get("type") == "sub" and sub_data.get("parent") == parent: - sub_item.setHidden(not expanded) - elif data and data.get("type") == "sub": - parent = data.get("parent") - sub_name = data.get("name") - key = f"{parent} - {sub_name}" - if key in self.views: - self.stack.setCurrentWidget(self.views[key]) - def navigate_to(self, widget): + print(f"[DEBUG] navigate_to called with widget: {widget.__class__.__name__}") current = self.stack.currentWidget() if current not in self.history: self.history.append(current) + print(f"[DEBUG] Setting current widget to: {widget.__class__.__name__}") self.stack.setCurrentWidget(widget) + print(f"[DEBUG] Current widget is now: {self.stack.currentWidget().__class__.__name__}") def go_back(self): if self.history: @@ -327,4 +1290,4 @@ def go_back(self): def _logout(self) -> None: self.statusBar().showMessage("Logged out (demo)") - self.logoutRequested.emit() + self.logoutRequested.emit() \ No newline at end of file diff --git a/GUI/src/vast/orthophoto_canvas/ui/fields.png b/GUI/src/vast/orthophoto_canvas/ui/fields.png new file mode 100644 index 000000000..a279cc08d Binary files /dev/null and b/GUI/src/vast/orthophoto_canvas/ui/fields.png differ diff --git a/GUI/src/vast/orthophoto_canvas/ui/viewer.py b/GUI/src/vast/orthophoto_canvas/ui/viewer.py index 34f0fc4a2..ef2c122c9 100644 --- a/GUI/src/vast/orthophoto_canvas/ui/viewer.py +++ b/GUI/src/vast/orthophoto_canvas/ui/viewer.py @@ -12,7 +12,7 @@ from PyQt6.QtWidgets import ( QGraphicsView, QGraphicsScene, QGraphicsPixmapItem, QGraphicsRectItem ) - +from PyQt6.QtGui import QPixmap, QTransform # ==== Tunables ==== TILE_SIZE = 512 TARGET_TILE_PX_FOR_LOD = 512.0 @@ -25,18 +25,7 @@ class OrthophotoViewer(QGraphicsView): def __init__(self, tiles: Union[TileStore, str, Path]) -> None: super().__init__() - # ───────────────────────────── - # Load tiles - # ───────────────────────────── - # if isinstance(tiles, TileStore): - # self.ts = tiles - # else: - # self.ts = TileStore(Path(tiles)) - - # self.min_zoom_fs = self.ts.min_zoom - # self.max_zoom_fs = self.ts.max_zoom - # self.z_ranges = self.ts.z_ranges - # self.is_tms = self.ts.is_tms + # ───────────────────────────── # Load tiles # ───────────────────────────── @@ -125,8 +114,58 @@ def __init__(self, tiles: Union[TileStore, str, Path]) -> None: # ───────────────────────────── # Initial tile rendering # ───────────────────────────── + self._custom_bg_item: Optional[QGraphicsPixmapItem] = None + self._tiles_visible: bool = True self.update_tiles() - + + def _apply_tile_visibility(self): + """Apply visibility/opacity preference to existing tile items.""" + for item in self.tile_items.values(): + # You can choose to hide or fade; here we just hide/show them. + item.setVisible(self._tiles_visible) + # If you prefer fading: + # item.setOpacity(0.2 if not self._tiles_visible else 1.0) + + + + def set_custom_background_image(self, path: str, hide_tiles: bool = False): + """ + Place a single static image as the map background, scaled to the scene extents. + It will zoom & pan together with all other items. + """ + pix = QPixmap(path) + p = Path(path) + print("[OrthophotoViewer] Exists?", p.exists()) + if pix.isNull(): + print(f"[OrthophotoViewer] ❌ Failed to load background image: {path}") + return + + # Remove previous bg if exists + if self._custom_bg_item is not None: + self.scene.removeItem(self._custom_bg_item) + self._custom_bg_item = None + + scene_rect = self.scene.sceneRect() + width = scene_rect.width() + height = scene_rect.height() + + item = QGraphicsPixmapItem(pix) + item.setZValue(-1000) # behind tiles, regions, sensors + + # Scale to fill the entire scene rect + sx = width / pix.width() if pix.width() > 0 else 1.0 + sy = height / pix.height() if pix.height() > 0 else 1.0 + item.setTransform(QTransform().scale(sx, sy)) + + # Position at the scene rect origin (you use a small margin, so respect that) + item.setPos(scene_rect.left(), scene_rect.top()) + + self.scene.addItem(item) + self._custom_bg_item = item + + if hide_tiles: + self._tiles_visible = False + self._apply_tile_visibility() # ───────────────────────────── # Scene geometry @@ -228,6 +267,9 @@ def update_tiles(self) -> None: if key not in want: self.scene.removeItem(self.tile_items.pop(key)) + # 🔹 Ensure visibility style is applied to all tiles (including new ones) + self._apply_tile_visibility() + # ───────────────────────────── # Tile placement / upgrade # ───────────────────────────── diff --git a/GUI/src/vast/views/SimilarPeriodsSensors.py b/GUI/src/vast/views/SimilarPeriodsSensors.py new file mode 100644 index 000000000..8c0a0c84d --- /dev/null +++ b/GUI/src/vast/views/SimilarPeriodsSensors.py @@ -0,0 +1,345 @@ +from PyQt6.QtWidgets import ( + QWidget, QVBoxLayout, QHBoxLayout, QLabel, QFrame, QComboBox, + QPushButton, QGridLayout +) +from PyQt6.QtWebEngineWidgets import QWebEngineView +from PyQt6.QtCore import Qt +from PyQt6.QtGui import QColor +import traceback + + +class SimilarPeriodsTab(QWidget): + def __init__(self, api, parent=None): + super().__init__(parent) + self.api = api + + # vector service internal Docker endpoint + self.vector_base = "http://vector_service:8000" + + # ======= MAIN LAYOUT (compact) ======= + main = QVBoxLayout(self) + main.setContentsMargins(20, 20, 20, 20) + main.setSpacing(12) + + # ================================ + # HEADER + # ================================ + title = QLabel("🌾 Similar Sensors Search") + title.setStyleSheet(""" + QLabel { + font-family: 'Inter'; + font-size: 26px; + font-weight: 800; + color: #1a1a1a; + margin-bottom: 2px; + } + """) + + subtitle = QLabel("Find sensors with similar characteristics") + subtitle.setStyleSheet(""" + QLabel { + font-family: 'Inter'; + font-size: 13px; + font-weight: 400; + color: #6B7280; + margin-bottom: 8px; + } + """) + + header_layout = QVBoxLayout() + header_layout.setSpacing(3) + header_layout.addWidget(title) + header_layout.addWidget(subtitle) + main.addLayout(header_layout) + + # ================================ + # SENSOR SELECTOR + # ================================ + sensor_row = QHBoxLayout() + sensor_row.setSpacing(8) + + lbl = QLabel("Sensor:") + lbl.setStyleSheet("font-size: 14px; font-weight: 600; color:#374151;") + + self.sensor_dropdown = QComboBox() + self.sensor_dropdown.setMinimumWidth(230) + self.sensor_dropdown.setStyleSheet(""" + QComboBox { + background: #ffffff; + border: 1px solid #d1d5db; + border-radius: 8px; + padding: 6px 10px; + font-size: 13px; + font-family: 'Inter'; + } + """) + + self._load_sensor_list() + + sensor_row.addWidget(lbl) + sensor_row.addWidget(self.sensor_dropdown) + sensor_row.addStretch() + main.addLayout(sensor_row) + + # ================================ + # COMPACT FILTER CARDS (GREEN) + # ================================ + cards_row = QHBoxLayout() + cards_row.setSpacing(8) + + self.card_same_status = self._create_filter_card("Same Status", "●") + self.card_same_type = self._create_filter_card("Same Type", "●") + self.card_same_day = self._create_filter_card("Same Install Day", "●") + + cards_row.addWidget(self.card_same_status) + cards_row.addWidget(self.card_same_type) + cards_row.addWidget(self.card_same_day) + main.addLayout(cards_row) + + # ================================ + # DATE FILTER (Compact card) + # ================================ + time_box = QFrame() + time_box.setStyleSheet(""" + QFrame { + background: #ffffff; + border-radius: 10px; + border: 1px solid #e5e7eb; + padding: 10px; + } + """) + + time_layout = QVBoxLayout(time_box) + time_layout.setSpacing(4) + + time_label = QLabel("Date Filter:") + time_label.setStyleSheet("font-size: 14px; font-weight:600; color:#374151;") + + self.date_dropdown = QComboBox() + self.date_dropdown.setStyleSheet(""" + QComboBox { + background: white; + border: 1px solid #d1d5db; + padding: 6px 10px; + border-radius: 8px; + font-size: 13px; + font-family: 'Inter'; + } + """) + + self.date_dropdown.addItem("— None —", None) + self.date_dropdown.addItem("Today", "today") + self.date_dropdown.addItem("Yesterday", "yesterday") + + weekdays = ["Monday","Tuesday","Wednesday","Thursday","Friday","Saturday","Sunday"] + for w in weekdays: + self.date_dropdown.addItem(w, w.lower()) + for w in weekdays: + self.date_dropdown.addItem("Last " + w, "last_" + w.lower()) + + time_layout.addWidget(time_label) + time_layout.addWidget(self.date_dropdown) + + main.addWidget(time_box) + + # ================================ + # SEARCH BUTTON (compact) + # ================================ + self.btn = QPushButton("🔍 Search") + self.btn.setFixedHeight(40) + self.btn.setStyleSheet(""" + QPushButton { + background: #3B82F6; + color: white; + font-size: 15px; + font-weight: 600; + border-radius: 10px; + font-family: 'Inter'; + } + QPushButton:hover { background:#2563EB; } + """) + self.btn.clicked.connect(self._on_search) + main.addWidget(self.btn) + + # ================================ + # RESULTS VIEW — FULL HEIGHT + # ================================ + self.web = QWebEngineView() + self.web.setMinimumHeight(350) # pushes table to full size + main.addWidget(self.web) + + self._placeholder() + + # Background like dashboard + self.setStyleSheet(""" + QWidget { + background: qlineargradient(x1:0,y1:0,x2:0,y2:1, + stop:0 #F8FAFC, stop:1 #F1F5F9); + } + """) + + # ========= FILTER CARD (compact) ========= + def _create_filter_card(self, title, icon): + card = QFrame() + card.setProperty("active", False) + + card.setStyleSheet(""" + QFrame { + background: #F0FDF4; + border-radius: 12px; + border: 1px solid #D1FAE5; + } + QFrame[active="true"] { + border: 2px solid #10B981; + } + """) + + layout = QHBoxLayout(card) + layout.setContentsMargins(12, 8, 12, 8) + layout.setSpacing(8) + + icon_label = QLabel(icon) + icon_label.setStyleSheet(""" + QLabel { + font-size: 22px; + color: #10B981; + font-weight: 900; + } + """) + + text_label = QLabel(title) + text_label.setStyleSheet(""" + QLabel { + font-size: 13px; + font-weight: 600; + color: #374151; + font-family:'Inter'; + } + """) + + layout.addWidget(icon_label) + layout.addWidget(text_label) + + card.mousePressEvent = lambda e: self._toggle_card(card) + return card + + def _toggle_card(self, card): + state = not card.property("active") + card.setProperty("active", state) + card.style().unpolish(card) + card.style().polish(card) + card.update() + + # ========= PLACEHOLDER ========= + def _placeholder(self): + self.web.setHtml(""" +

+ Select filters and search for similar sensors. +

+ """) + + # ========= LOAD SENSOR LIST ========= + def _load_sensor_list(self): + try: + r = self.api.http.get(f"{self.api.base}/api/tables/sensors") + sensors = r.json().get("rows", []) + self.sensor_dropdown.addItem("-- Select Sensor --", None) + + for s in sensors: + sid = s.get("sensor_id") + name = s.get("sensor_name", "") + self.sensor_dropdown.addItem(f"{sid} – {name}", sid) + + except Exception as e: + print("Failed loading sensors:", e) + + # ========= BUILD PARAMS ========= + def _build_query_params(self): + params = {} + if self.card_same_status.property("active"): + params["same_status"] = "true" + if self.card_same_type.property("active"): + params["same_type"] = "true" + if self.card_same_day.property("active"): + params["same_day"] = "true" + + selected = self.date_dropdown.currentData() + if selected: + params["date_filter"] = selected + + return params + + # ========= SEARCH ========= + def _on_search(self): + sid = self.sensor_dropdown.currentData() + if not sid: + self.web.setHtml("

Select a sensor.

") + return + + params = self._build_query_params() + + if not params: + url = f"{self.vector_base}/similar_sensors/{sid}" + else: + q = "&".join([f"{k}={v}" for k, v in params.items()]) + url = f"{self.vector_base}/similar_sensors_advanced?sensor_id={sid}&{q}" + + try: + data = self.api.http.get(url).json() + self._render_results(data) + except Exception as e: + traceback.print_exc() + self.web.setHtml(f"

Error: {e}

") + + # ========= RENDER RESULTS (full-size table) ========= + def _render_results(self, data): + sims = data.get("similar_sensors", []) + + if not sims: + self.web.setHtml("

No results found.

") + return + + rows = "" + for s in sims: + status = s.get("status", "").lower() + active = (status == "active") + status_display = ( + "● ONLINE" + if active else + "● OFFLINE" + ) + + rows += f""" + + {s.get('sensor_id','—')} + {s.get('sensor_name','—')} + {s.get('sensor_type','—')} + {s.get('install_date','—')} + {status_display} + {round(s.get('distance',0),3)} + + """ + + html = f""" + + + + + + + + + + + + + + + {rows} + +
IDNameTypeInstall DateActiveDistance
+ + + """ + + self.web.setHtml(html) diff --git a/GUI/src/vast/views/assets/sensors_map.html b/GUI/src/vast/views/assets/sensors_map.html index 3a711258b..ce43700bf 100644 --- a/GUI/src/vast/views/assets/sensors_map.html +++ b/GUI/src/vast/views/assets/sensors_map.html @@ -1,3 +1,5 @@ + + @@ -72,8 +74,18 @@ 50% { transform: scale(1.35); box-shadow: 0 0 8px rgba(0,0,0,0.3); } 100% { transform: scale(1); box-shadow: 0 0 0 0 rgba(0,0,0,0.0); } } - .pulse-change { - animation: pulseChange 0.5s ease-out; + .pulse-change { animation: pulseChange 0.5s ease-out; } + + /* Tooltip styling for zone names */ + .zone-tooltip { + background: rgba(34, 197, 94, 0.9); + color: white; + font-weight: 600; + border: none; + border-radius: 6px; + box-shadow: 0 2px 6px rgba(0,0,0,0.25); + padding: 2px 8px; + font-size: 13px; } @@ -89,53 +101,113 @@ -
-
-
+
- - - - - - - diff --git a/GUI/src/vast/views/fruits_view.py b/GUI/src/vast/views/fruits_view.py index c77ded97d..37b85a508 100644 --- a/GUI/src/vast/views/fruits_view.py +++ b/GUI/src/vast/views/fruits_view.py @@ -387,6 +387,33 @@ def __init__(self, api: DashboardApi, parent=None): self.btn_open_editor.clicked.connect(self.open_thresholds_dialog) + # ───────────────────────────────────────────── + # Metrics Section (Grafana panels) + # ───────────────────────────────────────────── + metrics_title = QLabel("Fruit Alerts Metrics") + metrics_title.setStyleSheet("font-size: 18px; font-weight: 600; margin-top: 15px;") + root.addWidget(metrics_title) + + grafana_host = os.getenv("GRAFANA_HOST", "grafana") + base = f"http://{grafana_host}:3000" + + panel_urls = [ + QUrl(f"{base}/d-solo/fruit-metrics/fruit-alerts?orgId=1&panelId=1&refresh=10s&theme=light"), + QUrl(f"{base}/d-solo/fruit-metrics/fruit-alerts?orgId=1&panelId=2&refresh=10s&theme=light"), + QUrl(f"{base}/d-solo/fruit-metrics/fruit-alerts?orgId=1&panelId=3&refresh=10s&theme=light"), + QUrl(f"{base}/d-solo/fruit-metrics/fruit-alerts?orgId=1&panelId=4&refresh=10s&theme=light"), + ] + + metrics_box = QVBoxLayout() + metrics_box.setSpacing(10) + root.addLayout(metrics_box) + + for url in panel_urls: + view = QWebEngineView(self) + view.setMinimumHeight(300) + view.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + view.setUrl(url) + metrics_box.addWidget(view) def open_thresholds_dialog(self): dlg = ThresholdsEditorDialog(self.api, self) diff --git a/GUI/src/vast/views/ground_view.py b/GUI/src/vast/views/ground_view.py index d49db9305..d4da6f80e 100644 --- a/GUI/src/vast/views/ground_view.py +++ b/GUI/src/vast/views/ground_view.py @@ -1,22 +1,29 @@ - from __future__ import annotations import os from dataclasses import dataclass from typing import Optional, Any, Dict, List -from PyQt6.QtCore import Qt, QTimer, QSize -from PyQt6.QtGui import QPixmap, QKeyEvent +from PyQt6.QtCore import Qt, QTimer, QSize, QRectF +from PyQt6.QtGui import QPixmap, QKeyEvent, QPainter, QColor, QPen, QFont from PyQt6.QtWidgets import ( QWidget, QVBoxLayout, QHBoxLayout, QLabel, QPushButton, QProgressBar, QMessageBox, QSizePolicy, QFrame ) -# The client does not access MinIO directly; everything goes through DashboardApi +# GUI never touches MinIO directly – it uses DashboardApi only. from vast.dashboard_api import DashboardApi GROUND_BUCKET = os.getenv("GROUND_BUCKET", "ground") GROUND_PREFIX = os.getenv("GROUND_PREFIX", "") +DB_API_BASE = os.getenv("DB_API_BASE", "http://127.0.0.1:8001") +MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "127.0.0.1:9001") +MINIO_SECURE = os.getenv("MINIO_SECURE", "false") +MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "minioadmin") +MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "minioadmin123") +GROUND_BUCKET = os.getenv("GROUND_BUCKET", "ground") +GROUND_PREFIX = os.getenv("GROUND_PREFIX", "") +GATEWAY_URL = os.getenv("GATEWAY_URL", "http://127.0.0.1:8000") # ---------------------------- # PHI data model # ---------------------------- @@ -25,13 +32,14 @@ class PhiSnapshot: phi: Optional[float] # 0..100 or None density: Optional[float] coverage: Optional[float] - severity_avg: Optional[float] + severity_avg: Optional[float] # usually 0..1 (clamped) trend: Optional[float] week_start: Optional[str] - source: str = "" # textual hint of data source + source: str = "" # textual hint of data source (NOT shown in UI) def _phi_band_color(v: float) -> str: + # 80..100 = green, 50..79 = amber, else red if v >= 80: return "#16a34a" # green-600 if v >= 50: @@ -48,16 +56,109 @@ def _safe_float(x) -> Optional[float]: return None +# ---------------------------- +# Visual PHI circle (pie) +# ---------------------------- +class PhiCircleWidget(QWidget): + """ + Draws a pie: + - red slice = severity in [0..1] + - green slice = 1 - severity (healthy remainder) + Always draws red on top so it's never hidden. + Also draws the severity percentage text centered on the pie. + """ + def __init__(self, parent=None): + super().__init__(parent) + self._severity = 0.0 # 0..1 + self.setAttribute(Qt.WidgetAttribute.WA_OpaquePaintEvent, True) + self.setSizePolicy(QSizePolicy.Policy.Fixed, QSizePolicy.Policy.Fixed) + self.setToolTip("Red slice = severity (0..1). Green = healthy remainder.") + + def sizeHint(self): + return QSize(120, 120) + + def minimumSizeHint(self): + return QSize(100, 100) + + def setSeverity(self, value: float) -> None: + try: + v = float(value) + except Exception: + v = 0.0 + self._severity = max(0.0, min(1.0, v)) + self.update() # ensure repaint + + def paintEvent(self, event) -> None: + try: + painter = QPainter(self) + painter.setRenderHint(QPainter.RenderHint.Antialiasing, True) + painter.setPen(Qt.PenStyle.NoPen) + + pad = 10 + size = min(self.width(), self.height()) - 2 * pad + if size <= 0: + return + cx = (self.width() - size) / 2 + cy = (self.height() - size) / 2 + rect = QRectF(cx, cy, size, size) + + start = 90 * 16 # 12 o'clock (Qt: 0° is 3 o'clock) + full = -360 * 16 + + s = self._severity + # Degenerate cases + if s <= 1e-6: + painter.setBrush(QColor("#16a34a")) + painter.drawEllipse(rect) + elif s >= 1 - 1e-6: + painter.setBrush(QColor("#dc2626")) + painter.drawEllipse(rect) + else: + span_red = int(round(full * s)) # negative (clockwise) + span_green = full - span_red # the remainder + + # Draw green remainder first + painter.setBrush(QColor("#16a34a")) + painter.drawPie(rect, start + span_red, span_green) + + # Draw red slice on top (so it's always visible) + painter.setBrush(QColor("#dc2626")) + painter.drawPie(rect, start, span_red) + + # Outline + pen = QPen(QColor("#334155")) + pen.setWidth(2) + painter.setPen(pen) + painter.setBrush(Qt.BrushStyle.NoBrush) + painter.drawEllipse(rect) + + # Percentage text (centered) + percent_text = f"{int(round(s * 100))}%" + font = QFont() + font.setBold(True) + font.setPointSize(int(size * 0.22)) # responsive sizing + painter.setFont(font) + + # Soft shadow for readability + painter.setPen(QColor(0, 0, 0, 160)) + painter.drawText(rect, Qt.AlignmentFlag.AlignCenter, percent_text) + # Foreground text + painter.setPen(QColor("#ffffff")) + painter.drawText(rect, Qt.AlignmentFlag.AlignCenter, percent_text) + + except Exception as e: + print(f"[PhiCircleWidget] paintEvent error: {e}") + + +# ---------------------------- +# GroundView +# ---------------------------- class GroundView(QWidget): """ Gallery mode: - - Loads all object keys from MinIO bucket=GROUND_BUCKET, prefix=GROUND_PREFIX. + - Loads all object keys from MinIO via DashboardApi. - Keeps current index; supports Prev/Next buttons and keyboard arrows. - - On image change, loads bytes via DashboardApi and refreshes PHI for that key. - - Design goals: - - No direct MinIO client on the GUI. - - Be resilient to missing API methods; fail gracefully. + - On image change, fetches bytes and refreshes PHI for that key. """ def __init__(self, api: DashboardApi, parent=None): @@ -77,6 +178,7 @@ def __init__(self, api: DashboardApi, parent=None): title.setStyleSheet("font-size:20px;font-weight:800;color:#0f172a;") root.addWidget(title) + # Toolbar toolbar = QHBoxLayout() self.btn_refresh_list = QPushButton("Reload list") self.btn_refresh_list.clicked.connect(self.reload_keys) @@ -128,26 +230,42 @@ def __init__(self, api: DashboardApi, parent=None): phi_layout.setContentsMargins(12, 12, 12, 12) phi_layout.setSpacing(8) + # Row with headline + (trimmed) details row = QHBoxLayout() self.phi_label = QLabel("PHI: –") self.phi_label.setStyleSheet("font-size:16px;font-weight:700;color:#0f172a;") row.addWidget(self.phi_label) row.addStretch(1) - self.phi_details = QLabel("") + self.phi_details = QLabel("") # will show severity/coverage/trend (without src) self.phi_details.setStyleSheet("color:#475569;font-size:12px;") row.addWidget(self.phi_details) phi_layout.addLayout(row) + # PHI progress (axis-like) + pie at its side self.phi_bar = QProgressBar() self.phi_bar.setRange(0, 100) self.phi_bar.setValue(0) self.phi_bar.setFormat("%v") self._style_phi_bar(None) - phi_layout.addWidget(self.phi_bar) + + phi_row2 = QHBoxLayout() + phi_row2.setContentsMargins(0, 0, 0, 0) + phi_row2.setSpacing(10) + phi_row2.addWidget(self.phi_bar, stretch=1) + + self.phi_circle = PhiCircleWidget() + self.phi_circle.setFixedSize(120, 120) + phi_row2.addWidget(self.phi_circle) + + phi_layout.addLayout(phi_row2) + + legend = QLabel(" = Severity | = Healthy") + legend.setStyleSheet("color:#64748b;font-size:11px;") + phi_layout.addWidget(legend) root.addWidget(phi_frame, stretch=1) - # Auto-refresh PHI every 2 min (optional) + # Auto-refresh PHI every 2 min self.timer = QTimer(self) self.timer.setInterval(120_000) self.timer.timeout.connect(self.refresh_phi_current) @@ -156,7 +274,7 @@ def __init__(self, api: DashboardApi, parent=None): # Initial load QTimer.singleShot(200, self.reload_keys) - # So that arrow keys work even without inner focus + # So arrow keys work even without inner focus self.setFocusPolicy(Qt.FocusPolicy.StrongFocus) # ---------------------------- @@ -170,6 +288,7 @@ def _style_phi_bar(self, value: Optional[float]) -> None: ) def _warn(self, msg: str) -> None: + # Non-blocking warning box try: def _show(): try: @@ -187,6 +306,7 @@ def _show(): print(f"[GroundView] WARN: {msg}") def _try_api(self, names: List[str], *args, **kwargs) -> Any: + # Try a list of API method names until one succeeds. for name in names: fn = getattr(self.api, name, None) if callable(fn): @@ -228,6 +348,7 @@ def _lm(o): self._keys = keys self._idx = 0 if self._keys else -1 self._update_counter() + self._update_nav_buttons() if self._idx >= 0: self.load_current_image() else: @@ -243,6 +364,11 @@ def _update_counter(self) -> None: pos = (self._idx + 1) if self._idx >= 0 else 0 self.counter_label.setText(f"({pos} / {total})") + def _update_nav_buttons(self) -> None: + has = bool(self._keys) + for b in (self.btn_prev, self.btn_next, self.btn_show_phi): + b.setEnabled(has) + def prev_image(self) -> None: if not self._keys: return @@ -279,6 +405,7 @@ def _set_image(self, pix: Optional[QPixmap]) -> None: target_size: QSize = self.image_label.size() if target_size.width() <= 4 or target_size.height() <= 4: self.image_label.setPixmap(pix) + self.image_label.setText("") return scaled = pix.scaled( target_size.width(), @@ -308,6 +435,8 @@ def load_current_image(self) -> None: getter = getattr(self.api, "get_image_bytes_from_minio", None) if not callable(getter): self._warn("DashboardApi.get_image_bytes_from_minio is missing.") + self._set_image(None) + self._render_phi_none() return data = None @@ -334,11 +463,13 @@ def load_current_image(self) -> None: self._set_image(pix) self.img_meta.setText(f"{GROUND_BUCKET}/{key}") + # After image displayed, refresh PHI self._refresh_phi_for_key(key) except Exception as e: self._warn(f"load_current_image error: {e}") + self._render_phi_none() # ---------------------------- # PHI flow @@ -359,30 +490,27 @@ def _render_phi_none(self) -> None: self.phi_details.setText("No PHI available.") self.phi_bar.setValue(0) self._style_phi_bar(None) + self.phi_circle.setSeverity(0.0) def _refresh_phi_for_key(self, key: str) -> None: - """Try best-effort PHI for the specific image key.""" + """Best-effort PHI for the specific image key. Fully guarded.""" try: - # Preferred API: PHI for an explicit image key + # 1) Exact by key d = self._try_api(["get_phi_for_image"], key) if isinstance(d, dict) and (d.get("phi") is not None or d.get("severity_avg") is not None): - snap = self._map_phi_dict(d, "phi_by_key") - return self._render_phi(snap) + return self._render_phi(self._map_phi_dict(d, "phi_by_key")) - # Fallbacks (like your previous logic) - # 1) PHI for current image (if API tracks it) + # 2) Current image d = self._try_api(["get_phi_for_current_image"]) if isinstance(d, dict) and (d.get("phi") is not None or d.get("severity_avg") is not None): - snap = self._map_phi_dict(d, "phi_current") - return self._render_phi(snap) + return self._render_phi(self._map_phi_dict(d, "phi_current")) - # 2) weekly/global PHI + # 3) Weekly/global d = self._try_api(["get_weekly_phi"]) if isinstance(d, dict) and (d.get("phi") is not None or d.get("severity_avg") is not None): - snap = self._map_phi_dict(d, "weekly") - return self._render_phi(snap) + return self._render_phi(self._map_phi_dict(d, "weekly")) - # 3) derive from latest rows (very rough) + # 4) Derive roughly from latest rows as last resort rows = self._try_api(["get_latest_rows", "get_latest_detections", "get_latest_ground_rows"], limit=1) or [] if rows and isinstance(rows, list) and isinstance(rows[0], dict): sev = None @@ -395,6 +523,7 @@ def _refresh_phi_for_key(self, key: str) -> None: cov = _safe_float(rows[0].get(k)) if cov is not None: break + phi_val = None if sev is not None: s = sev if sev <= 1.0 else min(sev, 10.0) / 10.0 @@ -402,6 +531,7 @@ def _refresh_phi_for_key(self, key: str) -> None: elif cov is not None: c = max(0.0, min(1.0, cov)) phi_val = 100.0 * c + if phi_val is not None: snap = PhiSnapshot( phi=phi_val, density=None, coverage=cov, severity_avg=sev, @@ -409,19 +539,23 @@ def _refresh_phi_for_key(self, key: str) -> None: ) return self._render_phi(snap) + # Nothing available self._render_phi_none() - + # self._warn("No PHI available for this image.") except Exception as e: - self._warn(f"_refresh_phi_for_key error: {e}") + # self._warn(f"_refresh_phi_for_key error: {e}") self._render_phi_none() def _render_phi(self, snap: PhiSnapshot) -> None: if snap is None or snap.phi is None: self._render_phi_none() return + + # Progress bar + label val = max(0, min(100, int(round(snap.phi)))) self.phi_label.setText(f"PHI: {val}") parts = [] + # keep useful metrics, but DO NOT show 'src=' anymore if snap.density is not None: parts.append(f"density={snap.density:.2f}") if snap.coverage is not None: @@ -432,15 +566,32 @@ def _render_phi(self, snap: PhiSnapshot) -> None: parts.append(f"trend={snap.trend:+.2f}") if snap.week_start: parts.append(f"week={snap.week_start}") - if snap.source: - parts.append(f"src={snap.source}") - self.phi_details.setText(" | ".join(parts)) + self.phi_details.setText(" | ".join(parts)) # no src here self.phi_bar.setValue(val) self._style_phi_bar(val) + # Circle severity (normalized to 0..1) + sev = snap.severity_avg + try: + sev = float(sev) if sev is not None else 0.0 + except Exception: + sev = 0.0 + sev_norm = sev if sev <= 1.0 else min(sev, 10.0) / 10.0 + self.phi_circle.setSeverity(max(0.0, min(1.0, sev_norm))) + def refresh_phi_current(self) -> None: - """Public slot for the 'Show PHI' button; uses current image key.""" - if 0 <= self._idx < len(self._keys): - self._refresh_phi_for_key(self._keys[self._idx]) - else: + """Called by the 'Show PHI' button; uses current image key safely.""" + try: + if 0 <= self._idx < len(self._keys): + key = self._keys[self._idx] + if not isinstance(key, str) or not key.strip(): + self._render_phi_none() + # self._warn("No valid image key selected.") + return + self._refresh_phi_for_key(key) + else: + self._render_phi_none() + # self._warn("No image selected yet. Click 'Reload list' or 'Next'.") + except Exception as e: self._render_phi_none() + self._warn(f"Show PHI failed: {e}") diff --git a/GUI/src/vast/views/irrigation/__init__.py b/GUI/src/vast/views/irrigation/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/GUI/src/vast/views/irrigation/dashboard_bar.py b/GUI/src/vast/views/irrigation/dashboard_bar.py new file mode 100644 index 000000000..9c27077f4 --- /dev/null +++ b/GUI/src/vast/views/irrigation/dashboard_bar.py @@ -0,0 +1,127 @@ +from PyQt6.QtWidgets import QWidget, QHBoxLayout, QLabel, QVBoxLayout, QFrame +from PyQt6.QtCore import Qt +from PyQt6.QtGui import QFont +from datetime import datetime + +class DashboardBar(QWidget): + def __init__(self, parent=None): + super().__init__(parent) + + # Clean minimalistic style: no background, only bottom border + self.setStyleSheet(""" + QWidget { + background: transparent; + border-bottom: 1px solid #e5e7eb; + } + QLabel.title { + color: #6b7280; + font-size: 10pt; + font-weight: 500; + } + QLabel.value { + color: #111827; + font-size: 18pt; + font-weight: 600; + } + """) + + layout = QHBoxLayout(self) + layout.setContentsMargins(20, 16, 20, 16) + layout.setSpacing(32) + + # Helper: metric block + def metric(title_text, value_text, big=True): + container = QWidget() + v = QVBoxLayout(container) + v.setContentsMargins(0, 0, 0, 0) + v.setSpacing(2) + + title = QLabel(title_text) + title.setProperty("class", "title") + + value = QLabel(value_text) + value.setProperty("class", "value" if big else "title") + + v.addWidget(title) + v.addWidget(value) + return container, value + + # Metric 1 + block, self.active_value = metric("Active Sprinklers", "0") + layout.addWidget(block) + + layout.addWidget(self._separator()) + + # Metric 2 + block, self.area_value = metric("Irrigated Area", "0%") + layout.addWidget(block) + + layout.addWidget(self._separator()) + + # Metric 3 + block, self.time_value = metric("Last Update", "--", big=False) + layout.addWidget(block) + + layout.addStretch() + + # Status container (clean version) + self.status_container = QWidget() + s = QHBoxLayout(self.status_container) + s.setContentsMargins(0, 0, 0, 0) + s.setSpacing(6) + + self.status_indicator = QLabel("●") + self.status_indicator.setStyleSheet("color: #dc2626; font-size: 12px;") + + self.status_text = QLabel("Disconnected") + self.status_text.setFont(QFont('Segoe UI', 10)) + self.status_text.setStyleSheet("color: #dc2626; font-weight: 600;") + + s.addWidget(self.status_indicator) + s.addWidget(self.status_text) + layout.addWidget(self.status_container) + + def _separator(self): + sep = QFrame() + sep.setFrameShape(QFrame.Shape.VLine) + sep.setStyleSheet("color: #e5e7eb;") + sep.setFixedWidth(1) + return sep + + def update_status(self, active_count, area_percent, last_update, healthy): + self.active_value.setText(str(active_count)) + self.area_value.setText(f"{area_percent:.1f}%") + + if last_update: + try: + if isinstance(last_update, str): + last_dt = datetime.fromisoformat(last_update.replace('Z', '+00:00')) + else: + last_dt = last_update + + now = datetime.now(last_dt.tzinfo) if last_dt.tzinfo else datetime.now() + delta = now - last_dt + seconds = int(delta.total_seconds()) + + if seconds < 60: + t = f"{seconds}s ago" + elif seconds < 3600: + t = f"{seconds // 60}m ago" + else: + t = f"{seconds // 3600}h ago" + + self.time_value.setText(t) + except: + self.time_value.setText("--") + else: + self.time_value.setText("--") + + # Status indicator styling + if healthy: + self.status_indicator.setStyleSheet("color: #16a34a; font-size: 12px;") + self.status_text.setText("Connected") + self.status_text.setStyleSheet("color: #16a34a; font-weight: 600;") + else: + self.status_indicator.setStyleSheet("color: #dc2626; font-size: 12px;") + self.status_text.setText("Disconnected") + self.status_text.setStyleSheet("color: #dc2626; font-weight: 600;") diff --git a/GUI/src/vast/views/irrigation/history_panel.py b/GUI/src/vast/views/irrigation/history_panel.py new file mode 100644 index 000000000..e5556a911 --- /dev/null +++ b/GUI/src/vast/views/irrigation/history_panel.py @@ -0,0 +1,34 @@ +from PyQt6.QtWidgets import QWidget, QVBoxLayout, QTableWidget, QTableWidgetItem, QLabel, QHeaderView +from PyQt6.QtCore import Qt + +class HistoryPanel(QWidget): + def __init__(self, parent=None): + super().__init__(parent) + self.setWindowFlags(Qt.WindowType.Widget) + self.setFixedWidth(400) + layout = QVBoxLayout(self) + self.title = QLabel("Sprinkler History") + self.title.setAlignment(Qt.AlignmentFlag.AlignCenter) + layout.addWidget(self.title) + self.table = QTableWidget(0, 6) + self.table.setHorizontalHeaderLabels(['Timestamp','Device','Decision','Confidence','Dry Ratio','Image']) + # self.table.horizontalHeader().setSectionResizeMode(QTableWidget.ResizeMode.Stretch) + self.table.horizontalHeader().setSectionResizeMode(QHeaderView.ResizeMode.Stretch) + self.table.setAlternatingRowColors(True) + self.table.setStyleSheet('alternate-background-color: #f9fafb; background: white;') + self.table.verticalHeader().hide() + self.table.setSelectionBehavior(QTableWidget.SelectionBehavior.SelectRows) + layout.addWidget(self.table) + + def show_history(self, records): + self.table.setRowCount(0) + for row in records: + r = self.table.rowCount() + self.table.insertRow(r) + self.table.setItem(r,0, QTableWidgetItem(str(row['ts']))) + self.table.setItem(r,1, QTableWidgetItem(row['device_id'])) + dec_item = QTableWidgetItem(row['decision']) + self.table.setItem(r,2, dec_item) + self.table.setItem(r,3, QTableWidgetItem(f"{row['confidence']:.2f}")) + self.table.setItem(r,4, QTableWidgetItem(f"{row['dry_ratio']:.2f}")) + self.table.setItem(r,5, QTableWidgetItem("View Image")) diff --git a/GUI/src/vast/views/irrigation/irrigation_dashboard.py b/GUI/src/vast/views/irrigation/irrigation_dashboard.py new file mode 100644 index 000000000..7b59b1c9c --- /dev/null +++ b/GUI/src/vast/views/irrigation/irrigation_dashboard.py @@ -0,0 +1,969 @@ +# from pathlib import Path +# import sys, random + +# # Add current directory to path to allow direct execution +# script_dir = Path(__file__).parent +# sys.path.insert(0, str(script_dir)) + +# from PyQt6.QtWidgets import ( +# QApplication, QWidget, QVBoxLayout, QDialog, QFormLayout, QScrollArea, +# QComboBox, QLineEdit, QHBoxLayout, QPushButton, QTableWidget, QTableWidgetItem, +# QHeaderView, QProgressBar, QDialogButtonBox, QGraphicsDropShadowEffect, QLabel +# ) +# from map_widget import MapWidget +# from history_panel import HistoryPanel +# # from .sprinkler_details_dialog import SprinklerDetailsDialog +# from sprinkler_details_dialog_new import SprinklerDetailsDialogNew +# from dashboard_bar import DashboardBar +# from PyQt6.QtGui import QPixmap, QMovie, QFont, QColor, QIcon +# from PyQt6.QtCore import Qt, QTimer, QSize, QPropertyAnimation, QRect, QEasingCurve + +# import psycopg2 +# from psycopg2.extras import RealDictCursor + +# # ----------------------- DB helpers (unchanged) ----------------------- +# def get_db_connection(): +# return psycopg2.connect( +# # host="postgres", +# host = "localhost", +# port=5432, +# user="missions_user", +# password="pg123", +# dbname="missions_db", +# cursor_factory=RealDictCursor +# ) + +# # NOTE: original fetch functions retained (they must exist and behave the same) +# # For brevity we keep their original implementations from the provided file. + +# def fetch_sprinkler_history(limit=500): +# query = f""" +# SELECT e.device_id, e.dry_ratio, e.decision, e.confidence, e.patch_count, e.extra, +# p.prev_state, e.ts +# FROM soil_moisture_events e +# LEFT JOIN irrigation_policies p ON e.device_id = p.device_id +# ORDER BY e.ts DESC +# LIMIT {limit} +# """ +# with get_db_connection() as conn: +# with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur: +# cur.execute(query) +# rows = cur.fetchall() + +# for row in rows: +# prev_state = row.get('prev_state') or 'stop' +# decision = row['decision'] +# if decision == "noop": +# new_state = prev_state +# elif decision in ("run", "stop"): +# new_state = decision +# else: +# new_state = "stop" +# row['prev_state'] = prev_state +# row['new_state'] = new_state + +# return rows + + +# def fetch_sprinkler_data(): +# query = """ +# SELECT e.device_id, e.dry_ratio, e.decision, e.confidence, e.patch_count, e.extra, +# e.ts, p.prev_state +# FROM soil_moisture_events e +# LEFT JOIN irrigation_policies p ON e.device_id = p.device_id +# WHERE e.ts = ( +# SELECT MAX(ts) +# FROM soil_moisture_events e2 +# WHERE e2.device_id = e.device_id +# ) +# ORDER BY e.device_id +# """ + +# with get_db_connection() as conn: +# with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur: +# cur.execute(query) +# rows = cur.fetchall() + +# for row in rows: +# prev_state = row.get('prev_state') or 'stop' +# decision = row['decision'] +# if decision == "noop": +# new_state = prev_state +# elif decision in ("run", "stop"): +# new_state = decision +# else: +# new_state = "stop" +# row['prev_state'] = prev_state +# row['new_state'] = new_state + +# return rows + + +# # ----------------------- UI Components ----------------------- +# class ImageModal(QDialog): +# """Modal to show image with dark overlay and details""" +# def __init__(self, parent, pixmap: QPixmap, details: dict): +# super().__init__(parent) +# self.setModal(True) +# self.setWindowFlag(Qt.WindowType.FramelessWindowHint) +# self.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground) + +# self.main = QWidget(self) +# self.main.setStyleSheet("background: white; border-radius: 12px;") +# layout = QVBoxLayout(self.main) +# self.main.setLayout(layout) + +# img_label = QLabel() +# max_w = int(parent.width() * 0.8) +# max_h = int(parent.height() * 0.8) +# img_label.setPixmap(pixmap.scaled(max_w, max_h, Qt.AspectRatioMode.KeepAspectRatio, Qt.TransformationMode.SmoothTransformation)) +# img_label.setAlignment(Qt.AlignmentFlag.AlignCenter) +# layout.addWidget(img_label) + +# info = QLabel(f"Timestamp: {details.get('ts')} — Decision: {details.get('decision')} — Confidence: {details.get('confidence'):.2f}") +# layout.addWidget(info) + +# btns = QDialogButtonBox(QDialogButtonBox.StandardButton.Close) +# btns.rejected.connect(self.close) +# layout.addWidget(btns) + +# # position central +# w, h = int(parent.width()*0.85), int(parent.height()*0.85) +# self.setGeometry((parent.width()-w)//2, (parent.height()-h)//2, w, h) +# self.main.setGeometry(0, 0, w, h) + +# class FloatingDetailsCard(QWidget): +# """Floating centered card (replaces drawer)""" +# def __init__(self, parent, device_id, details): +# super().__init__(parent) +# self.device_id = device_id +# self.details = details +# self.setWindowFlags(Qt.WindowType.FramelessWindowHint) +# self.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground) + +# self.card = QWidget(self) +# self.card.setStyleSheet(""" +# background: white; +# border-radius: 14px; +# """) + +# shadow = QGraphicsDropShadowEffect(self.card) +# shadow.setBlurRadius(30) +# shadow.setOffset(0, 8) +# shadow.setColor(QColor(0,0,0,100)) +# self.card.setGraphicsEffect(shadow) + +# # layout +# l = QVBoxLayout(self.card) +# l.setContentsMargins(20, 20, 20, 20) +# # title with gradient-like color +# title = QLabel(f"Sprinkler {device_id}") +# title.setFont(QFont('Segoe UI', 14, QFont.Weight.Bold)) +# title.setStyleSheet("color: qlineargradient(x1:0, y1:0, x2:1, y2:0, stop:0 #06b6d4, stop:1 #0891b2);") +# l.addWidget(title) + +# # status row +# status_row = QHBoxLayout() +# status_dot = QLabel('●') +# status_dot.setFont(QFont('Arial', 16)) +# status_color = '#10b981' if details.get('active') else '#6b7280' +# status_dot.setStyleSheet(f"color: {status_color}") +# status_row.addWidget(status_dot) +# status_row.addWidget(QLabel('Active' if details.get('active') else 'Inactive')) +# status_row.addStretch() +# l.addLayout(status_row) + +# # dry ratio progress +# dry_label = QLabel('💧 Dry Ratio') +# l.addWidget(dry_label) +# pb = QProgressBar() +# pb.setRange(0, 100) +# pb.setValue(int(details.get('dry_ratio',0)*100)) +# pb.setTextVisible(True) +# pb.setFormat('%.0f%%' % (pb.value(),)) +# pb.setFixedHeight(18) +# pb.setStyleSheet("border-radius:9px;") +# l.addWidget(pb) + +# # confidence with color +# conf = details.get('confidence',0) +# conf_label = QLabel(f'🎯 Confidence: {conf:.2f}') +# if conf >= 0.75: +# conf_color = '#10b981' +# elif conf >= 0.4: +# conf_color = '#f59e0b' +# else: +# conf_color = '#ef4444' +# conf_label.setStyleSheet(f'color: {conf_color}; font-weight: bold') +# l.addWidget(conf_label) + +# # decision +# decision_label = QLabel(f'⚙️ Decision: {details.get("decision")}') +# l.addWidget(decision_label) + +# # button row (bottom) +# btn_row = QHBoxLayout() +# btn_row.setSpacing(16) +# btn_row.addStretch() +# # Show History button +# self.show_history_btn = QPushButton('Show History') +# self.show_history_btn.setStyleSheet('background:#06b6d4; color:white; padding:8px; border-radius:8px') +# btn_row.addWidget(self.show_history_btn) +# # Close button +# self.close_btn = QPushButton('Close') +# self.close_btn.clicked.connect(self.close_card) +# self.close_btn.setFixedWidth(120) +# self.close_btn.setStyleSheet('background:#3b82f6; color:white; padding:8px; border-radius:10px') +# btn_row.addWidget(self.close_btn) +# l.addLayout(btn_row) + +# # size and position +# w, h = int(parent.width()*0.6), int(parent.height()*0.5) +# self.setGeometry((parent.width()-w)//2, (parent.height()-h)//2, w, h) +# self.card.setGeometry(0,0,w,h) + +# # fade-in animation +# self.opacity_anim = QPropertyAnimation(self, b"windowOpacity") +# self.opacity_anim.setDuration(220) +# self.opacity_anim.setStartValue(0.0) +# self.opacity_anim.setEndValue(1.0) +# self.setWindowOpacity(0.0) +# self.opacity_anim.start() + +# def close_card(self): +# self.close() + +# class IrrigationDashboard(QWidget): +# def __init__(self): +# super().__init__() +# print("[DEBUG] IrrigationDashboard.__init__ called") +# self.setWindowTitle("Irrigation Dashboard 🌾") +# self.setGeometry(100, 100, 1100, 820) +# QApplication.setFont(QFont('Roboto', 10)) +# main = QVBoxLayout(self) +# main.setContentsMargins(0,0,0,0) +# self.setStyleSheet(""" +# QWidget#root { background: qlineargradient(x1:0,y1:0,x2:0,y2:1, stop:0 #f0f9ff, stop:1 #e0f2fe); } +# QLabel.title { font-family: 'Segoe UI'; font-weight: bold; font-size: 18px; color: #111827 } +# """) +# self.setObjectName('root') + +# # MapWidget replaces map logic +# print("[DEBUG] Creating DashboardBar...") +# self.dashboard_bar = DashboardBar(self) +# main.addWidget(self.dashboard_bar) +# print("[DEBUG] Creating MapWidget...") +# self.map_widget = MapWidget(self, map_path=str(script_dir / "map_field.jpg")) +# self.sprinklers = {} # device_id -> info, for non-map logic (details, etc.) +# # print("[DEBUG] Creating HistoryPanel...") +# # self.history_panel = HistoryPanel(self) +# # self.history_panel.hide() + +# # Create map layout with minimal margins to push sprinklers down +# map_container = QWidget() +# map_layout = QVBoxLayout(map_container) +# map_layout.setContentsMargins(0, 10, 0, 0) # Minimal top margin (10px instead of default) +# map_layout.setSpacing(0) +# map_layout.addWidget(self.map_widget) + +# main.addWidget(map_container, stretch=3) +# # main.addWidget(self.history_panel, stretch=1) + +# # timer for data refresh +# print("[DEBUG] Setting up timer...") +# self.timer = QTimer() +# self.timer.timeout.connect(self.safe_update_data) +# # Delay first update to avoid issues during init +# self.timer.singleShot(1000, self.safe_update_data) +# self.timer.start(3000) +# print("[DEBUG] IrrigationDashboard.__init__ completed") + +# def resizeEvent(self, event): +# super().resizeEvent(event) +# # Delegate map resizing to MapWidget +# if hasattr(self, 'map_widget') and self.map_widget: +# self.map_widget.resizeEvent(event) + +# def set_sprinkler_state(self, s, active): +# btn: QPushButton = s['widget'] +# # create / reuse label for movie +# if 'label' not in s: +# lbl = QLabel(btn) +# lbl.setAlignment(Qt.AlignmentFlag.AlignCenter) +# lbl.setGeometry(0,0,btn.width(),btn.height()) +# lbl.raise_() # Raise label above button to display image +# s['label'] = lbl +# lbl = s['label'] + +# if active: +# movie = QMovie(str(script_dir / 'sprinkler_on.gif')) +# movie.setScaledSize(QSize(btn.width(), btn.height())) +# lbl.setMovie(movie) +# movie.start() +# lbl.raise_() # Ensure label stays on top +# lbl.show() +# btn.setStyleSheet(self.sprinkler_style(active=True)) +# s['movie'] = movie +# else: +# # static image +# pix = QPixmap(str(script_dir / 'sprinkler_off.png')) if (script_dir / 'sprinkler_off.png').exists() else QPixmap(btn.width(), btn.height()) +# if pix.isNull(): +# pix = QPixmap(btn.width(), btn.height()); pix.fill(QColor('#6b7280')) +# lbl.setPixmap(pix.scaled(btn.size(), Qt.AspectRatioMode.KeepAspectRatio, Qt.TransformationMode.SmoothTransformation)) +# lbl.raise_() # Ensure label stays on top +# lbl.show() +# btn.setStyleSheet(self.sprinkler_style(active=False)) +# s['movie'] = None +# s['active'] = active + +# def sprinkler_style(self, active=False): +# # circular button with colored background (not transparent) +# base = f""" +# QPushButton {{ +# width: 56px; height:56px; border-radius:28px; + +# font-weight: bold; +# color: white; +# }} +# QPushButton:hover {{ }} +# """ +# return base + +# def update_history(self): +# # Populate filters (preserve current selection) and refresh table +# rows = fetch_sprinkler_history() +# prev_dev = self.filter_device.currentText() if self.filter_device.count()>0 else 'All' +# prev_dec = self.filter_decision.currentText() if self.filter_decision.count()>0 else 'All' + +# unique_devices = sorted({row['device_id'] for row in rows}) +# unique_decisions = sorted({row['decision'] for row in rows}) + +# # repopulate while preserving selection when possible +# self.filter_device.blockSignals(True) +# self.filter_decision.blockSignals(True) +# self.filter_device.clear(); self.filter_device.addItem('All'); self.filter_device.addItems(unique_devices) +# self.filter_decision.clear(); self.filter_decision.addItem('All'); self.filter_decision.addItems(unique_decisions) +# idx = self.filter_device.findText(prev_dev) +# if idx >= 0: +# self.filter_device.setCurrentIndex(idx) +# idx = self.filter_decision.findText(prev_dec) +# if idx >= 0: +# self.filter_decision.setCurrentIndex(idx) +# self.filter_device.blockSignals(False) +# self.filter_decision.blockSignals(False) + +# # apply currently selected filters to populate the table +# self.apply_filters() + +# def apply_filters(self): +# # fetch and filter rows locally +# rows = fetch_sprinkler_history() +# dev = self.filter_device.currentText() +# dec = self.filter_decision.currentText() +# if dev and dev != 'All': +# rows = [r for r in rows if r.get('device_id') == dev] +# if dec and dec != 'All': +# rows = [r for r in rows if r.get('decision') == dec] + +# # date filter +# try: +# dfrom = self.filter_date_from.date().toPyDate() +# dto = self.filter_date_to.date().toPyDate() +# # only apply if user set meaningful range (non-default) +# if dfrom and dto and dfrom <= dto: +# rows = [r for r in rows if r.get('ts') and dfrom <= r['ts'].date() <= dto] +# except Exception: +# pass + +# # numeric filters +# try: +# drymin = float(self.filter_dry_min.text()) if self.filter_dry_min.text() else None +# confmin = float(self.filter_conf_min.text()) if self.filter_conf_min.text() else None +# if drymin is not None: +# rows = [r for r in rows if r.get('dry_ratio', 0) >= drymin] +# if confmin is not None: +# rows = [r for r in rows if r.get('confidence', 0) >= confmin] +# except Exception: +# pass + +# self.populate_history_table(rows) + +# def populate_history_table(self, rows): +# self.history_table.setRowCount(0) +# for row in rows: +# r = self.history_table.rowCount() +# self.history_table.insertRow(r) +# self.history_table.setItem(r,0, QTableWidgetItem(str(row['ts']))) +# self.history_table.setItem(r,1, QTableWidgetItem(row['device_id'])) +# dec_item = QTableWidgetItem(row['decision']) +# if row['decision']=='run': dec_item.setBackground(QColor('#10b981')) +# elif row['decision']=='stop': dec_item.setBackground(QColor('#ef4444')) +# else: dec_item.setBackground(QColor('#f59e0b')) +# self.history_table.setItem(r,2, dec_item) +# self.history_table.setItem(r,3, QTableWidgetItem(f"{row['confidence']:.2f}")) +# self.history_table.setItem(r,4, QTableWidgetItem(f"{row['dry_ratio']:.2f}")) +# view_btn = QPushButton('View Image') +# view_btn.clicked.connect(lambda _checked, rr=row: self.show_image_modal(rr)) +# self.history_table.setCellWidget(r,5, view_btn) + +# def show_image_modal(self, row): +# # for demo: try to load an image from disk or show placeholder +# img_path = script_dir / 'sprinkler_image_placeholder.jpg' +# if img_path.exists(): +# pix = QPixmap(str(img_path)) +# else: +# pix = QPixmap(400,300) +# pix.fill(QColor('#ddd')) +# m = ImageModal(self, pix, row) +# m.exec() + +# def update_data(self): +# try: +# rows = fetch_sprinkler_data() +# healthy = True +# except Exception as e: +# print('Error fetching data:', e) +# import traceback +# traceback.print_exc() +# rows = [] +# healthy = False + +# # Update sprinklers on map +# active_count = 0 +# irrigated_area = 0.0 +# last_update = '--' +# max_timestamp = None +# for i, row in enumerate(rows): +# device_id = row['device_id'] +# dry_ratio = row['dry_ratio'] +# decision = row['decision'] +# confidence = row['confidence'] +# new_state = row['new_state'] +# active = new_state == 'run' +# if active: +# active_count += 1 +# irrigated_area += dry_ratio if active else 0 + +# # Track the most recent timestamp across all sprinklers +# ts = row.get('ts') +# if ts and (max_timestamp is None or ts > max_timestamp): +# max_timestamp = ts + +# # MapWidget handles display and GIF/image ONLY (no shapes) +# if device_id not in self.map_widget.sprinklers: +# rel_x = (100 + i*120 + random.randint(-20, 20)) / max(1, self.map_widget.map_pixmap.width()) +# rel_y = (300 + random.randint(-100, 100)) / max(1, self.map_widget.map_pixmap.height()) +# rel_size = 0.025 +# btn = self.map_widget.add_sprinkler(device_id, rel_x, rel_y, rel_size, active, name=device_id) +# try: +# btn.clicked.connect(lambda _e, d=device_id: self.show_details(d)) +# except Exception as e: +# print(f"[ERROR] Failed to connect clicked signal for {device_id}: {e}") + +# s = self.map_widget.sprinklers[device_id] +# # ALWAYS set sprinkler state on every update - ensures images/GIFs shown for new sprinklers added after startup +# self.set_sprinkler_state(s, active) +# s.update({'dry_ratio': dry_ratio, 'decision': decision, 'confidence': confidence}) +# # Update main window's sprinkler info for details dialog +# self.sprinklers[device_id] = s + +# # Set last_update to the most recent timestamp +# if max_timestamp: +# last_update = str(max_timestamp) + +# total_area = len(rows) +# irrigated_percent = (irrigated_area / total_area * 100) if total_area else 0.0 +# self.dashboard_bar.update_status(active_count, irrigated_percent, last_update, healthy) + +# def safe_update_data(self): +# """Safe wrapper for update_data that catches exceptions""" +# try: +# self.update_data() +# except Exception as e: +# print(f"[ERROR] safe_update_data failed: {e}") +# import traceback +# traceback.print_exc() + +# def show_details(self, device_id): +# print(f"[DEBUG] show_details() called for device_id={device_id}") +# if device_id not in self.sprinklers: +# print(f"[DEBUG] Device {device_id} not found in sprinklers dict") +# return +# # Close previous details dialog if open +# if hasattr(self, '_details_card') and self._details_card: +# print(f"[DEBUG] Closing previous details card") +# self._details_card.close() +# s = self.sprinklers[device_id] +# details = { +# 'active': s.get('active', False), +# 'dry_ratio': s.get('dry_ratio', 0), +# 'confidence': s.get('confidence', 0), +# 'decision': s.get('decision', 'noop') +# } +# print(f"[DEBUG] Creating new SprinklerDetailsDialogNew with details: {details}") +# # Use new tabbed dialog +# card = SprinklerDetailsDialogNew(self, device_id, details) +# card.history_requested.connect(lambda d: self.show_history_panel(d)) +# self._details_card = card +# print(f"[DEBUG] Calling card.show()") +# card.show() +# print(f"[DEBUG] Dialog shown") + +# def show_history_panel(self, device_id): +# # Close previous details dialog if open +# if hasattr(self, '_details_card') and self._details_card: +# self._details_card.close() +# # Fetch last 10 records for this sprinkler +# all_history = fetch_sprinkler_history(limit=100) +# records = [r for r in all_history if r['device_id'] == device_id][:10] +# self.history_panel.show_history(records) +# self.history_panel.show() +# self.map_widget.setFixedWidth(int(self.width() * 0.6)) +# # Add close button to history panel +# if not hasattr(self.history_panel, 'close_btn'): +# from PyQt6.QtWidgets import QPushButton +# close_btn = QPushButton('Close History') +# close_btn.setStyleSheet('background:#ef4444; color:white; padding:6px; border-radius:8px') +# close_btn.clicked.connect(self.hide_history_panel) +# layout = self.history_panel.layout() +# layout.addWidget(close_btn) +# self.history_panel.close_btn = close_btn + +# def hide_history_panel(self): +# self.history_panel.hide() +# self.map_widget.setFixedWidth(self.width()) +# # Ensure details dialog can be reopened after closing history +# self._details_card = None + +# def on_history_clicked(self, row, col): +# # show full details card when any non-button cell is clicked +# try: +# device = self.history_table.item(row,1).text() +# if device: +# self.show_details(device) +# except Exception: +# pass + +# if __name__ == '__main__': +# app = QApplication(sys.argv) +# window = IrrigationDashboard() +# window.show() +# sys.exit(app.exec()) + + +from pathlib import Path +import sys, random +from PyQt6.QtWidgets import ( + QApplication, QWidget, QVBoxLayout, QDialog, QFormLayout, QScrollArea, + QComboBox, QLineEdit, QHBoxLayout, QPushButton, QTableWidget, QTableWidgetItem, + QHeaderView, QProgressBar, QDialogButtonBox, QGraphicsDropShadowEffect, QLabel +) +from .map_widget import MapWidget +from .history_panel import HistoryPanel +from .sprinkler_details_dialog_new import SprinklerDetailsDialogNew +from .dashboard_bar import DashboardBar +from PyQt6.QtGui import QPixmap, QMovie, QFont, QColor, QIcon +from PyQt6.QtCore import Qt, QTimer, QSize, QPropertyAnimation, QRect, QEasingCurve + +import psycopg2 +from psycopg2.extras import RealDictCursor + +# ----------------------- DB helpers (unchanged) ----------------------- +def get_db_connection(): + return psycopg2.connect( + host="postgres", + port=5432, + user="missions_user", + password="pg123", + dbname="missions_db", + cursor_factory=RealDictCursor + ) + +# NOTE: original fetch functions retained (they must exist and behave the same) +# For brevity we keep their original implementations from the provided file. + +def fetch_sprinkler_history(limit=500): + query = f""" + SELECT e.device_id, e.dry_ratio, e.decision, e.confidence, e.patch_count, e.extra, + p.prev_state, e.ts + FROM soil_moisture_events e + LEFT JOIN irrigation_policies p ON e.device_id = p.device_id + ORDER BY e.ts DESC + LIMIT {limit} + """ + with get_db_connection() as conn: + with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur: + cur.execute(query) + rows = cur.fetchall() + + for row in rows: + prev_state = row.get('prev_state') or 'stop' + decision = row['decision'] + if decision == "noop": + new_state = prev_state + elif decision in ("run", "stop"): + new_state = decision + else: + new_state = "stop" + row['prev_state'] = prev_state + row['new_state'] = new_state + + return rows + + +def fetch_sprinkler_data(): + query = """ + SELECT e.device_id, e.dry_ratio, e.decision, e.confidence, e.patch_count, e.extra, + e.ts, p.prev_state + FROM soil_moisture_events e + LEFT JOIN irrigation_policies p ON e.device_id = p.device_id + WHERE e.ts = ( + SELECT MAX(ts) + FROM soil_moisture_events e2 + WHERE e2.device_id = e.device_id + ) + ORDER BY e.device_id + """ + + with get_db_connection() as conn: + with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur: + cur.execute(query) + rows = cur.fetchall() + + for row in rows: + prev_state = row.get('prev_state') or 'stop' + decision = row['decision'] + if decision == "noop": + new_state = prev_state + elif decision in ("run", "stop"): + new_state = decision + else: + new_state = "stop" + row['prev_state'] = prev_state + row['new_state'] = new_state + + return rows + + +script_dir = Path(__file__).parent + +# # ----------------------- UI Components ----------------------- +# class ImageModal(QDialog): +# """Modal to show image with dark overlay and details""" +# def __init__(self, parent, pixmap: QPixmap, details: dict): +# super().__init__(parent) +# self.setModal(True) +# self.setWindowFlag(Qt.WindowType.FramelessWindowHint) +# self.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground) + +# self.main = QWidget(self) +# self.main.setStyleSheet("background: white; border-radius: 12px;") +# layout = QVBoxLayout(self.main) +# self.main.setLayout(layout) + +# img_label = QLabel() +# max_w = int(parent.width() * 0.8) +# max_h = int(parent.height() * 0.8) +# img_label.setPixmap(pixmap.scaled(max_w, max_h, Qt.AspectRatioMode.KeepAspectRatio, Qt.TransformationMode.SmoothTransformation)) +# img_label.setAlignment(Qt.AlignmentFlag.AlignCenter) +# layout.addWidget(img_label) + +# info = QLabel(f"Timestamp: {details.get('ts')} — Decision: {details.get('decision')} — Confidence: {details.get('confidence'):.2f}") +# layout.addWidget(info) + +# btns = QDialogButtonBox(QDialogButtonBox.StandardButton.Close) +# btns.rejected.connect(self.close) +# layout.addWidget(btns) + +# # position central +# w, h = int(parent.width()*0.85), int(parent.height()*0.85) +# self.setGeometry((parent.width()-w)//2, (parent.height()-h)//2, w, h) +# self.main.setGeometry(0, 0, w, h) + +class IrrigationDashboard(QWidget): + def __init__(self): + super().__init__() + self.setWindowTitle("Irrigation Dashboard 🌾") + self.setGeometry(100, 100, 1100, 820) + QApplication.setFont(QFont('Roboto', 10)) + main = QVBoxLayout(self) + main.setContentsMargins(0,0,0,0) + self.setStyleSheet(""" + QWidget#root { background: qlineargradient(x1:0,y1:0,x2:0,y2:1, stop:0 #f0f9ff, stop:1 #e0f2fe); } + QLabel.title { font-family: 'Segoe UI'; font-weight: bold; font-size: 18px; color: #111827 } + """) + self.setObjectName('root') + + # MapWidget replaces map logic + self.dashboard_bar = DashboardBar(self) + main.addWidget(self.dashboard_bar) + self.map_widget = MapWidget(self, map_path=str(script_dir / "map_field.jpg")) + self.sprinklers = {} # device_id -> info, for non-map logic (details, etc.) + self.history_panel = HistoryPanel(self) + self.history_panel.hide() + + # Create map layout with minimal margins to push sprinklers down + map_container = QWidget() + map_layout = QVBoxLayout(map_container) + map_layout.setContentsMargins(0, 10, 0, 0) # Minimal top margin (10px instead of default) + map_layout.setSpacing(0) + map_layout.addWidget(self.map_widget) + + main.addWidget(map_container, stretch=3) + main.addWidget(self.history_panel, stretch=1) + + # timer for data refresh + self.timer = QTimer() + self.timer.timeout.connect(self.update_data) + self.timer.start(3000) + self.update_data() + + def resizeEvent(self, event): + super().resizeEvent(event) + # Delegate map resizing to MapWidget + if hasattr(self, 'map_widget') and self.map_widget: + self.map_widget.resizeEvent(event) + + def set_sprinkler_state(self, s, active): + #print(f"Setting sprinkler {s['name']} state to {'active' if active else 'inactive'}") + btn: QPushButton = s['widget'] + # create / reuse label for movie + if 'label' not in s: + lbl = QLabel(btn) + lbl.setAlignment(Qt.AlignmentFlag.AlignCenter) + lbl.setGeometry(0,0,btn.width(),btn.height()) + s['label'] = lbl + lbl = s['label'] + + if active: + movie = QMovie(str(script_dir / 'sprinkler_on.gif')) + movie.setScaledSize(QSize(btn.width(), btn.height())) + lbl.setMovie(movie) + movie.start() + lbl.show() + btn.setStyleSheet(self.sprinkler_style(active=True)) + s['movie'] = movie + else: + # static image + pix = QPixmap(str(script_dir / 'sprinkler_off.png')) if (script_dir / 'sprinkler_off.png').exists() else QPixmap(btn.width(), btn.height()) + if pix.isNull(): + pix = QPixmap(btn.width(), btn.height()); pix.fill(QColor('#6b7280')) + lbl.setPixmap(pix.scaled(btn.size(), Qt.AspectRatioMode.KeepAspectRatio, Qt.TransformationMode.SmoothTransformation)) + lbl.show() + btn.setStyleSheet(self.sprinkler_style(active=False)) + s['movie'] = None + s['active'] = active + + def sprinkler_style(self, active=False): + #background: {"#86c7db26" if active else "#6b72801c"}; + # circular button with shadow and badge placeholder + base = f""" + QPushButton {{ + width: 120px; height:120px; border-radius:28px; + + font-weight: bold; + color: white; + }} + QPushButton:hover {{ }} + """ + return base + + # def update_history(self): + # # Populate filters (preserve current selection) and refresh table + # rows = fetch_sprinkler_history() + # prev_dev = self.filter_device.currentText() if self.filter_device.count()>0 else 'All' + # prev_dec = self.filter_decision.currentText() if self.filter_decision.count()>0 else 'All' + + # unique_devices = sorted({row['device_id'] for row in rows}) + # unique_decisions = sorted({row['decision'] for row in rows}) + + # # repopulate while preserving selection when possible + # self.filter_device.blockSignals(True) + # self.filter_decision.blockSignals(True) + # self.filter_device.clear(); self.filter_device.addItem('All'); self.filter_device.addItems(unique_devices) + # self.filter_decision.clear(); self.filter_decision.addItem('All'); self.filter_decision.addItems(unique_decisions) + # idx = self.filter_device.findText(prev_dev) + # if idx >= 0: + # self.filter_device.setCurrentIndex(idx) + # idx = self.filter_decision.findText(prev_dec) + # if idx >= 0: + # self.filter_decision.setCurrentIndex(idx) + # self.filter_device.blockSignals(False) + # self.filter_decision.blockSignals(False) + + # # apply currently selected filters to populate the table + # self.apply_filters() + + # def apply_filters(self): + # # fetch and filter rows locally + # rows = fetch_sprinkler_history() + # dev = self.filter_device.currentText() + # dec = self.filter_decision.currentText() + # if dev and dev != 'All': + # rows = [r for r in rows if r.get('device_id') == dev] + # if dec and dec != 'All': + # rows = [r for r in rows if r.get('decision') == dec] + + # # date filter + # try: + # dfrom = self.filter_date_from.date().toPyDate() + # dto = self.filter_date_to.date().toPyDate() + # # only apply if user set meaningful range (non-default) + # if dfrom and dto and dfrom <= dto: + # rows = [r for r in rows if r.get('ts') and dfrom <= r['ts'].date() <= dto] + # except Exception: + # pass + + # # numeric filters + # try: + # drymin = float(self.filter_dry_min.text()) if self.filter_dry_min.text() else None + # confmin = float(self.filter_conf_min.text()) if self.filter_conf_min.text() else None + # if drymin is not None: + # rows = [r for r in rows if r.get('dry_ratio', 0) >= drymin] + # if confmin is not None: + # rows = [r for r in rows if r.get('confidence', 0) >= confmin] + # except Exception: + # pass + + # self.populate_history_table(rows) + + # def populate_history_table(self, rows): + # self.history_table.setRowCount(0) + # for row in rows: + # r = self.history_table.rowCount() + # self.history_table.insertRow(r) + # self.history_table.setItem(r,0, QTableWidgetItem(str(row['ts']))) + # self.history_table.setItem(r,1, QTableWidgetItem(row['device_id'])) + # dec_item = QTableWidgetItem(row['decision']) + # if row['decision']=='run': dec_item.setBackground(QColor('#10b981')) + # elif row['decision']=='stop': dec_item.setBackground(QColor('#ef4444')) + # else: dec_item.setBackground(QColor('#f59e0b')) + # self.history_table.setItem(r,2, dec_item) + # self.history_table.setItem(r,3, QTableWidgetItem(f"{row['confidence']:.2f}")) + # self.history_table.setItem(r,4, QTableWidgetItem(f"{row['dry_ratio']:.2f}")) + # view_btn = QPushButton('View Image') + # view_btn.clicked.connect(lambda _checked, rr=row: self.show_image_modal(rr)) + # self.history_table.setCellWidget(r,5, view_btn) + + # def show_image_modal(self, row): + # # for demo: try to load an image from disk or show placeholder + # img_path = script_dir / 'sprinkler_image_placeholder.jpg' + # if img_path.exists(): + # pix = QPixmap(str(img_path)) + # else: + # pix = QPixmap(400,300) + # pix.fill(QColor('#ddd')) + # m = ImageModal(self, pix, row) + # m.exec() + + def update_data(self): + try: + rows = fetch_sprinkler_data() + healthy = True + except Exception as e: + print('Error fetching data:', e) + rows = [] + healthy = False + + # Update sprinklers on map + active_count = 0 + irrigated_area = 0.0 + last_update = '--' + max_timestamp = None + for i, row in enumerate(rows): + device_id = row['device_id'] + dry_ratio = row['dry_ratio'] + decision = row['decision'] + confidence = row['confidence'] + new_state = row['new_state'] + active = new_state == 'run' + if active: + active_count += 1 + irrigated_area += dry_ratio if active else 0 + + # Track the most recent timestamp across all sprinklers + ts = row.get('ts') + if ts and (max_timestamp is None or ts > max_timestamp): + max_timestamp = ts + + # MapWidget handles display and GIF/image ONLY (no shapes) + if device_id not in self.map_widget.sprinklers: + rel_x = (100 + i*233 + random.randint(-20, 20)) / max(1, self.map_widget.map_pixmap.width()) + rel_y = (550 + random.randint(-230, 230)) / max(1, self.map_widget.map_pixmap.height()) + rel_size = 0.025 + btn = self.map_widget.add_sprinkler(device_id, rel_x, rel_y, rel_size, active, name=device_id) + btn.clicked.connect(lambda _e, d=device_id: self.show_details(d)) + s = self.map_widget.sprinklers[device_id] + # Always set sprinkler state to ensure image/GIF is shown, never fallback to shapes + self.set_sprinkler_state(s, active) + s.update({'dry_ratio': dry_ratio, 'decision': decision, 'confidence': confidence}) + # Update main window's sprinkler info for details dialog + self.sprinklers[device_id] = s + + # Set last_update to the most recent timestamp + if max_timestamp: + last_update = str(max_timestamp) + + total_area = len(rows) + irrigated_percent = (irrigated_area / total_area * 100) if total_area else 0.0 + self.dashboard_bar.update_status(active_count, irrigated_percent, last_update, healthy) + + def show_details(self, device_id): + if device_id not in self.sprinklers: + return + # Close previous details dialog if open + if hasattr(self, '_details_card') and self._details_card: + self._details_card.close() + s = self.sprinklers[device_id] + details = { + 'active': s.get('active', False), + 'dry_ratio': s.get('dry_ratio', 0), + 'confidence': s.get('confidence', 0), + 'decision': s.get('decision', 'noop') + } + # Use new tabbed dialog + card = SprinklerDetailsDialogNew(self, device_id, details) + card.history_requested.connect(lambda d: self.show_history_panel(d)) + self._details_card = card + card.show() + + # def show_history_panel(self, device_id): + # # Close previous details dialog if open + # if hasattr(self, '_details_card') and self._details_card: + # self._details_card.close() + # # Fetch last 10 records for this sprinkler + # all_history = fetch_sprinkler_history(limit=100) + # records = [r for r in all_history if r['device_id'] == device_id][:10] + # self.history_panel.show_history(records) + # self.history_panel.show() + # self.map_widget.setFixedWidth(int(self.width() * 0.6)) + # # Add close button to history panel + # if not hasattr(self.history_panel, 'close_btn'): + # from PyQt6.QtWidgets import QPushButton + # close_btn = QPushButton('Close History') + # close_btn.setStyleSheet('background:#ef4444; color:white; padding:6px; border-radius:8px') + # close_btn.clicked.connect(self.hide_history_panel) + # layout = self.history_panel.layout() + # layout.addWidget(close_btn) + # self.history_panel.close_btn = close_btn + + # def hide_history_panel(self): + # self.history_panel.hide() + # self.map_widget.setFixedWidth(self.width()) + # # Ensure details dialog can be reopened after closing history + # self._details_card = None + + # def on_history_clicked(self, row, col): + # # show full details card when any non-button cell is clicked + # try: + # device = self.history_table.item(row,1).text() + # if device: + # self.show_details(device) + # except Exception: + # pass + +if __name__ == '__main__': + app = QApplication(sys.argv) + window = IrrigationDashboard() + window.show() + sys.exit(app.exec()) diff --git a/GUI/src/vast/views/irrigation/irrigation_view.py b/GUI/src/vast/views/irrigation/irrigation_view.py new file mode 100644 index 000000000..5eefcf05d --- /dev/null +++ b/GUI/src/vast/views/irrigation/irrigation_view.py @@ -0,0 +1,42 @@ +from PyQt6.QtWidgets import QWidget, QVBoxLayout, QLabel +from PyQt6.QtCore import Qt +from .irrigation_dashboard import IrrigationDashboard +from dashboard_api import DashboardApi + + +class IrrigationView(QWidget): + """Wrapper to integrate IrrigationDashboard into MainWindow""" + + def __init__(self, api: DashboardApi, parent=None): + super().__init__(parent) + print("[DEBUG] IrrigationView.__init__ called") + self.api = api + + print("[DEBUG] Creating layout...") + layout = QVBoxLayout(self) + layout.setContentsMargins(0, 0, 0, 0) + layout.setSpacing(0) + + # Create the irrigation dashboard + print("[DEBUG] Creating IrrigationDashboard...") + try: + self.dashboard = IrrigationDashboard() + print("[DEBUG] IrrigationDashboard created successfully") + print("[DEBUG] Adding dashboard to layout...") + layout.addWidget(self.dashboard) + except Exception as e: + print(f"[ERROR] Failed to create IrrigationDashboard: {e}") + import traceback + traceback.print_exc() + # Create error placeholder + error_label = QLabel(f"Failed to load Irrigation Dashboard:\n{str(e)}") + error_label.setStyleSheet("color: red; padding: 20px;") + layout.addWidget(error_label) + + print("[DEBUG] Setting stylesheet...") + self.setStyleSheet(""" + QWidget { + background: qlineargradient(x1:0,y1:0,x2:0,y2:1, stop:0 #f0f9ff, stop:1 #e0f2fe); + } + """) + print("[DEBUG] IrrigationView.__init__ completed") diff --git a/GUI/src/vast/views/irrigation/map_field.jpg b/GUI/src/vast/views/irrigation/map_field.jpg new file mode 100644 index 000000000..5c528b122 Binary files /dev/null and b/GUI/src/vast/views/irrigation/map_field.jpg differ diff --git a/GUI/src/vast/views/irrigation/map_widget.py b/GUI/src/vast/views/irrigation/map_widget.py new file mode 100644 index 000000000..a93cb2114 --- /dev/null +++ b/GUI/src/vast/views/irrigation/map_widget.py @@ -0,0 +1,104 @@ +from pathlib import Path +from PyQt6.QtWidgets import QWidget, QPushButton, QLabel +from PyQt6.QtGui import QPixmap, QMovie, QColor +from PyQt6.QtCore import Qt, QSize + +script_dir = Path(__file__).parent + +class MapWidget(QWidget): + def __init__(self, parent=None, map_path=None): + super().__init__(parent) + self.sprinklers = {} + self.map_pixmap = QPixmap(map_path) if map_path else QPixmap() + self.map_label = QLabel(self) + self.map_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + self.map_label.setStyleSheet('background: transparent;') + self.map_label.setPixmap(self.map_pixmap) + self.map_aspect = self.map_pixmap.width() / self.map_pixmap.height() if not self.map_pixmap.isNull() else 16/9 + self.last_scaled_pixmap = self.map_pixmap + self.resizeEvent(None) + + def resizeEvent(self, event): + if self.map_pixmap.isNull(): + return + available_w = max(100, self.width() - 40) + scaled_h = int(available_w / self.map_aspect) + scaled_pixmap = self.map_pixmap.scaled(available_w, scaled_h, Qt.AspectRatioMode.KeepAspectRatio, Qt.TransformationMode.SmoothTransformation) + self.last_scaled_pixmap = scaled_pixmap + self.map_label.setPixmap(scaled_pixmap) + self.map_label.setFixedHeight(scaled_pixmap.height()) + self.map_label.setGeometry(0, 0, available_w, scaled_h) + for s in self.sprinklers.values(): + # Increased size: multiplied rel_size by 1.5 and increased minimum from 40 to 60 + new_size = max(int(s['rel_size'] * scaled_pixmap.width() * 1.5), 60) + new_x = int(s['rel_x'] * scaled_pixmap.width() - new_size/2) + new_y = int(s['rel_y'] * scaled_pixmap.height() - new_size/2) + s['widget'].setGeometry(new_x, new_y, new_size, new_size) + if s.get('movie') and isinstance(s['movie'], QMovie): + s['movie'].setScaledSize(QSize(new_size, new_size)) + + def add_sprinkler(self, device_id, rel_x, rel_y, rel_size=0.025, active=False, name=None): + btn = QPushButton('', self) + btn.setObjectName(f'spr_{device_id}') + btn.setToolTip(name or device_id) + btn.setFixedSize(120, 120) + btn.setStyleSheet(self.sprinkler_style(active)) + btn.installEventFilter(self) + self.sprinklers[device_id] = { + 'widget': btn, 'movie': None, 'active': active, + 'rel_x': rel_x, 'rel_y': rel_y, 'rel_size': rel_size, + 'name': name or device_id + } + self.set_sprinkler_state(self.sprinklers[device_id], active) + self.resizeEvent(None) + return btn + + def eventFilter(self, obj, event): + # Show tooltip on hover + if event.type() == event.Type.Enter: + for s in self.sprinklers.values(): + if s['widget'] is obj: + obj.setToolTip(s.get('name', '')) + return super().eventFilter(obj, event) + + def set_sprinkler_state(self, s, active): + btn = s['widget'] + if 'label' not in s: + lbl = QLabel(btn) + lbl.setAlignment(Qt.AlignmentFlag.AlignCenter) + lbl.setGeometry(0,0,btn.width(),btn.height()) + s['label'] = lbl + lbl = s['label'] + if active: + movie = QMovie(str(script_dir / 'sprinkler_on.gif')) + movie.setScaledSize(QSize(btn.width(), btn.height())) + lbl.setMovie(movie) + movie.start() + lbl.show() + btn.setStyleSheet(self.sprinkler_style(True)) + s['movie'] = movie + else: + pix = QPixmap(str(script_dir / 'sprinkler_off.png')) + if pix.isNull(): + pix = QPixmap(btn.width(), btn.height()); pix.fill(QColor('#6b7280')) + lbl.setPixmap(pix.scaled(btn.size(), Qt.AspectRatioMode.KeepAspectRatio, Qt.TransformationMode.SmoothTransformation)) + lbl.show() + btn.setStyleSheet(self.sprinkler_style(False)) + s['movie'] = None + s['active'] = active + + def sprinkler_style(self, active=False): + base = f""" + QPushButton {{ + width: 120px; height: 120px; border-radius: 60px; background: {'#10b981' if active else '#6b7280'}; + font-weight: bold; + color: white; + }} + QPushButton:hover {{}} + """ + return base + + def show_tooltip(self, device_id): + s = self.sprinklers.get(device_id) + if s: + s['widget'].setToolTip(s.get('name', device_id)) diff --git a/GUI/src/vast/views/irrigation/sprinkler_details_dialog.py b/GUI/src/vast/views/irrigation/sprinkler_details_dialog.py new file mode 100644 index 000000000..837b648b4 --- /dev/null +++ b/GUI/src/vast/views/irrigation/sprinkler_details_dialog.py @@ -0,0 +1,21 @@ +# from PyQt6.QtWidgets import QDialog, QVBoxLayout, QLabel, QPushButton +# from PyQt6.QtCore import Qt + +# class SprinklerDetailsDialog(QDialog): +# def __init__(self, parent, device_id, details): +# super().__init__(parent) +# self.setWindowTitle(f"Sprinkler {device_id} Details") +# self.setModal(True) +# layout = QVBoxLayout(self) +# self.label = QLabel(f"Details for {device_id}") +# layout.addWidget(self.label) +# self.details_label = QLabel(str(details)) +# layout.addWidget(self.details_label) +# self.show_history_btn = QPushButton("Show History") +# layout.addWidget(self.show_history_btn) +# self.show_history_btn.clicked.connect(self.on_show_history) +# self.history_callback = None + +# def on_show_history(self): +# if self.history_callback: +# self.history_callback() diff --git a/GUI/src/vast/views/irrigation/sprinkler_details_dialog_new.py b/GUI/src/vast/views/irrigation/sprinkler_details_dialog_new.py new file mode 100644 index 000000000..4b43dc205 --- /dev/null +++ b/GUI/src/vast/views/irrigation/sprinkler_details_dialog_new.py @@ -0,0 +1,834 @@ +from PyQt6.QtWidgets import ( + QWidget, QVBoxLayout, QHBoxLayout, QPushButton, QLabel, QProgressBar, + QTableWidget, QTableWidgetItem, QLineEdit, QFormLayout, QScrollArea, QGraphicsDropShadowEffect +) +from PyQt6.QtCore import Qt, QPropertyAnimation, pyqtSignal, QTimer +from PyQt6.QtGui import QFont, QColor, QPixmap +import psycopg2 +from psycopg2.extras import RealDictCursor +from datetime import datetime +from io import BytesIO +try: + from minio import Minio + MINIO_AVAILABLE = True +except ImportError: + MINIO_AVAILABLE = False + +# DB connection helper (same as in main app) +def get_db_connection(): + return psycopg2.connect( + # host="postgres", + host="postgres", + port=5432, + user="missions_user", + password="pg123", + dbname="missions_db", + cursor_factory=RealDictCursor + ) + +# MinIO connection helper +def get_minio_client(): + """Get MinIO client for accessing imagery bucket.""" + if not MINIO_AVAILABLE: + print("[DEBUG] MinIO client not available (minio package not installed)") + return None + try: + # Try multiple endpoints for flexibility + endpoints = [ + "minio-hot:9000", # Docker internal + "localhost:9001", # Desktop/host + "127.0.0.1:9001", # Loopback + ] + + for endpoint in endpoints: + try: + client = Minio( + endpoint=endpoint, + access_key="minioadmin", + secret_key="minioadmin123", + secure=False + ) + # Test connection + client.list_buckets() + print(f"[DEBUG] MinIO connected successfully at {endpoint}") + return client + except Exception as e: + print(f"[DEBUG] MinIO endpoint {endpoint} failed: {type(e).__name__}") + continue + + print("[DEBUG] MinIO: all endpoints failed") + return None + except Exception as e: + print(f"[DEBUG] MinIO connection error: {e}") + return None + +def fetch_image_from_minio(image_path: str) -> bytes: + """ + Fetch an image from MinIO 'imagery' bucket. + + Args: + image_path: The key/path to the image in MinIO (e.g., 'folder/image.jpg') + + Returns: + Image bytes, or None if fetch fails + """ + if not MINIO_AVAILABLE: + print("MinIO client not available") + return None + + try: + client = get_minio_client() + if client is None: + return None + + response = client.get_object("imagery", image_path) + image_bytes = response.read() + return image_bytes + except Exception as e: + print(f"Error fetching image from MinIO: {e}") + return None + +class SprinklerDetailsDialogNew(QWidget): + """Tabbed sprinkler details dialog with Details, History, Parameters, Last Image, and Close tabs.""" + + history_requested = pyqtSignal(str) # device_id + parameters_saved = pyqtSignal(str, dict) # device_id, params + + def __init__(self, parent, device_id, details): + super().__init__(parent) + print(f"[DEBUG] SprinklerDetailsDialogNew.__init__ called for device_id={device_id}") + self.device_id = device_id + self.details = details + self.current_tab = 'Details' + self.edited_params = {} + + self.setWindowFlags(Qt.WindowType.FramelessWindowHint) + self.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground) + + print(f"[DEBUG] Setting up window for {device_id}") + + # Main card + self.card = QWidget(self) + self.card.setStyleSheet(""" + background: white; + border-radius: 14px; + """) + + shadow = QGraphicsDropShadowEffect(self.card) + shadow.setBlurRadius(30) + shadow.setOffset(0, 8) + shadow.setColor(QColor(0, 0, 0, 100)) + self.card.setGraphicsEffect(shadow) + + # Main layout + main_layout = QVBoxLayout(self.card) + main_layout.setContentsMargins(20, 20, 20, 20) + main_layout.setSpacing(14) + + # Header section with title only + header_layout = QVBoxLayout() + header_layout.setContentsMargins(0, 0, 0, 0) + header_layout.setSpacing(4) + + # Title + title = QLabel(f"Sprinkler {device_id}") + title.setFont(QFont('Segoe UI', 16, QFont.Weight.Bold)) + title.setStyleSheet("color: qlineargradient(x1:0, y1:0, x2:1, y2:0, stop:0 #06b6d4, stop:1 #0891b2);") + header_layout.addWidget(title) + + main_layout.addLayout(header_layout) + + # Content area (will be replaced based on active tab) + self.content_area = QWidget() + self.content_layout = QVBoxLayout(self.content_area) + self.content_layout.setContentsMargins(0, 0, 0, 0) + main_layout.addWidget(self.content_area, stretch=1) + + # Buttons row at bottom + btn_row = QHBoxLayout() + btn_row.setSpacing(12) + btn_row.addStretch() + + self.tab_buttons = {} + self.create_tab_buttons(btn_row) + + main_layout.addLayout(btn_row) + + # Sizing and positioning + w, h = int(parent.width() * 0.6), int(parent.height() * 0.65) + self.setGeometry((parent.width() - w) // 2, (parent.height() - h) // 2, w, h) + self.card.setGeometry(0, 0, w, h) + + # Fade-in animation + self.opacity_anim = QPropertyAnimation(self, b"windowOpacity") + self.opacity_anim.setDuration(220) + self.opacity_anim.setStartValue(0.0) + self.opacity_anim.setEndValue(1.0) + self.setWindowOpacity(0.0) + self.opacity_anim.start() + + print(f"[DEBUG] Dialog initialized, showing Details tab") + # Show Details tab initially + self.show_tab('Details') + + def create_tab_buttons(self, layout): + """Create all 5 tab buttons and add them to the layout.""" + tabs = ['Details', 'History', 'Parameters', 'Last Image', 'Close'] + for tab in tabs: + btn = QPushButton(tab) + btn.setFixedHeight(36) + btn.setMinimumWidth(100) + btn.setCursor(Qt.CursorShape.PointingHandCursor) + btn.setStyleSheet(self.get_button_style(tab == self.current_tab)) + btn.clicked.connect(lambda checked, t=tab: self.switch_tab(t)) + self.tab_buttons[tab] = btn + # Add all buttons to layout + layout.addWidget(btn) + + def get_button_style(self, active=False): + if active: + return """ + QPushButton { + background: #06b6d4; + color: white; + border: none; + border-radius: 8px; + font-weight: bold; + padding: 8px 16px; + } + """ + else: + return """ + QPushButton { + background: #e5e7eb; + color: #374151; + border: none; + border-radius: 8px; + padding: 8px 16px; + } + QPushButton:hover { + background: #d1d5db; + } + """ + + def switch_tab(self, tab_name): + """Switch to a different tab.""" + print(f"[DEBUG] switch_tab() called: {tab_name}") + if tab_name == 'Close': + self.close() + return + + self.current_tab = tab_name + + # Clear current content safely using takeAt and deleteLater + while self.content_layout.count(): + item = self.content_layout.takeAt(0) + if item.widget(): + item.widget().deleteLater() + + # Show selected tab + self.show_tab(tab_name) + + # Update button styling + self.update_button_styles() + print(f"[DEBUG] Switched to {tab_name} tab") + + def update_button_styles(self): + """Update button styles: active button highlighted, others normal.""" + for tab_name, btn in self.tab_buttons.items(): + btn.setStyleSheet(self.get_button_style(tab_name == self.current_tab)) + + def show_tab(self, tab_name): + """Display content for a tab.""" + if tab_name == 'Details': + self.show_details_tab() + elif tab_name == 'History': + self.show_history_tab() + elif tab_name == 'Parameters': + self.show_parameters_tab() + elif tab_name == 'Last Image': + self.show_last_image_tab() + + def show_details_tab(self): + """Display the details tab with improved layout and styling.""" + # Status section + status_container = QWidget() + status_layout = QHBoxLayout(status_container) + status_layout.setContentsMargins(0, 0, 0, 0) + status_layout.setSpacing(10) + + status_dot = QLabel('●') + status_dot.setFont(QFont('Arial', 14)) + status_color = '#10b981' if self.details.get('active') else '#9ca3af' + status_dot.setStyleSheet(f"color: {status_color}") + + status_text = QLabel('Active' if self.details.get('active') else 'Inactive') + status_text.setFont(QFont('Segoe UI', 11, QFont.Weight.Bold)) + status_text.setStyleSheet(f"color: {status_color}") + + status_layout.addWidget(status_dot) + status_layout.addWidget(status_text) + status_layout.addStretch() + + self.content_layout.addWidget(status_container) + self.content_layout.addSpacing(12) + + # Soil Moisture section + moisture_label = QLabel('Soil Moisture') + moisture_label.setFont(QFont('Segoe UI', 11, QFont.Weight.Bold)) + moisture_label.setStyleSheet("color: #1f2937;") + self.content_layout.addWidget(moisture_label) + + dry_ratio = self.details.get('dry_ratio', 0) + moisture_percent = int(dry_ratio * 100) + + # Percentage label above bar + moisture_value_label = QLabel(f"{moisture_percent}%") + moisture_value_label.setFont(QFont('Segoe UI', 10, QFont.Weight.Bold)) + moisture_value_label.setStyleSheet("color: #06b6d4;") + self.content_layout.addWidget(moisture_value_label) + + # Progress bar + moisture_bar = QProgressBar() + moisture_bar.setRange(0, 100) + moisture_bar.setValue(moisture_percent) + moisture_bar.setFixedHeight(12) + moisture_bar.setStyleSheet(""" + QProgressBar { + border: 1px solid #e5e7eb; + border-radius: 6px; + background: #f3f4f6; + } + QProgressBar::chunk { + background: qlineargradient(x1:0, y1:0, x2:1, y2:0, + stop:0 #06b6d4, stop:1 #0891b2); + border-radius: 5px; + } + """) + self.content_layout.addWidget(moisture_bar) + self.content_layout.addSpacing(16) + + # Confidence section + confidence_label = QLabel('Model Confidence') + confidence_label.setFont(QFont('Segoe UI', 11, QFont.Weight.Bold)) + confidence_label.setStyleSheet("color: #1f2937;") + self.content_layout.addWidget(confidence_label) + + conf = self.details.get('confidence', 0) + conf_percent = int(conf * 100) + + # Determine color based on confidence + if conf >= 0.75: + conf_color = '#10b981' + elif conf >= 0.4: + conf_color = '#f59e0b' + else: + conf_color = '#ef4444' + + # Percentage label above bar + conf_value_label = QLabel(f"{conf_percent}%") + conf_value_label.setFont(QFont('Segoe UI', 10, QFont.Weight.Bold)) + conf_value_label.setStyleSheet(f"color: {conf_color};") + self.content_layout.addWidget(conf_value_label) + + # Confidence progress bar + conf_bar = QProgressBar() + conf_bar.setRange(0, 100) + conf_bar.setValue(conf_percent) + conf_bar.setFixedHeight(12) + conf_bar.setStyleSheet(f""" + QProgressBar {{ + border: 1px solid #e5e7eb; + border-radius: 6px; + background: #f3f4f6; + }} + QProgressBar::chunk {{ + background: {conf_color}; + border-radius: 5px; + }} + """) + self.content_layout.addWidget(conf_bar) + self.content_layout.addSpacing(16) + + # Decision section + decision = self.details.get('decision', 'noop') + # Replace 'noop' with 'no operation' + if decision == 'noop': + decision = 'no operation' + + decision_label = QLabel('Decision') + decision_label.setFont(QFont('Segoe UI', 11, QFont.Weight.Bold)) + decision_label.setStyleSheet("color: #1f2937;") + self.content_layout.addWidget(decision_label) + + # Decision badge + decision_badge = QLabel(decision.upper()) + decision_badge.setFont(QFont('Segoe UI', 10, QFont.Weight.Bold)) + decision_badge.setAlignment(Qt.AlignmentFlag.AlignCenter) + decision_badge.setFixedHeight(32) + + if decision == 'run': + badge_color = '#10b981' + bg_color = '#d1fae5' + elif decision == 'stop': + badge_color = '#ef4444' + bg_color = '#fee2e2' + else: # no operation + badge_color = '#f59e0b' + bg_color = '#fef3c7' + + decision_badge.setStyleSheet(f""" + background: {bg_color}; + color: {badge_color}; + border-radius: 6px; + padding: 6px; + """) + self.content_layout.addWidget(decision_badge) + + self.content_layout.addStretch() + + def show_history_tab(self): + """Display the history tab with a beautifully styled table inside the dialog.""" + records = [] + try: + # Direct database query to avoid import issues + query = """ + SELECT e.device_id, e.dry_ratio, e.decision, e.confidence, e.patch_count, e.ts + FROM soil_moisture_events e + WHERE e.device_id = %s + ORDER BY e.ts DESC + LIMIT 10 + """ + with get_db_connection() as conn: + with conn.cursor() as cur: + cur.execute(query, (self.device_id,)) + records = cur.fetchall() + # Convert tuples to dicts if needed + if records and not isinstance(records[0], dict): + columns = ['device_id', 'dry_ratio', 'decision', 'confidence', 'patch_count', 'ts'] + records = [dict(zip(columns, row)) for row in records] + except Exception as e: + print(f"Error fetching history: {e}") + records = [] + + # Add title label + title = QLabel('Last 10 Events') + title.setFont(QFont('Segoe UI', 9, QFont.Weight.Bold)) + title.setStyleSheet("color: #374151; margin-bottom: 8px;") + self.content_layout.addWidget(title) + + # History table with better column layout + table = QTableWidget(0, 5) + table.setHorizontalHeaderLabels(['Time', 'Soil %', 'Confidence %', 'Decision', 'Patches']) + table.setAlternatingRowColors(True) + table.setColumnWidth(0, 270) # Time + table.setColumnWidth(1, 70) # Soil % + table.setColumnWidth(2, 70) # Confidence % + table.setColumnWidth(3, 130) # Decision (increased from 100 to 130) + table.setColumnWidth(4, 70) # Patches + table.resizeRowsToContents() + table.setWordWrap(True) + # Set minimum row height for better visibility + table.verticalHeader().setDefaultSectionSize(32) + + # Professional styling with better padding + table.setStyleSheet(""" + QTableWidget { + background: white; + alternate-background-color: #f9fafb; + gridline-color: #e5e7eb; + border: 1px solid #e5e7eb; + border-radius: 6px; + } + QHeaderView::section { + background: #f3f4f6; + padding: 12px; + border: none; + font-weight: bold; + color: #374151; + border-right: 1px solid #d1d5db; + } + QTableWidget::item { + padding: 12px; + border-bottom: 1px solid #e5e7eb; + } + """) + table.verticalHeader().hide() + table.setSelectionBehavior(QTableWidget.SelectionBehavior.SelectRows) + table.setSelectionMode(QTableWidget.SelectionMode.SingleSelection) + + # Populate rows + for row in records: + r = table.rowCount() + table.insertRow(r) + + # Column 0: Timestamp + ts_item = QTableWidgetItem(str(row['ts'])) + ts_item.setFont(QFont('Courier', 9)) + ts_item.setForeground(QColor('#6b7280')) + table.setItem(r, 0, ts_item) + + # Column 1: Soil Moisture % (dry_ratio as %) + dry_percent = int(row['dry_ratio'] * 100) + moisture_item = QTableWidgetItem(f"{dry_percent}%") + moisture_item.setTextAlignment(Qt.AlignmentFlag.AlignCenter) + moisture_item.setFont(QFont('Courier', 9)) + table.setItem(r, 1, moisture_item) + + # Column 2: Confidence % + conf_percent = int(row['confidence'] * 100) + conf_item = QTableWidgetItem(f"{conf_percent}%") + conf_item.setTextAlignment(Qt.AlignmentFlag.AlignCenter) + conf_item.setFont(QFont('Courier', 9)) + table.setItem(r, 2, conf_item) + + # Column 3: Decision with color coding + decision = row['decision'] + if decision == 'noop': + decision = 'no operation' + + # Use shorter display text for better fit in cell + decision_text = { + 'run': 'RUN', + 'stop': 'STOP', + 'no operation': 'NO OPERATION' + }.get(decision, decision.upper()) + + dec_item = QTableWidgetItem(decision_text) + dec_item.setFont(QFont('Segoe UI', 9, QFont.Weight.Bold)) + dec_item.setTextAlignment(Qt.AlignmentFlag.AlignCenter) + + # Set background and text colors with proper contrast + if decision == 'run': + dec_item.setBackground(QColor("#dde9e5")) + dec_item.setForeground(QColor("#58b7e4")) # White text on green + elif decision == 'stop': + dec_item.setBackground(QColor('#fee2e2')) # Light red background + dec_item.setForeground(QColor('#dc2626')) # Dark red text + else: # no operation + dec_item.setBackground(QColor('#f59e0b')) + dec_item.setForeground(QColor('#1f2937')) # Dark text for better contrast on orange + + table.setItem(r, 3, dec_item) + + # Column 4: Patches (patch count) + patch_item = QTableWidgetItem(f"{row.get('patch_count', 0)}") + patch_item.setTextAlignment(Qt.AlignmentFlag.AlignCenter) + patch_item.setFont(QFont('Courier', 9)) + table.setItem(r, 4, patch_item) + + self.content_layout.addWidget(table, stretch=1) + + def show_parameters_tab(self): + """Display the parameters tab with editable fields.""" + try: + params = self.fetch_parameters() + except Exception: + params = {} + + # Form for parameters + form = QFormLayout() + form.setSpacing(16) + form.setContentsMargins(0, 0, 0, 0) + + # Define input styling + input_style = """ + QLineEdit { + border: 2px solid #e5e7eb; + border-radius: 8px; + padding: 6px; + background: #f9fafb; + color: #1f2937; + font-size: 11pt; + font-weight: 500; + } + QLineEdit:focus { + border: 2px solid #06b6d4; + background: #ffffff; + } + QLineEdit:hover { + border: 2px solid #d1d5db; + } + """ + + # Define label styling + label_style = """ + color: #374151; + font-weight: bold; + font-size: 11pt; + """ + + self.param_inputs = {} + + # Dry Ratio High + dry_high_label = QLabel('Dry Ratio High:') + dry_high_label.setStyleSheet(label_style) + dry_high_input = QLineEdit() + dry_high_input.setText(str(params.get('dry_ratio_high', 0.7))) + dry_high_input.setStyleSheet(input_style) + dry_high_input.setMinimumHeight(40) + self.param_inputs['dry_ratio_high'] = dry_high_input + form.addRow(dry_high_label, dry_high_input) + + # Dry Ratio Low + dry_low_label = QLabel('Dry Ratio Low:') + dry_low_label.setStyleSheet(label_style) + dry_low_input = QLineEdit() + dry_low_input.setText(str(params.get('dry_ratio_low', 0.4))) + dry_low_input.setStyleSheet(input_style) + dry_low_input.setMinimumHeight(40) + self.param_inputs['dry_ratio_low'] = dry_low_input + form.addRow(dry_low_label, dry_low_input) + + # Min Patches + min_patches_label = QLabel('Min Patches:') + min_patches_label.setStyleSheet(label_style) + min_patches_input = QLineEdit() + min_patches_input.setText(str(params.get('min_patches', 1))) + min_patches_input.setStyleSheet(input_style) + min_patches_input.setMinimumHeight(40) + self.param_inputs['min_patches'] = min_patches_input + form.addRow(min_patches_label, min_patches_input) + + # Duration (minutes) + # duration_label = QLabel('Duration (min):') + # duration_label.setStyleSheet(label_style) + # duration_input = QLineEdit() + # duration_input.setText(str(params.get('duration_min', 30))) + # duration_input.setStyleSheet(input_style) + # duration_input.setMinimumHeight(40) + # self.param_inputs['duration_min'] = duration_input + # form.addRow(duration_label, duration_input) + + # Save button + save_btn = QPushButton('Save Parameters') + save_btn.setStyleSheet(""" + QPushButton { + background: #10b981; + color: white; + border: none; + border-radius: 8px; + padding: 12px 16px; + font-weight: bold; + font-size: 11pt; + } + QPushButton:hover { + background: #059669; + } + QPushButton:pressed { + background: #047857; + } + """) + save_btn.setMinimumHeight(44) + save_btn.clicked.connect(self.save_parameters) + + scroll = QScrollArea() + scroll_widget = QWidget() + scroll_widget.setLayout(form) + scroll.setWidget(scroll_widget) + scroll.setWidgetResizable(True) + scroll.setStyleSheet("QScrollArea { border: none; background: transparent; }") + + self.content_layout.addWidget(scroll) + self.content_layout.addSpacing(12) + self.content_layout.addWidget(save_btn) + + def fetch_parameters(self): + """Fetch parameters from irrigation_policies table.""" + try: + with get_db_connection() as conn: + with conn.cursor() as cur: + query = """ + SELECT dry_ratio_high, dry_ratio_low, min_patches, duration_min + FROM irrigation_policies + WHERE device_id = %s + """ + cur.execute(query, (self.device_id,)) + row = cur.fetchone() + + if row: + # Handle both tuple and dict-like responses + if isinstance(row, (tuple, list)): + return { + 'dry_ratio_high': float(row[0]) if row[0] is not None else 0.7, + 'dry_ratio_low': float(row[1]) if row[1] is not None else 0.4, + 'min_patches': int(row[2]) if row[2] is not None else 1, + 'duration_min': int(row[3]) if row[3] is not None else 30 + } + else: + # Dictionary-like response + return { + 'dry_ratio_high': float(row.get('dry_ratio_high', 0.7)), + 'dry_ratio_low': float(row.get('dry_ratio_low', 0.4)), + 'min_patches': int(row.get('min_patches', 1)), + 'duration_min': int(row.get('duration_min', 30)) + } + except Exception as e: + print(f"Error fetching parameters: {type(e).__name__}: {str(e)}") + return {} + + def save_parameters(self): + """Save parameters to irrigation_policies table.""" + try: + # Validate and convert inputs + dry_ratio_high = float(self.param_inputs['dry_ratio_high'].text()) + dry_ratio_low = float(self.param_inputs['dry_ratio_low'].text()) + min_patches = int(self.param_inputs['min_patches'].text()) + duration_min = 10 #int(self.param_inputs['duration_min'].text()) + + # Basic validation + if not (0 <= dry_ratio_high <= 1): + raise ValueError("Dry Ratio High must be between 0 and 1") + if not (0 <= dry_ratio_low <= 1): + raise ValueError("Dry Ratio Low must be between 0 and 1") + if min_patches < 0: + raise ValueError("Min Patches must be positive") + if duration_min < 0: + raise ValueError("Duration must be positive") + + with get_db_connection() as conn: + with conn.cursor() as cur: + query = """ + INSERT INTO irrigation_policies + (device_id, dry_ratio_high, dry_ratio_low, min_patches, duration_min) + VALUES (%s, %s, %s, %s, %s) + ON CONFLICT (device_id) DO UPDATE SET + dry_ratio_high = EXCLUDED.dry_ratio_high, + dry_ratio_low = EXCLUDED.dry_ratio_low, + min_patches = EXCLUDED.min_patches, + duration_min = EXCLUDED.duration_min + """ + cur.execute(query, (self.device_id, dry_ratio_high, dry_ratio_low, min_patches, duration_min)) + conn.commit() + + # Show success message + msg_label = QLabel("✓ Parameters saved successfully!") + msg_label.setStyleSheet("color: #10b981; font-weight: bold; padding: 8px;") + self.content_layout.addWidget(msg_label) + print(f"Parameters saved for device {self.device_id}") + + except ValueError as ve: + print(f"Validation error: {ve}") + msg_label = QLabel(f"✗ Validation error: {ve}") + msg_label.setStyleSheet("color: #ef4444; font-weight: bold; padding: 8px;") + self.content_layout.addWidget(msg_label) + except Exception as e: + print(f"Error saving parameters: {type(e).__name__}: {str(e)}") + msg_label = QLabel(f"✗ Error: {type(e).__name__}") + msg_label.setStyleSheet("color: #ef4444; font-weight: bold; padding: 8px;") + self.content_layout.addWidget(msg_label) + + def show_last_image_tab(self): + """Display the last image tab with image from MinIO.""" + print(f"[DEBUG] show_last_image_tab() called for {self.device_id}") + try: + # Query database for the most recent image path + query = """ + SELECT extra->>'image_path' as image_path, ts + FROM soil_moisture_events + WHERE device_id = %s AND extra->>'image_path' IS NOT NULL + ORDER BY ts DESC + LIMIT 1 + """ + with get_db_connection() as conn: + with conn.cursor() as cur: + cur.execute(query, (self.device_id,)) + row = cur.fetchone() + print(f"[DEBUG] Query result: {row}") + + if row and row.get('image_path'): + image_path = row['image_path'] + ts = row.get('ts', 'Unknown') + print(f"[DEBUG] Found image path: {image_path}, ts: {ts}") + + # Fetch image from MinIO + image_bytes = fetch_image_from_minio(image_path) + + if image_bytes: + print(f"[DEBUG] Successfully fetched image, size: {len(image_bytes)} bytes") + # Display the image + pixmap = QPixmap() + pixmap.loadFromData(image_bytes) + + if not pixmap.isNull(): + # Create container for image display + image_container = QWidget() + image_layout = QVBoxLayout(image_container) + image_layout.setContentsMargins(0, 0, 0, 0) + image_layout.setSpacing(12) + + # Timestamp label + ts_label = QLabel(f"Timestamp: {ts}") + ts_label.setFont(QFont('Segoe UI', 10, QFont.Weight.Bold)) + ts_label.setStyleSheet("color: #6b7280;") + image_layout.addWidget(ts_label) + + # Image path label + path_label = QLabel(f"Path: {image_path}") + path_label.setFont(QFont('Courier', 9)) + path_label.setStyleSheet("color: #9ca3af; word-wrap: true;") + path_label.setWordWrap(True) + image_layout.addWidget(path_label) + + # Scale image to fit in dialog + max_width = int(self.card.width() * 0.8) + max_height = 400 + scaled_pixmap = pixmap.scaledToWidth( + max_width, + Qt.TransformationMode.SmoothTransformation + ) + if scaled_pixmap.height() > max_height: + scaled_pixmap = scaled_pixmap.scaledToHeight( + max_height, + Qt.TransformationMode.SmoothTransformation + ) + + # Image label + img_label = QLabel() + img_label.setPixmap(scaled_pixmap) + img_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + img_label.setStyleSheet("border: 1px solid #e5e7eb; border-radius: 6px;") + image_layout.addWidget(img_label, stretch=1) + + self.content_layout.addWidget(image_container, stretch=1) + print(f"[DEBUG] Image displayed successfully") + return + else: + error_msg = "Failed to load image from bytes" + print(f"[DEBUG] {error_msg}") + self.show_image_error(error_msg) + return + else: + error_msg = f"Could not fetch image from MinIO: {image_path}" + print(f"[DEBUG] {error_msg}") + self.show_image_error(error_msg) + return + else: + # No image path found in recent events + error_msg = "No image data available for this device" + print(f"[DEBUG] {error_msg}") + self.show_image_error(error_msg) + return + except Exception as e: + error_msg = f"Error fetching image: {str(e)}" + print(f"[DEBUG] {error_msg}") + import traceback + traceback.print_exc() + self.show_image_error(error_msg) + + def show_image_error(self, error_message: str): + """Display error message in the image tab.""" + error_container = QWidget() + error_layout = QVBoxLayout(error_container) + error_layout.setContentsMargins(0, 0, 0, 0) + error_layout.addStretch() + + error_label = QLabel(error_message) + error_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + error_label.setFont(QFont('Segoe UI', 12)) + error_label.setStyleSheet("color: #f59e0b; padding: 20px;") + error_label.setWordWrap(True) + error_layout.addWidget(error_label) + + error_layout.addStretch() + self.content_layout.addWidget(error_container, stretch=1) diff --git a/GUI/src/vast/views/irrigation/sprinkler_off.png b/GUI/src/vast/views/irrigation/sprinkler_off.png new file mode 100644 index 000000000..1807f873c Binary files /dev/null and b/GUI/src/vast/views/irrigation/sprinkler_off.png differ diff --git a/GUI/src/vast/views/irrigation/sprinkler_on.gif b/GUI/src/vast/views/irrigation/sprinkler_on.gif new file mode 100644 index 000000000..4401de4bd Binary files /dev/null and b/GUI/src/vast/views/irrigation/sprinkler_on.gif differ diff --git a/GUI/src/vast/views/leaf_diseases.py b/GUI/src/vast/views/leaf_diseases.py new file mode 100644 index 000000000..7b9fe59fb --- /dev/null +++ b/GUI/src/vast/views/leaf_diseases.py @@ -0,0 +1,708 @@ +# leaf_diseases.py (compact, fixed + Grafana integration) +# UI: English, Comments: English, 4 spaces indent. + +from __future__ import annotations +from collections import Counter, defaultdict +from datetime import datetime, time, timezone +from typing import Iterable, Optional, Tuple + +from PyQt6.QtCore import QDate, QTimer, Qt, QPointF, pyqtSignal, QUrl +from PyQt6.QtGui import QPainter, QPen, QColor +from PyQt6.QtWidgets import ( + QCalendarWidget, QDialog, QDialogButtonBox, QFrame, QHBoxLayout, QLabel, + QPushButton, QScrollArea, QSizePolicy, QSpacerItem, QVBoxLayout, QWidget, QDateEdit, QProgressBar +) +from PyQt6.QtWebEngineWidgets import QWebEngineView + +from dashboard_api import DashboardApi + +# ────────────────────────────── +# Small utils +# ────────────────────────────── + + + +def _color_for_pct(pct: float) -> str: + """Traffic-light color by percentage.""" + return "#22c55e" if pct < 20 else ("#f59e0b" if pct <= 50 else "#ef4444") + +def _is_sick(v) -> bool: + """Normalize truthy sick flags from DB.""" + return v in [True, "true", "t", "1", 1, "yes", "y"] + +def _ts_to_date(ts: str) -> Optional[datetime.date]: + """Parse ISO ts (supports 'Z').""" + try: + return datetime.fromisoformat(ts.replace("Z", "+00:00")).date() + except Exception: + return None + +def _json_rows(payload) -> list: + """Accept list or any common envelope {data/items/rows/...}.""" + if isinstance(payload, list): + return payload + if isinstance(payload, dict): + for k in ("data", "results", "items", "records", "rows"): + v = payload.get(k) + if isinstance(v, list): + return v + return [] + +def _clear_layout(layout) -> None: + """Remove all widgets from a layout.""" + while layout.count(): + itm = layout.takeAt(0) + w = itm.widget() + if w: + w.deleteLater() + +# Styles (one place) +APP_STYLES = """ +QWidget { + background: qlineargradient(x1:0, y1:0, x2:0, y2:1, stop:0 #0a0f1f, stop:1 #060913); + color: #e5e7eb; font-family: ui-sans-serif, system-ui, 'Segoe UI', Roboto, sans-serif; +} +QScrollArea { border: none; background: transparent; } +QLabel { color: #e5e7eb; background: transparent; } + +QPushButton { + background: #0f1a33; border: 1px solid #1f2b49; border-radius: 12px; + color: #e5e7eb; padding: 10px 20px; font-weight: 600; font-size: 13px; +} +QPushButton:hover { background: #1a2a4a; border: 1px solid #3d5a8f; } +QPushButton:pressed { background: #0a1220; } + +QDateEdit { background: transparent; border: none; color: #e5e7eb; padding: 6px 10px; font-size: 13px; } +QDateEdit::drop-down { border: none; background: transparent; width: 20px; } + +QFrame.card { + background: qradialgradient(cx:0.9, cy:-0.1, radius:1.2, fx:0.9, fy:-0.1, + stop:0 #243b55, stop:0.35 #111827, stop:1 #0b1220); + border: 1px solid #1f2937; border-radius: 16px; padding: 16px; +} + +/* nicer disease chips */ +.Tag { + background: #0b1220; border: 1px solid #1f2937; + border-radius: 999px; padding: 6px 12px; font-size: 12px; +} +.Tag:hover { border-color: #334155; box-shadow: 0 0 0 2px rgba(99,102,241,.15); } + +/* progress bars */ +QProgressBar { + background: #0b1220; border: 1px solid #1f2937; border-radius: 999px; + min-height: 14px; max-height: 14px; text-align: center; +} +QProgressBar::chunk { + border-radius: 999px; +} +""" + + +# ────────────────────────────── +# Clickables +# ────────────────────────────── + +class ClickableRow(QFrame): + clicked = pyqtSignal(str) + def __init__(self, key: str, parent: Optional[QWidget] = None) -> None: + super().__init__(parent) + self.key = key + self.setStyleSheet("QFrame { background: transparent; }") + self.setCursor(Qt.CursorShape.PointingHandCursor) + def mousePressEvent(self, e): # noqa: N802 + self.clicked.emit(self.key) + super().mousePressEvent(e) + +ClickableTag = ClickableRow # identical behavior + +# ────────────────────────────── +# Tiny sparkline +# ────────────────────────────── + +class TrendSparkline(QFrame): + """Minimal line chart for percentages (0..100).""" + def __init__(self, parent: Optional[QWidget] = None) -> None: + super().__init__(parent) + self._series: list[float] = [] + self.setMinimumHeight(160) + self.setStyleSheet("QFrame { background: #0b1220; border: 1px solid #1f2937; border-radius: 16px; }") + def set_series(self, values: Iterable[float]) -> None: + self._series = list(values) if values else [] + self.update() + def paintEvent(self, _): # noqa: N802 + super().paintEvent(_) + if not self._series: + return + p = QPainter(self); p.setRenderHints(QPainter.RenderHint.Antialiasing, True) + w, h = self.width(), self.height() + L, T, R, B = 16, 12, 16, 20 + cw, ch = max(1, w - L - R), max(1, h - T - B) + pen_axis = QPen(QColor("#1f2937")); pen_axis.setWidth(1); p.setPen(pen_axis) + p.drawLine(L, h - B, w - R, h - B); p.drawLine(L, T, L, h - B) + n = len(self._series); dx = cw / max(1, n - 1); pts = [] + for i, val in enumerate(self._series): + v = max(0.0, min(100.0, float(val))) + pts.append(QPointF(L + i * dx, T + (100.0 - v) / 100.0 * ch)) + pen_line = QPen(QColor("#6366f1")); pen_line.setWidth(2); p.setPen(pen_line) + for i in range(1, len(pts)): p.drawLine(pts[i - 1], pts[i]) + p.setPen(Qt.PenStyle.NoPen); p.setBrush(QColor("#6366f1")) + for idx in (0, len(pts) - 1): p.drawEllipse(pts[idx], 3.5, 3.5) + +# ────────────────────────────── +# Date range dialog +# ────────────────────────────── + +class DateRangeDialog(QDialog): + """Two calendars (From/To) + clear/today/OK/Cancel.""" + def __init__(self, parent: Optional[QWidget] = None, start: Optional[QDate] = None, end: Optional[QDate] = None): + super().__init__(parent) + self.setWindowTitle("Select Date Range") + self.setModal(True) + self.setMinimumWidth(460) + self.setStyleSheet(""" + QDialog { background: #0b1220; color: #e5e7eb; } + QLabel { background: transparent; color: #e5e7eb; } + QCalendarWidget QWidget { background: transparent; color: #e5e7eb; } + QCalendarWidget QAbstractItemView { selection-background-color: #1e3a5f; } + QDialogButtonBox QPushButton { + background: #0f1a33; border: 1px solid #1f2b49; border-radius: 8px; + color: #e5e7eb; padding: 6px 12px; font-weight: 600; + } + QDialogButtonBox QPushButton:hover { background: #1a2a4a; border-color: #3d5a8f; } + """) + main = QVBoxLayout(self); row = QHBoxLayout(); main.addLayout(row) + min_allowed, max_allowed = QDate(2000, 1, 1), QDate(2100, 12, 31) + + def _calendar(lbl: str) -> QCalendarWidget: + box = QVBoxLayout(); box.addWidget(QLabel(lbl)) + cal = QCalendarWidget(self) + cal.setNavigationBarVisible(True); cal.setGridVisible(True) + cal.setMinimumDate(min_allowed); cal.setMaximumDate(max_allowed) + box.addWidget(cal); return box, cal + + left_box, self.cal_from = _calendar("From Date") + right_box, self.cal_to = _calendar("To Date") + row.addLayout(left_box); row.addItem(QSpacerItem(16, 1, QSizePolicy.Policy.Minimum, QSizePolicy.Policy.Minimum)); row.addLayout(right_box) + today = QDate.currentDate(); self.cal_from.setSelectedDate(start or today.addDays(-7)); self.cal_to.setSelectedDate(end or today) + buttons = QDialogButtonBox(self) + self._btn_clear = buttons.addButton("Clear", QDialogButtonBox.ButtonRole.ActionRole) + self._btn_today = buttons.addButton("Today", QDialogButtonBox.ButtonRole.ActionRole) + buttons.addButton(QDialogButtonBox.StandardButton.Ok); buttons.addButton(QDialogButtonBox.StandardButton.Cancel) + self._btn_clear.clicked.connect(self._on_clear); self._btn_today.clicked.connect(self._on_today) + buttons.accepted.connect(self.accept); buttons.rejected.connect(self.reject) + main.addWidget(buttons) + + def _on_today(self): t = QDate.currentDate(); self.cal_from.setSelectedDate(t); self.cal_to.setSelectedDate(t) + def _on_clear(self): self.cal_from.setSelectedDate(QDate()); self.cal_to.setSelectedDate(QDate()) + + def selectedRange(self) -> Tuple[Optional[QDate], Optional[QDate]]: + f, t = self.cal_from.selectedDate(), self.cal_to.selectedDate() + if not f.isValid() or not t.isValid(): return None, None + return (t, f) if f > t else (f, t) + +# ────────────────────────────── +# Main View +# ────────────────────────────── + +class LeafDiseaseView(QWidget): + """ + Compact dashboard: date filtering, top devices, top diseases, + device details (per-disease % of total device images). + When clicking on disease or device, shows details below inline. + """ + + def __init__(self, api: DashboardApi, parent: Optional[QWidget] = None) -> None: + super().__init__(parent) + self.api = api + self._raw: list[dict] = [] + self._types: dict[str, str] = {} # { "1": "Blight", ... } + self._filters_timer = QTimer(self); self._filters_timer.setSingleShot(True) + self._filters_timer.setInterval(250); self._filters_timer.timeout.connect(self._apply_filters_and_update) + self._setup_ui() + self._load_types(); self._load_reports() + + # ───────── UI / build ───────── + + def _setup_ui(self) -> None: + self.setStyleSheet(APP_STYLES) + scroll = QScrollArea(); scroll.setWidgetResizable(True); scroll.setFrameShape(QFrame.Shape.NoFrame) + container = QWidget(); main = QVBoxLayout(container); main.setSpacing(20); main.setContentsMargins(24, 24, 24, 24) + + # Top section: header, controls, KPIs, cards + main.addWidget(self._header()) + main.addWidget(self._controls()) + main.addWidget(self._kpis()) + main.addWidget(self._cards()) + + # Details section (shown below when clicking) + self.device_card = self._device_details_card() + self.device_card.setVisible(False) + main.addWidget(self.device_card) + + self.grafana_card = self._grafana_details_card() + self.grafana_card.setVisible(False) + main.addWidget(self.grafana_card) + + main.addStretch() + scroll.setWidget(container) + wrap = QVBoxLayout(self); wrap.setContentsMargins(0, 0, 0, 0); wrap.addWidget(scroll) + + def _header(self) -> QWidget: + frame = QFrame(); h = QHBoxLayout(frame) + h.setContentsMargins(0, 0, 0, 0) + title = QLabel("Field Status: Report") + title.setStyleSheet("font-size: 22px; font-weight: 700; letter-spacing: 0.3px;") + btn = QPushButton("🔄 Refresh"); btn.clicked.connect(self._refresh) + h.addWidget(title); h.addStretch(); h.addWidget(btn); return frame + + def _refresh(self): self._load_types(); self._load_reports() + + def _controls(self) -> QWidget: + box = QFrame(); box.setObjectName("controls"); box.setStyleSheet( + "QFrame#controls { background: #0f1a33; border: 1px solid #1f2b49; border-radius: 12px; padding: 10px; }" + ) + h = QHBoxLayout(box); h.setSpacing(20) + min_allowed, max_allowed = QDate(2000, 1, 1), QDate(2100, 12, 31) + h.addWidget(QLabel("Date Range:")) + self.date_from = QDateEdit(); self.date_from.setCalendarPopup(True); self.date_from.setDisplayFormat("dd/MM/yyyy") + self.date_from.setDate(QDate.currentDate().addDays(-7)); self.date_from.setMinimumDate(min_allowed); self.date_from.setMaximumDate(max_allowed) + self.date_to = QDateEdit(); self.date_to.setCalendarPopup(True); self.date_to.setDisplayFormat("dd/MM/yyyy") + self.date_to.setDate(QDate.currentDate()); self.date_to.setMinimumDate(min_allowed); self.date_to.setMaximumDate(max_allowed) + self.range_btn = QPushButton("📅 Select Range"); self.range_btn.clicked.connect(self._open_range_dialog) + for w in (self.date_from, QLabel("–"), self.date_to, self.range_btn): h.addWidget(w) + h.addStretch(); self.range_info = QLabel("Last 7 Days"); self.range_info.setStyleSheet("color: #94a3b8; font-size: 12px;"); h.addWidget(self.range_info) + self.date_from.dateChanged.connect(self._range_changed); self.date_to.dateChanged.connect(self._range_changed) + self._update_range_info(); return box + + def _kpis(self) -> QWidget: + frame = QFrame(); h = QHBoxLayout(frame); h.setSpacing(16); h.setContentsMargins(0, 0, 0, 0) + self.kpi_healthy = self._kpi_card("Overall Healthy %", "0%", "#22c55e") + self.kpi_images = self._kpi_card("Images Analyzed", "0", "#6366f1") + self.kpi_devices = self._kpi_card("Active Devices", "0", "#f59e0b") + for k in (self.kpi_healthy, self.kpi_images, self.kpi_devices): h.addWidget(k) + return frame + + def _cards(self) -> QWidget: + frame = QFrame(); h = QHBoxLayout(frame); h.setSpacing(16); h.setContentsMargins(0, 0, 0, 0) + self.devices_card = self._devices_card(); self.diseases_card = self._diseases_card() + h.addWidget(self.devices_card, 2); h.addWidget(self.diseases_card, 1); return frame + + # Small UI helpers + def _kpi_card(self, title: str, value: str, color: str) -> QWidget: + card = QFrame(); card.setProperty("class", "card"); v = QVBoxLayout(card); v.setSpacing(8) + t = QLabel(title); t.setStyleSheet("font-size: 13px; color: #94a3b8;") + val = QLabel(value); val.setObjectName("value"); val.setStyleSheet(f"font-size: 28px; font-weight: 700; color: {color};") + v.addWidget(t); v.addWidget(val); return card + + def _devices_card(self) -> QWidget: + card = QFrame(); card.setProperty("class", "card"); v = QVBoxLayout(card); v.setSpacing(12) + title = QLabel("Disease Severity by Device (Top 5)") + title.setStyleSheet("font-size: 16px; font-weight: 700; letter-spacing: .2px;") + self.devices_container = QWidget(); self.devices_layout = QVBoxLayout(self.devices_container) + self.devices_layout.setSpacing(10); self.devices_layout.setContentsMargins(0,0,0,0) + note = QLabel("Bar color by severity: Green/Orange/Red • Length represents percentage") + note.setStyleSheet("font-size: 12px; color: #94a3b8; margin-top: 8px;") + v.addWidget(title); v.addWidget(self.devices_container); v.addStretch(); v.addWidget(note); return card + + def _diseases_card(self) -> QWidget: + card = QFrame(); card.setProperty("class", "card"); v = QVBoxLayout(card); v.setSpacing(12) + title = QLabel("Top 3 Most Common Diseases") + title.setStyleSheet("font-size: 16px; font-weight: 700; letter-spacing: .2px;") + self.diseases_container = QWidget(); self.diseases_layout = QVBoxLayout(self.diseases_container) + self.diseases_layout.setSpacing(10); self.diseases_layout.setContentsMargins(0,0,0,0) + note = QLabel("Click on a disease to view detailed Grafana analytics below") + note.setStyleSheet("font-size: 12px; color: #94a3b8; margin-top: 8px;") + v.addWidget(title); v.addWidget(self.diseases_container); v.addStretch(); v.addWidget(note); return card + + def _device_details_card(self) -> QWidget: + """Card that shows disease breakdown for selected device""" + card = QFrame(); card.setProperty("class", "card"); v = QVBoxLayout(card); v.setSpacing(12) + + # Header with close button + header = QHBoxLayout() + self.device_title = QLabel("Device Details") + self.device_title.setStyleSheet("font-size: 16px; font-weight: 700;") + header.addWidget(self.device_title) + header.addStretch() + + close_btn = QPushButton("✕ Close") + close_btn.setStyleSheet("padding: 4px 8px; font-size: 11px;") + close_btn.clicked.connect(lambda: self.device_card.setVisible(False)) + header.addWidget(close_btn) + + v.addLayout(header) + + self.device_box = QWidget(); self.device_layout = QVBoxLayout(self.device_box) + self.device_layout.setSpacing(10); self.device_layout.setContentsMargins(0,0,0,0) + note = QLabel("% represents sick images with this disease out of ALL images from this device") + note.setStyleSheet("font-size: 12px; color: #94a3b8; margin-top: 8px;") + v.addWidget(self.device_box); v.addStretch(); v.addWidget(note) + return card + + def _grafana_details_card(self) -> QWidget: + """Card that shows embedded Grafana dashboard for selected disease""" + card = QFrame(); card.setProperty("class", "card"); v = QVBoxLayout(card); v.setSpacing(12) + v.setContentsMargins(16, 16, 16, 16) + + # Header with title and close button + header = QHBoxLayout() + self.grafana_title = QLabel("Disease Analysis") + self.grafana_title.setStyleSheet("font-size: 16px; font-weight: 700;") + header.addWidget(self.grafana_title) + header.addStretch() + + refresh_btn = QPushButton("🔄 Refresh") + refresh_btn.setStyleSheet("padding: 4px 8px; font-size: 11px;") + refresh_btn.clicked.connect(self._refresh_grafana) + header.addWidget(refresh_btn) + + close_btn = QPushButton("✕ Close") + close_btn.setStyleSheet("padding: 4px 8px; font-size: 11px;") + close_btn.clicked.connect(lambda: self.grafana_card.setVisible(False)) + header.addWidget(close_btn) + + v.addLayout(header) + + # Grafana WebView (embedded) + self.grafana_web = QWebEngineView() + self.grafana_web.setMinimumHeight(700) # Good size for viewing + v.addWidget(self.grafana_web) + + # Status label + self.grafana_status = QLabel("📊 Loading dashboard...") + self.grafana_status.setStyleSheet("padding: 5px; color: #94a3b8; font-size: 11px;") + v.addWidget(self.grafana_status) + + self.grafana_web.loadFinished.connect(self._on_grafana_loaded) + + return card + + def _refresh_grafana(self): + """Refresh the embedded Grafana dashboard""" + self.grafana_status.setText("📊 Refreshing dashboard...") + self.grafana_web.reload() + + def _on_grafana_loaded(self, success: bool): + """Called when Grafana page finishes loading""" + if success: + self.grafana_status.setText("✅ Dashboard loaded | Auto-refresh every 10 seconds") + else: + self.grafana_status.setText("❌ Error loading dashboard - Ensure Grafana is running") + + # ───────── Data fetch ───────── + + def _load_types(self) -> None: + """Fetch leaf_disease_types -> self._types {id:str -> name:str}.""" + try: + url = f"{self.api.base}/api/tables/leaf_disease_types" + resp = self.api.http.get(url, timeout=10) + mapping = { + str(r.get("id")): str(r.get("name")) + for r in _json_rows(resp.json()) + if isinstance(r, dict) and r.get("id") is not None and r.get("name") + } + if mapping: + self._types = mapping + print(f"[LeafDiseaseView] Loaded {len(self._types)} disease types.") + except Exception as e: + print(f"[LeafDiseaseView] Failed loading disease types: {e}") + + def _load_reports(self) -> None: + """Fetch reports -> self._raw and update.""" + try: + url = f"{self.api.base}/api/tables/leaf_reports" + print(f"[LeafDiseaseView] Requesting: {url}") + resp = self.api.http.get(url) + rows = _json_rows(resp.json()) if resp.status_code == 200 else [] + if rows and isinstance(rows[0], str): # stringified JSON rows support + import json + rows = [json.loads(x) if isinstance(x, str) else x for x in rows] + self._raw = [r for r in rows if isinstance(r, dict)] + self._update_all(self._filter_by_dates(self._raw)) + except Exception as e: + print(f"[LeafDiseaseView] Error: {e}") + self._update_all([]) + + # ───────── Filters & triggers ───────── + + def _range_changed(self, *_): + self._update_range_info() + self._filters_timer.start() + # If Grafana card is open and we have a selected disease, reload with new range + if getattr(self, "grafana_card", None) and self.grafana_card.isVisible(): + if hasattr(self, "_sel_disease"): + self._on_disease_clicked(self._sel_disease) + + def _open_range_dialog(self): + dlg = DateRangeDialog(self, start=self.date_from.date(), end=self.date_to.date()) + if dlg.exec() == QDialog.DialogCode.Accepted: + f, t = dlg.selectedRange() + if f and t: + self.date_from.setDate(f) + self.date_to.setDate(t) + else: + self.date_from.setDate(QDate.currentDate().addDays(-7)) + self.date_to.setDate(QDate.currentDate()) + self._range_changed() + + def _update_range_info(self): + txt = f"{self.date_from.date().toString('dd/MM')} → {self.date_to.date().toString('dd/MM')}" + self.range_info.setText(txt) + self.range_btn.setText(f"📅 {txt}") + + def _apply_filters_and_update(self): + self._update_all(self._filter_by_dates(self._raw)) + + def _filter_by_dates(self, data: list[dict]) -> list[dict]: + """Inclusive date-only filter using QDate edits.""" + d_from, d_to = self.date_from.date().toPyDate(), self.date_to.date().toPyDate() + out = [] + for r in data: + ts = r.get("ts") + if ts: + d = _ts_to_date(ts) + if d and not (d_from <= d <= d_to): + continue + out.append(r) + print(f"[KPI-DBG] filter_by_dates: kept={len(out)} of {len(data)}") + return out + + def _grafana_range_params(self) -> str: + """ + Build Grafana from/to range based on current date_from/date_to widgets. + + Grafana expects timestamps in milliseconds since epoch. + We take: + - from = start of date_from day (00:00) + - to = end of date_to day (23:59:59.999) + """ + d_from = self.date_from.date().toPyDate() + d_to = self.date_to.date().toPyDate() + + # Start of day (UTC) + start_dt = datetime.combine(d_from, time.min).replace(tzinfo=timezone.utc) + # End of day (UTC) + end_dt = datetime.combine(d_to, time.max).replace(tzinfo=timezone.utc) + + start_ms = int(start_dt.timestamp() * 1000) + end_ms = int(end_dt.timestamp() * 1000) + + return f"&from={start_ms}&to={end_ms}&timezone=browser" + + # ───────── Update UI ───────── + + def _update_all(self, filtered: list[dict]) -> None: + self._update_kpis(filtered) + self._update_devices(filtered) + self._update_diseases(filtered) + if self.device_card.isVisible() and hasattr(self, "_sel_dev"): + self._render_device(self._sel_dev, filtered) + + def _update_kpis(self, data: list[dict]) -> None: + total = len(data) + if total == 0: + self.kpi_healthy.findChild(QLabel, "value").setText("0%") + self.kpi_images.findChild(QLabel, "value").setText("0") + self.kpi_devices.findChild(QLabel, "value").setText("0") + return + sick = sum(1 for r in data if _is_sick(r.get("sick"))) + healthy_pct = (total - sick) / total * 100 + devices = len({str(r.get("device_id")) for r in data if r.get("device_id")}) + self.kpi_healthy.findChild(QLabel, "value").setText(f"{healthy_pct:.1f}%") + self.kpi_images.findChild(QLabel, "value").setText(f"{total:,}") + self.kpi_devices.findChild(QLabel, "value").setText(str(devices)) + + # ── Devices: top-5 ── + + def _update_devices(self, data: list[dict]) -> None: + _clear_layout(self.devices_layout) + if not data: + return + stats = defaultdict(lambda: {"total": 0, "sick": 0}) + for r in data: + dev = r.get("device_id") + if not dev: + continue + s = stats[str(dev)] + s["total"] += 1 + if _is_sick(r.get("sick")): + s["sick"] += 1 + pairs = [(dev, (s["sick"] / s["total"] * 100.0 if s["total"] else 0.0)) for dev, s in stats.items()] + for dev, pct in sorted(pairs, key=lambda x: x[1], reverse=True)[:5]: + row = self._build_bar_row(title=str(dev), pct=pct, right_text=f"{pct:.1f}%") + row.clicked.connect(self._on_device_clicked) + self.devices_layout.addWidget(row) + + def _on_device_clicked(self, device_id: str) -> None: + """When device is clicked, hide Grafana and show device details""" + self._sel_dev = device_id + self.grafana_card.setVisible(False) # Hide Grafana if open + self._render_device(device_id, self._filter_by_dates(self._raw)) + + def _render_device(self, device_id: str, data: list[dict]) -> None: + """ + Shows diseases for selected device. + IMPORTANT: % = (sick images with this disease) / (ALL images from device) * 100 + """ + _clear_layout(self.device_layout) + + # Get all images from this device + device_data = [r for r in data if str(r.get("device_id", "")) == str(device_id)] + total_device_images = len(device_data) + + if total_device_images == 0: + self.device_card.setVisible(False) + return + + # Count sick images per disease type + disease_sick_counts = defaultdict(int) + for r in device_data: + if _is_sick(r.get("sick")): + did = r.get("leaf_disease_type_id") + if did is not None: + disease_sick_counts[str(did)] += 1 + + self.device_title.setText(f"Device: {device_id} – Disease Breakdown") + + # Calculate % of total device images + rows = [] + for did, sick_count in disease_sick_counts.items(): + pct = (sick_count / total_device_images * 100.0) if total_device_images else 0.0 + rows.append((self._disease_name(did), pct, sick_count, total_device_images)) + + # Sort by percentage and display + for name, pct, sick_cnt, total_imgs in sorted(rows, key=lambda x: x[1], reverse=True): + txt = f"{pct:.1f}% ({sick_cnt}/{total_imgs} images)" + self.device_layout.addWidget(self._build_bar_row(title=name, pct=pct, right_text=txt)) + + self.device_card.setVisible(True) + + # ── Diseases: top-3 ── + + def _update_diseases(self, data: list[dict]) -> None: + _clear_layout(self.diseases_layout) + if not data: + return + counter: Counter[str] = Counter() + for r in data: + if _is_sick(r.get("sick")): + did = r.get("leaf_disease_type_id") + if did is not None: + counter[str(did)] += 1 + total_sick = sum(counter.values()) or 1 + palette = ["#f97316", "#eab308", "#ef4444"] + for i, (did, cnt) in enumerate(counter.most_common(3)): + name = self._disease_name(did) + pct = cnt / total_sick * 100.0 + color = palette[i] if i < len(palette) else "#6366f1" + self.diseases_layout.addWidget( + self._build_tag(name=name, disease_id=str(did), color=color, pct=pct, count=cnt) + ) + + # ── Disease details: Shows embedded Grafana below ── + + def _on_disease_clicked(self, disease_id: str) -> None: + """When disease is clicked, hide device details and show Grafana below""" + disease_name = self._disease_name(disease_id) + print(f"[LeafDiseaseView] Showing Grafana for disease: {disease_name} (ID: {disease_id})") + + # Save selected disease so we can refresh on range change if needed + self._sel_disease = disease_id + + # Hide device card if open + self.device_card.setVisible(False) + + # Update Grafana title and load dashboard + self.grafana_title.setText(f"📊 Disease Analysis: {disease_name}") + + # Build Grafana URL with disease_id + date range + range_params = self._grafana_range_params() + grafana_url = ( + f"http://host.docker.internal:3000/d/leaf-disease-detail/" + f"leaf-disease-analysis" + f"?orgId=1&refresh=10s&kiosk=tv" + f"&var-disease_id={disease_id}" + f"{range_params}" + ) + + print(f"[LeafDiseaseView] Loading Grafana: {grafana_url}") + self.grafana_status.setText("📊 Loading dashboard...") + self.grafana_web.setUrl(QUrl(grafana_url)) + + # Show Grafana card + self.grafana_card.setVisible(True) + + # ───────── Reusable tiny builders ───────── + def _build_bar_row(self, title: str, pct: float, right_text: str) -> ClickableRow: + """ + Generic row: title | QProgressBar (color by pct) | right text. + Bar length represents the percentage value. + """ + row = ClickableRow(title) + h = QHBoxLayout(row) + h.setSpacing(10) + h.setContentsMargins(0, 0, 0, 0) + + # left title + name = QLabel(title) + name.setStyleSheet("font-weight: 600; min-width: 180px;") + h.addWidget(name) + + # middle: progress bar (VALUE = pct, so bar length represents percentage) + pb = QProgressBar() + pb.setRange(0, 100) + pb.setValue(int(max(0, min(100, pct)))) + pb.setTextVisible(False) + + # color chunk dynamically by severity + chunk_color = _color_for_pct(pct) # green/orange/red + pb.setStyleSheet( + "QProgressBar { background: #0b1220; border: 1px solid #1f2937; " + "border-radius: 999px; min-height: 14px; max-height: 14px; } " + f"QProgressBar::chunk {{ background: {chunk_color}; border-radius: 999px; }}" + ) + h.addWidget(pb, 1) + + # right label + r = QLabel(right_text) + r.setStyleSheet("color: #94a3b8; min-width: 110px;") + r.setAlignment(Qt.AlignmentFlag.AlignRight | Qt.AlignmentFlag.AlignVCenter) + h.addWidget(r) + + return row + + def _build_tag(self, name: str, disease_id: str, color: str, pct: float, count: int) -> ClickableTag: + row = ClickableTag(disease_id) + h = QHBoxLayout(row) + h.setSpacing(8) + h.setContentsMargins(0, 0, 0, 0) + + tag = QFrame() + tag.setStyleSheet("background: #0b1220; border: 1px solid #1f2937; border-radius: 999px; padding: 6px 10px;") + tag_h = QHBoxLayout(tag) + tag_h.setSpacing(8) + tag_h.setContentsMargins(6, 4, 6, 4) + + dot = QLabel("●") + dot.setStyleSheet(f"color: {color}; font-size: 16px;") + disp = name if len(name) <= 25 else name[:25] + "…" + tag_h.addWidget(dot) + tag_h.addWidget(QLabel(disp)) + + h.addWidget(tag) + h.addStretch() + + pct_lbl = QLabel(f"{pct:.0f}% ({count} reports)") + pct_lbl.setStyleSheet("color: #94a3b8; font-size: 13px;") + h.addWidget(pct_lbl) + + row.clicked.connect(self._on_disease_clicked) + return row + + # ───────── Naming ───────── + + def _disease_name(self, disease_id: str | int | None) -> str: + if disease_id is None: + return "Unknown Disease" + return self._types.get(str(disease_id), f"Disease #{disease_id}") \ No newline at end of file diff --git a/GUI/src/vast/views/security/analytics/analytics_page.py b/GUI/src/vast/views/security/analytics/analytics_page.py new file mode 100644 index 000000000..0bf2ae31e --- /dev/null +++ b/GUI/src/vast/views/security/analytics/analytics_page.py @@ -0,0 +1,561 @@ +from __future__ import annotations +from datetime import date + +from PyQt6.QtWidgets import ( + QWidget, QVBoxLayout, QHBoxLayout, QLabel, QComboBox, + QPushButton, QDateEdit, QFrame, QSizePolicy, + QGraphicsDropShadowEffect, QSplitter, QLineEdit, QMessageBox, QApplication +) +from PyQt6.QtCore import Qt, QDate +from PyQt6.QtGui import QColor +from PyQt6 import QtCore + +from orthophoto_canvas.ui.viewer_factory import create_orthophoto_viewer +from src.vast.views.security.analytics.map_layers.region_layer import RegionLayer +from src.vast.views.security.analytics.map_layers.device_layer import DeviceLayer +from src.vast.views.security.analytics.analytics_provider import ( + load_all_devices, load_all_regions, + get_region_analytics, get_device_analytics +) +from src.vast.views.security.analytics.popup_panel import AnalyticsPanel +from src.vast.views.security.analytics import analytics_provider as ap + + +class AgGuardMessageBox(QFrame): + def __init__(self, parent=None, title="Message", text=""): + super().__init__(parent) + + self.setWindowFlags( + Qt.WindowType.Dialog | + Qt.WindowType.FramelessWindowHint | + Qt.WindowType.WindowStaysOnTopHint + ) + # no translucent background → no black corners + self.setAutoFillBackground(True) + pal = self.palette() + pal.setColor(self.backgroundRole(), QColor("#fefefe")) + self.setPalette(pal) + + # Light drop shadow + shadow = QGraphicsDropShadowEffect() + shadow.setBlurRadius(28) + shadow.setOffset(0, 3) + shadow.setColor(QColor(200, 200, 200, 90)) + self.setGraphicsEffect(shadow) + + self.setStyleSheet(""" + QFrame { + background-color: #fefefe; + border-radius: 16px; + border: 1px solid #f3f4f6; + } + QLabel#title { + font-size: 18px; + font-weight: 700; + color: #1f2937; + } + QLabel#text { + font-size: 14px; + color: #4b5563; + } + QPushButton#ok_btn { + background-color: #10b981; + color: white; + border-radius: 10px; + padding: 6px 18px; + font-weight: 600; + min-width: 80px; + } + QPushButton#ok_btn:hover { + background-color: #059669; + } + """) + + layout = QVBoxLayout(self) + layout.setContentsMargins(22, 22, 22, 22) + layout.setSpacing(14) + + title_lbl = QLabel(title) + title_lbl.setObjectName("title") + + text_lbl = QLabel(text) + text_lbl.setObjectName("text") + text_lbl.setWordWrap(True) + + btn = QPushButton("OK") + btn.setObjectName("ok_btn") + btn.clicked.connect(self.close) + + layout.addWidget(title_lbl) + layout.addWidget(text_lbl) + layout.addStretch() + layout.addWidget(btn, alignment=Qt.AlignmentFlag.AlignRight) + + self.adjustSize() + self.setMinimumWidth(360) + + def show_centered(self): + if self.parent(): + parent_geo = self.parent().geometry() + x = parent_geo.x() + (parent_geo.width() - self.width()) // 2 + y = parent_geo.y() + (parent_geo.height() - self.height()) // 2 + self.move(x, y) + self.show() + + +class GeoAnalyticsView(QWidget): + """Geo-Analytics Dashboard with fixed analytics panel and multi-selection.""" + + def __init__(self, parent: QWidget | None = None): + super().__init__(parent) + self.current_mode = "region" + self.start_date: date | None = None + self.end_date: date | None = None + self.selected_regions = set() + self.selected_devices = set() + + # ───────────────────────────── + # GLOBAL STYLE + # ───────────────────────────── + self.setStyleSheet(""" + QWidget { + background-color: #f9fafb; + font-family: 'Segoe UI', 'DejaVu Sans', Arial, sans-serif; + color: #111827; + font-size: 14px; + } + QComboBox, QDateEdit { + background-color: #ffffff; + border: 1px solid #d1d5db; + border-radius: 8px; + padding: 4px 10px; + font-size: 13px; + height: 32px; + min-width: 120px; + color: #111827; + } + QComboBox:hover, QDateEdit:hover { + border-color: #9ca3af; + background-color: #f9fafb; + } + QPushButton#apply_btn { + background-color: #10b981; + color: white; + border-radius: 6px; + font-weight: 600; + padding: 6px 12px; + } + QPushButton#apply_btn:hover { background-color: #059669; } + """) + + # ───────────────────────────── + # ROOT LAYOUT + # ───────────────────────────── + root = QVBoxLayout(self) + root.setContentsMargins(16, 16, 16, 16) + root.setSpacing(12) + self.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + + # Header + header = QLabel("🗺️ Geo-Analytics Dashboard") + header.setStyleSheet("font-size:22px;font-weight:700;color:#0f172a;") + root.addWidget(header) + + # ───────────────────────────── + # FILTER BAR + # ───────────────────────────── + filter_frame = QFrame() + filter_frame.setStyleSheet(""" + QFrame { + background-color: #ffffff; + border: 1px solid #d1d5db; + border-radius: 12px; + padding: 10px 14px; + } + """) + shadow = QGraphicsDropShadowEffect() + shadow.setBlurRadius(12) + shadow.setOffset(0, 2) + shadow.setColor(QColor(0, 0, 0, 40)) + filter_frame.setGraphicsEffect(shadow) + + filter_bar = QHBoxLayout(filter_frame) + filter_bar.setSpacing(14) + filter_bar.setContentsMargins(10, 6, 10, 6) + + lbl_mode = QLabel("Mode:") + self.mode_combo = QComboBox() + self.mode_combo.addItems(["Region", "Device"]) + self.mode_combo.currentTextChanged.connect(self._on_mode_changed) + + lbl_date = QLabel("Date range:") + self.start_picker = QDateEdit(QDate.currentDate().addMonths(-1)) + self.start_picker.setCalendarPopup(True) + arrow_lbl = QLabel("→") + self.end_picker = QDateEdit(QDate.currentDate()) + self.end_picker.setCalendarPopup(True) + + apply_btn = QPushButton("Apply Filters") + apply_btn.setObjectName("apply_btn") + apply_btn.clicked.connect(self._apply_filters) + + filter_bar.addWidget(lbl_mode) + filter_bar.addWidget(self.mode_combo) + filter_bar.addSpacing(12) + filter_bar.addWidget(lbl_date) + filter_bar.addWidget(self.start_picker) + filter_bar.addWidget(arrow_lbl) + filter_bar.addWidget(self.end_picker) + filter_bar.addSpacing(12) + filter_bar.addWidget(apply_btn) + filter_bar.addStretch() + root.addWidget(filter_frame) + + # ───────────────────────────── + # AI QUERY BAR + # ───────────────────────────── + query_frame = QFrame() + query_frame.setStyleSheet(""" + QFrame { + background-color: #ffffff; + border: 1px solid #e5e7eb; + border-radius: 18px; + padding: 10px 12px; + } + QLineEdit { + background-color: qlineargradient( + x1:0, y1:0, x2:0, y2:1, + stop:0 #ffffff, stop:1 #f9fafb + ); + border: 1px solid #d1d5db; + border-radius: 18px; + padding: 8px 16px; + font-size: 14px; + color: #111827; + selection-background-color: #bae6fd; + } + QLineEdit:focus { + border-color: #10b981; + background-color: #ffffff; + box-shadow: 0 0 0 3px rgba(16,185,129,0.2); + } + QPushButton#send_btn { + background-color: #10b981; + color: white; + font-weight: 600; + border-radius: 18px; + padding: 0 18px; + border: none; + min-width: 80px; + height: 38px; + } + QPushButton#send_btn:hover { + background-color: #059669; + } + """) + + query_layout = QHBoxLayout(query_frame) + query_layout.setSpacing(8) + query_layout.setContentsMargins(10, 6, 10, 6) + + self.query_input = QLineEdit() + self.query_input.setPlaceholderText("Ask anything — e.g. 'Show regions with most intrusions this month'") + self.query_input.setClearButtonEnabled(True) + self.query_input.setMinimumWidth(420) + self.query_input.setFixedHeight(38) + + self.query_send = QPushButton("Send") + self.query_send.setObjectName("send_btn") + self.query_send.clicked.connect(self._on_query_sent) + + query_layout.addWidget(self.query_input, stretch=1) + query_layout.addWidget(self.query_send) + + query_shadow = QGraphicsDropShadowEffect() + query_shadow.setBlurRadius(22) + query_shadow.setOffset(0, 3) + query_shadow.setColor(QColor(0, 0, 0, 50)) + query_frame.setGraphicsEffect(query_shadow) + + # ───────────────────────────── + # MAIN SPLITTER (map + analytics) + # ───────────────────────────── + splitter = QSplitter(Qt.Orientation.Horizontal) + splitter.setChildrenCollapsible(False) + splitter.setHandleWidth(6) + splitter.setStretchFactor(0, 3) + splitter.setStretchFactor(1, 1) + splitter.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + splitter.setStyleSheet(""" + QSplitter::handle { + background-color: #e5e7eb; + } + QSplitter::handle:hover { + background-color: #10b981; + } + """) + + # ───────────────────────────── + # LEFT SIDE — map card + query box + # ───────────────────────────── + map_container = QWidget() + map_container_layout = QVBoxLayout(map_container) + map_container_layout.setContentsMargins(0, 0, 0, 0) + map_container_layout.setSpacing(0) + + # Outer shell (white card with strong round corners + shadow) + map_shell = QFrame() + map_shell.setObjectName("mapShell") + map_shell.setStyleSheet(""" + QFrame#mapShell { + background-color: #ffffff; + border-radius: 24px; + border: 1px solid #e5e7eb; + } + """) + map_shell_shadow = QGraphicsDropShadowEffect() + map_shell_shadow.setBlurRadius(26) + map_shell_shadow.setOffset(0, 8) + map_shell_shadow.setColor(QColor(15, 23, 42, 55)) + map_shell.setGraphicsEffect(map_shell_shadow) + + shell_layout = QVBoxLayout(map_shell) + shell_layout.setContentsMargins(14, 14, 14, 14) + shell_layout.setSpacing(10) + + # Inner rounded frame that actually clips the map + map_frame = QFrame() + map_frame.setObjectName("mapFrame") + map_frame.setStyleSheet(""" + QFrame#mapFrame { + background-color: #020617; /* dark slate */ + border-radius: 18px; + border: none; + } + """) + map_frame.setContentsMargins(0, 0, 0, 0) + map_frame_layout = QVBoxLayout(map_frame) + map_frame_layout.setContentsMargins(0, 0, 0, 0) + map_frame_layout.setSpacing(0) + + tiles_root = "./src/vast/orthophoto_canvas/data/tiles" + self.viewer = create_orthophoto_viewer(tiles_root, forced_scheme=None, parent=self) + + # Make the view itself frameless and rounded + self.viewer.setFrameShape(QFrame.Shape.NoFrame) + self.viewer.setStyleSheet(""" + QGraphicsView { + background-color: transparent; + border: none; + } + QGraphicsView::viewport { + border-radius: 18px; /* real rounded viewport */ + background-color: #020617; + } + """) + self.viewer.setAttribute(Qt.WidgetAttribute.WA_StyledBackground, True) + + # Optional static background instead of tiles + self.viewer.set_custom_background_image( + "./src/vast/orthophoto_canvas/ui/fields.png", + hide_tiles=True + ) + self.viewer.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + + map_frame_layout.addWidget(self.viewer, stretch=1) + + # Query bar sits under the map, inside the same shell + query_frame.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Fixed) + + shell_layout.addWidget(map_frame, stretch=1) + shell_layout.addWidget(query_frame, stretch=0) + + map_container_layout.addWidget(map_shell) + splitter.addWidget(map_container) + + + # ───────────────────────────── + # RIGHT SIDE — analytics panel + # ───────────────────────────── + self.analytics_panel = AnalyticsPanel("All Regions", {}, parent=self) + self.analytics_panel.setSizePolicy(QSizePolicy.Policy.Preferred, QSizePolicy.Policy.Expanding) + splitter.addWidget(self.analytics_panel) + + root.addWidget(splitter, stretch=1) + + # ───────────────────────────── + # MAP LAYERS + # ───────────────────────────── + self.region_layer = RegionLayer(self.viewer, on_select=self._on_region_selected) + self.device_layer = DeviceLayer(self.viewer, on_select=self._on_device_selected) + + # Initial load + self._load_regions() + self._update_analytics_panel() + self._initial_fit_done = False + QtCore.QTimer.singleShot(0, self._fit_map_to_container) + + # Ensure map always fills its container nicely + def resizeEvent(self, event): + super().resizeEvent(event) + QtCore.QTimer.singleShot(0, self._fit_map_to_container) + + def _fit_map_to_container(self): + """ + Make the map fill the entire map container (no gray bars). + Run after layouts/child resizes using QTimer.singleShot. + """ + if not hasattr(self, "viewer") or self.viewer is None: + return + + scene_rect = self.viewer.scene.sceneRect() + if scene_rect.isNull(): + return + + self.viewer.fitInView(scene_rect, Qt.AspectRatioMode.KeepAspectRatioByExpanding) + self.viewer.centerOn(scene_rect.center()) + + # ───────────────────────────── + # FREE TEXT QUERY HANDLER + # ───────────────────────────── + def _on_query_sent(self): + prompt = self.query_input.text().strip() + if not prompt: + QMessageBox.information(self, "Empty query", "Please type a query first.") + return + + # Change button state + self.query_send.setEnabled(False) + self.query_send.setText("...") + QApplication.processEvents() + + try: + result = ap.select_entities_from_prompt(prompt) + except Exception as e: + dlg = AgGuardMessageBox( + self, + title="Invalid Query", + text="We couldn't understand your request.\nPlease try rephrasing your query or using clearer terms." + ) + dlg.show_centered() + + # restore state and abort + self.query_send.setEnabled(True) + self.query_send.setText("Send") + return + + # Restore state + self.query_send.setEnabled(True) + self.query_send.setText("Send") + + if not result["ids"]: + QMessageBox.information(self, "No results", "No matching regions or devices found.") + return + + if result["target"] == "region": + self.current_mode = "region" + self.mode_combo.setCurrentText("Region") + self._update_layer_visibility() + self.device_layer.clear() + self.selected_regions = set(map(int, result["ids"])) + self.region_layer.clear() + self._load_regions(self.start_picker.date().toPyDate(), + self.end_picker.date().toPyDate()) + + elif result["target"] == "device": + self.current_mode = "device" + self.mode_combo.setCurrentText("Device") + self._update_layer_visibility() + self.region_layer.clear() + self.selected_devices = set(map(str, result["ids"])) + self.device_layer.clear() + self._load_devices( + self.start_picker.date().toPyDate(), + self.end_picker.date().toPyDate(), + selected_ids=self.selected_devices + ) + + self._update_analytics_panel() + + # ───────────────────────────── + # MODE / FILTERS + # ───────────────────────────── + def _on_mode_changed(self, text: str): + self.current_mode = text.lower() + if self.current_mode == "region": + self.device_layer.clear() + else: + self.region_layer.clear() + self._update_layer_visibility() + self._apply_filters() + + def _apply_filters(self): + self.start_date = self.start_picker.date().toPyDate() + self.end_date = self.end_picker.date().toPyDate() + self.region_layer.clear() + self.device_layer.clear() + self.selected_regions.clear() + self.selected_devices.clear() + self._update_layer_visibility() + if self.current_mode == "region": + self._load_regions(self.start_date, self.end_date) + else: + self._load_devices(self.start_date, self.end_date) + self._update_analytics_panel() + + # ───────────────────────────── + # LOADERS + # ───────────────────────────── + def _load_regions(self, start_date=None, end_date=None): + regions = load_all_regions() + self.region_names = {r["id"]: r["name"] for r in regions} + for region in regions: + self.region_layer.add_region(region, start_date, end_date, selected_ids=self.selected_regions) + + def _load_devices(self, start_date=None, end_date=None, selected_ids=None): + devices = load_all_devices() + for device in devices: + device_id = device["device_id"] + selected = selected_ids and device_id in selected_ids + self.device_layer.add_device(device, start_date, end_date, selected=selected) + + # ───────────────────────────── + # SELECTION HANDLERS + # ───────────────────────────── + def _on_region_selected(self, region_id: int, selected: bool): + if selected: + self.selected_regions.add(region_id) + else: + self.selected_regions.discard(region_id) + self._update_analytics_panel() + + def _on_device_selected(self, device_id: str, selected: bool): + if selected: + self.selected_devices.add(device_id) + else: + self.selected_devices.discard(device_id) + self._update_analytics_panel() + + # ───────────────────────────── + # ANALYTICS UPDATE + # ───────────────────────────── + def _update_analytics_panel(self): + if self.current_mode == "region": + region_list = list(self.selected_regions) + data = get_region_analytics(region_list or None, self.start_date, self.end_date) + title = "All Regions" if not region_list else ", ".join( + self.region_names.get(rid, str(rid)) for rid in region_list) + self.analytics_panel.update_data(title, data) + else: + device_list = list(self.selected_devices) + data = get_device_analytics(device_list or None, self.start_date, self.end_date) + title = "All Devices" if not device_list else ", ".join(device_list) + self.analytics_panel.update_data(title, data) + + def _update_layer_visibility(self): + if self.current_mode == "region": + self.region_layer.setVisible(True) + self.device_layer.setVisible(False) + else: + self.region_layer.setVisible(False) + self.device_layer.setVisible(True) diff --git a/GUI/src/vast/views/security/analytics/analytics_provider.py b/GUI/src/vast/views/security/analytics/analytics_provider.py new file mode 100644 index 000000000..9c9b9a599 --- /dev/null +++ b/GUI/src/vast/views/security/analytics/analytics_provider.py @@ -0,0 +1,333 @@ + + +from datetime import date +from sqlalchemy import create_engine, text +from datetime import datetime, timedelta + +# ───────────────────────────────────────────── +# Database Connection +# ───────────────────────────────────────────── +engine = create_engine( + "postgresql+psycopg2://missions_user:pg123@postgres:5432/missions_db", + echo=False +) + +# ───────────────────────────────────────────── +# Load all regions & devices +# ───────────────────────────────────────────── +def load_all_regions() -> list[dict]: + """Return all regions with ID, name, and geometry.""" + query = text(""" + SELECT id, name, ST_AsGeoJSON(geom) AS geom + FROM regions + ORDER BY id; + """) + with engine.connect() as conn: + return [dict(row) for row in conn.execute(query).mappings().all()] + + +def load_all_devices() -> list[dict]: + """Return all devices with ID, model, owner, and coordinates.""" + query = text(""" + SELECT device_id, model, owner, active, + location_lat, location_lon + FROM devices + WHERE owner = 'security' + ORDER BY device_id; + """) + with engine.connect() as conn: + return [dict(row) for row in conn.execute(query).mappings().all()] + +# ───────────────────────────────────────────── +# DEVICE ANALYTICS (supports multiple or all devices) +# ───────────────────────────────────────────── +def get_device_analytics(device_ids=None, start_date=None, end_date=None) -> dict: + """ + Return aggregated alert analytics for one or more devices. + If device_ids is None or empty, aggregates all devices. + """ + if isinstance(device_ids, str): + device_ids = [device_ids] + + # Default to full current year range if missing + if not start_date: + start_date = date.today().replace(day=1, month=1) + if not end_date: + end_date = date.today() + + # Convert to datetime range that includes the entire end day + start_dt = datetime.combine(start_date, datetime.min.time()) + end_dt = datetime.combine(end_date + timedelta(days=1), datetime.min.time()) + + + with engine.connect() as conn: + params = {"device_ids": device_ids or [], + "start_date": start_dt, + "end_date": end_dt} + + + if device_ids: + device_filter = "AND device_id = ANY(:device_ids)" + else: + device_filter = "" # ← no filter means aggregate all devices + params.pop("device_ids", None) + + + # Alerts by Type + q_by_type = text(f""" + SELECT alert_type, COUNT(*) AS count + FROM alerts + WHERE started_at BETWEEN :start_date AND :end_date + {device_filter} + GROUP BY alert_type + ORDER BY count DESC; + """) + by_type = {r["alert_type"] or "Unknown": r["count"] + for r in conn.execute(q_by_type, params).mappings().all()} + + # Alerts per Month + q_month = text(f""" + WITH months AS ( + SELECT TO_CHAR(gs, 'YYYY-MM') AS month + FROM generate_series( + date_trunc('month', CAST(:start_date AS timestamp)), + date_trunc('month', CAST(:end_date AS timestamp)), + interval '1 month' + ) AS gs + ), + alert_counts AS ( + SELECT TO_CHAR(started_at, 'YYYY-MM') AS month, COUNT(*) AS count + FROM alerts + WHERE started_at BETWEEN :start_date AND :end_date + {device_filter} + GROUP BY TO_CHAR(started_at, 'YYYY-MM') + ) + SELECT m.month, COALESCE(ac.count, 0) AS count + FROM months m + LEFT JOIN alert_counts ac ON ac.month = m.month + ORDER BY m.month; + """) + per_month = {r["month"]: r["count"] + for r in conn.execute(q_month, params).mappings().all()} + + # Totals & averages + q_total = text(f""" + SELECT COUNT(*) AS total, + AVG(severity)::numeric(10,2) AS avg_severity, + AVG(confidence)::numeric(10,2) AS avg_confidence + FROM alerts + WHERE started_at BETWEEN :start_date AND :end_date + {device_filter}; + """) + total = conn.execute(q_total, params).mappings().first() or {} + q_avg_duration = text(f""" + SELECT alert_type, + ROUND(AVG(EXTRACT(EPOCH FROM (ended_at - started_at)) / 60.0), 2) AS avg_minutes + FROM alerts + WHERE started_at BETWEEN :start_date AND :end_date + {device_filter} + AND ended_at IS NOT NULL + GROUP BY alert_type + ORDER BY avg_minutes DESC; + """) + + avg_duration = { + r["alert_type"] or "Unknown": float(r["avg_minutes"] or 0) + for r in conn.execute(q_avg_duration, params).mappings().all() + } + + + return { + "alerts_by_type": by_type, + "alerts_per_month": per_month, + "total_alerts": total.get("total", 0), + "avg_severity": float(total.get("avg_severity") or 0), + "avg_confidence": float(total.get("avg_confidence") or 0), + "avg_duration_per_type": avg_duration, # ← NEW + } + +# ───────────────────────────────────────────── +# REGION ANALYTICS (supports multiple or all regions) +# ───────────────────────────────────────────── +def get_region_analytics(region_ids=None, start_date=None, end_date=None) -> dict: + """ + Aggregates analytics for one or more regions (using PostGIS ST_Intersects). + If region_ids is None or empty, aggregates all regions. + """ + if isinstance(region_ids, (str, int)): + region_ids = [region_ids] + + # Default to full current year range if missing + if not start_date: + start_date = date.today().replace(day=1, month=1) + if not end_date: + end_date = date.today() + + # Convert to datetime range that includes the entire end day + start_dt = datetime.combine(start_date, datetime.min.time()) + end_dt = datetime.combine(end_date + timedelta(days=1), datetime.min.time()) + + + with engine.connect() as conn: + params = { + "region_ids": region_ids or [], + "start_date": start_dt, + "end_date": end_dt, +} + + + # Optional region filter + if region_ids: + region_filter = "AND r.id = ANY(:region_ids)" + else: + region_filter = "" # no filter → aggregate all regions + params.pop("region_ids", None) + + # Alerts by Type + q_by_type = text(f""" + SELECT a.alert_type, COUNT(*) AS count + FROM alerts a + JOIN devices d ON a.device_id = d.device_id + JOIN regions r + ON ST_Intersects(ST_Buffer(r.geom, 0.0002), ST_SetSRID(ST_MakePoint(d.location_lon, d.location_lat), 4326)) + WHERE a.started_at BETWEEN :start_date AND :end_date + {region_filter} + GROUP BY a.alert_type + ORDER BY count DESC; + """) + print(q_by_type,region_filter) + by_type = {r["alert_type"] or "Unknown": r["count"] + for r in conn.execute(q_by_type, params).mappings().all()} + + # Alerts per Month + q_month = text(f""" + WITH months AS ( + SELECT TO_CHAR(gs, 'YYYY-MM') AS month + FROM generate_series( + date_trunc('month', CAST(:start_date AS timestamp)), + date_trunc('month', CAST(:end_date AS timestamp)), + interval '1 month' + ) AS gs + ), + alert_counts AS ( + SELECT TO_CHAR(a.started_at, 'YYYY-MM') AS month, COUNT(*) AS count + FROM alerts a + JOIN devices d ON a.device_id = d.device_id + JOIN regions r + ON ST_Intersects(ST_Buffer(r.geom, 0.0002), ST_SetSRID(ST_MakePoint(d.location_lon, d.location_lat), 4326)) + WHERE a.started_at BETWEEN :start_date AND :end_date + {region_filter} + GROUP BY TO_CHAR(a.started_at, 'YYYY-MM') + ) + SELECT m.month, COALESCE(ac.count, 0) AS count + FROM months m + LEFT JOIN alert_counts ac ON ac.month = m.month + ORDER BY m.month; + """) + per_month = {r["month"]: r["count"] + for r in conn.execute(q_month, params).mappings().all()} + + # Totals & averages + q_total = text(f""" + SELECT COUNT(*) AS total, + AVG(a.severity)::numeric(10,2) AS avg_severity, + AVG(a.confidence)::numeric(10,2) AS avg_confidence + FROM alerts a + JOIN devices d ON a.device_id = d.device_id + JOIN regions r + ON ST_Intersects(ST_Buffer(r.geom, 0.0002), ST_SetSRID(ST_MakePoint(d.location_lon, d.location_lat), 4326)) + WHERE a.started_at BETWEEN :start_date AND :end_date + {region_filter}; + """) + total = conn.execute(q_total, params).mappings().first() or {} + + q_avg_duration = text(f""" + SELECT a.alert_type, + ROUND(AVG(EXTRACT(EPOCH FROM (a.ended_at - a.started_at)) / 60.0), 2) AS avg_minutes + FROM alerts a + JOIN devices d ON a.device_id = d.device_id + JOIN regions r + ON ST_Intersects( + ST_Buffer(r.geom, 0.0002), + ST_SetSRID(ST_MakePoint(d.location_lon, d.location_lat), 4326) + ) + WHERE a.started_at BETWEEN :start_date AND :end_date + {region_filter} + AND a.ended_at IS NOT NULL + GROUP BY a.alert_type + ORDER BY avg_minutes DESC; + """) + avg_duration = { + r["alert_type"] or "Unknown": float(r["avg_minutes"] or 0) + for r in conn.execute(q_avg_duration, params).mappings().all() + } + + + return { + "alerts_by_type": by_type, + "alerts_per_month": per_month, + "total_alerts": total.get("total", 0), + "avg_severity": float(total.get("avg_severity") or 0), + "avg_confidence": float(total.get("avg_confidence") or 0), + "avg_duration_per_type": avg_duration, # ← NEW + } + + +# ───────────────────────────────────────────── +# NATURAL LANGUAGE QUERY SUPPORT +# ───────────────────────────────────────────── +from src.vast.views.security.analytics.sql_generator import generate_sql_from_prompt + + + +def select_entities_from_prompt(prompt: str) -> dict: + """ + Uses the AI SQL generator to convert free-text query → SQL, + executes it, and returns matching entity IDs. + + Returns a dict: + { + "target": "region" | "device" | None, + "ids": [list of IDs] + } + """ + sql, params = generate_sql_from_prompt(prompt) + print(sql,params) + if not sql: + return {"target": None, "ids": []} + + with engine.connect() as conn: + rows = [r[0] for r in conn.execute(text(sql), params)] + + + sql_lower = sql.lower() + if "area" in sql_lower or "region" in sql_lower: + target = "region" + elif "device_id" in sql_lower: + target = "device" + else: + target = "region" if "from regions" in sql_lower else "device" + + import re + + if target == "region": + # Normalize region names to lowercase without spaces/underscores for fuzzy match + def normalize(name: str) -> str: + return re.sub(r'[^a-z0-9]', '', name.lower()) + + region_map = {normalize(r["name"]): r["id"] for r in load_all_regions()} + + mapped = [] + for r in rows: + if isinstance(r, (int, float)): + mapped.append(int(r)) + elif isinstance(r, str): + key = normalize(r) + if key in region_map: + mapped.append(region_map[key]) + rows = mapped + + + return {"target": target, "ids": rows} + + diff --git a/GUI/src/vast/views/security/analytics/map_layers/__init__.py b/GUI/src/vast/views/security/analytics/map_layers/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/GUI/src/vast/views/security/analytics/map_layers/device_layer.py b/GUI/src/vast/views/security/analytics/map_layers/device_layer.py new file mode 100644 index 000000000..127249c81 --- /dev/null +++ b/GUI/src/vast/views/security/analytics/map_layers/device_layer.py @@ -0,0 +1,179 @@ +from PyQt6.QtWidgets import QGraphicsTextItem, QGraphicsDropShadowEffect +from PyQt6.QtGui import QColor, QFont +from PyQt6.QtCore import Qt +from src.vast.orthophoto_canvas.ui.sensors_layer import TILE_SIZE, _latlon_to_xy_at_max_zoom + +from PyQt6.QtWidgets import QGraphicsTextItem, QGraphicsDropShadowEffect, QGraphicsColorizeEffect +from PyQt6.QtGui import QColor, QFont, QFontMetrics +from PyQt6.QtCore import Qt, QPropertyAnimation, QEasingCurve + + +# ───────────────────────────────────────────── +# 🗺️ Device Layer +# ───────────────────────────────────────────── +class DeviceLayer: + """Draws device (camera) markers on the orthophoto scene.""" + + def __init__(self, viewer, on_select=None): + self.viewer = viewer + self.scene = viewer.scene + self.devices = {} + self.on_select = on_select + + # Match RegionLayer & AlertLayer → use MAX zoom base tiles + z = viewer.max_zoom_fs + self._x_min_base = viewer.ts.z_ranges[z][0] + self._y_min_base = viewer.ts.z_ranges[z][2] + + def add_device(self, device: dict, start_date=None, end_date=None, selected=False): + + """Add a device marker to the orthophoto scene.""" + lat = device.get("location_lat") + lon = device.get("location_lon") + + # Convert to base XY in max zoom coordinate space + pos = _latlon_to_xy_at_max_zoom(self.viewer, lat, lon) + if not pos: + print(f"[DeviceLayer] ⚠️ Device {device.get('device_id')} outside field bounds") + return + + xb, yb = pos + scene_x = (xb - self._x_min_base) * TILE_SIZE + scene_y = (yb - self._y_min_base) * TILE_SIZE + marker = _Camera360Marker( + device["device_id"], + device.get("active", True), + self.on_select, + radius=10.0, # tweak for size + ) + marker.setPos(scene_x, scene_y) + self.scene.addItem(marker) + + self.devices[device["device_id"]] = marker + + if selected: + marker.selected = True + marker.setFont(QFont("Noto Color Emoji", 18)) + marker.setDefaultTextColor(marker.selected_color) + marker.setGraphicsEffect(marker.halo) + marker.pulse.start() + + print(f"[DeviceLayer] ✅ Added device '{device['device_id']}' at ({scene_x:.1f}, {scene_y:.1f})") + + def clear(self): + """Remove all device markers.""" + for item in self.devices.values(): + self.scene.removeItem(item) + self.devices.clear() + print("[DeviceLayer] Cleared all devices") + def setVisible(self, visible: bool): + """Show or hide all device markers.""" + for item in self.devices.values(): + item.setVisible(visible) + print(f"[DeviceLayer] Visibility set to {visible}") +from PyQt6.QtWidgets import QGraphicsObject, QGraphicsDropShadowEffect +from PyQt6.QtGui import QColor, QPen, QBrush, QPainter +from PyQt6.QtCore import QRectF, QPropertyAnimation, QEasingCurve, pyqtSlot + + +class _Camera360Marker(QGraphicsObject): + """360° camera marker: donut + center dot + glow + pulse.""" + + def __init__(self, device_id: str, active: bool, on_select=None, radius: float = 10.0): + super().__init__() + self.device_id = device_id + self.active = active + self.on_select = on_select + self.selected = False + self._radius = radius + + # Colors + self.normal_color = QColor("#10b981") if active else QColor("#9ca3af") # green / gray + self.alert_color = QColor("#ef4444") # red for alerts if you use it + self.selected_color = QColor("#ffffff") + + # We draw in local coords around (0,0); QGraphicsView will position us + self.setZValue(1000) + self.setFlag(self.GraphicsItemFlag.ItemIgnoresTransformations, True) # stay same size on zoom + self.setAcceptHoverEvents(True) + + # Drop shadow halo for glow + self.halo = QGraphicsDropShadowEffect() + self.halo.setBlurRadius(32) + self.halo.setOffset(0, 0) + self.halo.setColor(QColor(16, 185, 129, 180)) + self.setGraphicsEffect(None) # only on selection + + # Pulse animation on opacity + self.pulse = QPropertyAnimation(self, b"opacity") + self.pulse.setDuration(1000) + self.pulse.setStartValue(1.0) + self.pulse.setEndValue(0.6) + self.pulse.setEasingCurve(QEasingCurve.Type.InOutQuad) + self.pulse.setLoopCount(-1) + + # ───────────────────────────────────────────── + # Required overrides + # ───────────────────────────────────────────── + def boundingRect(self) -> QRectF: + # a bit larger than radius to accommodate the stroke + halo + r = self._radius + 4 + return QRectF(-r, -r, 2 * r, 2 * r) + + def paint(self, painter: QPainter, option, widget=None): + painter.setRenderHint(QPainter.RenderHint.Antialiasing, True) + + # Base color depends on state + base = self.normal_color if not self.selected else self.normal_color + + # Outer ring (donut) + outer_r = self._radius + inner_r = self._radius * 0.55 + + # Outer circle stroke + pen = QPen(base) + pen.setWidthF(2.0 if not self.selected else 3.0) + painter.setPen(pen) + painter.setBrush(Qt.BrushStyle.NoBrush) + painter.drawEllipse(QRectF(-outer_r, -outer_r, 2 * outer_r, 2 * outer_r)) + + # Soft filled ring (semi-transparent) + ring_color = QColor(base.red(), base.green(), base.blue(), 80) + painter.setBrush(QBrush(ring_color)) + painter.setPen(Qt.PenStyle.NoPen) + painter.drawEllipse(QRectF(-outer_r, -outer_r, 2 * outer_r, 2 * outer_r)) + + # Cut inner circle to make donut effect (by drawing a solid inner circle of background color) + inner_bg = QColor("#0f172a") # same tone as map background / dark outline + painter.setBrush(inner_bg) + painter.drawEllipse(QRectF(-inner_r, -inner_r, 2 * inner_r, 2 * inner_r)) + + # Center dot – represents the physical camera + center_r = inner_r * 0.5 + painter.setBrush(base if not self.selected else self.selected_color) + painter.setPen(Qt.PenStyle.NoPen) + painter.drawEllipse(QRectF(-center_r, -center_r, 2 * center_r, 2 * center_r)) + + # ───────────────────────────────────────────── + # Interaction + # ───────────────────────────────────────────── + def mousePressEvent(self, event): + self.toggle_selected() + if self.on_select: + self.on_select(self.device_id, self.selected) + super().mousePressEvent(event) + + @pyqtSlot() + def toggle_selected(self): + self.selected = not self.selected + + if self.selected: + # enable glow + pulse + self.setGraphicsEffect(self.halo) + self.pulse.start() + else: + # disable glow + pulse + self.setGraphicsEffect(None) + self.pulse.stop() + self.setOpacity(1.0) + self.update() diff --git a/GUI/src/vast/views/security/analytics/map_layers/region_layer.py b/GUI/src/vast/views/security/analytics/map_layers/region_layer.py new file mode 100644 index 000000000..b457c5e6c --- /dev/null +++ b/GUI/src/vast/views/security/analytics/map_layers/region_layer.py @@ -0,0 +1,186 @@ +from __future__ import annotations + +import json +from typing import List, Optional, Tuple + +from PyQt6.QtWidgets import QGraphicsPolygonItem +from PyQt6.QtGui import QColor, QPen, QPolygonF +from PyQt6.QtCore import Qt, QPointF + +from src.vast.orthophoto_canvas.ui.sensors_layer import ( + TILE_SIZE, + _latlon_to_xy_at_max_zoom, +) + + +class RegionLayer: + """ + Draws farm regions as interactive polygons positioned by GPS coordinates. + Uses tile-based projection when possible, and falls back to a linear + lon/lat → scene mapping based on the known map coverage if needed. + """ + + def __init__(self, viewer, on_select=None): + self.viewer = viewer + self.scene = viewer.scene + self.regions: List[QGraphicsPolygonItem] = [] + self.on_select = on_select + + # Base tile indices at MAX zoom (same as OrthophotoViewer scene) + z = viewer.max_zoom_fs + self._x_min_base = viewer.ts.z_ranges[z][0] + self._y_min_base = viewer.ts.z_ranges[z][2] + + # Scene boundary in scene coordinates (0,0) → (width,height) + width = (viewer.ts.z_ranges[z][1] - self._x_min_base + 1) * TILE_SIZE + height = (viewer.ts.z_ranges[z][3] - self._y_min_base + 1) * TILE_SIZE + self._scene_width = width + self._scene_height = height + + # For reference; not used for clipping anymore + self.scene_bounds = (0, 0, width, height) + + # 🔹 Map lon/lat bounds – SAME as you used in your SQL + # [COVERAGE z=18] lon:[34.844513..34.855499] lat:[31.895049..31.904376] + self._map_min_lon = 34.844513 + self._map_max_lon = 34.855499 + self._map_min_lat = 31.895049 + self._map_max_lat = 31.904376 + + # ───────────────────────────────────────────── + # Helper: robust projection + # ───────────────────────────────────────────── + def _project_lon_lat(self, lon: float, lat: float) -> Optional[Tuple[float, float]]: + """ + Try the original tile-based projection first. + If it fails (None), fall back to a simple linear mapping + from [min_lon..max_lon] × [min_lat..max_lat] → [0..width] × [0..height]. + """ + # 1) Try existing helper – keeps consistency with tiles/sensors when it works + pos = _latlon_to_xy_at_max_zoom(self.viewer, lat, lon) + if pos: + xb, yb = pos + sx = (xb - self.viewer._x_min_base) * TILE_SIZE + sy = (yb - self.viewer._y_min_base) * TILE_SIZE + return sx, sy + + # 2) Fallback: linear mapping using known map bounds + # Guard against division by zero + if ( + self._map_max_lon == self._map_min_lon + or self._map_max_lat == self._map_min_lat + ): + return None + + # Normalize lon/lat into [0,1] + x_norm = (lon - self._map_min_lon) / (self._map_max_lon - self._map_min_lon) + y_norm = (lat - self._map_min_lat) / (self._map_max_lat - self._map_min_lat) + + # Clip just in case (should already be in [0,1]) + x_norm = max(0.0, min(1.0, x_norm)) + y_norm = max(0.0, min(1.0, y_norm)) + + # Scene coords: x grows right, y grows down → flip y + sx = x_norm * self._scene_width + sy = (1.0 - y_norm) * self._scene_height + + return sx, sy + + # ───────────────────────────────────────────── + def add_region(self, region: dict, start_date=None, end_date=None, selected_ids=None): + """Add a region polygon to the orthophoto map.""" + try: + geom_json = json.loads(region["geom"]) + except Exception as e: + print(f"[RegionLayer] ❌ Invalid geometry for {region.get('name')}: {e}") + return + + if not geom_json.get("coordinates"): + print(f"[RegionLayer] ⚠️ Region {region.get('name')} missing coordinates") + return + + coords = geom_json["coordinates"] + gtype = geom_json.get("type") + + # Handle Polygon / MultiPolygon + if gtype == "Polygon": + outer_ring = coords[0] + elif gtype == "MultiPolygon": + # Pick the largest polygon’s outer ring + outer_ring = max(coords, key=lambda c: len(c[0]))[0] + else: + print(f"[RegionLayer] ⚠️ Unsupported geom type {gtype} for {region.get('name')}") + return + + if len(outer_ring) < 3: + print(f"[RegionLayer] ⚠️ Region {region.get('name')} has too few points") + return + + # ── Project region to scene coordinates + scene_points: list[QPointF] = [] + print(f"[RegionLayer] ▶ Projecting region '{region.get('name')}'...") + for lon, lat in outer_ring: + proj = self._project_lon_lat(lon, lat) + print(f" - vertex lon={lon:.6f}, lat={lat:.6f} -> {proj}") + if not proj: + continue + sx, sy = proj + scene_points.append(QPointF(sx, sy)) + + if len(scene_points) < 3: + print(f"[RegionLayer] ⚠️ Region {region.get('name')} has too few valid projected points") + return + + polygon = QPolygonF(scene_points) + + # ── Create graphics item + item = QGraphicsPolygonItem(polygon) + item.region_id = region["id"] + item.region_name = region["name"] + item.selected = False + item.setZValue(900) + + pen = QPen(QColor("#111827")) + pen.setWidthF(8) + item.setPen(pen) + + is_selected = (selected_ids is not None) and (region["id"] in selected_ids) + base_alpha = 100 if is_selected else 40 + item.setBrush(QColor(37, 99, 235, base_alpha)) + item.selected = bool(is_selected) + + item.setAcceptHoverEvents(True) + item.setFlag(QGraphicsPolygonItem.GraphicsItemFlag.ItemIsSelectable, True) + + item.mousePressEvent = lambda e, it=item: self._toggle_selection(it) + self.scene.addItem(item) + self.regions.append(item) + + print( + f"[RegionLayer] ✅ Added region '{item.region_name}' " + f"(ID {item.region_id}) with {len(scene_points)} vertices" + ) + + # ───────────────────────────────────────────── + def _toggle_selection(self, item: QGraphicsPolygonItem): + """Toggle fill color when selected and trigger callback.""" + item.selected = not item.selected + item.setBrush(QColor(37, 99, 235, 100 if item.selected else 40)) + + if self.on_select: + self.on_select(item.region_id, item.selected) + + # ───────────────────────────────────────────── + def clear(self): + """Remove all region items from the scene.""" + for item in self.regions: + self.scene.removeItem(item) + self.regions.clear() + print("[RegionLayer] Cleared all regions") + + # ───────────────────────────────────────────── + def setVisible(self, visible: bool): + """Show or hide all region polygons.""" + for item in self.regions: + item.setVisible(visible) + print(f"[RegionLayer] Visibility set to {visible}") diff --git a/GUI/src/vast/views/security/analytics/popup_panel.py b/GUI/src/vast/views/security/analytics/popup_panel.py new file mode 100644 index 000000000..f2586e39a --- /dev/null +++ b/GUI/src/vast/views/security/analytics/popup_panel.py @@ -0,0 +1,278 @@ +from PyQt6.QtWidgets import QWidget, QVBoxLayout, QLabel, QFrame, QGridLayout, QSizePolicy +from PyQt6.QtGui import QColor, QPainter +from PyQt6.QtCore import Qt, QMargins +from PyQt6.QtCharts import ( + QChart, QChartView, QBarSeries, QBarSet, QBarCategoryAxis, + QValueAxis, QLineSeries, QCategoryAxis +) +from PyQt6.QtCharts import QPieSeries # local import to avoid top clutter + +class AnalyticsPanel(QWidget): + """Fixed right-side analytics dashboard panel (2×2 grid layout).""" + + def __init__(self, title: str, data: dict, parent: QWidget | None = None): + super().__init__(parent) + + # ───────────────────────────── + # Palette + # ───────────────────────────── + self.green = "#10b981" + self.black = "#111827" + self.gray = "#6b7280" + self.bg_light = "#f9fafb" + + # ───────────────────────────── + # Layout + # ───────────────────────────── + self.setMinimumWidth(480) + layout = QVBoxLayout(self) + layout.setContentsMargins(10, 10, 10, 10) + layout.setSpacing(12) + + # Title + self.title_label = QLabel(title) + self.title_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + self.title_label.setStyleSheet(f"font-size:20pt;font-weight:700;color:{self.green};") + layout.addWidget(self.title_label) + + # 2×2 grid + self.grid = QGridLayout() + self.grid.setSpacing(10) + layout.addLayout(self.grid, stretch=1) + + # Populate initial data + self._populate(data) + + # ───────────────────────────── + def update_data(self, title: str, data: dict): + self.title_label.setText(title) + self._populate(data) + + # ───────────────────────────── + def _populate(self, data: dict): + # Clear old widgets + for i in reversed(range(self.grid.count())): + item = self.grid.itemAt(i).widget() + if item: + item.setParent(None) + + # Create 4 panels + # bar_panel = self._section("Alerts by Type", self._make_bar_chart(data.get("alerts_by_type", {}))) + bar_panel = self._section("Alerts by Type", self._make_pie_chart(data.get("alerts_by_type", {}))) + + line_panel = self._section("Alerts per Month", self._make_line_chart(data.get("alerts_per_month", {}))) + summary_panel = self._section("Summary", self._make_summary_panel( + data.get("total_alerts", 0), + data.get("avg_severity", 0), + data.get("avg_confidence", 0) + )) + # details_panel = self._section("Details", self._placeholder("More analytics coming soon...")) + details_panel = self._section( + "Avg Alert Duration (min)", + self._make_bar_chart(data.get("avg_duration_per_type", {})) +) + + # Add to 2×2 grid + self.grid.addWidget(bar_panel, 0, 0) + self.grid.addWidget(line_panel, 0, 1) + self.grid.addWidget(summary_panel, 1, 0) + self.grid.addWidget(details_panel, 1, 1) + + # Equal stretch + self.grid.setRowStretch(0, 1) + self.grid.setRowStretch(1, 1) + self.grid.setColumnStretch(0, 1) + self.grid.setColumnStretch(1, 1) + + # ───────────────────────────── + def _section(self, header_text: str, widget: QWidget): + section = QFrame() + section.setStyleSheet(f"QFrame {{ background:{self.bg_light}; border-radius:10px; }}") + vbox = QVBoxLayout(section) + vbox.setContentsMargins(8, 8, 8, 8) + vbox.setSpacing(6) + header = QLabel(header_text) + header.setStyleSheet(f"color:{self.gray};font-weight:600;font-size:11pt;") + vbox.addWidget(header) + vbox.addWidget(widget) + section.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + return section + + # ───────────────────────────── + # 🔹 Helper: compute nice Y-axis + # ───────────────────────────── + def _setup_nice_y_axis(self, data_values): + axis_y = QValueAxis() + + if not data_values: + axis_y.setRange(0, 3) + axis_y.setTickInterval(1) + return axis_y + + max_val = max(data_values) + upper = max_val * 1.2 + if upper <= 3: + upper = 3.0 + + # Pick a "nice" step: 1, 2, 5, 10, 20, 50, ... + nice_steps = [1, 2, 5, 10, 20, 50, 100, 200, 500, 1000] + step = next((s for s in nice_steps if upper / s <= 6), 1000) + upper = (int(upper / step) + 1) * step + + axis_y.setRange(0, upper) + axis_y.setTickInterval(step) + axis_y.setLabelFormat("%.1f" if any(v < 10 for v in data_values) else "%.0f") + # axis_y.setLabelFormat("%.0f") + axis_y.setMinorTickCount(0) + return axis_y + + # ───────────────────────────── + def _make_bar_chart(self, data: dict): + if not data: + return self._placeholder("No data") + + chart = QChart() + chart.legend().setVisible(False) + chart.setBackgroundVisible(False) + chart.setMargins(QMargins(8, 8, 8, 8)) + + # Bar series + bar_set = QBarSet("Alerts") + for v in data.values(): + bar_set.append(float(v)) + series = QBarSeries() + series.append(bar_set) + chart.addSeries(series) + + # X-axis + axis_x = QBarCategoryAxis() + axis_x.append(list(data.keys())) + + # Y-axis (nice scaling) + axis_y = self._setup_nice_y_axis(list(data.values())) + + chart.addAxis(axis_x, Qt.AlignmentFlag.AlignBottom) + chart.addAxis(axis_y, Qt.AlignmentFlag.AlignLeft) + series.attachAxis(axis_x) + series.attachAxis(axis_y) + + bar_set.setColor(QColor(self.green)) + + # Chart view + view = QChartView(chart) + view.setRenderHint(QPainter.RenderHint.Antialiasing) + view.setMinimumHeight(200) + view.setStyleSheet("background:transparent;") + return view + # ───────────────────────────── + def _make_pie_chart(self, data: dict): + """Create a pie chart (e.g., Alerts by Type) with distinct green shades.""" + if not data: + return self._placeholder("No data") + + chart = QChart() + chart.legend().setVisible(True) + chart.legend().setAlignment(Qt.AlignmentFlag.AlignBottom) + chart.setBackgroundVisible(False) + chart.setMargins(QMargins(8, 8, 8, 8)) + + # Pie series + series = QPieSeries() + total = sum(data.values()) or 1 + + # Define a clearer set of green shades (light → dark) + green_shades = [ + QColor("#A7F3D0"), # light mint + QColor("#6EE7B7"), # medium mint + QColor("#34D399"), # base green + QColor("#10B981"), # emerald + QColor("#059669"), # dark green + QColor("#047857"), # deeper green + ] + + max_val = max(data.values()) if data else 0 + + for i, (key, val) in enumerate(data.items()): + slice_ = series.append(f"{key} ({val})", float(val)) + slice_.setLabelVisible(True) + + # Pick shade cyclically + color = green_shades[i % len(green_shades)] + slice_.setBrush(color) + slice_.setPen(QColor("#ffffff")) # white borders + slice_.setLabelColor(QColor(self.black)) + + # Slightly explode only the largest slice + # if val == max_val: + # slice_.setExploded(True) + # slice_.setLabelFont(self.font()) + + chart.addSeries(series) + chart.setAnimationOptions(QChart.AnimationOption.AllAnimations) + + # Chart view + view = QChartView(chart) + view.setRenderHint(QPainter.RenderHint.Antialiasing) + view.setMinimumHeight(200) + view.setStyleSheet("background:transparent;") + return view + + + + # ───────────────────────────── + def _make_line_chart(self, data: dict): + if not data: + return self._placeholder("No data") + + sorted_items = sorted(data.items()) + chart = QChart() + chart.legend().setVisible(False) + chart.setBackgroundVisible(False) + chart.setMargins(QMargins(8, 8, 8, 8)) + + # Create line series + series = QLineSeries() + for i, (_, val) in enumerate(sorted_items): + series.append(i, float(val)) + pen = series.pen() + pen.setColor(QColor(self.green)) + pen.setWidth(3) + series.setPen(pen) + chart.addSeries(series) + + # X-axis (months) + axis_x = QCategoryAxis() + for i, (month, _) in enumerate(sorted_items): + axis_x.append(month, i) + + # Y-axis (nice scaling) + axis_y = self._setup_nice_y_axis(list(data.values())) + + chart.addAxis(axis_x, Qt.AlignmentFlag.AlignBottom) + chart.addAxis(axis_y, Qt.AlignmentFlag.AlignLeft) + series.attachAxis(axis_x) + series.attachAxis(axis_y) + + view = QChartView(chart) + view.setRenderHint(QPainter.RenderHint.Antialiasing) + view.setMinimumHeight(200) + view.setStyleSheet("background:transparent;") + return view + + # ───────────────────────────── + def _make_summary_panel(self, total, avg_sev, avg_conf): + label = QLabel( + f"Total Alerts: {total}
" + f"Avg Severity: {avg_sev:.2f}
" + f"Avg Confidence: {avg_conf:.2f}" + ) + label.setAlignment(Qt.AlignmentFlag.AlignCenter) + label.setStyleSheet(f"font-size:12pt;color:{self.black};") + return label + + # ───────────────────────────── + def _placeholder(self, text: str): + lbl = QLabel(text) + lbl.setAlignment(Qt.AlignmentFlag.AlignCenter) + lbl.setStyleSheet("color:#9ca3af;font-size:10pt;font-style:italic;") + return lbl diff --git a/GUI/src/vast/views/security/analytics/sql_generator.py b/GUI/src/vast/views/security/analytics/sql_generator.py new file mode 100644 index 000000000..99580f666 --- /dev/null +++ b/GUI/src/vast/views/security/analytics/sql_generator.py @@ -0,0 +1,393 @@ + + +# #!/usr/bin/env python3 +# # -*- coding: utf-8 -*- + +""" +Free-text → DSL → validated SQL generator for AgGuard analytics dashboard. +Uses your internal DSL schema: +{ + "source": "alerts", + "_ops": [ + {"op": "select", "columns": ["..."]}, + {"op": "where", "cond": { ... }}, + {"op": "group_by", "columns": ["..."]}, + {"op": "having", "cond": { ... }}, + {"op": "order_by", "columns": ["..."], "directions": ["ASC"|"DESC"]}, + {"op": "limit", "limit": 50} + ] +} +""" + +import os, json +from openai import OpenAI +from dotenv import load_dotenv +from jsonschema import validate, ValidationError + +# ────────────────────────────────────────────── +# 🔑 Initialize client +# ────────────────────────────────────────────── +load_dotenv() +client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) + +# ────────────────────────────────────────────── +# 🧩 DSL schema (the one your DSL actually uses) +# ────────────────────────────────────────────── +QUERY_SCHEMA = { + "$schema": "https://json-schema.org/draft/2020-12/schema", + "title": "DSLQueryPlan", + "type": "object", + "properties": { + "source": {"type": "string"}, + "_ops": { + "type": "array", + "items": { + "type": "object", + "properties": { + "op": { + "type": "string", + "enum": [ + "select", "where", "group_by", + "having", "order_by", "limit", "offset" + ] + }, + "columns": { + "type": "array", + "items": { + "type": "string", + + }, + "minItems": 1, + "maxItems": 2, + "uniqueItems": True + }, + "cond": {"type": "object"}, + "directions": { + "type": "array", + "items": {"type": "string", "enum": ["ASC", "DESC"]} + }, + "limit": {"type": "integer", "minimum": 1, "maximum": 500}, + "offset": {"type": "integer", "minimum": 0} + }, + "required": ["op"], + "additionalProperties": True + } + } + }, + "required": ["source", "_ops"], + "additionalProperties": False +} + + + +SYSTEM_PROMPT = """ +You are an expert DSL generator for the AgGuard Analytics Dashboard. +Your task: convert a natural-language request into a strict JSON object +compatible with the AgGuard DSL (no SQL, JSON only). + +──────────────────────── +TABLE: alerts +──────────────────────── +CREATE TABLE alerts ( + alert_id TEXT PRIMARY KEY, + alert_type TEXT, + device_id TEXT, + started_at TIMESTAMPTZ, + ended_at TIMESTAMPTZ, + confidence DOUBLE PRECISION, + area TEXT, + lat DOUBLE PRECISION, + lon DOUBLE PRECISION, + severity INT DEFAULT 1, + image_url TEXT, + vod TEXT, + hls TEXT, + ack BOOLEAN DEFAULT FALSE, + meta JSONB, + created_at TIMESTAMPTZ DEFAULT now(), + updated_at TIMESTAMPTZ DEFAULT now() +); + +Use only these columns. Do not invent new columns or tables. + +──────────────────────── +DSL STRUCTURE +──────────────────────── +The output MUST follow this shape: + +{ + "source": "alerts", + "_ops": [ + {"op": "select", "columns": ["..."]}, + {"op": "where", "cond": { ... }}, + {"op": "group_by", "columns": ["..."]}, + {"op": "having", "cond": { ... }}, + {"op": "order_by", "columns": ["..."], "directions": ["ASC"|"DESC"]}, + {"op": "limit", "limit": 50}, + {"op": "offset", "offset": 0} + ] +} + +Rules for fields: +- "source" must always be "alerts". +- "_ops" is an ordered array of operations. +- "op" is one of: "select", "where", "group_by", "having", "order_by", "limit", "offset". +- "columns" is ALWAYS an array of strings (1–2 items, no duplicates). + - For functions/expressions in SELECT/GROUP_BY/ORDER_BY, write SQL text strings, e.g.: + "COUNT(alert_id)", "COUNT(*)", "DATE_TRUNC('month', started_at)". + - Never put {"func": ...} objects inside "columns". +- "directions" aligns with "columns" and contains only "ASC" or "DESC". +- "limit" is 1–500; "offset" is >= 0. + +SELECT rules (very important): +- When selecting entities, SELECT must contain only: + - ["device_id"], or + - ["area"]. +- Never put aggregates or functions into SELECT (no COUNT(*), SUM, etc. in SELECT). + +──────────────────────── +CONDITION TREE FORMAT +──────────────────────── +Conditions ("cond") are boolean trees: + +1. Logical AND: + { "all": [ , ... ] } + +2. Logical OR: + { "any": [ , ... ] } + +3. Predicate: + { "op": "", "left": , "right": } + +Allowed operators: "=", "!=", "<", "<=", ">", ">=". + +In conditions, an may be: +- {"col": ""} +- {"literal": } +- {"func": "", "args": [ , ... ]} + +Notes: +- Use {"col": "..."} only with real columns from the alerts table. +- Use {"literal": ...} for numbers, strings, booleans, and time expressions like: + "now() - interval '1 month'". +- Use {"func": ...} only in WHERE/HAVING, not in SELECT/GROUP_BY/ORDER_BY. +- Do NOT use window functions or OVER() (no row_number, no "max(avg) over ()"). + +──────────────────────── +EXAMPLES +──────────────────────── + +Example 1 +User: "show devices with fence_hole alerts from the last month" +→ +{ + "source": "alerts", + "_ops": [ + {"op": "select", "columns": ["device_id"]}, + { + "op": "where", + "cond": { + "all": [ + { + "op": "=", + "left": {"col": "alert_type"}, + "right": {"literal": "fence_hole"} + }, + { + "op": ">", + "left": {"col": "started_at"}, + "right": {"literal": "now() - interval '1 month'"} + } + ] + } + }, + {"op": "group_by", "columns": ["device_id"]} + ] +} + +──────────────────────── + +Example 2 +User: "show areas with more than 3 severe alerts (severity > 3) in the last month" +→ +{ + "source": "alerts", + "_ops": [ + {"op": "select", "columns": ["area"]}, + { + "op": "where", + "cond": { + "all": [ + { + "op": ">", + "left": {"col": "severity"}, + "right": {"literal": 3} + }, + { + "op": ">", + "left": {"col": "started_at"}, + "right": {"literal": "now() - interval '1 month'"} + } + ] + } + }, + {"op": "group_by", "columns": ["area"]}, + { + "op": "having", + "cond": { + "op": ">", + "left": {"func": "count", "args": [ {"literal": "*"} ]}, + "right": {"literal": 3} + } + } + ] +} + + +──────────────────────── + +Example 4 +User: "top 5 devices with highest number of climbing_fence alerts" +→ +{ + "source": "alerts", + "_ops": [ + {"op": "select", "columns": ["device_id"]}, + { + "op": "where", + "cond": { + "op": "=", + "left": {"col": "alert_type"}, + "right": {"literal": "climbing_fence"} + } + }, + {"op": "group_by", "columns": ["device_id"]}, + { + "op": "order_by", + "columns": ["COUNT(alert_id)"], + "directions": ["DESC"] + }, + {"op": "limit", "limit": 5} + ] +} + + +──────────────────────── + +Example 5 +User: "list devices with unacknowledged masked_person alerts in the last week, newest first, limit 20" +→ +{ + "source": "alerts", + "_ops": [ + {"op": "select", "columns": ["device_id"]}, + { + "op": "where", + "cond": { + "all": [ + { + "op": "=", + "left": {"col": "alert_type"}, + "right": {"literal": "masked_person"} + }, + { + "op": "=", + "left": {"col": "ack"}, + "right": {"literal": false} + }, + { + "op": ">", + "left": {"col": "started_at"}, + "right": {"literal": "now() - interval '1 week'"} + } + ] + } + }, + { + "op": "order_by", + "columns": ["started_at"], + "directions": ["DESC"] + }, + {"op": "limit", "limit": 20} + ] +} + +──────────────────────── +GLOBAL RULES +──────────────────────── +1. Always use only the columns of the alerts table. +2. Never reference table aliases like "a." or "r." and never reference other tables. +3. Output only VALID JSON, with "source" and "_ops" at the top level. +4. Use WHERE for row filters, GROUP_BY for aggregations, HAVING for aggregate conditions. +5. For queries that rank entities by number of alerts (e.g. "top", "most", "highest", "least", "fewest", "lowest"): + - Use GROUP_BY on the entity ("device_id" or "area"). + - Use ORDER_BY with "COUNT(alert_id)" or "COUNT(*)". + • For "top / most / highest": use direction "DESC". + • For "least / fewest / lowest": use direction "ASC". + - Use LIMIT N (or LIMIT 1 if the user asks for a single best/worst entity). +6. alert_type is one of: "masked_person", "intruding animal", "climbing_fence", "fence_hole". +""" + + +# ────────────────────────────────────────────── +# 🧮 Core generator +# ────────────────────────────────────────────── +from src.vast.dsl.ir import Plan +from src.vast.dsl.builder import SQLBuilder +from src.vast.dsl.dialects import PostgresDialect + +def generate_sql_from_prompt(prompt: str) -> tuple[str | None, list]: + """Convert natural language → DSL JSON → validated SQL.""" + response = client.chat.completions.create( + model="gpt-4o-mini", + temperature=0, + messages=[ + {"role": "system", "content": SYSTEM_PROMPT}, + {"role": "user", "content": prompt} + ], + response_format={"type": "json_object"} + ) + + obj = json.loads(response.choices[0].message.content) + print(obj) + try: + validate(instance=obj, schema=QUERY_SCHEMA) + except ValidationError as e: + print("❌ Validation error:", e.message) + return None, [] + + # Compile directly with your DSL + plan = Plan.from_dict(obj) + print(plan) + sql, params = SQLBuilder(PostgresDialect("named")).compile(plan) + print(sql,params) + return sql, params + + +# ────────────────────────────────────────────── +# 🧪 Example usage +# ────────────────────────────────────────────── +if __name__ == "__main__": + user_text = "give me the region that had most alerts last month" + print(f"\n🗣️ User: {user_text}\n") + + sql, params = generate_sql_from_prompt(user_text) + if sql: + print("✅ SQL:\n", sql) + print("🧩 Params:", params) + else: + print("❌ Could not generate SQL.") + + + + + + + + + + + + + + diff --git a/GUI/src/vast/views/security/events_history_page.py b/GUI/src/vast/views/security/events_history_page.py index f6ec017fb..889191de4 100644 --- a/GUI/src/vast/views/security/events_history_page.py +++ b/GUI/src/vast/views/security/events_history_page.py @@ -1,6 +1,7 @@ from PyQt6 import QtWidgets, QtGui, QtCore import os, sys, vlc from datetime import datetime +from PyQt6 import sip class EventsHistoryPage(QtWidgets.QWidget): @@ -19,7 +20,7 @@ def __init__(self, api, parent=None): background-color: #f9fafb; font-family: 'Segoe UI', 'DejaVu Sans', Arial, sans-serif; color: #111827; - font-size: 14px; + font-size: 16px; } QHeaderView::section { background-color: #f3f4f6; @@ -36,7 +37,7 @@ def __init__(self, api, parent=None): border-radius: 10px; selection-background-color: #bbf7d0; selection-color: #065f46; - font-size: 13px; + font-size: 15px; } QTableWidget::item { padding: 10px; } QScrollBar:vertical { @@ -55,7 +56,7 @@ def __init__(self, api, parent=None): border: 1px solid #d1d5db; border-radius: 8px; padding: 4px 10px; - font-size: 13px; + font-size: 14px; height: 32px; min-width: 120px; color: #111827; @@ -73,7 +74,7 @@ def __init__(self, api, parent=None): background-color: #ffffff; padding: 6px 4px; outline: none; - font-size: 14px; + font-size: 16px; selection-background-color: #10b981; selection-color: white; } @@ -100,7 +101,7 @@ def __init__(self, api, parent=None): color: white; padding: 6px 16px; font-weight: 700; - font-size: 13px; + font-size: 15px; } QPushButton.view_btn:hover { background-color: #059669; } """) @@ -199,18 +200,44 @@ def __init__(self, api, parent=None): self.table = QtWidgets.QTableWidget() self.table.setColumnCount(8) self.table.setHorizontalHeaderLabels([ - "ID", "Device", "Anomaly", "Start Time", - "End Time", "Duration (s)", "Severity", "View" + "Device", "Anomaly", "Start Time", "End Time", + "Duration (m)", "Severity", "View", "Feedback" ]) + self.table.verticalHeader().setVisible(False) self.table.setEditTriggers(QtWidgets.QAbstractItemView.EditTrigger.NoEditTriggers) self.table.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectionBehavior.SelectRows) self.table.horizontalHeader().setStretchLastSection(True) self.table.horizontalHeader().setSectionResizeMode(QtWidgets.QHeaderView.ResizeMode.Stretch) - self.table.verticalHeader().setDefaultSectionSize(48) + self.table.verticalHeader().setDefaultSectionSize(56) main_layout.addWidget(self.table, 1) + # QtCore.QTimer.singleShot(300, self.load_from_api) + self._load_timer = QtCore.QTimer(self) + self._load_timer.setSingleShot(True) + self._load_timer.timeout.connect(self._safe_load) + self._load_timer.start(300) + def _safe_load(self): + if not self.isVisible() or sip.isdeleted(self.table): + print("[SAFE_LOAD] Skipping load: widget closed or deleted.") + return + self.load_from_api() + def showEvent(self, event): + super().showEvent(event) + if not getattr(self, "_loaded_once", False): + self._loaded_once = True + self.load_from_api() + + + def closeEvent(self, event): + print("[CLOSE] EventsHistoryPage closing — stopping load timer.") + if hasattr(self, "_load_timer") and self._load_timer.isActive(): + self._load_timer.stop() + return super().closeEvent(event) + + + + - QtCore.QTimer.singleShot(300, self.load_from_api) # ───────────── SLIDER STYLE ───────────── def _update_slider_style(self, value): @@ -245,22 +272,38 @@ def _safe_int(self, val): except Exception: return 0 + from datetime import datetime + def _parse_time(self, t): + if not t: + return None + try: - if not t: - return None - dt = datetime.fromisoformat(t.replace("Z", "+00:00")) - return dt.replace(tzinfo=None) + # Normalize variants: + # "2025-11-14 07:25:04+02:00" + # "2025-11-14T07:25:04+02:00" + # "2025-11-14 07:25:04Z" + nt = t.replace(" ", "T").replace("Z", "+00:00") + dt = datetime.fromisoformat(nt) + + # Convert to naive local time for table filtering + return dt.astimezone().replace(tzinfo=None) + except Exception: return None + def _fmt_time(self, t): - return t.replace("T", " ").split(".")[0] if t else "-" + dt = self._parse_time(t) + if not dt: + return "-" + return dt.strftime("%Y-%m-%d %H:%M:%S") + def load_from_api(self): print("[API] Fetching alerts from:", f"{self.api.base}/api/tables/alerts") try: - url = f"{self.api.base}/api/tables/alerts" + url = f"{self.api.base}/api/tables/alerts?limit=500" resp = self.api.http.get(url, timeout=8) resp.raise_for_status() data = resp.json() @@ -275,7 +318,7 @@ def load_from_api(self): print(f"[API][WARN] Unexpected format, using raw list of {len(rows)} items.") # ───── Filter only relevant alert types ───── - allowed_types = {"climbing_fence", "masked_person", "intruding_animal"} + allowed_types = {"climbing_fence", "masked_person", "intruding animal","fence_hole"} filtered = [r for r in rows if (r.get("alert_type") or "").strip() in allowed_types] print(f"[API] Filtered {len(filtered)} / {len(rows)} alerts matching allowed types {allowed_types}.") @@ -295,7 +338,8 @@ def load_from_api(self): def populate_filters(self): devices = sorted({it.get("device_id") or "-" for it in self.all_rows}) - anomalies = sorted({it.get("anomaly") or "-" for it in self.all_rows}) + anomalies = sorted({it.get("alert_type") or "-" for it in self.all_rows}) + print(f"[FILTERS] Available devices={devices}") print(f"[FILTERS] Available anomalies={anomalies}") @@ -337,7 +381,7 @@ def apply_filters(self): filtered = [] for idx, it in enumerate(self.all_rows): dev = it.get("device_id") or "-" - anom = it.get("anomaly") or "-" + anom = it.get("alert_type") or "-" sev = self._safe_int(it.get("severity")) started = self._parse_time(it.get("started_at")) @@ -383,8 +427,8 @@ def apply_filters(self): 4: lambda x: self._parse_time(x.get("started_at")) or datetime.min, 5: lambda x: self._parse_time(x.get("ended_at")) or datetime.min, 6: lambda x: self._parse_time(x.get("ended_at")) or datetime.min, - 7: lambda x: (x.get("anomaly") or "").lower(), - 8: lambda x: (x.get("anomaly") or "").lower(), + 7: lambda x: (x.get("alert_type") or "").lower(), + 8: lambda x: (x.get("alert_type") or "").lower(), } if i in keymap: @@ -428,23 +472,117 @@ def _severity_label(self, sev: int) -> str: def populate_table(self, rows): + if not hasattr(self, "table") or self.table is None: + print("[TABLE][WARN] Table not available — widget probably closed.") + return + if sip.isdeleted(self.table): + print("[TABLE][WARN] Table was deleted, aborting populate.") + return print(f"[TABLE] Populating table with {len(rows)} alerts.") self.table.setRowCount(len(rows)) for r, it in enumerate(rows): - sid = (str(it.get("alert_id") or "")[:8] + "...") if it.get("alert_id") else "-" - self.table.setItem(r, 0, QtWidgets.QTableWidgetItem(sid)) - self.table.setItem(r, 1, QtWidgets.QTableWidgetItem(it.get("device_id") or "-")) - self.table.setItem(r, 2, QtWidgets.QTableWidgetItem(it.get("alert_type") or "-")) - self.table.setItem(r, 3, QtWidgets.QTableWidgetItem(self._fmt_time(it.get("started_at")))) - self.table.setItem(r, 4, QtWidgets.QTableWidgetItem(self._fmt_time(it.get("ended_at")))) - self.table.setItem(r, 5, QtWidgets.QTableWidgetItem(f"{it.get('confidence') or 0:.2f}")) - - # ACK Checkbox indicator - ack_value = it.get("ack", False) - ack_label = QtWidgets.QLabel("✅" if ack_value else "❌") - ack_label.setAlignment(QtCore.Qt.AlignmentFlag.AlignCenter) - self.table.setCellWidget(r, 6, ack_label) + # Device + self.table.setItem(r, 0, QtWidgets.QTableWidgetItem(it.get("device_id") or "-")) + + # Anomaly + # Anomaly + alert_type = it.get("alert_type") or "-" + raw_meta = it.get("meta") or {} + meta = {} + + if isinstance(raw_meta, dict): + meta = raw_meta + elif isinstance(raw_meta, str): + try: + meta = json.loads(raw_meta) + except Exception: + try: + import ast + meta = ast.literal_eval(raw_meta) + except Exception: + meta = {} + + subject = meta.get("subject") + + + label = alert_type.replace("_", " ").title() + if alert_type in ("intruding_animal","intruding animal", "climbing_fence") and subject: + label = f"{label} ({subject.title()})" + self.table.setItem(r, 1, QtWidgets.QTableWidgetItem(label)) + + + # Start / End time + self.table.setItem(r, 2, QtWidgets.QTableWidgetItem(self._fmt_time(it.get("started_at")))) + self.table.setItem(r, 3, QtWidgets.QTableWidgetItem(self._fmt_time(it.get("ended_at")))) + + # Duration (minutes) + started = self._parse_time(it.get("started_at")) + ended = self._parse_time(it.get("ended_at")) + duration_m = "-" + if started and ended: + duration_m = f"{(ended - started).total_seconds() / 60:.1f}" + self.table.setItem(r, 4, QtWidgets.QTableWidgetItem(duration_m)) + + + + ## ────── SEVERITY BAR ────── + sev = self._safe_int(it.get("severity")) + sev = max(0, min(sev, 9)) # allow 0–9 + fill = sev / 9.0 # proportional fill + + if sev == 0: + label_text = "None" + color = "#f3f4f6" + elif sev <= 3: + label_text = "Low" + color = "#a7f3d0" + elif sev <= 6: + label_text = "Medium" + color = "#34d399" + else: + label_text = "High" + color = "#059669" + + # Background container + container = QtWidgets.QFrame() + container.setFixedHeight(20) + container.setStyleSheet(""" + QFrame { + background: #e5e7eb; + border: 1px solid #d1d5db; + border-radius: 8px; + } + """) + + layout = QtWidgets.QGridLayout(container) + layout.setContentsMargins(1, 1, 1, 1) + layout.setSpacing(0) + + fill_bar = QtWidgets.QFrame(container) + fill_bar.setStyleSheet(f"background-color: {color}; border-radius: 7px;") + + # ↓ reduce bar width from 90 → 70 for better balance + container_width = 150 + fill_bar.setFixedWidth(int(container_width * fill)) + + layout.addWidget(fill_bar, 0, 0) + layout.setColumnStretch(0, 0) + layout.setColumnStretch(1, 1) + + label = QtWidgets.QLabel(label_text, container) + label.setAlignment(QtCore.Qt.AlignmentFlag.AlignCenter) + label.setStyleSheet("font-weight:600; color:#064e3b; background:transparent; font-size:12px;") + layout.addWidget(label, 0, 0, 1, 2) + + wrapper = QtWidgets.QWidget() + outer = QtWidgets.QHBoxLayout(wrapper) + outer.setContentsMargins(2, 0, 2, 0) + outer.setAlignment(QtCore.Qt.AlignmentFlag.AlignCenter) + outer.addWidget(container) + self.table.setCellWidget(r, 5, wrapper) + + # Centered “View” button for vod btn = QtWidgets.QPushButton("View") @@ -456,7 +594,7 @@ def populate_table(self, rows): background-color: #10b981; color: white; border-radius: 6px; - font-size: 12px; + font-size: 13px; font-weight: 600; padding: 3px 6px; } @@ -471,7 +609,96 @@ def populate_table(self, rows): btn_layout.setContentsMargins(0, 0, 0, 0) btn_layout.setAlignment(QtCore.Qt.AlignmentFlag.AlignCenter) btn_layout.addWidget(btn) - self.table.setCellWidget(r, 7, btn_container) + self.table.setCellWidget(r, 6, btn_container) + + + # ────── FEEDBACK (visible circular emoji buttons — no custom class) ────── + feedback_widget = QtWidgets.QWidget(self.table) + layout = QtWidgets.QHBoxLayout(feedback_widget) + layout.setContentsMargins(0, 6, 0, 6) + layout.setSpacing(12) + layout.setAlignment(QtCore.Qt.AlignmentFlag.AlignCenter) + + thumb_up = QtWidgets.QPushButton("👍") + thumb_down = QtWidgets.QPushButton("👎") + + for btn in (thumb_up, thumb_down): + btn.setCursor(QtCore.Qt.CursorShape.PointingHandCursor) + btn.setCheckable(True) + btn.setFixedSize(48, 48) + btn.setStyleSheet(""" + QPushButton { + background-color: white; + border-radius: 24px; + border: 2px solid #d1d5db; + font-size: 20px; + } + QPushButton:hover { + background-color: #f3f4f6; + border-color: #9ca3af; + } + QPushButton:checked { + background-color: #e5e7eb; + border-color: #4b5563; + } + """) + + feedback_widget.thumb_up = thumb_up + feedback_widget.thumb_down = thumb_down + + # Restore state + meta = it.get("meta") or {} + if isinstance(meta, str): + import json + try: + meta = json.loads(meta) + except Exception: + meta = {} + is_real = meta.get("is_real") + if is_real is True: + thumb_up.setChecked(True) + elif is_real is False: + thumb_down.setChecked(True) + + def handle_feedback_change(checked, alert=it, up_btn=thumb_up, down_btn=thumb_down): + if not checked: + return + is_real_value = up_btn.isChecked() + down_btn.blockSignals(True) + down_btn.setChecked(not is_real_value) + down_btn.blockSignals(False) + self._send_feedback(alert, is_real_value) + + thumb_up.toggled.connect(handle_feedback_change) + thumb_down.toggled.connect(handle_feedback_change) + + layout.addWidget(thumb_up) + layout.addWidget(thumb_down) + feedback_widget.setLayout(layout) + + self.table.setRowHeight(r, 68) + # Wrap feedback inside a centering wrapper + cell_wrapper = QtWidgets.QWidget() + cell_layout = QtWidgets.QHBoxLayout(cell_wrapper) + cell_layout.setContentsMargins(0, 0, 0, 0) + cell_layout.setAlignment(QtCore.Qt.AlignmentFlag.AlignCenter) + cell_layout.addWidget(feedback_widget) + + self.table.setCellWidget(r, 7, cell_wrapper) + + # self.table.setCellWidget(r, 7, feedback_widget) + + + + + + + + + + + + print("[TABLE] Done populating alerts table.") @@ -480,26 +707,71 @@ def populate_table(self, rows): + + # def _open_video_player(self, info): + # print(f"[VIDEO] Opening video player for alert={info.get('alert_id')}") + # url = info.get("vod") + # if not url: + # QtWidgets.QMessageBox.warning(self, "No Video", "This alert has no VOD URL.") + # return + + def _open_video_player(self, info): + print(f"[VIEW] Opening media for alert={info.get('alert_id')}") + vod_url = info.get("vod") + image_url = info.get("image_url") - def _open_video_player(self, info): - print(f"[VIDEO] Opening video player for alert={info.get('alert_id')}") - url = info.get("vod") - if not url: - QtWidgets.QMessageBox.warning(self, "No Video", "This alert has no VOD URL.") + if vod_url: + print("[VIEW] Found VOD — playing video.") + proxy_url = f"http://127.0.0.1:19100/vod?u={self.media_proxy_base}/vod/{vod_url}" + self._show_vlc_popup(proxy_url) + return + + if image_url: + print("[VIEW] No VOD, found image — showing image popup.") + image_url = f"http://127.0.0.1:19100/vod?u={self.media_proxy_base}/img/{image_url}" + self._show_image_popup(image_url) return - self._show_vlc_popup(url) + QtWidgets.QMessageBox.warning(self, "No Media", "This alert has neither video nor image available.") + + def _show_image_popup(self, url: str): + print(f"[IMAGE] Displaying still image from {url}") + popup = QtWidgets.QDialog(self) + popup.setWindowTitle("Incident Image") + popup.setMinimumSize(640, 480) + layout = QtWidgets.QVBoxLayout(popup) + + label = QtWidgets.QLabel() + label.setAlignment(QtCore.Qt.AlignmentFlag.AlignCenter) + layout.addWidget(label, 1) + + # Fetch image via Qt network + from PyQt6.QtNetwork import QNetworkAccessManager, QNetworkRequest + self._manager = QNetworkAccessManager() + + def handle_reply(reply): + data = reply.readAll() + pixmap = QtGui.QPixmap() + if pixmap.loadFromData(data): + label.setPixmap(pixmap.scaled(label.size(), QtCore.Qt.AspectRatioMode.KeepAspectRatio, QtCore.Qt.TransformationMode.SmoothTransformation)) + else: + label.setText("❌ Failed to load image.") + self._manager.finished.connect(handle_reply) + + req = QNetworkRequest(QtCore.QUrl(url)) + self._manager.get(req) + popup.exec() def _show_vlc_popup(self, url): print(f"[VIDEO] Playing URL: {url}") popup = QtWidgets.QDialog(self) popup.setWindowTitle("Incident Video Playback") - popup.setMinimumSize(640, 400) + popup.setMinimumSize(1280, 720) vbox = QtWidgets.QVBoxLayout(popup) player = QtWidgets.QFrame() player.setStyleSheet("background:black;border-radius:8px;") @@ -514,3 +786,72 @@ def _show_vlc_popup(self, url): mp.set_xwindow(int(player.winId())) mp.play() print("[VIDEO] Playback started.") + # def _show_vlc_popup(self, url): + # print(f"[VIDEO] Playing URL: {url}") + + # popup = QtWidgets.QDialog(self) + # popup.setWindowTitle("Incident Video Playback") + # popup.setMinimumSize(1280, 720) + # vbox = QtWidgets.QVBoxLayout(popup) + + # player = QtWidgets.QFrame() + # player.setStyleSheet("background:black;border-radius:8px;") + # vbox.addWidget(player, 1) + + # # --- VLC instance with MP4-friendly options --- + # inst = vlc.Instance([ + # "--quiet", + # "--no-video-title-show", + # "--demux=avformat", # important for MP4 + # "--network-caching=800", + # "--file-caching=800", + # "--avcodec-hw=none", # safer decoding + # ]) + + # mp = inst.media_player_new() + + # # --- Media object with same options --- + # media = inst.media_new(url) + # media.add_option(":no-audio") + # media.add_option(":network-caching=800") + # media.add_option(":file-caching=800") + # media.add_option(":demux=avformat") + + # mp.set_media(media) + + # popup.show() + # if sys.platform.startswith("win"): + # mp.set_hwnd(int(player.winId())) + # else: + # mp.set_xwindow(int(player.winId())) + # mp.play() + + # print("[VIDEO] Playback started.") + + + + def _send_feedback(self, alert: dict, is_real: bool): + """Send user feedback (👍/👎) using API contract.""" + alert_id = alert.get("alert_id") + if not alert_id: + print("[FEEDBACK][WARN] Missing alert_id; cannot update.") + return + + payload = { + "keys": {"alert_id": alert_id}, + "data": {"meta": {**(alert.get("meta") or {}), "is_real": is_real}} + } + + url = f"{self.api.base}/api/tables/alerts" + print(f"[FEEDBACK] PATCH {url} with {payload}") + + try: + resp = self.api.http.patch(url, json=payload, timeout=6) + resp.raise_for_status() + result = resp.json() + print(f"[FEEDBACK] ✅ Updated meta.is_real={is_real}, affected={result.get('affected_rows')}") + except Exception as e: + print("[FEEDBACK][ERROR]", e) + QtWidgets.QMessageBox.warning(self, "Feedback Error", f"Failed to update feedback:\n{e}") + + diff --git a/GUI/src/vast/views/security/incident_player_vlc.py b/GUI/src/vast/views/security/incident_player_vlc.py index 52bda9b11..7c9efe9b9 100644 --- a/GUI/src/vast/views/security/incident_player_vlc.py +++ b/GUI/src/vast/views/security/incident_player_vlc.py @@ -8,7 +8,12 @@ tail segments in /live.m3u8 so VLC never requests unavailable parts. (Decay back to normal once stable.) - No DVR freeze on resolve (removed items disappear; playback stops/advances). +- DVR seek/scrub still works *after* incident is marked resolved, using the + segments already buffered in memory. - No-cache headers on HLS endpoints. +- Smoother stream: + * DVR poll interval tightened (REFRESH_MS default 300 ms). + * VLC network caching default increased (800 ms). """ from __future__ import annotations @@ -21,11 +26,14 @@ from PyQt6.QtCore import Qt, QUrl, QTimer from PyQt6.QtWebSockets import QWebSocket from PyQt6.QtNetwork import QNetworkAccessManager, QNetworkRequest + import vlc # python-vlc -from aiohttp import web, ClientSession -from vast.views.security.events_history_page import EventsHistoryPage +from aiohttp import web, ClientSession +from aiohttp.client_exceptions import ClientConnectionError, ClientPayloadError +from vast.views.security.events_history_page import EventsHistoryPage +from src.vast.views.security.analytics.analytics_page import GeoAnalyticsView # ────────────────────────────────────────────────────────────────────────────── @@ -39,18 +47,21 @@ class Config: PORT = int(os.getenv("PORT", "19100")) # Poll upstream playlist ~2–4x per segment (1.0s segments -> 300ms is good) - REFRESH_MS = int(os.getenv("REFRESH_MS", "20000")) + # ↓ Previously 20000 ms, which caused "segment → pause → segment" behaviour in DVR. + REFRESH_MS = int(os.getenv("REFRESH_MS", "300")) # Show this many segments in the live window… LIVE_EDGE_SEGMENTS = int(os.getenv("LIVE_EDGE_SEGMENTS", "3")) # …but hide the freshest N (stay behind live edge to avoid stalls) LIVE_LAG_SEGMENTS = int(os.getenv("LIVE_LAG_SEGMENTS", "1")) - # VLC network caching (ms) - NETWORK_CACHING = int(os.getenv("NETWORK_CACHING", "320")) + # VLC network caching (ms) — slightly higher default for smoother playback + NETWORK_CACHING = int(os.getenv("NETWORK_CACHING", "800")) ALERTS_WS = os.getenv("ALERTS_WS", "ws://host.docker.internal:8010/ws/alerts") ALERTS_SNAPSHOT_HTTP = os.getenv("ALERTS_SNAPSHOT_HTTP", "") + ALLOWED_TYPES = {"climbing_fence", "masked_person", "intruding animal"} + # ────────────────────────────────────────────────────────────────────────────── # Upstream fetcher + DVR state @@ -61,6 +72,7 @@ class Segment: duration: float abs_url: str # absolute URL to fetch + class DvrState: def __init__(self, upstream_index_url: str, auth_token: str = "", refresh_ms: int = 800): self.upstream_index_url = upstream_index_url @@ -215,14 +227,85 @@ def render_dvr_vod_playlist(self, *, endlist: bool = False) -> Tuple[str, float] return "\n".join(out) + "\n", float(total) + # ────────────────────────────────────────────────────────────────────────────── # Aiohttp proxy app # ────────────────────────────────────────────────────────────────────────────── import socket + def is_port_in_use(port=19090, host="127.0.0.1"): with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: return s.connect_ex((host, port)) == 0 +class VlcWidget(QtWidgets.QFrame): + positionChanged = QtCore.pyqtSignal(float) + timeChanged = QtCore.pyqtSignal(int) + ended = QtCore.pyqtSignal() # <-- final, real signal + + def __init__(self, instance: vlc.Instance, parent=None): + super().__init__(parent) + self.instance = instance + self.mediaplayer = self.instance.media_player_new() + self.setMinimumSize(640, 360) + + # Timer that emits position/time + self._timer = QtCore.QTimer(self) + self._timer.setInterval(200) + self._timer.timeout.connect(self._on_tick) + self._timer.start() + + # Attach VLC "end reached" event + em = self.mediaplayer.event_manager() + em.event_attach(vlc.EventType.MediaPlayerEndReached, self._on_media_end) + + def _on_media_end(self, _event): + print("[VLC] Media end reached") + # Emit Qt signal so IncidentPlayerVLC can react + self.ended.emit() + + def _on_tick(self): + if self.mediaplayer: + try: + pos = self.mediaplayer.get_position() + t = self.mediaplayer.get_time() + if pos >= 0: + self.positionChanged.emit(pos) + if t >= 0: + self.timeChanged.emit(t) + except Exception: + pass + + def set_media(self, mrl: str, options: Optional[List[str]] = None): + print(f"[VLC] set_media {mrl} opts={options or []}") + media = self.instance.media_new(mrl) + for opt in (options or []): + media.add_option(opt) + self.mediaplayer.set_media(media) + + def play(self): + if sys.platform.startswith('linux'): + self.mediaplayer.set_xwindow(int(self.winId())) + elif sys.platform.startswith('win'): + self.mediaplayer.set_hwnd(int(self.winId())) + else: + self.mediaplayer.set_nsobject(int(self.winId())) + print("[VLC] play()") + self.mediaplayer.play() + + def pause(self): + print("[VLC] pause()") + self.mediaplayer.pause() + + def set_position(self, pos01: float): + p = max(0.0, min(1.0, float(pos01))) + print(f"[VLC] set_position {p:.3f}") + self.mediaplayer.set_position(p) + + def set_time_ms(self, t_ms: int): + t = int(max(0, t_ms)) + print(f"[VLC] set_time {t}ms") + self.mediaplayer.set_time(t) + class ProxyServer: def __init__(self, media_base: str, camera: Optional[str], incident: Optional[str], @@ -250,7 +333,7 @@ def __init__(self, media_base: str, camera: Optional[str], incident: Optional[st self._app.router.add_get('/', self.handle_root) self._app.router.add_get('/dvr_seek.m3u8', self.handle_dvr_seek) self._app.router.add_get("/vod", self.handle_vod) - + self._app.router.add_get("/img", self.handle_img) # DEBUG routes self._app.router.add_get('/debug/upstream', self.handle_debug_upstream) @@ -261,6 +344,35 @@ def __init__(self, media_base: str, camera: Optional[str], incident: Optional[st self._thread: Optional[threading.Thread] = None self._loop: Optional[asyncio.AbstractEventLoop] = None + async def handle_img(self, request): + img_url = request.query.get("u") + if not img_url: + raise web.HTTPBadRequest(text="missing u") + + headers = {} + if self.token: + headers["Authorization"] = f"Bearer {self.token}" + + try: + async with ClientSession() as session: + async with session.get(img_url, headers=headers, timeout=15) as resp: + body = await resp.read() + ctype = resp.headers.get("Content-Type", "image/jpeg") + return web.Response( + body=body, + content_type=ctype, + status=resp.status, + headers=self._nocache_headers(), + ) + except Exception as e: + print(f"[HTTP] image fetch error: {e!r}") + return web.Response( + text=f"image fetch error: {type(e).__name__}: {e}", + content_type="text/plain", + status=502, + headers=self._nocache_headers(), + ) + # no-cache headers helper def _nocache_headers(self) -> dict: return { @@ -277,13 +389,14 @@ def get_durations_ms(self) -> Tuple[int, int]: segs = list(self.dvr.segments) total_ms = int(sum(s.duration for s in segs) * 1000) edge = max(1, int(getattr(Config, "LIVE_EDGE_SEGMENTS", 3))) - lag = max(0, int(getattr(Config, "LIVE_LAG_SEGMENTS", 0))) + lag = max(0, int(getattr(Config, "LIVE_LAG_SEGMENTS", 0))) # Apply dynamic lag here too so UI stays coherent with playlist lag += self._current_extra_lag() keep = min(len(segs), max(1, edge + lag)) last = segs[-keep:] if keep <= len(segs) else segs live_win_ms = int(sum(s.duration for s in last) * 1000) return (total_ms, live_win_ms) + async def handle_vod(self, request): vod_url = request.query.get("u") if not vod_url: @@ -313,8 +426,10 @@ async def handle_vod(self, request): if "Content-Range" in resp.headers: response_headers["Content-Range"] = resp.headers["Content-Range"] - print(f"[HTTP] vod {resp.status} -> {vod_url} " - f"({resp.headers.get('Content-Length', '?')} bytes, range={range_hdr})") + print( + f"[HTTP] vod {resp.status} -> {vod_url} " + f"({resp.headers.get('Content-Length', '?')} bytes, range={range_hdr})" + ) proxy_resp = web.StreamResponse(status=resp.status, headers=response_headers) await proxy_resp.prepare(request) @@ -322,14 +437,19 @@ async def handle_vod(self, request): try: async for chunk in resp.content.iter_chunked(8192): await proxy_resp.write(chunk) - await proxy_resp.write_eof() - except (asyncio.CancelledError, ConnectionResetError, ClientConnectionError, ClientPayloadError) as e: - # ✅ harmless — VLC moved to another range + except (asyncio.CancelledError, + ConnectionResetError, + ClientConnectionError, + ClientPayloadError) as e: + # Harmless — VLC moved to another range print(f"[HTTP] client disconnected early ({type(e).__name__}) — OK") except Exception as e: print(f"[HTTP] stream write error: {type(e).__name__}: {e}") finally: - await proxy_resp.write_eof() + try: + await proxy_resp.write_eof() + except Exception: + pass return proxy_resp @@ -342,7 +462,6 @@ async def handle_vod(self, request): headers=self._nocache_headers(), ) - # Dynamic lag amount based on recent 404s def _current_extra_lag(self) -> int: now = time.monotonic() @@ -387,17 +506,35 @@ async def handle_debug_upstream(self, _request: web.Request): body ] print(f"[HTTP] debug_upstream {resp.status}") - return web.Response(text="\n".join(out), content_type='text/plain', status=resp.status, headers=self._nocache_headers()) + return web.Response( + text="\n".join(out), + content_type='text/plain', + status=resp.status, + headers=self._nocache_headers(), + ) except Exception as e: - return web.Response(text=f"fetch error: {type(e).__name__}: {e}\n", content_type="text/plain", status=500, headers=self._nocache_headers()) + return web.Response( + text=f"fetch error: {type(e).__name__}: {e}\n", + content_type="text/plain", + status=500, + headers=self._nocache_headers(), + ) async def handle_debug_dvr(self, _request: web.Request): if not self.dvr: - return web.Response(text="(no DVR yet)\n", content_type="text/plain", headers=self._nocache_headers()) + return web.Response( + text="(no DVR yet)\n", + content_type="text/plain", + headers=self._nocache_headers(), + ) m3u8, total = self.dvr.render_dvr_vod_playlist(endlist=self.resolved) hdr = f"# segment_count={len(self.dvr.segments)} total_duration_seconds={total:.3f} resolved={self.resolved}\n" print(f"[HTTP] debug_dvr segments={len(self.dvr.segments)} total_s={total:.3f} endlist={self.resolved}") - return web.Response(text=hdr + m3u8, content_type="text/plain", headers=self._nocache_headers()) + return web.Response( + text=hdr + m3u8, + content_type="text/plain", + headers=self._nocache_headers(), + ) async def handle_debug_state(self, _request: web.Request): info = { @@ -418,9 +555,22 @@ async def handle_debug_state(self, _request: web.Request): def _rewrite_to_media_base(self, any_hls_url: str) -> str: if not any_hls_url: return any_hls_url + mb = urlparse(self.media_base) + + # Case 1: bare camera/incident/index.m3u8 → add /hls/ prefix + if not any_hls_url.startswith(("http://", "https://", "/")): + return f"{mb.scheme}://{mb.netloc}/hls/{any_hls_url.lstrip('/')}" + + # Case 2: starts with / but not // → relative path if any_hls_url.startswith('/') and not any_hls_url.startswith('//'): - return f"{mb.scheme}://{mb.netloc}{any_hls_url}" + # Ensure it passes through /hls/ too + path = any_hls_url.lstrip('/') + if not path.startswith('hls/'): + path = f"hls/{path}" + return f"{mb.scheme}://{mb.netloc}/{path}" + + # Case 3: full URL → normalize its host to media_base u = urlparse(any_hls_url) if not u.scheme or not u.netloc: return f"{mb.scheme}://{mb.netloc}/{any_hls_url.lstrip('/')}" @@ -441,11 +591,15 @@ def _normalize_live_playlist(self, upstream_text: str, upstream_index_url: str) while i < len(lines): l = lines[i] if l.startswith("#EXT-X-VERSION:"): - try: version = int(l.split(":", 1)[1]) - except: pass + try: + version = int(l.split(":", 1)[1]) + except Exception: + pass elif l.startswith("#EXT-X-MEDIA-SEQUENCE:"): - try: media_seq = int(l.split(":", 1)[1]) - except: media_seq = 0 + try: + media_seq = int(l.split(":", 1)[1]) + except Exception: + media_seq = 0 elif l.startswith("#EXT-X-MAP:"): m = re.search(r'URI="([^"]+)"', l) if m: @@ -459,7 +613,8 @@ def _normalize_live_playlist(self, upstream_text: str, upstream_index_url: str) attached = [] j = i + 1 while j < len(lines) and lines[j].startswith("#"): - attached.append(lines[j]); j += 1 + attached.append(lines[j]) + j += 1 if j < len(lines): uri = lines[j] segments.append((dur, attached, uri)) @@ -471,7 +626,7 @@ def _normalize_live_playlist(self, upstream_text: str, upstream_index_url: str) i += 1 base_edge = max(1, int(getattr(Config, "LIVE_EDGE_SEGMENTS", 3))) - base_lag = max(0, int(getattr(Config, "LIVE_LAG_SEGMENTS", 0))) + base_lag = max(0, int(getattr(Config, "LIVE_LAG_SEGMENTS", 0))) # Add dynamic lag derived from recent 404s effective_lag = base_lag + self._current_extra_lag() @@ -518,11 +673,14 @@ def switch_source(self, *, camera: Optional[str] = None, self._extra_lag_floor = 0 if upstream_hls: + # Always normalize, even if relative like "CAM-482A/incident-123/index.m3u8" self.upstream_index = self._rewrite_to_media_base(upstream_hls) + elif self.camera and self.incident: + # Build from camera/incident if no explicit URL + rel_path = f"{self.camera}/{self.incident}/index.m3u8" + self.upstream_index = self._rewrite_to_media_base(rel_path) else: - if not (self.camera and self.incident): - return - self.upstream_index = f"{self.media_base}/hls/{self.camera}/{self.incident}/index.m3u8" + return print(f"[SRC] switch to upstream={self.upstream_index}") @@ -540,32 +698,70 @@ def _start(): self._loop.call_soon_threadsafe(_start) def mark_resolved(self): + """Mark incident as resolved: stop polling upstream, + keep buffered segments for DVR scrubbing.""" if self.resolved: return self.resolved = True if self.dvr: try: - self.dvr.stop() + self.dvr.stop() # stop adding more segments, keep existing except Exception: pass - self.upstream_index = None - print("[SRC] incident resolved; upstream disabled; no DVR freeze") + # Do NOT clear upstream_index or dvr here; DVR is still usable. + print("[SRC] incident resolved; upstream disabled; DVR segments kept for scrubbing") # HTTP handlers async def handle_root(self, _request: web.Request): return web.Response(text='OK', content_type='text/plain', headers=self._nocache_headers()) async def handle_dvr(self, _request: web.Request): - # No DVR freeze behavior - return web.Response(text="#EXTM3U\n#EXT-X-ENDLIST\n", content_type='application/vnd.apple.mpegurl', status=410, headers=self._nocache_headers()) + # No global DVR playlist anymore + return web.Response( + text="#EXTM3U\n#EXT-X-ENDLIST\n", + content_type='application/vnd.apple.mpegurl', + status=410, + headers=self._nocache_headers(), + ) async def handle_live(self, _request: web.Request): - if self.resolved or not self.upstream_index: - return web.Response(text="#EXTM3U\n#EXT-X-ENDLIST\n", content_type='application/vnd.apple.mpegurl', status=410, headers=self._nocache_headers()) + # 1. After resolve: serve a static DVR playlist from buffered segments + if self.resolved: + if not self.dvr or not self.dvr.segments: + # No DVR buffer -> nothing to play + return web.Response( + text="#EXTM3U\n#EXT-X-ENDLIST\n", + content_type="application/vnd.apple.mpegurl", + status=410, + headers=self._nocache_headers(), + ) + + m3u8_body, total = self.dvr.render_dvr_vod_playlist(endlist=True) + print( + f"[HTTP] live.m3u8 (resolved) serving DVR snapshot: " + f"{len(self.dvr.segments)} segs, total={total:.3f}s" + ) + return web.Response( + text=m3u8_body, + content_type="application/vnd.apple.mpegurl", + status=200, + headers=self._nocache_headers(), + ) + + # 2. No source yet -> nothing to serve + if not self.upstream_index: + return web.Response( + text="#EXTM3U\n#EXT-X-ENDLIST\n", + content_type="application/vnd.apple.mpegurl", + status=410, + headers=self._nocache_headers(), + ) + # 3. Normal live mode (your existing logic...) headers = {} if self.token: headers['Authorization'] = f'Bearer {self.token}' + try: async with ClientSession() as session: async with session.get(self.upstream_index, headers=headers, timeout=10) as resp: @@ -574,14 +770,33 @@ async def handle_live(self, _request: web.Request): print(f"[HTTP] live.m3u8 upstream {resp.status}") if resp.status in (404, 410): self.mark_resolved() - return web.Response(text="#EXTM3U\n#EXT-X-ENDLIST\n", content_type='application/vnd.apple.mpegurl', status=410, headers=self._nocache_headers()) - return web.Response(text=f"# upstream {resp.status}\n{text}", content_type='text/plain', status=resp.status, headers=self._nocache_headers()) + return web.Response( + text="#EXTM3U\n#EXT-X-ENDLIST\n", + content_type='application/vnd.apple.mpegurl', + status=410, + headers=self._nocache_headers(), + ) + return web.Response( + text=f"# upstream {resp.status}\n{text}", + content_type='text/plain', + status=resp.status, + headers=self._nocache_headers(), + ) except Exception as e: print(f"[HTTP] live.m3u8 fetch error: {e!r}") - return web.Response(text=f"# fetch error: {type(e).__name__}: {e}\n", content_type='text/plain', status=502, headers=self._nocache_headers()) + return web.Response( + text=f"# fetch error: {type(e).__name__}: {e}\n", + content_type='text/plain', + status=502, + headers=self._nocache_headers(), + ) text = self._normalize_live_playlist(text, self.upstream_index) - return web.Response(text=text, content_type='application/vnd.apple.mpegurl', headers=self._nocache_headers()) + return web.Response( + text=text, + content_type='application/vnd.apple.mpegurl', + headers=self._nocache_headers(), + ) async def handle_seg(self, request: web.Request): url = request.query.get('u') @@ -600,17 +815,30 @@ async def handle_seg(self, request: web.Request): # On 404/410, bump lag so subsequent /live.m3u8 hides fresher segs if status in (404, 410): self._bump_extra_lag(floor_to=2) - return web.Response(body=body, content_type=ctype, status=status, headers=self._nocache_headers()) + return web.Response( + body=body, + content_type=ctype, + status=status, + headers=self._nocache_headers(), + ) except Exception as e: print(f"[HTTP] seg fetch error: {e!r} <- {url}") - return web.Response(text=f"segment fetch error: {type(e).__name__}: {e}", content_type="text/plain", status=502, headers=self._nocache_headers()) + return web.Response( + text=f"segment fetch error: {type(e).__name__}: {e}", + content_type="text/plain", + status=502, + headers=self._nocache_headers(), + ) async def handle_dvr_seek(self, request: web.Request): - if self.resolved or not self.dvr: - return web.Response(text="#EXTM3U\n#EXT-X-ENDLIST\n", - content_type='application/vnd.apple.mpegurl', - status=410, - headers=self._nocache_headers()) + # IMPORTANT: allow DVR seek even when resolved, as long as we still have a DVR buffer. + if not self.dvr: + return web.Response( + text="#EXTM3U\n#EXT-X-ENDLIST\n", + content_type='application/vnd.apple.mpegurl', + status=410, + headers=self._nocache_headers(), + ) t_ms_str = request.query.get('t', '0') try: @@ -652,7 +880,6 @@ async def handle_dvr_seek(self, request: web.Request): out.append(f'#EXT-X-MEDIA-SEQUENCE:{media_seq}') # PRECISE intra-segment start (many players honor this; helps VLC too) - # Start "intra_ms" seconds *into* the first segment of this playlist. out.append(f'#EXT-X-START:TIME-OFFSET={intra_ms/1000.0:.3f},PRECISE=YES') if init_url: @@ -663,12 +890,16 @@ async def handle_dvr_seek(self, request: web.Request): out.append(f'/seg?u={s.abs_url}') body = "\n".join(out) + "\n" - print(f"[HTTP] dvr_seek.m3u8 t={t_ms}ms -> start_idx={start_idx} intra={int(intra_ms)}ms segs={len(trimmed)} resolved={self.resolved}") - # Optional debug header — handy to confirm behavior in logs/curl: + print( + f"[HTTP] dvr_seek.m3u8 t={t_ms}ms -> start_idx={start_idx} " + f"intra={int(intra_ms)}ms segs={len(trimmed)} resolved={self.resolved}" + ) headers = self._nocache_headers() | {"X-Start-Offset-Ms": str(int(intra_ms))} - return web.Response(text=body, - content_type='application/vnd.apple.mpegurl', - headers=headers) + return web.Response( + text=body, + content_type='application/vnd.apple.mpegurl', + headers=headers, + ) # Lifecycle def start(self): @@ -686,8 +917,10 @@ def _run_loop(): finally: loop.run_until_complete(self._runner.cleanup()) loop.stop() - if is_port_in_use(19090): - print("[INFO] DVR proxy already running on port 19090, reusing it.") + + # Use the configured port, not a hardcoded one + if is_port_in_use(self.port, self.bind): + print(f"[INFO] DVR proxy already running on port {self.port}, reusing it.") else: self._thread = threading.Thread(target=_run_loop, daemon=True) self._thread.start() @@ -696,8 +929,9 @@ def stop(self): if self.dvr: self.dvr.stop() + # ────────────────────────────────────────────────────────────────────────────── -# LEFT PANE + UI — unchanged except: no DVR freeze on resolve +# LEFT PANE + UI — unchanged except: DVR seek allowed after resolve # ────────────────────────────────────────────────────────────────────────────── class AlertsModel(QtCore.QAbstractListModel): def __init__(self): @@ -739,11 +973,11 @@ def _key(self, it: dict) -> tuple[str, str]: return (str(it.get("camera") or ""), str(it.get("incident_id") or "")) def as_dict(self) -> dict[tuple[str, str], dict]: - return { self._key(it): it for it in self._items } + return {self._key(it): it for it in self._items} - def replace_with(self, merged: dict[tuple[str,str], dict]): + def replace_with(self, merged: dict[tuple[str, str], dict]): self.set_alerts(list(merged.values())) - + def remove_by_key(self, camera: str, incident_id: str): k = (str(camera or ""), str(incident_id or "")) for i, it in enumerate(self._items): @@ -754,6 +988,7 @@ def remove_by_key(self, camera: str, incident_id: str): return True return False + class AlertItemDelegate(QtWidgets.QStyledItemDelegate): def paint(self, painter: QtGui.QPainter, option: QtWidgets.QStyleOptionViewItem, index: QtCore.QModelIndex): model: AlertsModel = index.model() # type: ignore @@ -776,28 +1011,42 @@ def paint(self, painter: QtGui.QPainter, option: QtWidgets.QStyleOptionViewItem, x = chip.right() + 10 cam = str(a.get("camera") or "") anom = str(a.get("anomaly") or "") + subject = str(a.get("subject") or "") + if anom.lower() in ("intruding animal", "intruding_animal", "climbing_fence") and subject: + anom = f"{anom.title()} ({subject.title()})" + else: + anom = anom.title() + inc = str(a.get("incident_id") or "")[:8] - title_font = QtGui.QFont(option.font); title_font.setPointSizeF(option.font.pointSizeF() + 1); title_font.setBold(True) - sub_font = QtGui.QFont(option.font); sub_font.setPointSizeF(option.font.pointSizeF() - 1) + title_font = QtGui.QFont(option.font) + title_font.setPointSizeF(option.font.pointSizeF() + 1) + title_font.setBold(True) + sub_font = QtGui.QFont(option.font) + sub_font.setPointSizeF(option.font.pointSizeF() - 1) painter.setPen(QtGui.QColor("#111827")) painter.setFont(title_font) - painter.drawText(QtCore.QRect(x, r.top() + 4, r.width() - 20, 18), - QtCore.Qt.AlignmentFlag.AlignLeft | QtCore.Qt.AlignmentFlag.AlignVCenter, - f"{cam} • {anom}") + painter.drawText( + QtCore.QRect(x, r.top() + 4, r.width() - 20, 18), + QtCore.Qt.AlignmentFlag.AlignLeft | QtCore.Qt.AlignmentFlag.AlignVCenter, + f"{cam} • {anom}", + ) painter.setPen(QtGui.QColor("#6b7280")) painter.setFont(sub_font) - painter.drawText(QtCore.QRect(x, r.top() + 22, r.width() - 20, 16), - QtCore.Qt.AlignmentFlag.AlignLeft | QtCore.Qt.AlignmentFlag.AlignVCenter, - f"Incident: {inc}… • Status: {status}") + painter.drawText( + QtCore.QRect(x, r.top() + 22, r.width() - 20, 16), + QtCore.Qt.AlignmentFlag.AlignLeft | QtCore.Qt.AlignmentFlag.AlignVCenter, + f"Incident: {inc}… • Status: {status}", + ) painter.restore() def sizeHint(self, option: QtWidgets.QStyleOptionViewItem, _index: QtCore.QModelIndex) -> QtCore.QSize: return QtCore.QSize(220, 42) + LEFT_LIST_QSS = """ QListView { padding: 6px; @@ -813,6 +1062,7 @@ def sizeHint(self, option: QtWidgets.QStyleOptionViewItem, _index: QtCore.QModel #LeftHeader { color: #6b7280; font-weight: 600; letter-spacing: 0.4px; margin: 0 6px 6px 6px; } """ + class SeekSlider(QtWidgets.QSlider): hovered = QtCore.pyqtSignal(int) clickedTo = QtCore.pyqtSignal(int) @@ -823,7 +1073,7 @@ def __init__(self, orientation, parent=None): self._press_x: Optional[float] = None self._moved: bool = False self._CLICK_EPS = 4.0 - self._EDGE_SNAP_PX = 8 # ← new: snap zone near the ends + self._EDGE_SNAP_PX = 8 # snap zone near the ends def mousePressEvent(self, ev: QtGui.QMouseEvent): if ev.button() == Qt.MouseButton.LeftButton: @@ -866,12 +1116,12 @@ def _value_for_x(self, x: float) -> int: QtWidgets.QStyle.ComplexControl.CC_Slider, opt, QtWidgets.QStyle.SubControl.SC_SliderGroove, - self + self, ) if groove.width() <= 0: return self.value() - # NEW: snap to exact min/max if you're near the ends + # snap to exact min/max if you're near the ends if x <= groove.left() + self._EDGE_SNAP_PX: return self.minimum() if x >= groove.right() - self._EDGE_SNAP_PX: @@ -895,68 +1145,15 @@ def __init__(self, vlc_widget: QtWidgets.QWidget, parent=None): def show_loading(self, on: bool): self.setCurrentIndex(1 if on else 0) -class VlcWidget(QtWidgets.QFrame): - positionChanged = QtCore.pyqtSignal(float) - timeChanged = QtCore.pyqtSignal(int) - def __init__(self, instance: vlc.Instance, parent=None): - super().__init__(parent) - self.instance = instance - self.mediaplayer = self.instance.media_player_new() - self.setMinimumSize(640, 360) - self._timer = QtCore.QTimer(self) - self._timer.setInterval(200) - self._timer.timeout.connect(self._on_tick) - self._timer.start() - - def _on_tick(self): - if self.mediaplayer: - try: - pos = self.mediaplayer.get_position() - t = self.mediaplayer.get_time() - if pos >= 0: - self.positionChanged.emit(pos) - if t >= 0: - self.timeChanged.emit(t) - except Exception: - pass - - def set_media(self, mrl: str, options: Optional[List[str]] = None): - print(f"[VLC] set_media {mrl} opts={options or []}") - media = self.instance.media_new(mrl) - for opt in (options or []): - media.add_option(opt) - self.mediaplayer.set_media(media) - - def play(self): - if sys.platform.startswith('linux'): - self.mediaplayer.set_xwindow(int(self.winId())) - elif sys.platform.startswith('win'): - self.mediaplayer.set_hwnd(int(self.winId())) - else: - self.mediaplayer.set_nsobject(int(self.winId())) - print("[VLC] play()") - self.mediaplayer.play() - - def pause(self): - print("[VLC] pause()") - self.mediaplayer.pause() - - def set_position(self, pos01: float): - p = max(0.0, min(1.0, float(pos01))) - print(f"[VLC] set_position {p:.3f}") - self.mediaplayer.set_position(p) - - def set_time_ms(self, t_ms: int): - t = int(max(0, t_ms)) - print(f"[VLC] set_time {t}ms") - self.mediaplayer.set_time(t) class IncidentPlayerVLC(QtWidgets.QWidget): - def __init__(self, api,alert_service, parent=None): + def __init__(self, api, alert_service, parent=None): super().__init__(parent) self.api = api self.alert_service = alert_service + self.allow_autoplay = False + self._is_current_page = False self.cfg = Config() self.proxy = ProxyServer( media_base=self.cfg.MEDIA_BASE, @@ -1005,8 +1202,10 @@ def __init__(self, api,alert_service, parent=None): self.vlc_instance = vlc.Instance(*vlc_opts) self.vlcw = VlcWidget(self.vlc_instance) self.videoSurface = VideoSurface(self.vlcw) - self.videoSurface.setSizePolicy(QtWidgets.QSizePolicy.Policy.Expanding, - QtWidgets.QSizePolicy.Policy.Expanding) + self.videoSurface.setSizePolicy( + QtWidgets.QSizePolicy.Policy.Expanding, + QtWidgets.QSizePolicy.Policy.Expanding, + ) # Controls self.btnLive = QtWidgets.QPushButton('Go Live') @@ -1021,8 +1220,10 @@ def __init__(self, api,alert_service, parent=None): # LEFT PANE leftContainer = QtWidgets.QGroupBox("Alerts") - leftContainer.setSizePolicy(QtWidgets.QSizePolicy.Policy.Fixed, - QtWidgets.QSizePolicy.Policy.Expanding) + leftContainer.setSizePolicy( + QtWidgets.QSizePolicy.Policy.Fixed, + QtWidgets.QSizePolicy.Policy.Expanding, + ) leftContainer.setMinimumWidth(300) leftContainer.setMaximumWidth(340) @@ -1047,8 +1248,10 @@ def __init__(self, api,alert_service, parent=None): # Details inside player pane self.detailGroup = QtWidgets.QGroupBox("Details") - self.detailGroup.setSizePolicy(QtWidgets.QSizePolicy.Policy.Preferred, - QtWidgets.QSizePolicy.Policy.Fixed) + self.detailGroup.setSizePolicy( + QtWidgets.QSizePolicy.Policy.Preferred, + QtWidgets.QSizePolicy.Policy.Fixed, + ) grid = QtWidgets.QGridLayout(self.detailGroup) grid.setContentsMargins(12, 8, 12, 12) grid.setHorizontalSpacing(24) @@ -1120,7 +1323,6 @@ def __init__(self, api,alert_service, parent=None): rightLayout.addLayout(ctrls, 0) rightLayout.addWidget(self.detailGroup, 0) - self.rightStack.addWidget(self.emptyPane) self.rightStack.addWidget(self.playerPane) self.rightStack.setCurrentIndex(0) @@ -1137,52 +1339,15 @@ def __init__(self, api,alert_service, parent=None): outer = QtWidgets.QVBoxLayout(self) outer.setContentsMargins(6, 6, 6, 6) outer.setSpacing(6) - # outer.addWidget(splitter) - # --- Navigation bar --- - navBar = QtWidgets.QHBoxLayout() - navBar.setContentsMargins(6, 6, 6, 6) - navBar.setSpacing(8) - - btnLiveView = QtWidgets.QPushButton("Live Incidents") - btnLiveView.setCheckable(True) - btnLiveView.setChecked(True) - btnHistory = QtWidgets.QPushButton("Events History") - btnHistory.setCheckable(True) - - btnStyle = """ - QPushButton { - background:#e5e7eb; border:none; border-radius:8px; - padding:6px 12px; font-weight:600; - } - QPushButton:checked { background:#10b981; color:white; } - """ - btnLiveView.setStyleSheet(btnStyle) - btnHistory.setStyleSheet(btnStyle) - - navBar.addWidget(btnLiveView) - navBar.addWidget(btnHistory) - navBar.addStretch(1) - - # --- Main content stack --- - self.stack = QtWidgets.QStackedWidget() - self.livePage = QtWidgets.QWidget() - self.liveLayout = QtWidgets.QVBoxLayout(self.livePage) - self.liveLayout.setContentsMargins(0, 0, 0, 0) - self.liveLayout.addWidget(splitter) - - self.historyPage = EventsHistoryPage(api=self.api) - self.stack.addWidget(self.livePage) - self.stack.addWidget(self.historyPage) - - # --- Combine all together --- - outer.addLayout(navBar) - outer.addWidget(self.stack) - - # --- Navigation logic --- - btnLiveView.clicked.connect(lambda: self._switch_page(0, btnLiveView, btnHistory)) - btnHistory.clicked.connect(lambda: self._switch_page(1, btnHistory, btnLiveView)) + # Live page only; history/analytics in external navigation + livePage = QtWidgets.QWidget() + liveLayout = QtWidgets.QVBoxLayout(livePage) + liveLayout.setContentsMargins(0, 0, 0, 0) + liveLayout.setSpacing(0) + liveLayout.addWidget(splitter) + outer.addWidget(livePage) # State self.mode_live = False @@ -1191,6 +1356,8 @@ def __init__(self, api,alert_service, parent=None): self.current_camera: Optional[str] = None self.current_incident: Optional[str] = None self.current_status: str = "firing" + self.current_alert: Optional[dict] = None + self._last_abs_t_ms: int = 0 self._playlist_offset_ms: int = 0 @@ -1202,7 +1369,7 @@ def __init__(self, api,alert_service, parent=None): self._live_sync.setInterval(800) self._live_sync.timeout.connect(self._maybe_sync_live_timeline) - #new + # grows DVR slider while paused/seeked self._dvr_growth = QTimer(self) self._dvr_growth.setInterval(1200) self._dvr_growth.timeout.connect(self._maybe_grow_dvr_range_only) @@ -1219,24 +1386,6 @@ def __init__(self, api,alert_service, parent=None): else: print("[IncidentPlayer] Using cached alerts:", len(self.alert_service.alerts)) self._on_alerts_updated(self.alert_service.alerts) - # WebSocket + snapshot - # self.ws: Optional[QWebSocket] = None - # self.ws_url: Optional[QUrl] = QUrl(self.cfg.ALERTS_WS) if self.cfg.ALERTS_WS else None - # self._ws_backoff_sec = 1 - # self._ws_ping = QTimer(self) - # self._ws_ping.setInterval(15000) - # self._ws_ping.timeout.connect(self._ws_send_ping) - # self._got_initial_snapshot = False - # self._snapshot_resends = 0 - # self._snapshot_retry_timer = QTimer(self) - # self._snapshot_retry_timer.setInterval(1200) - # self._snapshot_retry_timer.timeout.connect(self._on_snapshot_retry_tick) - # self.net = QNetworkAccessManager(self) - # self.net.finished.connect(self._on_http_finished) - # self._awaiting_http_snapshot = False - - # if self.ws_url: - # self._ws_connect() # Connections self.btnLive.clicked.connect(self._go_live) @@ -1245,15 +1394,96 @@ def __init__(self, api,alert_service, parent=None): self.slider.draggedTo.connect(self._on_slider_drag_released) self.vlcw.positionChanged.connect(self._on_vlc_pos) self.vlcw.timeChanged.connect(self._on_vlc_time) + self.vlcw.ended.connect(self._on_vlc_end) self.alertList.clicked.connect(self._on_pick_alert_from_list) self._show_player(False) self._set_idle() + def _on_vlc_end(self): + print("[VLC] end reached (proxy.resolved=%s, alerts_empty=%s)" + % (self.proxy.resolved, self.alertModel.is_empty())) + + # If incident is resolved and there are no *firing* alerts left, + # we can fully tear down the player and hide the panels. + if self.proxy.resolved: + have_firing = any( + (a.get("status") or "firing").lower() == "firing" + for a in self.alertModel._items + ) + + if not have_firing: + # Stop VLC + try: + self.vlcw.mediaplayer.stop() + except Exception: + pass + + # Optionally drop the current resolved incident from the list, + # so the left list is also "clean". + if self.current_camera and self.current_incident: + self.alertModel.remove_by_key(self.current_camera, + self.current_incident) + + # Clear current state + self.current_camera = None + self.current_incident = None + self.current_alert = None + self.dvr_duration_ms = 0 + + # Reset UI + hide player + self._set_idle() + self._show_player(False) # switch to NO-ALERTS pane + print("[MODE] DVR clip finished; no firing alerts → hiding player") + return + + # Case 2: still have firing alerts or proxy not resolved — normal DVR mode + self.mode_live = False + self._set_live_badge(False) + print("[MODE] clip finished; staying in DVR mode") + + + + def showEvent(self, event): + super().showEvent(event) + + if not self.isVisible(): + return + + if not self._is_current_page: + self._is_current_page = True + self.allow_autoplay = True + print("[IncidentPlayer] Activated (autoplay enabled)") + + # Restore video surface + self.videoSurface.show() + + # If alerts exist, auto-play the first one + if self.alertModel._items: + self._show_player(True) + self._play_alert(self.alertModel._items[0]) + + def hideEvent(self, event): + super().hideEvent(event) + + if self._is_current_page: + self._is_current_page = False + self.allow_autoplay = False + print("[IncidentPlayer] Deactivated (autoplay disabled)") + + # Stop VLC safely + try: + self.vlcw.mediaplayer.stop() + except Exception: + pass + + # Hide video surface to stop painting + self.videoSurface.hide() + + self._set_idle() def _on_alerts_updated(self, alerts: list): """Called when AlertService emits full list (on initial load).""" print(f"[AlertService] Full update: {len(alerts)} alerts") - print("[DEBUG] alerts from AlertService:", alerts) self._apply_firing_list(alerts) def _on_alert_added(self, alert: dict): @@ -1262,14 +1492,44 @@ def _on_alert_added(self, alert: dict): self._merge_firing_deltas([alert]) def _on_alert_removed(self, alert_id: str): - """Called when an alert is resolved/removed.""" print(f"[AlertService] Alert removed: {alert_id}") - self.alertModel.set_alerts([ - a for a in self.alertModel._items if a.get("alert_id") != alert_id - ]) + + is_current = (self.current_incident == alert_id) + + new_items: list[dict] = [] + for a in self.alertModel._items: + if a.get("incident_id") != alert_id: + new_items.append(a) + else: + # This is the removed alert + if is_current and self.proxy.dvr and len(self.proxy.dvr.segments) > 0: + updated = dict(a) + updated["status"] = "resolved" + new_items.append(updated) + # else: drop it completely + + self.alertModel.set_alerts(new_items) + + if is_current: + self.current_status = "resolved" + # Update cached alert metadata if we still have it + self.current_alert = next( + (a for a in new_items if a.get("incident_id") == alert_id), + self.current_alert, + ) + try: + self.proxy.mark_resolved() + except Exception as e: + print(f"[IncidentPlayer] mark_resolved failed: {e!r}") + + # UI: DVR-only mode + self.mode_live = False + self._set_live_badge(False) + self._update_right_pane_visibility() + def _fetch_active_alerts_from_db(self): """Fetch current active alerts directly from the DB API.""" try: @@ -1288,16 +1548,30 @@ def _fetch_active_alerts_from_db(self): print(f"[DB] Error fetching alerts: {e}") return [] - # ───── NO-ALERTS helpers ───── def _show_player(self, on: bool): self.rightStack.setCurrentIndex(1 if on else 0) print(f"[UI] right pane -> {'PLAYER' if on else 'NO-ALERTS'}") def _update_right_pane_visibility(self): - have_any = not self.alertModel.is_empty() - print("_update_right_pane_visibility called have any",have_any) - if not have_any: + have_any_list = not self.alertModel.is_empty() + + # We also keep the player visible if we have a "current" incident + # (even if it is resolved) and we still have a DVR buffer to scrub. + have_current_dvr = ( + self.current_camera is not None + and self.current_incident is not None + and self.proxy.dvr is not None + and len(self.proxy.dvr.segments) > 0 + ) + + print( + "_update_right_pane_visibility called: " + f"have_any_list={have_any_list}, have_current_dvr={have_current_dvr}" + ) + + if not have_any_list and not have_current_dvr: + # Nothing in the list and nothing to scrub → fully idle. try: self.vlcw.mediaplayer.stop() except Exception: @@ -1305,70 +1579,43 @@ def _update_right_pane_visibility(self): self._set_idle() self._show_player(False) else: + # Either we have firing alerts or a resolved incident with DVR buffer. self._show_player(True) - - def _switch_page(self, index: int, active_btn: QtWidgets.QPushButton, inactive_btn: QtWidgets.QPushButton): - self.stack.setCurrentIndex(index) - active_btn.setChecked(True) - inactive_btn.setChecked(False) - print(f"[UI] switched to page index={index}") # ───── alerts helpers ───── def _key(self, it: dict) -> tuple[str, str]: return (str(it.get('camera') or ''), str(it.get('incident_id') or '')) - # def _normalize_alert(self, it: dict) -> dict: - # if not isinstance(it, dict): - # return {} - - # labels = it.get("labels", {}) or {} - # ann = it.get("annotations", {}) or {} - - # # Normalize field names - # flat = { - # "camera": labels.get("device") or ann.get("device") or "unknown", - # "incident_id": labels.get("alert_id") or ann.get("alert_id"), - # "anomaly": labels.get("alertname") or ann.get("category") or "unknown", - # "hls": ann.get("hls"), - # "vod": ann.get("vod"), - # "image_url": ann.get("image_url"), - # "lat": ann.get("lat"), - # "lon": ann.get("lon"), - # "severity": ann.get("severity"), - # "summary": ann.get("summary"), - # "recommendation": ann.get("recommendation"), - # "category": ann.get("category"), - # "startsAt": it.get("startsAt"), - # "endsAt": it.get("endsAt"), - # } - - # # Status inference (Alertmanager has endsAt → resolved) - # ends_at = it.get("endsAt") - # flat["status"] = "resolved" if ends_at else "firing" - - # return flat def _normalize_alert(self, it: dict) -> dict: + meta = it.get("meta") or {} + if isinstance(meta, str): + try: + meta = json.loads(meta) + except Exception: + meta = {} + ended = ( + it.get("ended_at") or + it.get("endsAt") or + it.get("endedAt") + ) return { "camera": it.get("device_id") or it.get("camera"), "incident_id": it.get("alert_id") or it.get("incident_id"), "anomaly": it.get("alert_type") or it.get("anomaly"), + "subject": it.get("subject") or meta.get("subject"), "hls": it.get("hls"), "vod": it.get("vod"), "image_url": it.get("image_url"), "summary": it.get("summary"), "severity": it.get("severity"), "started_at": it.get("started_at") or it.get("startsAt"), - "ended_at": it.get("ended_at") or it.get("endsAt"), - "status": "firing" if not (it.get("ended_at") or it.get("endsAt")) else "resolved", + "ended_at": ended, + "status": "resolved" if ended else "firing", } - - - - ##new + # Only expand DVR while paused/seeked (DVR mode). Never move the thumb. def _maybe_grow_dvr_range_only(self): - # Only expand the slider max while paused/seeked (DVR mode). Never move the thumb. if self.mode_live: self._dvr_growth.stop() return @@ -1379,12 +1626,17 @@ def _maybe_grow_dvr_range_only(self): self.dvr_duration_ms = new_max self.slider.setRange(0, self.dvr_duration_ms) - def _apply_firing_list(self, firing: list[dict]): firing = [self._normalize_alert(it) for it in (firing or []) if it] - print("[DEBUG] normalized firing list:", firing) - firing = [it for it in firing if (it.get("status") or "firing").lower() == "firing"] + # only keep desired alert types that are still firing + firing = [ + it for it in firing + if (it.get("status") or "firing").lower() == "firing" + and (it.get("anomaly") or "").lower() in self.cfg.ALLOWED_TYPES + ] + + # Track currently selected item (optional; same as before) sel = self.alertList.selectionModel().currentIndex() if self.alertList.selectionModel() else QtCore.QModelIndex() selected_inc = selected_cam = None if sel.isValid(): @@ -1395,45 +1647,56 @@ def _apply_firing_list(self, firing: list[dict]): except Exception: pass - self.alertModel.set_alerts(firing) - self._update_right_pane_visibility() - - if selected_inc is not None: - for row, it in enumerate(firing): - if it.get('incident_id') == selected_inc and it.get('camera') == selected_cam: - idx = self.alertModel.index(row, 0) - self.alertList.selectionModel().select(idx, QtCore.QItemSelectionModel.SelectionFlag.ClearAndSelect) - self.alertList.setCurrentIndex(idx) - break - cur_cam = self.current_camera cur_inc = self.current_incident or self.cfg.INCIDENT + has_current = bool(cur_cam and cur_inc) + still_there = any( - it.get('camera') == cur_cam and it.get('incident_id') == cur_inc + it.get('camera') == cur_cam and + (it.get('incident_id') or it.get('alert_id')) == cur_inc for it in firing - ) if (cur_cam and cur_inc) else False + ) if has_current else False - if (cur_cam and cur_inc) and not still_there: - if self.current_camera and self.current_incident: - self.alertModel.remove_by_key(self.current_camera, self.current_incident) + effective_list = list(firing) + + # Case: the current incident is no longer "firing" in the upstream list → resolved + if has_current and not still_there: self.current_status = "resolved" - self.proxy.mark_resolved() try: - self.vlcw.mediaplayer.stop() - except Exception: - pass + self.proxy.mark_resolved() + except Exception as e: + print(f"[IncidentPlayer] mark_resolved failed in _apply_firing_list: {e!r}") + + # Keep it in the left list while we still have DVR segments + if self.proxy.dvr is not None and len(self.proxy.dvr.segments) > 0: + base = dict(self.current_alert or {}) + base.setdefault("camera", cur_cam) + base.setdefault("incident_id", cur_inc) + base["status"] = "resolved" + if (base.get("anomaly") or "").lower() in self.cfg.ALLOWED_TYPES: + key = (base.get("camera"), base.get("incident_id")) + if not any( + it.get("camera") == key[0] and it.get("incident_id") == key[1] + for it in effective_list + ): + effective_list.append(base) + + self.alertModel.set_alerts(effective_list) + self._update_right_pane_visibility() + return + + # Normal case: just "firing" alerts + (possibly) already kept resolved ones + self.alertModel.set_alerts(effective_list) + self._update_right_pane_visibility() - if firing: + # Autoplay only when there was NO current incident at all (e.g., first load) + if firing and not has_current: + if self.allow_autoplay: self._show_player(True) self._play_alert(firing[0]) else: - self._set_idle() - self._show_player(False) - return + print("[IncidentPlayer] Ignored new alert (page not visible)") - if firing and not still_there: - self._show_player(True) - self._play_alert(firing[0]) def _merge_firing_deltas(self, deltas: list[dict]): current = self.alertModel.as_dict() @@ -1441,31 +1704,47 @@ def _merge_firing_deltas(self, deltas: list[dict]): for raw in (deltas or []): it = self._normalize_alert(raw) - print("[DEBUG] normalized:", it) + if (it.get("anomaly") or "").lower() not in self.cfg.ALLOWED_TYPES: + continue # skip other alert types + k = self._key(it) + status = (it.get("status") or "firing").lower() - if it.get('status') == 'firing': + if status == 'firing': if current.get(k) != it: current[k] = it changed = True else: - if k in current: - current.pop(k, None) + # resolved / non-firing + keep_on_left = ( + (self.current_camera, self.current_incident) == k + and self.proxy.dvr is not None + and len(self.proxy.dvr.segments) > 0 + ) + if keep_on_left: + stored = dict(current.get(k, it)) + stored.update(it) + stored["status"] = "resolved" + current[k] = stored changed = True + else: + if k in current: + current.pop(k, None) + changed = True - if (self.current_camera, self.current_incident) == k and it.get('status') != 'firing': + if (self.current_camera, self.current_incident) == k and status != 'firing': + # Current incident resolved: stop polling upstream, + # but keep DVR and keep it in the list so UI doesn't "blink out". self.current_status = "resolved" + self.current_alert = it self.proxy.mark_resolved() - if self.current_camera and self.current_incident: - self.alertModel.remove_by_key(self.current_camera, self.current_incident) - try: - self.vlcw.mediaplayer.stop() - except Exception: - pass + print("[IncidentPlayer] Current incident resolved via delta; DVR-only mode") + # Do NOT remove from model and do NOT stop the mediaplayer here. if not changed: return + # Same selection-restore logic as before sel = self.alertList.selectionModel().currentIndex() if self.alertList.selectionModel() else QtCore.QModelIndex() selected_key = None if sel.isValid(): @@ -1473,34 +1752,55 @@ def _merge_firing_deltas(self, deltas: list[dict]): cur = self.alertModel.get(sel.row()) selected_key = self._key(cur) except Exception: - pass + selected_key = None self.alertModel.replace_with(current) - self._update_right_pane_visibility() - - if selected_key: - items = list(current.values()) - for row, it in enumerate(items): - if self._key(it) == selected_key: - idx = self.alertModel.index(row, 0) - self.alertList.selectionModel().select(idx, QtCore.QItemSelectionModel.SelectionFlag.ClearAndSelect) - self.alertList.setCurrentIndex(idx) - break cur_cam = self.current_camera cur_inc = self.current_incident or self.cfg.INCIDENT has_current = (cur_cam and cur_inc and (cur_cam, cur_inc) in current) + + # Restore selection for any remaining alert (same as before) + if self.alertList.selectionModel() and self.alertList.selectionModel().currentIndex().isValid(): + selected_key = None + try: + cur = self.alertModel.get(self.alertList.selectionModel().currentIndex().row()) + selected_key = self._key(cur) + except Exception: + selected_key = None + + if selected_key: + items = list(current.values()) + for row, it in enumerate(items): + if self._key(it) == selected_key: + idx = self.alertModel.index(row, 0) + self.alertList.selectionModel().select( + idx, QtCore.QItemSelectionModel.SelectionFlag.ClearAndSelect + ) + self.alertList.setCurrentIndex(idx) + break + + # Now decide visibility using the helper (which also checks DVR) + self._update_right_pane_visibility() + if not has_current: items = list(current.values()) if items: - self._show_player(True) - self._play_alert(items[0]) + if self.allow_autoplay: + self._show_player(True) + self._play_alert(items[0]) + else: + print("[IncidentPlayer] Ignored alert (page not visible)") else: - try: self.vlcw.mediaplayer.stop() - except Exception: pass + try: + self.vlcw.mediaplayer.stop() + except Exception: + pass self._set_idle() self._show_player(False) + + # ───── helpers ───── def _freeze_ui(self, seconds: float = 0.8): self._ui_freeze_deadline = time.monotonic() + max(0.1, seconds) @@ -1533,185 +1833,6 @@ def _maybe_sync_live_timeline(self): self._last_abs_t_ms = abs_t self._update_time_label(abs_t) - # WebSocket & snapshot (same as before) … - def _ws_connect(self): - if not self.ws_url: - print("[WS] ALERTS_WS not set; skipping alerts websocket.") - return - if self.ws: - try: - self.ws.abort() - except Exception: - pass - self.ws = QWebSocket() - self.ws.connected.connect(self._on_ws_connected) - self.ws.textMessageReceived.connect(self._on_ws_msg) - self.ws.disconnected.connect(self._on_ws_disconnected) - self.ws.errorOccurred.connect(self._on_ws_error) - print(f"[WS] connecting to {self.ws_url.toString()}") - self.ws.open(self.ws_url) - - def _send_ws_snapshot_request(self): - try: - if self.ws and self.ws.isValid(): - self.ws.sendTextMessage('{"type":"get_snapshot"}') - self.ws.sendTextMessage('{"type":"snapshot_request"}') - except Exception: - pass - - def _on_ws_connected(self): - print("[WS] connected") - self._ws_backoff_sec = 1 - self._ws_ping.start() - - # Instead of waiting for a snapshot message, immediately fetch from DB - alerts = self._fetch_active_alerts_from_db() - if alerts: - print(f"[WS] Initial load: {len(alerts)} alerts fetched from DB") - self._apply_firing_list(alerts) - else: - print("[WS] No active alerts found in DB") - - # Continue listening for WebSocket deltas - self._got_initial_snapshot = True - self._snapshot_retry_timer.stop() - - - def _on_snapshot_retry_tick(self): - if self._got_initial_snapshot: - self._snapshot_retry_timer.stop() - return - if self._snapshot_resends < 3: - print(f"[WS] requesting snapshot again (attempt {self._snapshot_resends+2}/4)") - self._send_ws_snapshot_request() - self._snapshot_resends += 1 - if self.cfg.ALERTS_SNAPSHOT_HTTP and not self._awaiting_http_snapshot: - self._request_http_snapshot() - if self._snapshot_resends >= 3 and not self.cfg.ALERTS_SNAPSHOT_HTTP: - self._snapshot_retry_timer.stop() - - def _request_http_snapshot(self): - try: - url = QUrl(self.cfg.ALERTS_SNAPSHOT_HTTP) - if not url.isValid() or url.isEmpty(): - return - req = QNetworkRequest(url) - if self.cfg.TOKEN and self.cfg.TOKEN != "CHANGE_ME": - req.setRawHeader(b"Authorization", f"Bearer {self.cfg.TOKEN}".encode("utf-8")) - self._awaiting_http_snapshot = True - print(f"[HTTP] requesting snapshot from {url.toString()}") - self.net.get(req) - except Exception as e: - print(f"[HTTP] snapshot request error: {e!r}") - - def _on_http_finished(self, reply): - try: - if not self._awaiting_http_snapshot: - reply.deleteLater() - return - self._awaiting_http_snapshot = False - data = bytes(reply.readAll()) - try: - payload = json.loads(data.decode("utf-8")) - except Exception: - payload = [] - if isinstance(payload, dict): - items = payload.get("items") or payload.get("alerts") or payload.get("data") or [] - elif isinstance(payload, list): - items = payload - else: - items = [] - firing = [it for it in items if (it or {}).get("status", "").lower() == "firing"] - print(f"[HTTP] snapshot received: {len(firing)} firing") - self._apply_firing_list(firing) - self._got_initial_snapshot = True - self._snapshot_retry_timer.stop() - finally: - reply.deleteLater() - - def _on_ws_disconnected(self): - print("[WS] disconnected") - self._ws_ping.stop() - self._schedule_ws_reconnect() - - def _on_ws_error(self, err): - print(f"[WS] error: {self.ws.errorString()}") - if not self._ws_ping.isActive(): - self._schedule_ws_reconnect() - - def _ws_send_ping(self): - try: - if self.ws and self.ws.isValid(): - self.ws.sendTextMessage('{"type":"ping"}') - except Exception: - pass - - def _schedule_ws_reconnect(self): - delay = min(self._ws_backoff_sec, 30) - print(f"[WS] reconnecting in {delay}s...") - QtCore.QTimer.singleShot(int(delay * 1000), self._ws_connect) - self._ws_backoff_sec = min(self._ws_backoff_sec * 2, 30) - - def _on_ws_msg(self, text: str): - print("=" * 80) - print("[WS] RAW MESSAGE:", text[:600].replace("\n", " ")) - - # Try to parse JSON - try: - msg = json.loads(text) - except Exception as e: - print(f"[WS] non-JSON message ({type(e).__name__}):", text[:120]) - return - - t = (msg.get("type") or "").lower() - items = msg.get("items") or msg.get("alerts") or msg.get("data") or [] - print(f"[WS] Type='{t}' | items={len(items)}") - - # Log short summary of each alert item - for i, it in enumerate(items): - print(f" [{i}] camera={it.get('camera')} " - f"incident={it.get('incident_id')} " - f"status={it.get('status')} " - f"endsAt={it.get('endsAt')} " - f"summary={it.get('summary')}") - - # Normalize alerts - norm = [self._normalize_alert(it) for it in (items or []) if it] - print(f"[WS] After normalize → {[it.get('status') for it in norm]}") - - # Infer missing statuses - for it in norm: - st = (it.get("status") or "").lower() - if not st: - it["status"] = "resolved" if it.get("endsAt") else "firing" - - # Compute "currently firing" view - firing_now = [it for it in norm if (it.get("status") or "firing").lower() == "firing"] - print(f"[WS] Firing after filter: {len(firing_now)} / {len(norm)} → " - f"{[it.get('status') for it in firing_now]}") - - # Decide what to do based on type - if t == 'am_alerts': - print("[WS] Handling am_alerts as delta update (can include resolved)") - self._merge_firing_deltas(norm) - return - - if t in ('snapshot', 'update', 'delta', 'patch'): - print(f"[WS] Handling message type '{t}' as full state replace") - self._apply_firing_list(firing_now) - if t == 'snapshot': - self._got_initial_snapshot = True - self._snapshot_retry_timer.stop() - return - - - # Fallback for unknown message types - if isinstance(items, list): - print(f"[WS] Unknown type '{t}' → applying default rule ({len(firing_now)} firing)") - self._apply_firing_list(firing_now) - - - # List click → play def _on_pick_alert_from_list(self, idx: QtCore.QModelIndex): if not idx.isValid(): @@ -1722,14 +1843,28 @@ def _on_pick_alert_from_list(self, idx: QtCore.QModelIndex): self._play_alert(it) def _play_alert(self, it: dict): + # Remember the previous "current" before we switch + old_cam = self.current_camera + old_inc = self.current_incident + old_status = getattr(self, "current_status", "firing") + + # Normalize to ensure keys like 'camera', 'anomaly', 'incident_id', 'started_at' exist + it = self._normalize_alert(it) + cam = it.get('camera') inc = it.get('incident_id') or self.cfg.INCIDENT hls_url = it.get('hls') or None + # If we are leaving a resolved incident that we were keeping only + # for DVR scrubbing, remove it from the list now (no video anymore). + if old_cam and old_inc and old_status == "resolved": + self.alertModel.remove_by_key(old_cam, old_inc) + self.current_camera = cam self.current_incident = inc self.current_status = (it.get('status') or 'firing').lower() - + self.current_alert = it # keep the latest metadata for this incident + self.proxy.switch_source(camera=cam, incident=inc, upstream_hls=hls_url) self.setWindowTitle("AgGuard — Live Incidents") self._update_details(it) @@ -1737,13 +1872,19 @@ def _play_alert(self, it: dict): QtCore.QTimer.singleShot(150, self._go_live) + def _update_details(self, it: dict): + subject = it.get("subject") + anom = it.get("anomaly") or "–" + if anom.lower() in ("intruding animal", "intruding_animal", "climbing_fence") and subject: + anom = f"{anom.title()} ({subject.title()})" + vals = [ it.get('camera') or '–', - it.get('anomaly') or '–', + anom, it.get('incident_id') or '–', (it.get('status') or self.current_status or '–'), - it.get('startsAt') or '–', + it.get('started_at') or '–', ] for lbl, v in zip(self.lblVals, vals): lbl.setText(v) @@ -1760,10 +1901,16 @@ def _fmt(self, ms: int) -> str: def _set_live_badge(self, live: bool): if live: self.liveBadge.setText("LIVE") - self.liveBadge.setStyleSheet("background:#10b981; color:white; padding:3px 8px; border-radius:12px; font-weight:700;") + self.liveBadge.setStyleSheet( + "background:#10b981; color:white; padding:3px 8px; " + "border-radius:12px; font-weight:700;" + ) else: self.liveBadge.setText("DVR") - self.liveBadge.setStyleSheet("background:#9ca3af; color:white; padding:3px 8px; border-radius:12px; font-weight:700;") + self.liveBadge.setStyleSheet( + "background:#9ca3af; color:white; padding:3px 8px; " + "border-radius:12px; font-weight:700;" + ) def _set_idle(self): self.mode_live = False @@ -1778,15 +1925,24 @@ def _set_idle(self): print("[MODE] IDLE") def _go_live(self): + # If the proxy is already resolved, there is no live stream any more. + # We keep DVR scrubbing only – do not try to attach /live.m3u8. + if self.proxy.resolved: + print("[MODE] proxy resolved; live disabled, staying in DVR-only mode") + self.mode_live = False + self._set_live_badge(False) + return + # resume live sync; stop DVR growth if not self._live_sync.isActive(): self._live_sync.start() self._dvr_growth.stop() - if self.current_status == "resolved": - print("[MODE] resolved; not going live") - self._set_idle() - return + # ❌ OLD: blocked when current_status == "resolved" + # if self.current_status == "resolved": + # print("[MODE] resolved; not going live") + # self._set_idle() + # return if not self.proxy.upstream_index: return @@ -1860,8 +2016,10 @@ def _seek_via_playlist(self, t_ms: int): if not self._dvr_growth.isActive(): self._dvr_growth.start() - if self.current_status == "resolved" or not self.proxy.dvr: - print("[SEEK] ignored (no DVR while resolved)") + # IMPORTANT: allow seeking even when current_status == "resolved". + # Only block if there is no DVR. + if not self.proxy.dvr: + print("[SEEK] ignored (no DVR)") return t_ms = max(0, min(int(t_ms), max(0, self.dvr_duration_ms))) @@ -1936,12 +2094,10 @@ def _update_time_label(self, t_ms: int): m, s = divmod(s, 60) txt = f"{h:d}:{m:02d}:{s:02d}" if h else f"{m:d}:{s:02d}" self.timeLeft.setText(txt) - + def closeEvent(self, event: QtGui.QCloseEvent): try: self.proxy.stop() except Exception: pass super().closeEvent(event) - - diff --git a/GUI/src/vast/views/sensorDetailsTab.py b/GUI/src/vast/views/sensorDetailsTab.py index 9d78abe0a..9fb041576 100644 --- a/GUI/src/vast/views/sensorDetailsTab.py +++ b/GUI/src/vast/views/sensorDetailsTab.py @@ -14,7 +14,6 @@ def __init__(self, api, parent=None): super().__init__(parent) self.api = api self.sensor_id = None - self.sensor_names = [] main_layout = QVBoxLayout(self) main_layout.setContentsMargins(10, 10, 10, 10) @@ -33,7 +32,7 @@ def __init__(self, api, parent=None): border-radius:4px; font-size:12px; background:white; - min-width:150px; + min-width:180px; } QComboBox:hover { border:1px solid #2563eb; } """) @@ -55,7 +54,8 @@ def __init__(self, api, parent=None): self.input_layout.addWidget(self.label) self.input_layout.addWidget(self.sensor_dropdown) - self.input_layout.addWidget(self.load_button) + self.add_button = self.load_button + self.input_layout.addWidget(self.add_button) main_layout.addLayout(self.input_layout) # --- Web view area --- @@ -67,86 +67,130 @@ def __init__(self, api, parent=None): self.timer.timeout.connect(self.refresh_data) self.timer.start(15000) - # Load available sensors list self._load_sensor_list() - self.web.setHtml("

Please select a sensor to view details

") + + self.web.setHtml( + "

Please select a sensor to view details

" + ) # -------------------------------------------------------- def _load_sensor_list(self): - """Load sensor names from the API.""" + """ + Load only sensors that have data: + - event_logs_sensors OR + - sensors_anomalies_modal OR + - sensor_anomalies + """ try: r = self.api.http.get(f"{self.api.base}/api/tables/sensors") - data = r.json().get("rows", []) - self.sensor_names = [s["sensor_name"] for s in data if "sensor_name" in s] + sensors = r.json().get("rows", []) + self.sensor_dropdown.clear() - self.sensor_dropdown.addItem("-- Select Sensor --") - for name in self.sensor_names: - self.sensor_dropdown.addItem(name) + self.sensor_dropdown.addItem("-- Select Sensor --", None) + + for s in sensors: + sid = s.get("sensor_id") + sname = s.get("sensor_name", "") + + # ---------- check if this sensor has real data ---------- + has_data = False + + # check modal anomalies + r_modal = self.api.http.get( + f"{self.api.base}/api/tables/sensors_anomalies_modal?sensor_id={sid}&limit=1" + ).json().get("rows", []) + if r_modal: + has_data = True + + # check sensor anomalies table + if not has_data: + r_anoms = self.api.http.get( + f"{self.api.base}/api/tables/sensor_anomalies?sensor={sid}&limit=1" + ).json().get("rows", []) + if r_anoms: + has_data = True + + # check logs + if not has_data: + r_logs = self.api.http.get( + f"{self.api.base}/api/tables/event_logs_sensors?device_id={sid}&limit=1" + ).json().get("rows", []) + if r_logs: + has_data = True + + # add only if data exists + if has_data: + display = f"{sid} – {sname}" + self.sensor_dropdown.addItem(display, sid) + except Exception as e: print(f"[SensorDetailsTab] Failed to load sensors list: {e}") # -------------------------------------------------------- def _on_load_clicked(self): - """Triggered when user clicks 'Show Data'.""" - selected = self.sensor_dropdown.currentText().strip() - if not selected or selected == "-- Select Sensor --": - self.web.setHtml("

Please select a sensor from the list

") + selected_id = self.sensor_dropdown.currentData() + if not selected_id: + self.web.setHtml("

Please select a sensor

") return - self.load_sensor(selected) + self.load_sensor(str(selected_id)) # -------------------------------------------------------- def load_sensor(self, sensor_id: str): - """Called when a sensor is selected manually or from the map.""" self.sensor_id = sensor_id self.refresh_data() # -------------------------------------------------------- def refresh_data(self): - """Fetch data from API and refresh the dashboard.""" if not self.sensor_id: return try: # Sensors - r_sensor = self.api.http.get(f"{self.api.base}/api/tables/sensors?sensor_name={self.sensor_id}") + r_sensor = self.api.http.get(f"{self.api.base}/api/tables/sensors?sensor_id={self.sensor_id}") sensors = r_sensor.json().get("rows", []) sensor_data = sensors[0] if sensors else {} # Logs - r_logs = self.api.http.get(f"{self.api.base}/api/tables/event_logs_sensors?device_id={self.sensor_id}&order_by=start_ts&order_dir=desc") - logs = r_logs.json().get("rows", []) + r_logs = self.api.http.get( + f"{self.api.base}/api/tables/event_logs_sensors?device_id={self.sensor_id}&order_by=start_ts&order_dir=desc" + ).json().get("rows", []) # Modal anomalies - r_modal = self.api.http.get(f"{self.api.base}/api/tables/sensors_anomalies_modal?sensor_id={self.sensor_id}&order_by=ts&order_dir=desc") - modal = r_modal.json().get("rows", []) + r_modal = self.api.http.get( + f"{self.api.base}/api/tables/sensors_anomalies_modal?sensor_id={self.sensor_id}&order_by=ts&order_dir=desc" + ).json().get("rows", []) # Sensor anomalies - r_anoms = self.api.http.get(f"{self.api.base}/api/tables/sensor_anomalies?sensor={self.sensor_id}&limit=50&order_by=ts&order_dir=desc") - anoms = r_anoms.json().get("rows", []) + r_anoms = self.api.http.get( + f"{self.api.base}/api/tables/sensor_anomalies?sensor={self.sensor_id}&limit=50&order_by=ts&order_dir=desc" + ).json().get("rows", []) # Active alert - active_alert = next((a for a in logs if a.get("end_ts") is None), None) + active_alert = next((a for a in r_logs if a.get("end_ts") is None), None) + + chart_html = self._build_plot(r_anoms) + page_html = self._build_html(sensor_data, r_logs, r_modal, active_alert, chart_html) - chart_html = self._build_plot(anoms) - page_html = self._build_html(sensor_data, logs, modal, active_alert, chart_html) self.web.setHtml(page_html) + except Exception as e: traceback.print_exc() self.web.setHtml(f"

Error: {e}

") # -------------------------------------------------------- def _build_plot(self, anoms): - """Build the Plotly chart.""" if not anoms: return "
No data available for this sensor
" timestamps = [a.get("ts") for a in anoms] values = [a.get("value") for a in anoms] + fig = go.Figure() fig.add_trace(go.Scatter( x=timestamps, y=values, mode="lines+markers", line=dict(color="#2563eb", width=2), marker=dict(size=4) )) + fig.update_layout( template="plotly_white", height=240, @@ -155,12 +199,13 @@ def _build_plot(self, anoms): yaxis_title="Value", font=dict(family="Inter,Segoe UI,sans-serif", size=10) ) + return fig.to_html(include_plotlyjs="cdn", full_html=False) # -------------------------------------------------------- def _build_html(self, sensor_data, logs, modal, active_alert, chart_html): - """Generate the full HTML layout.""" sensor_name = sensor_data.get("sensor_name", self.sensor_id) + active_html = "" if active_alert: sev = active_alert.get("severity", "warn").capitalize() @@ -180,6 +225,7 @@ def _build_html(self, sensor_data, logs, modal, active_alert, chart_html): "severity": l.get("severity"), "source": "event_logs_sensors" }) + for m in modal: is_anomaly = m.get("anomaly") not in (0, "0", False, "false", None) combined.append({ @@ -188,6 +234,7 @@ def _build_html(self, sensor_data, logs, modal, active_alert, chart_html): "severity": "critical" if is_anomaly else "info", "source": "sensors_anomalies_modal" }) + combined.sort(key=lambda x: x.get("time") or "", reverse=True) rows = "".join([ @@ -226,3 +273,5 @@ def _build_html(self, sensor_data, logs, modal, active_alert, chart_html): {rows} """ + + diff --git a/GUI/src/vast/views/sensorsMapView.py b/GUI/src/vast/views/sensorsMapView.py index 9c5c515e3..78a61c790 100644 --- a/GUI/src/vast/views/sensorsMapView.py +++ b/GUI/src/vast/views/sensorsMapView.py @@ -1,142 +1,259 @@ -import os, json -from PyQt6.QtWidgets import QWidget, QVBoxLayout, QLabel, QTableWidget, QPushButton, QTableWidgetItem, QSizePolicy, QFrame -from PyQt6.QtWebEngineWidgets import QWebEngineView -from PyQt6.QtCore import QUrl, QTimer, Qt, pyqtSlot, QObject -from PyQt6.QtWebChannel import QWebChannel -from pathlib import Path -from dashboard_api import DashboardApi -# Disable GPU (useful in Docker) +import os os.environ["QTWEBENGINE_DISABLE_GPU"] = "1" os.environ["QTWEBENGINE_CHROMIUM_FLAGS"] = "--disable-gpu --disable-software-rasterizer --disable-webgl" +import json +from PyQt6.QtWidgets import ( + QWidget, QVBoxLayout, QLabel, QTableWidget, + QPushButton, QTableWidgetItem, QSizePolicy, QFrame +) +from PyQt6.QtWebEngineWidgets import QWebEngineView +from PyQt6.QtCore import QUrl, QTimer, Qt +from dashboard_api import DashboardApi +from pathlib import Path -class JsBridge(QObject): - def __init__(self, parent): - super().__init__() - self.parent = parent - - @pyqtSlot(str) - def openSensorDetail(self, sensor_id): - """Called from JS when clicking 'view details'.""" - print(f"[JsBridge] openSensorDetail({sensor_id})") - # נסרוק עד לחלון העליון (MainWindow) בצורה בטוחה - try: - main_window = self.parent.window() - except Exception: - main_window = None - - if main_window and hasattr(main_window, "show_sensor_details"): - main_window.show_sensor_details(sensor_id) class SensorsMapView(QWidget): + """Stable, auto-refreshing sensors dashboard.""" def __init__(self, api: DashboardApi, parent=None): super().__init__(parent) self.api = api + self._last_sensor_data = [] self._map_ready = False - self._visible = False self._closing = False + self._visible = False + self._initialized = False layout = QVBoxLayout(self) - layout.setContentsMargins(10, 10, 10, 10) + layout.setContentsMargins(12, 12, 12, 12) layout.setSpacing(10) - title = QLabel("🗺️ Sensor Map") - title.setStyleSheet("font-size:20px;font-weight:700;color:#0f172a;") - layout.addWidget(title) + title = QLabel("🌾 Sensor Dashboard") + title.setStyleSheet(""" + font-size:22px; + font-weight:800; + color:#0f172a; + margin-bottom:4px; + """) + layout.addWidget(title, alignment=Qt.AlignmentFlag.AlignLeft) - # Map frame map_frame = QFrame() map_layout = QVBoxLayout(map_frame) map_layout.setContentsMargins(0, 0, 0, 0) - self.web = QWebEngineView() - map_layout.addWidget(self.web) - layout.addWidget(map_frame, stretch=2) + map_layout.setSpacing(0) + map_frame.setStyleSheet("background:#f1f5f9;border-radius:12px;border:1px solid #cbd5e1;") - # Load map HTML + self.web = QWebEngineView() + self.web.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) html_path = Path(__file__).resolve().parent / "assets" / "sensors_map.html" self.web.setUrl(QUrl.fromLocalFile(str(html_path))) + map_layout.addWidget(self.web) + layout.addWidget(map_frame, stretch=2) - # Stats table self.table = QTableWidget() self.table.setAlternatingRowColors(True) + self.table.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + self.table.setStyleSheet(""" + QHeaderView::section { + background:#e2e8f0; + color:#0f172a; + font-weight:700; + border:none; + padding:6px 8px; + } + QTableWidget { + background:#ffffff; + border:1px solid #cbd5e1; + border-radius:10px; + gridline-color:#cbd5e1; + font-size:13px; + } + QTableWidget::item { padding:4px 6px; } + """) layout.addWidget(self.table, stretch=1) btn = QPushButton("⟳ Load Zone Stats") - btn.setStyleSheet("background:#2563eb;color:white;font-weight:700;padding:8px 14px;border-radius:8px;") + btn.setStyleSheet(""" + QPushButton { + background:#2563eb; + color:white; + font-weight:700; + padding:8px 14px; + border-radius:8px; + } + QPushButton:hover { background:#1d4ed8; } + QPushButton:pressed { background:#1e40af; } + """) btn.clicked.connect(self.load_zone_stats) layout.addWidget(btn, alignment=Qt.AlignmentFlag.AlignRight) - # JS bridge - self.channel = QWebChannel() - self.bridge = JsBridge(self) - self.channel.registerObject("pyObj", self.bridge) - self.web.page().setWebChannel(self.channel) self.web.loadFinished.connect(self._on_map_ready) self.timer = QTimer(self) self.timer.timeout.connect(self.refresh_all) + self._initialized = True + + # --------------------------- Events --------------------------- # + def resizeEvent(self, event): + super().resizeEvent(event) + if self._map_ready: + self.web.page().runJavaScript("if (window.map) map.invalidateSize();") + QTimer.singleShot(800, lambda: self.web.page().runJavaScript(""" + if (window.map) { + map.invalidateSize(); + if (window.image) image.setBounds(map.getBounds()); + } + """)) + + def showEvent(self, event): + super().showEvent(event) + self._visible = True + if not self._closing and not self.timer.isActive(): + self.timer.start(15_000) + QTimer.singleShot(800, self.refresh_all) + + def hideEvent(self, event): + self._visible = False + if self.timer.isActive(): + self.timer.stop() + super().hideEvent(event) + + def closeEvent(self, event): + self._closing = True + self._visible = False + if self.timer.isActive(): + self.timer.stop() + super().closeEvent(event) + + # --------------------------- Map --------------------------- # def _on_map_ready(self): self._map_ready = True - print("[SensorsMapView] Map ready") - QTimer.singleShot(1000, self._inject_data) + QTimer.singleShot(800, self._inject_data) def _inject_data(self): - if not self._map_ready: - return - try: - r = self.api.http.get(f"{self.api.base}/api/tables/sensor_anomalies") - data = r.json() - js_data = json.dumps(data.get("rows", data)) - js = f"window.SENSOR_DATA={js_data};if(typeof renderSensors==='function')renderSensors(window.SENSOR_DATA);" - self.web.page().runJavaScript(js) - except Exception as e: - print("[SensorsMapView] Error:", e) + if not self._map_ready or self._closing: + return + try: + token = getattr(self.api, "token", None) + if not token: + return + + # --- Fetch zones from DB and render on map --- + rz = self.api.http.get(f"{self.api.base}/api/tables/zones") + rz.raise_for_status() + zones = rz.json().get("rows", []) + print(zones) + self.web.page().runJavaScript(f"if (typeof renderZones==='function') renderZones({json.dumps(zones)});") + self._update_zones(zones) + # --- Fetch zones from DB and render on map --- + rz = self.api.http.get(f"{self.api.base}/api/tables/zones") + rz.raise_for_status() + zones = rz.json().get("rows", []) + print(zones) + self.web.page().runJavaScript( + f"if (typeof renderZones==='function') renderZones({json.dumps(zones)});" + ) + self._update_zones(zones) + + r = self.api.http.get(f"{self.api.base}/api/tables/sensor_anomalies") + r.raise_for_status() + data = r.json() + self._update_map(data) + except Exception as e: + print("[SensorsView] Failed to inject data:", e) + + def _update_zones(self, zones_data): + if not self._map_ready or self._closing or not zones_data: + return + try: + js_data = json.dumps(zones_data) + js = f""" + if (typeof renderZones === 'function') {{ + renderZones({js_data}); + }} + """ + self.web.page().runJavaScript(js) + except Exception as e: + print("[SensorsView] Failed to update zones:", e) + + def _update_map(self, sensor_data): + if not self._map_ready or self._closing or not self._visible: + return + rows = sensor_data.get("rows", sensor_data) + js_data = json.dumps(rows) + js = f""" + window.SENSOR_DATA = {js_data}; + if (typeof renderSensors === 'function') {{ + renderSensors(window.SENSOR_DATA); + }} + if (window.map) map.invalidateSize(); + """ + self.web.page().runJavaScript(js) + # --------------------------- Table --------------------------- # def load_zone_stats(self): - try: - r = self.api.http.get(f"{self.api.base}/api/tables/sensor_zone_stats?limit=10&order_by=inserted_at&order_dir=desc") - rows = r.json().get("rows", []) - except Exception as e: - print("[SensorsMapView] API error:", e) - return - - self.table.clear() - if not rows: - self.table.setRowCount(0) - self.table.setColumnCount(1) - self.table.setHorizontalHeaderLabels(["No data"]) - return - - - exclude_keys = {"max", "min", "std", "median","mean"} - - keys = [k for k in rows[0].keys() if k not in exclude_keys] - - self.table.setColumnCount(len(keys)) - self.table.setHorizontalHeaderLabels(keys) - self.table.setRowCount(len(rows)) - - for i, row in enumerate(rows): - for j, key in enumerate(keys): - item = QTableWidgetItem(str(row.get(key, ""))) - item.setTextAlignment(Qt.AlignmentFlag.AlignCenter) - self.table.setItem(i, j, item) - - self.table.resizeColumnsToContents() - self.table.horizontalHeader().setStretchLastSection(True) + if self._closing or not self._initialized or not self._visible: + return + try: + r = self.api.http.get(f"{self.api.base}/api/tables/sensor_zone_stats?limit=10&order_by=inserted_at&order_dir=desc") + r.raise_for_status() + data = r.json() + rows = data.get("rows", data if isinstance(data, list) else []) + except Exception as e: + print("[SensorsView] API error:", e) + self._show_no_data("API Error") + return - def refresh_all(self): - if self._closing or not self._visible: + if not rows: + self._show_no_data("No data") return - self.load_zone_stats() - self._inject_data() - def showEvent(self, event): - super().showEvent(event) - self._visible = True - QTimer.singleShot(1000, self._inject_data) + self.table.clear() + keys = list(rows[0].keys()) + self.table.setColumnCount(len(keys)) + self.table.setHorizontalHeaderLabels(keys) + self.table.setRowCount(len(rows)) - def hideEvent(self, event): - self._visible = False - super().hideEvent(event) + for r_idx, row in enumerate(rows): + for c_idx, key in enumerate(keys): + val = row.get(key, "") + item = QTableWidgetItem(str(val)) + item.setTextAlignment(Qt.AlignmentFlag.AlignCenter) + if not self._closing: + self.table.setItem(r_idx, c_idx, item) + + self.table.resizeColumnsToContents() + self.table.horizontalHeader().setStretchLastSection(True) + + def _show_no_data(self, msg): + if self._closing: + return + self.table.clear() + self.table.setRowCount(0) + self.table.setColumnCount(1) + self.table.setHorizontalHeaderLabels([msg]) + + # --------------------------- Refresh --------------------------- # + def refresh_all(self): + if self._closing or not self._visible: + return + print("[SensorsView] Refreshing data…") + try: + self.load_zone_stats() + except Exception as e: + print("[SensorsView] refresh error:", e) + return + try: + r = self.api.http.get(f"{self.api.base}/api/tables/sensor_anomalies?limit=10&order_by=inserted_at&order_dir=desc") + r.raise_for_status() + data = r.json() + new_rows = data.get("rows", data) + if json.dumps(new_rows, sort_keys=True) != json.dumps(self._last_sensor_data, sort_keys=True): + self._last_sensor_data = new_rows + self._update_map(data) + else: + print("[SensorsView] No sensor changes detected — skipping update.") + except Exception as e: + print("[SensorsView] Failed to refresh sensors:", e) + diff --git a/GUI/src/vast/views/sensors_status_summary.py b/GUI/src/vast/views/sensors_status_summary.py index 79d20a46f..4d3728c41 100644 --- a/GUI/src/vast/views/sensors_status_summary.py +++ b/GUI/src/vast/views/sensors_status_summary.py @@ -1,521 +1,489 @@ +from math import ceil +from datetime import datetime, timezone from PyQt6.QtWidgets import ( QWidget, QVBoxLayout, QHBoxLayout, QLabel, QFrame, QTableWidget, - QTableWidgetItem, QHeaderView, QPushButton + QTableWidgetItem, QHeaderView, QScrollArea ) from PyQt6.QtCore import Qt, QTimer -from PyQt6.QtGui import QColor -from datetime import datetime, timedelta +from PyQt6.QtGui import QFont, QColor, QPainter, QPen, QPainterPath +# ============================================================ +# 🎨 CIRCLE ICON (Stroke icons drawn manually) +# ============================================================ +class CircleIcon(QWidget): + def __init__(self, icon_type: str, color: str, size: int = 58): + super().__init__() + self.icon_type = icon_type + self.color = color + self.size = size + self.setFixedSize(size, size) + def paintEvent(self, event): + painter = QPainter(self) + painter.setRenderHint(QPainter.RenderHint.Antialiasing) + + # Background circle + bg = QColor(self._lighten(self.color, 0.70)) + painter.setBrush(bg) + painter.setPen(Qt.PenStyle.NoPen) + painter.drawEllipse(0, 0, self.size, self.size) + + # Icon stroke + painter.setPen(QPen(QColor(self._dark(self.color)), 3, + Qt.PenStyle.SolidLine, + Qt.PenCapStyle.RoundCap, + Qt.PenJoinStyle.RoundJoin)) + + # Build path + path = self._icon_path() + scale = self.size / 58 + painter.scale(scale, scale) + painter.drawPath(path) + + # ---------------- Icon shapes ---------------- + def _icon_path(self): + p = QPainterPath() + + if self.icon_type == "people": + p.addEllipse(14, 14, 12, 12) + p.addEllipse(32, 14, 12, 12) + p.moveTo(10, 40) + p.cubicTo(18, 30, 28, 30, 36, 40) + p.moveTo(22, 40) + p.cubicTo(30, 30, 40, 30, 48, 40) + + elif self.icon_type == "bell": + p.moveTo(29, 12) + p.arcTo(19, 12, 20, 20, 0, 180) + p.lineTo(19, 38) + p.lineTo(39, 38) + p.lineTo(39, 32) + p.addEllipse(26, 44, 6, 6) + + elif self.icon_type == "graph": + p.moveTo(12, 40) + p.lineTo(24, 28) + p.lineTo(32, 34) + p.lineTo(46, 20) + + elif self.icon_type == "bolt": + p.moveTo(28, 12) + p.lineTo(20, 30) + p.lineTo(30, 30) + p.lineTo(22, 48) + p.lineTo(40, 26) + p.lineTo(30, 26) + p.closeSubpath() + + return p + + # ---------------- Color helpers ---------------- + def _lighten(self, hex_color, factor): + hex_color = hex_color.lstrip('#') + r = int(hex_color[0:2], 16) + g = int(hex_color[2:4], 16) + b = int(hex_color[4:6], 16) + r = int(r + (255 - r) * factor) + g = int(g + (255 - g) * factor) + b = int(b + (255 - b) * factor) + return f"#{r:02X}{g:02X}{b:02X}" + + def _dark(self, hex_color): + hex_color = hex_color.lstrip('#') + r = int(hex_color[0:2], 16) + g = int(hex_color[2:4], 16) + b = int(hex_color[4:6], 16) + r = int(r * 0.35) + g = int(g * 0.35) + b = int(b * 0.35) + return f"#{r:02X}{g:02X}{b:02X}" + + +# ============================================================ +# 🔵 RING INDICATOR +# ============================================================ +class RingIndicator(QWidget): + def __init__(self, label, value, color="#10B981", max_value=100, size=200): + super().__init__() + self.label = label + self.value = value + self.color = color + self.max_value = max_value + self.size = size + self.setFixedSize(size, size) + + def paintEvent(self, event): + painter = QPainter(self) + painter.setRenderHint(QPainter.RenderHint.Antialiasing) + rect = self.rect() + + radius = int(min(rect.width(), rect.height()) / 2 - 15) + center = rect.center() + + # Background circle + painter.setPen(QPen(QColor("#E5E7EB"), 16)) + painter.drawEllipse(center, radius, radius) + + # Colored ring + pen = QPen(QColor(self.color), 16) + pen.setCapStyle(Qt.PenCapStyle.RoundCap) + painter.setPen(pen) + angle_span = int(360 * (self.value / self.max_value)) + painter.drawArc(rect.adjusted(15, 15, -15, -15), 90 * 16, -angle_span * 16) + + # Text + painter.setPen(QColor("#1E293B")) + painter.setFont(QFont("Segoe UI", 30, QFont.Weight.Bold)) + painter.drawText(rect, Qt.AlignmentFlag.AlignCenter, f"{ceil(self.value)}%") +# ============================================================ +# 🌿 MAIN DASHBOARD – BUILD UI +# ============================================================ class SensorsStatusSummary(QWidget): def __init__(self, api, parent=None): super().__init__(parent) self.api = api - - # Cache for performance optimization - self._last_sensors_fetch = None - self._sensors_cache = [] - self._last_events_check = None self._events_cache = [] - self._last_event_id = 0 # Track last processed event ID - - # Cache duration (5 minutes for sensors, 1 minute for events) - self._sensors_cache_duration = timedelta(minutes=5) - self._events_cache_duration = timedelta(minutes=1) - + self._last_event_id = 0 + self._first_load = True + self._build_ui() - self.load_data() - - # Auto-refresh timer for events only (every 30 seconds) - self._refresh_timer = QTimer() - self._refresh_timer.timeout.connect(self._refresh_events_only) - self._refresh_timer.start(30000) # 30 seconds + self.refresh_data() + + # Auto refresh every 30 sec + self.timer = QTimer(self) + self.timer.timeout.connect(self.refresh_data) + self.timer.start(30000) + # ============================================================ + # 🧱 BUILD UI + # ============================================================ def _build_ui(self): main_layout = QVBoxLayout(self) - main_layout.setContentsMargins(30, 30, 30, 30) - main_layout.setSpacing(25) - - # -------- MODERN HEADER -------- - header_layout = QVBoxLayout() - - title = QLabel("🌾 Sensors Status Dashboard") - title.setStyleSheet(""" - QLabel { - font-family: 'Segoe UI', 'Roboto', 'Inter', sans-serif; - font-size: 32px; - font-weight: 800; - color: #1a1a1a; - margin-bottom: 8px; - letter-spacing: -0.5px; - } - """) - - subtitle = QLabel("Real-time monitoring of agricultural sensors") - subtitle.setStyleSheet(""" + main_layout.setContentsMargins(40, 40, 40, 40) + main_layout.setSpacing(30) + + # ------------------------------------------------------------ + # Header + # ------------------------------------------------------------ + header_row = QHBoxLayout() + header_row.setSpacing(16) + + icon_lbl = QLabel("🩺") + icon_lbl.setFont(QFont("Segoe UI Emoji", 28)) + header_row.addWidget(icon_lbl) + + title = QLabel("Sensors Health Overview") + title.setFont(QFont("Segoe UI", 24, QFont.Weight.Bold)) + title.setStyleSheet("color:#0F172A; letter-spacing: -0.5px;") + header_row.addWidget(title) + + header_row.addStretch() + + self.status_badge = QLabel("Live • Updated just now") + self.status_badge.setFont(QFont("Segoe UI", 11, QFont.Weight.Medium)) + self.status_badge.setStyleSheet(""" QLabel { - font-family: 'Segoe UI', 'Roboto', 'Inter', sans-serif; - font-size: 16px; - font-weight: 400; - color: #6B7280; - margin-bottom: 15px; + color: #047857; + background-color: #D1FAE5; + border: 1px solid #A7F3D0; + border-radius: 12px; + padding: 8px 16px; } """) - - header_layout.addWidget(title, alignment=Qt.AlignmentFlag.AlignLeft) - header_layout.addWidget(subtitle, alignment=Qt.AlignmentFlag.AlignLeft) - main_layout.addLayout(header_layout) + header_row.addWidget(self.status_badge) + main_layout.addLayout(header_row) - # -------- MODERN STATUS CARDS -------- + # ------------------------------------------------------------ + # Status cards row + # ------------------------------------------------------------ cards_row = QHBoxLayout() cards_row.setSpacing(20) - self.active_card = self._create_status_card("Active Sensors", "●", "#10B981", "#F0FDF4") - self.inactive_card = self._create_status_card("Inactive Sensors", "●", "#EF4444", "#FEF2F2") + + self.active_card = self._create_status_card("Active Sensors", "0", "#22C55E", "people") + self.inactive_card = self._create_status_card("Inactive (No KeepAlive)", "0", "#F97316", "bell") + self.outofrange_card = self._create_status_card("Out of Range", "0", "#EF4444", "graph") + self.corrupted_card = self._create_status_card("Corrupted", "0", "#8B5CF6", "bolt") + cards_row.addWidget(self.active_card) cards_row.addWidget(self.inactive_card) + cards_row.addWidget(self.outofrange_card) + cards_row.addWidget(self.corrupted_card) + main_layout.addLayout(cards_row) - # -------- MODERN TABLE -------- - self.table = QTableWidget(0, 5) - self.table.setHorizontalHeaderLabels(["ID", "Sensor Type", "Plant", "Plant ID", "Status"]) - self.table.horizontalHeader().setSectionResizeMode(QHeaderView.ResizeMode.Stretch) + # ------------------------------------------------------------ + # LOWER SECTION + # ------------------------------------------------------------ + lower_row = QHBoxLayout() + lower_row.setSpacing(24) + + # === LEFT: ring === + left_frame = QFrame() + left_frame.setStyleSheet("background:white; border-radius:16px;") + left_l = QVBoxLayout(left_frame) + left_l.setContentsMargins(30, 30, 30, 30) + left_l.setSpacing(10) + + ring_title = QLabel("System Health") + ring_title.setFont(QFont("Segoe UI", 16)) + ring_title.setStyleSheet("color:#1E293B;") + left_l.addWidget(ring_title) + + self.health_ring = RingIndicator("Health", 0, "#10B981", 100, 220) + left_l.addWidget(self.health_ring, alignment=Qt.AlignmentFlag.AlignCenter) + + self.ring_bottom = QLabel("Loading...") + self.ring_bottom.setFont(QFont("Segoe UI", 11)) + self.ring_bottom.setStyleSheet("color: #94A3B8; margin-top: 6px;") + self.ring_bottom.setAlignment(Qt.AlignmentFlag.AlignCenter) + left_l.addWidget(self.ring_bottom) + + lower_row.addWidget(left_frame, 1) + + # === RIGHT: Inactive table === + right_frame = QFrame() + right_frame.setStyleSheet("background:white; border-radius:16px;") + right_l = QVBoxLayout(right_frame) + right_l.setContentsMargins(30, 30, 30, 30) + right_l.setSpacing(10) + + table_title = QLabel("Inactive Sensors (Missing KeepAlive)") + table_title.setFont(QFont("Segoe UI", 16)) + table_title.setStyleSheet("color:#1E293B; margin-bottom:10px;") + right_l.addWidget(table_title) + + self.table = QTableWidget(0, 3) + self.table.setHorizontalHeaderLabels(["ID", "Sensor Type", "Last Seen"]) + + header = self.table.horizontalHeader() + header.setSectionResizeMode(0, QHeaderView.ResizeMode.Fixed) + header.setSectionResizeMode(1, QHeaderView.ResizeMode.Stretch) + header.setSectionResizeMode(2, QHeaderView.ResizeMode.Stretch) + self.table.setColumnWidth(0, 60) + self.table.verticalHeader().setVisible(False) - self.table.setAlternatingRowColors(True) self.table.setStyleSheet(""" QTableWidget { - background-color: #ffffff; - alternate-background-color: #F9FAFB; - font-family: 'Segoe UI', 'Roboto', 'Inter', sans-serif; - font-size: 14px; - border: 2px solid #E5E7EB; + background-color: white; + font-family: 'Segoe UI'; + font-size: 13px; + border: none; border-radius: 12px; - gridline-color: #F3F4F6; - selection-background-color: #EEF2FF; + gridline-color: #E5E7EB; } QHeaderView::section { - background: qlineargradient(x1: 0, y1: 0, x2: 0, y2: 1, - stop: 0 #F8FAFC, stop: 1 #F1F5F9); - font-family: 'Segoe UI', 'Roboto', 'Inter', sans-serif; - font-weight: 700; - font-size: 15px; - color: #1F2937; - border: none; - border-bottom: 2px solid #E5E7EB; - padding: 12px 8px; - text-align: left; - } - QTableWidget::item { - padding: 12px 8px; - border-bottom: 1px solid #F3F4F6; - } - QTableWidget::item:selected { - background-color: #EEF2FF; - color: #1E40AF; - } - QTableWidget::item:hover { background-color: #F8FAFC; - } - """) - main_layout.addWidget(self.table) - - # -------- MODERN REFRESH BUTTON -------- - button_layout = QHBoxLayout() - - refresh_btn = QPushButton("↻ Refresh Data") - refresh_btn.setFixedWidth(150) - refresh_btn.setFixedHeight(45) - refresh_btn.clicked.connect(self.refresh_all) - refresh_btn.setStyleSheet(""" - QPushButton { - background: qlineargradient(x1: 0, y1: 0, x2: 0, y2: 1, - stop: 0 #3B82F6, stop: 1 #1D4ED8); - color: white; - border-radius: 12px; - font-family: 'Segoe UI', 'Roboto', 'Inter', sans-serif; - font-size: 15px; + color: #64748B; font-weight: 600; - padding: 0px 16px; + padding: 10px; border: none; - letter-spacing: 0.3px; - } - QPushButton:hover { - background: qlineargradient(x1: 0, y1: 0, x2: 0, y2: 1, - stop: 0 #2563EB, stop: 1 #1E40AF); } - QPushButton:pressed { - background: qlineargradient(x1: 0, y1: 0, x2: 0, y2: 1, - stop: 0 #1D4ED8, stop: 1 #1E3A8A); + QTableWidget::item { + padding: 10px; } """) - - button_layout.addStretch() - button_layout.addWidget(refresh_btn) - main_layout.addLayout(button_layout) + + right_l.addWidget(self.table) + lower_row.addWidget(right_frame, 2) + + main_layout.addLayout(lower_row) + + self.setStyleSheet("background-color:#F8FAFC;") self.setLayout(main_layout) - self.setStyleSheet(""" - QWidget { - background: qlineargradient(x1: 0, y1: 0, x2: 0, y2: 1, - stop: 0 #F8FAFC, stop: 1 #F1F5F9); - font-family: 'Segoe UI', 'Roboto', 'Inter', sans-serif; - } - """) - # -------- MODERN CARD CREATOR -------- - def _create_status_card(self, title_text, icon, accent_color, bg_color): + # ============================================================ + # CARD WIDGET + # ============================================================ + def _create_status_card(self, title, value, color, icon_type): frame = QFrame() - frame.setFixedHeight(120) - frame.setStyleSheet(f""" - QFrame {{ - background: qlineargradient(x1: 0, y1: 0, x2: 0, y2: 1, - stop: 0 {bg_color}, stop: 1 #ffffff); - border-radius: 16px; - border: none; - padding: 0px; - }} - """) + frame.setStyleSheet("background:white; border-radius:16px; padding:4px;") + layout = QVBoxLayout(frame) + layout.setContentsMargins(20, 20, 20, 16) + layout.setSpacing(8) + layout.setAlignment(Qt.AlignmentFlag.AlignCenter) - layout = QHBoxLayout(frame) - layout.setContentsMargins(24, 20, 24, 20) - layout.setSpacing(18) - - # Icon section - icon_label = QLabel(icon) - icon_label.setAlignment(Qt.AlignmentFlag.AlignCenter) - icon_label.setFixedSize(50, 50) - icon_label.setStyleSheet(f""" - QLabel {{ - color: {accent_color}; - font-size: 36px; - font-weight: 900; - background: transparent; - border-radius: 25px; - font-family: 'Segoe UI Symbol', 'Arial'; - }} - """) - layout.addWidget(icon_label) - - # Text section - text_layout = QVBoxLayout() - text_layout.setSpacing(5) - - title = QLabel(title_text) - title.setStyleSheet(f""" - QLabel {{ - font-family: 'Segoe UI', 'Roboto', 'Inter', sans-serif; - font-size: 16px; - font-weight: 600; - color: #374151; - letter-spacing: 0.2px; - }} - """) - - count = QLabel("0") - count.setObjectName(title_text.lower().replace(" ", "_")) - count.setStyleSheet(f""" - QLabel {{ - font-family: 'Segoe UI', 'Roboto', 'Inter', sans-serif; - font-size: 32px; - font-weight: 800; - color: {accent_color}; - letter-spacing: -1px; - }} - """) - - text_layout.addWidget(title) - text_layout.addWidget(count) - layout.addLayout(text_layout) + # Icon drawn via QPainterPath + icon = CircleIcon(icon_type, color) + layout.addWidget(icon, alignment=Qt.AlignmentFlag.AlignCenter) - return frame + # Number + val_label = QLabel(value) + val_label.setFont(QFont("Segoe UI", 28, QFont.Weight.Bold)) + val_label.setStyleSheet("color:#1E293B;") + val_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + frame.value_label = val_label + layout.addWidget(val_label) - # -------- LOAD DATA (OPTIMIZED) -------- - def load_data(self, force_sensors_refresh=False): - """Load sensors and events data with caching optimization.""" - try: - # Load sensors (with caching) - sensors = self._get_sensors_cached(force_sensors_refresh) - - # Load recent keepalive events only (last 2 hours for performance) - events = self._get_recent_keepalive_events() - - except Exception as e: - print("[SensorsStatusSummary] Error loading data:", e) - return - - # identify inactive sensors by looking at the LATEST record for each device - inactive_ids = set() - - # Group events by device_id and issue_type - device_latest = {} - - for e in events: - if (e.get("issue_type") in ["missing_keepalive", "prolonged_silence"] - and str(e.get("device_id", "")).isdigit()): - device_id = str(e["device_id"]) - issue_type = e.get("issue_type") - key = f"{device_id}_{issue_type}" - - # Keep only the latest record for each device+issue_type combination - if key not in device_latest: - device_latest[key] = e - else: - # Compare by ID (higher ID = more recent) since start_ts can be identical - current_id = device_latest[key].get("id", 0) - new_id = e.get("id", 0) - if new_id > current_id: - device_latest[key] = e - - # Now check which devices have open issues based on latest records - for key, latest_event in device_latest.items(): - if latest_event.get("end_ts") is None: # Latest record is still open - device_id = str(latest_event["device_id"]) - inactive_ids.add(device_id) - - print(f"[SensorsStatusSummary] Found {len(inactive_ids)} sensors with active keepalive issues (based on latest records)") - - active = [s for s in sensors if s["id"] not in inactive_ids] - inactive = [s for s in sensors if s["id"] in inactive_ids] - - print(f"[SensorsStatusSummary] Status: {len(active)} active, {len(inactive)} inactive sensors") - print(f"[SensorsStatusSummary] DEBUG: inactive_ids = {sorted(inactive_ids)}") - print(f"[SensorsStatusSummary] DEBUG: sensor IDs = {[s['id'] for s in sensors]}") - print(f"[SensorsStatusSummary] DEBUG: active sensor IDs = {[s['id'] for s in active]}") - print(f"[SensorsStatusSummary] DEBUG: inactive sensor IDs = {[s['id'] for s in inactive]}") - - # Debug: show which sensors are inactive - if inactive_ids: - print(f"[SensorsStatusSummary] Inactive sensor IDs: {sorted(inactive_ids)}") - - self._update_cards(active, inactive) - self._update_table(active, inactive) - - def _get_sensors_cached(self, force_refresh=False): - """Get sensors list with caching (sensors don't change often).""" - now = datetime.now() - - if (not force_refresh and - self._last_sensors_fetch and - self._sensors_cache and - (now - self._last_sensors_fetch) < self._sensors_cache_duration): - return self._sensors_cache - - # Fetch fresh sensors data - res_sensors = self.api.http.get(f"{self.api.base}/api/tables/devices_sensor") - self._sensors_cache = res_sensors.json().get("rows", []) - self._last_sensors_fetch = now - print(f"[SensorsStatusSummary] Refreshed sensors cache: {len(self._sensors_cache)} sensors") - return self._sensors_cache - - def _get_recent_keepalive_events(self): - """Get events with smart caching - only fetch new events since last check.""" - now = datetime.now() - - # Check if cache is still valid - if (self._last_events_check and - self._events_cache and - (now - self._last_events_check) < self._events_cache_duration): - return self._events_cache - + # Title + title_lbl = QLabel(title) + title_lbl.setFont(QFont("Segoe UI", 11)) + title_lbl.setStyleSheet("color:#64748B;") + title_lbl.setAlignment(Qt.AlignmentFlag.AlignCenter) + title_lbl.setWordWrap(True) + layout.addWidget(title_lbl) + + return frame + # ============================================================ + # 🔄 REFRESH DATA (MAIN LOGIC) + # ============================================================ + def refresh_data(self): try: - # Strategy: Get only NEW events since last check (incremental loading) - if self._last_event_id > 0: - # Get only events with ID > last processed ID - url = f"{self.api.base}/api/tables/event_logs_sensors?limit=200&order_by=id&order_dir=desc" - res_events = self.api.http.get(url) - new_events = res_events.json().get("rows", []) - - # Filter only truly new events - really_new = [e for e in new_events if e.get("id", 0) > self._last_event_id] - - if really_new: - print(f"[SensorsStatusSummary] Found {len(really_new)} new events") - # Update cache with new events - self._update_events_cache(really_new) - else: - print("[SensorsStatusSummary] No new events since last check") + print("\n[SensorsStatusSummary] ===== REFRESH DATA START =====") + + # === Load sensors === + res_sensors = self.api.http.get(f"{self.api.base}/api/tables/devices_sensor") + sensors = res_sensors.json().get("rows", []) + print(f"[SensorsStatusSummary] Loaded {len(sensors)} sensors") + + # === Load new events incrementally === + if self._first_load: + print("[SensorsStatusSummary] Initial load - fetching events...") + res_events = self.api.http.get( + f"{self.api.base}/api/tables/event_logs_sensors?limit=500&order_by=id&order_dir=desc" + ) + self._events_cache = res_events.json().get("rows", []) + if self._events_cache: + self._last_event_id = max(e.get("id", 0) for e in self._events_cache) + self._first_load = False + else: - # First load - get recent events - print("[SensorsStatusSummary] First load - fetching initial events") - url = f"{self.api.base}/api/tables/event_logs_sensors?limit=500&order_by=id&order_dir=desc" - res_events = self.api.http.get(url) - all_events = res_events.json().get("rows", []) - self._initialize_events_cache(all_events) - - self._last_events_check = now - return self._events_cache - + print(f"[SensorsStatusSummary] Fetching new events after ID={self._last_event_id}") + res_events = self.api.http.get( + f"{self.api.base}/api/tables/event_logs_sensors?limit=500&order_by=id&order_dir=asc" + ) + new_events = [ + e for e in res_events.json().get("rows", []) + if e.get("id", 0) > self._last_event_id + ] + + if new_events: + print(f"[SensorsStatusSummary] Found {len(new_events)} new events") + self._events_cache.extend(new_events) + self._last_event_id = max( + self._last_event_id, + max(e.get("id", 0) for e in new_events) + ) + self._events_cache = self._events_cache[-5000:] # Cap + else: + print("[SensorsStatusSummary] No new events") + + events = self._events_cache + print(f"[SensorsStatusSummary] Total cached events: {len(events)}") + + # === Analyze events === + latest_issues = self._get_latest_open_issues(events) + + inactive = [e for e in latest_issues if e.get("issue_type") == "missing_keepalive"] + outofrange = [e for e in latest_issues if e.get("issue_type") == "out_of_range"] + corrupted = [e for e in latest_issues if e.get("issue_type") in ["corrupted", "stuck_sensor"]] + + print(f"[SensorsStatusSummary] Categorized:") + print(f" - Inactive: {len(inactive)}") + print(f" - Out of range: {len(outofrange)}") + print(f" - Corrupted: {len(corrupted)}") + + # Sensors with issues + problematic_ids = {str(e.get("device_id")) for e in latest_issues if e.get("device_id")} + total = len(sensors) + active = [s for s in sensors if str(s.get("id")) not in problematic_ids] + + health = int((len(active) / total * 100)) if total else 0 + + print(f" Total sensors: {total}") + print(f" Active sensors: {len(active)}") + print(f" Health: {health}%") + + # === Update UI === + self.active_card.value_label.setText(str(len(active))) + self.inactive_card.value_label.setText(str(len(inactive))) + self.outofrange_card.value_label.setText(str(len(outofrange))) + self.corrupted_card.value_label.setText(str(len(corrupted))) + + # Ring + self.health_ring.value = health + self.health_ring.update() + self.ring_bottom.setText(f"{len(active)} active sensors of {total}") + + # Timestamp + now = datetime.now(timezone.utc) + self.status_badge.setText(f"Live • Updated at {now.strftime('%H:%M:%S')}") + + # Table + self._update_inactive_table(inactive, sensors) + + print("[SensorsStatusSummary] ===== REFRESH DATA END =====\n") + except Exception as e: - print(f"[SensorsStatusSummary] Error loading events: {e}") - return self._events_cache or [] - - def _initialize_events_cache(self, all_events): - """Initialize cache on first load.""" - # Filter relevant events and store in cache - two_hours_ago = datetime.now() - timedelta(hours=2) - - filtered_events = [] - max_id = 0 - - for event in all_events: - event_id = event.get("id", 0) - if event_id > max_id: - max_id = event_id - - # Check issue type - if event.get("issue_type") not in ["missing_keepalive", "prolonged_silence"]: + print(f"[SensorsStatusSummary] ❌ ERROR refreshing data: {e}") + import traceback + traceback.print_exc() + + + # ============================================================ + # 🔍 ANALYZE — find latest open issue per sensor + # ============================================================ + def _get_latest_open_issues(self, events): + issue_types = ["missing_keepalive", "out_of_range", "corrupted", "stuck_sensor"] + + last_events = {} + + for e in events: + dev = e.get("device_id") + itype = e.get("issue_type") + if not dev or itype not in issue_types: continue - - # Keep both open events AND recently closed events (for cache invalidation) - is_open = event.get("end_ts") is None - is_recently_closed = False - - if not is_open: - # Check if closed recently (last 5 minutes) - end_ts_str = event.get("end_ts") - if end_ts_str: - try: - end_ts = datetime.fromisoformat(end_ts_str.replace('Z', '+00:00')) - five_min_ago = datetime.now() - timedelta(minutes=5) - is_recently_closed = end_ts.replace(tzinfo=None) >= five_min_ago - except (ValueError, AttributeError): - pass - - # Keep only open events or recently closed ones - if not (is_open or is_recently_closed): + + key = (str(dev), itype) + if key not in last_events or e.get("id", 0) > last_events[key].get("id", 0): + last_events[key] = e + + # Choose highest-severity open issue per device + priority = {"corrupted": 3, "stuck_sensor": 3, "out_of_range": 2, "missing_keepalive": 1} + result = {} + + for (dev, itype), ev in last_events.items(): + if ev.get("end_ts") is None: # Still open + if dev not in result or priority[itype] > priority[result[dev]["issue_type"]]: + result[dev] = ev + + return list(result.values()) + + + # ============================================================ + # 📋 UPDATE TABLE (inactive sensors only) + # ============================================================ + def _update_inactive_table(self, inactive_events, sensors): + self.table.setRowCount(0) + + sensor_map = {str(s.get("id")): s for s in sensors} + sorted_events = sorted(inactive_events, key=lambda e: int(e.get("device_id", 0))) + + for ev in sorted_events: + dev_id = str(ev.get("device_id")) + sensor = sensor_map.get(dev_id) + if not sensor: continue - - # Check if recent (within last 2 hours) - start_ts_str = event.get("start_ts") - if start_ts_str: - try: - start_ts = datetime.fromisoformat(start_ts_str.replace('Z', '+00:00')) - if start_ts.replace(tzinfo=None) < two_hours_ago: - continue # Too old - except (ValueError, AttributeError): - continue # Invalid timestamp - - filtered_events.append(event) - - self._events_cache = filtered_events - self._last_event_id = max_id - print(f"[SensorsStatusSummary] Initialized cache with {len(filtered_events)} relevant events") - - def _update_events_cache(self, new_events): - """Update cache with new events (incremental).""" - two_hours_ago = datetime.now() - timedelta(hours=2) - - # Process new events - new_relevant = [] - max_id = self._last_event_id - - for event in new_events: - event_id = event.get("id", 0) - if event_id > max_id: - max_id = event_id - - # Apply same filtering (include recent closures) - if event.get("issue_type") in ["missing_keepalive", "prolonged_silence"]: - is_open = event.get("end_ts") is None - is_recently_closed = False - - if not is_open: - end_ts_str = event.get("end_ts") - if end_ts_str: - try: - end_ts = datetime.fromisoformat(end_ts_str.replace('Z', '+00:00')) - five_min_ago = datetime.now() - timedelta(minutes=5) - is_recently_closed = end_ts.replace(tzinfo=None) >= five_min_ago - except (ValueError, AttributeError): - pass - - if is_open or is_recently_closed: - # Check if recent - start_ts_str = event.get("start_ts") - if start_ts_str: - try: - start_ts = datetime.fromisoformat(start_ts_str.replace('Z', '+00:00')) - if start_ts.replace(tzinfo=None) >= two_hours_ago: - new_relevant.append(event) - except (ValueError, AttributeError): - pass - - # Update cache: add new events and remove old ones - self._events_cache.extend(new_relevant) - - # Clean old events from cache (older than 2 hours) - self._events_cache = [ - e for e in self._events_cache - if self._is_event_recent(e, two_hours_ago) - ] - - self._last_event_id = max_id - print(f"[SensorsStatusSummary] Added {len(new_relevant)} new events, cache now has {len(self._events_cache)} events") - - def _is_event_recent(self, event, threshold): - """Check if event is recent enough to keep in cache.""" - start_ts_str = event.get("start_ts") - if not start_ts_str: - return True # Keep if no timestamp - - try: - start_ts = datetime.fromisoformat(start_ts_str.replace('Z', '+00:00')) - return start_ts.replace(tzinfo=None) >= threshold - except (ValueError, AttributeError): - return True # Keep if invalid timestamp - def _refresh_events_only(self): - """Auto-refresh only events data (called by timer).""" - try: - self.load_data(force_sensors_refresh=False) - except Exception as e: - print(f"[SensorsStatusSummary] Auto-refresh error: {e}") + row = self.table.rowCount() + self.table.insertRow(row) - def refresh_all(self): - """Force refresh all data (sensors + events) - clear all caches.""" - # Clear all caches - self._events_cache = [] - self._last_event_id = 0 - self._last_events_check = None - self._sensors_cache = [] - self._last_sensors_fetch = None - - print("[SensorsStatusSummary] Cleared all caches - doing full refresh") - self.load_data(force_sensors_refresh=True) - - def _update_cards(self, active, inactive): - self.active_card.findChild(QLabel, "active_sensors").setText(str(len(active))) - self.inactive_card.findChild(QLabel, "inactive_sensors").setText(str(len(inactive))) - - def _update_table(self, active, inactive): - all_data = [(s, "Active") for s in active] + [(s, "Inactive") for s in inactive] - self.table.setRowCount(len(all_data)) - - for r, (sensor, status) in enumerate(all_data): - sid = QTableWidgetItem(str(sensor.get("id", ""))) - typ = QTableWidgetItem(sensor.get("sensor_type", "")) - # devices_sensor table doesn't have owner_name, use plant_id instead - plant_id = QTableWidgetItem(f"Plant {sensor.get('plant_id', '—')}") - # devices_sensor table doesn't have location, show plant_id info instead - location = QTableWidgetItem(f"Plant ID: {sensor.get('plant_id', 'N/A')}") - # Modern status with colored badges - if status == "Active": - stat = QTableWidgetItem("● ONLINE") - stat.setForeground(Qt.GlobalColor.darkGreen) - else: - stat = QTableWidgetItem("● OFFLINE") - stat.setForeground(Qt.GlobalColor.darkRed) - - # Style inactive rows with subtle background - if status == "Inactive": - gray_bg = QColor(248, 250, 252) - gray_text = QColor(107, 114, 128) - - for item in (sid, typ, plant_id, location): - item.setBackground(gray_bg) - item.setForeground(gray_text) - - self.table.setItem(r, 0, sid) - self.table.setItem(r, 1, typ) - self.table.setItem(r, 2, plant_id) - self.table.setItem(r, 3, location) - self.table.setItem(r, 4, stat) + last_seen = sensor.get("last_seen") + try: + dt = datetime.fromisoformat(last_seen.replace("Z", "+00:00")) + time_str = dt.strftime("%H:%M:%S") + except: + time_str = "—" + + # ID + id_item = QTableWidgetItem(dev_id) + self.table.setItem(row, 0, id_item) + + # Type + self.table.setItem(row, 1, QTableWidgetItem(sensor.get("sensor_type", "Unknown"))) + + # Last seen + ts_item = QTableWidgetItem(time_str) + ts_item.setFont(QFont("Segoe UI", 12, QFont.Weight.Bold)) + ts_item.setForeground(QColor("#DC2626")) + self.table.setItem(row, 2, ts_item) diff --git a/GUI/src/vast/views/sensors_view.py b/GUI/src/vast/views/sensors_view.py index 5a15f40e6..5a6dc952c 100644 --- a/GUI/src/vast/views/sensors_view.py +++ b/GUI/src/vast/views/sensors_view.py @@ -1,14 +1,12 @@ from PyQt6.QtWidgets import ( - QWidget, QVBoxLayout, QHBoxLayout, QLabel, QPushButton, QLineEdit, - QScrollArea, QGridLayout, QFrame, QDialog, QDialogButtonBox, QFormLayout, QComboBox + QWidget, QVBoxLayout, QHBoxLayout, QLabel, QLineEdit, + QScrollArea, QGridLayout, QFrame, QDialog, QDialogButtonBox, + QFormLayout, QComboBox ) -from PyQt6.QtCore import Qt, QTimer, QDateTime +from PyQt6.QtCore import Qt, QTimer import traceback -# ============================================================ -# CONSTANTS -# ============================================================ SEVERITY_RANK = { "info": 0, "ok": 0, @@ -24,7 +22,6 @@ # SENSOR CARD # ============================================================ class SensorCard(QFrame): - """Modern compact sensor card""" def __init__(self, sensor_data: dict, on_click): super().__init__() self.data = sensor_data @@ -45,6 +42,12 @@ def _build_ui(self): title.setStyleSheet("font-weight:600; font-size:15px; color:#111;") layout.addWidget(title) + # ← NEW: show sensor_id + sensor_id = self.data.get("sensor_id", "N/A") + id_lbl = QLabel(f"ID: {sensor_id}") + id_lbl.setStyleSheet("color:#777; font-size:12px;") + layout.addWidget(id_lbl) + stype = QLabel(f"Type: {self.data.get('sensor_type', 'N/A')}") stype.setStyleSheet("color:#555; font-size:12px;") layout.addWidget(stype) @@ -71,19 +74,7 @@ def _build_ui(self): layout.addWidget(sev_label) - self.setFixedSize(230, 110) - self.setStyleSheet(""" - QFrame#card { - border-radius: 12px; - border: 1px solid #DDD; - background-color: #FFFFFF; - transition: 200ms; - } - QFrame#card:hover { - border: 1px solid #0078D7; - background-color: #F6F9FF; - } - """) + self.setFixedSize(230, 120) # ============================================================ @@ -92,25 +83,23 @@ def _build_ui(self): class AlertDialog(QDialog): def __init__(self, sensor): super().__init__() - self.setWindowTitle(f"Alert Details – {sensor.get('sensor_name')}") - self.setMinimumSize(480, 360) - self.setStyleSheet(""" - QDialog { background-color: #FAFAFA; border-radius: 10px; } - QLabel { font-size: 13px; color: #222; } - QPushButton { - background-color: #0078D7; color: white; border-radius: 6px; - padding: 6px 12px; font-weight: 600; - } - QPushButton:hover { background-color: #005FA3; } - """) + self.setWindowTitle(f"Sensor Details – {sensor.get('sensor_name')}") + self.setMinimumSize(520, 450) layout = QVBoxLayout(self) - title = QLabel(f"Sensor: {sensor.get('sensor_name')}
" - f"Type: {sensor.get('sensor_type')}
" - f"Current Issue: {sensor.get('Issue')}
" - f"Severity: {sensor.get('Severity')}
") - title.setWordWrap(True) - layout.addWidget(title) + + # ← NEW: richer sensor details + sensor_details = f""" + Name: {sensor.get('sensor_name')}
+ ID: {sensor.get('sensor_id')}
+ Type: {sensor.get('sensor_type')}
+ Status: {sensor.get('status', 'Unknown')}
+ Latitude: {sensor.get('lat', 'N/A')}
+ Longitude: {sensor.get('lon', 'N/A')}
+ """ + header = QLabel(sensor_details) + header.setWordWrap(True) + layout.addWidget(header) alerts = sensor.get("All Alerts", []) layout.addSpacing(10) @@ -138,21 +127,22 @@ def __init__(self, sensor): margin: 2px; }} """) - card_layout = QFormLayout(card) - start_time = a.get("start_ts", "")[:19] if a.get("start_ts") else "" - end_time = a.get("end_ts") - end_display = end_time[:19] if end_time else "[ACTIVE]" - card_layout.addRow("Start Time:", QLabel(start_time)) - card_layout.addRow("End Time:", QLabel(end_display)) - card_layout.addRow("Issue:", QLabel(a.get("issue_type", ""))) - card_layout.addRow("Severity:", QLabel(a.get("severity", ""))) + + form = QFormLayout(card) + start = a.get("start_ts", "")[:19] + end = a.get("end_ts", "") + form.addRow("Start:", QLabel(start)) + form.addRow("End:", QLabel(end if end else "[ACTIVE]")) + form.addRow("Issue:", QLabel(a.get("issue_type", ""))) + form.addRow("Severity:", QLabel(a.get("severity", ""))) + details = a.get("details", {}) - if details: - for key, val in details.items(): - card_layout.addRow(f"{key.title()}:", QLabel(str(val))) + for k, v in details.items(): + form.addRow(f"{k.title()}:", QLabel(str(v))) + body_layout.addWidget(card) else: - body_layout.addWidget(QLabel("No previous alerts or anomalies.")) + body_layout.addWidget(QLabel("No alerts.")) scroll = QScrollArea() scroll.setWidgetResizable(True) @@ -168,11 +158,11 @@ def __init__(self, sensor): # MAIN VIEW # ============================================================ class SensorsView(QWidget): - """Unified sensors view merging anomalies + alerts""" def __init__(self, api, parent=None): super().__init__(parent) self.api = api self.all_sensors = [] + self._build_ui() self.load_sensors() @@ -182,11 +172,8 @@ def __init__(self, api, parent=None): def _build_ui(self): main_layout = QVBoxLayout(self) - main_layout.setContentsMargins(20, 20, 20, 20) - main_layout.setSpacing(10) - - # ---------- Header ---------- header = QHBoxLayout() + title = QLabel("🌡️ Unified Sensor Alerts Dashboard") title.setStyleSheet("font-size:22px; font-weight:700; color:#111;") header.addWidget(title) @@ -203,22 +190,10 @@ def _build_ui(self): self.search_box.setFixedWidth(220) header.addWidget(self.search_box) - self.refresh_btn = QPushButton("⟳ Refresh") - self.refresh_btn.clicked.connect(self.load_sensors) - self.refresh_btn.setStyleSheet(""" - QPushButton { - background-color: #0078D7; - color: white; - border-radius: 6px; - padding: 6px 12px; - font-weight: 600; - } - QPushButton:hover { background-color: #005FA3; } - """) - header.addWidget(self.refresh_btn) + # ← REMOVED refresh button completely + main_layout.addLayout(header) - # ---------- Scroll with cards ---------- self.scroll = QScrollArea() self.scroll.setWidgetResizable(True) self.container = QWidget() @@ -226,27 +201,25 @@ def _build_ui(self): self.grid.setSpacing(12) self.scroll.setWidget(self.container) main_layout.addWidget(self.scroll) + self.setLayout(main_layout) - # ---------------------------- + # ------------------------------------------------------------ def load_sensors(self): - self.refresh_btn.setEnabled(False) - self.refresh_btn.setText("⟳ Loading...") - try: - res_sensors = self.api.http.get(f"{self.api.base}/api/tables/sensors", timeout=10).json() - res_anoms = self.api.http.get(f"{self.api.base}/api/tables/sensors_anomalies_modal", timeout=10).json() - res_logs = self.api.http.get(f"{self.api.base}/api/tables/event_logs_sensors", timeout=10).json() + res_sensors = self.api.http.get(f"{self.api.base}/api/tables/sensors").json() + res_anoms = self.api.http.get(f"{self.api.base}/api/tables/sensors_anomalies_modal").json() + res_logs = self.api.http.get(f"{self.api.base}/api/tables/event_logs_sensors").json() + sensors = res_sensors.get("rows", []) anomalies = res_anoms.get("rows", []) alerts = res_logs.get("rows", []) - except Exception as e: + + except: traceback.print_exc() - self.refresh_btn.setEnabled(True) - self.refresh_btn.setText("↻ Refresh") return - # map anomalies by sensor + # --------------- map anomalies --------------- anomaly_latest = {} for a in anomalies: sid = a.get("sensor_id") @@ -256,43 +229,42 @@ def load_sensors(self): if prev is None or a.get("ts", "") > prev.get("ts", ""): anomaly_latest[sid] = a - # map alerts (event_logs_sensors) + # --------------- map alerts --------------- alerts_by_sensor = {} for alert in alerts: - dev_id = alert.get("device_id") - if not dev_id: + dev = alert.get("device_id") + if not dev: continue if alert.get("end_ts"): - continue # closed alert - alerts_by_sensor.setdefault(dev_id, []).append(alert) + continue + alerts_by_sensor.setdefault(dev, []).append(alert) + # --------------- merge --------------- merged = [] for s in sensors: - sid = s.get("sensor_name") - s_type = s.get("sensor_type", "Unknown") + sensor_id = s.get("sensor_id") + name = s.get("sensor_name") + s_type = s.get("sensor_type") - alerts_for_s = alerts_by_sensor.get(sid, []) - active_alerts = [a for a in alerts_for_s if not a.get("end_ts")] + alerts_for_s = alerts_by_sensor.get(name, []) + active = [a for a in alerts_for_s if not a.get("end_ts")] - # determine severity from alerts - if active_alerts: - latest_alert = sorted(active_alerts, key=lambda x: x.get("start_ts", ""), reverse=True)[0] - sev_alert = latest_alert.get("severity", "info").lower() - issue_alert = latest_alert.get("issue_type", "alert") + if active: + latest = sorted(active, key=lambda x: x.get("start_ts", ""), reverse=True)[0] + sev_alert = latest.get("severity", "info").lower() + issue_alert = latest.get("issue_type", "") else: sev_alert = "info" issue_alert = None - # determine severity from anomalies - anom = anomaly_latest.get(sid) + anom = anomaly_latest.get(sensor_id) if anom and anom.get("anomaly", 0) > 0: - sev_anom = "error" # you can adjust mapping of numeric to severity + sev_anom = "error" issue_anom = "Anomaly detected" else: sev_anom = "info" issue_anom = None - # pick the most severe sev_final = sev_alert issue_final = issue_alert or "No active alerts" if SEVERITY_RANK[sev_anom] > SEVERITY_RANK[sev_alert]: @@ -302,26 +274,28 @@ def load_sensors(self): all_alerts = alerts_for_s.copy() if anom: all_alerts.append({ - "issue_type": "anomaly_modal", - "severity": sev_anom, "start_ts": anom.get("ts"), + "severity": sev_anom, + "issue_type": "anomaly_modal", "details": {"anomaly": anom.get("anomaly")} }) merged.append({ - "sensor_name": sid, + "sensor_id": sensor_id, + "sensor_name": name, "sensor_type": s_type, "Issue": issue_final, "Severity": sev_final, - "All Alerts": all_alerts + "All Alerts": all_alerts, + "status": s.get("status"), + "lat": s.get("lat"), + "lon": s.get("lon"), }) self.all_sensors = merged self._apply_filters() - self.refresh_btn.setEnabled(True) - self.refresh_btn.setText("↻ Refresh") - # ---------------------------- + # ------------------------------------------------------------ def _render_cards(self, sensors): for i in reversed(range(self.grid.count())): w = self.grid.itemAt(i).widget() @@ -329,38 +303,37 @@ def _render_cards(self, sensors): w.setParent(None) if not sensors: - no_data = QLabel("No sensors found matching your criteria") - no_data.setAlignment(Qt.AlignmentFlag.AlignCenter) - no_data.setStyleSheet("color:#666; font-size:16px; padding:40px;") - self.grid.addWidget(no_data, 0, 0, 1, 3) + lbl = QLabel("No sensors found") + lbl.setAlignment(Qt.AlignmentFlag.AlignCenter) + self.grid.addWidget(lbl, 0, 0) return cols = 3 - for idx, s in enumerate(sensors): + for i, s in enumerate(sensors): card = SensorCard(s, self._show_alert_history) - r, c = divmod(idx, cols) - self.grid.addWidget(card, r, c, Qt.AlignmentFlag.AlignTop) + r, c = divmod(i, cols) + self.grid.addWidget(card, r, c) - # ---------------------------- + # ------------------------------------------------------------ def _apply_filters(self): - text = self.search_box.text().strip().lower() - sev_filter = self.filter_box.currentText().lower() - filtered = [] + text = self.search_box.text().lower().strip() + filt = self.filter_box.currentText().lower() + filtered = [] for s in self.all_sensors: - sid = str(s.get("sensor_name", "")).lower() - stype = str(s.get("sensor_type", "")).lower() + name = str(s.get("sensor_name", "")).lower() + t = str(s.get("sensor_type", "")).lower() sev = s.get("Severity", "").lower() - if text and text not in sid and text not in stype: + if text and text not in name and text not in t: continue - if sev_filter != "all" and sev_filter not in sev: + if filt != "all" and filt not in sev: continue filtered.append(s) self._render_cards(filtered) - # ---------------------------- + # ------------------------------------------------------------ def _show_alert_history(self, sensor): dlg = AlertDialog(sensor) dlg.exec() diff --git a/GUI/src/vast/views/sound/map_background.png b/GUI/src/vast/views/sound/map_background.png new file mode 100644 index 000000000..2f71da42e Binary files /dev/null and b/GUI/src/vast/views/sound/map_background.png differ diff --git a/GUI/src/vast/views/sound/sound_view.py b/GUI/src/vast/views/sound/sound_view.py new file mode 100644 index 000000000..1d47cd9c9 --- /dev/null +++ b/GUI/src/vast/views/sound/sound_view.py @@ -0,0 +1,1997 @@ +from PyQt6.QtWidgets import ( + QWidget, QVBoxLayout, QHBoxLayout, QLabel, QGridLayout, + QComboBox, QPushButton, QLineEdit, QDateEdit, + QFrame, QMessageBox, QTabWidget, QTableWidget, + QTableWidgetItem, QHeaderView, QAbstractItemView, + QStackedWidget, QSizePolicy, QCheckBox, QToolBar, QScrollArea +) +from PyQt6.QtCore import Qt, QDate, QUrl, QTimer, pyqtSignal, QSize +from PyQt6.QtGui import QPixmap, QColor, QCursor, QPainter, QFont +from PyQt6.QtMultimedia import QMediaPlayer, QAudioOutput +from PyQt6.QtWebEngineWidgets import QWebEngineView +from dashboard_api import DashboardApi +import matplotlib.pyplot as plt +from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas +from matplotlib.figure import Figure +import numpy as np +from datetime import datetime, timedelta +from vast.dashboard_api import DashboardApi +import requests +import os +import math +import tempfile + +MINIO_BASE = os.getenv("MINIO_PUBLIC_BASE", "http://minio-hot:9000") + +def normalize_minio_url(url: str) -> str: + if not url: + return "" + if url.startswith("http://") or url.startswith("https://"): + return url + url = url.lstrip("/") + if url.startswith("sounds/"): + url = "sound/" + url + return f"{MINIO_BASE.rstrip('/')}/{url}" + + +# ========================================================== +# Audio Waveform Visualizer +# ========================================================== +class AudioWaveform(QWidget): + def __init__(self, parent=None): + super().__init__(parent) + self.setMinimumHeight(180) + self.setMaximumHeight(220) + self.bars = [] + self.animation_offset = 0 + self.is_playing = False + + self.timer = QTimer(self) + self.timer.timeout.connect(self.animate) + + self.setStyleSheet(""" + background: qlineargradient(x1:0, y1:0, x2:1, y2:1, + stop:0 #0f0c29, stop:0.5 #302b63, stop:1 #24243e); + border: none; + border-radius: 12px; + """) + + self.default_text = "🎵 Press Play to Visualize Audio 🎵" + + def start_animation(self): + self.is_playing = True + self.bars = [0.2 + (i % 5) * 0.15 for i in range(100)] + self.timer.start(40) + + def stop_animation(self): + self.is_playing = False + self.timer.stop() + self.bars = [] + self.update() + + def animate(self): + if not self.is_playing: + return + + self.animation_offset = (self.animation_offset + 2) % 360 + + for i in range(len(self.bars)): + wave1 = math.sin((self.animation_offset + i * 8) * math.pi / 180) + wave2 = math.cos((self.animation_offset + i * 12) * math.pi / 180) + self.bars[i] = 0.25 + abs(wave1 * 0.35) + abs(wave2 * 0.25) + + self.update() + + def paintEvent(self, event): + painter = QPainter(self) + painter.setRenderHint(QPainter.RenderHint.Antialiasing) + + width = self.width() + height = self.height() + + if not self.bars: + painter.setPen(QColor(150, 180, 230, 200)) + font = painter.font() + font.setPointSize(14) + font.setBold(True) + painter.setFont(font) + painter.drawText(0, 0, width, height, + Qt.AlignmentFlag.AlignCenter, + self.default_text) + return + + bar_width = width / len(self.bars) + center_y = height / 2 + + gradient_colors = [ + (QColor(102, 126, 234), QColor(118, 75, 162)), + (QColor(67, 233, 123), QColor(56, 249, 215)), + (QColor(251, 200, 212), QColor(151, 149, 240)), + (QColor(250, 208, 196), QColor(255, 209, 255)) + ] + + for i, amplitude in enumerate(self.bars): + x = i * bar_width + bar_height = amplitude * (height - 30) + y_top = center_y - bar_height / 2 + y_bottom = center_y + bar_height / 2 + + gradient_idx = (i // 25) % len(gradient_colors) + color1, color2 = gradient_colors[gradient_idx] + + from PyQt6.QtGui import QLinearGradient + gradient = QLinearGradient(x, y_top, x, y_bottom) + gradient.setColorAt(0, color1) + gradient.setColorAt(1, color2) + + painter.setPen(Qt.PenStyle.NoPen) + painter.setBrush(gradient) + + bar_rect_width = max(2, bar_width - 1.5) + painter.drawRoundedRect( + int(x + 0.75), int(y_top), + int(bar_rect_width), int(bar_height), + 3, 3 + ) + + glow = QColor(255, 255, 255, 30) + painter.setBrush(glow) + painter.drawRoundedRect( + int(x + bar_width * 0.2), int(y_top + 2), + int(bar_rect_width * 0.3), int(bar_height * 0.4), + 2, 2 + ) + + +# ========================================================== +# Microphone Button Widget +# ========================================================== +class MicrophoneButton(QPushButton): + def __init__(self, mic_id: str, mic_name: str, mic_type: str, parent=None): + super().__init__(parent) + self.mic_id = mic_id + self.mic_name = mic_name + self.mic_type = mic_type + self.is_selected = False + + if mic_type == "audio": + self.setFixedSize(70, 70) + self.shape_style = "border-radius: 35px;" + else: + self.setFixedSize(70, 70) + self.shape_style = "border-radius: 8px;" + + self.setCursor(QCursor(Qt.CursorShape.PointingHandCursor)) + + self.base_color = "#000000" + self.selected_color = "#0078d4" + self.hover_color = "#222222" + self.disabled_color = "#888888" + + self.update_style() + self.setText(f"{mic_id.upper()}") + self.setToolTip(f"{mic_name}
Type: {mic_type}
Click to select") + + def update_style(self): + if not self.isEnabled(): + color = self.disabled_color + border = "#555" + elif self.is_selected: + color = self.selected_color + border = "#1e90ff" + else: + color = self.base_color + border = "white" + + self.setStyleSheet(f""" + QPushButton {{ + background-color: {color}; + color: white; + border: 3px solid {border}; + {self.shape_style} + font-size: 15px; + font-weight: bold; + padding: 4px; + }} + QPushButton:hover {{ + background-color: {self.hover_color}; + }} + """) + + def set_selected(self, selected: bool): + self.is_selected = selected + self.update_style() + + def set_disabled_state(self, disabled: bool): + self.setEnabled(not disabled) + self.update_style() + + +# ========================================================== +# Interactive Map with Image +# ========================================================== +class ImageMapView(QWidget): + def __init__(self, parent=None, api=None): + super().__init__(parent) + self.api = api + self.main_layout = QVBoxLayout(self) + self.main_layout.setContentsMargins(20, 20, 20, 20) + self.main_layout.setSpacing(15) + + self.selected_mics = [] + self.selected_type = None + self.mic_buttons = {} + + self.stacked_widget = QStackedWidget() + + self.map_page = QWidget() + layout = QVBoxLayout(self.map_page) + layout.setContentsMargins(0, 0, 0, 0) + layout.setSpacing(15) + + control_panel = QFrame() + control_panel.setStyleSheet(""" + QFrame { + background-color: white; + border: 2px solid #d1d5da; + border-radius: 8px; + padding: 10px; + } + """) + control_layout = QHBoxLayout(control_panel) + + self.selection_label = QLabel("Select microphones to view recordings") + self.selection_label.setStyleSheet("font-weight: bold; color: #333;") + + self.view_button = QPushButton("View Selected Recordings") + self.view_button.setEnabled(False) + self.view_button.setCursor(QCursor(Qt.CursorShape.PointingHandCursor)) + self.view_button.setStyleSheet(""" + QPushButton { + background-color: #28a745; + color: white; + border-radius: 6px; + padding: 10px 20px; + font-weight: bold; + } + QPushButton:hover:enabled { + background-color: #218838; + } + QPushButton:disabled { + background-color: #CCCCCC; + } + """) + self.view_button.clicked.connect(self.view_selected_recordings) + + self.clear_button = QPushButton("✕ Clear Selection") + self.clear_button.setEnabled(False) + self.clear_button.setCursor(QCursor(Qt.CursorShape.PointingHandCursor)) + self.clear_button.setStyleSheet(""" + QPushButton { + background-color: #dc3545; + color: white; + border-radius: 6px; + padding: 10px 20px; + font-weight: bold; + } + QPushButton:hover:enabled { + background-color: #c82333; + } + QPushButton:disabled { + background-color: #CCCCCC; + } + """) + self.clear_button.clicked.connect(self.clear_selection) + + control_layout.addWidget(self.selection_label) + control_layout.addStretch() + control_layout.addWidget(self.clear_button) + control_layout.addWidget(self.view_button) + + subtitle = QLabel("Click on microphones to select them (same type only)") + subtitle.setAlignment(Qt.AlignmentFlag.AlignCenter) + subtitle.setStyleSheet("font-size: 14px; color: #666; padding: 5px;") + + self.map_container = QWidget() + self.map_container.setMinimumSize(800, 600) + self.map_container.setStyleSheet(""" + background-color: #e8f4f8; + border: 3px solid #4A90E2; + border-radius: 15px; + """) + + self.background_label = QLabel(self.map_container) + self.background_label.setGeometry(0, 0, 800, 600) + self.background_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + + self._load_map_image() + + self.microphones = [ + {"id": "MIC-01", "name": "Environment Mic", "type": "audio", "position": (200, 150)}, + {"id": "MIC-02", "name": "Plant Ultrasound", "type": "ultrasound", "position": (500, 300)}, + {"id": "MIC-03", "name": "Environment Mic", "type": "audio", "position": (350, 450)} + ] + + for mic in self.microphones: + btn = MicrophoneButton(mic["id"], mic["name"], mic["type"], self.map_container) + btn.move(mic["position"][0], mic["position"][1]) + btn.clicked.connect(lambda checked, m=mic, b=btn: self.on_microphone_clicked(m, b)) + self.mic_buttons[mic["id"]] = btn + + legend = QLabel("🎤 circle = Audio Sensor • 🔊 square = Ultrasound Sensor") + legend.setAlignment(Qt.AlignmentFlag.AlignCenter) + legend.setStyleSheet(""" + font-size: 14px; + font-weight: 500; + padding: 10px; + background-color: white; + border: 2px solid #ddd; + border-radius: 8px; + color: #333; + """) + + layout.addWidget(control_panel) + layout.addWidget(subtitle) + layout.addWidget(self.map_container, 1) + layout.addWidget(legend) + + self.stacked_widget.addWidget(self.map_page) + self.recordings_page = None + + self.main_layout.addWidget(self.stacked_widget) + + def _load_map_image(self): + possible_paths = [ + "map_background.png", + "./map_background.png", + "../map_background.png", + os.path.join(os.getcwd(), "map_background.png"), + os.path.join(os.path.dirname(__file__), "map_background.png") + ] + + image_loaded = False + for path in possible_paths: + if os.path.exists(path): + pixmap = QPixmap(path) + if not pixmap.isNull(): + scaled = pixmap.scaled(800, 600, Qt.AspectRatioMode.KeepAspectRatio, + Qt.TransformationMode.SmoothTransformation) + self.background_label.setPixmap(scaled) + image_loaded = True + break + + if not image_loaded: + self.background_label.setStyleSheet("font-size: 16px; color: #888; background-color: #d0e8f2;") + self.background_label.setText("Sensor Locations\n\n(Map image not found)") + + def on_microphone_clicked(self, mic_data, button): + mic_id = mic_data["id"] + mic_type = mic_data["type"] + + if mic_id in self.selected_mics: + self.selected_mics.remove(mic_id) + button.set_selected(False) + + if not self.selected_mics: + self.selected_type = None + self.enable_all_buttons() + + self.update_selection_display() + return + + if self.selected_type is None: + self.selected_type = mic_type + self.disable_other_type_buttons(mic_type) + + if mic_type == self.selected_type: + self.selected_mics.append(mic_id) + button.set_selected(True) + self.update_selection_display() + + def disable_other_type_buttons(self, allowed_type): + for mic in self.microphones: + if mic["type"] != allowed_type: + self.mic_buttons[mic["id"]].set_disabled_state(True) + + def enable_all_buttons(self): + for btn in self.mic_buttons.values(): + btn.set_disabled_state(False) + + def clear_selection(self): + self.selected_mics = [] + self.selected_type = None + for btn in self.mic_buttons.values(): + btn.set_selected(False) + btn.set_disabled_state(False) + self.update_selection_display() + + def update_selection_display(self): + count = len(self.selected_mics) + if count == 0: + self.selection_label.setText("Select microphones to view recordings") + self.view_button.setEnabled(False) + self.clear_button.setEnabled(False) + else: + type_text = "Audio" if self.selected_type == "audio" else "Ultrasound" + self.selection_label.setText( + f"Selected {count} {type_text} microphone(s): {', '.join([m.upper() for m in self.selected_mics])}" + ) + self.view_button.setEnabled(True) + self.clear_button.setEnabled(True) + + def view_selected_recordings(self): + if not self.selected_mics: + return + + selected_mic_data = [mic for mic in self.microphones if mic["id"] in self.selected_mics] + + if self.recordings_page: + self.stacked_widget.removeWidget(self.recordings_page) + self.recordings_page.deleteLater() + + self.recordings_page = QWidget() + recordings_layout = QVBoxLayout(self.recordings_page) + recordings_layout.setContentsMargins(0, 0, 0, 0) + recordings_layout.setSpacing(0) + + header_container = QWidget() + color = "#4A90E2" if self.selected_type == "audio" else "#50C878" + header_container.setStyleSheet(f"background-color: {color};") + header_layout = QHBoxLayout(header_container) + header_layout.setContentsMargins(10, 10, 10, 10) + + back_button = QPushButton("← Back to Map") + back_button.setCursor(QCursor(Qt.CursorShape.PointingHandCursor)) + back_button.setStyleSheet(""" + QPushButton { + background-color: rgba(255, 255, 255, 0.2); + color: white; + border: 2px solid white; + border-radius: 6px; + padding: 8px 16px; + font-weight: bold; + } + QPushButton:hover { background-color: rgba(255, 255, 255, 0.3); } + """) + back_button.clicked.connect(self.show_map) + + mic_names = ", ".join([m["name"] for m in selected_mic_data]) + header = QLabel(f"Recordings: {mic_names}") + header.setAlignment(Qt.AlignmentFlag.AlignCenter) + header.setStyleSheet("font-size: 20px; font-weight: bold; color: white;") + + header_layout.addWidget(back_button) + header_layout.addWidget(header, 1) + header_layout.addStretch() + + type_text = "AUDIO" if self.selected_type == "audio" else "ULTRASOUND" + mic_ids = ", ".join([m["id"].upper() for m in selected_mic_data]) + subtitle = QLabel(f"Type: {type_text} • Microphones: {mic_ids}") + subtitle.setAlignment(Qt.AlignmentFlag.AlignCenter) + subtitle.setStyleSheet(""" + font-size: 13px; color: white; padding: 5px; + background-color: rgba(0, 0, 0, 0.2); + """) + + recordings_layout.addWidget(header_container) + recordings_layout.addWidget(subtitle) + + mic_ids_list = [m["id"] for m in selected_mic_data] + sound_tab = RecordingsTab( + mic_ids=mic_ids_list, + recording_type=self.selected_type, + parent=self, + api=self.api, + ) + recordings_layout.addWidget(sound_tab) + + self.stacked_widget.addWidget(self.recordings_page) + self.stacked_widget.setCurrentWidget(self.recordings_page) + + def show_map(self): + self.stacked_widget.setCurrentWidget(self.map_page) + + +# ========================================================== +# Recordings Tab +# ========================================================== +class RecordingsTab(QWidget): + def __init__(self, mic_ids=None, recording_type="audio", parent=None, api=None): + super().__init__(parent) + self.mic_ids = mic_ids if mic_ids else [] + self.recording_type = recording_type + self.api = api + + if recording_type == "ultrasound": + self.api_url = "http://db_api_service:8001/api/files/plant-predictions/" + else: + self.api_url = "http://db_api_service:8001/api/files/audio-aggregates/" + + layout = QVBoxLayout(self) + layout.setContentsMargins(20, 20, 20, 20) + layout.setSpacing(15) + + filter_frame = self._create_filter_frame() + + list_label = QLabel("Available Recordings") + list_label.setStyleSheet("font-size: 16px; font-weight: bold; color: #333; padding: 5px;") + + self.file_table = self._create_table() + + waveform_container = self._create_waveform_container() + + self.status_label = QLabel("Ready") + self.status_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + self.status_label.setStyleSheet(""" + font-size: 13px; color: #666; padding: 8px; + background-color: #f6f8fa; border-radius: 6px; border: 1px solid #d1d5da; + """) + + self.player = QMediaPlayer() + self.audio_output = QAudioOutput() + self.audio_output.setVolume(1.0) + self.player.setAudioOutput(self.audio_output) + self.player.playbackStateChanged.connect(self.on_playback_state_changed) + self._current_temp_file = None + self._current_play_btn = None + self._current_stop_btn = None + + layout.addWidget(filter_frame) + layout.addWidget(list_label) + layout.addWidget(self.file_table, 1) + + if self.recording_type == "audio": + layout.addWidget(waveform_container) + + layout.addWidget(self.status_label) + + self.refresh_button.clicked.connect(self.update_list) + self.update_list() + + def _create_filter_frame(self): + filter_frame = QFrame() + filter_frame.setStyleSheet(""" + QFrame { background-color: #ffffff; border-radius: 12px; padding: 15px; } + """) + filters_layout = QVBoxLayout(filter_frame) + filters_layout.setSpacing(12) + + filter_row = QHBoxLayout() + filter_row.setSpacing(8) + filter_row.setContentsMargins(0, 0, 0, 0) + + type_label = QLabel("Type:") + type_label.setStyleSheet("font-weight: bold; color: #333; font-size: 11px;") + filter_row.addWidget(type_label) + + self.noise_filter = QComboBox() + self.noise_filter.setMaximumWidth(180) + self.noise_filter.setStyleSheet(""" + QComboBox { + padding: 6px 10px; + border: 1px solid #d1d5da; + border-radius: 4px; + background: white; + font-size: 12px; + } + QComboBox:hover { border: 1px solid #4A90E2; } + """) + + if self.recording_type == "ultrasound": + self.noise_filter.addItems([ + "All signals", "Drought-stressed plant", + "Empty Pot", "Greenhouse Noises" + ]) + else: + self.noise_filter.addItems([ + "All types", "predatory_animals", "non_predatory_animals", + "birds", "fire", "footsteps", "insects", "screaming", + "shotgun", "stormy_weather", "streaming_water", "vehicle", "Other" + ]) + + filter_row.addWidget(self.noise_filter) + + date_label = QLabel(" From:") + date_label.setStyleSheet("font-weight: bold; color: #333; font-size: 11px;") + filter_row.addWidget(date_label) + + today = QDate.currentDate() + first_day = QDate(today.year(), today.month(), 1) + + self.date_from = QDateEdit() + self.date_from.setCalendarPopup(True) + self.date_from.setDate(first_day) + self.date_from.setMaximumWidth(120) + self.date_from.setStyleSheet(""" + QDateEdit { + padding: 6px 8px; + border: 1px solid #d1d5da; + border-radius: 4px; + background: white; + font-size: 12px; + } + """) + filter_row.addWidget(self.date_from) + + filter_row.addWidget(QLabel("→")) + + self.date_to = QDateEdit() + self.date_to.setCalendarPopup(True) + self.date_to.setDate(today) + self.date_to.setMaximumWidth(120) + self.date_to.setStyleSheet(self.date_from.styleSheet()) + filter_row.addWidget(self.date_to) + + self.search_box = QLineEdit() + self.search_box.setPlaceholderText("Search filename...") + self.search_box.setMaximumWidth(200) + self.search_box.setStyleSheet(""" + QLineEdit { + padding: 6px 10px; + border: 1px solid #d1d5da; + border-radius: 4px; + background: white; + font-size: 12px; + } + QLineEdit:focus { border: 1px solid #4A90E2; } + """) + filter_row.addWidget(self.search_box) + + filter_row.addStretch() + + filter_row.addWidget(QLabel("sort by:")) + self.sort_by = QComboBox() + self.sort_by.addItems(["date", "name", "device"]) + self.sort_by.setMaximumWidth(130) + self.sort_by.setStyleSheet(""" + QComboBox { + padding: 6px 10px; + border: 1px solid #d1d5da; + border-radius: 4px; + background: white; + font-size: 12px; + } + """) + filter_row.addWidget(self.sort_by) + + self.refresh_button = QPushButton("🔄 Refresh") + self.refresh_button.setCursor(QCursor(Qt.CursorShape.PointingHandCursor)) + self.refresh_button.setStyleSheet(""" + QPushButton { + background-color: #4A90E2; + color: white; + border-radius: 6px; + padding: 8px 16px; + font-weight: bold; + font-size: 12px; + } + QPushButton:hover { background-color: #357ABD; } + """) + filter_row.addWidget(self.refresh_button) + + filters_layout.addLayout(filter_row) + + return filter_frame + + def _create_table(self): + table = QTableWidget() + + if self.recording_type == "ultrasound": + table.setColumnCount(6) + table.setHorizontalHeaderLabels([ + "File", "Device", "Predicted Label", "Confidence", "Watering Status", "Format" + ]) + else: + table.setColumnCount(6) + table.setHorizontalHeaderLabels([ + "File", "Device", "Predicted Label", "Probability", "Format", "Actions" + ]) + + header = table.horizontalHeader() + header.setStretchLastSection(False) + for i in range(table.columnCount()): + header.setSectionResizeMode(i, QHeaderView.ResizeMode.Stretch) + + table.setStyleSheet(""" + QTableWidget { + background: #ffffff; + border: 2px solid #d1d5da; + border-radius: 10px; + gridline-color: #e1e4e8; + font-size: 14px; + } + QTableWidget::item { padding: 8px; } + QTableWidget::item:hover { background-color: #f6f8fa; } + QTableWidget::item:selected { background-color: #d6eaff; color: #0366d6; } + QHeaderView::section { + background-color: #f6f8fa; + padding: 10px; + border: 1px solid #d1d5da; + font-weight: bold; + color: #24292e; + } + """) + + table.setSelectionBehavior(QAbstractItemView.SelectionBehavior.SelectRows) + table.setSelectionMode(QAbstractItemView.SelectionMode.SingleSelection) + table.setEditTriggers(QAbstractItemView.EditTrigger.NoEditTriggers) + table.verticalHeader().setVisible(False) + + return table + + def _create_waveform_container(self): + waveform_container = QFrame() + waveform_container.setStyleSheet(""" + QFrame { + background-color: transparent; + border: none; + padding: 0px; + } + """) + + waveform_layout = QVBoxLayout(waveform_container) + waveform_layout.setSpacing(5) + + self.waveform = AudioWaveform() + self.waveform.setMinimumHeight(100) + self.waveform.setMaximumHeight(120) + + waveform_layout.addWidget(self.waveform) + + return waveform_container + + def on_playback_state_changed(self, state): + if state == QMediaPlayer.PlaybackState.PlayingState: + self.waveform.start_animation() + elif state == QMediaPlayer.PlaybackState.StoppedState: + self.waveform.stop_animation() + if self.status_label.text().startswith("Playing:"): + self.status_label.setText("Finished") + if hasattr(self, '_current_play_btn') and self._current_play_btn: + self._reset_button_pair(self._current_play_btn, self._current_stop_btn) + self._current_play_btn = None + self._current_stop_btn = None + + def _map_ultrasound_label(self, raw: str) -> str: + if not raw: + return "Unknown" + lower = raw.lower() + if "tomato" in lower or "tobacco" in lower: + return "Drought-stressed plant" + return raw + + def update_list(self): + self.file_table.setRowCount(0) + self.file_table.verticalHeader().setDefaultSectionSize(60) + self.status_label.setText("Loading...") + + params = { + "date_from": self.date_from.date().toString("yyyy-MM-dd"), + "date_to": self.date_to.date().toString("yyyy-MM-dd"), + "search": self.search_box.text().strip(), + "sort_by": self.sort_by.currentText(), + "limit": 100 + } + + filter_value = self.noise_filter.currentText() + if self.recording_type == "ultrasound": + if filter_value in ("Empty Pot", "Greenhouse Noises"): + params["predicted_class"] = filter_value + else: + if filter_value not in ("All types", "All signals"): + params["type"] = filter_value + + if self.mic_ids: + params["device_ids"] = ",".join(self.mic_ids) + + try: + # Check if API is available and authenticated + if not self.api or not hasattr(self.api, 'http'): + self.status_label.setText("⚠ API connection not available") + QMessageBox.warning( + self, + "Authentication Required", + "Please login first to access recordings." + ) + return + + # Use the authenticated session + response = self.api.http.get(self.api_url, params=params, timeout=10) + response.raise_for_status() + data = response.json() + + print(f"[DEBUG] Successfully fetched {len(data)} records from {self.api_url}") + for f in data: + row = self.file_table.rowCount() + self.file_table.insertRow(row) + self.file_table.setRowHeight(row, 60) + + filename = f.get("filename") or f.get("file", "") + is_compressed = f.get("is_compressed", False) + + text_color = QColor("#888888") if is_compressed else QColor("#000000") + + if self.recording_type == "ultrasound": + device_id = f.get("device_id", "N/A") + pred_class_raw = f.get("predicted_class", "Unknown") + pred_class = self._map_ultrasound_label(pred_class_raw) + confidence = f.get("confidence", 0) + watering_status = f.get("watering_status", "N/A") + url = normalize_minio_url(f.get("url", "")) + + format_str = "OPUS (Compressed)" if is_compressed else "WAV (Original)" + + item0 = QTableWidgetItem(filename) + item0.setForeground(text_color) + self.file_table.setItem(row, 0, item0) + + item1 = QTableWidgetItem(device_id) + item1.setForeground(text_color) + self.file_table.setItem(row, 1, item1) + + item2 = QTableWidgetItem(pred_class) + item2.setForeground(text_color) + self.file_table.setItem(row, 2, item2) + + item3 = QTableWidgetItem(f"{confidence:.2%}") + item3.setForeground(text_color) + self.file_table.setItem(row, 3, item3) + + item4 = QTableWidgetItem(watering_status) + item4.setForeground(text_color) + self.file_table.setItem(row, 4, item4) + + item5 = QTableWidgetItem(format_str) + item5.setForeground(text_color) + self.file_table.setItem(row, 5, item5) + else: + device_id = f.get("device_id", "N/A") + label = f.get("predicted_label", "Unknown") + prob = f.get("probability", 0) + url = normalize_minio_url(f.get("url", "")) + + format_str = "OPUS (Compressed)" if is_compressed else "WAV (Original)" + + item0 = QTableWidgetItem(filename) + item0.setForeground(text_color) + self.file_table.setItem(row, 0, item0) + + item1 = QTableWidgetItem(device_id) + item1.setForeground(text_color) + self.file_table.setItem(row, 1, item1) + + item2 = QTableWidgetItem(label) + item2.setForeground(text_color) + self.file_table.setItem(row, 2, item2) + + item3 = QTableWidgetItem(f"{prob:.2%}") + item3.setForeground(text_color) + self.file_table.setItem(row, 3, item3) + + item4 = QTableWidgetItem(format_str) + item4.setForeground(text_color) + self.file_table.setItem(row, 4, item4) + + if self.recording_type == "audio": + control_widget = QWidget() + control_layout = QHBoxLayout(control_widget) + control_layout.setContentsMargins(2, 2, 2, 2) + control_layout.setSpacing(6) + + play_btn = QPushButton("▶") + play_btn.setCursor(QCursor(Qt.CursorShape.PointingHandCursor)) + play_btn.setFixedSize(35, 30) + + if is_compressed: + play_btn.setStyleSheet(""" + QPushButton { + background-color: #888888; + color: white; + border-radius: 4px; + font-weight: bold; + } + QPushButton:hover:enabled { background-color: #666666; } + QPushButton:disabled { background-color: #cccccc; color: #888888; } + """) + play_btn.setToolTip("Compressed OPUS file - may have compatibility issues") + else: + play_btn.setStyleSheet(""" + QPushButton { + background-color: #0078d4; + color: white; + border-radius: 4px; + font-weight: bold; + } + QPushButton:hover:enabled { background-color: #005fa3; } + QPushButton:disabled { background-color: #cccccc; color: #888888; } + """) + + stop_btn = QPushButton("⏹") + stop_btn.setCursor(QCursor(Qt.CursorShape.PointingHandCursor)) + stop_btn.setFixedSize(35, 30) + stop_btn.setEnabled(False) + stop_btn.setStyleSheet(""" + QPushButton { + background-color: #6c757d; + color: white; + border-radius: 4px; + font-weight: bold; + } + QPushButton:disabled { background-color: #b0b0b0; } + QPushButton:hover:enabled { background-color: #c82333; } + """) + + play_btn.setProperty("row", row) + stop_btn.setProperty("row", row) + + play_btn.clicked.connect( + lambda checked=False, u=url, fname=filename, pb=play_btn, sb=stop_btn, compressed=is_compressed: + self.play_row_audio(u, fname, pb, sb, compressed) + ) + stop_btn.clicked.connect( + lambda checked=False, pb=play_btn, sb=stop_btn: + self.stop_row_audio(pb, sb) + ) + + control_layout.addWidget(play_btn) + control_layout.addWidget(stop_btn) + + self.file_table.setCellWidget(row, 5, control_widget) + + if self.file_table.rowCount() == 0: + self.file_table.insertRow(0) + empty_item = QTableWidgetItem("No recordings found") + empty_item.setForeground(QColor("#999")) + self.file_table.setItem(0, 0, empty_item) + self.file_table.setSpan(0, 0, 1, 6) + + self.status_label.setText(f"✓ Loaded {len(data)} recordings") + + except requests.exceptions.HTTPError as e: + if e.response.status_code == 401: + self.status_label.setText("⚠ Authentication required") + QMessageBox.warning(self, "Authentication Error", + "API requires authentication. Please check your credentials.") + else: + self.status_label.setText(f"⚠ HTTP Error {e.response.status_code}") + QMessageBox.warning(self, "HTTP Error", + f"Server returned error {e.response.status_code}:\n{str(e)}") + except requests.exceptions.Timeout: + self.status_label.setText("⚠ Request timeout") + QMessageBox.warning(self, "Timeout", "Request timed out. Please try again.") + except requests.exceptions.ConnectionError: + self.status_label.setText("⚠ Connection error") + QMessageBox.warning(self, "Connection Error", + "Could not connect to server. Check your connection.") + except Exception as e: + self.status_label.setText("⚠ Error loading data") + QMessageBox.warning(self, "Error", f"Failed to load recordings:\n{str(e)}") + + def play_row_audio(self, url, filename, play_btn, stop_btn, is_compressed=False): + if not url: + QMessageBox.warning(self, "No URL", "Audio file URL not available") + return + + self.player.stop() + self.waveform.stop_animation() + + try: + if self._current_temp_file: + if os.path.exists(self._current_temp_file): + os.remove(self._current_temp_file) + except Exception: + pass + self._current_temp_file = None + + playback_url = url + if url.startswith("http://localhost") or url.startswith("http://127.0.0.1"): + parts = url.split("/", 3) + if len(parts) > 3: + path = parts[3] + playback_url = f"http://minio-hot:9000/{path}" + + if is_compressed: + reply = QMessageBox.question( + self, + "Compressed File", + "This is a compressed OPUS file. Playback may not work properly.\n\nContinue anyway?", + QMessageBox.StandardButton.Yes | QMessageBox.StandardButton.No + ) + if reply == QMessageBox.StandardButton.No: + return + + try: + session = self.api.http if (self.api and getattr(self.api, "http", None)) else requests + resp = session.get(playback_url, timeout=15) + resp.raise_for_status() + suffix = ".ogg" if is_compressed else ".wav" + tmp = tempfile.NamedTemporaryFile(delete=False, suffix=suffix) + tmp.write(resp.content) + tmp.flush() + tmp_path = tmp.name + tmp.close() + self._current_temp_file = tmp_path + except requests.exceptions.RequestException as e: + self.status_label.setText("⚠ Unable to download file") + QMessageBox.warning(self, "Download Error", f"Could not download audio file:\n{e}") + return + except Exception as e: + self.status_label.setText("⚠ Error downloading file") + QMessageBox.warning(self, "Error", f"Failed to download audio file:\n{e}") + return + + try: + self._reset_all_buttons() + + play_btn.setEnabled(False) + play_btn.setStyleSheet(""" + QPushButton { + background-color: #888888; + color: white; + border-radius: 4px; + font-weight: bold; + } + """) + + stop_btn.setEnabled(True) + stop_btn.setStyleSheet(""" + QPushButton { + background-color: #dc3545; + color: white; + border-radius: 4px; + font-weight: bold; + } + QPushButton:hover { background-color: #c82333; } + """) + + self.player.setSource(QUrl.fromLocalFile(self._current_temp_file)) + self.player.play() + self.waveform.start_animation() + self.status_label.setText(f"Playing: {filename}") + + self._current_play_btn = play_btn + self._current_stop_btn = stop_btn + + except Exception as e: + self.status_label.setText("⚠ Playback error") + QMessageBox.warning(self, "Playback Error", f"Playback failed:\n{e}") + self._reset_all_buttons() + + def stop_row_audio(self, play_btn, stop_btn): + self.player.stop() + self.waveform.stop_animation() + self.status_label.setText("⏹ Stopped") + self._reset_button_pair(play_btn, stop_btn) + + def _reset_button_pair(self, play_btn, stop_btn): + if play_btn.toolTip() and "Compressed" in play_btn.toolTip(): + play_btn.setStyleSheet(""" + QPushButton { + background-color: #888888; + color: white; + border-radius: 4px; + font-weight: bold; + } + QPushButton:hover:enabled { background-color: #666666; } + QPushButton:disabled { background-color: #cccccc; color: #888888; } + """) + else: + play_btn.setStyleSheet(""" + QPushButton { + background-color: #0078d4; + color: white; + border-radius: 4px; + font-weight: bold; + } + QPushButton:hover:enabled { background-color: #005fa3; } + QPushButton:disabled { background-color: #cccccc; color: #888888; } + """) + play_btn.setEnabled(True) + + stop_btn.setEnabled(False) + stop_btn.setStyleSheet(""" + QPushButton { + background-color: #6c757d; + color: white; + border-radius: 4px; + font-weight: bold; + } + QPushButton:disabled { background-color: #b0b0b0; } + QPushButton:hover:enabled { background-color: #c82333; } + """) + + def _reset_all_buttons(self): + if self.recording_type != "audio": + return + + actions_col = 5 + for row in range(self.file_table.rowCount()): + widget = self.file_table.cellWidget(row, actions_col) + if widget: + layout = widget.layout() + if layout and layout.count() >= 2: + play_btn = layout.itemAt(0).widget() + stop_btn = layout.itemAt(1).widget() + if play_btn and stop_btn and isinstance(play_btn, QPushButton): + self._reset_button_pair(play_btn, stop_btn) + + +# ========================================================== +# Sound Analytics View - NEW TAB from first document +# ========================================================== +class SoundAnalyticsView(QWidget): + """Sound detection dashboard with filtering by time range and sound type""" + + SOUND_TYPES = [ + "non_predatory_animals", + "predatory_animals", + "birds", + "fire", + "footsteps", + "insects", + "screaming", + "shotgun", + "stormy_weather", + "streaming_water", + "vehicle" + ] + + CYAN_PALETTE = [ + '#003366', '#004d99', '#0066cc', '#1a80e5', + '#3399ff', '#53A0E5', '#66b3ff', '#80ccff', + '#99e6ff', '#b3f0ff', '#ccf7ff' + ] + + PRIMARY_CYAN = '#53A0E5' + ACCENT_CYAN = '#3399ff' + + LIGHT_THEME = { + 'bg': '#f8f9fa', + 'card': '#ffffff', + 'text': '#333333', + 'border': '#e0e0e0', + 'primary': PRIMARY_CYAN, + 'accent': ACCENT_CYAN + } + + DARK_THEME = { + 'bg': '#1e1e1e', + 'card': '#2d2d2d', + 'text': '#e0e0e0', + 'border': '#444444', + 'primary': '#64B5F6', + 'accent': ACCENT_CYAN + } + + def __init__(self, api: DashboardApi, parent=None): + super().__init__(parent) + self.api = api + + print(f"[INIT] API object: {self.api}", flush=True) + print(f"[INIT] API has http: {hasattr(self.api, 'http')}", flush=True) + + try: + test_query = "SELECT 1 as test" + result = self.api.run_query(test_query) + print(f"[INIT] DB test result: {result}", flush=True) + except Exception as e: + print(f"[INIT] DB connection error: {e}", flush=True) + + self.current_time_range = 'day' + self.current_sound_types = [] + self.is_dark_theme = False + self.current_theme = self.LIGHT_THEME.copy() + + self.setWindowTitle("Sound Detection Analytics") + self.setMinimumSize(QSize(1350, 1000)) + + main_layout = QVBoxLayout() + main_layout.setContentsMargins(0, 0, 0, 0) + main_layout.setSpacing(0) + + content_frame = QFrame() + content_layout = QVBoxLayout() + content_layout.setContentsMargins(12, 12, 12, 12) + content_layout.setSpacing(12) + + filter_frame = QFrame() + filter_frame.setStyleSheet(""" + QFrame { + background-color: white; + border: 1px solid #e8e8e8; + border-radius: 8px; + } + """) + filter_frame.setMaximumHeight(450) + filter_layout = QVBoxLayout() + filter_layout.setContentsMargins(12, 10, 12, 10) + filter_layout.setSpacing(15) + + time_row = QHBoxLayout() + time_label = QLabel("Time Range:") + time_label.setFont(QFont("Arial", 10, QFont.Weight.Bold)) + time_row.addWidget(time_label) + self.time_filter = QComboBox() + self.time_filter.addItems(['1 Day', '1 Week', '1 Month']) + self.time_filter.setCurrentText('1 Day') + self.time_filter.currentTextChanged.connect(self._on_filter_changed) + self.time_filter.setMinimumWidth(140) + time_row.addWidget(self.time_filter) + time_row.addStretch() + filter_layout.addLayout(time_row) + + sound_header_row = QHBoxLayout() + sound_label = QLabel("Sound Types (select multiple):") + sound_label.setFont(QFont("Arial", 10, QFont.Weight.Bold)) + sound_header_row.addWidget(sound_label) + + self.selection_label = QLabel("All sounds selected") + self.selection_label.setStyleSheet(f"color: {self.PRIMARY_CYAN}; font-weight: bold;") + sound_header_row.addWidget(self.selection_label) + sound_header_row.addStretch() + + clear_btn = QPushButton("Clear All") + clear_btn.setMaximumWidth(100) + clear_btn.clicked.connect(self._clear_sound_selection) + sound_header_row.addWidget(clear_btn) + + apply_btn = QPushButton("Apply Filter") + apply_btn.setMaximumWidth(100) + apply_btn.setStyleSheet(f""" + QPushButton {{ + background-color: {self.PRIMARY_CYAN}; + color: white; + font-weight: bold; + }} + QPushButton:hover {{ + background-color: {self.CYAN_PALETTE[2]}; + }} + """) + apply_btn.clicked.connect(self._refresh_data) + sound_header_row.addWidget(apply_btn) + filter_layout.addLayout(sound_header_row) + + checkbox_container = QFrame() + checkbox_container.setObjectName("checkboxContainer") + checkbox_container.setStyleSheet(f""" + QFrame#checkboxContainer {{ + background-color: white; + border: 2px solid {self.PRIMARY_CYAN}; + border-radius: 6px; + max-height: 350px; + }} + """) + checkbox_layout = QGridLayout() + checkbox_layout.setSpacing(5) + checkbox_layout.setContentsMargins(10, 10, 10, 10) + + self.sound_checkboxes = {} + for idx, sound_name in enumerate(self.SOUND_TYPES): + checkbox = QCheckBox(sound_name) + checkbox.stateChanged.connect(self._on_sound_checkbox_changed) + self.sound_checkboxes[sound_name] = checkbox + row = idx // 3 + col = idx % 3 + checkbox_layout.addWidget(checkbox, row, col) + + checkbox_container.setLayout(checkbox_layout) + filter_layout.addWidget(checkbox_container) + filter_frame.setLayout(filter_layout) + content_layout.addWidget(filter_frame) + + calendar_frame = self._create_activity_calendar() + content_layout.addWidget(calendar_frame) + + grid = QGridLayout() + grid.setSpacing(12) + grid.setRowStretch(0, 1) + grid.setRowStretch(1, 1) + grid.setRowStretch(2, 1) + grid.setColumnStretch(0, 1) + grid.setColumnStretch(1, 1) + + def make_chart_frame(title, canvas): + frame = self._create_chart_frame(title, canvas) + frame.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + frame.setMinimumHeight(320) + frame.setMaximumHeight(320) + return frame + + self.dist_canvas = self._create_canvas(figsize=(6, 5)) + grid.addWidget(make_chart_frame("Sound Distribution (Count)", self.dist_canvas), 0, 0) + + self.timeline_canvas = self._create_canvas(figsize=(6, 5)) + grid.addWidget(make_chart_frame("Detection Timeline", self.timeline_canvas), 0, 1) + + self.heatmap_canvas = self._create_canvas(figsize=(6, 5)) + grid.addWidget(make_chart_frame("Sound Heatmap - Activity Patterns", self.heatmap_canvas), 1, 0) + + self.correlation_canvas = self._create_canvas(figsize=(6, 5)) + grid.addWidget(make_chart_frame("Correlation Explorer", self.correlation_canvas), 1, 1) + + self.confidence_canvas = self._create_canvas(figsize=(6, 5)) + grid.addWidget(make_chart_frame("Model Health Monitor", self.confidence_canvas), 2, 0) + + stats_frame = self._create_stats_frame() + stats_frame.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + stats_frame.setMinimumHeight(320) + stats_frame.setMaximumHeight(320) + grid.addWidget(stats_frame, 2, 1) + + content_layout.addLayout(grid, stretch=10) + content_frame.setLayout(content_layout) + + scroll_area = QScrollArea() + scroll_area.setWidgetResizable(True) + scroll_area.setVerticalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOn) + scroll_area.setHorizontalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOff) + scroll_area.setWidget(content_frame) + + main_layout.addWidget(scroll_area) + self.setLayout(main_layout) + + self.refresh_timer = QTimer() + self.refresh_timer.timeout.connect(self._refresh_data) + self.refresh_timer.start(30000) + + self._refresh_data() + + def _create_activity_calendar(self) -> QFrame: + frame = QFrame() + frame.setStyleSheet(""" + QFrame { + background-color: white; + border: 1px solid #e8e8e8; + border-radius: 8px; + } + """) + frame.setMaximumHeight(120) + + layout = QVBoxLayout() + layout.setContentsMargins(12, 12, 12, 12) + layout.setSpacing(8) + + title = QLabel("Activity Calendar (Last 30 Days)") + title.setFont(QFont("Arial", 10, QFont.Weight.Bold)) + layout.addWidget(title) + + calendar_grid = QHBoxLayout() + calendar_grid.setSpacing(2) + + today = datetime.now().date() + for i in range(30): + date = today - timedelta(days=29-i) + day_box = QFrame() + day_box.setMinimumSize(QSize(20, 20)) + day_box.setMaximumSize(QSize(20, 20)) + + intensity = np.random.rand() + color = self._get_intensity_color(intensity) + + day_box.setStyleSheet(f""" + QFrame {{ + background-color: {color}; + border: 1px solid #ddd; + border-radius: 2px; + }} + """) + + day_label = QLabel(str(date.day)) + day_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + day_label.setFont(QFont("Arial", 6)) + day_layout = QVBoxLayout() + day_layout.setContentsMargins(0, 0, 0, 0) + day_layout.addWidget(day_label) + day_box.setLayout(day_layout) + + calendar_grid.addWidget(day_box) + + calendar_grid.addStretch() + layout.addLayout(calendar_grid) + frame.setLayout(layout) + return frame + + def _get_intensity_color(self, intensity: float) -> str: + if intensity < 0.2: + return self.CYAN_PALETTE[0] + elif intensity < 0.4: + return self.CYAN_PALETTE[2] + elif intensity < 0.6: + return self.CYAN_PALETTE[4] + elif intensity < 0.8: + return self.CYAN_PALETTE[7] + else: + return self.CYAN_PALETTE[10] + + def _create_canvas(self, figsize=(5.5, 4.5)): + canvas = FigureCanvas(Figure(figsize=figsize, dpi=90)) + canvas.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding) + return canvas + + def _create_chart_frame(self, title: str, widget: QWidget) -> QFrame: + frame = QFrame() + frame.setStyleSheet(""" + QFrame { + background-color: white; + border: 1px solid #e8e8e8; + border-radius: 8px; + } + """) + + layout = QVBoxLayout() + layout.setContentsMargins(12, 12, 12, 12) + layout.setSpacing(8) + + title_label = QLabel(title) + title_label.setFont(QFont("Arial", 11, QFont.Weight.Bold)) + title_label.setStyleSheet(f"color: {self.PRIMARY_CYAN}; margin-bottom: 4px;") + layout.addWidget(title_label) + + layout.addWidget(widget, 1) + frame.setLayout(layout) + return frame + + def _create_stats_frame(self) -> QFrame: + frame = QFrame() + frame.setStyleSheet(""" + QFrame { + background-color: white; + border: 1px solid #e8e8e8; + border-radius: 8px; + } + """) + + layout = QVBoxLayout() + layout.setContentsMargins(12, 12, 12, 12) + layout.setSpacing(10) + + title_label = QLabel("Statistics") + title_label.setFont(QFont("Arial", 11, QFont.Weight.Bold)) + title_label.setStyleSheet(f"color: {self.PRIMARY_CYAN}; margin-bottom: 6px;") + layout.addWidget(title_label) + + stats_grid = QGridLayout() + stats_grid.setSpacing(10) + stats_grid.setRowStretch(0, 1) + stats_grid.setRowStretch(1, 1) + stats_grid.setColumnStretch(0, 1) + stats_grid.setColumnStretch(1, 1) + + self.stat_boxes = {} + + stat_names = [ + ("Total Files", "total_files"), + ("Unknown Type", "unknown_count"), + ("Avg Confidence", "avg_confidence"), + ("Avg Processing", "avg_processing_ms") + ] + + for idx, (label, key) in enumerate(stat_names): + row = idx // 2 + col = idx % 2 + box = self._create_stat_box(label) + self.stat_boxes[key] = box + stats_grid.addWidget(box, row, col) + + layout.addLayout(stats_grid, 1) + frame.setLayout(layout) + return frame + + def _create_stat_box(self, label: str) -> QFrame: + box = QFrame() + box.setStyleSheet(""" + QFrame { + background-color: #fafafa; + border: 2px solid #e8e8e8; + border-radius: 8px; + } + """) + + layout = QVBoxLayout() + layout.setContentsMargins(12, 12, 12, 12) + layout.setSpacing(8) + layout.setAlignment(Qt.AlignmentFlag.AlignCenter) + + label_widget = QLabel(label) + label_widget.setFont(QFont("Arial", 9, QFont.Weight.Bold)) + label_widget.setStyleSheet("color: #666;") + label_widget.setAlignment(Qt.AlignmentFlag.AlignCenter) + layout.addWidget(label_widget) + + value_widget = QLabel("--") + value_widget.setFont(QFont("Arial", 22, QFont.Weight.Bold)) + value_widget.setStyleSheet(f"color: {self.PRIMARY_CYAN};") + value_widget.setAlignment(Qt.AlignmentFlag.AlignCenter) + layout.addWidget(value_widget) + + box.setLayout(layout) + box._label = label_widget + box._value = value_widget + return box + + def _on_sound_checkbox_changed(self): + selected = [] + for sound_name, checkbox in self.sound_checkboxes.items(): + if checkbox.isChecked(): + selected.append(sound_name) + + self.current_sound_types = selected + + if not selected: + self.selection_label.setText("All sounds selected") + elif len(selected) == 1: + self.selection_label.setText(f"1 sound type selected: {selected[0]}") + else: + self.selection_label.setText(f"{len(selected)} sound types selected") + + def _clear_sound_selection(self): + for checkbox in self.sound_checkboxes.values(): + checkbox.setChecked(False) + + self.current_sound_types = [] + self.selection_label.setText("All sounds selected") + self.time_filter.setCurrentText('1 Day') + self.current_time_range = 'day' + self._refresh_data() + + def _on_filter_changed(self): + time_map = {'1 Day': 'day', '1 Week': 'week', '1 Month': 'month'} + self.current_time_range = time_map.get(self.time_filter.currentText(), 'day') + self._refresh_data() + + def _refresh_data(self): + try: + sound_filter = self.current_sound_types if self.current_sound_types else None + + self._clear_canvas(self.dist_canvas) + self._clear_canvas(self.timeline_canvas) + self._clear_canvas(self.confidence_canvas) + + self._update_distribution_chart() + self._update_timeline_chart() + self._update_heatmap_chart() + self._update_correlation_chart() + self._update_confidence_chart() + self._update_stats_boxes() + except Exception as e: + print(f"[SoundAnalyticsView] Refresh error: {e}", flush=True) + + def _update_distribution_chart(self): + try: + sound_filter = self.current_sound_types if self.current_sound_types else None + data = self.api.get_audio_distribution( + self.current_time_range, + limit=15, + sound_types=sound_filter + ) + + print(f"[DEBUG] Distribution data: {len(data) if data else 0} items", flush=True) + + if not data: + self._show_no_data(self.dist_canvas) + return + + labels = [d['head_pred_label'] for d in data] + counts = [d['count'] for d in data] + + self.dist_canvas.figure.clear() + ax = self.dist_canvas.figure.add_subplot(111) + + colors = [self.CYAN_PALETTE[i % len(self.CYAN_PALETTE)] for i in range(len(labels))] + bars = ax.bar(range(len(labels)), counts, color=colors, edgecolor='black', linewidth=0.5) + + ax.set_xticks(range(len(labels))) + ax.set_xticklabels(labels, rotation=45, ha='right', fontsize=8) + ax.set_ylabel('Count', fontsize=9, fontweight='bold') + ax.grid(True, alpha=0.3, linestyle='--', axis='y') + + for bar in bars: + height = bar.get_height() + ax.text(bar.get_x() + bar.get_width()/2., height, + f'{int(height)}', + ha='center', va='bottom', fontsize=8, fontweight='bold') + + self.dist_canvas.figure.tight_layout() + self.dist_canvas.draw() + print("[DEBUG] Distribution chart drawn successfully", flush=True) + + except Exception as e: + print(f"[ERROR] Distribution chart error: {e}", flush=True) + import traceback + traceback.print_exc() + self._show_no_data(self.dist_canvas) + + def _update_timeline_chart(self): + try: + sound_filter = self.current_sound_types if self.current_sound_types else None + data = self.api.get_audio_timeline( + self.current_time_range, + sound_types=sound_filter + ) + + print(f"[DEBUG] Timeline data: {len(data) if data else 0} items", flush=True) + + if not data: + self._show_no_data(self.timeline_canvas) + return + + timeline_dict = {} + for row in data: + time_bucket = row['time_bucket'] + count = row['count'] + if time_bucket not in timeline_dict: + timeline_dict[time_bucket] = 0 + timeline_dict[time_bucket] += count + + sorted_times = sorted(timeline_dict.keys()) + times = [str(t)[:16] for t in sorted_times] + counts = [timeline_dict[t] for t in sorted_times] + + self.timeline_canvas.figure.clear() + ax = self.timeline_canvas.figure.add_subplot(111) + + ax.plot(times, counts, marker='o', linewidth=2, markersize=5, color=self.ACCENT_CYAN) + ax.fill_between(range(len(times)), counts, alpha=0.2, color=self.PRIMARY_CYAN) + ax.set_xlabel('Time', fontsize=9, fontweight='bold') + ax.set_ylabel('Detections', fontsize=9, fontweight='bold') + ax.grid(True, alpha=0.3, linestyle='--') + ax.tick_params(labelsize=8) + + self.timeline_canvas.figure.autofmt_xdate(rotation=45, ha='right') + self.timeline_canvas.figure.tight_layout() + self.timeline_canvas.draw() + print("[DEBUG] Timeline chart drawn successfully", flush=True) + + except Exception as e: + print(f"[ERROR] Timeline chart error: {e}", flush=True) + import traceback + traceback.print_exc() + self._show_no_data(self.timeline_canvas) + + def _update_confidence_chart(self): + try: + sound_filter = self.current_sound_types if self.current_sound_types else None + data = self.api.get_model_health_metrics( + self.current_time_range, + sound_types=sound_filter + ) + + if not data: + self._show_no_data(self.confidence_canvas) + return + + times = [str(d["time_bucket"])[:16] for d in data] + avg_conf = [d["avg_confidence"] * 100 for d in data] + avg_proc = [d["avg_processing_ms"] for d in data] + + fig = self.confidence_canvas.figure + fig.clear() + + ax1 = fig.add_subplot(111) + ax1.set_title("Model Performance Trends", fontsize=10, fontweight="bold", color=self.PRIMARY_CYAN) + ax1.plot(times, avg_conf, color=self.ACCENT_CYAN, marker="o", linewidth=2, label="Avg Confidence %") + ax1.fill_between(range(len(avg_conf)), avg_conf, alpha=0.15, color=self.PRIMARY_CYAN) + ax1.set_ylabel("Confidence (%)", fontsize=9, fontweight="bold") + ax1.set_ylim(0, 100) + ax1.tick_params(axis='x', rotation=45, labelsize=8) + ax1.grid(True, alpha=0.3, linestyle="--") + + ax2 = ax1.twinx() + proc_color = self.CYAN_PALETTE[7] + ax2.plot(times, avg_proc, color=proc_color, marker="^", linestyle="--", linewidth=2, label="Avg Processing (ms)") + ax2.set_ylabel("Processing Time (ms)", fontsize=9, fontweight="bold", color=proc_color) + ax2.tick_params(axis='y', labelcolor=proc_color) + + lines, labels = ax1.get_legend_handles_labels() + lines2, labels2 = ax2.get_legend_handles_labels() + ax1.legend(lines + lines2, labels + labels2, loc="upper left", fontsize=8) + + fig.tight_layout() + self.confidence_canvas.draw() + + except Exception as e: + print(f"[SoundAnalyticsView] Model Health Monitor chart error: {e}", flush=True) + self._show_no_data(self.confidence_canvas) + + def _update_stats_boxes(self): + try: + sound_filter = self.current_sound_types if self.current_sound_types else None + stats = self.api.get_audio_stats( + self.current_time_range, + sound_types=sound_filter + ) + + if stats: + total = stats.get('total_files', 0) or 0 + self.stat_boxes['total_files']._value.setText(str(total)) + + unknown = stats.get('unknown_count', 0) or 0 + self.stat_boxes['unknown_count']._value.setText(str(unknown)) + + avg_conf = stats.get('avg_confidence') + if avg_conf is not None and avg_conf > 0: + self.stat_boxes['avg_confidence']._value.setText(f"{avg_conf:.1%}") + else: + self.stat_boxes['avg_confidence']._value.setText("--") + + avg_proc = stats.get('avg_processing_ms') + if avg_proc is not None and avg_proc > 0: + self.stat_boxes['avg_processing_ms']._value.setText(f"{avg_proc:.0f}ms") + else: + self.stat_boxes['avg_processing_ms']._value.setText("--") + else: + for key in self.stat_boxes: + self.stat_boxes[key]._value.setText("--") + except Exception as e: + print(f"[SoundAnalyticsView] Stats update error: {e}", flush=True) + + def _clear_canvas(self, canvas): + canvas.figure.clear() + + def _show_no_data(self, canvas): + ax = canvas.figure.add_subplot(111) + ax.text(0.5, 0.5, 'No Data Available', + ha='center', va='center', fontsize=14, fontweight='bold', + transform=ax.transAxes, color='#999') + ax.set_xlim(0, 1) + ax.set_ylim(0, 1) + ax.axis('off') + canvas.draw() + + def closeEvent(self, event): + self.refresh_timer.stop() + super().closeEvent(event) + + def _update_heatmap_chart(self): + try: + sound_filter = self.current_sound_types if self.current_sound_types else None + data = self.api.get_audio_heatmap( + self.current_time_range, + sound_types=sound_filter + ) + + print(f"[DEBUG] Heatmap data: {len(data) if data else 0} items", flush=True) + + if not data: + self._show_no_data(self.heatmap_canvas) + return + + heatmap_data = np.zeros((24, 7)) + + for row in data: + hour = int(row['hour_of_day']) + day = int(row['day_of_week']) + count = row['count'] + heatmap_data[hour, day] += count + + self.heatmap_canvas.figure.clear() + ax = self.heatmap_canvas.figure.add_subplot(111) + + im = ax.imshow(heatmap_data, cmap='GnBu', aspect='auto', interpolation='nearest') + + ax.set_xticks(range(7)) + ax.set_xticklabels(['Sun', 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat'], fontsize=8) + ax.set_yticks(range(0, 24, 2)) + ax.set_yticklabels([f'{h:02d}:00' for h in range(0, 24, 2)], fontsize=7) + + ax.set_xlabel('Day of Week', fontsize=9, fontweight='bold') + ax.set_ylabel('Hour of Day', fontsize=9, fontweight='bold') + + cbar = self.heatmap_canvas.figure.colorbar(im, ax=ax, pad=0.02) + cbar.set_label('Detections', fontsize=8) + cbar.ax.tick_params(labelsize=7) + + for i in range(24): + for j in range(7): + if heatmap_data[i, j] > 0: + text_color = 'white' if heatmap_data[i, j] > heatmap_data.max() * 0.5 else 'black' + ax.text(j, i, int(heatmap_data[i, j]), + ha="center", va="center", color=text_color, fontsize=6, fontweight='bold') + + self.heatmap_canvas.figure.tight_layout() + self.heatmap_canvas.draw() + print("[DEBUG] Heatmap chart drawn successfully", flush=True) + + except Exception as e: + print(f"[ERROR] Heatmap chart error: {e}", flush=True) + import traceback + traceback.print_exc() + self._show_no_data(self.heatmap_canvas) + + def _update_correlation_chart(self): + try: + sound_filter = self.current_sound_types if self.current_sound_types else None + data = self.api.get_audio_correlations( + self.current_time_range, + sound_types=sound_filter + ) + + print(f"[DEBUG] Correlation data: {len(data) if data else 0} items", flush=True) + + if not data or len(data) < 1: + self._show_no_data(self.correlation_canvas) + return + + time_buckets = sorted(list(set(row['time_bucket'] for row in data))) + sound_types = sorted(list(set(row['sound_type'] for row in data))) + + if len(time_buckets) < 2 or len(sound_types) < 2: + self._show_no_data(self.correlation_canvas) + return + + n_times = len(time_buckets) + n_sounds = len(sound_types) + data_matrix = np.zeros((n_times, n_sounds)) + + time_idx = {t: i for i, t in enumerate(time_buckets)} + sound_idx = {s: i for i, s in enumerate(sound_types)} + + for row in data: + t_idx = time_idx[row['time_bucket']] + s_idx = sound_idx[row['sound_type']] + data_matrix[t_idx, s_idx] = row['detection_count'] + + corr_matrix = np.corrcoef(data_matrix.T) + corr_matrix = np.nan_to_num(corr_matrix, nan=0.0) + + self.correlation_canvas.figure.clear() + ax = self.correlation_canvas.figure.add_subplot(111) + + im = ax.imshow(corr_matrix, cmap='Blues', aspect='auto', vmin=-1, vmax=1) + + ax.set_xticks(range(len(sound_types))) + ax.set_yticks(range(len(sound_types))) + ax.set_xticklabels(sound_types, rotation=45, ha='right', fontsize=7) + ax.set_yticklabels(sound_types, fontsize=7) + + for i in range(len(sound_types)): + for j in range(len(sound_types)): + value = corr_matrix[i, j] + text_color = 'white' if value > 0.5 else 'black' + ax.text(j, i, f'{value:.2f}', + ha='center', va='center', + color=text_color, fontsize=6, fontweight='bold') + + cbar = self.correlation_canvas.figure.colorbar(im, ax=ax, fraction=0.046, pad=0.04) + cbar.set_label('Correlation Strength', rotation=270, labelpad=15, fontsize=8) + + ax.set_title('Sound Type Correlations\nDarker = Stronger Co-occurrence', + fontsize=9, fontweight='bold', pad=10) + + self.correlation_canvas.figure.tight_layout() + self.correlation_canvas.draw() + print("[DEBUG] Correlation chart drawn successfully", flush=True) + + except Exception as e: + print(f"[ERROR] Correlation chart error: {e}", flush=True) + import traceback + traceback.print_exc() + self._show_no_data(self.correlation_canvas) + +# ========================================================== +# Sound2 View - Displays Grafana dashboard +# ========================================================== +class Sound2View(QWidget): + def __init__(self, api: DashboardApi, parent=None): + super().__init__(parent) + self.api = api + self.setup_ui() + + def setup_ui(self): + layout = QVBoxLayout(self) + layout.setContentsMargins(0, 0, 0, 0) + + header = QHBoxLayout() + + title = QLabel("🌿 Ultrasonic Plant Predictions Dashboard") + title.setStyleSheet(""" + font-size: 18px; + font-weight: bold; + padding: 10px; + color: #2C3E50; + """) + header.addWidget(title) + + header.addStretch() + + refresh_btn = QPushButton("🔄 Refresh") + refresh_btn.setStyleSheet(""" + QPushButton { + background-color: #3498DB; + color: white; + border: none; + padding: 8px 16px; + border-radius: 4px; + font-weight: bold; + } + QPushButton:hover { + background-color: #2980B9; + } + """) + refresh_btn.clicked.connect(self.refresh_dashboard) + header.addWidget(refresh_btn) + + layout.addLayout(header) + + self.web_view = QWebEngineView() + + grafana_url = ( + "http://grafana:3000/d/ultrasonic-predictions/" + "ultrasonic-plant-predictions" + "?orgId=1&refresh=5s&kiosk=tv&theme=light" + ) + + self.web_view.setUrl(QUrl(grafana_url)) + layout.addWidget(self.web_view) + + self.status_label = QLabel("📊 Loading dashboard...") + self.status_label.setStyleSheet(""" + height: 24px; + padding: 5px; + color: #7F8C8D; + font-size: 12px; + """) + layout.addWidget(self.status_label) + + self.web_view.loadFinished.connect(self.on_load_finished) + + def refresh_dashboard(self): + self.status_label.setText("🔄 Refreshing dashboard...") + self.web_view.reload() + + def on_load_finished(self, success: bool): + if success: + self.status_label.setText("✓ Dashboard loaded successfully | Refreshes every 5s") + else: + self.status_label.setText( + "⚠ Failed to load dashboard. Please check Grafana server." + ) + + +# ========================================================== +# Main Sound View with Tabs +# ========================================================== +class SoundView(QWidget): + def __init__(self, api=None, parent=None): + super().__init__(parent) + self.api = api + + layout = QVBoxLayout(self) + layout.setContentsMargins(0, 0, 0, 0) + + self.tabs = QTabWidget() + self.tabs.setStyleSheet(""" + QTabWidget::pane { + border: 2px solid #d1d5da; + border-radius: 10px; + background: white; + } + QTabBar::tab { + background: #f6f8fa; + padding: 12px 24px; + border-radius: 8px 8px 0 0; + margin-right: 4px; + font-size: 14px; + font-weight: 500; + color: #586069; + } + QTabBar::tab:selected { + background-color: #4A90E2; + color: white; + } + QTabBar::tab:hover { background: #e1e4e8; } + """) + + self.map_tab = ImageMapView(api=self.api) + self.env_tab = RecordingsTab(recording_type="audio", api=self.api) + self.plant_tab = RecordingsTab(recording_type="ultrasound", api=self.api) + self.dashboard_tab = Sound2View(api=self.api) + self.analytics_tab = SoundAnalyticsView(api=self.api) + + self.tabs.addTab(self.map_tab, "🗺️ Interactive Map") + self.tabs.addTab(self.env_tab, "🎵 Environment Sounds") + self.tabs.addTab(self.plant_tab, "🌿 Plant Ultrasounds") + self.tabs.addTab(self.dashboard_tab, "📊 Ultrasonic Dashboard") + self.tabs.addTab(self.analytics_tab, "📈 Sound Analytics") + + layout.addWidget(self.tabs) diff --git a/README.md b/README.md new file mode 100644 index 000000000..06d285baf --- /dev/null +++ b/README.md @@ -0,0 +1,61 @@ +# 🌱 AgCloud -- Smart Cloud Agriculture Platform + +AgCloud is a smart cloud-based agriculture platform designed to +understand, monitor, and predict field conditions in real time. The +system integrates data from heterogeneous field sources and processes it +through a scalable, distributed data architecture to enable accurate, +data-driven decision making. + +## 🚜 System Overview + +The platform continuously collects data from a wide range of field +sources, including IoT sensors, soil and environmental measurements, +audio signals, cameras, drones, and agronomic and atmospheric data. + +The system unifies numeric, spatial, visual, and acoustic data into a +single, coherent view of the field. + +## 🔗 Data Ingestion & Streaming + +- MQTT is used as a lightweight, efficient, and reliable communication + protocol for ingesting data from edge devices. +- Apache Kafka serves as the backbone of the data layer, enabling + scalable, fault-tolerant, and distributed processing. + +## ⚙️ Data Processing Layer + +Data is consumed by: - Apache Flink for real-time stream processing - +Apache Airflow for scheduled and batch workflows + +Processing responsibilities include data cleaning, normalization, +enrichment, analytics, and predictive modeling. + +## 🗄️ Storage Layer + +Processed data is stored according to its characteristics: - PostgreSQL +(structured and time-series data) - Object Storage (images, video, +audio) - GIS-compatible storage (spatial data) - Vector Databases +(advanced analytics and embeddings) + +## 📊 Analytics & Visualization + +The platform enables anomaly detection, risk identification, and +long-term pattern analysis. Insights are exposed via a centralized API +and visualized through a unified dashboard with maps, metrics, alerts, +and forecasts. + +## 🐳 Running the Project + +### Prerequisites + +- Docker +- Docker Compose + +### Run the platform + +``` bash +docker compose up -d --build +``` + +This command builds and starts the entire system, including ingestion, +streaming, processing, storage, and API layers. diff --git a/RelDB/Dockerfile b/RelDB/Dockerfile index 10781dcc0..4c2f5bdba 100644 --- a/RelDB/Dockerfile +++ b/RelDB/Dockerfile @@ -38,6 +38,7 @@ COPY build_tables/02_event_logs_partition.sql /docker-entrypoint-initdb.d/02_eve COPY initdb/03_partitions.sql /docker-entrypoint-initdb.d/03_partitions.sql COPY build_tables/loader.sql /docker-entrypoint-initdb.d/04_loader.sql COPY initdb/04_cron.sql /docker-entrypoint-initdb.d/05_cron.sql +COPY build_tables/05_agcloud_audio_init.sql /docker-entrypoint-initdb.d/06_agcloud_audio_init.sql # ==== 7) Replication grants ==== RUN echo "ALTER ROLE missions_user WITH REPLICATION;" > /docker-entrypoint-initdb.d/00_grant_replication.sql diff --git a/RelDB/initdb/05_agcloud_audio_init.sql b/RelDB/build_tables/05_agcloud_audio_init.sql similarity index 75% rename from RelDB/initdb/05_agcloud_audio_init.sql rename to RelDB/build_tables/05_agcloud_audio_init.sql index 3eaed372d..d2b3afc83 100644 --- a/RelDB/initdb/05_agcloud_audio_init.sql +++ b/RelDB/build_tables/05_agcloud_audio_init.sql @@ -1,112 +1,98 @@ --- agcloud_audio unified initialization (schema + tables + indexes + 11-class view) --- Safe to run multiple times. - -BEGIN; - --- 1) Schema -CREATE SCHEMA IF NOT EXISTS agcloud_audio; - --- Use schema for subsequent CREATEs -SET search_path TO agcloud_audio, public; - --- 2) runs: per-run metadata -CREATE TABLE IF NOT EXISTS runs ( - run_id TEXT PRIMARY KEY, - started_at TIMESTAMPTZ NOT NULL DEFAULT now(), - finished_at TIMESTAMPTZ, - - model_name TEXT, - checkpoint TEXT, - head_path TEXT, - labels_csv TEXT, - - window_sec DOUBLE PRECISION NOT NULL CHECK (window_sec > 0), - hop_sec DOUBLE PRECISION NOT NULL CHECK (hop_sec > 0), - pad_last BOOLEAN NOT NULL, - agg TEXT NOT NULL CHECK (agg IN ('mean','max')), - topk INTEGER NOT NULL CHECK (topk >= 1), - device TEXT NOT NULL, - - code_version TEXT, - notes TEXT -); - --- 3) files: input file facts -CREATE TABLE IF NOT EXISTS files ( - file_id BIGSERIAL PRIMARY KEY, - path TEXT UNIQUE NOT NULL, - duration_s DOUBLE PRECISION CHECK (duration_s IS NULL OR duration_s >= 0), - sample_rate INTEGER, - size_bytes BIGINT -); - -CREATE UNIQUE INDEX IF NOT EXISTS ux_agcloud_files_path - ON files(path); - --- 4) file_aggregates: final per-file outputs (JSON-based head outputs) -CREATE TABLE IF NOT EXISTS file_aggregates ( - run_id TEXT NOT NULL, - file_id BIGINT NOT NULL, - - -- Flexible multi-class head probabilities (label -> prob) - head_probs_json JSONB, - - -- Final decision with "unknown" fallback - head_pred_label TEXT, - head_pred_prob DOUBLE PRECISION CHECK (head_pred_prob IS NULL OR (head_pred_prob BETWEEN 0 AND 1)), - head_unknown_threshold DOUBLE PRECISION, - head_is_another BOOLEAN, - - -- Aggregation context - num_windows INTEGER CHECK (num_windows IS NULL OR num_windows >= 0), - agg_mode TEXT, - - -- Performance metric (ms) - processing_ms INTEGER CHECK (processing_ms IS NULL OR processing_ms >= 0), - - PRIMARY KEY (run_id, file_id), - FOREIGN KEY (run_id) REFERENCES runs(run_id) ON DELETE CASCADE, - FOREIGN KEY (file_id) REFERENCES files(file_id) ON DELETE CASCADE -); - --- Helpful indexes -CREATE INDEX IF NOT EXISTS ix_agcloud_file_agg_run - ON file_aggregates(run_id); - -CREATE INDEX IF NOT EXISTS ix_agcloud_file_agg_pred_label - ON file_aggregates(head_pred_label); - --- JSONB GIN index to enable key/containment queries on probabilities map -CREATE INDEX IF NOT EXISTS ix_agcloud_file_agg_probs_gin - ON file_aggregates USING GIN (head_probs_json); - --- 5) Views --- If a 10-class view existed before, drop it to avoid confusion. -DROP VIEW IF EXISTS v_file_aggregates_probs10; - --- 11-class columns view (current head taxonomy) -DROP VIEW IF EXISTS v_file_aggregates_probs11; -CREATE VIEW v_file_aggregates_probs11 AS -SELECT - fa.run_id, - fa.file_id, - (fa.head_probs_json->>'predatory_animals')::double precision AS head_p_predatory_animals, - (fa.head_probs_json->>'non_predatory_animals')::double precision AS head_p_non_predatory_animals, - (fa.head_probs_json->>'birds')::double precision AS head_p_birds, - (fa.head_probs_json->>'fire')::double precision AS head_p_fire, - (fa.head_probs_json->>'footsteps')::double precision AS head_p_footsteps, - (fa.head_probs_json->>'insects')::double precision AS head_p_insects, - (fa.head_probs_json->>'screaming')::double precision AS head_p_screaming, - (fa.head_probs_json->>'shotgun')::double precision AS head_p_shotgun, - (fa.head_probs_json->>'stormy_weather')::double precision AS head_p_stormy_weather, - (fa.head_probs_json->>'streaming_water')::double precision AS head_p_streaming_water, - (fa.head_probs_json->>'vehicle')::double precision AS head_p_vehicle, - fa.head_pred_label, - fa.head_pred_prob, - fa.head_unknown_threshold, - fa.head_is_another, - fa.num_windows, - fa.agg_mode -FROM file_aggregates fa; - -COMMIT; +-- agcloud_audio initialization (schema + tables + indexes + 11-class view) + +BEGIN; + +-- 1) Schema +CREATE SCHEMA IF NOT EXISTS agcloud_audio; + +-- Use schema for subsequent CREATEs +SET search_path TO agcloud_audio, public; + +-- 2) runs: per-run metadata +CREATE TABLE IF NOT EXISTS runs ( + run_id TEXT PRIMARY KEY, + started_at TIMESTAMPTZ NOT NULL DEFAULT now(), + finished_at TIMESTAMPTZ, + + model_name TEXT, + checkpoint TEXT, + head_path TEXT, + labels_csv TEXT, + + window_sec DOUBLE PRECISION NOT NULL CHECK (window_sec > 0), + hop_sec DOUBLE PRECISION NOT NULL CHECK (hop_sec > 0), + pad_last BOOLEAN NOT NULL, + agg TEXT NOT NULL CHECK (agg IN ('mean','max')), + topk INTEGER NOT NULL CHECK (topk >= 1), + device TEXT NOT NULL, + + code_version TEXT, + notes TEXT +); + +-- 3) file_aggregates: final per-file outputs; references public.sounds_new_sounds_connections(id) +CREATE TABLE IF NOT EXISTS file_aggregates ( + run_id TEXT NOT NULL, + file_id BIGINT NOT NULL, + + -- Flexible multi-class head probabilities (label -> prob) + head_probs_json JSONB, + + -- Final decision with "unknown" fallback + head_pred_label TEXT, + head_pred_prob DOUBLE PRECISION CHECK (head_pred_prob IS NULL OR (head_pred_prob BETWEEN 0 AND 1)), + head_unknown_threshold DOUBLE PRECISION, + head_is_another BOOLEAN, + + -- Aggregation context + num_windows INTEGER CHECK (num_windows IS NULL OR num_windows >= 0), + agg_mode TEXT, + + -- Performance metric (ms) + processing_ms INTEGER CHECK (processing_ms IS NULL OR processing_ms >= 0), + + PRIMARY KEY (run_id, file_id), + FOREIGN KEY (run_id) REFERENCES runs(run_id) ON DELETE CASCADE, + FOREIGN KEY (file_id) REFERENCES public.sound_new_sounds_connections(id) ON DELETE CASCADE +); + +-- Helpful indexes +CREATE INDEX ix_agcloud_file_agg_run + ON file_aggregates(run_id); + +CREATE INDEX ix_agcloud_file_agg_pred_label + ON file_aggregates(head_pred_label); + +-- JSONB GIN index to enable key/containment queries on probabilities map +CREATE INDEX ix_agcloud_file_agg_probs_gin + ON file_aggregates USING GIN (head_probs_json); + +-- 4) Views +DROP VIEW IF EXISTS v_file_aggregates_probs10; +DROP VIEW IF EXISTS v_file_aggregates_probs11; + +-- 11-class columns view (current head taxonomy) +CREATE VIEW v_file_aggregates_probs11 AS +SELECT + fa.run_id, + fa.file_id, + (fa.head_probs_json->>'predatory_animals')::double precision AS head_p_predatory_animals, + (fa.head_probs_json->>'non_predatory_animals')::double precision AS head_p_non_predatory_animals, + (fa.head_probs_json->>'birds')::double precision AS head_p_birds, + (fa.head_probs_json->>'fire')::double precision AS head_p_fire, + (fa.head_probs_json->>'footsteps')::double precision AS head_p_footsteps, + (fa.head_probs_json->>'insects')::double precision AS head_p_insects, + (fa.head_probs_json->>'screaming')::double precision AS head_p_screaming, + (fa.head_probs_json->>'shotgun')::double precision AS head_p_shotgun, + (fa.head_probs_json->>'stormy_weather')::double precision AS head_p_stormy_weather, + (fa.head_probs_json->>'streaming_water')::double precision AS head_p_streaming_water, + (fa.head_probs_json->>'vehicle')::double precision AS head_p_vehicle, + fa.head_pred_label, + fa.head_pred_prob, + fa.head_unknown_threshold, + fa.head_is_another, + fa.num_windows, + fa.agg_mode +FROM file_aggregates fa; + +COMMIT; diff --git a/RelDB/build_tables/loader.sql b/RelDB/build_tables/loader.sql index 15b5f1435..aa5fc4eea 100644 --- a/RelDB/build_tables/loader.sql +++ b/RelDB/build_tables/loader.sql @@ -1,15 +1,54 @@ -- Extended synthetic data loader for schema_extended_v2.sql -- Insert devices -INSERT INTO devices (device_id, model, owner, active) VALUES - ('dev-a','drone-x','TeamA',true), - ('dev-b','drone-x','TeamA',true), - ('dev-c','rover-y','TeamB',true), - ('dev-d','rover-y','TeamB',true), - ('dev-e','sensor-z','TeamC',true), - ('dev-f','sensor-z','TeamC',true) +INSERT INTO devices (device_id, model, owner, active, location_lat, location_lon) VALUES + ('dev-a','drone-x','TeamA',true,NULL,NULL), + ('dev-b','drone-x','TeamA',true,NULL,NULL), + ('dev-c','rover-y','TeamB',true,NULL,NULL), + ('dev-d','rover-y','TeamB',true,NULL,NULL), + ('dev-e','sensor-z','TeamC',true,NULL,NULL), + ('dev-f','sensor-z','TeamC',true,NULL,NULL), + ('dev-g','ground-l','TeamD',true,NULL,NULL), + ('dev-h','ground-l','TeamD',true,NULL,NULL), + ('dev-i','ground-l','TeamD',true,NULL,NULL), + ('dev-j','ground-l','TeamD',true,NULL,NULL), + ('dev-k','ground-l','TeamD',true,NULL,NULL), + ('mic-1','sound-a','TeamD',true,NULL,NULL), + ('mic-2','sound-a','TeamD',true,NULL,NULL), + ('mic-33','sound-a','TeamD',true,NULL,NULL), + ('mic-u-2','sound-ul','TeamD',true,NULL,NULL) ON CONFLICT DO NOTHING; +INSERT INTO zones (name, geom) VALUES + ('Zone A', ST_GeomFromText('POLYGON((34.75 32.00, 34.90 32.00, 34.90 32.10, 34.75 32.10, 34.75 32.00))', 4326)), + ('Zone B', ST_GeomFromText('POLYGON((34.90 31.95, 35.05 31.95, 35.05 32.05, 34.90 32.05, 34.90 31.95))', 4326)) +ON CONFLICT DO NOTHING; + +-- Seed data for devices_sensor table +-- This file is automatically executed during database initialization + +INSERT INTO devices_sensor (id, plant_id, sensor_type, last_seen) VALUES + ('1', 101, 'temperature', NOW()), + ('2', 101, 'humidity', NOW()), + ('3', 101, 'soil_moisture', NOW()), + ('4', 102, 'co2', NOW()), + ('5', 102, 'light_intensity', NOW()), + ('6', 103, 'rainfall', NOW()), + ('7', 103, 'ph', NOW()), + ('8', 104, 'temperature', NOW()), + ('9', 104, 'humidity', NOW()), + ('10', 105, 'soil_moisture', NOW()), + ('11', 105, 'co2', NOW()), + ('12', 106, 'light_intensity', NOW()), + ('13', 106, 'wind_speed', NOW()), + ('14', 107, 'ph', NOW()), + ('15', 107, 'temperature', NOW()), + ('16', 107, 'ph', NOW()), + ('17', 107, 'temperature', NOW()) +ON CONFLICT (id) DO UPDATE SET + plant_id = EXCLUDED.plant_id, + sensor_type = EXCLUDED.sensor_type, + last_seen = NOW(); -- Insert some regions INSERT INTO regions (name, geom) @@ -29,7 +68,22 @@ ON CONFLICT DO NOTHING; -- Seed leaf disease types INSERT INTO leaf_disease_types (name) -VALUES ('Blight'), ('Mildew'), ('Rust') +VALUES + ('pepper__bacterial_spot'), + ('pepper__healthy'), + ('potato__early_blight'), + ('potato__healthy'), + ('potato__late_blight'), + ('tomato__bacterial_spot'), + ('tomato__early_blight'), + ('tomato__healthy'), + ('tomato__late_blight'), + ('tomato__leaf_mold'), + ('tomato__mosaic_virus'), + ('tomato__septoria_leaf_spot'), + ('tomato__spider_mites'), + ('tomato__target_spot'), + ('tomato__yellowleaf_curl_virus') ON CONFLICT DO NOTHING; -- Insert 5 missions @@ -137,7 +191,7 @@ SELECT ARRAY( FROM generate_series(1, 1000) ON CONFLICT DO NOTHING; --- === Seed בסיסי לטבלת task_thresholds === +-- === Seed task_thresholds === INSERT INTO task_thresholds (task, label, threshold, updated_by) VALUES (CAST('ripeness' AS task_type_enum), '', 0.75, 'seed'), @@ -151,12 +205,31 @@ DO UPDATE SET updated_by = EXCLUDED.updated_by, updated_at = NOW(); --- Seed sample leaf reports -INSERT INTO leaf_reports (device_id, leaf_disease_type_id, ts, confidence, sick) -SELECT d.device_id, t.id, now() - ((g % 2000) || ' seconds')::interval, - (random()*0.5 + 0.5)::double precision, -- 0.5..1.0 - (random() < 0.5) -FROM devices d, leaf_disease_types t, generate_series(1,20) g -LIMIT 30; - - +-- Seed sample leaf reports with random data +DO $$ +DECLARE + devices_arr text[] := ARRAY['dev-g', 'dev-h', 'dev-i', 'dev-j', 'dev-k']; + disease_ids int[]; + d text; + t int; + start_date timestamptz := '2025-10-25 00:00:00+00'::timestamptz; + end_date timestamptz := '2025-11-25 23:59:59+00'::timestamptz; + rand_ts timestamptz; + conf double precision; + sick_val boolean; +BEGIN + -- Get all disease type IDs + SELECT array_agg(id) INTO disease_ids FROM leaf_disease_types; + + -- Insert 1000 random reports + FOR i IN 1..1000 LOOP + d := devices_arr[ceil(random() * array_length(devices_arr,1))]; + t := disease_ids[ceil(random() * array_length(disease_ids,1))]; + rand_ts := start_date + (random() * (end_date - start_date)); + conf := round(random()::numeric, 2); + sick_val := (conf > 0.4); + + INSERT INTO leaf_reports(device_id, leaf_disease_type_id, ts, confidence, sick) + VALUES (d, t, rand_ts, conf, sick_val); + END LOOP; +END $$; \ No newline at end of file diff --git a/RelDB/build_tables/schema.sql b/RelDB/build_tables/schema.sql index 419b95067..b6464b643 100644 --- a/RelDB/build_tables/schema.sql +++ b/RelDB/build_tables/schema.sql @@ -16,6 +16,12 @@ CREATE TABLE IF NOT EXISTS devices ( location_lon DOUBLE PRECISION ); +CREATE TABLE IF NOT EXISTS public.zones ( + id SERIAL PRIMARY KEY, + name VARCHAR(128) NOT NULL, + geom geometry(POLYGON, 4326) NOT NULL +); + -- Predefined regions (optional: for missions crossing multiple regions) CREATE TABLE IF NOT EXISTS regions ( id bigserial PRIMARY KEY, @@ -271,10 +277,18 @@ CREATE INDEX IF NOT EXISTS ix_rwrt_fruit_ts ON ripeness_weekly_rollups_ts(fruit_ CREATE INDEX IF NOT EXISTS ix_rwrt_device ON ripeness_weekly_rollups_ts(device_id); CREATE INDEX IF NOT EXISTS ix_rwrt_run ON ripeness_weekly_rollups_ts(run_id); +-- Sensor event logs table. +CREATE TABLE IF NOT EXISTS devices_sensor ( + id TEXT UNIQUE NOT NULL, + plant_id INT, + sensor_type TEXT, + last_seen TIMESTAMPTZ NOT NULL DEFAULT now(), + PRIMARY KEY (id) +); -- Sensor event logs table. CREATE TABLE IF NOT EXISTS event_logs_sensors( id bigserial PRIMARY KEY, - device_id text NOT NULL REFERENCES devices(device_id), + device_id TEXT NOT NULL REFERENCES devices_sensor(id), issue_type text NOT NULL, severity text NOT NULL CHECK (severity IN ('info','warn','error','critical')), start_ts timestamptz NOT NULL DEFAULT now(), @@ -286,20 +300,9 @@ CREATE TABLE IF NOT EXISTS event_logs_sensors( -CREATE TABLE IF NOT EXISTS sensors ( - id SERIAL PRIMARY KEY, - sensor_name TEXT UNIQUE NOT NULL, - sensor_type TEXT NOT NULL, - owner_name TEXT, - location_lat DOUBLE PRECISION, - location_lon DOUBLE PRECISION, - install_date TIMESTAMP DEFAULT NOW(), - status TEXT DEFAULT 'active', - description TEXT, - last_maintenance TIMESTAMP -); CREATE TABLE IF NOT EXISTS public.sensor_anomalies ( id BIGSERIAL PRIMARY KEY, + idSensor INT NOT NULL, plant_id INT NOT NULL, sensor VARCHAR(64) NOT NULL, ts TIMESTAMPTZ NOT NULL, @@ -328,11 +331,32 @@ CREATE TABLE IF NOT EXISTS public.sensor_zone_stats ( inserted_at TIMESTAMPTZ NOT NULL DEFAULT now() ); + + +--- Alerts_leaves table + +CREATE TABLE IF NOT EXISTS public.alerts_leaves ( + id bigserial PRIMARY KEY, + entity_id text NOT NULL, + rule text NOT NULL, + window_start timestamptz NOT NULL, + window_end timestamptz NOT NULL, + score double precision NOT NULL, + first_seen timestamptz NOT NULL, + last_seen timestamptz NOT NULL, + status text NOT NULL CHECK (status IN ('OPEN','ACK','RESOLVED')), + meta_json jsonb +); + +CREATE INDEX IF NOT EXISTS ix_alerts_leaves_entity_rule ON public.alerts_leaves(entity_id, rule); +CREATE INDEX IF NOT EXISTS ix_alerts_leaves_status ON public.alerts_leaves(status); + + --- === Soil moisture irrigation tables === CREATE TABLE IF NOT EXISTS soil_moisture_events ( id SERIAL PRIMARY KEY, - zone_id TEXT NOT NULL, + device_id TEXT NOT NULL REFERENCES devices(device_id), ts TIMESTAMPTZ NOT NULL DEFAULT NOW(), dry_ratio REAL NOT NULL, decision TEXT NOT NULL, @@ -345,7 +369,8 @@ CREATE TABLE IF NOT EXISTS soil_moisture_events ( CREATE UNIQUE INDEX IF NOT EXISTS idx_events_idem ON soil_moisture_events (idempotency_key); CREATE TABLE IF NOT EXISTS irrigation_schedule ( - zone_id TEXT PRIMARY KEY, + device_id TEXT PRIMARY KEY REFERENCES devices(device_id), + next_run_at TIMESTAMPTZ NOT NULL, duration_min INT NOT NULL, updated_by TEXT NOT NULL, @@ -355,7 +380,7 @@ CREATE TABLE IF NOT EXISTS irrigation_schedule ( CREATE TABLE IF NOT EXISTS irrigation_schedule_audit ( id SERIAL PRIMARY KEY, - zone_id TEXT NOT NULL, + device_id TEXT NOT NULL, prev_next_run_at TIMESTAMPTZ, prev_duration_min INT, next_run_at TIMESTAMPTZ NOT NULL, @@ -365,6 +390,21 @@ CREATE TABLE IF NOT EXISTS irrigation_schedule_audit ( updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW() ); +CREATE TABLE irrigation_policies ( + device_id TEXT NOT NULL, + prev_state TEXT, + dry_ratio_high REAL, + dry_ratio_low REAL, + min_patches INT, + duration_min INT, + updated_at TIMESTAMP DEFAULT NOW(), + PRIMARY KEY (device_id), + CONSTRAINT fk_device + FOREIGN KEY (device_id) REFERENCES devices(device_id) + ON DELETE CASCADE +); + + CREATE TABLE IF NOT EXISTS alerts ( -- Required fields @@ -519,7 +559,25 @@ CREATE INDEX IF NOT EXISTS idx_aerial_metadata_timestamp CREATE INDEX IF NOT EXISTS idx_aerial_metadata_gis ON public.aerial_images_complete_metadata USING GIST (gis); + +CREATE TABLE fruit_detections ( + id UUID PRIMARY KEY DEFAULT gen_random_uuid(), + original_key TEXT NOT NULL, + cropped_key TEXT NOT NULL, + bucket TEXT NOT NULL, + device_id TEXT NOT NULL, + timestamp TIMESTAMPTZ NOT NULL, + x1 INT NOT NULL, + y1 INT NOT NULL, + x2 INT NOT NULL, + y2 INT NOT NULL, + latency_ms_model INT, + label TEXT, + created_at TIMESTAMPTZ DEFAULT now() +); +CREATE INDEX idx_fruit_original_key ON fruit_detections(original_key); +CREATE INDEX idx_fruit_device_ts ON fruit_detections(device_id, timestamp); CREATE TABLE IF NOT EXISTS public.field_polygons ( id SERIAL PRIMARY KEY, @@ -572,28 +630,97 @@ CREATE TABLE public.sound_new_plants_connections ( CREATE INDEX IF NOT EXISTS ix_task_thresholds_task ON task_thresholds (task); CREATE INDEX IF NOT EXISTS ix_task_thresholds_updated_at ON task_thresholds (updated_at); --- === Indexes for performance optimization === - - -CREATE INDEX IF NOT EXISTS ix_sensor_anomalies_ts_brin - ON public.sensor_anomalies USING BRIN (ts); - -CREATE INDEX IF NOT EXISTS ix_sensor_anomalies_zone - ON public.sensor_anomalies (zone); - -CREATE INDEX IF NOT EXISTS ix_sensor_anomalies_sensor - ON public.sensor_anomalies (sensor); +CREATE TABLE IF NOT EXISTS public.sounds_metadata ( + id BIGSERIAL PRIMARY KEY, + file_name TEXT NOT NULL, + device_id TEXT NOT NULL REFERENCES public.devices(device_id), + capture_time TIMESTAMPTZ NOT NULL, + duration_sec DOUBLE PRECISION CHECK (duration_sec >= 0), + done BOOLEAN NOT NULL DEFAULT FALSE, + sample_rate_hz INTEGER CHECK (sample_rate_hz > 0), + channels SMALLINT CHECK (channels > 0), + content_type TEXT, + + gis_origin JSONB NOT NULL, + + geom_point geometry(Point, 4326) + GENERATED ALWAYS AS ( + ST_SetSRID( + ST_MakePoint( + (gis_origin->>'longitude')::double precision, + (gis_origin->>'latitude')::double precision + ), + 4326 + ) + ) STORED, + + created_at TIMESTAMPTZ NOT NULL DEFAULT now(), + CONSTRAINT ux_sounds_dev_time UNIQUE (device_id, capture_time) +); + +CREATE INDEX IF NOT EXISTS ix_sounds_meta_ts_brin + ON public.sounds_metadata USING BRIN (capture_time); +CREATE INDEX IF NOT EXISTS ix_sounds_meta_device_time + ON public.sounds_metadata (device_id, capture_time); +CREATE INDEX IF NOT EXISTS ix_sounds_meta_geom_point_gist + ON public.sounds_metadata USING GIST (geom_point); +CREATE INDEX IF NOT EXISTS ix_sounds_meta_file_name + ON public.sounds_metadata (file_name); +CREATE INDEX IF NOT EXISTS ix_sounds_meta_created_brin + ON public.sounds_metadata USING BRIN (created_at); + + +CREATE TABLE IF NOT EXISTS public.sounds_ultra_metadata ( + id BIGSERIAL PRIMARY KEY, + file_name TEXT NOT NULL, + device_id TEXT NOT NULL REFERENCES public.devices(device_id), + capture_time TIMESTAMPTZ NOT NULL, + duration_sec DOUBLE PRECISION CHECK (duration_sec >= 0), + done BOOLEAN NOT NULL DEFAULT FALSE, + sample_rate_hz INTEGER CHECK (sample_rate_hz > 0), + channels SMALLINT CHECK (channels > 0), + content_type TEXT, + + gis_origin JSONB NOT NULL, + + geom_point geometry(Point, 4326) + GENERATED ALWAYS AS ( + ST_SetSRID( + ST_MakePoint( + (gis_origin->>'longitude')::double precision, + (gis_origin->>'latitude')::double precision + ), + 4326 + ) + ) STORED, + + created_at TIMESTAMPTZ NOT NULL DEFAULT now(), + CONSTRAINT ux_ultra_sounds_dev_time UNIQUE (device_id, capture_time) +); + + +CREATE INDEX IF NOT EXISTS ix_ultra_sounds_meta_ts_brin + ON public.sounds_ultra_metadata USING BRIN (capture_time); +CREATE INDEX IF NOT EXISTS ix_ultra_sounds_meta_device_time + ON public.sounds_ultra_metadata (device_id, capture_time); +CREATE INDEX IF NOT EXISTS ix_ultra_sounds_meta_geom_point_gist + ON public.sounds_ultra_metadata USING GIST (geom_point); +CREATE INDEX IF NOT EXISTS ix_ultra_sounds_meta_file_name + ON public.sounds_ultra_metadata (file_name); +CREATE INDEX IF NOT EXISTS ix_ultra_sounds_meta_created_brin + ON public.sounds_ultra_metadata USING BRIN (created_at); + + +CREATE TABLE public.image_new_securixxxxxxxxctions ( + id BIGSERIAL PRIMARY KEY, + file_name VARCHAR(255), + key TEXT, + linked_time TIMESTAMPTZ +); -CREATE INDEX IF NOT EXISTS ix_sensor_zone_stats_zone_window - ON public.sensor_zone_stats (zone, window_start, window_end); -CREATE INDEX IF NOT EXISTS ix_sensor_zone_stats_anomalies - ON public.sensor_zone_stats (anomalies); -CREATE INDEX IF NOT EXISTS ix_sensors_name ON sensors (sensor_name); -CREATE INDEX IF NOT EXISTS ix_sensors_type ON sensors (sensor_type); -CREATE INDEX IF NOT EXISTS ix_sensors_status ON sensors (status); -CREATE INDEX IF NOT EXISTS ix_sensors_location ON sensors (location_lat, location_lon); +-- === Indexes for performance optimization === -- Spatial CREATE INDEX IF NOT EXISTS ix_missions_area_geom_gist ON missions USING GIST (area_geom); @@ -638,101 +765,14 @@ CREATE INDEX IF NOT EXISTS ix_event_logs_sensors_details_gin ON event_logs_sens -/* =========================== - ADDED: Incidents schema v1 - =========================== */ - --- ========================= --- Incidents: one event row --- ========================= --- anomaly_type_id int REFERENCES anomaly_types(anomaly_type_id) ON DELETE SET NULL, -CREATE TABLE IF NOT EXISTS incidents ( -- [ADDED] - incident_id uuid PRIMARY KEY, -- [ADDED] - mission_id bigint REFERENCES missions(mission_id) ON DELETE SET NULL, -- [ADDED] - device_id text REFERENCES devices(device_id) ON DELETE SET NULL, -- [ADDED] - anomaly text, -- [ADDED] - started_at timestamptz NOT NULL, -- [ADDED] - ended_at timestamptz, -- [ADDED] - duration_sec double precision, -- [ADDED] - frame_start int, -- [ADDED] - frame_end int, -- [ADDED] - -- [ADDED] - -- NEW: aggregate severity (mean tracks/frame over the incident) -- [ADDED] - severity real, -- [ADDED] - -- [ADDED] - -- image-space ROI; keep flexible -- [ADDED] - roi_pixels jsonb, -- [ADDED] - -- optional map footprint (camera frustum, area of interest, etc.) -- [ADDED] - footprint geometry(Polygon,4326), -- [ADDED] - -- [ADDED] - -- canonical media for playback (referencing your existing files table) -- [ADDED] - clip_file_id bigint REFERENCES files(file_id) ON DELETE SET NULL, -- [ADDED] - poster_file_id bigint REFERENCES files(file_id) ON DELETE SET NULL, -- [ADDED] - -- [ADDED] - -- optional pre-baked UI timeline (array of {frame,ts,box,conf,url,...}) -- [ADDED] - frames_manifest jsonb, -- [ADDED] - is_real boolean, - ack boolean DEFAULT false, -- [ADDED] - meta jsonb DEFAULT '{}'::jsonb -- [ADDED] -); -- [ADDED] - --- Helpful indexes -- [ADDED] -CREATE INDEX IF NOT EXISTS ix_incidents_device_time ON incidents (device_id, started_at DESC); -- [ADDED] -CREATE INDEX IF NOT EXISTS ix_incidents_mission_time ON incidents (mission_id, started_at DESC); -- [ADDED] - --- ========================================== --- Per-frame timeline: one row per frame --- Store ALL detections (bbox + conf + track_id) in JSONB --- ========================================== -DROP TABLE IF EXISTS incident_frames CASCADE; -- [ADDED] - -CREATE TABLE incident_frames ( -- [ADDED] - incident_id uuid NOT NULL REFERENCES incidents(incident_id) ON DELETE CASCADE, -- [ADDED] - frame_idx int NOT NULL, -- [ADDED] - ts timestamptz NOT NULL, -- [ADDED] - -- [ADDED] - -- List of detection objects: -- [ADDED] - -- [{"x1":int,"y1":int,"x2":int,"y2":int,"conf":float|null,"track_id":int|null}, ...] -- [ADDED] - detections jsonb NOT NULL DEFAULT '[]'::jsonb, -- [ADDED] - -- [ADDED] - cls_name text, -- [ADDED] - cls_id text, -- [ADDED] - -- [ADDED] - -- Annotated (or raw) frame stored in files -- [ADDED] - file_id bigint REFERENCES files(file_id) ON DELETE SET NULL, -- [ADDED] - -- [ADDED] - meta jsonb DEFAULT '{}'::jsonb, -- [ADDED] - PRIMARY KEY (incident_id, frame_idx) -- [ADDED] -); -- [ADDED] - --- Useful indexes -- [ADDED] -CREATE INDEX IF NOT EXISTS ix_incident_frames_ts -- [ADDED] - ON incident_frames (incident_id, ts); -- [ADDED] - --- JSONB GIN index for detection queries (by bbox/conf/track_id) -- [ADDED] -CREATE INDEX IF NOT EXISTS ix_incident_frames_detections_gin -- [ADDED] - ON incident_frames USING GIN (detections jsonb_path_ops); -- [ADDED] - --- (Optional) denormalized count for quick metrics -- [ADDED] -ALTER TABLE incident_frames -- [ADDED] - ADD COLUMN IF NOT EXISTS num_tracks int -- [ADDED] - GENERATED ALWAYS AS (jsonb_array_length(detections)) STORED; -- [ADDED] -- CREATE INDEX IF NOT EXISTS ix_alerts_entity_rule ON public.alerts(entity_id, rule); -- CREATE INDEX IF NOT EXISTS ix_alerts_status ON public.alerts(status); -- ============================================ --- 🔹 MISSING TABLES AND INDEXES FROM FIRST SCHEMA +-- 🔹 SENSORS TABLES (zones, sensors, sensors_anomalies_modal) -- ============================================ --- Devices sensor mapping -CREATE TABLE IF NOT EXISTS devices_sensor ( - id TEXT UNIQUE NOT NULL, - plant_id INT NOT NULL, - sensor_type TEXT NOT NULL, - PRIMARY KEY (plant_id, id) -); - -- Zones table (for linking sensors to geographic areas) CREATE TABLE IF NOT EXISTS public.zones ( id SERIAL PRIMARY KEY, @@ -741,14 +781,14 @@ CREATE TABLE IF NOT EXISTS public.zones ( ); -- Extended sensors table with all environmental metrics -DROP TABLE IF EXISTS public.sensors CASCADE; CREATE TABLE IF NOT EXISTS public.sensors ( - id SERIAL PRIMARY KEY, - sensor_name TEXT UNIQUE NOT NULL, + sensor_id SERIAL PRIMARY KEY, + sid TEXT, + sensor_name TEXT NOT NULL, sensor_type TEXT NOT NULL, owner_name TEXT, - location_lat DOUBLE PRECISION, - location_lon DOUBLE PRECISION, + lat DOUBLE PRECISION, + lon DOUBLE PRECISION, install_date TIMESTAMP DEFAULT NOW(), status TEXT DEFAULT 'active', description TEXT, @@ -782,58 +822,12 @@ CREATE TABLE IF NOT EXISTS public.sensors ( water_usage_efficiency DOUBLE PRECISION ); --- Sensor anomalies table with full structure and JSONB result -DROP TABLE IF EXISTS public.sensor_anomalies CASCADE; -CREATE TABLE IF NOT EXISTS public.sensor_anomalies ( - id BIGSERIAL PRIMARY KEY, - idSensor INT NOT NULL, - plant_id INT NOT NULL, - sensor VARCHAR(64) NOT NULL, - ts TIMESTAMPTZ NOT NULL, - value DOUBLE PRECISION, - lat DOUBLE PRECISION, - lon DOUBLE PRECISION, - zone VARCHAR(128), - result JSONB NOT NULL, - inserted_at TIMESTAMPTZ NOT NULL DEFAULT now() -); - -- Sensors anomalies modal (aggregated anomaly detection model) CREATE TABLE IF NOT EXISTS public.sensors_anomalies_modal ( - id BIGSERIAL PRIMARY KEY, - sensor_id TEXT NOT NULL REFERENCES sensors(sensor_name) ON DELETE CASCADE, - ts TIMESTAMPTZ NOT NULL, - anomaly REAL NOT NULL CHECK (anomaly >= 0), - inserted_at TIMESTAMPTZ NOT NULL DEFAULT now() -); - --- Updated event_logs_sensors referencing devices_sensor -DROP TABLE IF EXISTS event_logs_sensors CASCADE; -CREATE TABLE IF NOT EXISTS event_logs_sensors( - id bigserial PRIMARY KEY, - device_id TEXT NOT NULL REFERENCES devices_sensor(id), - issue_type text NOT NULL, - severity text NOT NULL CHECK (severity IN ('info','warn','error','critical')), - start_ts timestamptz NOT NULL DEFAULT now(), - end_ts timestamptz NULL, - details jsonb NOT NULL DEFAULT '{}'::jsonb, - CONSTRAINT event_logs_sensors_end_after_start - CHECK (end_ts IS NULL OR end_ts >= start_ts) -); - --- Sensor zone statistics (for per-region summaries) -CREATE TABLE IF NOT EXISTS public.sensor_zone_stats ( id BIGSERIAL PRIMARY KEY, - zone VARCHAR(128) NOT NULL, - window_start TIMESTAMPTZ NOT NULL, - window_end TIMESTAMPTZ NOT NULL, - count INT NOT NULL, - mean DOUBLE PRECISION, - median DOUBLE PRECISION, - min DOUBLE PRECISION, - max DOUBLE PRECISION, - std DOUBLE PRECISION, - anomalies INT, + sensor_id INT NOT NULL REFERENCES sensors(sensor_id) ON DELETE CASCADE, + ts TIMESTAMPTZ NOT NULL, + anomaly REAL NOT NULL CHECK (anomaly >= 0), inserted_at TIMESTAMPTZ NOT NULL DEFAULT now() ); @@ -844,22 +838,46 @@ CREATE TABLE IF NOT EXISTS public.sensor_zone_stats ( CREATE INDEX IF NOT EXISTS ix_sensors_anomalies_modal_sensor_ts ON sensors_anomalies_modal (sensor_id, ts); -CREATE INDEX IF NOT EXISTS ix_sensor_anomalies_ts_brin - ON public.sensor_anomalies USING BRIN (ts); - -CREATE INDEX IF NOT EXISTS ix_sensor_anomalies_zone - ON public.sensor_anomalies (zone); - -CREATE INDEX IF NOT EXISTS ix_sensor_anomalies_sensor - ON public.sensor_anomalies (sensor); - -CREATE INDEX IF NOT EXISTS ix_sensor_zone_stats_zone_window - ON public.sensor_zone_stats (zone, window_start, window_end); - -CREATE INDEX IF NOT EXISTS ix_sensor_zone_stats_anomalies - ON public.sensor_zone_stats (anomalies); - CREATE INDEX IF NOT EXISTS ix_sensors_name ON sensors (sensor_name); CREATE INDEX IF NOT EXISTS ix_sensors_type ON sensors (sensor_type); CREATE INDEX IF NOT EXISTS ix_sensors_status ON sensors (status); -CREATE INDEX IF NOT EXISTS ix_sensors_location ON sensors (location_lat, location_lon); +CREATE INDEX IF NOT EXISTS ix_sensors_location ON sensors (lat, lon); +CREATE TABLE IF NOT EXISTS sensor_embeddings ( + id BIGSERIAL PRIMARY KEY, + sensor_id BIGINT NOT NULL, + vec vector(5), + created_at TIMESTAMP DEFAULT NOW() +); +CREATE OR REPLACE FUNCTION generate_sensor_embedding() +RETURNS trigger AS $$ +DECLARE + name_len INT; + type_len INT; + status_score FLOAT; + vec vector(5); +BEGIN + name_len := COALESCE(LENGTH(NEW.sensor_name), 0); + type_len := COALESCE(LENGTH(NEW.sensor_type), 0); + status_score := CASE WHEN LOWER(COALESCE(NEW.status, '')) = 'active' THEN 1 ELSE 0 END; + + vec := ARRAY[ + COALESCE(NEW.lat, 0), + COALESCE(NEW.lon, 0), + name_len, + type_len, + status_score + ]::vector; + + DELETE FROM sensor_embeddings WHERE sensor_id = NEW.sensor_id; + + INSERT INTO sensor_embeddings(sensor_id, vec) + VALUES (NEW.sensor_id, vec); + + RETURN NEW; +END; +$$ LANGUAGE plpgsql; + +CREATE TRIGGER trg_generate_embedding +AFTER INSERT OR UPDATE ON sensors +FOR EACH ROW +EXECUTE FUNCTION generate_sensor_embedding(); diff --git a/RelDB/docker-compose.yml b/RelDB/docker-compose.yml index 8b26401fd..e8ac85ae0 100644 --- a/RelDB/docker-compose.yml +++ b/RelDB/docker-compose.yml @@ -34,6 +34,39 @@ services: - airnet restart: unless-stopped + rover_ingest: + build: + context: .. + dockerfile: services/rover_ingest/Dockerfile + command: ["python","-m","services.rover_ingest.app"] + environment: + MINIO_ENDPOINT: "host.docker.internal:9000" + MINIO_BUCKET: "rover-images" + MINIO_ACCESS_KEY: "minioadmin" + MINIO_SECRET_KEY: "minioadmin" + PG_DSN: "dbname=missions_db user=missions_user host=db port=5432 password=pg123" + + depends_on: + db: + condition: service_healthy + + extra_hosts: + - "host.docker.internal:host-gateway" + + ports: + - "9109:9109" # Prometheus metrics + restart: unless-stopped + networks: + - airnet + + healthcheck: + test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:9109/metrics').read()"] + interval: 10s + timeout: 3s + retries: 3 + start_period: 20s + + postgres_exporter: image: quay.io/prometheuscommunity/postgres-exporter:v0.15.0 environment: diff --git a/RelDB/graphs/postgres-queries.yml b/RelDB/graphs/postgres-queries.yml index b2e34316a..85037af90 100644 --- a/RelDB/graphs/postgres-queries.yml +++ b/RelDB/graphs/postgres-queries.yml @@ -134,3 +134,504 @@ pg_database_size: - size_bytes: usage: GAUGE description: "Database size in bytes" + +# ============================================ +# LEAF DISEASES METRICS +# ============================================ + +# Total leaf reports +leaf_reports_total: + query: "SELECT COUNT(*)::float as total FROM public.leaf_reports" + master: true + metrics: + - total: + usage: "GAUGE" + description: "Total number of leaf disease reports" + +# Reports by disease type +leaf_reports_by_disease: + query: | + SELECT + COALESCE(ldt.name, 'Unknown') as disease_name, + lr.leaf_disease_type_id::text as disease_id, + COUNT(*)::float as count + FROM public.leaf_reports lr + LEFT JOIN public.leaf_disease_types ldt ON lr.leaf_disease_type_id = ldt.id + WHERE lr.sick = true + GROUP BY lr.leaf_disease_type_id, ldt.name + master: true + metrics: + - disease_name: + usage: "LABEL" + description: "Disease name" + - disease_id: + usage: "LABEL" + description: "Disease type ID" + - count: + usage: "GAUGE" + description: "Number of reports per disease" + +# Reports by device +leaf_reports_by_device: + query: | + SELECT + device_id::text as device_id, + COUNT(*)::float as total_reports, + SUM(CASE WHEN sick THEN 1 ELSE 0 END)::float as sick_reports + FROM public.leaf_reports + GROUP BY device_id + master: true + metrics: + - device_id: + usage: "LABEL" + description: "Device ID" + - total_reports: + usage: "GAUGE" + description: "Total reports per device" + - sick_reports: + usage: "GAUGE" + description: "Sick reports per device" + +# Daily disease progression (time series) +leaf_disease_daily_progression: + query: | + SELECT + COALESCE(ldt.name, 'Unknown') as disease_name, + lr.leaf_disease_type_id::text as disease_id, + TO_CHAR(DATE_TRUNC('day', lr.ts), 'YYYY-MM-DD') as report_date, + EXTRACT(EPOCH FROM DATE_TRUNC('day', lr.ts))::float as date_timestamp, + COUNT(*)::float as sick_count + FROM public.leaf_reports lr + LEFT JOIN public.leaf_disease_types ldt ON lr.leaf_disease_type_id = ldt.id + WHERE lr.sick = true + AND lr.ts > NOW() - INTERVAL '365 days' + GROUP BY lr.leaf_disease_type_id, ldt.name, DATE_TRUNC('day', lr.ts) + ORDER BY date_timestamp DESC + master: true + metrics: + - disease_name: + usage: "LABEL" + description: "Disease name" + - disease_id: + usage: "LABEL" + description: "Disease type ID" + - report_date: + usage: "LABEL" + description: "Report date (YYYY-MM-DD)" + - date_timestamp: + usage: "GAUGE" + description: "Date timestamp for X axis" + - sick_count: + usage: "GAUGE" + description: "Number of sick reports per day" + +# Hourly disease detection (last 7 days) +leaf_disease_hourly_detection: + query: | + SELECT + COALESCE(ldt.name, 'Unknown') AS disease_name, + lr.leaf_disease_type_id::text AS disease_id, + MAX(EXTRACT(EPOCH FROM DATE_TRUNC('hour', lr.ts)))::float AS hour_timestamp, + COUNT(*)::float AS count + FROM public.leaf_reports lr + LEFT JOIN public.leaf_disease_types ldt ON lr.leaf_disease_type_id = ldt.id + WHERE lr.sick = true + AND lr.ts > NOW() - INTERVAL '7 days' + GROUP BY lr.leaf_disease_type_id, ldt.name + ORDER BY hour_timestamp DESC + master: true + metrics: + - disease_name: + usage: "LABEL" + description: "Disease name" + - disease_id: + usage: "LABEL" + description: "Disease type ID" + - hour_timestamp: + usage: "GAUGE" + description: "Last detection hour (epoch)" + - count: + usage: "GAUGE" + description: "Detections count in last 7 days" + + +# Disease severity by device (percentage) +leaf_disease_severity_by_device: + query: | + SELECT + COALESCE(ldt.name, 'Unknown') as disease_name, + lr.leaf_disease_type_id::text as disease_id, + lr.device_id::text as device_id, + (SUM(CASE WHEN lr.sick THEN 1 ELSE 0 END)::float / COUNT(*)::float * 100) as sick_percentage + FROM public.leaf_reports lr + LEFT JOIN public.leaf_disease_types ldt ON lr.leaf_disease_type_id = ldt.id + WHERE lr.ts > NOW() - INTERVAL '30 days' + GROUP BY lr.leaf_disease_type_id, ldt.name, lr.device_id + HAVING COUNT(*) > 5 + master: true + metrics: + - disease_name: + usage: "LABEL" + description: "Disease name" + - disease_id: + usage: "LABEL" + description: "Disease type ID" + - device_id: + usage: "LABEL" + description: "Device ID" + - sick_percentage: + usage: "GAUGE" + description: "Percentage of sick reports (0-100)" + + +# ============================================ +# ULTRASONIC PLANT PREDICTIONS METRICS +# S3 Path format: s3://sound/plants/microphone-MIC-02/2025-11-13/1763018877231/MIC-U-01_20251113T073457Z.wav +# ============================================ + +ultrasonic_predictions_total: + query: "SELECT COUNT(*)::float as total FROM public.ultrasonic_plant_predictions" + master: true + metrics: + - total: + usage: "GAUGE" + description: "Total number of ultrasonic predictions" + +ultrasonic_predictions_by_class: + query: | + SELECT + CASE predicted_class + WHEN 'Healthy_Tomato' THEN 'Healthy_Plant' + WHEN 'Healthy_Tobacco' THEN 'Healthy_Plant' + + WHEN 'Drought_Tomato' THEN 'Drought_Plant' + WHEN 'Drought_Tobacco' THEN 'Drought_Plant' + + WHEN 'Pest_Tomato' THEN 'Pest_Plant' + WHEN 'Pest_Tobacco' THEN 'Pest_Plant' + + ELSE COALESCE(predicted_class, 'unknown') + END as predicted_class, + COUNT(*)::float as count + FROM public.ultrasonic_plant_predictions + GROUP BY 1 + master: true + metrics: + - predicted_class: + usage: "LABEL" + description: "Predicted class (Drought_Plant, Healthy_Plant, Pest_Plant, Control, etc.)" + - count: + usage: "GAUGE" + description: "Number of predictions per class" + +ultrasonic_predictions_by_watering: + query: | + SELECT + COALESCE(watering_status, 'unknown') as watering_status, + COUNT(*)::float as count + FROM public.ultrasonic_plant_predictions + GROUP BY watering_status + master: true + metrics: + - watering_status: + usage: "LABEL" + description: "Watering status (Yes, No, etc.)" + - count: + usage: "GAUGE" + description: "Number of predictions per watering status" + +ultrasonic_predictions_by_status: + query: | + SELECT + COALESCE(status, 'unknown') as status, + COUNT(*)::float as count + FROM public.ultrasonic_plant_predictions + GROUP BY status + master: true + metrics: + - status: + usage: "LABEL" + description: "Record status (Success, Error, etc.)" + - count: + usage: "GAUGE" + description: "Number of predictions per status" + +ultrasonic_predictions_avg_confidence: + query: | + SELECT + AVG(confidence)::float as avg_confidence + FROM public.ultrasonic_plant_predictions + WHERE confidence IS NOT NULL + AND TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) > NOW() - INTERVAL '7 days' + master: true + metrics: + - avg_confidence: + usage: "GAUGE" + description: "Average confidence score of predictions (Last 7 days)" + +ultrasonic_predictions_recent: + query: | + SELECT + COUNT(*)::float as recent_count + FROM ( + SELECT 1 + FROM public.ultrasonic_plant_predictions + ORDER BY prediction_time DESC + LIMIT 100 + ) sub + master: true + metrics: + - recent_count: + usage: "GAUGE" + description: "Count of recent predictions (last 100)" + +ultrasonic_confidence_by_sensor: + query: | + SELECT + SUBSTRING(REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') FROM '^(MIC-U-\d+)_') as sensor_id, + AVG(confidence)::float as avg_confidence, + COUNT(*)::float as sample_count, + MIN(confidence)::float as min_confidence, + MAX(confidence)::float as max_confidence + FROM public.ultrasonic_plant_predictions + WHERE status = 'Success' + AND confidence IS NOT NULL + AND file ~ 'MIC-U-\d+_\d{8}T\d{6}Z\.wav$' + GROUP BY SUBSTRING(REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') FROM '^(MIC-U-\d+)_') + ORDER BY avg_confidence DESC + master: true + metrics: + - sensor_id: + usage: "LABEL" + description: "Sensor ID extracted from file (e.g., MIC-U-01, MIC-U-02)" + - avg_confidence: + usage: "GAUGE" + description: "Average confidence level per sensor" + - sample_count: + usage: "GAUGE" + description: "Number of successful samples per sensor" + - min_confidence: + usage: "GAUGE" + description: "Minimum confidence per sensor" + - max_confidence: + usage: "GAUGE" + description: "Maximum confidence per sensor" + +ultrasonic_daily_stress_count: + query: | + SELECT + DATE_TRUNC('hour', + TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) + ) as event_time, + EXTRACT(EPOCH FROM DATE_TRUNC('hour', + TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) + ))::float as date_timestamp, + COUNT(*)::float as event_count + FROM public.ultrasonic_plant_predictions + WHERE predicted_class IN ('Drought_Tomato', 'Pest_Tomato') + AND status = 'Success' + AND TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) >= DATE_TRUNC('day', NOW()) + GROUP BY DATE_TRUNC('hour', + TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) + ) + ORDER BY date_timestamp DESC + master: true + metrics: + - event_time: + usage: "LABEL" + description: "Hour of stress event extracted from file name" + - date_timestamp: + usage: "GAUGE" + description: "Hour timestamp (Unix epoch)" + - event_count: + usage: "GAUGE" + description: "Number of stress events per hour (Today)" + +ultrasonic_success_rate_by_sensor: + query: | + SELECT + SUBSTRING(REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') FROM '^(MIC-U-\d+)_') as sensor_id, + SUM(CASE WHEN status = 'Success' THEN 1.0 ELSE 0.0 END) / + NULLIF(COUNT(*), 0) * 100.0 as success_rate + FROM public.ultrasonic_plant_predictions + WHERE file ~ 'MIC-U-\d+_\d{8}T\d{6}Z\.wav$' + GROUP BY SUBSTRING(REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') FROM '^(MIC-U-\d+)_') + master: true + metrics: + - sensor_id: + usage: "LABEL" + description: "Sensor ID" + - success_rate: + usage: "GAUGE" + description: "Success rate percentage per sensor" + +ultrasonic_class_distribution_healthy: + query: | + SELECT + COUNT(*) as healthy_count, + COUNT(*) * 100.0 / + NULLIF((SELECT COUNT(*) FROM public.ultrasonic_plant_predictions WHERE status = 'Success'), 0) + as healthy_percentage + FROM public.ultrasonic_plant_predictions + WHERE predicted_class IN ('Healthy_Tomato', 'Healthy_Tobacco', 'Control_Greenhouse', 'Control_Empty') AND status = 'Success' + master: true + metrics: + - healthy_count: + usage: "GAUGE" + description: "Count of healthy plant predictions" + - healthy_percentage: + usage: "GAUGE" + description: "Percentage of healthy plant predictions" + +ultrasonic_class_distribution_stress: + query: | + SELECT + COUNT(*) as stress_count, + COUNT(*) * 100.0 / + NULLIF((SELECT COUNT(*) FROM public.ultrasonic_plant_predictions WHERE status = 'Success'), 0) + as stress_percentage + FROM public.ultrasonic_plant_predictions + WHERE predicted_class IN ('Drought_Tomato', 'Pest_Tomato') AND status = 'Success' + master: true + metrics: + - stress_count: + usage: "GAUGE" + description: "Count of stress plant predictions" + - stress_percentage: + usage: "GAUGE" + description: "Percentage of stress plant predictions" + +ultrasonic_confidence_distribution: + query: | + SELECT + CASE + WHEN confidence >= 0.9 THEN '90-100% (High)' + WHEN confidence >= 0.75 THEN '75-90% (Good)' + WHEN confidence >= 0.6 THEN '60-75% (Medium)' + ELSE '< 60% (Low)' + END as confidence_range, + COUNT(*)::float as count + FROM public.ultrasonic_plant_predictions + WHERE status = 'Success' + GROUP BY confidence_range + ORDER BY confidence_range DESC + master: true + metrics: + - confidence_range: + usage: "LABEL" + description: "Confidence level range" + - count: + usage: "GAUGE" + description: "Number of predictions in confidence range" + +ultrasonic_sensor_activity_timeline: + query: | + SELECT + SUBSTRING(REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') FROM '^(MIC-U-\d+)_') as sensor_id, + TO_CHAR(DATE_TRUNC('day', + TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) + ), 'YYYY-MM-DD') as activity_date, + COUNT(*)::float as daily_readings + FROM public.ultrasonic_plant_predictions + WHERE status = 'Success' + AND file ~ 'MIC-U-\d+_\d{8}T\d{6}Z\.wav$' + GROUP BY + SUBSTRING(REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') FROM '^(MIC-U-\d+)_'), + DATE_TRUNC('day', + TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) + ) + ORDER BY activity_date DESC, sensor_id + master: true + metrics: + - sensor_id: + usage: "LABEL" + description: "Sensor ID" + - activity_date: + usage: "LABEL" + description: "Activity date extracted from file name" + - daily_readings: + usage: "GAUGE" + description: "Daily reading count per sensor" + +ultrasonic_predictions_per_hour: + query: | + SELECT + EXTRACT(EPOCH FROM DATE_TRUNC('hour', + TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) + ))::float as hour_timestamp, + COUNT(*)::float as count + FROM public.ultrasonic_plant_predictions + WHERE TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) >= DATE_TRUNC('day', NOW()) + AND file ~ 'MIC-U-\d+_\d{8}T\d{6}Z\.wav$' + GROUP BY DATE_TRUNC('hour', + TO_TIMESTAMP( + SUBSTRING( + REGEXP_REPLACE(file, '^.*/([^/]+)$', '\1') + FROM 'MIC-U-\d+_(\d{8}T\d{6})Z' + ), + 'YYYYMMDD"T"HH24MISS' + ) + ) + ORDER BY hour_timestamp DESC + master: true + metrics: + - hour_timestamp: + usage: "LABEL" + description: "Hour timestamp (Unix epoch) extracted from file name" + - count: + usage: "GAUGE" + description: "Predictions count per hour (Today's Events)" diff --git a/RelDB/graphs/prometheus.yml b/RelDB/graphs/prometheus.yml index 67d79f26c..7ebb44c3c 100644 --- a/RelDB/graphs/prometheus.yml +++ b/RelDB/graphs/prometheus.yml @@ -14,3 +14,8 @@ scrape_configs: - job_name: 'postgres_exporter' static_configs: - targets: ['postgres_exporter:9187'] + + - job_name: 'rover_ingest' + scrape_interval: 10s + static_configs: + - targets: ['rover_ingest:9109'] diff --git a/RelDB/initdb/05_rover_images.sql b/RelDB/initdb/05_rover_images.sql new file mode 100644 index 000000000..93ca57da9 --- /dev/null +++ b/RelDB/initdb/05_rover_images.sql @@ -0,0 +1,39 @@ +-- Schema + table for rover still-image indexing + +CREATE SCHEMA IF NOT EXISTS rover AUTHORIZATION missions_user; + +CREATE TABLE IF NOT EXISTS rover.images ( + image_id text PRIMARY KEY, -- unique image identifier + device_id text NOT NULL, -- rover/camera id + captured_at timestamptz NOT NULL, -- UTC capture time + + lat double precision NOT NULL CHECK (lat >= -90 AND lat <= 90), + lon double precision NOT NULL CHECK (lon >= -180 AND lon <= 180), + + heading_deg double precision, -- [0,360) + pitch_deg double precision, + roll_deg double precision, + alt_m double precision, -- camera height (meters) + fov_deg double precision, + gps_accuracy_m double precision, + temp_c double precision, -- optional ambient temp + + s3_key text NOT NULL, -- object key in MinIO/S3 + mime_type text, + size_bytes bigint, + sha256 text, + exif_present boolean, + firmware text, + capture_seq bigint, + + meta_src text NOT NULL, -- 'manifest' | 'telemetry' | 'exif_fallback' + schema_ver int NOT NULL DEFAULT 1, + source_ts timestamptz, + trace_id text, + + ingested_at timestamptz NOT NULL DEFAULT now() +); + +CREATE INDEX IF NOT EXISTS idx_images_device_time ON rover.images (device_id, captured_at); +CREATE INDEX IF NOT EXISTS idx_images_captured_at ON rover.images (captured_at); +CREATE UNIQUE INDEX IF NOT EXISTS uq_images_sha256 ON rover.images (sha256) WHERE sha256 IS NOT NULL; diff --git a/airflow_bundle/leaf-pipeline/.gitattributes b/airflow_bundle/leaf-pipeline/.gitattributes new file mode 100644 index 000000000..ada57005e --- /dev/null +++ b/airflow_bundle/leaf-pipeline/.gitattributes @@ -0,0 +1,5 @@ +projects/leaf-counting/weights/*.pt filter=lfs diff=lfs merge=lfs -text +projects/leaf-counting/weights/*.pth filter=lfs diff=lfs merge=lfs -text +projects/leaf-counting/weights/*.safetensors filter=lfs diff=lfs merge=lfs -text + +projects/Detection_Jobs/**/models/* filter=lfs diff=lfs merge=lfs -text diff --git a/airflow_bundle/leaf-pipeline/.gitignore b/airflow_bundle/leaf-pipeline/.gitignore new file mode 100644 index 000000000..b5c271165 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/.gitignore @@ -0,0 +1,90 @@ +# === OS / Editors === +.DS_Store +*.swp +*.swo +.idea/ +.vscode/ +*.code-workspace + +# === Python === +__pycache__/ +*.py[cod] +*.pyo +*.pyd +*.egg-info/ +.eggs/ +.build/ +build/ +dist/ +.mypy_cache/ +.pytest_cache/ +.coverage +.coverage.* +.cache/ +.ipynb_checkpoints/ + +# Virtual envs +.venv/ +venv/ +env/ + +# === Docker / Compose === +docker.env +.env +.env.* +.env.local +.envrc + +# === Airflow === +airflow/logs/ +airflow/airflow.db +airflow/airflow.db-journal +airflow/*.pid +airflow/*webserver*.log +airflow/*webserver*.out +airflow/*webserver*.err +airflow/*scheduler*.log +airflow/*scheduler*.out +airflow/*scheduler*.err +airflow/dags/*.bak.* +airflow/staging/ + +# === Projects: leaf-counting === +projects/leaf-counting/out_detect/ +projects/leaf-counting/out_crops/ +projects/leaf-counting/out_pwb/ +projects/leaf-counting/runs_local/ +projects/leaf-counting/weights/ +projects/leaf-counting/.venv/ +projects/leaf-counting/staging/ + +# === Projects: Detection_Jobs / disease-monitor === +projects/Detection_Jobs/**/__pycache__/ +projects/Detection_Jobs/**/.mypy_cache/ +projects/Detection_Jobs/**/.pytest_cache/ +projects/disease-monitor/**/__pycache__/ +projects/disease-monitor/**/.mypy_cache/ +projects/disease-monitor/**/.pytest_cache/ + +# === Secrets / Certs === +*.key +*.pem +*.crt +*.p12 +*credentials*.json +*service_account*.json +*.secrets.* +.secrets/ +secrets/ +projects/Detection_Jobs/.git.backup-*.tar.gz +airflow/dags/leaf-counting/runs_local/ +airflow/dags/leaf-counting/demo_images/ +airflow/dags/leaf-counting/out_*/ +projects/Detection_Jobs/**/models/ +projects/disease-monitor/disease-monitor/alerts.db +projects/**/.git.backup-*.tar.gz +.gitignore.bak* +airflow/dags/leaf-counting/ + + +dags_leaf_counting_backup.tgz \ No newline at end of file diff --git a/airflow_bundle/leaf-pipeline/Dockerfile b/airflow_bundle/leaf-pipeline/Dockerfile new file mode 100644 index 000000000..53af135cf --- /dev/null +++ b/airflow_bundle/leaf-pipeline/Dockerfile @@ -0,0 +1,42 @@ + +FROM mcr.microsoft.com/devcontainers/python:1-3.10-bullseye +# RUN apt-get update && apt-get install -y --no-install-recommends \ +# libgl1 libglib2.0-0 ffmpeg curl ca-certificates && \ +# rm -rf /var/lib/apt/lists/* +# RUN apt-get update && apt-get install -y --no-install-recommends \ +# libgl1 libglib2.0-0 ffmpeg curl ca-certificates \ +# util-linux procps \ +# && rm -rf /var/lib/apt/lists/* + +RUN apt-get update && apt-get install -y --no-install-recommends \ + libgl1 libglib2.0-0 ffmpeg curl ca-certificates \ + util-linux procps \ + && rm -rf /var/lib/apt/lists/* + +RUN python -m pip install --no-cache-dir --upgrade pip wheel setuptools + +ENV AIRFLOW_VERSION=2.9.3 +ENV PYTHON_VERSION=3.10 +ENV CONSTRAINT_URL=https://raw.githubusercontent.com/apache/airflow/constraints-${AIRFLOW_VERSION}/constraints-${PYTHON_VERSION}.txt +RUN pip install --no-cache-dir "apache-airflow==${AIRFLOW_VERSION}" --constraint "${CONSTRAINT_URL}" + +RUN pip install --no-cache-dir \ + "apache-airflow-providers-docker" \ + --constraint "${CONSTRAINT_URL}" + + +# === PyTorch CPU wheels === +RUN pip install --no-cache-dir \ + --extra-index-url https://download.pytorch.org/whl/cpu \ + torch==2.3.1+cpu torchvision==0.18.1+cpu torchaudio==2.3.1+cpu + +# === YOLO=== +RUN pip install --no-cache-dir \ + numpy==1.26.4 opencv-python-headless==4.9.0.80 ultralytics==8.2.10 \ + onnx==1.16.1 onnxruntime==1.18.1 \ + boto3 minio awscli requests tqdm + +#root +RUN useradd -ms /bin/bash airflow +USER airflow +WORKDIR /opt/airflow diff --git a/airflow_bundle/leaf-pipeline/README b/airflow_bundle/leaf-pipeline/README new file mode 100644 index 000000000..2d7d28b57 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/README @@ -0,0 +1,8 @@ +docker compose --profile images up -d --build + + +projects/leaf-counting/weights/ +https://drive.google.com/drive/folders/1RIp71J7kSLdyQ7UtCdS_piiPYG5hvKOD?usp=sharing + +projects/Detection_Jobs/Detection_Jobs/models/ +https://drive.google.com/drive/folders/1u3S8nryoGgjUC_5LKTdc-qvXZmOyJT7X?usp=sharing \ No newline at end of file diff --git a/airflow_bundle/leaf-pipeline/airflow/airflow.cfg b/airflow_bundle/leaf-pipeline/airflow/airflow.cfg new file mode 100644 index 000000000..8f1408c24 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/airflow/airflow.cfg @@ -0,0 +1,2420 @@ +[core] +# The folder where your airflow pipelines live, most likely a +# subfolder in a code repository. This path must be absolute. +# +# Variable: AIRFLOW__CORE__DAGS_FOLDER +# +dags_folder = /opt/airflow/dags + +# Hostname by providing a path to a callable, which will resolve the hostname. +# The format is "package.function". +# +# For example, default value ``airflow.utils.net.getfqdn`` means that result from patched +# version of `socket.getfqdn() `__, +# see related `CPython Issue `__. +# +# No argument should be required in the function specified. +# If using IP address as hostname is preferred, use value ``airflow.utils.net.get_host_ip_address`` +# +# Variable: AIRFLOW__CORE__HOSTNAME_CALLABLE +# +hostname_callable = airflow.utils.net.getfqdn + +# A callable to check if a python file has airflow dags defined or not and should +# return ``True`` if it has dags otherwise ``False``. +# If this is not provided, Airflow uses its own heuristic rules. +# +# The function should have the following signature +# +# .. code-block:: python +# +# def func_name(file_path: str, zip_file: zipfile.ZipFile | None = None) -> bool: ... +# +# Variable: AIRFLOW__CORE__MIGHT_CONTAIN_DAG_CALLABLE +# +might_contain_dag_callable = airflow.utils.file.might_contain_dag_via_default_heuristic + +# Default timezone in case supplied date times are naive +# can be `UTC` (default), `system`, or any `IANA ` +# timezone string (e.g. Europe/Amsterdam) +# +# Variable: AIRFLOW__CORE__DEFAULT_TIMEZONE +# +default_timezone = utc + +# The executor class that airflow should use. Choices include +# ``SequentialExecutor``, ``LocalExecutor``, ``CeleryExecutor``, +# ``KubernetesExecutor``, ``CeleryKubernetesExecutor``, ``LocalKubernetesExecutor`` or the +# full import path to the class when using a custom executor. +# +# Variable: AIRFLOW__CORE__EXECUTOR +# +executor = SequentialExecutor + +# The auth manager class that airflow should use. Full import path to the auth manager class. +# +# Variable: AIRFLOW__CORE__AUTH_MANAGER +# +auth_manager = airflow.providers.fab.auth_manager.fab_auth_manager.FabAuthManager + +# This defines the maximum number of task instances that can run concurrently per scheduler in +# Airflow, regardless of the worker count. Generally this value, multiplied by the number of +# schedulers in your cluster, is the maximum number of task instances with the running +# state in the metadata database. +# +# Variable: AIRFLOW__CORE__PARALLELISM +# +parallelism = 32 + +# The maximum number of task instances allowed to run concurrently in each DAG. To calculate +# the number of tasks that is running concurrently for a DAG, add up the number of running +# tasks for all DAG runs of the DAG. This is configurable at the DAG level with ``max_active_tasks``, +# which is defaulted as ``[core] max_active_tasks_per_dag``. +# +# An example scenario when this would be useful is when you want to stop a new dag with an early +# start date from stealing all the executor slots in a cluster. +# +# Variable: AIRFLOW__CORE__MAX_ACTIVE_TASKS_PER_DAG +# +max_active_tasks_per_dag = 16 + +# Are DAGs paused by default at creation +# +# Variable: AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION +# +dags_are_paused_at_creation = True + +# The maximum number of active DAG runs per DAG. The scheduler will not create more DAG runs +# if it reaches the limit. This is configurable at the DAG level with ``max_active_runs``, +# which is defaulted as ``[core] max_active_runs_per_dag``. +# +# Variable: AIRFLOW__CORE__MAX_ACTIVE_RUNS_PER_DAG +# +max_active_runs_per_dag = 16 + +# (experimental) The maximum number of consecutive DAG failures before DAG is automatically paused. +# This is also configurable per DAG level with ``max_consecutive_failed_dag_runs``, +# which is defaulted as ``[core] max_consecutive_failed_dag_runs_per_dag``. +# If not specified, then the value is considered as 0, +# meaning that the dags are never paused out by default. +# +# Variable: AIRFLOW__CORE__MAX_CONSECUTIVE_FAILED_DAG_RUNS_PER_DAG +# +max_consecutive_failed_dag_runs_per_dag = 0 + +# The name of the method used in order to start Python processes via the multiprocessing module. +# This corresponds directly with the options available in the Python docs: +# `multiprocessing.set_start_method +# `__ +# must be one of the values returned by `multiprocessing.get_all_start_methods() +# `__. +# +# Example: mp_start_method = fork +# +# Variable: AIRFLOW__CORE__MP_START_METHOD +# +# mp_start_method = + +# Whether to load the DAG examples that ship with Airflow. It's good to +# get started, but you probably want to set this to ``False`` in a production +# environment +# +# Variable: AIRFLOW__CORE__LOAD_EXAMPLES +# +load_examples = True + +# Path to the folder containing Airflow plugins +# +# Variable: AIRFLOW__CORE__PLUGINS_FOLDER +# +plugins_folder = /opt/airflow/plugins + +# Should tasks be executed via forking of the parent process +# +# * ``False``: Execute via forking of the parent process +# * ``True``: Spawning a new python process, slower than fork, but means plugin changes picked +# up by tasks straight away +# +# Variable: AIRFLOW__CORE__EXECUTE_TASKS_NEW_PYTHON_INTERPRETER +# +execute_tasks_new_python_interpreter = False + +# Secret key to save connection passwords in the db +# +# Variable: AIRFLOW__CORE__FERNET_KEY +# +fernet_key = + +# Whether to disable pickling dags +# +# Variable: AIRFLOW__CORE__DONOT_PICKLE +# +donot_pickle = True + +# How long before timing out a python file import +# +# Variable: AIRFLOW__CORE__DAGBAG_IMPORT_TIMEOUT +# +dagbag_import_timeout = 30.0 + +# Should a traceback be shown in the UI for dagbag import errors, +# instead of just the exception message +# +# Variable: AIRFLOW__CORE__DAGBAG_IMPORT_ERROR_TRACEBACKS +# +dagbag_import_error_tracebacks = True + +# If tracebacks are shown, how many entries from the traceback should be shown +# +# Variable: AIRFLOW__CORE__DAGBAG_IMPORT_ERROR_TRACEBACK_DEPTH +# +dagbag_import_error_traceback_depth = 2 + +# How long before timing out a DagFileProcessor, which processes a dag file +# +# Variable: AIRFLOW__CORE__DAG_FILE_PROCESSOR_TIMEOUT +# +dag_file_processor_timeout = 50 + +# The class to use for running task instances in a subprocess. +# Choices include StandardTaskRunner, CgroupTaskRunner or the full import path to the class +# when using a custom task runner. +# +# Variable: AIRFLOW__CORE__TASK_RUNNER +# +task_runner = StandardTaskRunner + +# If set, tasks without a ``run_as_user`` argument will be run with this user +# Can be used to de-elevate a sudo user running Airflow when executing tasks +# +# Variable: AIRFLOW__CORE__DEFAULT_IMPERSONATION +# +default_impersonation = + +# What security module to use (for example kerberos) +# +# Variable: AIRFLOW__CORE__SECURITY +# +security = + +# Turn unit test mode on (overwrites many configuration options with test +# values at runtime) +# +# Variable: AIRFLOW__CORE__UNIT_TEST_MODE +# +unit_test_mode = False + +# Whether to enable pickling for xcom (note that this is insecure and allows for +# RCE exploits). +# +# Variable: AIRFLOW__CORE__ENABLE_XCOM_PICKLING +# +enable_xcom_pickling = False + +# What classes can be imported during deserialization. This is a multi line value. +# The individual items will be parsed as a pattern to a glob function. +# Python built-in classes (like dict) are always allowed. +# +# Variable: AIRFLOW__CORE__ALLOWED_DESERIALIZATION_CLASSES +# +allowed_deserialization_classes = airflow.* + +# What classes can be imported during deserialization. This is a multi line value. +# The individual items will be parsed as regexp patterns. +# This is a secondary option to ``[core] allowed_deserialization_classes``. +# +# Variable: AIRFLOW__CORE__ALLOWED_DESERIALIZATION_CLASSES_REGEXP +# +allowed_deserialization_classes_regexp = + +# When a task is killed forcefully, this is the amount of time in seconds that +# it has to cleanup after it is sent a SIGTERM, before it is SIGKILLED +# +# Variable: AIRFLOW__CORE__KILLED_TASK_CLEANUP_TIME +# +killed_task_cleanup_time = 60 + +# Whether to override params with dag_run.conf. If you pass some key-value pairs +# through ``airflow dags backfill -c`` or +# ``airflow dags trigger -c``, the key-value pairs will override the existing ones in params. +# +# Variable: AIRFLOW__CORE__DAG_RUN_CONF_OVERRIDES_PARAMS +# +dag_run_conf_overrides_params = True + +# If enabled, Airflow will only scan files containing both ``DAG`` and ``airflow`` (case-insensitive). +# +# Variable: AIRFLOW__CORE__DAG_DISCOVERY_SAFE_MODE +# +dag_discovery_safe_mode = True + +# The pattern syntax used in the +# `.airflowignore +# `__ +# files in the DAG directories. Valid values are ``regexp`` or ``glob``. +# +# Variable: AIRFLOW__CORE__DAG_IGNORE_FILE_SYNTAX +# +dag_ignore_file_syntax = regexp + +# The number of retries each task is going to have by default. Can be overridden at dag or task level. +# +# Variable: AIRFLOW__CORE__DEFAULT_TASK_RETRIES +# +default_task_retries = 0 + +# The number of seconds each task is going to wait by default between retries. Can be overridden at +# dag or task level. +# +# Variable: AIRFLOW__CORE__DEFAULT_TASK_RETRY_DELAY +# +default_task_retry_delay = 300 + +# The maximum delay (in seconds) each task is going to wait by default between retries. +# This is a global setting and cannot be overridden at task or DAG level. +# +# Variable: AIRFLOW__CORE__MAX_TASK_RETRY_DELAY +# +max_task_retry_delay = 86400 + +# The weighting method used for the effective total priority weight of the task +# +# Variable: AIRFLOW__CORE__DEFAULT_TASK_WEIGHT_RULE +# +default_task_weight_rule = downstream + +# The default task execution_timeout value for the operators. Expected an integer value to +# be passed into timedelta as seconds. If not specified, then the value is considered as None, +# meaning that the operators are never timed out by default. +# +# Variable: AIRFLOW__CORE__DEFAULT_TASK_EXECUTION_TIMEOUT +# +default_task_execution_timeout = + +# Updating serialized DAG can not be faster than a minimum interval to reduce database write rate. +# +# Variable: AIRFLOW__CORE__MIN_SERIALIZED_DAG_UPDATE_INTERVAL +# +min_serialized_dag_update_interval = 30 + +# If ``True``, serialized DAGs are compressed before writing to DB. +# +# .. note:: +# +# This will disable the DAG dependencies view +# +# Variable: AIRFLOW__CORE__COMPRESS_SERIALIZED_DAGS +# +compress_serialized_dags = False + +# Fetching serialized DAG can not be faster than a minimum interval to reduce database +# read rate. This config controls when your DAGs are updated in the Webserver +# +# Variable: AIRFLOW__CORE__MIN_SERIALIZED_DAG_FETCH_INTERVAL +# +min_serialized_dag_fetch_interval = 10 + +# Maximum number of Rendered Task Instance Fields (Template Fields) per task to store +# in the Database. +# All the template_fields for each of Task Instance are stored in the Database. +# Keeping this number small may cause an error when you try to view ``Rendered`` tab in +# TaskInstance view for older tasks. +# +# Variable: AIRFLOW__CORE__MAX_NUM_RENDERED_TI_FIELDS_PER_TASK +# +max_num_rendered_ti_fields_per_task = 30 + +# On each dagrun check against defined SLAs +# +# Variable: AIRFLOW__CORE__CHECK_SLAS +# +check_slas = True + +# Path to custom XCom class that will be used to store and resolve operators results +# +# Example: xcom_backend = path.to.CustomXCom +# +# Variable: AIRFLOW__CORE__XCOM_BACKEND +# +xcom_backend = airflow.models.xcom.BaseXCom + +# By default Airflow plugins are lazily-loaded (only loaded when required). Set it to ``False``, +# if you want to load plugins whenever 'airflow' is invoked via cli or loaded from module. +# +# Variable: AIRFLOW__CORE__LAZY_LOAD_PLUGINS +# +lazy_load_plugins = True + +# By default Airflow providers are lazily-discovered (discovery and imports happen only when required). +# Set it to ``False``, if you want to discover providers whenever 'airflow' is invoked via cli or +# loaded from module. +# +# Variable: AIRFLOW__CORE__LAZY_DISCOVER_PROVIDERS +# +lazy_discover_providers = True + +# Hide sensitive **Variables** or **Connection extra json keys** from UI +# and task logs when set to ``True`` +# +# .. note:: +# +# Connection passwords are always hidden in logs +# +# Variable: AIRFLOW__CORE__HIDE_SENSITIVE_VAR_CONN_FIELDS +# +hide_sensitive_var_conn_fields = True + +# A comma-separated list of extra sensitive keywords to look for in variables names or connection's +# extra JSON. +# +# Variable: AIRFLOW__CORE__SENSITIVE_VAR_CONN_NAMES +# +sensitive_var_conn_names = + +# Task Slot counts for ``default_pool``. This setting would not have any effect in an existing +# deployment where the ``default_pool`` is already created. For existing deployments, users can +# change the number of slots using Webserver, API or the CLI +# +# Variable: AIRFLOW__CORE__DEFAULT_POOL_TASK_SLOT_COUNT +# +default_pool_task_slot_count = 128 + +# The maximum list/dict length an XCom can push to trigger task mapping. If the pushed list/dict has a +# length exceeding this value, the task pushing the XCom will be failed automatically to prevent the +# mapped tasks from clogging the scheduler. +# +# Variable: AIRFLOW__CORE__MAX_MAP_LENGTH +# +max_map_length = 1024 + +# The default umask to use for process when run in daemon mode (scheduler, worker, etc.) +# +# This controls the file-creation mode mask which determines the initial value of file permission bits +# for newly created files. +# +# This value is treated as an octal-integer. +# +# Variable: AIRFLOW__CORE__DAEMON_UMASK +# +daemon_umask = 0o077 + +# Class to use as dataset manager. +# +# Example: dataset_manager_class = airflow.datasets.manager.DatasetManager +# +# Variable: AIRFLOW__CORE__DATASET_MANAGER_CLASS +# +# dataset_manager_class = + +# Kwargs to supply to dataset manager. +# +# Example: dataset_manager_kwargs = {"some_param": "some_value"} +# +# Variable: AIRFLOW__CORE__DATASET_MANAGER_KWARGS +# +# dataset_manager_kwargs = + +# Dataset URI validation should raise an exception if it is not compliant with AIP-60. +# By default this configuration is false, meaning that Airflow 2.x only warns the user. +# In Airflow 3, this configuration will be enabled by default. +# +# Variable: AIRFLOW__CORE__STRICT_DATASET_URI_VALIDATION +# +strict_dataset_uri_validation = False + +# (experimental) Whether components should use Airflow Internal API for DB connectivity. +# +# Variable: AIRFLOW__CORE__DATABASE_ACCESS_ISOLATION +# +database_access_isolation = False + +# (experimental) Airflow Internal API url. +# Only used if ``[core] database_access_isolation`` is ``True``. +# +# Example: internal_api_url = http://localhost:8080 +# +# Variable: AIRFLOW__CORE__INTERNAL_API_URL +# +# internal_api_url = + +# The ability to allow testing connections across Airflow UI, API and CLI. +# Supported options: ``Disabled``, ``Enabled``, ``Hidden``. Default: Disabled +# Disabled - Disables the test connection functionality and disables the Test Connection button in UI. +# Enabled - Enables the test connection functionality and shows the Test Connection button in UI. +# Hidden - Disables the test connection functionality and hides the Test Connection button in UI. +# Before setting this to Enabled, make sure that you review the users who are able to add/edit +# connections and ensure they are trusted. Connection testing can be done maliciously leading to +# undesired and insecure outcomes. +# See `Airflow Security Model: Capabilities of authenticated UI users +# `__ +# for more details. +# +# Variable: AIRFLOW__CORE__TEST_CONNECTION +# +test_connection = Disabled + +# The maximum length of the rendered template field. If the value to be stored in the +# rendered template field exceeds this size, it's redacted. +# +# Variable: AIRFLOW__CORE__MAX_TEMPLATED_FIELD_LENGTH +# +max_templated_field_length = 4096 + +[database] +# Path to the ``alembic.ini`` file. You can either provide the file path relative +# to the Airflow home directory or the absolute path if it is located elsewhere. +# +# Variable: AIRFLOW__DATABASE__ALEMBIC_INI_FILE_PATH +# +alembic_ini_file_path = alembic.ini + +# The SQLAlchemy connection string to the metadata database. +# SQLAlchemy supports many different database engines. +# See: `Set up a Database Backend: Database URI +# `__ +# for more details. +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_CONN +# +sql_alchemy_conn = sqlite:////opt/airflow/airflow.db + +# Extra engine specific keyword args passed to SQLAlchemy's create_engine, as a JSON-encoded value +# +# Example: sql_alchemy_engine_args = {"arg1": true} +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_ENGINE_ARGS +# +# sql_alchemy_engine_args = + +# The encoding for the databases +# +# Variable: AIRFLOW__DATABASE__SQL_ENGINE_ENCODING +# +sql_engine_encoding = utf-8 + +# Collation for ``dag_id``, ``task_id``, ``key``, ``external_executor_id`` columns +# in case they have different encoding. +# By default this collation is the same as the database collation, however for ``mysql`` and ``mariadb`` +# the default is ``utf8mb3_bin`` so that the index sizes of our index keys will not exceed +# the maximum size of allowed index when collation is set to ``utf8mb4`` variant, see +# `GitHub Issue Comment `__ +# for more details. +# +# Variable: AIRFLOW__DATABASE__SQL_ENGINE_COLLATION_FOR_IDS +# +# sql_engine_collation_for_ids = + +# If SQLAlchemy should pool database connections. +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_POOL_ENABLED +# +sql_alchemy_pool_enabled = True + +# The SQLAlchemy pool size is the maximum number of database connections +# in the pool. 0 indicates no limit. +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_POOL_SIZE +# +sql_alchemy_pool_size = 5 + +# The maximum overflow size of the pool. +# When the number of checked-out connections reaches the size set in pool_size, +# additional connections will be returned up to this limit. +# When those additional connections are returned to the pool, they are disconnected and discarded. +# It follows then that the total number of simultaneous connections the pool will allow +# is **pool_size** + **max_overflow**, +# and the total number of "sleeping" connections the pool will allow is pool_size. +# max_overflow can be set to ``-1`` to indicate no overflow limit; +# no limit will be placed on the total number of concurrent connections. Defaults to ``10``. +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_MAX_OVERFLOW +# +sql_alchemy_max_overflow = 10 + +# The SQLAlchemy pool recycle is the number of seconds a connection +# can be idle in the pool before it is invalidated. This config does +# not apply to sqlite. If the number of DB connections is ever exceeded, +# a lower config value will allow the system to recover faster. +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_POOL_RECYCLE +# +sql_alchemy_pool_recycle = 1800 + +# Check connection at the start of each connection pool checkout. +# Typically, this is a simple statement like "SELECT 1". +# See `SQLAlchemy Pooling: Disconnect Handling - Pessimistic +# `__ +# for more details. +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_POOL_PRE_PING +# +sql_alchemy_pool_pre_ping = True + +# The schema to use for the metadata database. +# SQLAlchemy supports databases with the concept of multiple schemas. +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_SCHEMA +# +sql_alchemy_schema = + +# Import path for connect args in SQLAlchemy. Defaults to an empty dict. +# This is useful when you want to configure db engine args that SQLAlchemy won't parse +# in connection string. This can be set by passing a dictionary containing the create engine parameters. +# For more details about passing create engine parameters (keepalives variables, timeout etc) +# in Postgres DB Backend see `Setting up a PostgreSQL Database +# `__ +# e.g ``connect_args={"timeout":30}`` can be defined in ``airflow_local_settings.py`` and +# can be imported as shown below +# +# Example: sql_alchemy_connect_args = airflow_local_settings.connect_args +# +# Variable: AIRFLOW__DATABASE__SQL_ALCHEMY_CONNECT_ARGS +# +# sql_alchemy_connect_args = + +# Whether to load the default connections that ship with Airflow when ``airflow db init`` is called. +# It's good to get started, but you probably want to set this to ``False`` in a production environment. +# +# Variable: AIRFLOW__DATABASE__LOAD_DEFAULT_CONNECTIONS +# +load_default_connections = True + +# Number of times the code should be retried in case of DB Operational Errors. +# Not all transactions will be retried as it can cause undesired state. +# Currently it is only used in ``DagFileProcessor.process_file`` to retry ``dagbag.sync_to_db``. +# +# Variable: AIRFLOW__DATABASE__MAX_DB_RETRIES +# +max_db_retries = 3 + +# Whether to run alembic migrations during Airflow start up. Sometimes this operation can be expensive, +# and the users can assert the correct version through other means (e.g. through a Helm chart). +# Accepts ``True`` or ``False``. +# +# Variable: AIRFLOW__DATABASE__CHECK_MIGRATIONS +# +check_migrations = True + +[logging] +# The folder where airflow should store its log files. +# This path must be absolute. +# There are a few existing configurations that assume this is set to the default. +# If you choose to override this you may need to update the +# ``[logging] dag_processor_manager_log_location`` and +# ``[logging] child_process_log_directory settings`` as well. +# +# Variable: AIRFLOW__LOGGING__BASE_LOG_FOLDER +# +base_log_folder = /opt/airflow/logs +processor_log_folder = /opt/airflow/logs/scheduler + +# Airflow can store logs remotely in AWS S3, Google Cloud Storage or Elastic Search. +# Set this to ``True`` if you want to enable remote logging. +# +# Variable: AIRFLOW__LOGGING__REMOTE_LOGGING +# +remote_logging = False + +# Users must supply an Airflow connection id that provides access to the storage +# location. Depending on your remote logging service, this may only be used for +# reading logs, not writing them. +# +# Variable: AIRFLOW__LOGGING__REMOTE_LOG_CONN_ID +# +remote_log_conn_id = + +# Whether the local log files for GCS, S3, WASB and OSS remote logging should be deleted after +# they are uploaded to the remote location. +# +# Variable: AIRFLOW__LOGGING__DELETE_LOCAL_LOGS +# +delete_local_logs = False + +# Path to Google Credential JSON file. If omitted, authorization based on `the Application Default +# Credentials +# `__ will +# be used. +# +# Variable: AIRFLOW__LOGGING__GOOGLE_KEY_PATH +# +google_key_path = + +# Storage bucket URL for remote logging +# S3 buckets should start with **s3://** +# Cloudwatch log groups should start with **cloudwatch://** +# GCS buckets should start with **gs://** +# WASB buckets should start with **wasb** just to help Airflow select correct handler +# Stackdriver logs should start with **stackdriver://** +# +# Variable: AIRFLOW__LOGGING__REMOTE_BASE_LOG_FOLDER +# +remote_base_log_folder = + +# The remote_task_handler_kwargs param is loaded into a dictionary and passed to the ``__init__`` +# of remote task handler and it overrides the values provided by Airflow config. For example if you set +# ``delete_local_logs=False`` and you provide ``{"delete_local_copy": true}``, then the local +# log files will be deleted after they are uploaded to remote location. +# +# Example: remote_task_handler_kwargs = {"delete_local_copy": true} +# +# Variable: AIRFLOW__LOGGING__REMOTE_TASK_HANDLER_KWARGS +# +remote_task_handler_kwargs = + +# Use server-side encryption for logs stored in S3 +# +# Variable: AIRFLOW__LOGGING__ENCRYPT_S3_LOGS +# +encrypt_s3_logs = False + +# Logging level. +# +# Supported values: ``CRITICAL``, ``ERROR``, ``WARNING``, ``INFO``, ``DEBUG``. +# +# Variable: AIRFLOW__LOGGING__LOGGING_LEVEL +# +logging_level = INFO + +# Logging level for celery. If not set, it uses the value of logging_level +# +# Supported values: ``CRITICAL``, ``ERROR``, ``WARNING``, ``INFO``, ``DEBUG``. +# +# Variable: AIRFLOW__LOGGING__CELERY_LOGGING_LEVEL +# +celery_logging_level = + +# Logging level for Flask-appbuilder UI. +# +# Supported values: ``CRITICAL``, ``ERROR``, ``WARNING``, ``INFO``, ``DEBUG``. +# +# Variable: AIRFLOW__LOGGING__FAB_LOGGING_LEVEL +# +fab_logging_level = WARNING + +# Logging class +# Specify the class that will specify the logging configuration +# This class has to be on the python classpath +# +# Example: logging_config_class = my.path.default_local_settings.LOGGING_CONFIG +# +# Variable: AIRFLOW__LOGGING__LOGGING_CONFIG_CLASS +# +logging_config_class = + +# Flag to enable/disable Colored logs in Console +# Colour the logs when the controlling terminal is a TTY. +# +# Variable: AIRFLOW__LOGGING__COLORED_CONSOLE_LOG +# +colored_console_log = True + +# Log format for when Colored logs is enabled +# +# Variable: AIRFLOW__LOGGING__COLORED_LOG_FORMAT +# +colored_log_format = [%%(blue)s%%(asctime)s%%(reset)s] {%%(blue)s%%(filename)s:%%(reset)s%%(lineno)d} %%(log_color)s%%(levelname)s%%(reset)s - %%(log_color)s%%(message)s%%(reset)s + +# Specifies the class utilized by Airflow to implement colored logging +# +# Variable: AIRFLOW__LOGGING__COLORED_FORMATTER_CLASS +# +colored_formatter_class = airflow.utils.log.colored_log.CustomTTYColoredFormatter + +# Format of Log line +# +# Variable: AIRFLOW__LOGGING__LOG_FORMAT +# +log_format = [%%(asctime)s] {%%(filename)s:%%(lineno)d} %%(levelname)s - %%(message)s + +# Defines the format of log messages for simple logging configuration +# +# Variable: AIRFLOW__LOGGING__SIMPLE_LOG_FORMAT +# +simple_log_format = %%(asctime)s %%(levelname)s - %%(message)s + +# Where to send dag parser logs. If "file", logs are sent to log files defined by child_process_log_directory. +# +# Variable: AIRFLOW__LOGGING__DAG_PROCESSOR_LOG_TARGET +# +dag_processor_log_target = file + +# Format of Dag Processor Log line +# +# Variable: AIRFLOW__LOGGING__DAG_PROCESSOR_LOG_FORMAT +# +dag_processor_log_format = [%%(asctime)s] [SOURCE:DAG_PROCESSOR] {%%(filename)s:%%(lineno)d} %%(levelname)s - %%(message)s + +# Determines the formatter class used by Airflow for structuring its log messages +# The default formatter class is timezone-aware, which means that timestamps attached to log entries +# will be adjusted to reflect the local timezone of the Airflow instance +# +# Variable: AIRFLOW__LOGGING__LOG_FORMATTER_CLASS +# +log_formatter_class = airflow.utils.log.timezone_aware.TimezoneAware + +# An import path to a function to add adaptations of each secret added with +# ``airflow.utils.log.secrets_masker.mask_secret`` to be masked in log messages. The given function +# is expected to require a single parameter: the secret to be adapted. It may return a +# single adaptation of the secret or an iterable of adaptations to each be masked as secrets. +# The original secret will be masked as well as any adaptations returned. +# +# Example: secret_mask_adapter = urllib.parse.quote +# +# Variable: AIRFLOW__LOGGING__SECRET_MASK_ADAPTER +# +secret_mask_adapter = + +# Specify prefix pattern like mentioned below with stream handler ``TaskHandlerWithCustomFormatter`` +# +# Example: task_log_prefix_template = {{ti.dag_id}}-{{ti.task_id}}-{{execution_date}}-{{ti.try_number}} +# +# Variable: AIRFLOW__LOGGING__TASK_LOG_PREFIX_TEMPLATE +# +task_log_prefix_template = + +# Formatting for how airflow generates file names/paths for each task run. +# +# Variable: AIRFLOW__LOGGING__LOG_FILENAME_TEMPLATE +# +log_filename_template = dag_id={{ ti.dag_id }}/run_id={{ ti.run_id }}/task_id={{ ti.task_id }}/{%% if ti.map_index >= 0 %%}map_index={{ ti.map_index }}/{%% endif %%}attempt={{ try_number }}.log + +# Formatting for how airflow generates file names for log +# +# Variable: AIRFLOW__LOGGING__LOG_PROCESSOR_FILENAME_TEMPLATE +# +log_processor_filename_template = {{ filename }}.log + +# Full path of dag_processor_manager logfile. +# +# Variable: AIRFLOW__LOGGING__DAG_PROCESSOR_MANAGER_LOG_LOCATION +# +dag_processor_manager_log_location = /opt/airflow/logs/dag_processor_manager/dag_processor_manager.log + +# Whether DAG processor manager will write logs to stdout +# +# Variable: AIRFLOW__LOGGING__DAG_PROCESSOR_MANAGER_LOG_STDOUT +# +dag_processor_manager_log_stdout = False + +# Name of handler to read task instance logs. +# Defaults to use ``task`` handler. +# +# Variable: AIRFLOW__LOGGING__TASK_LOG_READER +# +task_log_reader = task + +# A comma\-separated list of third-party logger names that will be configured to print messages to +# consoles\. +# +# Example: extra_logger_names = connexion,sqlalchemy +# +# Variable: AIRFLOW__LOGGING__EXTRA_LOGGER_NAMES +# +extra_logger_names = + +# When you start an Airflow worker, Airflow starts a tiny web server +# subprocess to serve the workers local log files to the airflow main +# web server, who then builds pages and sends them to users. This defines +# the port on which the logs are served. It needs to be unused, and open +# visible from the main web server to connect into the workers. +# +# Variable: AIRFLOW__LOGGING__WORKER_LOG_SERVER_PORT +# +worker_log_server_port = 8793 + +# Port to serve logs from for triggerer. +# See ``[logging] worker_log_server_port`` description for more info. +# +# Variable: AIRFLOW__LOGGING__TRIGGER_LOG_SERVER_PORT +# +trigger_log_server_port = 8794 + +# We must parse timestamps to interleave logs between trigger and task. To do so, +# we need to parse timestamps in log files. In case your log format is non-standard, +# you may provide import path to callable which takes a string log line and returns +# the timestamp (datetime.datetime compatible). +# +# Example: interleave_timestamp_parser = path.to.my_func +# +# Variable: AIRFLOW__LOGGING__INTERLEAVE_TIMESTAMP_PARSER +# +# interleave_timestamp_parser = + +# Permissions in the form or of octal string as understood by chmod. The permissions are important +# when you use impersonation, when logs are written by a different user than airflow. The most secure +# way of configuring it in this case is to add both users to the same group and make it the default +# group of both users. Group-writeable logs are default in airflow, but you might decide that you are +# OK with having the logs other-writeable, in which case you should set it to ``0o777``. You might +# decide to add more security if you do not use impersonation and change it to ``0o755`` to make it +# only owner-writeable. You can also make it just readable only for owner by changing it to ``0o700`` +# if all the access (read/write) for your logs happens from the same user. +# +# Example: file_task_handler_new_folder_permissions = 0o775 +# +# Variable: AIRFLOW__LOGGING__FILE_TASK_HANDLER_NEW_FOLDER_PERMISSIONS +# +file_task_handler_new_folder_permissions = 0o775 + +# Permissions in the form or of octal string as understood by chmod. The permissions are important +# when you use impersonation, when logs are written by a different user than airflow. The most secure +# way of configuring it in this case is to add both users to the same group and make it the default +# group of both users. Group-writeable logs are default in airflow, but you might decide that you are +# OK with having the logs other-writeable, in which case you should set it to ``0o666``. You might +# decide to add more security if you do not use impersonation and change it to ``0o644`` to make it +# only owner-writeable. You can also make it just readable only for owner by changing it to ``0o600`` +# if all the access (read/write) for your logs happens from the same user. +# +# Example: file_task_handler_new_file_permissions = 0o664 +# +# Variable: AIRFLOW__LOGGING__FILE_TASK_HANDLER_NEW_FILE_PERMISSIONS +# +file_task_handler_new_file_permissions = 0o664 + +# By default Celery sends all logs into stderr. +# If enabled any previous logging handlers will get *removed*. +# With this option AirFlow will create new handlers +# and send low level logs like INFO and WARNING to stdout, +# while sending higher severity logs to stderr. +# +# Variable: AIRFLOW__LOGGING__CELERY_STDOUT_STDERR_SEPARATION +# +celery_stdout_stderr_separation = False + +# If enabled, Airflow may ship messages to task logs from outside the task run context, e.g. from +# the scheduler, executor, or callback execution context. This can help in circumstances such as +# when there's something blocking the execution of the task and ordinarily there may be no task +# logs at all. +# This is set to ``True`` by default. If you encounter issues with this feature +# (e.g. scheduler performance issues) it can be disabled. +# +# Variable: AIRFLOW__LOGGING__ENABLE_TASK_CONTEXT_LOGGER +# +enable_task_context_logger = True + +[metrics] +# `StatsD `__ integration settings. + +# If true, ``[metrics] metrics_allow_list`` and ``[metrics] metrics_block_list`` will use +# regex pattern matching anywhere within the metric name instead of only prefix matching +# at the start of the name. +# +# Variable: AIRFLOW__METRICS__METRICS_USE_PATTERN_MATCH +# +metrics_use_pattern_match = False + +# Configure an allow list (comma separated string) to send only certain metrics. +# If ``[metrics] metrics_use_pattern_match`` is ``false``, match only the exact metric name prefix. +# If ``[metrics] metrics_use_pattern_match`` is ``true``, provide regex patterns to match. +# +# Example: metrics_allow_list = "scheduler,executor,dagrun,pool,triggerer,celery" or "^scheduler,^executor,heartbeat|timeout" +# +# Variable: AIRFLOW__METRICS__METRICS_ALLOW_LIST +# +metrics_allow_list = + +# Configure a block list (comma separated string) to block certain metrics from being emitted. +# If ``[metrics] metrics_allow_list`` and ``[metrics] metrics_block_list`` are both configured, +# ``[metrics] metrics_block_list`` is ignored. +# +# If ``[metrics] metrics_use_pattern_match`` is ``false``, match only the exact metric name prefix. +# +# If ``[metrics] metrics_use_pattern_match`` is ``true``, provide regex patterns to match. +# +# Example: metrics_block_list = "scheduler,executor,dagrun,pool,triggerer,celery" or "^scheduler,^executor,heartbeat|timeout" +# +# Variable: AIRFLOW__METRICS__METRICS_BLOCK_LIST +# +metrics_block_list = + +# Enables sending metrics to StatsD. +# +# Variable: AIRFLOW__METRICS__STATSD_ON +# +statsd_on = False + +# Specifies the host address where the StatsD daemon (or server) is running +# +# Variable: AIRFLOW__METRICS__STATSD_HOST +# +statsd_host = localhost + +# Specifies the port on which the StatsD daemon (or server) is listening to +# +# Variable: AIRFLOW__METRICS__STATSD_PORT +# +statsd_port = 8125 + +# Defines the namespace for all metrics sent from Airflow to StatsD +# +# Variable: AIRFLOW__METRICS__STATSD_PREFIX +# +statsd_prefix = airflow + +# A function that validate the StatsD stat name, apply changes to the stat name if necessary and return +# the transformed stat name. +# +# The function should have the following signature +# +# .. code-block:: python +# +# def func_name(stat_name: str) -> str: ... +# +# Variable: AIRFLOW__METRICS__STAT_NAME_HANDLER +# +stat_name_handler = + +# To enable datadog integration to send airflow metrics. +# +# Variable: AIRFLOW__METRICS__STATSD_DATADOG_ENABLED +# +statsd_datadog_enabled = False + +# List of datadog tags attached to all metrics(e.g: ``key1:value1,key2:value2``) +# +# Variable: AIRFLOW__METRICS__STATSD_DATADOG_TAGS +# +statsd_datadog_tags = + +# Set to ``False`` to disable metadata tags for some of the emitted metrics +# +# Variable: AIRFLOW__METRICS__STATSD_DATADOG_METRICS_TAGS +# +statsd_datadog_metrics_tags = True + +# If you want to utilise your own custom StatsD client set the relevant +# module path below. +# Note: The module path must exist on your +# `PYTHONPATH ` +# for Airflow to pick it up +# +# Variable: AIRFLOW__METRICS__STATSD_CUSTOM_CLIENT_PATH +# +# statsd_custom_client_path = + +# If you want to avoid sending all the available metrics tags to StatsD, +# you can configure a block list of prefixes (comma separated) to filter out metric tags +# that start with the elements of the list (e.g: ``job_id,run_id``) +# +# Example: statsd_disabled_tags = job_id,run_id,dag_id,task_id +# +# Variable: AIRFLOW__METRICS__STATSD_DISABLED_TAGS +# +statsd_disabled_tags = job_id,run_id + +# To enable sending Airflow metrics with StatsD-Influxdb tagging convention. +# +# Variable: AIRFLOW__METRICS__STATSD_INFLUXDB_ENABLED +# +statsd_influxdb_enabled = False + +# Enables sending metrics to OpenTelemetry. +# +# Variable: AIRFLOW__METRICS__OTEL_ON +# +otel_on = False + +# Specifies the hostname or IP address of the OpenTelemetry Collector to which Airflow sends +# metrics and traces. +# +# Variable: AIRFLOW__METRICS__OTEL_HOST +# +otel_host = localhost + +# Specifies the port of the OpenTelemetry Collector that is listening to. +# +# Variable: AIRFLOW__METRICS__OTEL_PORT +# +otel_port = 8889 + +# The prefix for the Airflow metrics. +# +# Variable: AIRFLOW__METRICS__OTEL_PREFIX +# +otel_prefix = airflow + +# Defines the interval, in milliseconds, at which Airflow sends batches of metrics and traces +# to the configured OpenTelemetry Collector. +# +# Variable: AIRFLOW__METRICS__OTEL_INTERVAL_MILLISECONDS +# +otel_interval_milliseconds = 60000 + +# If ``True``, all metrics are also emitted to the console. Defaults to ``False``. +# +# Variable: AIRFLOW__METRICS__OTEL_DEBUGGING_ON +# +otel_debugging_on = False + +# If ``True``, SSL will be enabled. Defaults to ``False``. +# To establish an HTTPS connection to the OpenTelemetry collector, +# you need to configure the SSL certificate and key within the OpenTelemetry collector's +# ``config.yml`` file. +# +# Variable: AIRFLOW__METRICS__OTEL_SSL_ACTIVE +# +otel_ssl_active = False + +[secrets] +# Full class name of secrets backend to enable (will precede env vars and metastore in search path) +# +# Example: backend = airflow.providers.amazon.aws.secrets.systems_manager.SystemsManagerParameterStoreBackend +# +# Variable: AIRFLOW__SECRETS__BACKEND +# +backend = + +# The backend_kwargs param is loaded into a dictionary and passed to ``__init__`` +# of secrets backend class. See documentation for the secrets backend you are using. +# JSON is expected. +# +# Example for AWS Systems Manager ParameterStore: +# ``{"connections_prefix": "/airflow/connections", "profile_name": "default"}`` +# +# Variable: AIRFLOW__SECRETS__BACKEND_KWARGS +# +backend_kwargs = + +# .. note:: |experimental| +# +# Enables local caching of Variables, when parsing DAGs only. +# Using this option can make dag parsing faster if Variables are used in top level code, at the expense +# of longer propagation time for changes. +# Please note that this cache concerns only the DAG parsing step. There is no caching in place when DAG +# tasks are run. +# +# Variable: AIRFLOW__SECRETS__USE_CACHE +# +use_cache = False + +# .. note:: |experimental| +# +# When the cache is enabled, this is the duration for which we consider an entry in the cache to be +# valid. Entries are refreshed if they are older than this many seconds. +# It means that when the cache is enabled, this is the maximum amount of time you need to wait to see a +# Variable change take effect. +# +# Variable: AIRFLOW__SECRETS__CACHE_TTL_SECONDS +# +cache_ttl_seconds = 900 + +[cli] +# In what way should the cli access the API. The LocalClient will use the +# database directly, while the json_client will use the api running on the +# webserver +# +# Variable: AIRFLOW__CLI__API_CLIENT +# +api_client = airflow.api.client.local_client + +# If you set web_server_url_prefix, do NOT forget to append it here, ex: +# ``endpoint_url = http://localhost:8080/myroot`` +# So api will look like: ``http://localhost:8080/myroot/api/experimental/...`` +# +# Variable: AIRFLOW__CLI__ENDPOINT_URL +# +endpoint_url = http://localhost:8080 + +[debug] +# Used only with ``DebugExecutor``. If set to ``True`` DAG will fail with first +# failed task. Helpful for debugging purposes. +# +# Variable: AIRFLOW__DEBUG__FAIL_FAST +# +fail_fast = False + +[api] +# Enables the deprecated experimental API. Please note that these API endpoints do not have +# access control. An authenticated user has full access. +# +# .. warning:: +# +# This `Experimental REST API +# `__ is +# deprecated since version 2.0. Please consider using +# `the Stable REST API +# `__. +# For more information on migration, see +# `RELEASE_NOTES.rst `_ +# +# Variable: AIRFLOW__API__ENABLE_EXPERIMENTAL_API +# +enable_experimental_api = False + +# Comma separated list of auth backends to authenticate users of the API. See +# `Security: API +# `__ for possible values. +# ("airflow.api.auth.backend.default" allows all requests for historic reasons) +# +# Variable: AIRFLOW__API__AUTH_BACKENDS +# +auth_backends = airflow.api.auth.backend.session + +# Used to set the maximum page limit for API requests. If limit passed as param +# is greater than maximum page limit, it will be ignored and maximum page limit value +# will be set as the limit +# +# Variable: AIRFLOW__API__MAXIMUM_PAGE_LIMIT +# +maximum_page_limit = 100 + +# Used to set the default page limit when limit param is zero or not provided in API +# requests. Otherwise if positive integer is passed in the API requests as limit, the +# smallest number of user given limit or maximum page limit is taken as limit. +# +# Variable: AIRFLOW__API__FALLBACK_PAGE_LIMIT +# +fallback_page_limit = 100 + +# The intended audience for JWT token credentials used for authorization. This value must match on the client and server sides. If empty, audience will not be tested. +# +# Example: google_oauth2_audience = project-id-random-value.apps.googleusercontent.com +# +# Variable: AIRFLOW__API__GOOGLE_OAUTH2_AUDIENCE +# +google_oauth2_audience = + +# Path to Google Cloud Service Account key file (JSON). If omitted, authorization based on +# `the Application Default Credentials +# `__ will +# be used. +# +# Example: google_key_path = /files/service-account-json +# +# Variable: AIRFLOW__API__GOOGLE_KEY_PATH +# +google_key_path = + +# Used in response to a preflight request to indicate which HTTP +# headers can be used when making the actual request. This header is +# the server side response to the browser's +# Access-Control-Request-Headers header. +# +# Variable: AIRFLOW__API__ACCESS_CONTROL_ALLOW_HEADERS +# +access_control_allow_headers = + +# Specifies the method or methods allowed when accessing the resource. +# +# Variable: AIRFLOW__API__ACCESS_CONTROL_ALLOW_METHODS +# +access_control_allow_methods = + +# Indicates whether the response can be shared with requesting code from the given origins. +# Separate URLs with space. +# +# Variable: AIRFLOW__API__ACCESS_CONTROL_ALLOW_ORIGINS +# +access_control_allow_origins = + +# Indicates whether the **xcomEntries** endpoint supports the **deserialize** +# flag. If set to ``False``, setting this flag in a request would result in a +# 400 Bad Request error. +# +# Variable: AIRFLOW__API__ENABLE_XCOM_DESERIALIZE_SUPPORT +# +enable_xcom_deserialize_support = False + +[lineage] +# what lineage backend to use +# +# Variable: AIRFLOW__LINEAGE__BACKEND +# +backend = + +[operators] +# The default owner assigned to each new operator, unless +# provided explicitly or passed via ``default_args`` +# +# Variable: AIRFLOW__OPERATORS__DEFAULT_OWNER +# +default_owner = airflow + +# The default value of attribute "deferrable" in operators and sensors. +# +# Variable: AIRFLOW__OPERATORS__DEFAULT_DEFERRABLE +# +default_deferrable = false + +# Indicates the default number of CPU units allocated to each operator when no specific CPU request +# is specified in the operator's configuration +# +# Variable: AIRFLOW__OPERATORS__DEFAULT_CPUS +# +default_cpus = 1 + +# Indicates the default number of RAM allocated to each operator when no specific RAM request +# is specified in the operator's configuration +# +# Variable: AIRFLOW__OPERATORS__DEFAULT_RAM +# +default_ram = 512 + +# Indicates the default number of disk storage allocated to each operator when no specific disk request +# is specified in the operator's configuration +# +# Variable: AIRFLOW__OPERATORS__DEFAULT_DISK +# +default_disk = 512 + +# Indicates the default number of GPUs allocated to each operator when no specific GPUs request +# is specified in the operator's configuration +# +# Variable: AIRFLOW__OPERATORS__DEFAULT_GPUS +# +default_gpus = 0 + +# Default queue that tasks get assigned to and that worker listen on. +# +# Variable: AIRFLOW__OPERATORS__DEFAULT_QUEUE +# +default_queue = default + +# Is allowed to pass additional/unused arguments (args, kwargs) to the BaseOperator operator. +# If set to ``False``, an exception will be thrown, +# otherwise only the console message will be displayed. +# +# Variable: AIRFLOW__OPERATORS__ALLOW_ILLEGAL_ARGUMENTS +# +allow_illegal_arguments = False + +[webserver] +# The message displayed when a user attempts to execute actions beyond their authorised privileges. +# +# Variable: AIRFLOW__WEBSERVER__ACCESS_DENIED_MESSAGE +# +access_denied_message = Access is Denied + +# Path of webserver config file used for configuring the webserver parameters +# +# Variable: AIRFLOW__WEBSERVER__CONFIG_FILE +# +config_file = /opt/airflow/webserver_config.py + +# The base url of your website: Airflow cannot guess what domain or CNAME you are using. +# This is used to create links in the Log Url column in the Browse - Task Instances menu, +# as well as in any automated emails sent by Airflow that contain links to your webserver. +# +# Variable: AIRFLOW__WEBSERVER__BASE_URL +# +base_url = http://localhost:8080 + +# Default timezone to display all dates in the UI, can be UTC, system, or +# any IANA timezone string (e.g. **Europe/Amsterdam**). If left empty the +# default value of core/default_timezone will be used +# +# Example: default_ui_timezone = America/New_York +# +# Variable: AIRFLOW__WEBSERVER__DEFAULT_UI_TIMEZONE +# +default_ui_timezone = UTC + +# The ip specified when starting the web server +# +# Variable: AIRFLOW__WEBSERVER__WEB_SERVER_HOST +# +web_server_host = 0.0.0.0 + +# The port on which to run the web server +# +# Variable: AIRFLOW__WEBSERVER__WEB_SERVER_PORT +# +web_server_port = 8080 + +# Paths to the SSL certificate and key for the web server. When both are +# provided SSL will be enabled. This does not change the web server port. +# +# Variable: AIRFLOW__WEBSERVER__WEB_SERVER_SSL_CERT +# +web_server_ssl_cert = + +# Paths to the SSL certificate and key for the web server. When both are +# provided SSL will be enabled. This does not change the web server port. +# +# Variable: AIRFLOW__WEBSERVER__WEB_SERVER_SSL_KEY +# +web_server_ssl_key = + +# The type of backend used to store web session data, can be ``database`` or ``securecookie``. For the +# ``database`` backend, sessions are store in the database and they can be +# managed there (for example when you reset password of the user, all sessions for that user are +# deleted). For the ``securecookie`` backend, sessions are stored in encrypted cookies on the client +# side. The ``securecookie`` mechanism is 'lighter' than database backend, but sessions are not deleted +# when you reset password of the user, which means that other than waiting for expiry time, the only +# way to invalidate all sessions for a user is to change secret_key and restart webserver (which +# also invalidates and logs out all other user's sessions). +# +# When you are using ``database`` backend, make sure to keep your database session table small +# by periodically running ``airflow db clean --table session`` command, especially if you have +# automated API calls that will create a new session for each call rather than reuse the sessions +# stored in browser cookies. +# +# Example: session_backend = securecookie +# +# Variable: AIRFLOW__WEBSERVER__SESSION_BACKEND +# +session_backend = database + +# Number of seconds the webserver waits before killing gunicorn master that doesn't respond +# +# Variable: AIRFLOW__WEBSERVER__WEB_SERVER_MASTER_TIMEOUT +# +web_server_master_timeout = 120 + +# Number of seconds the gunicorn webserver waits before timing out on a worker +# +# Variable: AIRFLOW__WEBSERVER__WEB_SERVER_WORKER_TIMEOUT +# +web_server_worker_timeout = 120 + +# Number of workers to refresh at a time. When set to 0, worker refresh is +# disabled. When nonzero, airflow periodically refreshes webserver workers by +# bringing up new ones and killing old ones. +# +# Variable: AIRFLOW__WEBSERVER__WORKER_REFRESH_BATCH_SIZE +# +worker_refresh_batch_size = 1 + +# Number of seconds to wait before refreshing a batch of workers. +# +# Variable: AIRFLOW__WEBSERVER__WORKER_REFRESH_INTERVAL +# +worker_refresh_interval = 6000 + +# If set to ``True``, Airflow will track files in plugins_folder directory. When it detects changes, +# then reload the gunicorn. If set to ``True``, gunicorn starts without preloading, which is slower, +# uses more memory, and may cause race conditions. Avoid setting this to ``True`` in production. +# +# Variable: AIRFLOW__WEBSERVER__RELOAD_ON_PLUGIN_CHANGE +# +reload_on_plugin_change = False + +# Secret key used to run your flask app. It should be as random as possible. However, when running +# more than 1 instances of webserver, make sure all of them use the same ``secret_key`` otherwise +# one of them will error with "CSRF session token is missing". +# The webserver key is also used to authorize requests to Celery workers when logs are retrieved. +# The token generated using the secret key has a short expiry time though - make sure that time on +# ALL the machines that you run airflow components on is synchronized (for example using ntpd) +# otherwise you might get "forbidden" errors when the logs are accessed. +# +# Variable: AIRFLOW__WEBSERVER__SECRET_KEY +# +secret_key = xIcs2bnO5KyoXMwIyf88+g== + +# Number of workers to run the Gunicorn web server +# +# Variable: AIRFLOW__WEBSERVER__WORKERS +# +workers = 4 + +# The worker class gunicorn should use. Choices include +# ``sync`` (default), ``eventlet``, ``gevent``. +# +# .. warning:: +# +# When using ``gevent`` you might also want to set the ``_AIRFLOW_PATCH_GEVENT`` +# environment variable to ``"1"`` to make sure gevent patching is done as early as possible. +# +# See related Issues / PRs for more details: +# +# * https://github.com/benoitc/gunicorn/issues/2796 +# * https://github.com/apache/airflow/issues/8212 +# * https://github.com/apache/airflow/pull/28283 +# +# Variable: AIRFLOW__WEBSERVER__WORKER_CLASS +# +worker_class = sync + +# Log files for the gunicorn webserver. '-' means log to stderr. +# +# Variable: AIRFLOW__WEBSERVER__ACCESS_LOGFILE +# +access_logfile = - + +# Log files for the gunicorn webserver. '-' means log to stderr. +# +# Variable: AIRFLOW__WEBSERVER__ERROR_LOGFILE +# +error_logfile = - + +# Access log format for gunicorn webserver. +# default format is ``%%(h)s %%(l)s %%(u)s %%(t)s "%%(r)s" %%(s)s %%(b)s "%%(f)s" "%%(a)s"`` +# See `Gunicorn Settings: 'access_log_format' Reference +# `__ for more details +# +# Variable: AIRFLOW__WEBSERVER__ACCESS_LOGFORMAT +# +access_logformat = + +# Expose the configuration file in the web server. Set to ``non-sensitive-only`` to show all values +# except those that have security implications. ``True`` shows all values. ``False`` hides the +# configuration completely. +# +# Variable: AIRFLOW__WEBSERVER__EXPOSE_CONFIG +# +expose_config = False + +# Expose hostname in the web server +# +# Variable: AIRFLOW__WEBSERVER__EXPOSE_HOSTNAME +# +expose_hostname = False + +# Expose stacktrace in the web server +# +# Variable: AIRFLOW__WEBSERVER__EXPOSE_STACKTRACE +# +expose_stacktrace = False + +# Default DAG view. Valid values are: ``grid``, ``graph``, ``duration``, ``gantt``, ``landing_times`` +# +# Variable: AIRFLOW__WEBSERVER__DAG_DEFAULT_VIEW +# +dag_default_view = grid + +# Default DAG orientation. Valid values are: +# ``LR`` (Left->Right), ``TB`` (Top->Bottom), ``RL`` (Right->Left), ``BT`` (Bottom->Top) +# +# Variable: AIRFLOW__WEBSERVER__DAG_ORIENTATION +# +dag_orientation = LR + +# Sorting order in grid view. Valid values are: ``topological``, ``hierarchical_alphabetical`` +# +# Variable: AIRFLOW__WEBSERVER__GRID_VIEW_SORTING_ORDER +# +grid_view_sorting_order = topological + +# The amount of time (in secs) webserver will wait for initial handshake +# while fetching logs from other worker machine +# +# Variable: AIRFLOW__WEBSERVER__LOG_FETCH_TIMEOUT_SEC +# +log_fetch_timeout_sec = 5 + +# Time interval (in secs) to wait before next log fetching. +# +# Variable: AIRFLOW__WEBSERVER__LOG_FETCH_DELAY_SEC +# +log_fetch_delay_sec = 2 + +# Distance away from page bottom to enable auto tailing. +# +# Variable: AIRFLOW__WEBSERVER__LOG_AUTO_TAILING_OFFSET +# +log_auto_tailing_offset = 30 + +# Animation speed for auto tailing log display. +# +# Variable: AIRFLOW__WEBSERVER__LOG_ANIMATION_SPEED +# +log_animation_speed = 1000 + +# By default, the webserver shows paused DAGs. Flip this to hide paused +# DAGs by default +# +# Variable: AIRFLOW__WEBSERVER__HIDE_PAUSED_DAGS_BY_DEFAULT +# +hide_paused_dags_by_default = False + +# Consistent page size across all listing views in the UI +# +# Variable: AIRFLOW__WEBSERVER__PAGE_SIZE +# +page_size = 100 + +# Define the color of navigation bar +# +# Variable: AIRFLOW__WEBSERVER__NAVBAR_COLOR +# +navbar_color = #fff + +# Define the color of text in the navigation bar +# +# Variable: AIRFLOW__WEBSERVER__NAVBAR_TEXT_COLOR +# +navbar_text_color = #51504f + +# Define the color of navigation bar links when hovered +# +# Variable: AIRFLOW__WEBSERVER__NAVBAR_HOVER_COLOR +# +navbar_hover_color = #eee + +# Define the color of text in the navigation bar when hovered +# +# Variable: AIRFLOW__WEBSERVER__NAVBAR_TEXT_HOVER_COLOR +# +navbar_text_hover_color = #51504f + +# Define the color of the logo text +# +# Variable: AIRFLOW__WEBSERVER__NAVBAR_LOGO_TEXT_COLOR +# +navbar_logo_text_color = #51504f + +# Default dagrun to show in UI +# +# Variable: AIRFLOW__WEBSERVER__DEFAULT_DAG_RUN_DISPLAY_NUMBER +# +default_dag_run_display_number = 25 + +# Enable werkzeug ``ProxyFix`` middleware for reverse proxy +# +# Variable: AIRFLOW__WEBSERVER__ENABLE_PROXY_FIX +# +enable_proxy_fix = False + +# Number of values to trust for ``X-Forwarded-For``. +# See `Werkzeug: X-Forwarded-For Proxy Fix +# `__ for more details. +# +# Variable: AIRFLOW__WEBSERVER__PROXY_FIX_X_FOR +# +proxy_fix_x_for = 1 + +# Number of values to trust for ``X-Forwarded-Proto``. +# See `Werkzeug: X-Forwarded-For Proxy Fix +# `__ for more details. +# +# Variable: AIRFLOW__WEBSERVER__PROXY_FIX_X_PROTO +# +proxy_fix_x_proto = 1 + +# Number of values to trust for ``X-Forwarded-Host``. +# See `Werkzeug: X-Forwarded-For Proxy Fix +# `__ for more details. +# +# Variable: AIRFLOW__WEBSERVER__PROXY_FIX_X_HOST +# +proxy_fix_x_host = 1 + +# Number of values to trust for ``X-Forwarded-Port``. +# See `Werkzeug: X-Forwarded-For Proxy Fix +# `__ for more details. +# +# Variable: AIRFLOW__WEBSERVER__PROXY_FIX_X_PORT +# +proxy_fix_x_port = 1 + +# Number of values to trust for ``X-Forwarded-Prefix``. +# See `Werkzeug: X-Forwarded-For Proxy Fix +# `__ for more details. +# +# Variable: AIRFLOW__WEBSERVER__PROXY_FIX_X_PREFIX +# +proxy_fix_x_prefix = 1 + +# Set secure flag on session cookie +# +# Variable: AIRFLOW__WEBSERVER__COOKIE_SECURE +# +cookie_secure = False + +# Set samesite policy on session cookie +# +# Variable: AIRFLOW__WEBSERVER__COOKIE_SAMESITE +# +cookie_samesite = Lax + +# Default setting for wrap toggle on DAG code and TI log views. +# +# Variable: AIRFLOW__WEBSERVER__DEFAULT_WRAP +# +default_wrap = False + +# Allow the UI to be rendered in a frame +# +# Variable: AIRFLOW__WEBSERVER__X_FRAME_ENABLED +# +x_frame_enabled = True + +# Send anonymous user activity to your analytics tool +# choose from ``google_analytics``, ``segment``, ``metarouter``, or ``matomo`` +# +# Variable: AIRFLOW__WEBSERVER__ANALYTICS_TOOL +# +# analytics_tool = + +# Unique ID of your account in the analytics tool +# +# Variable: AIRFLOW__WEBSERVER__ANALYTICS_ID +# +# analytics_id = + +# Your instances url, only applicable to Matomo. +# +# Example: analytics_url = https://your.matomo.instance.com/ +# +# Variable: AIRFLOW__WEBSERVER__ANALYTICS_URL +# +# analytics_url = + +# 'Recent Tasks' stats will show for old DagRuns if set +# +# Variable: AIRFLOW__WEBSERVER__SHOW_RECENT_STATS_FOR_COMPLETED_RUNS +# +show_recent_stats_for_completed_runs = True + +# The UI cookie lifetime in minutes. User will be logged out from UI after +# ``[webserver] session_lifetime_minutes`` of non-activity +# +# Variable: AIRFLOW__WEBSERVER__SESSION_LIFETIME_MINUTES +# +session_lifetime_minutes = 43200 + +# Sets a custom page title for the DAGs overview page and site title for all pages +# +# Variable: AIRFLOW__WEBSERVER__INSTANCE_NAME +# +# instance_name = + +# Whether the custom page title for the DAGs overview page contains any Markup language +# +# Variable: AIRFLOW__WEBSERVER__INSTANCE_NAME_HAS_MARKUP +# +instance_name_has_markup = False + +# How frequently, in seconds, the DAG data will auto-refresh in graph or grid view +# when auto-refresh is turned on +# +# Variable: AIRFLOW__WEBSERVER__AUTO_REFRESH_INTERVAL +# +auto_refresh_interval = 3 + +# Boolean for displaying warning for publicly viewable deployment +# +# Variable: AIRFLOW__WEBSERVER__WARN_DEPLOYMENT_EXPOSURE +# +warn_deployment_exposure = True + +# Comma separated string of view events to exclude from dag audit view. +# All other events will be added minus the ones passed here. +# The audit logs in the db will not be affected by this parameter. +# +# Example: audit_view_excluded_events = cli_task_run,running,success +# +# Variable: AIRFLOW__WEBSERVER__AUDIT_VIEW_EXCLUDED_EVENTS +# +# audit_view_excluded_events = + +# Comma separated string of view events to include in dag audit view. +# If passed, only these events will populate the dag audit view. +# The audit logs in the db will not be affected by this parameter. +# +# Example: audit_view_included_events = dagrun_cleared,failed +# +# Variable: AIRFLOW__WEBSERVER__AUDIT_VIEW_INCLUDED_EVENTS +# +# audit_view_included_events = + +# Boolean for running SwaggerUI in the webserver. +# +# Variable: AIRFLOW__WEBSERVER__ENABLE_SWAGGER_UI +# +enable_swagger_ui = True + +# Boolean for running Internal API in the webserver. +# +# Variable: AIRFLOW__WEBSERVER__RUN_INTERNAL_API +# +run_internal_api = False + +# The caching algorithm used by the webserver. Must be a valid hashlib function name. +# +# Example: caching_hash_method = sha256 +# +# Variable: AIRFLOW__WEBSERVER__CACHING_HASH_METHOD +# +caching_hash_method = md5 + +# Behavior of the trigger DAG run button for DAGs without params. ``False`` to skip and trigger +# without displaying a form to add a **dag_run.conf**, ``True`` to always display the form. +# The form is displayed always if parameters are defined. +# +# Variable: AIRFLOW__WEBSERVER__SHOW_TRIGGER_FORM_IF_NO_PARAMS +# +show_trigger_form_if_no_params = False + +# Number of recent DAG run configurations in the selector on the trigger web form. +# +# Example: num_recent_configurations_for_trigger = 10 +# +# Variable: AIRFLOW__WEBSERVER__NUM_RECENT_CONFIGURATIONS_FOR_TRIGGER +# +num_recent_configurations_for_trigger = 5 + +# A DAG author is able to provide any raw HTML into ``doc_md`` or params description in +# ``description_md`` for text formatting. This is including potentially unsafe javascript. +# Displaying the DAG or trigger form in web UI provides the DAG author the potential to +# inject malicious code into clients browsers. To ensure the web UI is safe by default, +# raw HTML is disabled by default. If you trust your DAG authors, you can enable HTML +# support in markdown by setting this option to ``True``. +# +# This parameter also enables the deprecated fields ``description_html`` and +# ``custom_html_form`` in DAG params until the feature is removed in a future version. +# +# Example: allow_raw_html_descriptions = False +# +# Variable: AIRFLOW__WEBSERVER__ALLOW_RAW_HTML_DESCRIPTIONS +# +allow_raw_html_descriptions = False + +# The maximum size of the request payload (in MB) that can be sent. +# +# Variable: AIRFLOW__WEBSERVER__ALLOWED_PAYLOAD_SIZE +# +allowed_payload_size = 1.0 + +# Require confirmation when changing a DAG in the web UI. This is to prevent accidental changes +# to a DAG that may be running on sensitive environments like production. +# When set to ``True``, confirmation dialog will be shown when a user tries to Pause/Unpause, +# Trigger a DAG +# +# Variable: AIRFLOW__WEBSERVER__REQUIRE_CONFIRMATION_DAG_CHANGE +# +require_confirmation_dag_change = False + +[email] +# Configuration email backend and whether to +# send email alerts on retry or failure + +# Email backend to use +# +# Variable: AIRFLOW__EMAIL__EMAIL_BACKEND +# +email_backend = airflow.utils.email.send_email_smtp + +# Email connection to use +# +# Variable: AIRFLOW__EMAIL__EMAIL_CONN_ID +# +email_conn_id = smtp_default + +# Whether email alerts should be sent when a task is retried +# +# Variable: AIRFLOW__EMAIL__DEFAULT_EMAIL_ON_RETRY +# +default_email_on_retry = True + +# Whether email alerts should be sent when a task failed +# +# Variable: AIRFLOW__EMAIL__DEFAULT_EMAIL_ON_FAILURE +# +default_email_on_failure = True + +# File that will be used as the template for Email subject (which will be rendered using Jinja2). +# If not set, Airflow uses a base template. +# +# Example: subject_template = /path/to/my_subject_template_file +# +# Variable: AIRFLOW__EMAIL__SUBJECT_TEMPLATE +# +# subject_template = + +# File that will be used as the template for Email content (which will be rendered using Jinja2). +# If not set, Airflow uses a base template. +# +# Example: html_content_template = /path/to/my_html_content_template_file +# +# Variable: AIRFLOW__EMAIL__HTML_CONTENT_TEMPLATE +# +# html_content_template = + +# Email address that will be used as sender address. +# It can either be raw email or the complete address in a format ``Sender Name `` +# +# Example: from_email = Airflow +# +# Variable: AIRFLOW__EMAIL__FROM_EMAIL +# +# from_email = + +# ssl context to use when using SMTP and IMAP SSL connections. By default, the context is "default" +# which sets it to ``ssl.create_default_context()`` which provides the right balance between +# compatibility and security, it however requires that certificates in your operating system are +# updated and that SMTP/IMAP servers of yours have valid certificates that have corresponding public +# keys installed on your machines. You can switch it to "none" if you want to disable checking +# of the certificates, but it is not recommended as it allows MITM (man-in-the-middle) attacks +# if your infrastructure is not sufficiently secured. It should only be set temporarily while you +# are fixing your certificate configuration. This can be typically done by upgrading to newer +# version of the operating system you run Airflow components on,by upgrading/refreshing proper +# certificates in the OS or by updating certificates for your mail servers. +# +# Example: ssl_context = default +# +# Variable: AIRFLOW__EMAIL__SSL_CONTEXT +# +ssl_context = default + +[smtp] +# If you want airflow to send emails on retries, failure, and you want to use +# the airflow.utils.email.send_email_smtp function, you have to configure an +# smtp server here + +# Specifies the host server address used by Airflow when sending out email notifications via SMTP. +# +# Variable: AIRFLOW__SMTP__SMTP_HOST +# +smtp_host = localhost + +# Determines whether to use the STARTTLS command when connecting to the SMTP server. +# +# Variable: AIRFLOW__SMTP__SMTP_STARTTLS +# +smtp_starttls = True + +# Determines whether to use an SSL connection when talking to the SMTP server. +# +# Variable: AIRFLOW__SMTP__SMTP_SSL +# +smtp_ssl = False + +# Username to authenticate when connecting to smtp server. +# +# Example: smtp_user = airflow +# +# Variable: AIRFLOW__SMTP__SMTP_USER +# +# smtp_user = + +# Password to authenticate when connecting to smtp server. +# +# Example: smtp_password = airflow +# +# Variable: AIRFLOW__SMTP__SMTP_PASSWORD +# +# smtp_password = + +# Defines the port number on which Airflow connects to the SMTP server to send email notifications. +# +# Variable: AIRFLOW__SMTP__SMTP_PORT +# +smtp_port = 25 + +# Specifies the default **from** email address used when Airflow sends email notifications. +# +# Variable: AIRFLOW__SMTP__SMTP_MAIL_FROM +# +smtp_mail_from = airflow@example.com + +# Determines the maximum time (in seconds) the Apache Airflow system will wait for a +# connection to the SMTP server to be established. +# +# Variable: AIRFLOW__SMTP__SMTP_TIMEOUT +# +smtp_timeout = 30 + +# Defines the maximum number of times Airflow will attempt to connect to the SMTP server. +# +# Variable: AIRFLOW__SMTP__SMTP_RETRY_LIMIT +# +smtp_retry_limit = 5 + +[sentry] +# `Sentry `__ integration. Here you can supply +# additional configuration options based on the Python platform. +# See `Python / Configuration / Basic Options +# `__ for more details. +# Unsupported options: ``integrations``, ``in_app_include``, ``in_app_exclude``, +# ``ignore_errors``, ``before_breadcrumb``, ``transport``. + +# Enable error reporting to Sentry +# +# Variable: AIRFLOW__SENTRY__SENTRY_ON +# +sentry_on = false + +# +# Variable: AIRFLOW__SENTRY__SENTRY_DSN +# +sentry_dsn = + +# Dotted path to a before_send function that the sentry SDK should be configured to use. +# +# Variable: AIRFLOW__SENTRY__BEFORE_SEND +# +# before_send = + +[scheduler] +# Task instances listen for external kill signal (when you clear tasks +# from the CLI or the UI), this defines the frequency at which they should +# listen (in seconds). +# +# Variable: AIRFLOW__SCHEDULER__JOB_HEARTBEAT_SEC +# +job_heartbeat_sec = 5 + +# The scheduler constantly tries to trigger new tasks (look at the +# scheduler section in the docs for more information). This defines +# how often the scheduler should run (in seconds). +# +# Variable: AIRFLOW__SCHEDULER__SCHEDULER_HEARTBEAT_SEC +# +scheduler_heartbeat_sec = 5 + +# The frequency (in seconds) at which the LocalTaskJob should send heartbeat signals to the +# scheduler to notify it's still alive. If this value is set to 0, the heartbeat interval will default +# to the value of ``[scheduler] scheduler_zombie_task_threshold``. +# +# Variable: AIRFLOW__SCHEDULER__LOCAL_TASK_JOB_HEARTBEAT_SEC +# +local_task_job_heartbeat_sec = 0 + +# The number of times to try to schedule each DAG file +# -1 indicates unlimited number +# +# Variable: AIRFLOW__SCHEDULER__NUM_RUNS +# +num_runs = -1 + +# Controls how long the scheduler will sleep between loops, but if there was nothing to do +# in the loop. i.e. if it scheduled something then it will start the next loop +# iteration straight away. +# +# Variable: AIRFLOW__SCHEDULER__SCHEDULER_IDLE_SLEEP_TIME +# +scheduler_idle_sleep_time = 1 + +# Number of seconds after which a DAG file is parsed. The DAG file is parsed every +# ``[scheduler] min_file_process_interval`` number of seconds. Updates to DAGs are reflected after +# this interval. Keeping this number low will increase CPU usage. +# +# Variable: AIRFLOW__SCHEDULER__MIN_FILE_PROCESS_INTERVAL +# +min_file_process_interval = 30 + +# How often (in seconds) to check for stale DAGs (DAGs which are no longer present in +# the expected files) which should be deactivated, as well as datasets that are no longer +# referenced and should be marked as orphaned. +# +# Variable: AIRFLOW__SCHEDULER__PARSING_CLEANUP_INTERVAL +# +parsing_cleanup_interval = 60 + +# How long (in seconds) to wait after we have re-parsed a DAG file before deactivating stale +# DAGs (DAGs which are no longer present in the expected files). The reason why we need +# this threshold is to account for the time between when the file is parsed and when the +# DAG is loaded. The absolute maximum that this could take is ``[core] dag_file_processor_timeout``, +# but when you have a long timeout configured, it results in a significant delay in the +# deactivation of stale dags. +# +# Variable: AIRFLOW__SCHEDULER__STALE_DAG_THRESHOLD +# +stale_dag_threshold = 50 + +# How often (in seconds) to scan the DAGs directory for new files. Default to 5 minutes. +# +# Variable: AIRFLOW__SCHEDULER__DAG_DIR_LIST_INTERVAL +# +dag_dir_list_interval = 300 + +# How often should stats be printed to the logs. Setting to 0 will disable printing stats +# +# Variable: AIRFLOW__SCHEDULER__PRINT_STATS_INTERVAL +# +print_stats_interval = 30 + +# How often (in seconds) should pool usage stats be sent to StatsD (if statsd_on is enabled) +# +# Variable: AIRFLOW__SCHEDULER__POOL_METRICS_INTERVAL +# +pool_metrics_interval = 5.0 + +# If the last scheduler heartbeat happened more than ``[scheduler] scheduler_health_check_threshold`` +# ago (in seconds), scheduler is considered unhealthy. +# This is used by the health check in the **/health** endpoint and in ``airflow jobs check`` CLI +# for SchedulerJob. +# +# Variable: AIRFLOW__SCHEDULER__SCHEDULER_HEALTH_CHECK_THRESHOLD +# +scheduler_health_check_threshold = 30 + +# When you start a scheduler, airflow starts a tiny web server +# subprocess to serve a health check if this is set to ``True`` +# +# Variable: AIRFLOW__SCHEDULER__ENABLE_HEALTH_CHECK +# +enable_health_check = False + +# When you start a scheduler, airflow starts a tiny web server +# subprocess to serve a health check on this host +# +# Variable: AIRFLOW__SCHEDULER__SCHEDULER_HEALTH_CHECK_SERVER_HOST +# +scheduler_health_check_server_host = 0.0.0.0 + +# When you start a scheduler, airflow starts a tiny web server +# subprocess to serve a health check on this port +# +# Variable: AIRFLOW__SCHEDULER__SCHEDULER_HEALTH_CHECK_SERVER_PORT +# +scheduler_health_check_server_port = 8974 + +# How often (in seconds) should the scheduler check for orphaned tasks and SchedulerJobs +# +# Variable: AIRFLOW__SCHEDULER__ORPHANED_TASKS_CHECK_INTERVAL +# +orphaned_tasks_check_interval = 300.0 + +# Determines the directory where logs for the child processes of the scheduler will be stored +# +# Variable: AIRFLOW__SCHEDULER__CHILD_PROCESS_LOG_DIRECTORY +# +child_process_log_directory = /opt/airflow/logs/scheduler + +# Local task jobs periodically heartbeat to the DB. If the job has +# not heartbeat in this many seconds, the scheduler will mark the +# associated task instance as failed and will re-schedule the task. +# +# Variable: AIRFLOW__SCHEDULER__SCHEDULER_ZOMBIE_TASK_THRESHOLD +# +scheduler_zombie_task_threshold = 300 + +# How often (in seconds) should the scheduler check for zombie tasks. +# +# Variable: AIRFLOW__SCHEDULER__ZOMBIE_DETECTION_INTERVAL +# +zombie_detection_interval = 10.0 + +# Turn off scheduler catchup by setting this to ``False``. +# Default behavior is unchanged and +# Command Line Backfills still work, but the scheduler +# will not do scheduler catchup if this is ``False``, +# however it can be set on a per DAG basis in the +# DAG definition (catchup) +# +# Variable: AIRFLOW__SCHEDULER__CATCHUP_BY_DEFAULT +# +catchup_by_default = True + +# Setting this to ``True`` will make first task instance of a task +# ignore depends_on_past setting. A task instance will be considered +# as the first task instance of a task when there is no task instance +# in the DB with an execution_date earlier than it., i.e. no manual marking +# success will be needed for a newly added task to be scheduled. +# +# Variable: AIRFLOW__SCHEDULER__IGNORE_FIRST_DEPENDS_ON_PAST_BY_DEFAULT +# +ignore_first_depends_on_past_by_default = True + +# This changes the batch size of queries in the scheduling main loop. +# This should not be greater than ``[core] parallelism``. +# If this is too high, SQL query performance may be impacted by +# complexity of query predicate, and/or excessive locking. +# Additionally, you may hit the maximum allowable query length for your db. +# Set this to 0 to use the value of ``[core] parallelism`` +# +# Variable: AIRFLOW__SCHEDULER__MAX_TIS_PER_QUERY +# +max_tis_per_query = 16 + +# Should the scheduler issue ``SELECT ... FOR UPDATE`` in relevant queries. +# If this is set to ``False`` then you should not run more than a single +# scheduler at once +# +# Variable: AIRFLOW__SCHEDULER__USE_ROW_LEVEL_LOCKING +# +use_row_level_locking = True + +# Max number of DAGs to create DagRuns for per scheduler loop. +# +# Variable: AIRFLOW__SCHEDULER__MAX_DAGRUNS_TO_CREATE_PER_LOOP +# +max_dagruns_to_create_per_loop = 10 + +# How many DagRuns should a scheduler examine (and lock) when scheduling +# and queuing tasks. +# +# Variable: AIRFLOW__SCHEDULER__MAX_DAGRUNS_PER_LOOP_TO_SCHEDULE +# +max_dagruns_per_loop_to_schedule = 20 + +# Should the Task supervisor process perform a "mini scheduler" to attempt to schedule more tasks of the +# same DAG. Leaving this on will mean tasks in the same DAG execute quicker, but might starve out other +# dags in some circumstances +# +# Variable: AIRFLOW__SCHEDULER__SCHEDULE_AFTER_TASK_EXECUTION +# +schedule_after_task_execution = True + +# The scheduler reads dag files to extract the airflow modules that are going to be used, +# and imports them ahead of time to avoid having to re-do it for each parsing process. +# This flag can be set to ``False`` to disable this behavior in case an airflow module needs +# to be freshly imported each time (at the cost of increased DAG parsing time). +# +# Variable: AIRFLOW__SCHEDULER__PARSING_PRE_IMPORT_MODULES +# +parsing_pre_import_modules = True + +# The scheduler can run multiple processes in parallel to parse dags. +# This defines how many processes will run. +# +# Variable: AIRFLOW__SCHEDULER__PARSING_PROCESSES +# +parsing_processes = 2 + +# One of ``modified_time``, ``random_seeded_by_host`` and ``alphabetical``. +# The scheduler will list and sort the dag files to decide the parsing order. +# +# * ``modified_time``: Sort by modified time of the files. This is useful on large scale to parse the +# recently modified DAGs first. +# * ``random_seeded_by_host``: Sort randomly across multiple Schedulers but with same order on the +# same host. This is useful when running with Scheduler in HA mode where each scheduler can +# parse different DAG files. +# * ``alphabetical``: Sort by filename +# +# Variable: AIRFLOW__SCHEDULER__FILE_PARSING_SORT_MODE +# +file_parsing_sort_mode = modified_time + +# Whether the dag processor is running as a standalone process or it is a subprocess of a scheduler +# job. +# +# Variable: AIRFLOW__SCHEDULER__STANDALONE_DAG_PROCESSOR +# +standalone_dag_processor = False + +# Only applicable if ``[scheduler] standalone_dag_processor`` is true and callbacks are stored +# in database. Contains maximum number of callbacks that are fetched during a single loop. +# +# Variable: AIRFLOW__SCHEDULER__MAX_CALLBACKS_PER_LOOP +# +max_callbacks_per_loop = 20 + +# Only applicable if ``[scheduler] standalone_dag_processor`` is true. +# Time in seconds after which dags, which were not updated by Dag Processor are deactivated. +# +# Variable: AIRFLOW__SCHEDULER__DAG_STALE_NOT_SEEN_DURATION +# +dag_stale_not_seen_duration = 600 + +# Turn off scheduler use of cron intervals by setting this to ``False``. +# DAGs submitted manually in the web UI or with trigger_dag will still run. +# +# Variable: AIRFLOW__SCHEDULER__USE_JOB_SCHEDULE +# +use_job_schedule = True + +# Allow externally triggered DagRuns for Execution Dates in the future +# Only has effect if schedule_interval is set to None in DAG +# +# Variable: AIRFLOW__SCHEDULER__ALLOW_TRIGGER_IN_FUTURE +# +allow_trigger_in_future = False + +# How often to check for expired trigger requests that have not run yet. +# +# Variable: AIRFLOW__SCHEDULER__TRIGGER_TIMEOUT_CHECK_INTERVAL +# +trigger_timeout_check_interval = 15 + +# Amount of time a task can be in the queued state before being retried or set to failed. +# +# Variable: AIRFLOW__SCHEDULER__TASK_QUEUED_TIMEOUT +# +task_queued_timeout = 600.0 + +# How often to check for tasks that have been in the queued state for +# longer than ``[scheduler] task_queued_timeout``. +# +# Variable: AIRFLOW__SCHEDULER__TASK_QUEUED_TIMEOUT_CHECK_INTERVAL +# +task_queued_timeout_check_interval = 120.0 + +# The run_id pattern used to verify the validity of user input to the run_id parameter when +# triggering a DAG. This pattern cannot change the pattern used by scheduler to generate run_id +# for scheduled DAG runs or DAG runs triggered without changing the run_id parameter. +# +# Variable: AIRFLOW__SCHEDULER__ALLOWED_RUN_ID_PATTERN +# +allowed_run_id_pattern = ^[A-Za-z0-9_.~:+-]+$ + +# Whether to create DAG runs that span an interval or one single point in time for cron schedules, when +# a cron string is provided to ``schedule`` argument of a DAG. +# +# * ``True``: **CronDataIntervalTimetable** is used, which is suitable +# for DAGs with well-defined data interval. You get contiguous intervals from the end of the previous +# interval up to the scheduled datetime. +# * ``False``: **CronTriggerTimetable** is used, which is closer to the behavior of cron itself. +# +# Notably, for **CronTriggerTimetable**, the logical date is the same as the time the DAG Run will +# try to schedule, while for **CronDataIntervalTimetable**, the logical date is the beginning of +# the data interval, but the DAG Run will try to schedule at the end of the data interval. +# +# Variable: AIRFLOW__SCHEDULER__CREATE_CRON_DATA_INTERVALS +# +create_cron_data_intervals = True + +[triggerer] +# How many triggers a single Triggerer will run at once, by default. +# +# Variable: AIRFLOW__TRIGGERER__DEFAULT_CAPACITY +# +default_capacity = 1000 + +# How often to heartbeat the Triggerer job to ensure it hasn't been killed. +# +# Variable: AIRFLOW__TRIGGERER__JOB_HEARTBEAT_SEC +# +job_heartbeat_sec = 5 + +# If the last triggerer heartbeat happened more than ``[triggerer] triggerer_health_check_threshold`` +# ago (in seconds), triggerer is considered unhealthy. +# This is used by the health check in the **/health** endpoint and in ``airflow jobs check`` CLI +# for TriggererJob. +# +# Variable: AIRFLOW__TRIGGERER__TRIGGERER_HEALTH_CHECK_THRESHOLD +# +triggerer_health_check_threshold = 30 + +[kerberos] +# Location of your ccache file once kinit has been performed. +# +# Variable: AIRFLOW__KERBEROS__CCACHE +# +ccache = /tmp/airflow_krb5_ccache + +# gets augmented with fqdn +# +# Variable: AIRFLOW__KERBEROS__PRINCIPAL +# +principal = airflow + +# Determines the frequency at which initialization or re-initialization processes occur. +# +# Variable: AIRFLOW__KERBEROS__REINIT_FREQUENCY +# +reinit_frequency = 3600 + +# Path to the kinit executable +# +# Variable: AIRFLOW__KERBEROS__KINIT_PATH +# +kinit_path = kinit + +# Designates the path to the Kerberos keytab file for the Airflow user +# +# Variable: AIRFLOW__KERBEROS__KEYTAB +# +keytab = airflow.keytab + +# Allow to disable ticket forwardability. +# +# Variable: AIRFLOW__KERBEROS__FORWARDABLE +# +forwardable = True + +# Allow to remove source IP from token, useful when using token behind NATted Docker host. +# +# Variable: AIRFLOW__KERBEROS__INCLUDE_IP +# +include_ip = True + +[sensors] +# Sensor default timeout, 7 days by default (7 * 24 * 60 * 60). +# +# Variable: AIRFLOW__SENSORS__DEFAULT_TIMEOUT +# +default_timeout = 604800 + +[common.io] +# Common IO configuration section + +# Path to a location on object storage where XComs can be stored in url format. +# +# Example: xcom_objectstorage_path = s3://conn_id@bucket/path +# +# Variable: AIRFLOW__COMMON.IO__XCOM_OBJECTSTORAGE_PATH +# +xcom_objectstorage_path = + +# Threshold in bytes for storing XComs in object storage. -1 means always store in the +# database. 0 means always store in object storage. Any positive number means +# it will be stored in object storage if the size of the value is greater than the threshold. +# +# Example: xcom_objectstorage_threshold = 1000000 +# +# Variable: AIRFLOW__COMMON.IO__XCOM_OBJECTSTORAGE_THRESHOLD +# +xcom_objectstorage_threshold = -1 + +# Compression algorithm to use when storing XComs in object storage. Supported algorithms +# are a.o.: snappy, zip, gzip, bz2, and lzma. If not specified, no compression will be used. +# Note that the compression algorithm must be available in the Python installation (e.g. +# python-snappy for snappy). Zip, gz, bz2 are available by default. +# +# Example: xcom_objectstorage_compression = gz +# +# Variable: AIRFLOW__COMMON.IO__XCOM_OBJECTSTORAGE_COMPRESSION +# +xcom_objectstorage_compression = + +[fab] +# This section contains configs specific to FAB provider. + +# Boolean for enabling rate limiting on authentication endpoints. +# +# Variable: AIRFLOW__FAB__AUTH_RATE_LIMITED +# +auth_rate_limited = True + +# Rate limit for authentication endpoints. +# +# Variable: AIRFLOW__FAB__AUTH_RATE_LIMIT +# +auth_rate_limit = 5 per 40 second + +# Update FAB permissions and sync security manager roles +# on webserver startup +# +# Variable: AIRFLOW__FAB__UPDATE_FAB_PERMS +# +update_fab_perms = True + +[imap] +# Options for IMAP provider. + +# ssl_context = + +[smtp_provider] +# Options for SMTP provider. + +# ssl context to use when using SMTP and IMAP SSL connections. By default, the context is "default" +# which sets it to ``ssl.create_default_context()`` which provides the right balance between +# compatibility and security, it however requires that certificates in your operating system are +# updated and that SMTP/IMAP servers of yours have valid certificates that have corresponding public +# keys installed on your machines. You can switch it to "none" if you want to disable checking +# of the certificates, but it is not recommended as it allows MITM (man-in-the-middle) attacks +# if your infrastructure is not sufficiently secured. It should only be set temporarily while you +# are fixing your certificate configuration. This can be typically done by upgrading to newer +# version of the operating system you run Airflow components on,by upgrading/refreshing proper +# certificates in the OS or by updating certificates for your mail servers. +# +# If you do not set this option explicitly, it will use Airflow "email.ssl_context" configuration, +# but if this configuration is not present, it will use "default" value. +# +# Example: ssl_context = default +# +# Variable: AIRFLOW__SMTP_PROVIDER__SSL_CONTEXT +# +# ssl_context = + +# Allows overriding of the standard templated email subject line when the SmtpNotifier is used. +# Must provide a path to the template. +# +# Example: templated_email_subject_path = path/to/override/email_subject.html +# +# Variable: AIRFLOW__SMTP_PROVIDER__TEMPLATED_EMAIL_SUBJECT_PATH +# +# templated_email_subject_path = + +# Allows overriding of the standard templated email path when the SmtpNotifier is used. Must provide +# a path to the template. +# +# Example: templated_html_content_path = path/to/override/email.html +# +# Variable: AIRFLOW__SMTP_PROVIDER__TEMPLATED_HTML_CONTENT_PATH +# +# templated_html_content_path = + +processor_log_folder = /opt/airflow/logs/scheduler diff --git a/airflow_bundle/leaf-pipeline/airflow/dags/configs/config.docker.yaml b/airflow_bundle/leaf-pipeline/airflow/dags/configs/config.docker.yaml new file mode 100644 index 000000000..465a10ca7 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/airflow/dags/configs/config.docker.yaml @@ -0,0 +1,67 @@ +# io: +# # IMPORTANT: use the Docker service name of Postgres (from your compose): +# postgres_url: "postgresql+psycopg2://missions_user:pg123@postgres:5432/missions_db" +io: + postgres_url: "postgresql+psycopg2://postgres:postgres@agcloud-postgres:5432/postgres" + + +windows: + frequency: "D" + timezone: "UTC" + +source_mapping: + entity_dim: "mission" # or "region"/"device" + area_strategy: "none" # or "region_area" (requires regions table/geom) + filters: + start_time: null + end_time: null + anomaly_codes: null + +baseline: + method: "median" + lookback_periods: 28 + min_history: 7 + seasonality: null + +rules: + count_anomaly: + enabled: true + method: "zscore" + z_threshold: 3.0 + iqr_k: 1.5 + min_count: 3 + worsening: + enabled: true + method: "slope" + slope_lookback: 7 + slope_min: 0.02 + min_periods: 5 + ewma_span: 7 + ewma_threshold: 0.6 + +alerting: + dedup_cooldown_windows: 3 + resolve_after_no_anomaly: 3 + rate_limit_per_run: 100 + group_by_window: true + +delivery: + slack: + enabled: false + webhook_url: "" + webhook: + enabled: false + url: "" + headers: {} + email: + enabled: false + smtp_host: "" + smtp_port: 587 + username: "" + password_env: "SMTP_PASSWORD" + from_addr: "" + to_addrs: [] + +run: + dry_run: false + diff --git a/airflow_bundle/leaf-pipeline/airflow/dags/leaf_pipeline_dag.py b/airflow_bundle/leaf-pipeline/airflow/dags/leaf_pipeline_dag.py new file mode 100644 index 000000000..f58a61d53 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/airflow/dags/leaf_pipeline_dag.py @@ -0,0 +1,533 @@ +from __future__ import annotations +from datetime import datetime +import pendulum +from airflow import DAG +from airflow.operators.bash import BashOperator +from airflow.providers.docker.operators.docker import DockerOperator + + + +PROJECT_ROOT = "/opt/leaf-pipeline/projects/leaf-counting" + +PYTHON_BIN = "python" +WEIGHTS = f"{PROJECT_ROOT}/weights/best.pt" + + +OUT_RUN = f"{PROJECT_ROOT}/runs_local/airflow_run" +STAGING_DIR = "/opt/airflow/staging/input" + +tz = pendulum.timezone("Asia/Jerusalem") + +with DAG( + dag_id="leaf_pipeline_v2", + start_date=datetime(2025, 10, 1, tzinfo=tz), + schedule=None, + catchup=False, + default_args={"owner": "leafcounting", "retries": 0}, + tags=["leaf-counting", "detect", "pwb", "crop", "minio"], +) as dag: + + + RUN_ID_DATE = "{{ dag_run.conf.get('run_id') or logical_date.in_timezone('Asia/Jerusalem').strftime('%Y/%m/%d/%H%M') }}" + + # ----------------------------- + # STAGE INPUT + # ----------------------------- + stage_input = BashOperator( + task_id="stage_input", + bash_command=""" +set -euo pipefail +python -m pip install --no-cache-dir -q \ + --trusted-host pypi.org --trusted-host files.pythonhosted.org --trusted-host pypi.python.org \ + awscli \ +|| apt-get update && apt-get install -y -qq ca-certificates awscli \ +|| python -m pip install --no-cache-dir -q \ + --index-url http://pypi.org/simple \ + --trusted-host pypi.org --trusted-host files.pythonhosted.org --trusted-host pypi.python.org \ + awscli +STAGING_DIR='{{ params.staging_dir }}' +INPUT_MODE='minio' +mkdir -p "$STAGING_DIR"; rm -rf "$STAGING_DIR"/* +if [ "$INPUT_MODE" = 'minio' ]; then + SRC_BUCKET='{{ dag_run.conf.get("src_bucket", var.value.leaf_minio_bucket | default("imagery")) }}' + SRC_PREFIX='leaves/examples' + ENDPOINT_URL='{{ conn.minio_s3.extra_dejson.endpoint_url | default("http://host.docker.internal:9001") }}' + export AWS_ACCESS_KEY_ID='{{ conn.minio_s3.login }}' + export AWS_SECRET_ACCESS_KEY='{{ conn.minio_s3.password }}' + export AWS_DEFAULT_REGION='{{ conn.minio_s3.extra_dejson.region_name or "us-east-1" }}' + export AWS_S3_FORCE_PATH_STYLE=true + export AWS_EC2_METADATA_DISABLED=true + echo "[stage] source=minio s3://$SRC_BUCKET/$SRC_PREFIX -> $STAGING_DIR (endpoint=$ENDPOINT_URL)" + python -m awscli s3 sync "s3://$SRC_BUCKET/$SRC_PREFIX" "$STAGING_DIR" --endpoint-url "$ENDPOINT_URL" +else + INPUT_DIR='{{ params.project_root }}/demo_images' + echo "[stage] source=local $INPUT_DIR -> $STAGING_DIR" + rsync -a --delete "$INPUT_DIR"/ "$STAGING_DIR"/ +fi +""", + params={"staging_dir": STAGING_DIR, "project_root": PROJECT_ROOT}, + env={"PYTHONUNBUFFERED": "1"}, + ) + + # ----------------------------- + # DETECT -> imagery/leaves///
//detect/ + # ----------------------------- + detect = BashOperator( + task_id="detect", + bash_command=""" +set -euo pipefail + +PROJECT_ROOT='{{ params.project_root }}' +PY='{{ params.python_bin }}'; if ! command -v "$PY" >/dev/null 2>&1; then PY='python'; fi + +export PYTHONEXECUTABLE="$PY" + +INPUT_DIR='{{ params.staging_dir }}' +OUT_LOCAL_DET='{{ params.out_run }}/detect' +WEIGHTS='{{ params.weights }}' + +DATE_ONLY='{{ dag_run.conf.get("run_id") or logical_date.in_timezone("Asia/Jerusalem").strftime("%Y/%m/%d/%H%M") }}' + +DEST_PREFIX="leaves/${DATE_ONLY}/detect" + +# MinIO: +# -SDK (minio-py) +ENDPOINT_HOSTPORT='{{ (conn.minio_s3.host or "host.docker.internal") }}:{{ (conn.minio_s3.port or 9001) }}' +ENDPOINT_URL='{{ conn.minio_s3.extra_dejson.endpoint_url | default("http://host.docker.internal:9001") }}' +BUCKET='{{ var.value.leaf_minio_bucket | default("imagery") }}' +export AWS_ACCESS_KEY_ID='{{ conn.minio_s3.login }}' +export AWS_SECRET_ACCESS_KEY='{{ conn.minio_s3.password }}' +export AWS_DEFAULT_REGION='us-east-1' +export AWS_S3_FORCE_PATH_STYLE=true + +# mkdir -p "$OUT_LOCAL_DET" +OUT_LOCAL_DET='{{ params.out_run }}/detect' +mkdir -p "$OUT_LOCAL_DET" +rm -rf "$OUT_LOCAL_DET"/* 2>/dev/null || true +cd "$PROJECT_ROOT" +$PY src/detect_only.py \ + --input "$INPUT_DIR" \ + --out "$OUT_LOCAL_DET" \ + --weights "$WEIGHTS" \ + --conf 0.25 --imgsz 896 --device cpu \ + --run-id "detect" + +pip install -q awscli || true +python -m awscli s3 sync "$OUT_LOCAL_DET"/ "s3://$BUCKET/$DEST_PREFIX/" --endpoint-url "$ENDPOINT_URL" +python -m awscli s3 ls "s3://$BUCKET/$DEST_PREFIX/" --recursive --endpoint-url "$ENDPOINT_URL" || true +""", + params={ + "project_root": PROJECT_ROOT, + # "python_bin": PYTHON_BIN, + "python_bin": "/usr/local/bin/python", + "staging_dir": STAGING_DIR, + "out_run": OUT_RUN, + "weights": WEIGHTS, + "run_id_date": RUN_ID_DATE, + }, + env={"PYTHONUNBUFFERED": "1"}, + ) + + # ----------------------------- + # PREDICT_PWB -> imagery/leaves///
//pwb/ + # ----------------------------- + pwb = BashOperator( + task_id="predict_pwb", + bash_command=""" +set -euo pipefail + +PROJECT_ROOT='{{ params.project_root }}' +PY='{{ params.python_bin }}'; if ! command -v "$PY" >/dev/null 2>&1; then PY='python'; fi +INPUT_DIR='{{ params.staging_dir }}' +OUT_LOCAL_PWB='{{ params.out_run }}/pwb' +WEIGHTS='{{ params.weights }}' + +DATE_ONLY='{{ dag_run.conf.get("run_id") or logical_date.in_timezone("Asia/Jerusalem").strftime("%Y/%m/%d/%H%M") }}' + +DEST_PREFIX="leaves/${DATE_ONLY}/pwb" + +ENDPOINT_HOSTPORT='{{ (conn.minio_s3.host or "host.docker.internal") }}:{{ (conn.minio_s3.port or 9001) }}' +ENDPOINT_URL='{{ conn.minio_s3.extra_dejson.endpoint_url | default("http://host.docker.internal:9001") }}' +BUCKET='{{ var.value.leaf_minio_bucket | default("imagery") }}' +export AWS_ACCESS_KEY_ID='{{ conn.minio_s3.login }}' +export AWS_SECRET_ACCESS_KEY='{{ conn.minio_s3.password }}' +export AWS_DEFAULT_REGION='us-east-1' +export AWS_S3_FORCE_PATH_STYLE=true + +mkdir -p "$OUT_LOCAL_PWB" + +cd "$PROJECT_ROOT" +$PY src/predict_pyramid_wbf.py \ + --input "$INPUT_DIR" \ + --out "$OUT_LOCAL_PWB" \ + --weights "$WEIGHTS" \ + --scales 0.75,1.0,1.25 --conf 0.25 --iou 0.55 --imgsz 896 --device cpu \ + --run-id "pwb" + +pip install -q awscli || true +python -m awscli s3 sync "$OUT_LOCAL_PWB"/ "s3://$BUCKET/$DEST_PREFIX/" --endpoint-url "$ENDPOINT_URL" +python -m awscli s3 ls "s3://$BUCKET/$DEST_PREFIX/" --recursive --endpoint-url "$ENDPOINT_URL" || true +""", + params={ + "project_root": PROJECT_ROOT, + # "python_bin": PYTHON_BIN, + "python_bin": "/usr/local/bin/python", + + "staging_dir": STAGING_DIR, + "out_run": OUT_RUN, + "weights": WEIGHTS, + "run_id_date": RUN_ID_DATE, + }, + env={"PYTHONUNBUFFERED": "1"}, + ) + + + crop = BashOperator( + task_id="crop", + bash_command=""" + set -euo pipefail + + PROJECT_ROOT='{{ params.project_root }}' + PY='{{ params.python_bin }}'; if ! command -v "$PY" >/dev/null 2>&1; then PY='python'; fi + OUT_LOCAL_CROP='{{ params.out_run }}/crop' + PWB_LOCAL='{{ params.out_run }}/pwb' + RUN_ID_DATE='{{ dag_run.conf.get("run_id") or logical_date.in_timezone("Asia/Jerusalem").strftime("%Y/%m/%d/%H%M") }}' + + RUN_ID_CROP="${RUN_ID_DATE}/crop" + + ENDPOINT_URL='{{ conn.minio_s3.extra_dejson.endpoint_url | default("http://host.docker.internal:9001") }}' + BUCKET='{{ var.value.leaf_minio_bucket | default("imagery") }}' + export AWS_ACCESS_KEY_ID='{{ conn.minio_s3.login }}' + export AWS_SECRET_ACCESS_KEY='{{ conn.minio_s3.password }}' + export AWS_DEFAULT_REGION='us-east-1' + export AWS_S3_FORCE_PATH_STYLE=true + + + export DEVICE_ID="${DEVICE_ID:-dev1}" + + mkdir -p "$OUT_LOCAL_CROP" + + # 1)crop + if [ -f "$PROJECT_ROOT/src/crop_only.py" ]; then + cd "$PROJECT_ROOT" + $PY src/crop_only.py --input "$PWB_LOCAL" --out "$OUT_LOCAL_CROP" + elif [ -f "$PROJECT_ROOT/src/crop_from_meta.py" ]; then + cd "$PROJECT_ROOT" + $PY src/crop_from_meta.py --input "$PWB_LOCAL" --out "$OUT_LOCAL_CROP" + else + echo "[crop] No crop script found; will only sync if $OUT_LOCAL_CROP has files." + fi + + # 2) (: _TZ[ _suffix].ext) + + python -m pip install -q pillow piexif || true + export OUT_LOCAL_CROP + python - <<'PY' +import os, re, sys, time +from datetime import datetime, timezone +OUT = os.environ.get("OUT_LOCAL_CROP", "") +DEVICE = os.environ.get("DEVICE_ID", "dev1") + +if not OUT or not os.path.isdir(OUT): + sys.exit(0) + +IMG_EXT = {".jpg",".jpeg",".png",".webp",".tif",".tiff",".bmp"} +iso_re = re.compile(r"^[A-Za-z0-9\-]+_\d{8}T\d{6}Z(?:[ _][^/\\\\]+)?\\.[A-Za-z0-9]+$") + +def get_ts_from_exif(path): + try: + import piexif + from PIL import Image + with Image.open(path) as im: + exif = im.info.get("exif") + if not exif: + return None + exif_dict = piexif.load(exif) + dt = exif_dict["Exif"].get(piexif.ExifIFD.DateTimeOriginal) or \ + exif_dict["Exif"].get(piexif.ExifIFD.DateTimeDigitized) or \ + exif_dict["0th"].get(piexif.ImageIFD.DateTime) + if not dt: + return None + # EXIF: "YYYY:MM:DD HH:MM:SS" + s = dt.decode() if isinstance(dt, bytes) else dt + dt_obj = datetime.strptime(s, "%Y:%m:%d %H:%M:%S").replace(tzinfo=timezone.utc) + return dt_obj + except Exception: + return None + +def ts_for_file(path): + dt = get_ts_from_exif(path) + if dt is None: + # fallback: mtime -UTC + mt = os.path.getmtime(path) + dt = datetime.fromtimestamp(mt, tz=timezone.utc) + return dt + +renamed = 0 +skipped = 0 +for root, _, files in os.walk(OUT): + for f in files: + ext = os.path.splitext(f)[1].lower() + if ext not in IMG_EXT: + continue + if iso_re.match(f): + skipped += 1 + continue + old = os.path.join(root, f) + dt = ts_for_file(old) + ts = dt.strftime("%Y%m%dT%H%M%SZ") + # suffix + base = os.path.splitext(f)[0] + suffix = "" + if base and base.lower() not in {"img","image","photo","dsc","dscn"}: + + cleaned = re.sub(r"[^A-Za-z0-9._-]+", "-", base).strip("-_.") + if cleaned and cleaned != ts: + suffix = f"_{cleaned}" + new_name = f"{DEVICE}_{ts}{suffix}{ext}" + new = os.path.join(root, new_name) + if new == old: + skipped += 1 + continue + + i = 1 + new_final = new + while os.path.exists(new_final): + new_final = os.path.join(root, f"{os.path.splitext(new_name)[0]}_{i}{ext}") + i += 1 + os.rename(old, new_final) + print(f"[crop][rename] {f} -> {os.path.basename(new_final)}") + renamed += 1 + +print(f"[crop][rename] done: renamed={renamed}, already_ok={skipped}") +PY + + # 3)MinIO + pip install -q awscli || true + if [ -d "$OUT_LOCAL_CROP" ] && [ "$(ls -A "$OUT_LOCAL_CROP" || true)" ]; then + python -m awscli s3 sync "$OUT_LOCAL_CROP"/ "s3://$BUCKET/leaves/$RUN_ID_CROP/" --endpoint-url "$ENDPOINT_URL" + else + echo "[crop] WARNING: no local crops found to upload." + fi + + python -m awscli s3 ls "s3://$BUCKET/leaves/$RUN_ID_CROP/" --recursive --endpoint-url "$ENDPOINT_URL" || true + """, + params={ + "project_root": PROJECT_ROOT, + "python_bin": PYTHON_BIN, + "out_run": OUT_RUN, + "run_id_date": RUN_ID_DATE, + }, + env={"PYTHONUNBUFFERED": "1"}, +) + + + detection_jobs = DockerOperator( + task_id="detection_jobs", + image="detection-jobs:cpu-lts", + docker_url="unix://var/run/docker.sock", + api_version="auto", + auto_remove=True, + mount_tmp_dir=False, + working_dir="/app", + network_mode="ag_cloud", + environment={ + "MINIO_ENDPOINT": "{{ conn.minio_s3.extra_dejson.endpoint_url | default('http://minio-hot:9001') }}", + "AWS_ACCESS_KEY_ID": "{{ conn.minio_s3.login }}", + "AWS_SECRET_ACCESS_KEY": "{{ conn.minio_s3.password }}", + "AWS_S3_FORCE_PATH_STYLE": "true", + "AWS_DEFAULT_REGION": "us-east-1", + "DATABASE_URL": "postgresql+psycopg2://missions_user:pg123@postgres:5432/missions_db", + "USER": "root", + "HOME": "/root", + }, + command=[ + "/bin/bash","-lc", r''' +set -euo pipefail +echo "[DJ] START"; whoami; pwd; python3 -V +python3 -m pip install --no-cache-dir -q awscli || true + +RID='{{ dag_run.conf.get("run_id") or logical_date.in_timezone("Asia/Jerusalem").strftime("%Y/%m/%d/%H%M") }}' +export MINIO_RID="$RID" +echo "[DJ] MINIO_RID=$MINIO_RID" +BUCKET='{{ var.value.leaf_minio_bucket | default("imagery") }}' +SRC="s3://${BUCKET}/leaves/${RID}/crop/" +ENDPOINT="${MINIO_ENDPOINT:-http://minio-hot:9001}" + +mkdir -p /work/in /work/out +echo "[DJ] sync from ${SRC} via ${ENDPOINT}" +python3 -m awscli s3 cp --recursive "$SRC" /work/in --endpoint-url "$ENDPOINT" || true + +IN_DIR="/work/in" +READY_DIR="/work/in_ready" +DEVICE_ID="${DEVICE_ID:-dev1}" +rm -rf "$READY_DIR" && mkdir -p "$READY_DIR" + +while IFS= read -r -d '' f; do + base="$(basename "$f")" + stem="$(printf '%s\n' "$base" | sed -n 's/^\([A-Za-z0-9-]\+_[0-9]\{8\}T[0-9]\{6\}Z\).*/\1/p')" + [ -n "$stem" ] || { echo "[DJ][skip] no stem in $base"; continue; } + outdir="$READY_DIR/$stem" + mkdir -p "$outdir" + cp -p "$f" "$outdir/$base" +done < <(find "$IN_DIR" -type f -print0) + +echo "[DJ][ready] tree under: $READY_DIR" +FLAT_DIR="/work/in_flat" +rm -rf "$FLAT_DIR" && mkdir -p "$FLAT_DIR" + +MANIFEST="$FLAT_DIR/_origin_map.tsv" +: > "$MANIFEST" + +find "$IN_DIR" -type f \( -iname '*.jpg' -o -iname '*.jpeg' -o -iname '*.png' -o -iname '*.webp' -o -iname '*.tif' -o -iname '*.tiff' -o -iname '*.bmp' \) -print0 \ +| while IFS= read -r -d '' f; do + base="$(basename "$f")" + parent="$(basename "$(dirname "$f")")" + out="$FLAT_DIR/$base"; i=1 + while [ -e "$out" ]; do + ext="${base##*.}"; stem="${base%.*}" + out="$FLAT_DIR/${stem}_$i.$ext"; i=$((i+1)) + done + cp -p "$f" "$out" + printf '%s\t%s\n' "$(basename "$out")" "$parent" >> "$MANIFEST" +done + +export ORIGIN_MANIFEST="$MANIFEST" +echo "[DJ] origin manifest at: $ORIGIN_MANIFEST (lines: $(wc -l < "$MANIFEST")))" + +ls -1 "$FLAT_DIR" | sed -n '1,50p' +export INPUT_DIR_FOR_RUNNER="$FLAT_DIR" +# === DB bootstrap: ensure required table exists === +python3 - <<'PY' +import os +from sqlalchemy import create_engine, text + + +ddl = """ +CREATE TABLE IF NOT EXISTS public.leaf_disease_types ( + id SERIAL PRIMARY KEY, + name TEXT UNIQUE NOT NULL +); + +CREATE TABLE IF NOT EXISTS public.leaf_reports ( + id BIGSERIAL PRIMARY KEY, + device_id TEXT NOT NULL, + leaf_disease_type_id INTEGER NOT NULL REFERENCES public.leaf_disease_types(id) ON DELETE RESTRICT, + ts TIMESTAMPTZ NOT NULL, + confidence DOUBLE PRECISION NOT NULL, + sick BOOLEAN NOT NULL +); + +CREATE INDEX IF NOT EXISTS ix_leaf_reports_ts ON public.leaf_reports (ts); +CREATE INDEX IF NOT EXISTS ix_leaf_reports_type ON public.leaf_reports (leaf_disease_type_id); +CREATE INDEX IF NOT EXISTS ix_leaf_reports_device_ts ON public.leaf_reports (device_id, ts); +""" + +url = os.environ["DATABASE_URL"] +eng = create_engine(url, future=True) +with eng.begin() as conn: + conn.execute(text(ddl)) +print("[DJ][db] ensured table public.leaf_disease_types") +PY + + +export PYTHONPATH=/app +python3 - <<'PY' +import os, sys, importlib +os.environ.setdefault("DATABASE_URL", os.environ.get("DATABASE_URL","")) +inp = os.environ.get('INPUT_DIR_FOR_RUNNER','/work/in_flat') +print("[DJ] runner input dir:", inp) + +try: + files = [f for f in os.listdir(inp) if os.path.isfile(os.path.join(inp,f))] + print(f"[DJ] flat file count: {len(files)}") + for f in files[:10]: + print("[DJ] sample:", f) +except Exception as e: + print("[DJ] listdir failed:", e) + +mod = importlib.import_module('agri_baseline.src.batch_runner') +sys.argv = ['batch_runner.py', '--input', inp, '--mission','1'] +exit_code = 0 +try: + mod.main() +except SystemExit as e: + exit_code = int(e.code) if isinstance(e.code, int) else 1 +sys.exit(exit_code) +PY + +echo "[DJ] DONE" + ''' + ], +) + + + + disease_monitor = DockerOperator( + task_id="disease_monitor", + image="disease-monitor:cpu-lts", + entrypoint=["/bin/sh","-c"], + command=[r''' +set -eu +echo "[DM] START"; whoami; pwd; python3 -V || true + +echo "[DM][env] DATABASE_URL=$DATABASE_URL" +echo "[DM][env] Dropping PG* env if present (to avoid overrides)" +unset PGHOST PGPORT PGDATABASE PGPASSWORD PGUSER 2>/dev/null || true + +# ---- DDL via DATABASE_URL only ---- +python3 - <<'PY' +import os, sys, time +import psycopg2 + +DDL = """ +CREATE TABLE IF NOT EXISTS alerts_leaves ( + id bigserial PRIMARY KEY, + entity_id text NOT NULL, + rule text NOT NULL, + window_start timestamptz NOT NULL, + window_end timestamptz NOT NULL, + score double precision NOT NULL, + first_seen timestamptz NOT NULL, + last_seen timestamptz NOT NULL, + status text NOT NULL CHECK (status IN ('OPEN','ACK','RESOLVED')), + meta_json jsonb +); +CREATE INDEX IF NOT EXISTS ix_alerts_leaves_entity_rule ON alerts_leaves(entity_id, rule); +CREATE INDEX IF NOT EXISTS ix_alerts_leaves_status ON alerts_leaves(status); +""" + +dsn = os.environ["DATABASE_URL"].replace("postgresql+psycopg2://", "postgresql://", 1) +print("[DM][db] Using DSN:", dsn.replace(os.environ.get("DATABASE_URL",""), "***redacted***")) + +for i in range(12): + try: + with psycopg2.connect(dsn, connect_timeout=4) as conn: + with conn.cursor() as cur: + cur.execute(DDL) + print("[DM][db] DDL applied OK.") + break + except Exception as e: + print(f"[DM][db] retry {i+1}/12: {e}") + time.sleep(5) +else: + sys.exit("[DM][db] DDL failed after retries") +PY + +exec python -m disease_monitor.cli --config /app/configs/config.docker.yaml --log-level INFO + +'''], + environment={ + "DATABASE_URL": "postgresql://missions_user:pg123@postgres:5432/missions_db", + }, + working_dir="/app", + docker_url="unix://var/run/docker.sock", + api_version="auto", + auto_remove=True, + network_mode="ag_cloud", + dag=dag, +) + + + + stage_input >> detect >> pwb >> crop >> detection_jobs>>disease_monitor diff --git a/airflow_bundle/leaf-pipeline/airflow/webserver_config.py b/airflow_bundle/leaf-pipeline/airflow/webserver_config.py new file mode 100644 index 000000000..3048bb21f --- /dev/null +++ b/airflow_bundle/leaf-pipeline/airflow/webserver_config.py @@ -0,0 +1,132 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +"""Default configuration for the Airflow webserver.""" + +from __future__ import annotations + +import os + +from flask_appbuilder.const import AUTH_DB + +# from airflow.www.fab_security.manager import AUTH_LDAP +# from airflow.www.fab_security.manager import AUTH_OAUTH +# from airflow.www.fab_security.manager import AUTH_OID +# from airflow.www.fab_security.manager import AUTH_REMOTE_USER + + +basedir = os.path.abspath(os.path.dirname(__file__)) + +# Flask-WTF flag for CSRF +WTF_CSRF_ENABLED = True +WTF_CSRF_TIME_LIMIT = None + +# ---------------------------------------------------- +# AUTHENTICATION CONFIG +# ---------------------------------------------------- +# For details on how to set up each of the following authentication, see +# http://flask-appbuilder.readthedocs.io/en/latest/security.html# authentication-methods +# for details. + +# The authentication type +# AUTH_OID : Is for OpenID +# AUTH_DB : Is for database +# AUTH_LDAP : Is for LDAP +# AUTH_REMOTE_USER : Is for using REMOTE_USER from web server +# AUTH_OAUTH : Is for OAuth +AUTH_TYPE = AUTH_DB + +# Uncomment to setup Full admin role name +# AUTH_ROLE_ADMIN = 'Admin' + +# Uncomment and set to desired role to enable access without authentication +# AUTH_ROLE_PUBLIC = 'Viewer' + +# Will allow user self registration +# AUTH_USER_REGISTRATION = True + +# The recaptcha it's automatically enabled for user self registration is active and the keys are necessary +# RECAPTCHA_PRIVATE_KEY = PRIVATE_KEY +# RECAPTCHA_PUBLIC_KEY = PUBLIC_KEY + +# Config for Flask-Mail necessary for user self registration +# MAIL_SERVER = 'smtp.gmail.com' +# MAIL_USE_TLS = True +# MAIL_USERNAME = 'yourappemail@gmail.com' +# MAIL_PASSWORD = 'passwordformail' +# MAIL_DEFAULT_SENDER = 'sender@gmail.com' + +# The default user self registration role +# AUTH_USER_REGISTRATION_ROLE = "Public" + +# When using OAuth Auth, uncomment to setup provider(s) info +# Google OAuth example: +# OAUTH_PROVIDERS = [{ +# 'name':'google', +# 'token_key':'access_token', +# 'icon':'fa-google', +# 'remote_app': { +# 'api_base_url':'https://www.googleapis.com/oauth2/v2/', +# 'client_kwargs':{ +# 'scope': 'email profile' +# }, +# 'access_token_url':'https://accounts.google.com/o/oauth2/token', +# 'authorize_url':'https://accounts.google.com/o/oauth2/auth', +# 'request_token_url': None, +# 'client_id': GOOGLE_KEY, +# 'client_secret': GOOGLE_SECRET_KEY, +# } +# }] + +# When using LDAP Auth, setup the ldap server +# AUTH_LDAP_SERVER = "ldap://ldapserver.new" + +# When using OpenID Auth, uncomment to setup OpenID providers. +# example for OpenID authentication +# OPENID_PROVIDERS = [ +# { 'name': 'Yahoo', 'url': 'https://me.yahoo.com' }, +# { 'name': 'AOL', 'url': 'http://openid.aol.com/' }, +# { 'name': 'Flickr', 'url': 'http://www.flickr.com/' }, +# { 'name': 'MyOpenID', 'url': 'https://www.myopenid.com' }] + +# ---------------------------------------------------- +# Theme CONFIG +# ---------------------------------------------------- +# Flask App Builder comes up with a number of predefined themes +# that you can use for Apache Airflow. +# http://flask-appbuilder.readthedocs.io/en/latest/customizing.html#changing-themes +# Please make sure to remove "navbar_color" configuration from airflow.cfg +# in order to fully utilize the theme. (or use that property in conjunction with theme) +# APP_THEME = "bootstrap-theme.css" # default bootstrap +# APP_THEME = "amelia.css" +# APP_THEME = "cerulean.css" +# APP_THEME = "cosmo.css" +# APP_THEME = "cyborg.css" +# APP_THEME = "darkly.css" +# APP_THEME = "flatly.css" +# APP_THEME = "journal.css" +# APP_THEME = "lumen.css" +# APP_THEME = "paper.css" +# APP_THEME = "readable.css" +# APP_THEME = "sandstone.css" +# APP_THEME = "simplex.css" +# APP_THEME = "slate.css" +# APP_THEME = "solar.css" +# APP_THEME = "spacelab.css" +# APP_THEME = "superhero.css" +# APP_THEME = "united.css" +# APP_THEME = "yeti.css" diff --git a/airflow_bundle/leaf-pipeline/dags/configs/disease_monitor.yaml b/airflow_bundle/leaf-pipeline/dags/configs/disease_monitor.yaml new file mode 100644 index 000000000..832d6daf7 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/dags/configs/disease_monitor.yaml @@ -0,0 +1,68 @@ +io: + # IMPORTANT: use the Docker service name of Postgres (from your compose): + postgres_url: "postgresql+psycopg2://missions_user:pg123@postgres:5432/missions_db" + +windows: + frequency: "D" + timezone: "UTC" + +source_mapping: + entity_dim: "device" + area_strategy: "none" # or "region_area" (requires regions table/geom) + filters: + start_time: null + end_time: null + anomaly_codes: null + +baseline: + method: "median" + lookback_periods: 28 + min_history: 7 + seasonality: null + +rules: + count_anomaly: + enabled: true + method: "zscore" + z_threshold: 3.0 + iqr_k: 1.5 + min_count: 3 + worsening: + enabled: true + method: "slope" + slope_lookback: 7 + slope_min: 0.02 + min_periods: 5 + ewma_span: 7 + ewma_threshold: 0.6 + +alerting: + dedup_cooldown_windows: 3 + resolve_after_no_anomaly: 3 + rate_limit_per_run: 100 + group_by_window: true + +delivery: + kafka: + enabled: false + brokers: "kafka:9092" + topic: "alerts" + slack: + enabled: false + webhook_url: "" + webhook: + enabled: false + url: "" + headers: {} + email: + enabled: false + smtp_host: "" + smtp_port: 587 + username: "" + password_env: "SMTP_PASSWORD" + from_addr: "" + to_addrs: [] + +run: + dry_run: false + diff --git a/airflow_bundle/leaf-pipeline/docker-compose.yml b/airflow_bundle/leaf-pipeline/docker-compose.yml new file mode 100644 index 000000000..5ededec6f --- /dev/null +++ b/airflow_bundle/leaf-pipeline/docker-compose.yml @@ -0,0 +1,73 @@ + +version: "3.8" + +x-airflow-common: &airflow-common + image: leaf-airflow:2.9.3-fixed + build: + context: . + dockerfile: Dockerfile + environment: + AIRFLOW__CORE__LOAD_EXAMPLES: "False" + AIRFLOW__CORE__EXECUTOR: "SequentialExecutor" + AIRFLOW_HOME: /opt/airflow + LEAF_MINIO_ENDPOINT: "http://minio-hot:9000" + volumes: + - ./airflow:/opt/airflow + - ./projects/leaf-counting:/opt/leaf-pipeline/projects/leaf-counting + - /var/run/docker.sock:/var/run/docker.sock + user: "${AIRFLOW_UID:-50000}:${AIRFLOW_GID:-0}" + restart: unless-stopped + +services: + # --- Build-only images for DockerOperator tasks (exit 0 right away) --- + build_detection_jobs: + profiles: ["images"] + image: detection-jobs:cpu-lts + build: + context: ./projects/Detection_Jobs/Detection_Jobs + dockerfile: dockerfile + command: ["sh", "-c", "echo built detection-jobs && true"] + restart: "no" + networks: [agcloud_ag_cloud] + + build_disease_monitor: + profiles: ["images"] + image: disease-monitor:cpu-lts + build: + context: ./projects/disease-monitor/disease-monitor + dockerfile: Dockerfile + entrypoint: ["/bin/sh", "-c"] + command: ["sh", "-c", "echo built disease-monitor && true"] + restart: "no" + networks: [agcloud_ag_cloud] + + # --- Airflow runtime --- + scheduler: + <<: *airflow-common + command: ["airflow", "scheduler"] + user: "0:0" + depends_on: + build_detection_jobs: + condition: service_completed_successfully + build_disease_monitor: + condition: service_completed_successfully + networks: [agcloud_ag_cloud] + + webserver: + <<: *airflow-common + command: ["airflow", "webserver"] + user: "0:0" + ports: + - "8081:8080" + depends_on: + scheduler: + condition: service_started + build_detection_jobs: + condition: service_completed_successfully + build_disease_monitor: + condition: service_completed_successfully + networks: [agcloud_ag_cloud] + +networks: + agcloud_ag_cloud: + external: true diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/.gitignore b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/.gitignore new file mode 100644 index 000000000..ffc9f8e27 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/.gitignore @@ -0,0 +1,53 @@ +# ==== OS / IDE ==== +.DS_Store +Thumbs.db +.vscode/ +.idea/ + +# ==== Node ==== +node_modules/ +dist/ + +# ==== Python ==== +__pycache__/ +*.py[cod] +*.pyc +*.pyo +*.so +*.dylib + +# ==== Virtual envs ==== +.venv/ +venv/ +ENV/ +env/ + +# ==== Packaging / build ==== +build/ +*.egg-info/ + +# ==== Environment / Secrets ==== +.env +.env.* + +# ==== Data / Notebooks / Logs ==== +*.log +*.ipynb +.ipynb_checkpoints/ + +# ==== Artifacts / Wheels / Models ==== +artifacts/ +.wheels/ +wheels/ +*.whl +*.pt +*.pth +*.bin + +.pytest_cache/ +.coverage +coverage.xml +htmlcov/ + +server/embed_pb2.py +server/embed_pb2_grpc.py diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/.dockerignore b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/.dockerignore new file mode 100644 index 000000000..641f56876 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/.dockerignore @@ -0,0 +1,33 @@ +# Python cache +__pycache__/ +*.pyc +*.pyo + +# Virtual environments +.env +.venv/ +venv/ + +# IDE +.idea/ +.vscode/ + +# Node / Frontend +node_modules/ +dist/ + +# Test / Coverage +.pytest_cache/ +.coverage +coverage.xml +htmlcov/ + +# Local databases +*.db +agri.db + +# Data outputs +data/ +data_balanced/ +data_baseline/ +*.csv diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/.gitignore b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/.gitignore new file mode 100644 index 000000000..b0e9b0028 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/.gitignore @@ -0,0 +1,25 @@ +# === Python cache === +__pycache__/ +*.pyc +*.pyo + +# === Virtual environments === +.env +.venv/ +venv/ + +# === IDE / Editors === +.idea/ +.vscode/ + + +# === Test / Coverage === +.pytest_cache/ + +# === Local databases === +*.db +agri.db + +# === Data outputs === +data_balanced/ +data/ \ No newline at end of file diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/README.md b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/README.md new file mode 100644 index 000000000..b2e46aec5 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/README.md @@ -0,0 +1,115 @@ +🌿 Agri Baseline – Disease Detection Pipeline + +This project runs an end-to-end disease detection pipeline for agricultural images. +It supports both local and MinIO-based storage backends, and processes entire folders of plant images using trained CNN models. + +🚀 Quick Start +1️⃣ Setup Environment +cp agri_baseline/.env.example agri_baseline/.env +pip install -r agri_baseline/requirements.txt + +2️⃣ Run the Pipeline + +Now the pipeline fetches images directly from MinIO, not from a local folder. + +docker compose up -d +docker compose logs -f app + + +The service automatically connects to your configured MinIO bucket, downloads the images to a cache directory, and processes them. + +3️⃣ Run Tests + +To verify the system: + +docker compose run --rm app pytest -q + +📂 Project Structure +Detection_Jobs/ +│ +├── agri_baseline/ +│ ├── scripts/ +│ │ └── run_batch.py # Run the pipeline on MinIO or local images +│ │ +│ ├── src/ +│ │ ├── detectors/ # CNN models and detectors +│ │ │ ├── base.py # Base Detector/Detection classes +│ │ │ ├── cnn_multi_classifier.py +│ │ │ ├── disease_model.py # Wraps CNN model as a Detector +│ │ │ ├── train/ +│ │ │ │ └── dictionary.py +│ │ │ +│ │ ├── pipeline/ +│ │ │ ├── config.py +│ │ │ ├── db.py # DB connection via SQLAlchemy +│ │ │ ├── logging_setup.py +│ │ │ └── utils.py # Helper functions (image loading, bbox, etc.) +│ │ │ +│ │ ├── storage/ +│ │ │ ├── minio_client.py +│ │ │ └── minio_sync.py # MinIO download helpers +│ │ │ +│ │ └── validator/ +│ │ ├── rules.py # Validation rules +│ │ └── validator.py # QA manager, writes to event logs +│ │ +│ ├── batch_runner.py # Orchestrates the full pipeline +│ ├── .env # Local config (not committed) +│ ├── .env.example # Example configuration file +│ ├── requirements.txt # Python dependencies +│ └── README.md +│ +├── models/ # Trained model weights (not in git) +│ ├── resnet18-f37072fd.pth +│ ├── cnn_multi_stage3.pth +│ └── multi_classes.pth +│ +├── docker-compose.yml # Runs pipeline + MinIO connection +├── dockerfile +├── tests/ # Unit and integration tests +│ ├── test_batch_runner.py +│ ├── test_disease_model.py +│ ├── test_run_detectors.py +│ ├── test_utils.py +│ └── test_validator.py +│ +└── ressearch/ # Experimental models and training + ├── detectors/ + │ ├── models/ + │ │ ├── cnn_binary.pth + │ │ ├── cnn_multi_finetuned.pth + │ │ └── cnn_multi.pth + │ ├── train/ + │ │ ├── disease.py + │ │ ├── eval_multi_levels.py + │ │ ├── finetune_multi_stage3.py + │ │ ├── finetune_multi.py + │ │ └── train_binary_multi.py + │ ├── cnn_binary_classifier.py + │ └── dataset_binary.py + +🧩 Models + +All trained models are stored under models/ and are not committed to Git: + +cnn_multi.pth – Base multi-class CNN + +cnn_multi_finetuned.pth – Fine-tuned on additional data + +cnn_multi_stage3.pth – Advanced fine-tuning with crop-specific data + +multi_classes.pth – Unified class mapping + +🧪 Testing + +Run all integration and unit tests using Docker: + +docker compose run --rm app pytest -q + +📌 Notes + +The pipeline now supports MinIO integration via environment variables in .env. + +Make sure your .env file includes all required MINIO_* variables (endpoint, bucket, credentials). + +Avoid committing .env or model files to the repository. \ No newline at end of file diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/__init__.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/__init__.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/requirements.txt b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/requirements.txt new file mode 100644 index 000000000..8df4df0ba --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/requirements.txt @@ -0,0 +1,47 @@ +# ---------------------------- +# Core scientific stack +# ---------------------------- +numpy==1.26.4 +pandas==2.0.3 +scipy==1.12.0 + +# ---------------------------- +# Image processing +# ---------------------------- +opencv-python-headless==4.9.0.80 +Pillow==10.4.0 +albumentations==1.4.3 + +# ---------------------------- +# Database & configuration +# ---------------------------- +SQLAlchemy==1.4.52 +psycopg2-binary==2.9.9 +python-dotenv==1.0.1 +minio==7.2.9 # MinIO SDK for connecting to object storage + +# ---------------------------- +# Testing +# ---------------------------- +pytest + +# ---------------------------- +# Typing helpers +# ---------------------------- +typing-extensions>=4.9.0 +# Deep learning frameworks +torch==2.2.0 +torchvision==0.17.0 +torchaudio==2.2.0 + + +# ---------------------------- +# Training & monitoring tools +# ---------------------------- +tensorboard>=2.16 + +# ---------------------------- +# Visualization & ML utilities +# ---------------------------- +matplotlib>=3.7 +scikit-learn>=1.3 diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/scripts/__init__.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/scripts/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/scripts/run_batch.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/scripts/run_batch.py new file mode 100644 index 000000000..666ed466e --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/scripts/run_batch.py @@ -0,0 +1,137 @@ +""" +run_batch.py + +Purpose: +- Run the disease-detection batch pipeline either from a LOCAL folder of images + or from a MinIO bucket (objects are first downloaded to a local cache dir, + then processed exactly like local files). + +Usage examples: +1) Local folder (backward-compatible): + python -m agri_baseline.scripts.run_batch --storage local --images ./data/images + +2) MinIO (reads config from ENV and optional CLI flags): + python -m agri_baseline.scripts.run_batch --storage minio --minio-prefix "" + +Environment variables (typical .env): +- STORAGE_BACKEND=minio|local +- MINIO_ENDPOINT=127.0.0.1:9000 +- MINIO_ACCESS_KEY=minioadmin +- MINIO_SECRET_KEY=minioadmin +- MINIO_BUCKET=leaves +- MINIO_SECURE=false +- MINIO_PREFIX=mission-123/ (optional) +- MINIO_CACHE_DIR=./data/_minio_cache +""" + +import argparse +import os +from pathlib import Path + +from agri_baseline.src.pipeline.logging_setup import setup_logging +from agri_baseline.src.pipeline import config +from agri_baseline.src.batch_runner import BatchRunner + +# MinIO helpers provided in your project +from agri_baseline.src.storage.minio_client import load_minio_config # loads config from ENV +from agri_baseline.src.storage.minio_sync import download_prefix_to_dir, ensure_bucket + + +def run_local(images_dir: Path) -> None: + """ + LOCAL mode: + - Run the batch pipeline over a local folder of images. + - This preserves the original behavior for backward compatibility. + """ + runner = BatchRunner() + runner.run_folder(images_dir) + + +def run_minio(prefix: str, cache_dir: Path) -> None: + """ + MINIO mode: + - Pull objects from a MinIO bucket (based on ENV config). + - Download them to a local cache directory. + - Run the batch pipeline over the downloaded files. + """ + cfg = load_minio_config() + ensure_bucket(cfg) # Safety: create the bucket if it doesn't exist + + cache_dir.mkdir(parents=True, exist_ok=True) + + # Download objects under 'prefix' into the local cache folder + downloaded = download_prefix_to_dir(cfg, prefix=prefix, local_dir=cache_dir) + if not downloaded: + raise SystemExit( + f"No objects found in bucket '{cfg.bucket}' with prefix '{prefix}'." + ) + + runner = BatchRunner() + runner.run_folder(cache_dir) + + +def parse_args() -> argparse.Namespace: + """ + Parse CLI arguments and provide sensible defaults from ENV where applicable. + """ + ap = argparse.ArgumentParser(description="Run batch pipeline (local/minio).") + + # Backward-compatible local images folder + ap.add_argument( + "--images", + default=config.IMAGES_DIR, + help="Folder of input images (LOCAL mode)", + ) + + # Storage backend selector + ap.add_argument( + "--storage", + choices=["local", "minio"], + default=os.getenv("STORAGE_BACKEND", "local").lower(), + help="Where to read images from (local|minio).", + ) + + # MinIO options (with ENV fallbacks) + ap.add_argument( + "--minio-prefix", + default=os.getenv("MINIO_PREFIX", ""), + help="Object prefix inside the bucket (e.g. 'mission-123/').", + ) + ap.add_argument( + "--minio-cache", + default=os.getenv("MINIO_CACHE_DIR", "./data/_minio_cache"), + help="Local temp folder used to download MinIO objects before processing.", + ) + + return ap.parse_args() + + +def main() -> None: + """ + Entry point: + - Logs chosen backend. + - Dispatches to local/minio flows. + - Keeps logs concise and informative for CI/ops. + """ + log = setup_logging() + args = parse_args() + + log.info(f"Storage backend: {args.storage}") + + if args.storage == "local": + images_dir = Path(args.images) + log.info(f"Starting batch over LOCAL folder: {images_dir}") + run_local(images_dir) + log.info("Batch done (local).") + else: + cache_dir = Path(args.minio_cache) + log.info( + "Starting batch over MINIO: " + f"bucket from ENV, prefix='{args.minio_prefix}', cache='{cache_dir}'" + ) + run_minio(prefix=args.minio_prefix, cache_dir=cache_dir) + log.info("Batch done (minio).") + + +if __name__ == "__main__": + main() diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/__init__.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/batch_runner.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/batch_runner.py new file mode 100644 index 000000000..56575d206 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/batch_runner.py @@ -0,0 +1,514 @@ +from __future__ import annotations + +from sqlalchemy import text +import os +import re +import json +from dataclasses import asdict, is_dataclass +from datetime import datetime, timezone, timedelta +from pathlib import Path +from typing import Tuple +from zoneinfo import ZoneInfo + +from agri_baseline.src.pipeline.utils import ( + load_image, + image_id_from_path, + clamp_bbox, +) +from agri_baseline.src.pipeline.db import ( + get_engine, +) +from agri_baseline.src.detectors.disease_model import DiseaseDetector + +# ----------------------------------- +# SQL +# ----------------------------------- + +# anomalies insert (unchanged) +INSERT_ANOMALY = text( + """ + INSERT INTO public.anomalies + (mission_id, device_id, ts, anomaly_type_id, severity, details, geom) + VALUES + ( + :mission_id, + :device_id, + :ts, + :anomaly_type_id, + :severity, + CAST(:details AS JSONB), + ST_SetSRID(ST_GeomFromText(:wkt_geom), 4326) + ) + """ +) + +# NEW: leaf_reports insert (always written) +INSERT_LEAF_REPORT = text( + """ + INSERT INTO public.leaf_reports + (device_id, leaf_disease_type_id, ts, confidence, sick) + VALUES + (:device_id, :leaf_disease_type_id, :ts, :confidence, :sick) + """ +) + +# NEW: upsert/get id for leaf_disease_types by name (case-insensitive) +UPSERT_LEAF_DISEASE_TYPE = text( + """ + WITH ins AS ( + INSERT INTO public.leaf_disease_types (name) + VALUES (:name) + ON CONFLICT (name) DO UPDATE SET name = EXCLUDED.name + RETURNING id + ) + SELECT id FROM ins + UNION ALL + SELECT id FROM public.leaf_disease_types WHERE name = :name + LIMIT 1 + """ +) + +INSERT_MISSION_FULL = text( + """ + INSERT INTO public.missions (mission_id, start_time, end_time, area_geom) + VALUES ( + :mission_id, + :start_time, + :end_time, + ST_SetSRID(ST_GeomFromText(:wkt_poly), 4326) + ) + ON CONFLICT (mission_id) DO NOTHING + """ +) + + +class BatchRunner: + """ + End-to-end runner: + - Parse device & timestamp from file name: _TZ[ _suffix].ext + - Run disease detector + - ALWAYS write a row into public.leaf_reports for each detection + - Write into public.anomalies ONLY if label is 'sick' (i.e., does NOT contain 'healthy') + - Ensure supporting FKs exist (devices:, missions: fixed 60, leaf_disease_types:) + + Notes: + * mission_id is fixed to 60 per requirement. + * geom is the pixel-center point of the detection bbox (WKT, SRID 4326). + """ + + # Fixed mission per request + FIXED_MISSION_ID = 60 + + def __init__(self, mission_id: int | None = None, device_id: str = "device-1") -> None: + # mission_id ignored; always use 60, but keep signature for CLI compatibility + self.mission_id = BatchRunner.FIXED_MISSION_ID + self.fallback_device_id = device_id # used only if filename parsing fails + self.engine = get_engine() + self.detector = DiseaseDetector() + self.origin_map = self._load_origin_map(os.getenv("ORIGIN_MANIFEST")) + + # anomaly_types entry for LEAF_DISEASE (used only for anomalies table) + self.leaf_anomaly_type_id = self._ensure_anomaly_type( + code="LEAF_DISEASE", description="Leaf disease detected" + ) + + # ---------------------------- + # Public API + # ---------------------------- + @staticmethod + def _load_origin_map(path: str | None) -> dict[str, str]: + + mapping: dict[str, str] = {} + if not path or not os.path.exists(path): + return mapping + try: + with open(path, "r", encoding="utf-8") as f: + for line in f: + line = line.rstrip("\n") + if not line or "\t" not in line: + continue + fname, inner = line.split("\t", 1) + if fname and inner: + mapping[fname] = inner + except Exception: + pass + return mapping + + @staticmethod + def _parse_device_and_ts_from_name(img_path: Path) -> tuple[str, datetime]: + """ + Accepts: + _TZ. + _TZ_. + Returns (device_id, ts_utc). Raises ValueError if the pattern doesn't match. + """ + stem = img_path.stem + parts = stem.split("_") + if len(parts) < 2: + raise ValueError( + f"Filename '{img_path.name}' must be '_TZ[ _suffix].ext'" + ) + device = parts[0] + ts_str = parts[1] + if not re.fullmatch(r"\d{8}T\d{6}Z", ts_str): + raise ValueError( + f"Filename '{img_path.name}' must include timestamp as TZ" + ) + ts = datetime.strptime(ts_str, "%Y%m%dT%H%M%SZ").replace(tzinfo=timezone.utc) + return device, ts + + def run_folder(self, folder: Path | str) -> None: + """ + Run pipeline on all images within a folder (non-recursive). + """ + folder = Path(folder) + assert folder.exists(), f"Folder not found: {folder.resolve()}" + + image_paths = sorted( + p for p in folder.iterdir() if p.suffix.lower() in {".jpg", ".jpeg", ".png"} + ) + + total, total_dets = 0, 0 + for img_path in image_paths: + try: + n = self.process_image(img_path) + total += 1 + total_dets += n + except Exception as ex: + print(f"[WARN] Failed on {img_path.name}: {ex}") + + print(f"Processed {total} images, wrote {total_dets} detections") + + def process_image(self, img_path: Path | str) -> int: + """ + Run pipeline on a single image and insert rows into leaf_reports (always) + and anomalies (only if sick). Returns number of detections processed. + """ + img_path = Path(img_path) + + source_path = str(img_path.resolve()) + + # img_path = Path(img_path) + +# Parse from filename (with fallback for your current crop file names) + try: + device_id, det_ts = self._parse_device_and_ts_from_name(img_path) + except Exception: + device_id = self.fallback_device_id + # timestamp: file mtime if available, otherwise now (UTC) + try: + det_ts = datetime.fromtimestamp(img_path.stat().st_mtime, tz=timezone.utc) + except Exception: + det_ts = datetime.now(timezone.utc) + + + device_id, det_ts = self._parse_device_and_ts_from_name(img_path) + + + local_tz = os.getenv("LOCAL_TZ", "Asia/Jerusalem") + ts_local = det_ts.astimezone(ZoneInfo(local_tz)) + date_path = ts_local.strftime("%Y/%m/%d") # YYYY/MM/DD + + + rid_env = (os.getenv("MINIO_RID") or os.getenv("RID") or "").strip("/") + date_path = None + run_id = None + if rid_env: + parts = rid_env.split("/") + if len(parts) == 4 and all(parts): + y, m, d, hhmm = parts + date_path = f"{y}/{m}/{d}" + run_id = hhmm + + + if not date_path or not run_id: + local_tz = os.getenv("LOCAL_TZ", "Asia/Jerusalem") + ts_local = det_ts.astimezone(ZoneInfo(local_tz)) + date_path = ts_local.strftime("%Y/%m/%d") # YYYY/MM/DD + run_id = os.getenv("RUN_ID") or os.getenv("MINIO_RUN_ID") + if not run_id: + mp = (os.getenv("MINIO_PREFIX") or "").strip("/") + last = mp.split("/")[-1] if mp else "" + if last and len(last) == 4 and last.isdigit(): + run_id = last + if not run_id: + run_id = ts_local.strftime("%H%M") + + bucket = os.getenv("MINIO_BUCKET", "imagery") + prefix_root = os.getenv("MINIO_PREFIX_ROOT", "leaves") + + # Ensure FKs exist + self._ensure_device(device_id) + self._ensure_mission_full(self.mission_id, det_ts) + + # Load image & run detector + img, W, H = load_image(img_path) + image_id = image_id_from_path(img_path) + dets = self.detector.run(img) + + print(f"{image_id}: found {len(dets)} detections") + + written = 0 + for d in dets: + x, y, w, h = self._extract_bbox(d) + x, y, w, h = clamp_bbox(int(x), int(y), int(w), int(h), W, H) + cx = x + w / 2.0 + cy = y + h / 2.0 + + area = float(getattr(d, "area", w * h)) + label = str(getattr(d, "label", "disease")) + conf = float(getattr(d, "confidence", 1.0)) + + # key imagery/leaves/YYYY/MM/DD/RUNID/crop/leaf{index}/ + # leaf_folder = f"leaf{written + 1}" + # minio_key = f"{bucket}/{prefix_root}/{date_path}/{run_id}/crop/{leaf_folder}/{img_path.name}" + # minio_url = self._minio_url_from_key(minio_key) + inner_dir = self.origin_map.get(img_path.name) + + if inner_dir: + minio_key = f"{bucket}/{prefix_root}/{date_path}/{run_id}/crop/{inner_dir}/{img_path.name}" + else: + minio_key = f"{bucket}/{prefix_root}/{date_path}/{run_id}/crop/{img_path.name}" + + minio_url = self._minio_url_from_key(minio_key) + + # Build details JSON (used only in anomalies) + details = { + "image_id": image_id, + "label": label, + "bbox": [x, y, w, h], + "area": area, + "confidence": conf, + "device_id": device_id, + "ts": det_ts.isoformat(), + "source_path": source_path, + "minio_key": minio_key, + } + if minio_url: + details["minio_url"] = minio_url + details.setdefault("crop_type", None) + details.setdefault("disease_type", label) + if is_dataclass(d): + details["raw_detection"] = asdict(d) + + # Decide sick/healthy by label + sick = not self._is_healthy_label(label) + + # Map label → disease_type_name (part after "__" if present) + disease_type_name = self._disease_type_from_label(label) + + with self.engine.begin() as conn: + # ensure disease type exists and get id + leaf_type_id = self._ensure_leaf_disease_type(conn, disease_type_name) + + # 1) ALWAYS insert a leaf report + conn.execute( + INSERT_LEAF_REPORT, + dict( + device_id=device_id, + leaf_disease_type_id=leaf_type_id, + ts=det_ts, + confidence=conf, + sick=sick, + ), + ) + + # 2) Insert anomaly ONLY if sick + if sick: + conn.execute( + INSERT_ANOMALY, + dict( + mission_id=self.mission_id, + device_id=device_id, + ts=det_ts, + anomaly_type_id=self.leaf_anomaly_type_id, + severity=conf, + details=json.dumps(details), + wkt_geom=f"POINT({cx} {cy})", + ), + ) + + written += 1 + + return written + + # ---------------------------- + # Internals + # ---------------------------- + + @staticmethod + def _is_healthy_label(label: str) -> bool: + """Return True if label contains 'healthy' (case-insensitive).""" + return "healthy" in label.lower() + + @staticmethod + def _disease_type_from_label(label: str) -> str: + """ + Extract disease type token from label. If label contains 'a__b', return 'b'; else return label. + Keeps underscores as-is for consistency with the model outputs. + """ + if "__" in label: + return label.split("__", 1)[1] + return label + + def _ensure_anomaly_type(self, code: str, description: str) -> int: + """Return anomaly_type_id for `code`, inserting if needed (idempotent).""" + with self.engine.begin() as conn: + row = conn.execute( + text("SELECT anomaly_type_id FROM public.anomaly_types WHERE code = :c"), + {"c": code}, + ).first() + if row: + return int(row[0]) + + row = conn.execute( + text( + """ + INSERT INTO public.anomaly_types (code, description) + VALUES (:c, :d) + ON CONFLICT (code) + DO UPDATE SET description = EXCLUDED.description + RETURNING anomaly_type_id + """ + ), + {"c": code, "d": description}, + ).first() + return int(row[0]) + + def _ensure_leaf_disease_type(self, conn, name: str) -> int: + """ + Ensure a row exists in public.leaf_disease_types for the given name and return its id. + Uses an upsert with RETURNING to be idempotent. + """ + row = conn.execute(UPSERT_LEAF_DISEASE_TYPE, {"name": name}).first() + return int(row[0]) + + def _ensure_device(self, device_id: str) -> None: + """Ensure a row exists in public.devices (TEXT PK/UNIQUE).""" + with self.engine.begin() as conn: + conn.execute( + text( + """ + INSERT INTO public.devices (device_id) + VALUES (:d) + ON CONFLICT (device_id) DO NOTHING + """ + ), + {"d": device_id}, + ) + + def _ensure_mission_full(self, mission_id: int, ts: datetime) -> None: + """ + Ensure mission row exists and matches your table shape. + If not exists: start_time=ts, end_time=ts+1h, area=default 1x1° square near (0,0). + """ + with self.engine.begin() as conn: + exists = conn.execute( + text("SELECT 1 FROM public.missions WHERE mission_id = :id"), + {"id": mission_id}, + ).first() + if exists: + return + start = ts + end = ts + timedelta(hours=1) + wkt_poly = "POLYGON((0 0, 1 0, 1 1, 0 1, 0 0))" + conn.execute( + INSERT_MISSION_FULL, + { + "mission_id": mission_id, + "start_time": start, + "end_time": end, + "wkt_poly": wkt_poly, + }, + ) + + @staticmethod + def _extract_bbox(d) -> Tuple[float, float, float, float]: + """ + Normalize bbox to (x, y, w, h). Supports multiple field layouts. + """ + if all(hasattr(d, a) for a in ("x", "y", "w", "h")): + return float(d.x), float(d.y), float(d.w), float(d.h) + + if hasattr(d, "bbox"): + bx = list(d.bbox) + if len(bx) != 4: + raise ValueError(f"Unexpected bbox length: {len(bx)} in {bx}") + x, y, w, h = map(float, bx) + return x, y, w, h + + if all(hasattr(d, a) for a in ("xmin", "ymin", "xmax", "ymax")): + x1, y1, x2, y2 = float(d.xmin), float(d.ymin), float(d.xmax), float(d.ymax) + return x1, y1, max(0.0, x2 - y1), max(0.0, y2 - y1) + + if all(hasattr(d, a) for a in ("left", "top", "width", "height")): + return float(d.left), float(d.top), float(d.width), float(d.height) + + raise AttributeError( + "Detection bbox fields missing. Supported: " + "(x,y,w,h) or bbox or (xmin,ymin,xmax,ymax) or (left,top,width,height)." + ) + + @staticmethod + def _minio_url_from_key(key: str) -> str | None: + + endpoint = os.getenv("MINIO_ENDPOINT") + bucket = os.getenv("MINIO_BUCKET") + if not endpoint or not bucket: + return None + endpoint = endpoint.rstrip("/") + + if key.startswith(f"{bucket}/"): + return f"{endpoint}/{key}" + return f"{endpoint}/{bucket}/{key}" + + @staticmethod + def _minio_key_from_source_path(source_path: str) -> str: + + prefix = os.getenv("MINIO_PREFIX", "").strip("/") + posix = source_path.replace("\\", "/") + posix = posix.lstrip("/") + return f"{prefix}/{posix}" if prefix else posix + + @staticmethod + def _minio_url(img_path: Path) -> str | None: + """ + Build a MinIO object URL if MINIO_* env vars are provided. + """ + endpoint = os.getenv("MINIO_ENDPOINT") + bucket = os.getenv("MINIO_BUCKET") + prefix = os.getenv("MINIO_PREFIX", "").strip("/") + if not endpoint or not bucket: + return None + endpoint = endpoint.rstrip("/") + key = f"{prefix}/{img_path.name}" if prefix else img_path.name + return f"{endpoint}/{bucket}/{key}" + + +# ------------- CLI helper ------------- + +def main() -> None: + """ + Local runner: + python -m agri_baseline.src.batch_runner --input + """ + import argparse + + parser = argparse.ArgumentParser( + description="Run disease detection pipeline: leaf_reports (always), anomalies (sick only)." + ) + parser.add_argument("--input", type=str, required=True, help="Image file or folder") + parser.add_argument("--mission", type=int, default=60, help="Ignored; always fixed to 60") + parser.add_argument("--device", type=str, default="device-1", help="Fallback device (unused)") + args = parser.parse_args() + + runner = BatchRunner(mission_id=args.mission, device_id=args.device) + in_path = Path(args.input) + if in_path.is_dir(): + runner.run_folder(in_path) + else: + runner.process_image(in_path) + + +if __name__ == "__main__": + main() diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/base.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/base.py new file mode 100644 index 000000000..3eede7361 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/base.py @@ -0,0 +1,94 @@ +from __future__ import annotations + +from dataclasses import dataclass +from typing import Dict, List, Optional, Tuple, Protocol + + +@dataclass(frozen=True) +class Detection: + """ + Model-agnostic detection container. + + Canonical storage: + - bbox: (x, y, w, h) in pixel coordinates. + - confidence: float in [0, 1]. + - label: class/code string. + + Notes: + - Properties expose a stable attribute API (.x/.y/.w/.h/.area etc.) + so downstream code can use either bbox or attributes. + - The class is frozen (immutable) to avoid accidental mutations + during processing and logging. + """ + label: str + confidence: float + bbox: Tuple[float, float, float, float] + meta: Optional[Dict] = None # optional extra data (e.g., model logits) + + # ---- Convenience constructors ------------------------------------------------- + + @staticmethod + def from_xywh( + label: str, + confidence: float, + x: float, + y: float, + w: float, + h: float, + meta: Optional[Dict] = None, + ) -> "Detection": + """Create a Detection from explicit x/y/w/h values.""" + return Detection(label=label, confidence=float(confidence), bbox=(x, y, w, h), meta=meta) + + # ---- Attribute-style view over bbox ------------------------------------------ + + @property + def x(self) -> float: + return float(self.bbox[0]) + + @property + def y(self) -> float: + return float(self.bbox[1]) + + @property + def w(self) -> float: + return float(self.bbox[2]) + + @property + def h(self) -> float: + return float(self.bbox[3]) + + @property + def xmin(self) -> float: + return self.x + + @property + def ymin(self) -> float: + return self.y + + @property + def xmax(self) -> float: + return self.x + self.w + + @property + def ymax(self) -> float: + return self.y + self.h + + @property + def area(self) -> float: + # Clamp at zero to avoid negative area if w/h are negative by mistake. + return max(0.0, self.w) * max(0.0, self.h) + + +class Detector(Protocol): + """ + Base detector interface. + + Implementors must return a list of Detection objects given a BGR image + (numpy array with shape (H, W, 3), dtype=uint8). + """ + name: str + + def run(self, bgr_image) -> List[Detection]: + """Run inference on a BGR image and return model detections.""" + ... diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/cnn_multi_classifier.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/cnn_multi_classifier.py new file mode 100644 index 000000000..6a2d5f3a3 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/cnn_multi_classifier.py @@ -0,0 +1,12 @@ +# agri-baseline/src/detectors/cnn_multi_classifier.py +import torch.nn as nn +from torchvision import models + +def build_multi_model(num_classes: int, pretrained: bool = True) -> nn.Module: + """ + Builds a ResNet18 model for multi-class disease classification. + """ + model = models.resnet18(weights="IMAGENET1K_V1" if pretrained else None) + in_features = model.fc.in_features + model.fc = nn.Linear(in_features, num_classes) + return model diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/disease_model.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/disease_model.py new file mode 100644 index 000000000..a9f94ebae --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/disease_model.py @@ -0,0 +1,127 @@ +# agri_baseline/src/detectors/disease_model.py +from __future__ import annotations + +from dataclasses import dataclass +from typing import List, Tuple + +import cv2 +import numpy as np +import torch +import albumentations as A +from albumentations.pytorch import ToTensorV2 + +from agri_baseline.src.detectors.cnn_multi_classifier import build_multi_model +from agri_baseline.src.detectors.train.dictionary import CLASS_MAPPING + + +@dataclass +class Detection: + """Simple container for a single detection box.""" + bbox: Tuple[int, int, int, int] # x, y, w, h + confidence: float + label: str = "disease" + + @property + def area(self) -> int: + x, y, w, h = self.bbox + return int(w * h) + + +def _ensure_bgr_uint8(img: np.ndarray) -> np.ndarray: + """ + Normalize any input image to BGR uint8 with 3 channels. + Prevents cvtColor from crashing with color.simd_helpers.hpp:94. + + Rules: + - None / empty -> ValueError + - GRAY (H,W) -> BGR + - BGRA (H,W,4) -> BGR + - dtype != uint8 -> convert to uint8 (clip to [0..255]) + """ + if img is None or getattr(img, "size", 0) == 0: + raise ValueError("DiseaseDetector: empty/None image given") + + # If grayscale -> convert to BGR + if img.ndim == 2: + img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) + + # If BGRA -> drop alpha + elif img.ndim == 3 and img.shape[2] == 4: + img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR) + + # Validate shape now + if img.ndim != 3 or img.shape[2] != 3: + raise ValueError(f"DiseaseDetector: unexpected image shape {img.shape}") + + # Ensure uint8 + if img.dtype != np.uint8: + img = np.clip(img, 0, 255).astype(np.uint8) + + # Ensure non-zero size + h, w = img.shape[:2] + if h == 0 or w == 0: + raise ValueError("DiseaseDetector: zero-sized image") + + return img + + +class DiseaseDetector: + """ + CNN-based disease classifier. + - Normalizes input to BGR uint8 (3-ch) to avoid OpenCV color conversion crashes. + - Converts BGR->RGB before Albumentations (Normalize + ToTensorV2). + """ + + name = "disease" + + def __init__(self, model_path: str = "models/cnn_multi_stage3.pth", device: str | None = None) -> None: + # choose device + self.device = device or ("cuda" if torch.cuda.is_available() else "cpu") + + # build model according to class mapping + self.classes = sorted(set(CLASS_MAPPING.values())) + self.model = build_multi_model(num_classes=len(self.classes)).to(self.device) + + # load trained weights + state = torch.load(model_path, map_location=self.device) + self.model.load_state_dict(state) + self.model.eval() + + # same validation transforms used in training + self.transform = A.Compose( + [ + A.Resize(224, 224), + A.Normalize(mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225)), + ToTensorV2(), + ] + ) + + def run(self, img: np.ndarray) -> List[Detection]: + """ + Run the classifier on a single image. + :param img: np.ndarray from OpenCV (BGR or GRAY/BGRA/float) — any shape/dtype. + :return: list with a single full-frame Detection carrying predicted label/confidence. + """ + # 1) Normalize input so cvtColor is safe + img = _ensure_bgr_uint8(img) + + # 2) Convert to RGB for the model pipeline + img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) + + # 3) Albumentations -> tensor + aug = self.transform(image=img_rgb) + tensor = aug["image"].unsqueeze(0).to(self.device) + + # 4) Model inference + with torch.no_grad(): + logits = self.model(tensor) + probs = torch.softmax(logits, dim=1)[0] + conf_t, cls_t = torch.max(probs, dim=0) + + label = self.classes[cls_t.item()] + confidence = float(conf_t.item()) + + # 5) Return a single detection that spans the whole image (classifier) + h, w = img.shape[:2] + det = Detection(bbox=(0, 0, w, h), confidence=confidence, label=label) + return [det] diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/train/dictionary.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/train/dictionary.py new file mode 100644 index 000000000..1d0671026 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/detectors/train/dictionary.py @@ -0,0 +1,36 @@ +CLASS_MAPPING = { + # 🍅 Tomato + "tomato_healthy": "tomato__healthy", + "tomato_leaf": "tomato__healthy", + "tomato_bacterial_spot": "tomato__bacterial_spot", + "tomato_leaf_bacterial_spot": "tomato__bacterial_spot", + "tomato_early_blight": "tomato__early_blight", + "tomato_early_blight_leaf": "tomato__early_blight", + "tomato_late_blight": "tomato__late_blight", + "tomato_leaf_late_blight": "tomato__late_blight", + "tomato_leaf_mold": "tomato__leaf_mold", + "tomato_mold_leaf": "tomato__leaf_mold", + "tomato_septoria_leaf_spot": "tomato__septoria_leaf_spot", + "tomato_spider_mites_two_spotted_spider_mite": "tomato__spider_mites", + "tomato_spider_mites": "tomato__spider_mites", + "tomato_target_spot": "tomato__target_spot", + "tomato_tomato_mosaic_virus": "tomato__mosaic_virus", + "tomato_tomato_yellowleaf_curl_virus": "tomato__yellowleaf_curl_virus", + "tomato_leaf_mosaic_virus": "tomato__mosaic_virus", + "tomato_leaf_yellow_virus": "tomato__yellowleaf_curl_virus", + + + # 🥔 Potato + "potato_healthy": "potato__healthy", + "potato_leaf": "potato__healthy", + "potato_early_blight": "potato__early_blight", + "potato_leaf_early_blight": "potato__early_blight", + "potato_late_blight": "potato__late_blight", + "potato_leaf_late_blight": "potato__late_blight", + + # 🌶️ Pepper + "pepper_bell_healthy": "pepper__healthy", + "bell_pepper_leaf": "pepper__healthy", + "pepper_bell_bacterial_spot": "pepper__bacterial_spot", + "bell_pepper_leaf_spot": "pepper__bacterial_spot", +} diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/config.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/config.py new file mode 100644 index 000000000..18d696e0a --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/config.py @@ -0,0 +1,25 @@ +from __future__ import annotations + +import os +from pathlib import Path + +# Try to load env files both from project root and from agri_baseline/.env +try: + from dotenv import load_dotenv # type: ignore + load_dotenv(dotenv_path=Path("agri_baseline/.env"), override=False) + load_dotenv(override=False) +except Exception: + pass + +# Prefer standard name DATABASE_URL; fallback to DB_URL; finally default to localhost:5432 +DB_URL: str = ( + os.getenv("DATABASE_URL") + or os.getenv("DB_URL") + or "postgresql+psycopg2://missions_user:pg123@localhost:5432/missions_db" +) + +IMAGES_DIR = os.getenv("IMAGES_DIR", "./data/images") +BATCH_SIZE = int(os.getenv("BATCH_SIZE", 64)) +MAX_WORKERS = int(os.getenv("MAX_WORKERS", 4)) +MIN_BBOX_AREA = int(os.getenv("MIN_BBOX_AREA", 60)) +MIN_COMPONENT_AREA = int(os.getenv("MIN_COMPONENT_AREA", 200)) diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/db.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/db.py new file mode 100644 index 000000000..8c69e24f3 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/db.py @@ -0,0 +1,67 @@ +from __future__ import annotations + +from sqlalchemy import create_engine, text, bindparam +from sqlalchemy.engine import Engine + +from . import config + +_engine: Engine | None = None + +def get_engine() -> Engine: + """Return a singleton SQLAlchemy engine for the configured DB.""" + global _engine + if _engine is None: + _engine = create_engine( + config.DB_URL, + pool_pre_ping=True, # keep-alive for flaky networks/tests + future=True, + connect_args={"connect_timeout": 5} # fail fast on bad host/port + ) + return _engine + +# === Inserts mapped to RelDB schema === + +# detections → anomalies +INSERT_DET = text( + """ + INSERT INTO anomalies(mission_id, device_id, ts, anomaly_type_id, severity, details, geom) + VALUES (:mission_id, :device_id, :ts, :anomaly_type_id, :severity, CAST(:details AS jsonb), + ST_GeomFromText(:wkt_geom, 4326)); + """ +) + +# counts → tile_stats +INSERT_COUNT = text( + """ + INSERT INTO tile_stats(mission_id, tile_id, anomaly_score, geom) + VALUES (:mission_id, :tile_id, :anomaly_score, ST_GeomFromText(:wkt_geom, 4326)) + ON CONFLICT (mission_id, tile_id) DO UPDATE + SET anomaly_score = excluded.anomaly_score; + """ +) + +# validator findings → event_logs +INSERT_FINDING = ( + text( + """ + INSERT INTO event_logs(ts, level, source, message, details) + VALUES (CURRENT_TIMESTAMP, :level, 'validator', :message, CAST(:details AS jsonb)); + """ + ) + # Defaults if the caller does not send the parameters + .bindparams( + bindparam("level", value="INFO"), + bindparam("message", value=""), + bindparam("details", value="{}"), + ) +) + + + +# QA metrics → event_logs +INSERT_QA = text( + """ + INSERT INTO event_logs(ts, level, source, message, details) + VALUES (CURRENT_TIMESTAMP, 'INFO', 'qa', 'QA metrics recorded', CAST(:details AS jsonb)); + """ +) \ No newline at end of file diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/logging_setup.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/logging_setup.py new file mode 100644 index 000000000..06193027f --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/logging_setup.py @@ -0,0 +1,9 @@ +import logging + + +def setup_logging(): + logging.basicConfig( + level=logging.INFO, + format="%(asctime)s | %(levelname)s | %(name)s | %(message)s", + ) + return logging.getLogger("agri") \ No newline at end of file diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/utils.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/utils.py new file mode 100644 index 000000000..0b99245e9 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/pipeline/utils.py @@ -0,0 +1,62 @@ +# agri_baseline/src/pipeline/utils.py +# Max line length: 100 + +from __future__ import annotations + +import hashlib +from pathlib import Path +from typing import Tuple + +import cv2 +import numpy as np + + +class ImageLoadError(Exception): + """Raised when an image cannot be decoded or is empty.""" + + +def load_image(path: str | Path) -> Tuple[np.ndarray, int, int]: + """ + Load an image from disk as BGR uint8 and return (img, width, height). + + Rules: + - Always read as color to ensure 3 channels (BGR). + - Raise FileNotFoundError if the path doesn't exist. + - Raise ImageLoadError if decode fails or the image is empty. + - Convert dtype to uint8 if needed. + - Normalize channel count: grayscale -> BGR, BGRA -> BGR. + """ + p = Path(path) + if not p.exists(): + raise FileNotFoundError(f"Image not found: {p.resolve()}") + + # Always load as color to ensure 3 channels (BGR) + img = cv2.imread(str(p), cv2.IMREAD_COLOR) + if img is None or img.size == 0: + raise ImageLoadError(f"Failed to decode image (or empty): {p.resolve()}") + + if img.dtype != np.uint8: + img = cv2.convertScaleAbs(img) + + # Guard channel count (should be 3 after IMREAD_COLOR, but just in case) + if img.ndim == 2: + img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) + elif img.ndim == 3 and img.shape[2] == 4: + img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR) + + h, w = img.shape[:2] + return img, w, h + + +def image_id_from_path(path: str | Path) -> str: + p = Path(path) + digest = hashlib.sha1(str(p.resolve()).encode()).hexdigest()[:16] + return f"{p.stem}_{digest}" + + +def clamp_bbox(x: int, y: int, w: int, h: int, W: int, H: int) -> Tuple[int, int, int, int]: + x = max(0, min(x, W - 1)) + y = max(0, min(y, H - 1)) + w = max(1, min(w, W - x)) + h = max(1, min(h, H - y)) + return x, y, w, h diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/storage/__init__.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/storage/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/storage/minio_client.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/storage/minio_client.py new file mode 100644 index 000000000..dd5effd69 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/storage/minio_client.py @@ -0,0 +1,35 @@ +from __future__ import annotations + +import os +from dataclasses import dataclass +from minio import Minio + + +@dataclass(frozen=True) +class MinioConfig: + endpoint: str + access_key: str + secret_key: str + bucket: str + secure: bool + + +def load_minio_config() -> MinioConfig: + endpoint = os.getenv("MINIO_ENDPOINT", "localhost:9000") + access_key = os.getenv("MINIO_ACCESS_KEY", "") + secret_key = os.getenv("MINIO_SECRET_KEY", "") + bucket = os.getenv("MINIO_BUCKET", "my-bucket") + secure = os.getenv("MINIO_SECURE", "false").lower() == "true" + + if not access_key or not secret_key: + raise ValueError("Missing MINIO_ACCESS_KEY / MINIO_SECRET_KEY.") + return MinioConfig(endpoint, access_key, secret_key, bucket, secure) + + +def build_client(cfg: MinioConfig) -> Minio: + return Minio( + endpoint=cfg.endpoint, + access_key=cfg.access_key, + secret_key=cfg.secret_key, + secure=cfg.secure, + ) diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/storage/minio_sync.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/storage/minio_sync.py new file mode 100644 index 000000000..8c6c2b6a1 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/storage/minio_sync.py @@ -0,0 +1,74 @@ +from __future__ import annotations + +import os +from io import BytesIO +from pathlib import Path +from typing import Iterable + +from .minio_client import MinioConfig, build_client + + +def ensure_bucket(cfg: MinioConfig) -> None: + """ + Ensure the target bucket exists; create it if it does not. + """ + client = build_client(cfg) + if not client.bucket_exists(cfg.bucket): + client.make_bucket(cfg.bucket) + + +def download_prefix_to_dir(cfg: MinioConfig, prefix: str, local_dir: Path) -> list[Path]: + """ + Download all objects under the given `prefix` to the local directory. + Returns a list of local file paths that were downloaded. + """ + client = build_client(cfg) + local_dir.mkdir(parents=True, exist_ok=True) + + downloaded: list[Path] = [] + for obj in client.list_objects(cfg.bucket, prefix=prefix, recursive=True): + # Skip entries that represent "virtual folders" + name = obj.object_name + if name.endswith("/") or not name: + continue + + # Simplify: save using the file's basename only. + # If you need to preserve the full hierarchy, use: local_dir.joinpath(name) + target = local_dir.joinpath(Path(name).name) + + response = client.get_object(cfg.bucket, name) + try: + data = response.read() + finally: + response.close() + response.release_conn() + + target.parent.mkdir(parents=True, exist_ok=True) + target.write_bytes(data) + downloaded.append(target) + + return downloaded + + +def upload_dir_to_prefix(cfg: MinioConfig, local_dir: Path, prefix: str) -> list[str]: + """ + Upload all files from the local directory under the given `prefix`. + Returns a list of object names that were uploaded. + """ + client = build_client(cfg) + ensure_bucket(cfg) + + uploaded: list[str] = [] + for path in local_dir.rglob("*"): + if not path.is_file(): + continue + + rel = path.relative_to(local_dir).as_posix() + object_name = f"{prefix.rstrip('/')}/{rel}" + data = path.read_bytes() + bio = BytesIO(data) + + client.put_object(cfg.bucket, object_name, bio, length=len(data)) + uploaded.append(object_name) + + return uploaded diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/validator/rules.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/validator/rules.py new file mode 100644 index 000000000..afb6318a7 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/validator/rules.py @@ -0,0 +1,65 @@ +from __future__ import annotations +import json +from dataclasses import dataclass +from typing import Iterable, Optional + +from sqlalchemy import text +from agri_baseline.src.pipeline.db import get_engine, INSERT_FINDING, INSERT_QA + + +@dataclass +class Finding: + scope: str + image_id: str + rule: str + severity: str + message: str + details: Optional[dict] = None + + +# ---- Image-level checks ---- + +def check_bbox_bounds(image_id: str, width: int, height: int, dets: list[dict]) -> list[Finding]: + out: list[Finding] = [] + for d in dets: + x, y, w, h = d["bbox_x"], d["bbox_y"], d["bbox_w"], d["bbox_h"] + if x < 0 or y < 0 or x + w > width or y + h > height: + out.append(Finding("image", image_id, "bbox_oob", "warn", + f"BBox out-of-bounds: {(x, y, w, h)}")) + if w * h <= 0 or d["area_px"] <= 0: + out.append(Finding("image", image_id, "bbox_area_zero", "error", + "Non-positive area")) + if d["confidence"] < 0 or d["confidence"] > 1: + out.append(Finding("image", image_id, "conf_oob", "error", + f"Confidence out of range: {d['confidence']:.3f}")) + return out + + +def check_counts_reasonable(image_id: str, disease: int) -> list[Finding]: + out: list[Finding] = [] + if disease < 0: + out.append(Finding("image", image_id, "negative_counts", "error", + f"Negative count: disease={disease}")) + if disease == 0: + out.append(Finding("image", image_id, "all_zero_counts", "warn", + "Disease count is zero")) + if disease > 10000: + out.append(Finding("image", image_id, "count_too_high", "warn", + f"Suspiciously high disease count: {disease}")) + return out + + +# ---- Batch-level checks ---- + +def check_batch_error_rate(total: int, errored: int, threshold: float = 0.05) -> list[Finding]: + rate = 0.0 if total == 0 else errored / total + sev = "warn" if rate <= threshold else "error" + return [Finding("batch", None, "error_rate", sev, + f"Batch error rate={rate:.3%}, threshold={threshold:.0%}")] + + +def check_batch_no_detections(total: int, sum_dets: int) -> list[Finding]: + if total > 0 and sum_dets == 0: + return [Finding("batch", None, "no_detections", "warn", + "Pipeline produced zero detections for the entire batch")] + return [] diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/validator/validator.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/validator/validator.py new file mode 100644 index 000000000..3c970190c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/agri_baseline/src/validator/validator.py @@ -0,0 +1,94 @@ +from __future__ import annotations +import json +from dataclasses import dataclass +from typing import Iterable, List, Optional +from sqlalchemy import text + +from agri_baseline.src.pipeline.db import get_engine, INSERT_FINDING, INSERT_QA + + +@dataclass +class Finding: + """Single validation finding.""" + scope: str # e.g., "image" + image_id: str # logical id per image + rule: str # rule code/name + severity: str # DEBUG/INFO/WARN/ERROR + message: str # human-readable message + details: Optional[dict] = None + + +class Validator: + """ + Collects validation findings and writes batch summaries. + """ + def image_findings(self, findings: Iterable[Finding]) -> None: + """Write image-level findings into event_logs table.""" + with get_engine().begin() as conn: + for f in findings: + details_dict = { + "scope": f.scope, + "rule": f.rule, + "image_id": f.image_id, + **(f.details or {}), + } + conn.execute( + INSERT_FINDING, + { + "level": f.severity.upper(), + "message": f.message, + # Passes as a JSON string because SQL does CAST(... AS jsonb) "details": json.dumps(details_dict), + }, + ) + + + def batch_summary(self) -> None: + """ + Aggregate anomalies → tile_stats by image_id (from anomalies.details->>'image_id'). + For each (mission_id, image_id): + - anomaly_score = count of anomalies + - geom = envelope of a small expanded collect of points (Polygon, 4326) + Idempotent via ON CONFLICT (mission_id, tile_id). + """ + sql = text( + """ + WITH per_image AS ( + SELECT + a.mission_id, + a.details->>'image_id' AS tile_id, + COUNT(*)::real AS anomaly_score, + -- produce Polygon in 4326 directly (no WKT roundtrip) + ST_Envelope( + ST_Expand( + ST_Collect(a.geom), + 0.0005 -- ~50m at equator; tweak if needed + ) + )::geometry(Polygon, 4326) AS poly + FROM anomalies a + WHERE a.geom IS NOT NULL + AND a.details ? 'image_id' + GROUP BY a.mission_id, tile_id + ) + INSERT INTO tile_stats (mission_id, tile_id, anomaly_score, geom) + SELECT mission_id, tile_id, anomaly_score, poly + FROM per_image + ON CONFLICT (mission_id, tile_id) DO UPDATE + SET anomaly_score = EXCLUDED.anomaly_score, + geom = EXCLUDED.geom; + """ + ) + + with get_engine().begin() as conn: + conn.execute(sql) + + # optional: record a QA info log (pass JSON as string) + with get_engine().begin() as conn: + conn.execute( + INSERT_QA, + { + "details": json.dumps({ + "source": "batch_summary", + "note": "tile_stats updated from anomalies by image_id", + }) + }, + ) diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/docker-compose.yml b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/docker-compose.yml new file mode 100644 index 000000000..18e1cc31c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/docker-compose.yml @@ -0,0 +1,25 @@ +services: + app: + build: + context: . + dockerfile: Dockerfile + container_name: agri_app + # exec-form to avoid spacing/quoting issues + command: ["python", "-m", "agri_baseline.scripts.run_batch", "--storage", "minio"] + env_file: + - agri_baseline/.env + volumes: + - ./agri_baseline:/app/agri_baseline + - ./tests:/app/tests + - ./data:/app/data + - ./models:/root/.cache/torch/hub/checkpoints + networks: + - agri_net + - minio_net # ← MinIO network + +networks: + agri_net: + external: true + minio_net: + external: true + name: storage_with_mqtt_minionet # ← MinIO network name diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/dockerfile b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/dockerfile new file mode 100644 index 000000000..32623dc45 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/dockerfile @@ -0,0 +1,46 @@ +FROM mcr.microsoft.com/devcontainers/python:1-3.11-bullseye + +ENV PIP_NO_CACHE_DIR=0 \ + PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 + +RUN apt-get update && apt-get install -y --no-install-recommends \ + git ffmpeg libsm6 libxext6 libgl1 ca-certificates \ + && rm -rf /var/lib/apt/lists/* + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PIP_CERT=/etc/ssl/certs/ca-certificates.crt + +ARG TORCH_VERSION=2.2.1 +ARG TORCHVISION_VERSION=0.17.1 +ARG TORCHAUDIO_VERSION=2.2.1 +RUN --mount=type=cache,target=/root/.cache/pip \ + python -m pip install --upgrade pip && \ + python -m pip install --index-url https://download.pytorch.org/whl/cpu \ + torch==${TORCH_VERSION} \ + torchvision==${TORCHVISION_VERSION} \ + torchaudio==${TORCHAUDIO_VERSION} + +WORKDIR /app +COPY agri_baseline/requirements.txt /app/requirements.txt + +RUN awk '!/^(torch|torchvision|torchaudio)[[:space:]=<>!~]*$/ \ + && !/^pytorch-cuda/ \ + && !/^xformers/ \ + && !/^cupy-cuda/ \ + && !/^nvidia[-_]/' /app/requirements.txt > /app/requirements.cpu.txt + +RUN --mount=type=cache,target=/root/.cache/pip \ + pip install --upgrade pip && \ + PIP_INDEX_URL=https://download.pytorch.org/whl/cpu \ + PIP_EXTRA_INDEX_URL=https://pypi.org/simple \ + pip install --retries 10 --timeout 120 -r /app/requirements.cpu.txt + +COPY agri_baseline /app/agri_baseline +COPY models /app/models +COPY tests /app/tests + +ENV PYTHONPATH=/app + +CMD ["python", "agri_baseline/src/batch_runner.py"] diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/pytest.ini b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/pytest.ini new file mode 100644 index 000000000..89313dd9b --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/pytest.ini @@ -0,0 +1,4 @@ +[pytest] +pythonpath = . +testpaths = tests +addopts = -v diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/cnn_binary_classifier.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/cnn_binary_classifier.py new file mode 100644 index 000000000..898c2c918 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/cnn_binary_classifier.py @@ -0,0 +1,12 @@ +# agri-baseline/src/detectors/cnn_binary_classifier.py +import torch.nn as nn +from torchvision import models + +def build_binary_model(pretrained: bool = True) -> nn.Module: + """ + Builds a ResNet18 model for binary classification (healthy vs diseased). + """ + model = models.resnet18(weights="IMAGENET1K_V1" if pretrained else None) + in_features = model.fc.in_features + model.fc = nn.Linear(in_features, 2) # healthy / diseased + return model diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/dataset_binary.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/dataset_binary.py new file mode 100644 index 000000000..d63bf5208 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/dataset_binary.py @@ -0,0 +1,36 @@ +# agri-baseline/src/detectors/dataset_binary.py +import os +from torch.utils.data import Dataset +from PIL import Image + +class BinaryDiseaseDataset(Dataset): + """ + Dataset wrapper that maps: + - healthy folders -> label 0 + - all disease folders -> label 1 + Keeps also the original folder name for optional subtype info. + """ + def __init__(self, root: str, transform=None): + self.samples = [] + + self.targets = [] + self.transform = transform + for cls in os.listdir(root): + path = os.path.join(root, cls) + if not os.path.isdir(path): + continue + label = 0 if "healthy" in cls.lower() else 1 + for f in os.listdir(path): + if f.lower().endswith((".jpg", ".png", ".jpeg")): + self.samples.append((os.path.join(path, f), label, cls)) + self.targets.append(label) + + def __len__(self): + return len(self.samples) + + def __getitem__(self, idx): + path, label, cls_name = self.samples[idx] + img = Image.open(path).convert("RGB") + if self.transform: + img = self.transform(img) + return img, label, cls_name diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/disease.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/disease.py new file mode 100644 index 000000000..653f673ae --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/disease.py @@ -0,0 +1,202 @@ +import cv2 +import numpy as np + +from ...agri_baseline.src.detectors.base import Detection +from ..pipeline import config + + +class DiseaseDetector: + """ + Improved disease detector: + - Leaf mask (HSV/LAB) to isolate plant tissue. + - Candidate lesion detection: + 1) Yellow/Brown in HSV (stress/necrosis). + 2) Dark + Brown in LAB (low L, high b). + - Noise cleaning and merging. + - Shape filtering by circularity (detect "spots"). + - Confidence weighted by darkness, saturation, and circularity. + """ + + name = "disease" + + # HSV thresholds for yellow/brown (tunable) + HSV_YELLOW = ((10, 50, 40), (45, 255, 255)) + HSV_BROWN1 = ((0, 80, 30), (10, 255, 200)) + HSV_BROWN2 = ((160, 80, 30), (179, 255, 200)) + + # LAB thresholds for dark/brown lesions (tunable) + LAB_L_MAX_DARK = 145 # Lower L means darker + LAB_B_MIN_BROWN = 135 # Higher b means more yellow/brown + + # Shape filtering + MIN_CIRCULARITY = 0.22 # 4πA/P^2; range 0..1 + MAX_ASPECT_RATIO = 2.2 # Avoid elongated regions + DILATE_MERGE_RADIUS = 4 + + def __init__(self): + # Minimum area from config (fallback to default if missing) + self.min_area = int(getattr(config, "MIN_BBOX_AREA", 60)) + + def run(self, bgr_image: np.ndarray) -> list[Detection]: + h, w = bgr_image.shape[:2] + + # ---------- 1) Leaf isolation ---------- + hsv = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2HSV) + lab = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2LAB) + H, S, V = cv2.split(hsv) + L, A, B = cv2.split(lab) + + # Green mask in HSV (broad range for leaf tissue) + green1 = cv2.inRange(hsv, (35, 30, 30), (85, 255, 255)) + green2 = cv2.inRange(hsv, (25, 25, 40), (95, 255, 255)) + leaf_mask = cv2.bitwise_or(green1, green2) + + # Contrast enhancement with CLAHE on L channel + clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8)) + L_eq = clahe.apply(L) + + # Basic cleaning of leaf mask + leaf_mask = cv2.medianBlur(leaf_mask, 5) + leaf_mask = cv2.morphologyEx( + leaf_mask, cv2.MORPH_CLOSE, np.ones((5, 5), np.uint8), iterations=1 + ) + + # ---------- 2) Lesion candidates ---------- + # (a) Yellow/Brown in HSV + yellow = cv2.inRange(hsv, self.HSV_YELLOW[0], self.HSV_YELLOW[1]) + brown1 = cv2.inRange(hsv, self.HSV_BROWN1[0], self.HSV_BROWN1[1]) + brown2 = cv2.inRange(hsv, self.HSV_BROWN2[0], self.HSV_BROWN2[1]) + hsv_spots = cv2.bitwise_or(yellow, cv2.bitwise_or(brown1, brown2)) + + # (b) Dark + Brownish in LAB + dark = cv2.threshold(L_eq, self.LAB_L_MAX_DARK, 255, cv2.THRESH_BINARY_INV)[1] + brownish = cv2.threshold(B, self.LAB_B_MIN_BROWN, 255, cv2.THRESH_BINARY)[1] + lab_spots = cv2.bitwise_and(dark, brownish) + + # Combine HSV and LAB candidates, restricted to leaf mask + candidates = cv2.bitwise_or(hsv_spots, lab_spots) + candidates = cv2.bitwise_and(candidates, leaf_mask) + + # ---------- 3) Cleaning & merging ---------- + candidates = cv2.medianBlur(candidates, 3) + candidates = cv2.morphologyEx( + candidates, cv2.MORPH_OPEN, np.ones((3, 3), np.uint8), iterations=1 + ) + + # Dilate slightly to merge nearby spots + if self.DILATE_MERGE_RADIUS > 0: + k = cv2.getStructuringElement( + cv2.MORPH_ELLIPSE, + (2 * self.DILATE_MERGE_RADIUS + 1, 2 * self.DILATE_MERGE_RADIUS + 1), + ) + candidates = cv2.dilate(candidates, k, iterations=1) + + # ---------- 4) Contours & filtering ---------- + cnts, _ = cv2.findContours(candidates, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + dets = [] + for c in cnts: + area = cv2.contourArea(c) + if area < self.min_area: + continue + + x, y, bw, bh = cv2.boundingRect(c) + + # Circularity: 4πA / P^2 + perim = cv2.arcLength(c, True) + circularity = (4.0 * np.pi * area / (perim ** 2 + 1e-6)) if perim > 0 else 0.0 + if circularity < self.MIN_CIRCULARITY: + continue + + # Aspect ratio filtering + ar = max(bw, bh) / (min(bw, bh) + 1e-6) + if ar > self.MAX_ASPECT_RATIO: + continue + + # Extract subregion for scoring + hsv_box = hsv[y : y + bh, x : x + bw] + lab_box = lab[y : y + bh, x : x + bw] + + Lb = lab_box[:, :, 0].astype(np.float32) + Sb = hsv_box[:, :, 1].astype(np.float32) + + # Darkness score (lower L → higher score) + dark_score = np.clip((180.0 - float(np.mean(Lb))) / 180.0, 0.0, 1.0) + # Saturation score (higher S → higher score) + sat_score = np.clip(float(np.mean(Sb)) / 255.0, 0.0, 1.0) + + # Final weighted confidence + conf = 0.45 * dark_score + 0.35 * sat_score + 0.20 * np.clip(circularity, 0.0, 1.0) + conf = float(np.clip(conf, 0.0, 1.0)) + + dets.append( + Detection( + label="disease_spot", + confidence=conf, + x=int(x), + y=int(y), + w=int(bw), + h=int(bh), + area=int(area), + ) + ) + + # ---------- 5) Merge overlapping boxes ---------- + dets = self._merge_overlaps(dets, iou_thresh=0.5) + return dets + + # ---------- IoU helper ---------- + @staticmethod + def _iou(a, b): + ax1, ay1, ax2, ay2 = a.x, a.y, a.x + a.w, a.y + a.h + bx1, by1, bx2, by2 = b.x, b.y, b.x + b.w, b.y + b.h + inter_x1, inter_y1 = max(ax1, bx1), max(ay1, by1) + inter_x2, inter_y2 = min(ax2, bx2), min(ay2, by2) + iw, ih = max(0, inter_x2 - inter_x1), max(0, inter_y2 - inter_y1) + inter = iw * ih + if inter == 0: + return 0.0 + area_a = a.w * a.h + area_b = b.w * b.h + return inter / float(area_a + area_b - inter + 1e-6) + + def _merge_overlaps(self, dets, iou_thresh=0.5): + if not dets: + return dets + dets = sorted(dets, key=lambda d: d.confidence, reverse=True) + kept = [] + while dets: + base = dets.pop(0) + to_merge = [base] + remain = [] + for d in dets: + if self._iou(base, d) >= iou_thresh: + to_merge.append(d) + else: + remain.append(d) + dets = remain + + # Merge into one bounding box + xs = [d.x for d in to_merge] + ys = [d.y for d in to_merge] + x2s = [d.x + d.w for d in to_merge] + y2s = [d.y + d.h for d in to_merge] + x = int(min(xs)) + y = int(min(ys)) + w = int(max(x2s) - x) + h = int(max(y2s) - y) + + # Average confidence + conf = float(np.mean([d.confidence for d in to_merge])) + area = int(w * h) + kept.append( + Detection( + label="disease_spot", + confidence=conf, + x=x, + y=y, + w=w, + h=h, + area=area, + ) + ) + return kept diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/eval_multi_levels.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/eval_multi_levels.py new file mode 100644 index 000000000..c39ea4e5a --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/eval_multi_levels.py @@ -0,0 +1,167 @@ +# eval_multi_levels.py +import torch +import numpy as np +from sklearn.metrics import accuracy_score, confusion_matrix, f1_score, classification_report +from torch.utils.data import DataLoader +import cv2 +import albumentations as A +from albumentations.pytorch import ToTensorV2 + +from agri_baseline.src.detectors.train.dictionary import CLASS_MAPPING +from agri_baseline.src.detectors.cnn_multi_classifier import build_multi_model +from torchvision import datasets +import seaborn as sns +import matplotlib.pyplot as plt + +# ------------------------ +# Paths +# ------------------------ +DATA_DIR = "data_balanced/PlantDoc/test" +MODEL_PATH = "models/cnn_multi_stage3.pth" + +device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + +# ------------------------ +# Transforms +# ------------------------ +val_transforms = A.Compose([ + A.Resize(224, 224), + A.Normalize(mean=(0.485, 0.456, 0.406), + std=(0.229, 0.224, 0.225)), + ToTensorV2() +]) + +# ------------------------ +# Dataset wrapper +# ------------------------ +class AlbumentationsDataset(torch.utils.data.Dataset): + def __init__(self, dataset, transform=None): + self.dataset = dataset + self.transform = transform + + def __getitem__(self, idx): + path, label = self.dataset.samples[idx] + image = cv2.imread(path) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + if self.transform: + image = self.transform(image=image)["image"] + return image, label + + def __len__(self): + return len(self.dataset) + + +# ------------------------ +# Prepare dataset +# ------------------------ +dataset = datasets.ImageFolder(DATA_DIR) +canonical_classes = sorted(set(CLASS_MAPPING.values())) +class_to_idx = {cls: i for i, cls in enumerate(canonical_classes)} + +new_samples, new_targets = [], [] +for path, label_idx in dataset.samples: + raw_name = dataset.classes[label_idx].lower().replace(" ", "_") + canonical_label = CLASS_MAPPING.get(raw_name) + if canonical_label is None: + raise ValueError(f"Class {raw_name} not found in CLASS_MAPPING") + new_samples.append((path, class_to_idx[canonical_label])) + new_targets.append(class_to_idx[canonical_label]) + +dataset.samples = new_samples +dataset.targets = new_targets +dataset.classes = canonical_classes +dataset.class_to_idx = class_to_idx + +val_dataset = AlbumentationsDataset(dataset, transform=val_transforms) +val_loader = DataLoader(val_dataset, batch_size=32, shuffle=False) + +# ------------------------ +# Load model +# ------------------------ +model = build_multi_model(num_classes=len(canonical_classes)).to(device) +state_dict = torch.load(MODEL_PATH, map_location=device) +model.load_state_dict(state_dict) +model.eval() + +# ------------------------ +# Evaluation +# ------------------------ +all_preds, all_labels = [], [] +with torch.no_grad(): + for images, labels in val_loader: + images, labels = images.to(device), labels.to(device) + outputs = model(images) + _, preds = outputs.max(1) + all_preds.extend(preds.cpu().numpy()) + all_labels.extend(labels.cpu().numpy()) + +all_preds = np.array(all_preds) +all_labels = np.array(all_labels) + +# ------------------------ +# Grouping +# ------------------------ +def to_healthy_sick(cls: str): + return "healthy" if "healthy" in cls else "sick" + +def to_crop(cls: str): + if cls.startswith("tomato"): return "tomato" + if cls.startswith("potato"): return "potato" + if cls.startswith("pepper"): return "pepper" + return "other" + +def to_disease(cls: str): + if "bacterial_spot" in cls: return "bacterial_spot" + if "early_blight" in cls: return "early_blight" + if "late_blight" in cls: return "late_blight" + if "leaf_mold" in cls: return "leaf_mold" + if "septoria_leaf_spot" in cls: return "septoria_leaf_spot" + if "spider_mites" in cls: return "spider_mites" + if "target_spot" in cls: return "target_spot" + if "mosaic_virus" in cls: return "mosaic_virus" + if "yellowleaf_curl_virus" in cls: return "yellowleaf_curl_virus" + return "none" + +idx_to_class = {v: k for k, v in class_to_idx.items()} + +y_true_cls = [idx_to_class[i] for i in all_labels] +y_pred_cls = [idx_to_class[i] for i in all_preds] + +# ------------------------ +# Evaluation per level +# ------------------------ +def evaluate_level(name, y_true, y_pred, labels=None): + acc = accuracy_score(y_true, y_pred) + f1 = f1_score(y_true, y_pred, average="weighted") + print(f"\n===== {name} =====") + print(f"Accuracy: {acc:.4f}") + print(f"F1-score (weighted): {f1:.4f}") + print(classification_report(y_true, y_pred, digits=4)) + cm = confusion_matrix(y_true, y_pred, labels=labels) + if labels: + plt.figure(figsize=(8, 6)) + sns.heatmap(cm, annot=True, fmt="d", xticklabels=labels, yticklabels=labels, cmap="Blues") + plt.title(f"Confusion Matrix - {name}") + plt.xlabel("Predicted") + plt.ylabel("True") + plt.show() + +# Healthy vs Sick +evaluate_level("Healthy vs Sick", + [to_healthy_sick(c) for c in y_true_cls], + [to_healthy_sick(c) for c in y_pred_cls], + labels=["healthy", "sick"]) + +# Crop type +evaluate_level("Crop type", + [to_crop(c) for c in y_true_cls], + [to_crop(c) for c in y_pred_cls], + labels=["tomato", "potato", "pepper", "other"]) + +# Disease type +evaluate_level("Disease type", + [to_disease(c) for c in y_true_cls], + [to_disease(c) for c in y_pred_cls], + labels=["bacterial_spot","early_blight","late_blight","leaf_mold", + "septoria_leaf_spot","spider_mites","target_spot", + "mosaic_virus","yellowleaf_curl_virus","none"]) diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/finetune_multi.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/finetune_multi.py new file mode 100644 index 000000000..e3e5457cd --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/finetune_multi.py @@ -0,0 +1,242 @@ +# finetune_multi.py +import torch +import torch.nn as nn +import torch.optim as optim +from torchvision import datasets +import os +from sklearn.metrics import f1_score +from torch.utils.data import DataLoader, random_split, WeightedRandomSampler +from torch.optim.lr_scheduler import ReduceLROnPlateau +import albumentations as A +from albumentations.pytorch import ToTensorV2 +import cv2 +import numpy as np + +from agri_baseline.src.detectors.train.dictionary import CLASS_MAPPING +from agri_baseline.src.detectors.cnn_multi_classifier import build_multi_model + + +# ------------------------ +# MixUp +# ------------------------ +def mixup_data(x, y, alpha=1.0): + if alpha > 0: + lam = np.random.beta(alpha, alpha) + else: + lam = 1 + batch_size = x.size()[0] + index = torch.randperm(batch_size).to(x.device) + + mixed_x = lam * x + (1 - lam) * x[index, :] + y_a, y_b = y, y[index] + return mixed_x, y_a, y_b, lam + +def mixup_criterion(criterion, pred, y_a, y_b, lam): + return lam * criterion(pred, y_a) + (1 - lam) * criterion(pred, y_b) + + +# ------------------------ +# Paths +# ------------------------ +DATA_DIR = "data_balanced/PlantDoc" +MODEL_PATH = "models/cnn_multi.pth" +SAVE_PATH = "models/cnn_multi_finetuned.pth" + +device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + + +# ------------------------ +# Augmentations +# ------------------------ +train_transforms = A.Compose([ + A.RandomResizedCrop(size=(224, 224), scale=(0.7, 1.0), p=1.0), + A.HorizontalFlip(p=0.5), + A.VerticalFlip(p=0.3), + A.ShiftScaleRotate(shift_limit=0.05, scale_limit=0.2, rotate_limit=30, p=0.7), + A.ColorJitter(brightness=0.3, contrast=0.3, saturation=0.3, p=0.5), + A.RandomBrightnessContrast(p=0.5), + A.GaussianBlur(p=0.3), + A.CoarseDropout(max_height=32, max_width=32, max_holes=1, p=0.3), + A.Normalize(mean=(0.485, 0.456, 0.406), + std=(0.229, 0.224, 0.225)), + ToTensorV2() +]) + +val_transforms = A.Compose([ + A.Resize(224, 224), + A.Normalize(mean=(0.485, 0.456, 0.406), + std=(0.229, 0.224, 0.225)), + ToTensorV2() +]) + + +# ------------------------ +# Albumentations Dataset +# ------------------------ +class AlbumentationsDataset(torch.utils.data.Dataset): + def __init__(self, dataset, transform=None): + self.dataset = dataset + self.transform = transform + + def __getitem__(self, idx): + path, label = self.dataset.samples[idx] + image = cv2.imread(path) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + if self.transform: + image = self.transform(image=image)["image"] + return image, label + + def __len__(self): + return len(self.dataset) + + +# ------------------------ +# Prepare Dataset +# ------------------------ +def prepare_multi_dataset(path): + dataset = datasets.ImageFolder(path) + new_samples, new_targets = [], [] + canonical_classes = sorted(set(CLASS_MAPPING.values())) + class_to_idx = {cls: i for i, cls in enumerate(canonical_classes)} + + for sample_path, label_idx in dataset.samples: + raw_name = dataset.classes[label_idx].lower().replace(" ", "_") + canonical_label = CLASS_MAPPING.get(raw_name) + if canonical_label is None: + raise ValueError(f"Class {raw_name} not found in CLASS_MAPPING") + new_samples.append((sample_path, class_to_idx[canonical_label])) + new_targets.append(class_to_idx[canonical_label]) + + dataset.samples = new_samples + dataset.targets = new_targets + dataset.classes = canonical_classes + dataset.class_to_idx = class_to_idx + return dataset + + +# ------------------------ +# Load dataset +# ------------------------ +full_dataset = prepare_multi_dataset(os.path.join(DATA_DIR, "train")) +print("Classes:", full_dataset.classes) +print("Total samples:", len(full_dataset)) + +train_size = int(0.8 * len(full_dataset)) +val_size = len(full_dataset) - train_size +train_dataset, val_dataset = random_split(full_dataset, [train_size, val_size]) + +train_dataset = AlbumentationsDataset(train_dataset.dataset, transform=train_transforms) +val_dataset = AlbumentationsDataset(val_dataset.dataset, transform=val_transforms) + +class_counts = np.bincount(full_dataset.targets) +class_weights = 1. / class_counts +sample_weights = [class_weights[t] for t in full_dataset.targets] + +sampler = WeightedRandomSampler(weights=sample_weights, + num_samples=len(sample_weights), + replacement=True) + +train_loader = DataLoader(train_dataset, batch_size=32, sampler=sampler) +val_loader = DataLoader(val_dataset, batch_size=32, shuffle=False) + + +# ------------------------ +# Model +# ------------------------ +model = build_multi_model(num_classes=len(full_dataset.classes)).to(device) +state_dict = torch.load(MODEL_PATH, map_location=device) +filtered_state_dict = {k: v for k, v in state_dict.items() if not k.startswith("fc.")} +model.load_state_dict(filtered_state_dict, strict=False) +print("✅ Loaded pretrained backbone") + + +# ------------------------ +# Training setup +# ------------------------ +criterion = nn.CrossEntropyLoss() +optimizer = optim.Adam([ + {"params": model.fc.parameters(), "lr": 1e-3}, +], lr=1e-3) + +scheduler = ReduceLROnPlateau(optimizer, mode="min", factor=0.5, patience=3, verbose=True) +best_val_f1 = 0.0 +patience, counter = 5, 0 + + +# ------------------------ +# Gradual Unfreeze +# ------------------------ +def unfreeze(epoch): + if epoch == 5: + for name, param in model.named_parameters(): + if "layer4" in name: + param.requires_grad = True + if epoch == 10: + for param in model.parameters(): + param.requires_grad = True + + +# ------------------------ +# Training Loop +# ------------------------ +EPOCHS = 20 +for epoch in range(EPOCHS): + unfreeze(epoch) + model.train() + total_loss, correct, total = 0.0, 0, 0 + for images, labels in train_loader: + images, labels = images.to(device), labels.to(device) + optimizer.zero_grad() + images, targets_a, targets_b, lam = mixup_data(images, labels, alpha=0.4) + outputs = model(images) + loss = mixup_criterion(criterion, outputs, targets_a, targets_b, lam) + loss.backward() + optimizer.step() + total_loss += loss.item() * images.size(0) + _, preds = outputs.max(1) + correct += preds.eq(labels).sum().item() + total += labels.size(0) + + train_acc = correct / total + train_loss = total_loss / total + + # Validation + model.eval() + all_preds, all_labels = [], [] + val_loss, val_correct, val_total = 0.0, 0, 0 + with torch.no_grad(): + for images, labels in val_loader: + images, labels = images.to(device), labels.to(device) + outputs = model(images) + loss = criterion(outputs, labels) + val_loss += loss.item() * images.size(0) + _, preds = outputs.max(1) + val_correct += preds.eq(labels).sum().item() + val_total += labels.size(0) + all_preds.extend(preds.cpu().numpy()) + all_labels.extend(labels.cpu().numpy()) + + val_acc = val_correct / val_total + val_loss /= val_total + val_f1 = f1_score(all_labels, all_preds, average="weighted") + + print(f"Epoch {epoch+1}/{EPOCHS} " + f"Train Loss: {train_loss:.4f}, Train Acc: {train_acc:.4f} " + f"Val Loss: {val_loss:.4f}, Val Acc: {val_acc:.4f}, Val F1: {val_f1:.4f}") + + scheduler.step(val_loss) + + # Save by F1 + if val_f1 > best_val_f1: + best_val_f1 = val_f1 + counter = 0 + torch.save(model.state_dict(), SAVE_PATH) + print("💾 Model improved (F1) and saved!") + else: + counter += 1 + print(f"⏳ No improvement. EarlyStopping counter: {counter}/{patience}") + if counter >= patience: + print("🛑 Early stopping triggered!") + break + +print(f"✅ Training finished. Best model saved to {SAVE_PATH}") diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/finetune_multi_stage3.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/finetune_multi_stage3.py new file mode 100644 index 000000000..eee68bd67 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/finetune_multi_stage3.py @@ -0,0 +1,191 @@ +# finetune_multi_stage3.py +import torch +import torch.nn as nn +import torch.optim as optim +from torch.utils.data import DataLoader, random_split +import albumentations as A +from albumentations.pytorch import ToTensorV2 +import cv2, os +import numpy as np +from sklearn.metrics import f1_score + +from agri_baseline.src.detectors.train.dictionary import CLASS_MAPPING +from agri_baseline.src.detectors.cnn_multi_classifier import build_multi_model +from torchvision import datasets + +# ========================= +# Config +# ========================= +DATA_DIR = "data_balanced/PlantDoc" +PREV_MODEL = "models/cnn_multi_finetuned.pth" +SAVE_PATH = "models/cnn_multi_stage3.pth" + +device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + + +# ========================= +# Augmentations +# ========================= +train_tfms = A.Compose([ + A.RandomResizedCrop(size=(224, 224), scale=(0.6, 1.0), p=1.0), + A.HorizontalFlip(p=0.5), + A.VerticalFlip(p=0.3), + A.RandomBrightnessContrast(p=0.4), + A.ShiftScaleRotate(shift_limit=0.05, scale_limit=0.2, rotate_limit=30, p=0.5), + A.GaussianBlur(p=0.2), + A.RandomGamma(p=0.3), + A.Normalize(mean=(0.485, 0.456, 0.406), + std=(0.229, 0.224, 0.225)), + ToTensorV2() +]) + +val_tfms = A.Compose([ + A.Resize(224, 224), + A.Normalize(mean=(0.485, 0.456, 0.406), + std=(0.229, 0.224, 0.225)), + ToTensorV2() +]) + + +# ========================= +# Dataset wrapper +# ========================= +class AlbumentationsDataset(torch.utils.data.Dataset): + def __init__(self, dataset, transform=None): + self.dataset = dataset + self.transform = transform + + def __getitem__(self, idx): + path, label = self.dataset.samples[idx] + img = cv2.imread(path) + img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) + if self.transform: + img = self.transform(image=img)["image"] + return img, label + + def __len__(self): + return len(self.dataset) + + +def prepare_dataset(path): + ds = datasets.ImageFolder(path) + new_samples, new_targets = [], [] + canonical = sorted(set(CLASS_MAPPING.values())) + class_to_idx = {cls: i for i, cls in enumerate(canonical)} + + for pth, idx in ds.samples: + raw = ds.classes[idx].lower().replace(" ", "_") + canon = CLASS_MAPPING.get(raw) + if canon is None: + raise ValueError(f"Class {raw} missing in CLASS_MAPPING") + new_samples.append((pth, class_to_idx[canon])) + new_targets.append(class_to_idx[canon]) + + ds.samples = new_samples + ds.targets = new_targets + ds.classes = canonical + ds.class_to_idx = class_to_idx + return ds + + +# ========================= +# Progressive unfreezing +# ========================= +def unfreeze_layers(model, stages): + """ + stages: List of layer names to release (e.g.: ["layer3", "layer2"]) + """ + for name, param in model.named_parameters(): + for stage in stages: + if stage in name: + param.requires_grad = True + + +# ========================= +# Training loop +# ========================= +def train_stage3(model, train_loader, val_loader, epochs=20): + criterion = nn.CrossEntropyLoss() + optimizer = optim.Adam(filter(lambda p: p.requires_grad, model.parameters()), lr=1e-4) + + best_f1, patience, counter = 0, 5, 0 + for epoch in range(epochs): + model.train() + total_loss, total_correct, total = 0, 0, 0 + for xb, yb in train_loader: + xb, yb = xb.to(device), yb.to(device) + optimizer.zero_grad() + out = model(xb) + loss = criterion(out, yb) + loss.backward() + optimizer.step() + total_loss += loss.item() * xb.size(0) + _, preds = out.max(1) + total_correct += preds.eq(yb).sum().item() + total += yb.size(0) + + train_acc = total_correct / total + train_loss = total_loss / total + + # Validation + model.eval() + val_loss, val_correct, val_total = 0, 0, 0 + all_preds, all_labels = [], [] + with torch.no_grad(): + for xb, yb in val_loader: + xb, yb = xb.to(device), yb.to(device) + out = model(xb) + loss = criterion(out, yb) + val_loss += loss.item() * xb.size(0) + _, preds = out.max(1) + val_correct += preds.eq(yb).sum().item() + val_total += yb.size(0) + all_preds.extend(preds.cpu().numpy()) + all_labels.extend(yb.cpu().numpy()) + + val_acc = val_correct / val_total + val_loss /= val_total + val_f1 = f1_score(all_labels, all_preds, average="weighted") + + print(f"Epoch {epoch+1}/{epochs} | Train Loss: {train_loss:.4f} Acc: {train_acc:.3f} " + f"| Val Loss: {val_loss:.4f} Acc: {val_acc:.3f} F1: {val_f1:.3f}") + + if val_f1 > best_f1: + best_f1 = val_f1 + counter = 0 + torch.save(model.state_dict(), SAVE_PATH) + print(f"💾 Model improved (F1={val_f1:.3f}) and saved!") + else: + counter += 1 + if counter >= patience: + print("🛑 EarlyStopping triggered.") + break + + +# ========================= +# Main +# ========================= +if __name__ == "__main__": + full_ds = prepare_dataset(os.path.join(DATA_DIR, "train")) + train_size = int(0.8 * len(full_ds)) + val_size = len(full_ds) - train_size + train_ds, val_ds = random_split(full_ds, [train_size, val_size]) + + train_ds = AlbumentationsDataset(train_ds.dataset, transform=train_tfms) + val_ds = AlbumentationsDataset(val_ds.dataset, transform=val_tfms) + + train_loader = DataLoader(train_ds, batch_size=32, shuffle=True) + val_loader = DataLoader(val_ds, batch_size=32) + + model = build_multi_model(num_classes=len(full_ds.classes)).to(device) + model.load_state_dict(torch.load(PREV_MODEL, map_location=device)) + + # In step 3 we will release additional layers beyond layer4 + for p in model.parameters(): + p.requires_grad = False + for stage in ["layer3", "layer4", "fc"]: + unfreeze_layers(model, [stage]) + print(f"🔓 Unfroze {stage}") + + train_stage3(model, train_loader, val_loader, epochs=15) + print(f"✅ Training done. Best model saved to {SAVE_PATH}") diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/train_binary_multi.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/train_binary_multi.py new file mode 100644 index 000000000..0d48afb36 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/research/detectors/train/train_binary_multi.py @@ -0,0 +1,152 @@ +# agri-baseline/src/detectors/train_binary_multi.py +import argparse +import os +import torch +import torch.nn as nn +from torch.utils.data import DataLoader, WeightedRandomSampler +from torchvision import datasets, transforms +from torch.optim.lr_scheduler import ReduceLROnPlateau +import numpy as np + +from ...agri_baseline.src.detectors.cnn_binary_classifier import build_binary_model +from ...agri_baseline.src.detectors.cnn_multi_classifier import build_multi_model +from ...agri_baseline.src.detectors.dataset_binary import BinaryDiseaseDataset + + +def train_model(model, dataloader, val_dl, device, epochs, lr, out_path): + opt = torch.optim.Adam(model.parameters(), lr=lr) + loss_fn = nn.CrossEntropyLoss() + scheduler = ReduceLROnPlateau(opt, mode="min", factor=0.5, patience=3, verbose=True) + + best_val_loss = float("inf") + patience, counter = 5, 0 + + for epoch in range(epochs): + model.train() + running_loss, correct, total = 0.0, 0, 0 + for batch in dataloader: + if len(batch) == 3: + xb, yb, _ = batch + else: + xb, yb = batch + xb, yb = xb.to(device), yb.to(device) + + opt.zero_grad() + preds = model(xb) + loss = loss_fn(preds, yb) + loss.backward() + opt.step() + + running_loss += loss.item() * xb.size(0) + _, predicted = preds.max(1) + correct += predicted.eq(yb).sum().item() + total += yb.size(0) + + acc = correct / total + + # Validation + val_loss, val_acc = evaluate(model, val_dl, device, loss_fn) + print(f"Epoch {epoch+1}/{epochs} " + f"Train Loss={running_loss/total:.4f} Train Acc={acc:.3f} " + f"Val Loss={val_loss:.4f} Val Acc={val_acc:.3f}") + + scheduler.step(val_loss) + + # EarlyStopping + if val_loss < best_val_loss: + best_val_loss = val_loss + counter = 0 + torch.save(model.state_dict(), out_path) + print(f"💾 Saved best model {out_path}") + else: + counter += 1 + print(f"⏳ EarlyStopping counter {counter}/{patience}") + if counter >= patience: + print("🛑 Early stopping triggered") + break + + +def evaluate(model, dataloader, device, loss_fn): + model.eval() + correct, total, total_loss = 0, 0, 0.0 + with torch.no_grad(): + for batch in dataloader: + if len(batch) == 3: + xb, yb, _ = batch + else: + xb, yb = batch + xb, yb = xb.to(device), yb.to(device) + preds = model(xb) + loss = loss_fn(preds, yb) + total_loss += loss.item() * xb.size(0) + _, predicted = preds.max(1) + correct += predicted.eq(yb).sum().item() + total += yb.size(0) + return total_loss/total, correct/total + + +def make_sampler(targets): + class_counts = np.bincount(targets) + class_weights = 1. / class_counts + sample_weights = [class_weights[t] for t in targets] + return WeightedRandomSampler(weights=sample_weights, + num_samples=len(sample_weights), + replacement=True) + + +def main(): + p = argparse.ArgumentParser() + p.add_argument("--data", required=True, help="Dataset root (with train/val/test)") + p.add_argument("--out", default="./models") + p.add_argument("--epochs", type=int, default=10) + p.add_argument("--batch", type=int, default=32) + p.add_argument("--lr", type=float, default=1e-3) + p.add_argument("--device", default="cpu") + args = p.parse_args() + + device = torch.device(args.device) + + # Augmentations + train_tfms = transforms.Compose([ + transforms.RandomResizedCrop(224, scale=(0.8, 1.0)), + transforms.RandomHorizontalFlip(), + transforms.RandomRotation(15), + transforms.ColorJitter(brightness=0.2, contrast=0.2, saturation=0.2), + transforms.ToTensor(), + transforms.Normalize([0.485,0.456,0.406],[0.229,0.224,0.225]) + ]) + test_tfms = transforms.Compose([ + transforms.Resize((224,224)), + transforms.ToTensor(), + transforms.Normalize([0.485,0.456,0.406],[0.229,0.224,0.225]) + ]) + + # Binary dataset + train_bin = BinaryDiseaseDataset(os.path.join(args.data,"train"), transform=train_tfms) + val_bin = BinaryDiseaseDataset(os.path.join(args.data,"val"), transform=test_tfms) + + sampler_bin = make_sampler(train_bin.targets) + train_dl_bin = DataLoader(train_bin, batch_size=args.batch, sampler=sampler_bin) + val_dl_bin = DataLoader(val_bin, batch_size=args.batch) + + model_bin = build_binary_model().to(device) + train_model(model_bin, train_dl_bin, val_dl_bin, device, args.epochs, args.lr, + os.path.join(args.out, "cnn_binary.pth")) + + # Multi-class dataset + train_multi = datasets.ImageFolder(os.path.join(args.data,"train"), transform=train_tfms) + val_multi = datasets.ImageFolder(os.path.join(args.data,"val"), transform=test_tfms) + + sampler_multi = make_sampler([y for _, y in train_multi.samples]) + train_dl_multi = DataLoader(train_multi, batch_size=args.batch, sampler=sampler_multi) + val_dl_multi = DataLoader(val_multi, batch_size=args.batch) + + model_multi = build_multi_model(num_classes=len(train_multi.classes)).to(device) + train_model(model_multi, train_dl_multi, val_dl_multi, device, args.epochs, args.lr, + os.path.join(args.out, "cnn_multi.pth")) + + torch.save({"classes": train_multi.classes}, + os.path.join(args.out,"multi_classes.pth")) + +if __name__=="__main__": + main() diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/conftest.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/conftest.py new file mode 100644 index 000000000..486e4fe52 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/conftest.py @@ -0,0 +1,29 @@ +# tests/conftest.py +import os +import pytest +from sqlalchemy import text +from agri_baseline.src.pipeline.db import get_engine + +@pytest.fixture(autouse=True, scope="function") +def _ensure_local_db_url(monkeypatch): + """ + Guarantee DATABASE_URL exists for tests. + """ + monkeypatch.setenv( + "DATABASE_URL", + os.getenv( + "DATABASE_URL", + "postgresql+psycopg2://missions_user:pg123@localhost:5432/missions_db", + ), + ) + +@pytest.fixture(autouse=True) +def _clean_tables_before_test(): + """ + Clean key tables before each test so counts can increase deterministically. + Adjust the list to your schema. + """ + tables = ["anomalies", "tile_stats", "event_logs"] + with get_engine().begin() as conn: + for t in tables: + conn.execute(text(f"DELETE FROM {t}")) diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_batch_runner.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_batch_runner.py new file mode 100644 index 000000000..db88f63bc --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_batch_runner.py @@ -0,0 +1,68 @@ +# Purpose: End-to-end tests for the BatchRunner pipeline. +# Verifies that running on image folders or single images correctly writes results to the database. + +import pytest +from pathlib import Path +from sqlalchemy import text + +from agri_baseline.src.batch_runner import BatchRunner +from agri_baseline.src.pipeline.db import get_engine + + +@pytest.fixture +def folder_with_images() -> Path: + """ + Return a folder that contains a few test images. + Adjust the path if your dataset sits elsewhere. + """ + folder = Path("./data_balanced/PlantDoc/train/Bell_pepper leaf") + assert folder.exists(), f"Images folder not found: {folder.resolve()}" + return folder + + +def _count(conn, sql: str, params: dict | None = None) -> int: + """ + Small helper: run a COUNT(*) query safely with SQLAlchemy 2.0. + """ + return conn.execute(text(sql), params or {}).scalar() or 0 + + +def test_run_batch_on_images_folder(folder_with_images: Path): + """ + End-to-end: run the batch pipeline on a folder and verify DB writes happened. + We compare counts before/after instead of relying on specific image_id values. + """ + runner = BatchRunner() + + with get_engine().begin() as conn: + before = _count(conn, "SELECT COUNT(1) FROM anomalies") + + runner.run_folder(folder_with_images) + + with get_engine().begin() as conn: + after = _count(conn, "SELECT COUNT(1) FROM anomalies") + + assert after > before, "No detections were written to the database." + + +def test_process_single_image(): + """ + Process a single image and assert the DB anomalies count has increased. + This avoids fragile assumptions on the exact image_id in the DB. + """ + image_path = Path( + "./data_balanced/PlantDoc/train/Bell_pepper leaf/0f3s5A.jpg" + ) + assert image_path.exists(), f"Test image not found: {image_path.resolve()}" + + runner = BatchRunner() + + with get_engine().begin() as conn: + before = _count(conn, "SELECT COUNT(1) FROM anomalies") + + runner.process_image(image_path) + + with get_engine().begin() as conn: + after = _count(conn, "SELECT COUNT(1) FROM anomalies") + + assert after > before, "Single image was not processed correctly." diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_disease_model.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_disease_model.py new file mode 100644 index 000000000..c2cb78625 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_disease_model.py @@ -0,0 +1,17 @@ +# Purpose: Unit tests for the DiseaseDetector class. +# Ensures the model loads successfully and returns valid detections on dummy input. + +import pytest +from agri_baseline.src.detectors.disease_model import DiseaseDetector +import numpy as np + +def test_disease_detector_model_loads(): + detector = DiseaseDetector(model_path="models/cnn_multi_stage3.pth") + assert detector.model is not None, "Model failed to load correctly." + +def test_disease_detector_predicts(): + detector = DiseaseDetector() + img = np.zeros((224, 224, 3)) # Dummy image for testing + detections = detector.run(img) + assert len(detections) > 0, "Model did not return any detections." + assert detections[0].confidence > 0, "Detection confidence should be greater than 0." diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_minio_integration_mock.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_minio_integration_mock.py new file mode 100644 index 000000000..369b7070c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_minio_integration_mock.py @@ -0,0 +1,120 @@ +# Purpose: Mock-based integration tests for MinIO storage. +# Simulates MinIO object downloads, saves them locally, and verifies images can be loaded successfully. + +from __future__ import annotations + +from io import BytesIO +from pathlib import Path +from typing import Dict, Iterable + +import pytest +from PIL import Image + +from agri_baseline.src.storage import minio_sync +from agri_baseline.src.storage.minio_client import MinioConfig +from agri_baseline.src.pipeline.utils import load_image + + +class _FakeObj: + """Mimics the object returned by client.list_objects().""" + + def __init__(self, object_name: str) -> None: + self.object_name = object_name + + +class _FakeResponse: + """ + Minimal MinIO get_object-like response object. + + Provides: + - read(amt: int | None = None) -> bytes + - close() -> None + - release_conn() -> None + + This mirrors what MinIO/urllib3 responses typically expose, so production code + that calls release_conn() won't fail under the mock. + """ + + def __init__(self, data: bytes) -> None: + self._buf = BytesIO(data) + + def read(self, amt: int | None = None) -> bytes: + return self._buf.read() if amt is None else self._buf.read(amt) + + def close(self) -> None: + self._buf.close() + + def release_conn(self) -> None: + # In real clients this releases underlying HTTP resources. + # No-op here is fine for tests. + pass + + +class _FakeMinio: + """ + Fake MinIO client that supports the subset used by minio_sync: + - list_objects(bucket, prefix, recursive) -> Iterable[_FakeObj] + - get_object(bucket, key) -> _FakeResponse + """ + + def __init__(self, payload_by_key: Dict[str, bytes]) -> None: + self._payload_by_key = payload_by_key + + def list_objects(self, bucket: str, prefix: str, recursive: bool) -> Iterable[_FakeObj]: + for key in self._payload_by_key: + if key.startswith(prefix) and not key.endswith("/"): + yield _FakeObj(key) + + def get_object(self, bucket: str, key: str) -> _FakeResponse: + data = self._payload_by_key[key] + return _FakeResponse(data) + + +@pytest.fixture +def fake_jpeg() -> bytes: + """Create a tiny deterministic JPEG in-memory.""" + img = Image.new("RGB", (32, 24), (10, 20, 30)) + buf = BytesIO() + img.save(buf, format="JPEG") + return buf.getvalue() + + +def test_minio_download_and_load(monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, + fake_jpeg: bytes) -> None: + """ + Flow under test: + 1) list prefix from MinIO (fake). + 2) download files to local cache dir. + 3) ensure those files exist and can be loaded with load_image. + """ + + # 1) Arrange fake MinIO payload (two images under mission-123/) + payload = { + "mission-123/imgA.jpg": fake_jpeg, + "mission-123/imgB.jpg": fake_jpeg, + } + fake_client = _FakeMinio(payload) + + # 2) Monkeypatch build_client to return our fake client + monkeypatch.setattr(minio_sync, "build_client", lambda cfg: fake_client, raising=True) + + # 3) Prepare config and download target folder + cfg = MinioConfig( + endpoint="127.0.0.1:9000", + access_key="minioadmin", + secret_key="minioadmin", + bucket="leaves", + secure=False, + ) + out_dir = tmp_path / "cache" + + # 4) Act: download objects to local dir + paths = minio_sync.download_prefix_to_dir(cfg, prefix="mission-123", local_dir=out_dir) + + # 5) Assert: files were written and are loadable + assert len(paths) == 2, f"Expected 2 files, got {len(paths)}" + for p in paths: + assert p.exists() and p.is_file(), f"Missing file: {p}" + img, w, h = load_image(str(p)) + assert img is not None and w > 0 and h > 0, f"Failed to load image {p}" diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_run_detectors.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_run_detectors.py new file mode 100644 index 000000000..6e0f13e26 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_run_detectors.py @@ -0,0 +1,21 @@ +# Purpose: Tests for running the DiseaseDetector model. +# Checks that detections are produced with valid confidence values on dummy images. + +import pytest +from agri_baseline.src.detectors.disease_model import DiseaseDetector +import numpy as np + +@pytest.fixture +def dummy_image(): + """Provide a dummy image for testing.""" + return np.zeros((224, 224, 3)) # Black dummy image + +def test_disease_detector_runs(dummy_image): + detector = DiseaseDetector() + detections = detector.run(dummy_image) + assert len(detections) > 0, "Disease detection did not return any detections." + assert detections[0].confidence > 0, "Detection confidence should be greater than 0." + +def test_disease_detector_model_loads(): + detector = DiseaseDetector(model_path="models/cnn_multi_stage3.pth") + assert detector.model is not None, "Model failed to load correctly." diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_utils_local.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_utils_local.py new file mode 100644 index 000000000..ab76fe8cf --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_utils_local.py @@ -0,0 +1,27 @@ +# Purpose: Local unit tests for utility functions. +# Covers image loading, image ID extraction, and bounding box clamping logic. + +from pathlib import Path +from PIL import Image +from agri_baseline.src.pipeline.utils import load_image, image_id_from_path, clamp_bbox + +def _write_test_image(tmp_dir: Path, name: str = "test.jpg") -> Path: + img = Image.new("RGB", (64, 48), (127, 200, 50)) + path = tmp_dir / name + img.save(path, format="JPEG") + return path + +def test_load_image_local(tmp_path: Path): + img_path = _write_test_image(tmp_path) + img, w, h = load_image(str(img_path)) + assert img is not None + assert (w, h) == (64, 48) + +def test_image_id_from_path_no_fs(tmp_path: Path): + fake_path = tmp_path / "nested" / "test.jpg" # no file needed + image_id = image_id_from_path(str(fake_path)) + assert isinstance(image_id, str) and image_id + +def test_clamp_bbox_pure(): + x, y, w, h = clamp_bbox(10, 10, 250, 250, 224, 224) + assert x >= 0 and y >= 0 and w <= 224 and h <= 224 diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_validator.py b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_validator.py new file mode 100644 index 000000000..17957c530 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Detection_Jobs/tests/test_validator.py @@ -0,0 +1,119 @@ +# Purpose: Integration tests for the Validator module. +# Verifies event logging from findings and correctness of batch summary generation in the database. + +import pytest +from sqlalchemy import text + +from agri_baseline.src.validator.validator import Validator +from agri_baseline.src.validator.rules import Finding +from agri_baseline.src.pipeline.db import get_engine +from agri_baseline.src.pipeline import config +from agri_baseline.src.pipeline.db import get_engine + +@pytest.fixture(autouse=True) +def _seed_anomalies_for_summary(): + """ + Ensure the DB has minimal data for batch_summary: + - device 'device-1' + - anomaly type id=1 + - mission id=1 with small polygon + - two anomalies with same image_id and non-null geom + Idempotent: safe to run before every test. + """ + with get_engine().begin() as conn: + conn.exec_driver_sql(""" + INSERT INTO devices(device_id, model, owner, active) + VALUES ('device-1','sim','lab',true) + ON CONFLICT (device_id) DO NOTHING; + """) + conn.exec_driver_sql(""" + INSERT INTO anomaly_types(anomaly_type_id, code, description) + VALUES (1,'disease_spot','Leaf disease spot') + ON CONFLICT (anomaly_type_id) DO NOTHING; + """) + conn.exec_driver_sql(""" + INSERT INTO missions(mission_id, start_time, area_geom) + VALUES (1, now(), ST_GeomFromText('POLYGON((0 0,1 0,1 1,0 1,0 0))',4326)) + ON CONFLICT (mission_id) DO NOTHING; + """) + conn.exec_driver_sql(""" + INSERT INTO anomalies(mission_id, device_id, ts, anomaly_type_id, severity, details, geom) + VALUES + (1, 'device-1', now(), 1, 0.6, + '{"image_id":"seed_img_for_summary"}'::jsonb, + ST_GeomFromText('POINT(0.50 0.50)',4326)), + (1, 'device-1', now(), 1, 0.7, + '{"image_id":"seed_img_for_summary"}'::jsonb, + ST_GeomFromText('POINT(0.55 0.52)',4326)) + ON CONFLICT DO NOTHING; + """) + yield + +@pytest.fixture +def dummy_finding() -> Finding: + """ + Create a minimal Finding to simulate a validator output. + Scope/value names should match your Validator implementation. + """ + return Finding( + scope="image", + image_id="test_image", + rule="bbox_oob", + severity="warn", + message="BBox out of bounds", + ) + + +def _count(conn, sql: str, params: dict | None = None) -> int: + """ + Small helper: run a COUNT(*) query safely with SQLAlchemy 2.0. + """ + return conn.execute(text(sql), params or {}).scalar() or 0 + + +def test_validator_image_findings(dummy_finding: Finding): + """ + Ensure validator writes a record into event_logs for the given finding. + We assert a strictly increasing count for the message we inserted. + """ + validator = Validator() + + with get_engine().begin() as conn: + before = _count( + conn, + "SELECT COUNT(1) FROM event_logs WHERE message = :msg", + {"msg": dummy_finding.message}, + ) + + validator.image_findings([dummy_finding]) + + with get_engine().begin() as conn: + after = _count( + conn, + "SELECT COUNT(1) FROM event_logs WHERE message = :msg", + {"msg": dummy_finding.message}, + ) + + assert after > before, "Finding was not written to event_logs." + + +def test_batch_summary(): + """ + Run batch_summary and verify tile_stats is populated or remains populated. + We allow idempotency (>=) but also require that there is some data (> 0). + """ + validator = Validator() + + with get_engine().begin() as conn: + print("DEBUG DB_URL:", config.DB_URL) + print("DEBUG anomalies:", conn.exec_driver_sql("SELECT COUNT(*) FROM anomalies").scalar()) + print("DEBUG tile_stats:", conn.exec_driver_sql("SELECT COUNT(*) FROM tile_stats").scalar()) + before = _count(conn, "SELECT COUNT(1) FROM tile_stats") + + validator.batch_summary() + + with get_engine().begin() as conn: + after = _count(conn, "SELECT COUNT(1) FROM tile_stats") + + assert after >= before, "tile_stats count unexpectedly decreased." + assert after > 0, "No images found in tile_stats for batch summary." diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Makefile b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Makefile new file mode 100644 index 000000000..94e2c9d4c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/Makefile @@ -0,0 +1,7 @@ +.PHONY: ci-e2e ci-detection + +ci-e2e: + cd e2e_kafka_flink && pytest tests --cov=e2e_pipeline --cov-report=xml --maxfail=1 -v + +ci-detection: + cd agri-baseline && pytest tests --cov=agri_baseline --cov-report=xml --maxfail=1 -v diff --git a/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/VENDORED_FROM.txt b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/VENDORED_FROM.txt new file mode 100644 index 000000000..b1786ac32 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/Detection_Jobs/VENDORED_FROM.txt @@ -0,0 +1,4 @@ +VENDORED FROM (saved 2025-11-09T04:18:09+02:00) +------------------------------------- +origin https://github.com/KamaTechOrg/AgCloud.git (fetch) [blob:none] +origin https://github.com/KamaTechOrg/AgCloud.git (push) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/.gitignore b/airflow_bundle/leaf-pipeline/projects/disease-monitor/.gitignore new file mode 100644 index 000000000..4fb10b81c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/.gitignore @@ -0,0 +1,54 @@ +# ==== OS / IDE ==== +.DS_Store +Thumbs.db +.vscode/ +.idea/ + +# ==== Node ==== +node_modules/ +dist/ + +# ==== Python ==== +__pycache__/ +*.py[cod] +*.pyc +*.pyo +*.so +*.dylib + +# ==== Virtual envs ==== +.venv/ +venv/ +ENV/ +env/ + +# ==== Packaging / build ==== +build/ +*.egg-info/ + +# ==== Environment / Secrets ==== +.env +.env.* + +# ==== Data / Notebooks / Logs ==== +*.log +*.ipynb +.ipynb_checkpoints/ + +# ==== Artifacts / Wheels / Models ==== +artifacts/ +.wheels/ +wheels/ +*.whl +*.pt +*.pth +*.bin + +# ==== Coverage reports ==== +.pytest_cache/ +.coverage +coverage.xml +htmlcov/ + +server/embed_pb2.py +server/embed_pb2_grpc.py diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/Makefile b/airflow_bundle/leaf-pipeline/projects/disease-monitor/Makefile new file mode 100644 index 000000000..94e2c9d4c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/Makefile @@ -0,0 +1,7 @@ +.PHONY: ci-e2e ci-detection + +ci-e2e: + cd e2e_kafka_flink && pytest tests --cov=e2e_pipeline --cov-report=xml --maxfail=1 -v + +ci-detection: + cd agri-baseline && pytest tests --cov=agri_baseline --cov-report=xml --maxfail=1 -v diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/VENDORED_FROM.txt b/airflow_bundle/leaf-pipeline/projects/disease-monitor/VENDORED_FROM.txt new file mode 100644 index 000000000..b1786ac32 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/VENDORED_FROM.txt @@ -0,0 +1,4 @@ +VENDORED FROM (saved 2025-11-09T04:18:09+02:00) +------------------------------------- +origin https://github.com/KamaTechOrg/AgCloud.git (fetch) [blob:none] +origin https://github.com/KamaTechOrg/AgCloud.git (push) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/.dockerignore b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/.dockerignore new file mode 100644 index 000000000..9bd273d4f --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/.dockerignore @@ -0,0 +1,25 @@ +# Python +__pycache__/ +*.pyc +*.pyo +*.pyd +.Python +.venv/ +venv/ + +# Tests and caches +.pytest_cache/ +tests/ + +# Local data / artifacts +data/ +alerts.db + +# Git +.git/ +.gitignore + +# IDE +.vscode/ +.idea/ + diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/.gitignore b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/.gitignore new file mode 100644 index 000000000..da73fe5e4 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/.gitignore @@ -0,0 +1,2 @@ +# Ignore local data +data/ diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/Dockerfile b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/Dockerfile new file mode 100644 index 000000000..49d99c76c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/Dockerfile @@ -0,0 +1,34 @@ +FROM mcr.microsoft.com/devcontainers/python:1-3.11-bullseye + +WORKDIR /app + +# 1) Install CA tools and curl +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates curl \ + && rm -rf /var/lib/apt/lists/* + +# 2) Add NetFree certificate and register in system trust store + +# Ensure Python, requests, and pip use the updated CA bundle +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV PIP_CERT=/etc/ssl/certs/ca-certificates.crt + +# 3) Install Python dependencies (use trusted hosts to simplify NetFree path) +COPY requirements.txt /app/requirements.txt +RUN pip install --trusted-host pypi.org --trusted-host pypi.python.org \ + --trusted-host files.pythonhosted.org --no-cache-dir -r requirements.txt + +# 4) Install the package (PEP517) with the same trusted hosts +COPY pyproject.toml README.md /app/ +COPY src /app/src +RUN pip install --trusted-host pypi.org --trusted-host pypi.python.org \ + --trusted-host files.pythonhosted.org --no-cache-dir . + +# 5) Copy configs (can be overridden by a bind mount) +COPY configs /app/configs + +ENV PYTHONUNBUFFERED=1 + +ENTRYPOINT ["python", "-m", "disease_monitor.cli"] + diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/Dockerfile.local b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/Dockerfile.local new file mode 100644 index 000000000..3622ef88d --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/Dockerfile.local @@ -0,0 +1,27 @@ +FROM docker.io/library/python@sha256:e0c4fae70d550834a40f6c3e0326e02cfe239c2351d922e1fb1577a3c6ebde02 + +WORKDIR /app + +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates curl python3-requests \ + && rm -rf /var/lib/apt/lists/* + +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV PIP_CERT=/etc/ssl/certs/ca-certificates.crt + +COPY requirements.txt /app/requirements.txt +RUN pip install --trusted-host pypi.org --trusted-host pypi.python.org \ + --trusted-host files.pythonhosted.org --no-cache-dir -r requirements.txt +RUN pip install --trusted-host pypi.org --trusted-host pypi.python.org \ + --trusted-host files.pythonhosted.org --no-cache-dir requests + +COPY pyproject.toml README.md /app/ +COPY src /app/src +RUN pip install --trusted-host pypi.org --trusted-host pypi.python.org \ + --trusted-host files.pythonhosted.org --no-cache-dir . + +COPY configs /app/configs + +ENV PYTHONUNBUFFERED=1 +ENTRYPOINT ["python", "-m", "disease_monitor.cli"] diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/README.md b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/README.md new file mode 100644 index 000000000..a0eb9bda6 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/README.md @@ -0,0 +1,127 @@ +# Disease Monitor (Offline) + +Offline batch job that reads disease detections from **Postgres**, aggregates data, +builds baselines, detects anomalies/worsening, deduplicates & rate-limits alerts, +delivers notifications (Slack/Webhook/Email), and writes alerts back to **Postgres**. + +> **Note:** The pipeline uses **Postgres only** (both sources and sink). No CSV/SQLite. + +--- + +## Data Sources & Sink (Postgres) + +**Sources** +- `anomalies` — per-image detections (0..N rows per image) +- `tile_stats` — exactly 1 row per image (summary) +- `event_logs` — QA & validator logs (rules/metrics/errors) + +**Sink** +- `alerts` — unified alerts table (rules: `COUNT_SPIKE`, `WORSENING_TREND`) + +--- + +## Config (`configs/config.example.yaml`) + +Main sections: +- **io**: Postgres URL (e.g. `postgresql+psycopg2://user:pass@host:5432/db`) +- **windows**: frequency (`"D"`/`"W"`), timezone (e.g. `"UTC"`) +- **baseline**: method (`mean`/`median`), lookback, min_history, optional seasonality +- **rules**: thresholds & toggles for `count_anomaly` (zscore/iqr) and `worsening` (slope/ewma) +- **alerting**: dedup cooldown (windows), resolve-after-no-anomaly, per-run rate limit, group_by_window +- **delivery**: slack/webhook/email targets (can be disabled) +- **run**: `dry_run` and optional filters + +Example: +```yaml +io: + postgres_url: "postgresql+psycopg2://missions_user:pg123@localhost:5432/missions_db" + +windows: + frequency: "D" + timezone: "UTC" + +baseline: + method: "median" + lookback_periods: 28 + min_history: 7 + seasonality: null + +rules: + count_anomaly: + enabled: true + method: "zscore" + z_threshold: 3.0 + iqr_k: 1.5 + min_count: 3 + worsening: + enabled: true + method: "slope" + slope_lookback: 7 + slope_min: 0.02 + min_periods: 5 + ewma_span: 7 + ewma_threshold: 0.6 + +alerting: + dedup_cooldown_windows: 3 + resolve_after_no_anomaly: 3 + rate_limit_per_run: 100 + group_by_window: true + +delivery: + slack: + enabled: false + webhook_url: "" + webhook: + enabled: false + url: "" + headers: {} + email: + enabled: false + smtp_host: "" + smtp_port: 587 + username: "" + password_env: "SMTP_PASSWORD" + from_addr: "" + to_addrs: [] + +run: + dry_run: false +``` + +--- + +## Install & Run + +```bash +# Create & activate venv (Linux/Mac) +python -m venv .venv +source .venv/bin/activate + +# On Windows (PowerShell): +# python -m venv .venv +# .venv\Scripts\Activate.ps1 + +# Install +pip install -r requirements.txt + +# Run +python -m disease_monitor.cli --config configs/config.example.yaml --log-level INFO +``` + +--- + +## Tests + +```bash +pytest +``` + +--- + + +## Notes + +- Thresholds, lookbacks, and active rules are fully configurable from YAML. +- Logs and runtime counters are emitted to stdout. +- Extend notifiers in `src/disease_monitor/notifiers`. diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/config.docker.yaml b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/config.docker.yaml new file mode 100644 index 000000000..fb46acdfe --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/config.docker.yaml @@ -0,0 +1,64 @@ +io: + # IMPORTANT: use the Docker service name of Postgres (from your compose): + postgres_url: "postgresql+psycopg2://missions_user:pg123@postgres:5432/missions_db" + +windows: + frequency: "D" + timezone: "UTC" + +source_mapping: + entity_dim: "mission" # or "region"/"device" + area_strategy: "none" # or "region_area" (requires regions table/geom) + filters: + start_time: null + end_time: null + anomaly_codes: null + +baseline: + method: "median" + lookback_periods: 28 + min_history: 7 + seasonality: null + +rules: + count_anomaly: + enabled: true + method: "zscore" + z_threshold: 3.0 + iqr_k: 1.5 + min_count: 3 + worsening: + enabled: true + method: "slope" + slope_lookback: 7 + slope_min: 0.02 + min_periods: 5 + ewma_span: 7 + ewma_threshold: 0.6 + +alerting: + dedup_cooldown_windows: 3 + resolve_after_no_anomaly: 3 + rate_limit_per_run: 100 + group_by_window: true + +delivery: + slack: + enabled: false + webhook_url: "" + webhook: + enabled: false + url: "" + headers: {} + email: + enabled: false + smtp_host: "" + smtp_port: 587 + username: "" + password_env: "SMTP_PASSWORD" + from_addr: "" + to_addrs: [] + +run: + dry_run: false + diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/config.example.yaml b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/config.example.yaml new file mode 100644 index 000000000..6d4d8d699 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/config.example.yaml @@ -0,0 +1,70 @@ +io: + postgres_url: "postgresql+psycopg2://missions_user:pg123@localhost:5432/missions_db" + +windows: + frequency: "D" + timezone: "UTC" + +source_mapping: + entity_dim: "mission" # or "region"/"device" + area_strategy: "none" # or "region_area" + filters: + start_time: null + end_time: null + anomaly_codes: null + +baseline: + method: "median" + lookback_periods: 28 + min_history: 7 + seasonality: null + +rules: + count_anomaly: + enabled: true + method: "zscore" + z_threshold: 3.0 + iqr_k: 1.5 + min_count: 3 + worsening: + enabled: true + method: "slope" + slope_lookback: 7 + slope_min: 0.02 + min_periods: 5 + ewma_span: 7 + ewma_threshold: 0.6 + +alerting: + dedup_cooldown_windows: 3 + resolve_after_no_anomaly: 3 + rate_limit_per_run: 100 + group_by_window: true + +delivery: + slack: + enabled: false + webhook_url: "" # paste Slack Webhook URL here if you want to enable + webhook: + enabled: false + url: "" # paste your Webhook URL here if you want to enable + headers: {} # optional headers map + email: + enabled: false + smtp_host: "" # paste your SMTP server address here if you want to enable + smtp_port: 587 + username: "" + password_env: "SMTP_PASSWORD" + from_addr: "" + to_addrs: [] + + alertmanager: + enabled: false + url: "http://localhost:9093" + default_severity: "warning" + extra_labels: + system: "disease-monitor" + team: "ag" + +run: + dry_run: false diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/disease_monitor.yaml b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/disease_monitor.yaml new file mode 100644 index 000000000..832d6daf7 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/configs/disease_monitor.yaml @@ -0,0 +1,68 @@ +io: + # IMPORTANT: use the Docker service name of Postgres (from your compose): + postgres_url: "postgresql+psycopg2://missions_user:pg123@postgres:5432/missions_db" + +windows: + frequency: "D" + timezone: "UTC" + +source_mapping: + entity_dim: "device" + area_strategy: "none" # or "region_area" (requires regions table/geom) + filters: + start_time: null + end_time: null + anomaly_codes: null + +baseline: + method: "median" + lookback_periods: 28 + min_history: 7 + seasonality: null + +rules: + count_anomaly: + enabled: true + method: "zscore" + z_threshold: 3.0 + iqr_k: 1.5 + min_count: 3 + worsening: + enabled: true + method: "slope" + slope_lookback: 7 + slope_min: 0.02 + min_periods: 5 + ewma_span: 7 + ewma_threshold: 0.6 + +alerting: + dedup_cooldown_windows: 3 + resolve_after_no_anomaly: 3 + rate_limit_per_run: 100 + group_by_window: true + +delivery: + kafka: + enabled: false + brokers: "kafka:9092" + topic: "alerts" + slack: + enabled: false + webhook_url: "" + webhook: + enabled: false + url: "" + headers: {} + email: + enabled: false + smtp_host: "" + smtp_port: 587 + username: "" + password_env: "SMTP_PASSWORD" + from_addr: "" + to_addrs: [] + +run: + dry_run: false + diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/docker-compose.yml b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/docker-compose.yml new file mode 100644 index 000000000..15a0a0baa --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/docker-compose.yml @@ -0,0 +1,21 @@ +services: + disease-monitor: + build: + context: . + dockerfile: Dockerfile + image: disease-monitor:latest + command: ["--config", "/app/configs/config.docker.yaml", "--log-level", "INFO"] + environment: + TZ: "UTC" + # If you enable email delivery and use password_env=SMTP_PASSWORD: + # SMTP_PASSWORD: "your-smtp-password" + volumes: + - ./configs:/app/configs:ro + networks: + - worktree-main_ag_cloud + restart: on-failure + +networks: + # Use the external network created by your worktree-main compose + worktree-main_ag_cloud: + external: true diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/pyproject.toml b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/pyproject.toml new file mode 100644 index 000000000..063c0697f --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/pyproject.toml @@ -0,0 +1,14 @@ +[build-system] +requires = ["setuptools>=68", "wheel"] +build-backend = "setuptools.build_meta" + +[project] +name = "disease-monitor" +version = "0.1.0" +description = "Offline anomaly & worsening detection for disease cases in trees/plots/regions." +readme = "README.md" +requires-python = ">=3.10" + +[tool.pytest.ini_options] +pythonpath = ["src"] +addopts = "-q" diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/requirements.txt b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/requirements.txt new file mode 100644 index 000000000..46a776a5b --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/requirements.txt @@ -0,0 +1,11 @@ +pandas>=2.3.0,<2.4 +numpy>=2.2,<2.4 +pyyaml==6.0.2 +sqlalchemy==2.0.32 +pydantic==2.9.2 +scipy>=1.14.1,<1.15 +pytest==8.3.2 +python-dateutil==2.9.0.post0 +psycopg2-binary==2.9.7 +requests>=2.31 +kafka-python==2.0.2 diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/__init__.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/__init__.py new file mode 100644 index 000000000..a9a2c5b3b --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/__init__.py @@ -0,0 +1 @@ +__all__ = [] diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/alerting.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/alerting.py new file mode 100644 index 000000000..fe3802cba --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/alerting.py @@ -0,0 +1,99 @@ +from __future__ import annotations +import logging +from datetime import datetime +from typing import Dict, Any, List, Tuple +import pandas as pd + +LOGGER = logging.getLogger(__name__) + +def _merge_reasons(s: pd.Series) -> list[str]: + items = [] + for x in s: + if isinstance(x, (list, tuple, set)): + items.extend(list(x)) + else: + items.append(str(x)) + return sorted(set(items)) + +def enforce_policies(candidates: pd.DataFrame, open_alerts_df: pd.DataFrame, + cfg: Dict[str, Any]) -> List[Dict[str, Any]]: + """ + Deduplicate per (entity, rule) with cooldown; update OPEN alerts if still anomalous; + create RESOLVED entries after consecutive non-anomalous windows (handled by absence). + Rate limiting applied. + """ + if candidates.empty: + return [] + + candidates = candidates.copy() + candidates["window_start"] = pd.to_datetime(candidates["window"]) + candidates["window_end"] = pd.to_datetime(candidates["window_end"]) + candidates["first_seen"] = candidates["window_start"] + candidates["last_seen"] = candidates["window_end"] + candidates["status"] = "OPEN" + + # Dedup cooldown: skip if there is OPEN/ACK within last N windows for same (entity, rule) + cooldown = cfg["alerting"]["dedup_cooldown_windows"] + frequency = cfg["windows"]["frequency"] + + alerts_out: List[Dict[str, Any]] = [] + rate_limit = cfg["alerting"]["rate_limit_per_run"] + emitted = 0 + + # Grouping by window if requested + if cfg["alerting"]["group_by_window"]: + group_keys = ["entity_id", "rule", "window_start", "window_end"] + else: + group_keys = ["entity_id", "rule"] + + g = candidates.groupby(group_keys, as_index=False).agg({ + "score": "max", + "disease_count": "max", + "avg_severity": "max", + "affected_area": "max", + "reason": _merge_reasons +}) + + for _, row in g.iterrows(): + if emitted >= rate_limit: + LOGGER.warning("Rate limit reached (%d).", rate_limit) + break + entity, rule = row["entity_id"], row["rule"] + ws, we = row["window_start"], row["window_end"] + # Check cooldown against open alerts + if not open_alerts_df.empty: + same = open_alerts_df[(open_alerts_df["entity_id"] == entity) & + (open_alerts_df["rule"] == rule)] + # In cooldown if last_seen within last cooldown windows + recent = same[same["last_seen"] >= (ws - _windows_to_offset(frequency, cooldown))] + if not recent.empty: + LOGGER.info("Cooldown skip for %s/%s at %s.", entity, rule, ws) + continue + + meta = { + "reasons": row["reason"], + "disease_count": int(row["disease_count"]), + "avg_severity": float(row["avg_severity"]), + "affected_area": float(row["affected_area"]), + } + alerts_out.append({ + "entity_id": entity, + "rule": rule, + "window_start": ws.to_pydatetime(), + "window_end": we.to_pydatetime(), + "score": float(row["score"]), + "first_seen": ws.to_pydatetime(), + "last_seen": we.to_pydatetime(), + "status": "OPEN", + "meta": meta + }) + emitted += 1 + + return alerts_out + +def _windows_to_offset(freq: str, n: int) -> pd.Timedelta: + if n <= 0: + return pd.Timedelta(0) + if freq.upper().startswith("W"): + return pd.to_timedelta(7 * n, unit="D") + return pd.to_timedelta(n, unit="D") diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/baseline.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/baseline.py new file mode 100644 index 000000000..71e976c08 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/baseline.py @@ -0,0 +1,38 @@ +from __future__ import annotations +import pandas as pd +import numpy as np + +def compute_baseline(agg: pd.DataFrame, method: str, lookback: int, + min_history: int, seasonality: int | None) -> pd.DataFrame: + """ + Returns agg with baseline columns for disease_count, avg_severity, affected_area: + *_bl, *_std (or IQR helpers). + """ + df = agg.sort_values(["entity_id", "window"]).copy() + keys = ["entity_id"] + metrics = ["disease_count", "avg_severity", "affected_area"] + + # Optionally seasonal lag indexing + if seasonality and seasonality > 1: + df["season_index"] = df.groupby(keys)["window"].rank(method="first").astype(int) % seasonality + groupers = keys + ["season_index"] + else: + groupers = keys + + for m in metrics: + if method == "mean": + bl = df.groupby(groupers)[m].transform(lambda s: s.shift(1).rolling(lookback, min_periods=min_history).mean()) + sd = df.groupby(groupers)[m].transform(lambda s: s.shift(1).rolling(lookback, min_periods=min_history).std(ddof=0)) + else: + bl = df.groupby(groupers)[m].transform(lambda s: s.shift(1).rolling(lookback, min_periods=min_history).median()) + sd = df.groupby(groupers)[m].transform(lambda s: s.shift(1).rolling(lookback, min_periods=min_history).std(ddof=0)) + df[f"{m}_bl"] = bl.fillna(0.0) + df[f"{m}_std"] = sd.fillna(0.0) + + # IQR helpers + q1 = df.groupby(groupers)[m].transform(lambda s: s.shift(1).rolling(lookback, min_periods=min_history).quantile(0.25)) + q3 = df.groupby(groupers)[m].transform(lambda s: s.shift(1).rolling(lookback, min_periods=min_history).quantile(0.75)) + df[f"{m}_q1"] = q1.fillna(0.0) + df[f"{m}_q3"] = q3.fillna(0.0) + + return df diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/cli.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/cli.py new file mode 100644 index 000000000..74817d4cb --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/cli.py @@ -0,0 +1,121 @@ +import argparse +import json +import logging +from typing import Dict, Any, List + +import yaml +import pandas as pd + +from .logging_utils import setup_logging +from .config import AppConfig +from . import io as io_mod +from .baseline import compute_baseline +from .rules import apply_rules +from .alerting import enforce_policies +from .notifiers.base import Notifier +from .notifiers.slack import SlackNotifier +from .notifiers.webhook import WebhookNotifier +from .notifiers.emailer import EmailNotifier +from .notifiers.kafka_notifier import KafkaNotifier +from .io import load_inputs_from_postgres , upsert_alerts_pg , fetch_open_alerts_pg + + +LOGGER = logging.getLogger("disease_monitor") + + +def parse_args(): + parser = argparse.ArgumentParser(description="Offline disease anomaly detector") + parser.add_argument("--config", required=True, help="Path to config file (YAML)") + parser.add_argument("--log-level", default="INFO", help="Logging level") + return parser.parse_args() + + +def load_config(path: str) -> Dict[str, Any]: + with open(path, "r", encoding="utf-8") as f: + cfg = yaml.safe_load(f) + AppConfig(**cfg) # validation + return cfg + +def build_notifiers(cfg: Dict[str, Any]) -> List[Notifier]: + ns: List[Notifier] = [] + d = cfg.get("delivery", {}) + + kafka_cfg = d.get("kafka", {}) + if kafka_cfg.get("enabled"): + brokers = kafka_cfg["brokers"] + topic = kafka_cfg.get("topic", "alerts") + ns.append(KafkaNotifier(brokers, topic)) + LOGGER.info("Using KafkaNotifier to send alerts.") + return ns + + slack = d.get("slack", {}) + if slack.get("enabled") and slack.get("webhook_url"): + ns.append(SlackNotifier(slack["webhook_url"])) + + webhook = d.get("webhook", {}) + if webhook.get("enabled") and webhook.get("url"): + ns.append(WebhookNotifier(webhook["url"], webhook.get("headers") or {})) + + email = d.get("email", {}) + if email.get("enabled") and email.get("to_addrs"): + ns.append(EmailNotifier(email["smtp_host"], email["smtp_port"], email["username"], + email["password_env"], email["from_addr"], email["to_addrs"])) + return ns + +def main() -> None: + args = parse_args() + setup_logging(args.log_level) + cfg = load_config(args.config) + + tz = cfg["windows"]["timezone"] + freq = cfg["windows"]["frequency"] + + # Load inputs + det, reg = load_inputs_from_postgres(cfg["io"]["postgres_url"], tz, cfg) + + # Optional filters + run_cfg = cfg["run"] + if run_cfg.get("disease_filter"): + det = det[det["disease_type"].isin(run_cfg["disease_filter"])] + if run_cfg.get("limit_entities"): + keep = det["entity_id"].drop_duplicates().head(run_cfg["limit_entities"]).tolist() + det = det[det["entity_id"].isin(keep)] + + # Aggregation + baseline + agg = io_mod.aggregate(det, freq=freq) + agg_bl = compute_baseline( + agg, + method=cfg["baseline"]["method"], + lookback=cfg["baseline"]["lookback_periods"], + min_history=cfg["baseline"]["min_history"], + seasonality=cfg["baseline"]["seasonality"], + ) + + # Rules + candidates = apply_rules(agg_bl, cfg) + LOGGER.info("Candidate alerts: %d", 0 if candidates is None else len(candidates)) + + # Policies need knowledge of currently OPEN alerts from the chosen backend + open_alerts = fetch_open_alerts_pg(cfg["io"]["postgres_url"]) + alerts = enforce_policies(candidates, open_alerts, cfg) + LOGGER.info("Alerts after policies: %d", len(alerts)) + + # Delivery + notifiers = build_notifiers(cfg) + dry_run = cfg["run"]["dry_run"] + + if not dry_run and alerts: + io_mod.upsert_alerts_pg(cfg["io"]["postgres_url"], alerts) + for a in alerts: + for n in notifiers: + try: + n.send(a) + except Exception as ex: + LOGGER.error("Notifier failed: %s", ex) + else: + LOGGER.info("Dry-run or no alerts. Skipping DB write & delivery.") + LOGGER.info("Preview alerts: %s", json.dumps(alerts, default=str, ensure_ascii=False)) + + +if __name__ == "__main__": + main() diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/config.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/config.py new file mode 100644 index 000000000..a2e0aa83f --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/config.py @@ -0,0 +1,114 @@ +from pydantic import BaseModel, Field, model_validator +from typing import Optional, List, Dict, Any + +# ------------------------------ +# IO: Postgres-only +# ------------------------------ +class IOConfig(BaseModel): + postgres_url: str # required: Postgres-only + + @model_validator(mode="after") + def _ensure_pg_only(self): + url = self.postgres_url + if not isinstance(url, str) or not url.lower().startswith( + ("postgresql://", "postgresql+psycopg2://") + ): + raise ValueError("io.postgres_url is required and must be a PostgreSQL URL.") + return self + + +# ------------------------------ +# Windows/Baseline/Rules/Alerting +# ------------------------------ +class WindowsConfig(BaseModel): + frequency: str = "D" + timezone: str = "UTC" + +class BaselineConfig(BaseModel): + method: str = "median" + lookback_periods: int = 28 + min_history: int = 7 + seasonality: Optional[int] = None + +class CountAnomalyRule(BaseModel): + enabled: bool = True + method: str = "zscore" + z_threshold: float = 3.0 + iqr_k: float = 1.5 + min_count: int = 3 + +class WorseningRule(BaseModel): + enabled: bool = True + method: str = "slope" + slope_lookback: int = 7 + slope_min: float = 0.02 + min_periods: int = 5 + ewma_span: int = 7 + ewma_threshold: float = 0.6 + +class RulesConfig(BaseModel): + count_anomaly: CountAnomalyRule = Field(default_factory=CountAnomalyRule) + worsening: WorseningRule = Field(default_factory=WorseningRule) + +class AlertingConfig(BaseModel): + dedup_cooldown_windows: int = 3 + resolve_after_no_anomaly: int = 3 + rate_limit_per_run: int = 100 + group_by_window: bool = True + + +# ------------------------------ +# Delivery: add Alertmanager section +# ------------------------------ +class SlackConfig(BaseModel): + enabled: bool = False + webhook_url: Optional[str] = None + +class WebhookConfig(BaseModel): + enabled: bool = False + url: Optional[str] = None + headers: Dict[str, Any] = Field(default_factory=dict) + +class EmailConfig(BaseModel): + enabled: bool = False + smtp_host: str = "" + smtp_port: int = 587 + username: str = "" + password_env: str = "SMTP_PASSWORD" + from_addr: str = "" + to_addrs: List[str] = Field(default_factory=list) + +class AlertmanagerConfig(BaseModel): + enabled: bool = False + url: Optional[str] = None + default_severity: str = "warning" + extra_labels: Dict[str, str] = Field(default_factory=dict) + auth: Dict[str, Any] = Field(default_factory=lambda: {"type": "none"}) # {"type":"none"} or {"type":"basic",...} + +class DeliveryConfig(BaseModel): + slack: SlackConfig = Field(default_factory=SlackConfig) + webhook: WebhookConfig = Field(default_factory=WebhookConfig) + email: EmailConfig = Field(default_factory=EmailConfig) + alertmanager: AlertmanagerConfig = Field(default_factory=AlertmanagerConfig) + + +# ------------------------------ +# Run +# ------------------------------ +class RunConfig(BaseModel): + dry_run: bool = False + limit_entities: Optional[int] = None + disease_filter: Optional[List[str]] = None + + +# ------------------------------ +# AppConfig +# ------------------------------ +class AppConfig(BaseModel): + io: IOConfig + windows: WindowsConfig = Field(default_factory=WindowsConfig) + baseline: BaselineConfig = Field(default_factory=BaselineConfig) + rules: RulesConfig = Field(default_factory=RulesConfig) + alerting: AlertingConfig = Field(default_factory=AlertingConfig) + delivery: DeliveryConfig = Field(default_factory=DeliveryConfig) + run: RunConfig = Field(default_factory=RunConfig) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/io.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/io.py new file mode 100644 index 000000000..98b100f77 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/io.py @@ -0,0 +1,208 @@ +from __future__ import annotations + +import json +import logging +from typing import Tuple, Iterable, Dict, Any, List + +import pandas as pd +from sqlalchemy import create_engine, text + +LOGGER = logging.getLogger(__name__) + +# --------------------------------------------------------------------- +# Postgres sources: anomalies / anomaly_types / regions +# --------------------------------------------------------------------- + +_BASE_SQLS: Dict[str, str] = { + "device": """ + SELECT a.ts AS "timestamp", + a.device_id AS entity_id, + at.code AS disease_type, + COALESCE(a.severity::double precision, 0.0) AS severity, + 0.0 AS affected_area + FROM public.anomalies a + JOIN public.anomaly_types at ON at.anomaly_type_id = a.anomaly_type_id + WHERE a.ts IS NOT NULL + {AND_CODE_FILTER} + {AND_TIME_RANGE} + """, + "mission": """ + SELECT a.ts AS "timestamp", + a.mission_id::text AS entity_id, + at.code AS disease_type, + COALESCE(a.severity::double precision, 0.0) AS severity, + 0.0 AS affected_area + FROM public.anomalies a + JOIN public.anomaly_types at ON at.anomaly_type_id = a.anomaly_type_id + WHERE a.ts IS NOT NULL + {AND_CODE_FILTER} + {AND_TIME_RANGE} + """, + "region": """ + SELECT a.ts AS "timestamp", + r.id::text AS entity_id, + at.code AS disease_type, + COALESCE(a.severity::double precision, 0.0) AS severity, + {AREA_EXPR} AS affected_area + FROM public.anomalies a + JOIN public.anomaly_types at ON at.anomaly_type_id = a.anomaly_type_id + JOIN public.regions r ON ST_Contains(r.geom, a.geom) + WHERE a.ts IS NOT NULL AND a.geom IS NOT NULL + {AND_CODE_FILTER} + {AND_TIME_RANGE} + """, + +} + + +def _build_sql( + entity_dim: str, + area_strategy: str, + codes: List[str] | None, + start: str | None, + end: str | None, +) -> tuple[str, dict]: + """ + Build parametrized SQL for reading anomalies with chosen entity dimension and area strategy. + """ + sql = _BASE_SQLS[entity_dim] + area_expr = "0.0" + if entity_dim == "region" and area_strategy == "region_area": + area_expr = "ST_Area(r.geom::geography)::double precision" + + and_code = "" + params: Dict[str, Any] = {} + if codes: + and_code = "AND at.code = ANY(:codes)" + params["codes"] = codes + + and_time = "" + if start: + and_time += " AND a.ts >= :start_time" + params["start_time"] = start + if end: + and_time += " AND a.ts < :end_time" + params["end_time"] = end + + sql = ( + sql.replace("{AREA_EXPR}", area_expr) + .replace("{AND_CODE_FILTER}", and_code) + .replace("{AND_TIME_RANGE}", and_time) + ) + return sql, params + + +# --------------------------------------------------------------------- +# Postgres input (canonical) +# --------------------------------------------------------------------- + +def load_inputs_from_postgres(pg_url: str, tz: str, cfg: dict) -> Tuple[pd.DataFrame, pd.DataFrame]: + """ + Load inputs from Postgres (public.anomalies/anomaly_types/regions). + Controlled by cfg['source_mapping'] (entity_dim, area_strategy, filters, codes). + Returns: + det: columns [timestamp, entity_id, disease_type, severity, affected_area] + reg: columns [entity_id, entity_type] + """ + edim = cfg["source_mapping"]["entity_dim"] + area = cfg["source_mapping"].get("area_strategy", "none") + codes = cfg["source_mapping"].get("anomaly_codes") + filters = cfg["source_mapping"].get("filters") or {} + start = filters.get("start_time") + end = filters.get("end_time") + + sql, params = _build_sql(edim, area, codes, start, end) + + eng = create_engine(pg_url) + with eng.begin() as conn: + det = pd.read_sql(text(sql), conn, params=params) + reg = det[["entity_id"]].drop_duplicates().assign(entity_type=edim) + + det["timestamp"] = pd.to_datetime(det["timestamp"], utc=True).dt.tz_convert(tz) + + required = {"timestamp", "entity_id", "disease_type", "severity", "affected_area"} + if not required.issubset(det.columns): + missing = required - set(det.columns) + raise ValueError(f"det: missing {missing}") + if not {"entity_id", "entity_type"}.issubset(reg.columns): + raise ValueError("reg: missing cols") + + return det, reg + + +# --------------------------------------------------------------------- +# Aggregation +# --------------------------------------------------------------------- + +def aggregate(det: pd.DataFrame, freq: str) -> pd.DataFrame: + """ + Aggregate by entity_id + window and compute disease_count, avg_severity, affected_area. + """ + df = det.copy() + + # Normalize tz: drop tz-info to use pandas period-based bucketing safely + if pd.api.types.is_datetime64tz_dtype(df["timestamp"]): + df["timestamp"] = df["timestamp"].dt.tz_convert("UTC").dt.tz_localize(None) + + df["window"] = df["timestamp"].dt.to_period(freq).dt.start_time + grp = df.groupby(["entity_id", "window"], as_index=False).agg( + disease_count=("disease_type", "count"), + avg_severity=("severity", "mean"), + affected_area=("affected_area", "sum"), + ) + grp["window_end"] = grp["window"] + pd.tseries.frequencies.to_offset(freq) + return grp + + +# --------------------------------------------------------------------- +# Alerts: Postgres backend +# --------------------------------------------------------------------- + + +def fetch_open_alerts_pg(pg_url: str) -> pd.DataFrame: + eng = create_engine(pg_url) + sql = """ + SELECT id, entity_id, rule, window_start, window_end, score, + first_seen, last_seen, status, meta_json + FROM alerts_leaves + WHERE status IN ('OPEN','ACK') + """ + with eng.begin() as conn: + df = pd.read_sql(text(sql), conn) + if not df.empty: + for c in ("first_seen", "last_seen", "window_start", "window_end"): + # make tz-aware UTC then drop tz -> naive UTC + s = pd.to_datetime(df[c], utc=True) + df[c] = s.dt.tz_convert("UTC").dt.tz_localize(None) + + return df + + +def upsert_alerts_pg(pg_url: str, alerts: Iterable[Dict[str, Any]]) -> None: + rows = list(alerts) + if not rows: + return + eng = create_engine(pg_url) + sql = """ + INSERT INTO alerts_leaves + (entity_id, rule, window_start, window_end, score, + first_seen, last_seen, status, meta_json) + VALUES + (:entity_id, :rule, :window_start, :window_end, :score, + :first_seen, :last_seen, :status, CAST(:meta_json AS jsonb)) + """ + payload = [{ + "entity_id": a["entity_id"], + "rule": a["rule"], + "window_start": a["window_start"], + "window_end": a["window_end"], + "score": float(a["score"]), + "first_seen": a["first_seen"], + "last_seen": a["last_seen"], + "status": a["status"], + "meta_json": json.dumps(a["meta"], ensure_ascii=False), + } for a in rows] + + with eng.begin() as conn: + conn.execute(text(sql), payload) + LOGGER.info("Inserted %d alerts into Postgres.", len(rows)) \ No newline at end of file diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/logging_utils.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/logging_utils.py new file mode 100644 index 000000000..f9618ff02 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/logging_utils.py @@ -0,0 +1,10 @@ +import logging +import sys + +def setup_logging(level: str = "INFO") -> None: + handler = logging.StreamHandler(sys.stdout) + fmt = "%(asctime)s %(levelname)s %(name)s - %(message)s" + handler.setFormatter(logging.Formatter(fmt)) + root = logging.getLogger() + root.setLevel(level.upper()) + root.handlers = [handler] diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/models.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/models.py new file mode 100644 index 000000000..4796fecd8 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/models.py @@ -0,0 +1,15 @@ +from dataclasses import dataclass +from typing import Optional, Dict +from datetime import datetime + +@dataclass +class Alert: + entity_id: str + rule: str + window_start: datetime + window_end: datetime + score: float + first_seen: datetime + last_seen: datetime + status: str # OPEN | ACK | RESOLVED + meta: Dict diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/base.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/base.py new file mode 100644 index 000000000..1f8bc409a --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/base.py @@ -0,0 +1,13 @@ +from __future__ import annotations +from typing import Dict, Any, List + +class Notifier: + def send(self, alert: Dict[str, Any]) -> None: + raise NotImplementedError + +def render_text(alert: Dict[str, Any]) -> str: + return ( + f"[{alert['status']}] {alert['rule']} for {alert['entity_id']} " + f"{alert['window_start']}..{alert['window_end']} " + f"score={alert['score']:.2f} reasons={alert['meta'].get('reasons')}" + ) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/emailer.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/emailer.py new file mode 100644 index 000000000..695e0ddfe --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/emailer.py @@ -0,0 +1,28 @@ +from __future__ import annotations +import os +import smtplib +from email.mime.text import MIMEText +from typing import Dict, Any, List +from .base import Notifier, render_text + +class EmailNotifier(Notifier): + def __init__(self, host: str, port: int, username: str, password_env: str, + from_addr: str, to_addrs: List[str]) -> None: + self.host = host + self.port = port + self.username = username + self.password_env = password_env + self.from_addr = from_addr + self.to_addrs = to_addrs + + def send(self, alert: Dict[str, Any]) -> None: + password = os.getenv(self.password_env, "") + msg = MIMEText(render_text(alert)) + msg["Subject"] = f"Alert: {alert['rule']} {alert['entity_id']}" + msg["From"] = self.from_addr + msg["To"] = ", ".join(self.to_addrs) + with smtplib.SMTP(self.host, self.port, timeout=10) as s: + s.starttls() + if self.username and password: + s.login(self.username, password) + s.sendmail(self.from_addr, self.to_addrs, msg.as_string()) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/kafka_notifier.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/kafka_notifier.py new file mode 100644 index 000000000..7552bfa1f --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/kafka_notifier.py @@ -0,0 +1,49 @@ +from __future__ import annotations +import json, uuid, datetime, logging +from kafka import KafkaProducer +from typing import Dict, Any +from .base import Notifier + +LOGGER = logging.getLogger(__name__) + +def _json_default(obj): + if isinstance(obj, (datetime.datetime, datetime.date)): + return obj.isoformat() + raise TypeError(f"Type {type(obj)} not serializable") + + +class KafkaNotifier(Notifier): + def __init__(self, brokers: str, topic: str): + self.producer = KafkaProducer( + bootstrap_servers=brokers.split(","), + value_serializer=lambda v: json.dumps(v, default=_json_default).encode("utf-8"), + ) + self.topic = topic + + def send(self, alert: Dict[str, Any]) -> None: + msg = { + "alert_id": alert.get("alert_id") or str(uuid.uuid4()), + "alert_type": alert.get("rule", "disease_detected"), + "device_id": alert.get("entity_id"), + "started_at": alert.get("window_start"), + "ended_at": alert.get("window_end"), + "confidence": alert.get("score"), + "severity": int(alert.get("meta", {}).get("severity", 1)), + "area": alert.get("meta", {}).get("area"), + "lat": alert.get("meta", {}).get("lat"), + "lon": alert.get("meta", {}).get("lon"), + "image_url": alert.get("meta", {}).get("image_url"), + "vod": alert.get("meta", {}).get("vod"), + "hls": alert.get("meta", {}).get("hls"), + "meta": alert.get("meta", {}), + } + + try: + self.producer.send(self.topic, msg) + self.producer.flush() + LOGGER.info( + "KafkaNotifier: sent alert %s to topic '%s' with rule '%s' (confidence=%.2f)", + msg["alert_id"], self.topic, msg["alert_type"], msg["confidence"] or 0, + ) + except Exception as e: + LOGGER.error("KafkaNotifier failed to send alert: %s", e) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/slack.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/slack.py new file mode 100644 index 000000000..68925060a --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/slack.py @@ -0,0 +1,15 @@ +from __future__ import annotations +import os +import json +import requests +from typing import Dict, Any +from .base import Notifier, render_text + +class SlackNotifier(Notifier): + def __init__(self, webhook_url: str) -> None: + self.webhook_url = webhook_url + + def send(self, alert: Dict[str, Any]) -> None: + text = render_text(alert) + payload = {"text": text} + requests.post(self.webhook_url, data=json.dumps(payload), timeout=10) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/webhook.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/webhook.py new file mode 100644 index 000000000..1e84232c7 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/notifiers/webhook.py @@ -0,0 +1,13 @@ +from __future__ import annotations +import json +import requests +from typing import Dict, Any +from .base import Notifier + +class WebhookNotifier(Notifier): + def __init__(self, url: str, headers: Dict[str, str] | None = None) -> None: + self.url = url + self.headers = headers or {} + + def send(self, alert: Dict[str, Any]) -> None: + requests.post(self.url, json=alert, headers=self.headers, timeout=10) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/rules.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/rules.py new file mode 100644 index 000000000..eeba8ec4c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/src/disease_monitor/rules.py @@ -0,0 +1,108 @@ +from __future__ import annotations +import logging +from typing import List, Dict, Any, Tuple +import pandas as pd +import numpy as np +from scipy import stats + +LOGGER = logging.getLogger(__name__) + +def zscore_anomalies(df: pd.DataFrame, threshold: float, min_count: int) -> pd.DataFrame: + s = df["disease_count"] + mu = df["disease_count_bl"] + # Use small epsilon for zero/NaN std to avoid z=0 + sd = df["disease_count_std"] + eps = 1e-6 + sd = sd.where(sd > 0, other=eps).fillna(eps) + + z = (s - mu) / sd + cond = (z >= threshold) & (s >= min_count) + + out = df.loc[cond].copy() + out["score"] = z.loc[cond] + out["rule"] = "COUNT_SPIKE" + out["reason"] = "zscore" + return out + +def iqr_anomalies(df: pd.DataFrame, k: float, min_count: int) -> pd.DataFrame: + q1 = df["disease_count_q1"] + q3 = df["disease_count_q3"] + iqr = (q3 - q1).replace(0, np.nan) + upper = q3 + k * iqr + cond = (df["disease_count"] > upper.fillna(float("inf"))) & (df["disease_count"] >= min_count) + out = df.loc[cond].copy() + out["score"] = (df["disease_count"] - upper).loc[cond].fillna(0.0) + out["rule"] = "COUNT_SPIKE" + out["reason"] = "iqr" + return out + +def slope_worsening(df: pd.DataFrame, metric: str, lookback: int, + slope_min: float, min_periods: int) -> pd.DataFrame: + # Per entity rolling slope (OLS) + rows = [] + for entity, g in df.groupby("entity_id"): + g = g.sort_values("window") + y = g[metric].rolling(lookback, min_periods=min_periods).apply(_rolling_slope, raw=False) + cond = y >= slope_min + sel = g.loc[cond].copy() + if sel.empty: + continue + sel["score"] = y.loc[cond] + sel["rule"] = "WORSENING_TREND" + sel["reason"] = f"slope_{metric}" + rows.append(sel) + return pd.concat(rows, ignore_index=True) if rows else pd.DataFrame(columns=df.columns.tolist() + ["score","rule","reason"]) + +def _rolling_slope(s: pd.Series) -> float: + x = np.arange(len(s)) + res = stats.linregress(x, s.values) + return float(res.slope) + +def ewma_worsening(df: pd.DataFrame, metric: str, span: int, threshold: float, min_periods: int) -> pd.DataFrame: + rows = [] + for entity, g in df.groupby("entity_id"): + g = g.sort_values("window").copy() + ew = g[metric].ewm(span=span, adjust=False).mean() + cond = (ew >= threshold) & (g[metric].rolling(span, min_periods=min_periods).count() >= min_periods) + sel = g.loc[cond].copy() + if sel.empty: + continue + sel["score"] = ew.loc[cond] + sel["rule"] = "WORSENING_TREND" + sel["reason"] = f"ewma_{metric}" + rows.append(sel) + return pd.concat(rows, ignore_index=True) if rows else pd.DataFrame(columns=df.columns.tolist() + ["score","rule","reason"]) + +def apply_rules(df: pd.DataFrame, cfg: Dict[str, Any]) -> pd.DataFrame: + results = [] + + # Count anomaly + rc = cfg["rules"]["count_anomaly"] + if rc["enabled"]: + if rc["method"] == "zscore": + results.append(zscore_anomalies(df, rc["z_threshold"], rc["min_count"])) + elif rc["method"] == "iqr": + results.append(iqr_anomalies(df, rc["iqr_k"], rc["min_count"])) + else: + # Placeholder: CUSUM can be added similarly + results.append(zscore_anomalies(df, rc["z_threshold"], rc["min_count"])) + + # Worsening trend on severity and area + rw = cfg["rules"]["worsening"] + if rw["enabled"]: + if rw["method"] == "slope": + for m in ["avg_severity", "affected_area"]: + results.append(slope_worsening(df, m, rw["slope_lookback"], rw["slope_min"], rw["min_periods"])) + else: + for m in ["avg_severity", "affected_area"]: + results.append(ewma_worsening(df, m, rw["ewma_span"], rw["ewma_threshold"], rw["min_periods"])) + + if not results: + return pd.DataFrame() + out = pd.concat([r for r in results if r is not None and not r.empty], ignore_index=True) \ + if any((r is not None and not r.empty) for r in results) else pd.DataFrame() + # Prepare common fields + if not out.empty: + out = out[["entity_id", "window", "window_end", "rule", "score", "reason", + "disease_count", "avg_severity", "affected_area"]].copy() + return out diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/conftest.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/conftest.py new file mode 100644 index 000000000..043dc1712 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/conftest.py @@ -0,0 +1,17 @@ +import pandas as pd +import numpy as np +from datetime import datetime, timedelta, timezone + +TZ = "UTC" + +def make_series(start: str, days: int, entity: str, base_count=1, bump_at=None, bump=5): + rows = [] + start_dt = pd.to_datetime(start).tz_localize("UTC") + for i in range(days): + ts = start_dt + pd.Timedelta(days=i) + count = base_count + if bump_at is not None and i in bump_at: + count = bump + rows.append({"timestamp": ts, "entity_id": entity, "disease_type": "x", + "severity": 0.1 * count, "affected_area": 2.0 * count}) + return pd.DataFrame(rows) diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_aggregation.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_aggregation.py new file mode 100644 index 000000000..bb0a42558 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_aggregation.py @@ -0,0 +1,17 @@ +import pandas as pd +from disease_monitor.io import aggregate + +def test_aggregate_basic(): + det = pd.DataFrame({ + "timestamp": pd.to_datetime(["2025-08-01", "2025-08-01", "2025-08-02"]).tz_localize("UTC"), + "entity_id": ["A","A","A"], + "disease_type": ["x","x","x"], + "severity": [0.2, 0.4, 0.3], + "affected_area": [1,2,3], + }) + out = aggregate(det, "D") + assert len(out) == 2 + d1 = out[out["window"] == pd.to_datetime("2025-08-01")] + assert int(d1["disease_count"].iloc[0]) == 2 + assert abs(float(d1["avg_severity"].iloc[0]) - 0.3) < 1e-9 + assert int(d1["affected_area"].iloc[0]) == 3 diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_alerting.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_alerting.py new file mode 100644 index 000000000..48126beaf --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_alerting.py @@ -0,0 +1,34 @@ +import pandas as pd +from disease_monitor.alerting import enforce_policies + +def test_dedup_cooldown(): + candidates = pd.DataFrame({ + "entity_id": ["A","A"], + "window": pd.to_datetime(["2025-08-10","2025-08-11"]), + "window_end": pd.to_datetime(["2025-08-11","2025-08-12"]), + "rule": ["COUNT_SPIKE","COUNT_SPIKE"], + "score": [3.1, 3.2], + "reason": [["zscore"],["zscore"]], + "disease_count": [10, 9], + "avg_severity": [0.5, 0.4], + "affected_area": [10.0, 9.0], + }) + open_alerts = pd.DataFrame({ + "entity_id": ["A"], + "rule": ["COUNT_SPIKE"], + "last_seen": pd.to_datetime(["2025-08-10"]), + "window_start": pd.to_datetime(["2025-08-10"]), + "window_end": pd.to_datetime(["2025-08-11"]), + "first_seen": pd.to_datetime(["2025-08-10"]), + "status": ["OPEN"], + "id": [1], + "score": [3.1] + }) + cfg = { + "alerting": {"dedup_cooldown_windows": 3, "resolve_after_no_anomaly": 3, + "rate_limit_per_run": 10, "group_by_window": True}, + "windows": {"frequency": "D"} + } + res = enforce_policies(candidates, open_alerts, cfg) + # Second day should be skipped due to cooldown + assert len(res) == 0 or len(res) == 1 diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_anomaly_rules.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_anomaly_rules.py new file mode 100644 index 000000000..23f595a7a --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_anomaly_rules.py @@ -0,0 +1,22 @@ +import pandas as pd +from disease_monitor.baseline import compute_baseline +from disease_monitor.rules import apply_rules + +def test_zscore_spike_detected(): + # mostly low counts, then spike + det = [] + for d in range(10): + det.append({"window": pd.to_datetime(f"2025-08-{d+1:02d}"), + "entity_id": "E1", + "disease_count": 1 if d < 8 else (10 if d==8 else 1), + "avg_severity": 0.2, "affected_area": 2.0}) + df = pd.DataFrame(det) + df["window_end"] = df["window"] + pd.Timedelta(days=1) + bl = compute_baseline(df.rename(columns={"window":"window"}), "median", 7, 3, None) + cfg = { + "rules": {"count_anomaly": {"enabled": True, "method": "zscore", "z_threshold": 2.5, "min_count": 3}, + "worsening": {"enabled": False}}, + } + out = apply_rules(bl, cfg) + assert not out.empty + assert "COUNT_SPIKE" in out["rule"].unique() diff --git a/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_worsening_rules.py b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_worsening_rules.py new file mode 100644 index 000000000..e17b34e57 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/disease-monitor/disease-monitor/tests/test_worsening_rules.py @@ -0,0 +1,24 @@ +import pandas as pd +from disease_monitor.baseline import compute_baseline +from disease_monitor.rules import apply_rules + +def test_worsening_slope_on_severity(): + rows = [] + for i in range(10): + rows.append({ + "window": pd.to_datetime(f"2025-08-{i+1:02d}"), + "entity_id": "E1", + "disease_count": 1, + "avg_severity": 0.1 + 0.03*i, + "affected_area": 2 + i + }) + df = pd.DataFrame(rows) + df["window_end"] = df["window"] + pd.Timedelta(days=1) + bl = compute_baseline(df, "median", 7, 3, None) + cfg = {"rules": + {"count_anomaly": {"enabled": False}, + "worsening": {"enabled": True, "method": "slope", + "slope_lookback": 7, "slope_min": 0.02, "min_periods": 5}}} + out = apply_rules(bl, cfg) + assert not out.empty + assert "WORSENING_TREND" in out["rule"].unique() diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/demo_images/10/Bell_pepper leaf spot/05.jpg b/airflow_bundle/leaf-pipeline/projects/leaf-counting/demo_images/10/Bell_pepper leaf spot/05.jpg new file mode 100644 index 000000000..09be3be5f Binary files /dev/null and b/airflow_bundle/leaf-pipeline/projects/leaf-counting/demo_images/10/Bell_pepper leaf spot/05.jpg differ diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/demo_images/10/Bell_pepper leaf spot/bacterialspot3_600px.jpg b/airflow_bundle/leaf-pipeline/projects/leaf-counting/demo_images/10/Bell_pepper leaf spot/bacterialspot3_600px.jpg new file mode 100644 index 000000000..c56ceecd3 Binary files /dev/null and b/airflow_bundle/leaf-pipeline/projects/leaf-counting/demo_images/10/Bell_pepper leaf spot/bacterialspot3_600px.jpg 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leaf/tomato_plants_1_original.JPG_1407178095.jpg differ diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/requirements.orig.txt b/airflow_bundle/leaf-pipeline/projects/leaf-counting/requirements.orig.txt new file mode 100644 index 000000000..81958653a --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/leaf-counting/requirements.orig.txt @@ -0,0 +1,5 @@ + +ultralytics>=8.1.0 +opencv-python-headless>=4.9.0.80 +numpy>=1.23.0 +minio>=7.1.15 diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/requirements.txt b/airflow_bundle/leaf-pipeline/projects/leaf-counting/requirements.txt new file mode 100644 index 000000000..0c27d4902 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/leaf-counting/requirements.txt @@ -0,0 +1,9 @@ +--extra-index-url https://download.pytorch.org/whl/cpu +torch==2.6.0+cpu +torchvision==0.21.0+cpu +torchaudio==2.6.0+cpu + +ultralytics>=8.1.0 +opencv-python-headless>=4.9.0.80 +numpy>=1.23.0 +minio>=7.1.15 diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/__init__.py b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/__init__.py new file mode 100644 index 000000000..ee49d4339 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/__init__.py @@ -0,0 +1,5 @@ +# decompyle3 version 3.9.3 +# Python bytecode version base 3.12.0 (3531) +# Decompiled from: Python 3.12.3 (main, Aug 14 2025, 17:47:21) [GCC 13.3.0] +# Embedded file name: /home/user/ml-workspace/projects/leaf-counting/src/__init__.py +# Compiled at: 2025-10-20 13:47:51 diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/common.py b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/common.py new file mode 100644 index 000000000..ea30f64ea --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/common.py @@ -0,0 +1,35 @@ +from __future__ import annotations +from pathlib import Path +import cv2 +import numpy as np + +IMG_EXTS = {".jpg", ".jpeg", ".png", ".bmp", ".tif", ".tiff", ".webp"} + +def is_image(path: Path) -> bool: + return path.suffix.lower() in IMG_EXTS + +def iter_images(inp: Path): + p = Path(inp) + if p.is_file() and is_image(p): + yield p + elif p.is_dir(): + for q in sorted(p.rglob("*")): + if q.is_file() and is_image(q): + yield q + +def ensure_dir(p: Path) -> Path: + Path(p).mkdir(parents=True, exist_ok=True) + return Path(p) + +def draw_boxes(img_bgr: np.ndarray, boxes, color=(0,255,0), thickness=2): + h, w = img_bgr.shape[:2] + out = img_bgr.copy() + for (x1,y1,x2,y2,conf,cls_id) in boxes: + x1 = max(0, min(w-1, int(x1))) + y1 = max(0, min(h-1, int(y1))) + x2 = max(0, min(w-1, int(x2))) + y2 = max(0, min(h-1, int(y2))) + cv2.rectangle(out, (x1,y1), (x2,y2), color, thickness) + label = f"{int(cls_id)}:{conf:.2f}" + cv2.putText(out, label, (x1, max(0, y1-5)), cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 1, cv2.LINE_AA) + return out \ No newline at end of file diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/crop_only.py b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/crop_only.py new file mode 100644 index 000000000..517481860 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/crop_only.py @@ -0,0 +1,143 @@ +from __future__ import annotations +import json, argparse +from pathlib import Path +from typing import Optional +import cv2 +from common import ensure_dir +from datetime import datetime + +try: + from minio_io import get_client, ensure_bucket, put_png +except Exception: + get_client = ensure_bucket = put_png = None + + +def _load_jsons(inp: Path): + jdir = inp / "json" + if not jdir.exists(): + raise SystemExit(f"[ERR] Expected JSON dir not found: {jdir} (run detect_only.py first)") + + for jp in sorted(jdir.rglob("*.json")): + with jp.open("r", encoding="utf-8") as f: + j = json.load(f) + yield jp, j + +def _safe_crop(img, x1, y1, x2, y2): + h, w = img.shape[:2] + x1 = max(0, min(w-1, int(x1))); y1 = max(0, min(h-1, int(y1))) + x2 = max(0, min(w-1, int(x2))); y2 = max(0, min(h-1, int(y2))) + if x2 <= x1: x2 = min(w-1, x1+1) + if y2 <= y1: y2 = min(h-1, y1+1) + return img[y1:y2, x1:x2] + + +def run_crop(inp: Path, out_dir: Path, size: int=224, margin: float=0.1, min_wh: int=8, + orig_dir: Optional[Path]=None, flat: bool=False, + minio_endpoint: Optional[str]=None, minio_access: Optional[str]=None, + minio_secret: Optional[str]=None, minio_bucket: Optional[str]=None, + minio_prefix: str="CROP", minio_secure: bool=False, + run_id: Optional[str]=None): + run_id = run_id or datetime.now().strftime("%Y/%m/%d/%H%M") + out_dir = ensure_dir(out_dir) + + cli = None + if minio_endpoint and minio_access and minio_secret and minio_bucket: + if get_client is None: + raise SystemExit("[ERR] minio minio_io.") + cli = get_client(minio_endpoint, minio_access, minio_secret, secure=minio_secure) + ensure_bucket(cli, minio_bucket) + + count = 0 + for jp, j in _load_jsons(inp): + + if "source_path" in j: + img_path = Path(j["source_path"]) + rel_path = j.get("rel_path", j["image"]) + elif "rel_path" in j: + if orig_dir is None: + raise SystemExit("[ERR] JSON rel_path") + img_path = Path(orig_dir) / j["rel_path"] + rel_path = j["rel_path"] + else: + if orig_dir is None: + raise SystemExit("[ERR] JSON source_path/rel_path; --orig image") + img_path = Path(orig_dir) / j["image"] + rel_path = j["image"] + + if not img_path.exists(): + print(f"[WARN] Original image not found: {img_path}, skipping") + continue + + img = cv2.imread(str(img_path)) + if img is None: + print(f"[WARN] Can't read image: {img_path}") + continue + + rel_parent = str(Path(rel_path).parent) + rel_stem = Path(rel_path).stem + + + if flat: + dest_dir = ensure_dir(out_dir) + minio_subprefix = minio_prefix + else: + dest_dir = ensure_dir(out_dir / rel_parent / rel_stem) + minio_subprefix = f"{minio_prefix}/{rel_parent}/{rel_stem}" if rel_parent != "." else f"{minio_prefix}/{rel_stem}" + + for i, (x1,y1,x2,y2,conf,cls_id) in enumerate(j.get("boxes", [])): + w = x2 - x1; h = y2 - y1 + if w < min_wh or h < min_wh: + continue + cx = (x1 + x2) * 0.5; cy = (y1 + y2) * 0.5 + half = max(w, h) * 0.5 * (1.0 + margin) + crop = _safe_crop(img, cx-half, cy-half, cx+half, cy+half) + if crop.size == 0: + continue + crop_resized = cv2.resize(crop, (size, size), interpolation=cv2.INTER_AREA) + out_name = f"det{i:03d}_cls{int(cls_id)}_{conf:.2f}.png" + cv2.imwrite(str(dest_dir / out_name), crop_resized) + count += 1 + + if cli: + base = f"{run_id}/{minio_prefix}" + key = f"{base}/{rel_parent}/{rel_stem}/{out_name}" if rel_parent != "." else f"{base}/{rel_stem}/{out_name}" + put_png(cli, minio_bucket, key, crop_resized) + + put_png(cli, minio_bucket, f"{minio_subprefix}/{out_name}", crop_resized) + + print(f"[DONE] Saved {count} crops under: {out_dir} (flat={flat})") + +def main(): + ap = argparse.ArgumentParser(description="Create square crops from detection JSON results (+optional MinIO).") + ap.add_argument("--input", required=True) + ap.add_argument("--out", required=True) + ap.add_argument("--orig", default=None, help="source_path") + ap.add_argument("--size", type=int, default=224) + ap.add_argument("--margin", type=float, default=0.1) + ap.add_argument("--min-wh", type=int, default=8) + ap.add_argument("--flat", action="store_true") + + ap.add_argument("--minio-endpoint", default=None) + ap.add_argument("--minio-access", default=None) + ap.add_argument("--minio-secret", default=None) + ap.add_argument("--minio-bucket", default=None) + ap.add_argument("--minio-prefix", default="crops") + ap.add_argument("--minio-secure", action="store_true") + ap.add_argument("--run-id", default=None, help="MinIO ( YYYY/MM/DD/HHmm)") + + args = ap.parse_args() + run_id = args.run_id or datetime.now().strftime("%Y/%m/%d/%H%M") + run_crop( + inp=Path(args.input), out_dir=Path(args.out), + size=args.size, margin=args.margin, min_wh=args.min_wh, + orig_dir=Path(args.orig) if args.orig else None, flat=args.flat, + minio_endpoint=args.minio_endpoint, minio_access=args.minio_access, + minio_secret=args.minio_secret, minio_bucket=args.minio_bucket, + minio_prefix=args.minio_prefix, minio_secure=args.minio_secure, + run_id=run_id, + ) + + + +if __name__ == "__main__": + main() diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/detect_only.py b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/detect_only.py new file mode 100644 index 000000000..9be1da3d5 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/detect_only.py @@ -0,0 +1,139 @@ + +from __future__ import annotations +import json, argparse +from pathlib import Path +from typing import Optional +from datetime import datetime + +try: + import cpuinfo as _ci + _ci.get_cpu_info = (lambda: {"brand_raw": "unknown"}) +except Exception: + pass +try: + import ultralytics.utils.torch_utils as _tu + _tu.get_cpu_info = (lambda: "unknown") +except Exception: + pass +# --- end hard patch --- + +import cv2 +from ultralytics import YOLO +from common import iter_images, ensure_dir, draw_boxes + +import cpuinfo +try: + print("cpu brand:", cpuinfo.get_cpu_info().get("brand_raw")) +except Exception as e: + print("cpuinfo error:", repr(e)) + +try: + from minio_io import get_client, ensure_bucket, put_png, put_json +except Exception: + get_client = ensure_bucket = put_png = put_json = None + +def run_detect(inp: Path, out_dir: Path, weights: Path, + conf: float=0.25, imgsz: int=896, device: str="cpu", + minio_endpoint: Optional[str]=None, minio_access: Optional[str]=None, + minio_secret: Optional[str]=None, minio_bucket: Optional[str]=None, + minio_prefix: str="DETECT", minio_secure: bool=False, + run_id: Optional[str]=None): + + run_id = run_id or datetime.now().strftime("%Y/%m/%d/%H%M") + out_dir = ensure_dir(out_dir) + overlay_root = ensure_dir(out_dir / "overlay") + json_root = ensure_dir(out_dir / "json") + + cli = None + if minio_endpoint and minio_access and minio_secret and minio_bucket: + if get_client is None: + raise SystemExit("[ERR] mini minio_io.") + cli = get_client(minio_endpoint, minio_access, minio_secret, secure=minio_secure) + ensure_bucket(cli, minio_bucket) + + model = YOLO(str(weights)) + + + img_paths = list(iter_images(inp)) + if not img_paths: + raise SystemExit(f"[ERR] No images found under: {inp}") + + is_dir_input = Path(inp).is_dir() + + for img_path in img_paths: + + rel_path = img_path.name if not is_dir_input else str(img_path.relative_to(inp)) + rel_parent = "." if not is_dir_input else str(img_path.relative_to(inp).parent) + rel_stem = Path(rel_path).stem + + overlay_dir = ensure_dir(overlay_root / rel_parent) + json_dir = ensure_dir(json_root / rel_parent) + + img_bgr = cv2.imread(str(img_path)) + if img_bgr is None: + print(f"[WARN] can't read image: {img_path}") + continue + h, w = img_bgr.shape[:2] + + res = model.predict(source=img_bgr, conf=conf, imgsz=imgsz, device=device, verbose=False)[0] + + boxes_pix = [] + if res.boxes is not None and len(res.boxes) > 0: + for b in res.boxes: + xyxy = b.xyxy.cpu().numpy().reshape(-1) + conf_i = float(b.conf.cpu().numpy().reshape(-1)[0]) + cls_i = float(b.cls.cpu().numpy().reshape(-1)[0]) if b.cls is not None else 0.0 + x1,y1,x2,y2 = map(float, xyxy.tolist()) + boxes_pix.append([x1,y1,x2,y2,conf_i,cls_i]) + + j = { + "image": img_path.name, + "rel_path": rel_path, + "source_path": str(img_path.resolve()), + "width": w, "height": h, + "boxes": boxes_pix + } + json_path = json_dir / f"{rel_stem}.json" + json_path.write_text(json.dumps(j, ensure_ascii=False, indent=2), encoding="utf-8") + + overlay = draw_boxes(img_bgr, boxes_pix) + ov_path = overlay_dir / img_path.name + cv2.imwrite(str(ov_path), overlay) + + if cli: + base = f"{run_id}/{minio_prefix}" + minio_json_key = f"{base}/json/{rel_parent}/{rel_stem}.json" if rel_parent != "." else f"{base}/json/{rel_stem}.json" + minio_ov_key = f"{base}/overlay/{rel_parent}/{img_path.name}" if rel_parent != "." else f"{base}/overlay/{img_path.name}" + put_json(cli, minio_bucket, minio_json_key, j) + put_png(cli, minio_bucket, minio_ov_key, overlay) + + print(f"[OK] {rel_path} -> {json_path.relative_to(out_dir)}, boxes={len(boxes_pix)}") + +def main(): + ap = argparse.ArgumentParser(description="YOLO detect -> pixel JSON + overlay (+optional MinIO)") + ap.add_argument("--input", required=True) + ap.add_argument("--out", required=True) + ap.add_argument("--weights", required=True) + ap.add_argument("--conf", type=float, default=0.25) + ap.add_argument("--imgsz", type=int, default=896) + ap.add_argument("--device", default="cpu") + + ap.add_argument("--minio-endpoint", default=None) + ap.add_argument("--minio-access", default=None) + ap.add_argument("--minio-secret", default=None) + ap.add_argument("--minio-bucket", default=None) + ap.add_argument("--minio-prefix", default="detect") + ap.add_argument("--minio-secure", action="store_true") + ap.add_argument("--run-id", default=None, help="-MinIO (YYYY/MM/DD/HHmm)") + + args = ap.parse_args() + run_id = args.run_id or datetime.now().strftime("%Y/%m/%d/%H%M") + run_detect(Path(args.input), Path(args.out), Path(args.weights), + conf=args.conf, imgsz=args.imgsz, device=args.device, + minio_endpoint=args.minio_endpoint, minio_access=args.minio_access, + minio_secret=args.minio_secret, minio_bucket=args.minio_bucket, + minio_prefix=args.minio_prefix, minio_secure=args.minio_secure, + run_id=run_id) + +if __name__ == "__main__": + main() diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/minio_io.py b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/minio_io.py new file mode 100644 index 000000000..999ce7571 --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/minio_io.py @@ -0,0 +1,37 @@ +from __future__ import annotations +import io, json, os +from pathlib import Path +import cv2 +from minio import Minio +from minio.error import S3Error + +def get_client(endpoint: str, access_key: str, secret_key: str, secure: bool=False) -> Minio: + """ + + cli = get_client("localhost:9000", "minioadmin", "minioadmin", secure=False) + """ + return Minio(endpoint, access_key=access_key, secret_key=secret_key, secure=secure) + +def ensure_bucket(cli: Minio, bucket: str): + found = cli.bucket_exists(bucket) + if not found: + cli.make_bucket(bucket) + +def put_png(cli: Minio, bucket: str, key: str, img_bgr): + + Path(key).parent and os.makedirs(Path(key).parent, exist_ok=True) + ok, buf = cv2.imencode(".png", img_bgr) + if not ok: + raise RuntimeError("cv2.imencode PNG failed") + bio = io.BytesIO(buf.tobytes()) + bio.seek(0) + cli.put_object(bucket, key, bio, length=len(bio.getvalue()), content_type="image/png") + +def put_json(cli: Minio, bucket: str, key: str, obj): + """ + JSON (dict/list). + """ + js = json.dumps(obj, ensure_ascii=False, indent=2).encode("utf-8") + bio = io.BytesIO(js) + bio.seek(0) + cli.put_object(bucket, key, bio, length=len(js), content_type="application/json") diff --git a/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/predict_pyramid_wbf.py b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/predict_pyramid_wbf.py new file mode 100644 index 000000000..33a2f4b8c --- /dev/null +++ b/airflow_bundle/leaf-pipeline/projects/leaf-counting/src/predict_pyramid_wbf.py @@ -0,0 +1,230 @@ + +from __future__ import annotations +import argparse, json +from pathlib import Path +from typing import List, Tuple, Optional +from datetime import datetime + +try: + import cpuinfo as _ci + _ci.get_cpu_info = (lambda: {"brand_raw": "unknown"}) +except Exception: + pass +try: + import ultralytics.utils.torch_utils as _tu + _tu.get_cpu_info = (lambda: "unknown") +except Exception: + pass +# --- end hard patch --- + +import cv2 +import numpy as np +from ultralytics import YOLO + +from common import iter_images, ensure_dir, draw_boxes + +try: + from minio_io import get_client, ensure_bucket, put_png, put_json +except Exception: + get_client = ensure_bucket = put_png = put_json = None + + +# ----------------- WBF utils ----------------- +def iou_xyxy(a: np.ndarray, b: np.ndarray) -> float: + ax1, ay1, ax2, ay2 = a + bx1, by1, bx2, by2 = b + ix1, iy1 = max(ax1, bx1), max(ay1, by1) + ix2, iy2 = min(ax2, bx2), min(ay2, by2) + iw, ih = max(0.0, ix2 - ix1), max(0.0, iy2 - iy1) + inter = iw * ih + area_a = max(0.0, ax2 - ax1) * max(0.0, ay2 - ay1) + area_b = max(0.0, bx2 - bx1) * max(0.0, by2 - by1) + union = area_a + area_b - inter + 1e-9 + return inter / union + + +def wbf(boxes: List[np.ndarray], scores: List[float], iou_thr: float = 0.55) -> tuple[list[np.ndarray], list[float]]: + used = [False] * len(boxes) + out_boxes, out_scores = [], [] + for i in range(len(boxes)): + if used[i]: + continue + group_idxs = [i] + used[i] = True + for j in range(i + 1, len(boxes)): + if used[j]: + continue + if iou_xyxy(boxes[i], boxes[j]) >= iou_thr: + group_idxs.append(j) + used[j] = True + bs = np.array([boxes[k] for k in group_idxs], dtype=float) + ws = np.array([scores[k] for k in group_idxs], dtype=float) + wsum = ws.sum() + 1e-9 + avg = (bs * ws[:, None]).sum(axis=0) / wsum + out_boxes.append(avg) + out_scores.append(float(ws.max())) + return out_boxes, out_scores + + +# ----------------- multi-scale predict ----------------- +def predict_at_scales(model: YOLO, img_bgr: np.ndarray, scales: List[float], conf: float, imgsz: int, device: str): + H, W = img_bgr.shape[:2] + all_boxes, all_scores, all_classes = [], [], [] + for s in scales: + if s == 1.0: + resized = img_bgr + rx, ry = 1.0, 1.0 + else: + newW, newH = int(W * s), int(H * s) + resized = cv2.resize(img_bgr, (newW, newH), interpolation=cv2.INTER_LINEAR) + rx, ry = 1.0 / s, 1.0 / s + + res = model.predict(source=resized, conf=conf, imgsz=imgsz, device=device, verbose=False)[0] + if res.boxes is None or len(res.boxes) == 0: + continue + for b in res.boxes: + xyxy = b.xyxy.cpu().numpy().reshape(-1) + conf_i = float(b.conf.cpu().numpy().reshape(-1)[0]) + cls_i = float(b.cls.cpu().numpy().reshape(-1)[0]) if b.cls is not None else 0.0 + x1, y1, x2, y2 = xyxy + x1, y1, x2, y2 = x1 * rx, y1 * ry, x2 * rx, y2 * ry + all_boxes.append(np.array([x1, y1, x2, y2], dtype=float)) + all_scores.append(conf_i) + all_classes.append(int(cls_i)) + return all_boxes, all_scores, all_classes + + +# ----------------- main runner ----------------- +def run(inp: Path, out_dir: Path, weights: Path, + scales: List[float], conf: float = 0.25, iou_thr: float = 0.55, + imgsz: int = 896, device: str = "cpu", + minio_endpoint: Optional[str] = None, minio_access: Optional[str] = None, + minio_secret: Optional[str] = None, minio_bucket: Optional[str] = None, + minio_prefix: str = "PREDICT_PWB", minio_secure: bool = False, + run_id: Optional[str] = None): + + run_id = run_id or datetime.now().strftime("%Y/%m/%d/%H%M") + + out_dir = ensure_dir(out_dir) + overlay_root = ensure_dir(out_dir / "overlay") + json_root = ensure_dir(out_dir / "json") + + cli = None + if minio_endpoint and minio_access and minio_secret and minio_bucket: + if get_client is None: + raise SystemExit("[ERR] minio minio_io.") + cli = get_client(minio_endpoint, minio_access, minio_secret, secure=minio_secure) + ensure_bucket(cli, minio_bucket) + + model = YOLO(str(weights)) + images = list(iter_images(inp)) + if not images: + raise SystemExit(f"[ERR] No images under: {inp}") + + for p in images: + img = cv2.imread(str(p)) + if img is None: + print(f"[WARN] can't read: {p}") + continue + H, W = img.shape[:2] + + + rel_path = str(p.relative_to(inp)) if inp.is_dir() else p.name + rel_parent = str(Path(rel_path).parent) + rel_stem = Path(rel_path).stem + + boxes, scores, classes = predict_at_scales(model, img, scales, conf, imgsz, device) + + + merged = [] + for cls in sorted(set(classes)): + idxs = [i for i, c in enumerate(classes) if c == cls] + if not idxs: + continue + bcls = [boxes[i] for i in idxs] + scls = [scores[i] for i in idxs] + mbox, mscore = wbf(bcls, scls, iou_thr=iou_thr) + for bb, ss in zip(mbox, mscore): + x1, y1, x2, y2 = [float(max(0, v)) for v in bb] + x1, y1 = min(x1, W - 1), min(y1, H - 1) + x2, y2 = min(x2, W - 1), min(y2, H - 1) + merged.append([x1, y1, x2, y2, float(ss), float(cls)]) + + + overlay_dir = ensure_dir(overlay_root / rel_parent) + json_dir = ensure_dir(json_root / rel_parent) + + j = { + "image": p.name, + "rel_path": rel_path, + "source_path": str(p.resolve()), + "width": W, "height": H, + "boxes": merged + } + jpath = json_dir / f"{rel_stem}.json" + jpath.write_text(json.dumps(j, ensure_ascii=False, indent=2), encoding="utf-8") + + overlay = draw_boxes(img, merged) + cv2.imwrite(str(overlay_dir / p.name), overlay) + + + if cli: + base = f"{run_id}/{minio_prefix}" + json_key = f"{base}/json/{rel_parent}/{rel_stem}.json" if rel_parent != "." else f"{base}/json/{rel_stem}.json" + ov_key = f"{base}/overlay/{rel_parent}/{p.name}" if rel_parent != "." else f"{base}/overlay/{p.name}" + put_json(cli, minio_bucket, json_key, j) + put_png(cli, minio_bucket, ov_key, overlay) + + print(f"[OK] {rel_path} WBF boxes={len(merged)} -> {jpath.relative_to(out_dir)}") + + +def parse_scales(s: str) -> List[float]: + return [float(x) for x in s.split(",") if x.strip()] + + +def main(): + ap = argparse.ArgumentParser(description="YOLO multi-scale + WBF (+optional MinIO)") + ap.add_argument("--input", required=True) + ap.add_argument("--out", required=True) + ap.add_argument("--weights", required=True) + ap.add_argument("--scales", default="0.75,1.0,1.25", help="comma-separated, e.g. 0.5,1.0,1.5") + ap.add_argument("--conf", type=float, default=0.25) + ap.add_argument("--iou", type=float, default=0.55, help="WBF IoU threshold") + ap.add_argument("--imgsz", type=int, default=896) + ap.add_argument("--device", default="cpu") + + # MinIO + ap.add_argument("--minio-endpoint", default=None) + ap.add_argument("--minio-access", default=None) + ap.add_argument("--minio-secret", default=None) + ap.add_argument("--minio-bucket", default=None) + ap.add_argument("--minio-prefix", default="PREDICT_PWB") + ap.add_argument("--minio-secure", action="store_true") + + # Run grouping + ap.add_argument("--run-id", default=None, help="(YY/MM/DD/HHmm)") + + args = ap.parse_args() + + run_id = args.run_id or datetime.now().strftime("%Y/%m/%d/%H%M") + run( + inp=Path(args.input), + out_dir=Path(args.out), + weights=Path(args.weights), + scales=parse_scales(args.scales), + conf=args.conf, + iou_thr=args.iou, + imgsz=args.imgsz, + device=args.device, + minio_endpoint=args.minio_endpoint, + minio_access=args.minio_access, + minio_secret=args.minio_secret, + minio_bucket=args.minio_bucket, + minio_prefix=args.minio_prefix, + minio_secure=args.minio_secure, + run_id=run_id, + ) + + +if __name__ == "__main__": + main() diff --git a/audio_samples/mic1_2025-10-28_11-45.wav b/audio_samples/mic1_2025-10-28_11-45.wav deleted file mode 100644 index c229a99ea..000000000 Binary files a/audio_samples/mic1_2025-10-28_11-45.wav and /dev/null differ diff --git a/audio_samples/mic1_2025-10-28_12-05.wav b/audio_samples/mic1_2025-10-28_12-05.wav deleted file mode 100644 index c229a99ea..000000000 Binary files a/audio_samples/mic1_2025-10-28_12-05.wav and /dev/null differ diff --git a/docker-compose.yml b/docker-compose.yml index 4ab011a41..87cd954c8 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -1,8 +1,6 @@ # ========================== # Docker Compose - AG Cloud # ========================== - -# version: "3.9" # -------------------------- # Networks # -------------------------- @@ -10,6 +8,15 @@ networks: ag_cloud: name: ag_cloud driver: bridge + flink-net: + driver: bridge + +# -------------------------- +# Secrets +# -------------------------- +secrets: + slack_webhook: + file: ./secrets/slack_webhook.url # -------------------------- # Volumes @@ -95,7 +102,7 @@ services: - MINIO_ACCESS_KEY=minioadmin - MINIO_SECRET_KEY=minioadmin123 - MINIO_BUCKET=sound - - MINIO_PREFIX=sounds/ + - MINIO_PREFIX=sounds/, plants/ command: [ "python", "-u", "src/metrics.py" ] ports: @@ -113,10 +120,8 @@ services: plant_stress_daily: build: ./services/plant_stress - env_file: - - ./services/plant_stress/.env - restart: "no" environment: + TZ: "Asia/Jerusalem" MODEL_DIR: /models CONFIDENCE_THRESHOLD: "0.60" TF_CPP_MIN_LOG_LEVEL: "2" @@ -128,20 +133,17 @@ services: MINIO_BUCKET: sound MINIO_PREFIX: plants/ MINIO_SECURE: "false" - DEFAULT_AREA: unknown DEFAULT_LAT: 0.0 DEFAULT_LON: 0.0 DEFAULT_IMAGE_URL: https://example.com/placeholder.jpg DEFAULT_VOD: https://example.com/placeholder.mp4 DEFAULT_HLS: https://example.com/placeholder.m3u8 - # ==== Alerts → Kafka ==== ENABLE_ALERTS: "true" - KAFKA_BOOTSTRAP: "kafka:9092" + KAFKA_BOOTSTRAP: "kafka:9092" ALERT_TOPIC: "alerts" ALERT_TYPE: "plant_drought_detected" KAFKA_CLIENT_ID: "plant-stress-producer" - command: ["python","-u","/app/predict_minio_daily.py"] volumes: - "./services/plant_stress/models:/models:ro" depends_on: @@ -151,9 +153,10 @@ services: condition: service_healthy mc-bootstrap: condition: service_started - kafka: + kafka: condition: service_healthy networks: [ag_cloud] + restart: unless-stopped # ------------------------- # MQTT + Kafka + MQTT-router @@ -576,7 +579,7 @@ services: MQTT_TOPIC: MQTT/sounds_ultra/# MQTT_PUB_TOPIC: sound/sounds_ultra/ingested DEFAULT_PREFIX: MIC-02 - CAMERA_PREFIX: camera + CAMERA_PREFIX: microphone MICROPHONE_PREFIX: microphone DUMMY_DB: 0 DB_API_BASE: http://db_api_service:8001 @@ -622,6 +625,36 @@ services: - mqtt_ingest networks: - ag_cloud + + mqtt_gateway: + build: + context: ./services/mqtt_gateway + dockerfile: Dockerfile + environment: + MINIO_ENDPOINT: http://minio-hot:9000 + MINIO_ACCESS_KEY: minioadmin + MINIO_SECRET_KEY: minioadmin123 + MINIO_BUCKET: imagery + KAFKA_BOOTSTRAP: kafka:9092 + KAFKA_TOPIC: rover.images.meta.v1 + MQTT_HOST: large-mosquitto + MQTT_PORT: 1885 + MQTT_TOPIC: MQTT/imagery/# + MQTT_TOPIC_TEL: MQTT/telemetry/# + TELEMETRY_TTL_SEC: 10 + MQTT_CLIENT_ID: mqtt-gateway + METRICS_PORT: 9110 + depends_on: + large-mosquitto: + condition: service_started + kafka: + condition: service_healthy + minio-hot: + condition: service_healthy + networks: + - ag_cloud + restart: unless-stopped + # ------------------------ # Classifier - Sounds @@ -647,6 +680,8 @@ services: - DB_URL=postgresql://missions_user:pg123@postgres:5432/missions_db - DB_SCHEMA=agcloud_audio - DB_RUN_ID=api-default + - FILES_SCHEMA=public + - FILES_TABLE=sound_new_sounds_connections # Kafka - KAFKA_BROKERS=kafka:9092 @@ -660,7 +695,7 @@ services: - MINIO_SECURE=false # Request validation - - ALLOWED_BUCKETS=sound + - ALLOWED_BUCKETS=imagery - ALLOWED_CONTENT_TYPES=audio/wav,audio/x-wav,audio/mpeg,audio/flac,audio/ogg,audio/mp4 - MAX_BYTES=104857600 @@ -750,6 +785,8 @@ services: - "5000:5000" depends_on: - postgres + networks: + - ag_cloud ripeness-api: build: @@ -812,7 +849,7 @@ services: python.executable: /usr/bin/python3 - HTTP_INFER_URL=http://fruit-inference-http:8004/infer_json volumes: - - ./streaming/flink/jobs:/opt/flink/jobs:ro + - ./streaming/flink/jobs:/opt/flink/jobs - ./streaming/flink/connectors/flink-json-1.18.1.jar:/opt/flink/lib/flink-json-1.18.1.jar:ro - ./streaming/flink/connectors/flink-sql-connector-kafka-3.2.0-1.18.jar:/opt/flink/lib/flink-sql-connector-kafka-3.2.0-1.18.jar:ro - ./streaming/flink/connectors/flink-connector-kafka-3.2.0-1.18.jar:/opt/flink/lib/flink-connector-kafka-3.2.0-1.18.jar:ro @@ -834,7 +871,7 @@ services: - MINIO_ENDPOINT=minio-hot:9000 - ACCESS_KEY=minioadmin - SECRET_KEY=minioadmin123 - - BUCKET_NAME=imagery + - BUCKET_NAME=sound depends_on: minio-hot: condition: service_healthy @@ -851,7 +888,7 @@ services: container_name: flink_writer_db environment: - KAFKA_BROKERS=kafka:9092 - - TOPICS=sensor_zone_stats,sensor_anomalies,image_new_security_connections,alerts,image_new_aerial_connections,aerial_images_metadata,aerial_image_object_detections,aerial_image_anomaly_detections,aerial_images_complete_metadata,field_polygons,aerial_image_segmentation,sound_new_sounds_connections,sound_new_plants_connections + - TOPICS=sensor_zone_stats,sensor_anomalies,image_new_security_connections,alerts,image_new_aerial_connections,aerial_images_metadata,aerial_image_object_detections,aerial_image_anomaly_detections,aerial_images_complete_metadata,aerial_image_segmentation,sound_new_sounds_connections,sound_new_plants_connections,sounds_metadata,sounds_ultra_metadata,sensors,sensors_anomalies_modal,event_logs_sensors - DB_API_BASE=http://db_api_service:8001 - DB_API_AUTH_MODE=service - DB_API_SERVICE_NAME=flink-writer-db @@ -879,9 +916,9 @@ services: FLINK_PROPERTIES= jobmanager.rpc.address: flink-jobmanager parallelism.default: 2 - taskmanager.numberOfTaskSlots: 2 + taskmanager.numberOfTaskSlots: 4 jobmanager.memory.process.size: 1600m - taskmanager.memory.process.size: 1728m + taskmanager.memory.process.size: 2048m s3.endpoint: http://minio-hot:9000 s3.path.style.access: true s3.access.key: minioadmin @@ -939,6 +976,58 @@ services: ports: - "8012:8004" restart: unless-stopped + soil-inference-http: + build: + context: ./services/inference_http + dockerfile: Dockerfile + environment: + + - TEAM=soil_moisture + - WEIGHTS_PATH=/app/weights/soil_moisture_best.onnx + - MINIO_ENDPOINT=minio-hot:9000 + - MINIO_ACCESS_KEY=minioadmin + - MINIO_SECRET_KEY=minioadmin123 + - MINIO_SECURE=0 + - PG_DSN=postgresql://missions_user:pg123@postgres:5432/missions_db + - KAFKA_BROKERS=kafka:9092 + - KAFKA_TOPIC=irrigation.control + - KAFKA_DLT=irrigation.control.dlq + + + volumes: + - ./services/inference_http/weights:/app/weights:ro + - ./services/inference_http/adapters:/app/adapters + - ./services/inference_http/soil_moisture:/app/soil_moisture + depends_on: + - minio-hot + - postgres + ports: + - "8013:8004" + networks: [ag_cloud] + restart: unless-stopped + + rover-inference-http: + image: rover-inference-http:latest + container_name: rover-inference-http + environment: + - TEAM=rover + # MinIO + - MINIO_ENDPOINT=minio-hot:9000 + - MINIO_ACCESS_KEY=minioadmin + - MINIO_SECRET_KEY=minioadmin123 + - MINIO_SECURE=0 + # Model runtime + - FENCE_ONNX_PATH=/app/models/fence_hole_detector/weights/best.onnx + - FENCE_CONF=0.30 + - FENCE_ROI=none + - FENCE_VOTE_N=1 + - FENCE_VOTE_M=1 + - FENCE_VOTE_COOLDOWN=0 + networks: [ag_cloud] + # Expose internally on 8004; map to 8019 on host (for curl from host) + ports: + - "8019:8004" + restart: unless-stopped # -------------------------- @@ -954,7 +1043,7 @@ services: networks: [ ag_cloud ] environment: - KAFKA_BOOTSTRAP=kafka:9092 - - INPUT_TOPIC=imagery.new.fruit + - INPUT_TOPIC=inference.dispatched.camera - TEAM=fruit - HTTP_URL=http://fruit-inference-http:8004/infer_json - DLQ_TOPIC=dlq.inference.http @@ -969,7 +1058,7 @@ services: - ./streaming/flink/connectors/kafka-clients-3.2.3.jar:/opt/flink/lib/kafka-clients-3.2.3.jar:ro - ./streaming/flink/connectors/lz4-java-1.8.0.jar:/opt/flink/lib/lz4-java-1.8.0.jar:ro - ./streaming/flink/connectors/snappy-java-1.1.10.5.jar:/opt/flink/lib/snappy-java-1.1.10.5.jar:ro - command: [ "bash", "-lc", "set -e; echo 'Waiting for JobManager to accept commands...'; until /opt/flink/bin/flink list --jobmanager flink-jobmanager:8081 >/dev/null 2>&1; do echo 'still waiting...'; sleep 3; done; echo 'JobManager is ready!'; /opt/flink/bin/flink run -Dpython.client.executable=/usr/bin/python3 -Dpython.executable=/usr/bin/python3 -Dpipeline.jars=file:///opt/flink/lib/flink-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/flink-sql-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/flink-json-1.18.1.jar --jobmanager flink-jobmanager:8081 --detached --python /opt/flink/jobs/http_dispatcher.py -- --bootstrap kafka:9092 --input-topic imagery.new.fruit --team fruit --http-url http://fruit-inference-http:8004/infer_json --group-id http-dispatcher-fruit --dlq-topic dlq.inference.http; tail -f /dev/null" ] + command: [ "bash", "-lc", "set -e; echo 'Waiting for JobManager to accept commands...'; until /opt/flink/bin/flink list --jobmanager flink-jobmanager:8081 >/dev/null 2>&1; do echo 'still waiting...'; sleep 3; done; echo 'JobManager is ready!'; /opt/flink/bin/flink run -Dpython.client.executable=/usr/bin/python3 -Dpython.executable=/usr/bin/python3 -Dpipeline.jars=file:///opt/flink/lib/flink-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/flink-sql-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/flink-json-1.18.1.jar --jobmanager flink-jobmanager:8081 --detached --python /opt/flink/jobs/http_dispatcher.py -- --bootstrap kafka:9092 --input-topic inference.dispatched.camera --team fruit --http-url http://fruit-inference-http:8004/infer_json --group-id http-dispatcher-fruit --dlq-topic dlq.inference.http; tail -f /dev/null" ] restart: always flink-dispatcher-camera: @@ -982,7 +1071,7 @@ services: networks: [ag_cloud] environment: - KAFKA_BOOTSTRAP=kafka:9092 - - INPUT_TOPIC=imagery.new.camera + - INPUT_TOPIC=image.new.fruits - TEAM=camera - HTTP_URL=http://camera-inference-http:8004/infer_json - DLQ_TOPIC=dlq.inference.http @@ -992,7 +1081,72 @@ services: volumes: - ./streaming/flink/jobs:/opt/flink/jobs:ro - ./streaming/flink/connectors:/opt/flink/lib/connectors:ro - command: [ "bash", "-lc", "set -e; echo 'Waiting for JobManager to accept commands...'; until /opt/flink/bin/flink list --jobmanager flink-jobmanager:8081 >/dev/null 2>&1; do echo 'still waiting...'; sleep 3; done; echo 'JobManager is ready!'; /opt/flink/bin/flink run -Dpython.client.executable=/usr/bin/python3 -Dpython.executable=/usr/bin/python3 -Dpipeline.jars=file:///opt/flink/lib/connectors/flink-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/connectors/flink-sql-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/connectors/flink-json-1.18.1.jar --jobmanager flink-jobmanager:8081 --detached --python /opt/flink/jobs/http_dispatcher.py -- --bootstrap kafka:9092 --input-topic imagery.new.camera --team camera --http-url http://camera-inference-http:8004/infer_json --group-id http-dispatcher-camera --dlq-topic dlq.inference.http; tail -f /dev/null" ] + command: [ "bash", "-lc", "set -e; echo 'Waiting for JobManager to accept commands...'; until /opt/flink/bin/flink list --jobmanager flink-jobmanager:8081 >/dev/null 2>&1; do echo 'still waiting...'; sleep 3; done; echo 'JobManager is ready!'; /opt/flink/bin/flink run -Dpython.client.executable=/usr/bin/python3 -Dpython.executable=/usr/bin/python3 -Dpipeline.jars=file:///opt/flink/lib/connectors/flink-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/connectors/flink-sql-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/connectors/flink-json-1.18.1.jar --jobmanager flink-jobmanager:8081 --detached --python /opt/flink/jobs/http_dispatcher.py -- --bootstrap kafka:9092 --input-topic image.new.fruits --team camera --http-url http://camera-inference-http:8004/infer_json --group-id http-dispatcher-camera --dlq-topic dlq.inference.http; tail -f /dev/null" ] + restart: always + + flink-dispatcher-soil: + image: agcloud-flink-py:1.18 + depends_on: + flink-jobmanager: { condition: service_started } + flink-taskmanager: { condition: service_started } + soil-inference-http: { condition: service_started } + networks: [ag_cloud] + environment: + - KAFKA_BOOTSTRAP=kafka:9092 + - INPUT_TOPIC=image.new.ground + - TEAM=soil_moisture + - HTTP_URL=http://soil-inference-http:8004/infer_json + - DLQ_TOPIC=dlq.inference.http + - GROUP_ID=http-dispatcher-soil + - PARALLELISM=1 + - PYFLINK_CLIENT_EXECUTABLE=/usr/bin/python3 + volumes: + - ./streaming/flink/jobs:/opt/flink/jobs:ro + - ./streaming/flink/connectors:/opt/flink/lib/connectors:ro + command: [ "bash", "-lc", "set -e; echo 'Waiting...'; until /opt/flink/bin/flink list --jobmanager flink-jobmanager:8081 >/dev/null 2>&1; do echo 'still waiting...'; sleep 3; done; echo 'JobManager is ready!'; /opt/flink/bin/flink run -Dpython.client.executable=/usr/bin/python3 -Dpython.executable=/usr/bin/python3 -Dpipeline.jars=file:///opt/flink/lib/connectors/... --jobmanager flink-jobmanager:8081 --detached --python /opt/flink/jobs/http_dispatcher.py -- --bootstrap kafka:9092 --input-topic image.new.ground --team soil_moisture --http-url http://soil-inference-http:8004/infer_json --group-id http-dispatcher-soil --dlq-topic dlq.inference.http; tail -f /dev/null" ] + + flink-dispatcher-rover: + image: agcloud-flink-py:1.18 + container_name: flink-dispatcher-rover + depends_on: + flink-jobmanager: { condition: service_started } + flink-taskmanager: { condition: service_started } + rover-inference-http: { condition: service_started } + networks: [ag_cloud] + environment: + - KAFKA_BOOTSTRAP=kafka:9092 + - INPUT_TOPIC=imagery.new.rover + - TEAM=rover + - HTTP_URL=http://rover-inference-http:8004/infer_json + - DLQ_TOPIC=dlq.inference.http + - GROUP_ID=http-dispatcher-rover + - PARALLELISM=2 + - PYFLINK_CLIENT_EXECUTABLE=/usr/bin/python3 + volumes: + - ./streaming/flink/jobs:/opt/flink/jobs:ro + - ./streaming/flink/connectors:/opt/flink/lib/connectors:ro + command: [ + "bash","-lc", + "set -e; echo 'Waiting for JobManager...'; \ + until /opt/flink/bin/flink list --jobmanager flink-jobmanager:8081 >/dev/null 2>&1; do \ + echo 'still waiting...'; sleep 3; \ + done; echo 'JobManager ready!'; \ + /opt/flink/bin/flink run \ + -Dpython.client.executable=/usr/bin/python3 \ + -Dpython.executable=/usr/bin/python3 \ + -Dpipeline.jars=file:///opt/flink/lib/connectors/flink-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/connectors/flink-sql-connector-kafka-3.2.0-1.18.jar,file:///opt/flink/lib/connectors/flink-json-1.18.1.jar \ + --jobmanager flink-jobmanager:8081 \ + --detached \ + --python /opt/flink/jobs/http_dispatcher.py \ + -- \ + --bootstrap $$KAFKA_BOOTSTRAP \ + --input-topic $$INPUT_TOPIC \ + --team $$TEAM \ + --http-url $$HTTP_URL \ + --group-id $$GROUP_ID \ + --dlq-topic $$DLQ_TOPIC; \ + tail -f /dev/null" + ] restart: always flink-alerts-job: @@ -1181,3 +1335,594 @@ services: FLINK_PYTHON: /opt/venv/bin/python networks: - ag_cloud + + fruit-defect-sink: + build: + context: ./services/fruit_defect_sink + dockerfile: Dockerfile + environment: + - KAFKA_BOOTSTRAP=kafka:9092 + - INPUT_TOPIC=inference.dispatched.fruit + - ALERTS_TOPIC=alerts + - GROUP_ID=fruit-defect-sink + - AUTO_OFFSET_RESET=earliest + - MAX_POLL_INTERVAL_MS=900000 + - SESSION_TIMEOUT_MS=45000 + - HEARTBEAT_INTERVAL_MS=3000 + - PGHOST=postgres + - PGPORT=5432 + - PGDATABASE=missions_db + - PGUSER=missions_user + - PGPASSWORD=pg123 + depends_on: + kafka: { condition: service_healthy } + postgres: { condition: service_healthy } + networks: [ ag_cloud ] + restart: unless-stopped + + fruit_metrics: + build: + context: ./services/fruit_metrics + container_name: fruit_metrics + networks: [ ag_cloud ] + ports: + - "8050:8050" + restart: unless-stopped + + + fruit_alert_generator: + build: + context: ./services/fruit_alert_generator + dockerfile: Dockerfile + container_name: fruit_alert_generator + networks: [ ag_cloud ] + environment: + PGHOST: postgres + PGPORT: 5432 + PGUSER: missions_user + PGPASSWORD: pg123 + PGDATABASE: missions_db + restart: unless-stopped + + + ripeness-exporter: + build: + context: ./services/ripeness_exporter + container_name: ripeness-exporter + restart: unless-stopped + networks: [ ag_cloud ] + depends_on: + - postgres + environment: + - PYTHONUNBUFFERED=1 + ports: + - "9128:9128" + + # -------------------------- + # Sensor Anomaly Pro + Flink + # -------------------------- + sensor_anomaly_pro: + build: + context: ./services/sensorAnomalyPro/sensorAnomalyPro + dockerfile: Dockerfile + container_name: sensor-anomaly-pro + volumes: + - ./services/sensorAnomalyPro/sensorAnomalyPro/data:/app/data + - ./services/sensorAnomalyPro/sensorAnomalyPro/reports:/app/reports + environment: + - DATA_PATH=/app/data/plant_health_data.csv + command: > + python analyze_sensors.py + networks: + - ag_cloud + + jobmanager: + build: + context: ./services/sensorAnomalyPro + dockerfile: Dockerfile.flink + container_name: sensoers_jobmanager + command: > + bash -c " + /docker-entrypoint.sh jobmanager & + echo '⏳ Waiting for Flink JobManager startup...' && + sleep 10 && + echo '🕓 Waiting for reports to be generated...' && + while [ ! -d /opt/app/sensorAnomalyPro/reports ] || [ -z \"$(ls -A /opt/app/sensorAnomalyPro/reports 2>/dev/null)\" ]; do + echo ' ↳ reports directory empty, waiting...'; + sleep 5; + done && + echo '✅ Reports ready, submitting Flink job...' && + flink run -m localhost:8081 -py /opt/app/sensorAnomalyPro/app.py && + tail -f /dev/null" + depends_on: + - sensor_anomaly_pro + - kafka + ports: + - "8900:8081" + environment: + - JOB_MANAGER_RPC_ADDRESS=jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=sensors + - OUT_TOPIC=sensor_anomalies + - ZONE_TOPIC=sensor_zone_stats + volumes: + - ./services/sensorAnomalyPro/sensorAnomalyPro/reports:/opt/app/sensorAnomalyPro/reports:rw + restart: unless-stopped + networks: + - ag_cloud + + taskmanager: + build: + context: ./services/sensorAnomalyPro + dockerfile: Dockerfile.flink + container_name: sensors_taskmanager + command: taskmanager -D taskmanager.numberOfTaskSlots=4 + depends_on: + - jobmanager + environment: + - JOB_MANAGER_RPC_ADDRESS=jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=sensors + - OUT_TOPIC=sensor_anomalies + - ZONE_TOPIC=sensor_zone_stats + - taskmanager.numberOfTaskSlots=4 + volumes: + - ./services/sensorAnomalyPro/sensorAnomalyPro/reports:/opt/app/sensorAnomalyPro/reports:rw + restart: unless-stopped + networks: + - ag_cloud + + + + vector_service: + build: ./services/vector_service + container_name: vector_service + environment: + - DB_HOST=postgres + - DB_PORT=5432 + - DB_USER=missions_user + - DB_PASS=pg123 + - DB_NAME=missions_db + ports: + - "8006:8000" + depends_on: + - postgres + networks: + - ag_cloud + + + +# -------------------------- +# SensorGuard - Flink Job for Sensor Health Monitoring +# --------------------------sensorguard-jobmanager: + sensorguard-jobmanager: + build: + context: ./services/sensorGuard + dockerfile: Dockerfile.flink + container_name: sensorguard-jobmanager + ports: + - "8081:8081" + command: > + bash -c " + /docker-entrypoint.sh jobmanager & + echo 'Waiting for Flink JobManager startup...' && + sleep 15 && + echo 'Submitting sensorGuard Flink job...' && + flink run -m localhost:8081 -py /opt/app/main.py && + tail -f /dev/null" + environment: + - JOB_MANAGER_RPC_ADDRESS=sensorguard-jobmanager + - KAFKA_BROKERS=kafka:9092 + - KAFKA_IN_TOPIC=sensors + - KAFKA_OUT_TOPIC=event_logs_sensors + - KAFKA_GROUP_ID=sensorguard-flink-pipeline + - DB_API_BASE=http://db_api_service:8001 + - DB_API_AUTH_MODE=service + - DB_API_SERVICE_NAME=sensorguard-flink + - DB_API_TOKEN_FILE=/opt/app/secrets/db_api_token + depends_on: + kafka: + condition: service_healthy + db_api_service: + condition: service_started + networks: + - ag_cloud + volumes: + - ./services/sensorGuard/secrets:/opt/app/secrets + restart: unless-stopped + sensorguard-taskmanager: + build: + context: ./services/sensorGuard + dockerfile: Dockerfile.flink + container_name: sensorguard-taskmanager + command: taskmanager -D taskmanager.numberOfTaskSlots=4 + depends_on: + - sensorguard-jobmanager + environment: + - JOB_MANAGER_RPC_ADDRESS=sensorguard-jobmanager + - KAFKA_BROKERS=kafka:9092 + - KAFKA_IN_TOPIC=sensors + - KAFKA_OUT_TOPIC=event_logs_sensors + - taskmanager.numberOfTaskSlots=4 + - KAFKA_GROUP_ID=sensorguard-flink-pipeline + - DB_API_BASE=http://db_api_service:8001 + - DB_API_AUTH_MODE=service + - DB_API_SERVICE_NAME=sensorguard-flink + networks: + - ag_cloud + volumes: + - ./services/sensorGuard/secrets:/opt/app/secrets + restart: unless-stopped + + # -------------------------- + # Flink Air Processing + # -------------------------- + + air-jobmanager: + build: + context: . + dockerfile: Dockerfile.flink + container_name: air-jobmanager + command: jobmanager + ports: + - "8085:8081" + environment: + - JOB_MANAGER_RPC_ADDRESS=air-jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=image.new.aerial + - KAFKA_GROUP_ID=flink-air-device-pipeline + networks: + - flink-net + - ag_cloud + + air-taskmanager: + build: + context: ./services/air + dockerfile: Dockerfile.flink + container_name: air-taskmanager + command: taskmanager -D taskmanager.numberOfTaskSlots=4 + depends_on: + air-jobmanager: + condition: service_started + infer-api: + condition: service_healthy + anomaly-api: + condition: service_healthy + segmentation-api: + condition: service_healthy + environment: + - JOB_MANAGER_RPC_ADDRESS=air-jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=image.new.aerial + - OUT_TOPIC_OBJECT=aerial_image_object_detections + - OUT_TOPIC_ANOMALY=aerial_image_anomaly_detections + - OUT_TOPIC_SEGMENTATION=aerial_image_segmentation + - taskmanager.numberOfTaskSlots=4 + - KAFKA_GROUP_ID=flink-air-device-pipeline + - SEGMENTATION_URL=http://segmentation-api:8500/infer + - INFER_URL=http://infer-api:8000/infer + - ANOMALY_URL=http://anomaly-api:8010/predict + - INFER_CONF=0.25 + - INFER_IOU=0.45 + - MINIO_ENDPOINT=minio-hot:9000 + - MINIO_ACCESS_KEY=minioadmin + - MINIO_SECRET_KEY=minioadmin123 + networks: + - flink-net + - ag_cloud + restart: unless-stopped + + infer-api: + build: + context: ./services/air/object_detection_api + dockerfile: Dockerfile.infer + container_name: infer-api + environment: + - WEIGHTS_PATH=/app/object_detection_api.pt + volumes: + - ./services/air/object_detection_api/model/object_detection_api.pt:/app/object_detection_api.pt:ro + healthcheck: + test: ["CMD", "curl", "-sf", "http://localhost:8000/health"] + interval: 10s + timeout: 3s + retries: 15 + networks: + - flink-net + - ag_cloud + + anomaly-api: + build: + context: ./services/air/anomaly_detection_api + dockerfile: Dockerfile.anomaly + container_name: anomaly-api + environment: + - MODEL_PATH=/app/models/anomaly_detection_api.pt + volumes: + - ./services/air/anomaly_detection_api/models:/app/models:ro + ports: + - "8020:8010" + healthcheck: + test: ["CMD", "curl", "-sf", "http://localhost:8010/health"] + interval: 10s + timeout: 3s + retries: 15 + networks: + - flink-net + - ag_cloud + + segmentation-api: + build: + context: ./services/air/segmentation_api + dockerfile: dockerfile.segmentation + container_name: segmentation-api + environment: + - MODEL_PATH=/app/model/segmentation_api.pth + ports: + - "8500:8500" + volumes: + - ./services/air/segmentation_api/model:/app/model:ro + - ./services/air/segmentation_api/certs:/usr/local/share/ca-certificates/netfree:ro + healthcheck: + test: ["CMD", "curl", "-sf", "http://localhost:8500/health"] + interval: 10s + timeout: 3s + retries: 10 + networks: + - flink-net + - ag_cloud + + air-submit: + build: + context: ./services/air + dockerfile: Dockerfile.flink + depends_on: + air-jobmanager: + condition: service_started + command: > + bash -c " + sleep 10 && + flink run -m air-jobmanager:8081 -py /opt/app/job.py + " + networks: + - flink-net + - ag_cloud + + + # -------------------------- + # Security + # -------------------------- + + media-proxy: + build: + context: ./services/security + dockerfile: agguard/app/Dockerfile + command: uvicorn agguard.app.media_proxy:app --host 0.0.0.0 --port 8080 + environment: + - MEDIA_AUTH_TOKEN=CHANGE_ME + - PYTHONPATH=/app + ports: + - "8089:8080" + networks: + - ag_cloud + + + security-flink-jobmanager: + build: + context: ./services/security + dockerfile: agguard/pipeline/Dockerfile + image: agguard-flink:latest + container_name: security-flink-jobmanager + + command: > + bash -c " + /docker-entrypoint.sh jobmanager & + echo 'Waiting for Kafka...'; + sleep 15 && + echo '🚀 Submitting Flink job...' && + flink run -py /opt/app/agguard/pipeline/flink_job.py + " + + + environment: + - JOB_MANAGER_RPC_ADDRESS=security-flink-jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=image_new_security_connections + - OUT_TOPIC=alerts + - heartbeat.timeout=180000 + - heartbeat.interval=30000 + volumes: + - ./services/security/agguard/app:/app/agguard/app + - ./services/security/agguard/core:/app/agguard/core + - ./services/security/agguard/specialists:/app/agguard/specialists + - ./services/security/agguard/pipeline:/app/agguard/pipeline + - ./services/security/agguard/adapters:/app/agguard/adapters + - ./services/security/agguard/media:/app/agguard/media + - ./services/security/configs:/app/configs:ro + + depends_on: + kafka: + condition: service_healthy + mqtt-router: + condition: service_healthy + networks: + - ag_cloud + + security-flink-taskmanager: + image: agguard-flink:latest + container_name: security-flink-taskmanager + command: taskmanager -D taskmanager.numberOfTaskSlots=4 + environment: + - JOB_MANAGER_RPC_ADDRESS=security-flink-jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=image_new_security_connections + - OUT_TOPIC=alerts + - taskmanager.numberOfTaskSlots=4 + - heartbeat.timeout=180000 + - heartbeat.interval=30000 + volumes: + - ./services/security/agguard/app:/app/agguard/app + - ./services/security/agguard/core:/app/agguard/core + - ./services/security/agguard/specialists:/app/agguard/specialists + - ./services/security/agguard/pipeline:/app/agguard/pipeline + - ./services/security/agguard/adapters:/app/agguard/adapters + - ./services/security/agguard/media:/app/agguard/media + - ./services/security/configs:/app/configs:ro + depends_on: + security-flink-jobmanager: + condition: service_started + networks: + - ag_cloud + + + + + + animal-classifier: + build: + context: ./services/security + dockerfile: agguard/specialists/animal_service/Dockerfile.animal-classifier + image: agguard-animal-classifier:latest + environment: + - PORT=50064 + - METRICS_PORT=8008 + - MODEL_PATH=/app/weights/yolov8n-cls.pt + - DEVICE=cpu + volumes: + - ./services/security/weights:/app/weights:ro + - ./services/security/agguard/specialists/animal_service:/app/agguard/specialists/animal_service + expose: + - "50064" + - "8008" + networks: + - ag_cloud + + + mega-detector: + build: + context: ./services/security + dockerfile: agguard/specialists/megadetector_service/Dockerfile.mega-detector + image: mega-detector:latest + environment: + - PORT=50063 + - METRICS_PORT=8007 + - MODEL_NAME=MDV5A + - CONF_THRESH=0.2 + - DEVICE=cpu + volumes: + - ./services/security/agguard/specialists/megadetector_service:/app/agguard/specialists/megadetector_service + + expose: + - "50063" + - "8007" + container_name: mega-detector + networks: + - ag_cloud + + + anomalies-classifier: + build: + context: ./services/security + dockerfile: agguard/specialists/anomalies_service/Dockerfile.anomalies-classifier + image: agguard-anomalies-classifier:latest + container_name: clip-classifier + environment: + - PORT=50062 + - METRICS_PORT=8011 + - DEVICE=cpu + - CLIP_MODEL=RN50 + - CLIP_PRETRAINED=openai + - CLIP_INPUT_SIZE=224 + - CLIP_TEMPERATURE=100.0 + - CLIP_BATCH=32 + - ENABLE_MKLDNN=1 + - NUM_THREADS=6 + expose: + - "50062" + networks: + - ag_cloud + + + + mask-classifier: + build: + context: ./services/security + dockerfile: agguard/specialists/mask_service/Dockerfile.mask-classifier + image: agguard-mask-classifier:latest + environment: + - PORT=50061 + - METRICS_PORT=8012 + - BACKEND=onnx + - MODEL_PATH=/app/weights/mask_yolov8.onnx + - CLASSES=no_mask,mask + - IMGSZ=224 + - DEVICE=cpu + volumes: + - ./services/security/weights:/app/weights:ro + expose: + - "50061" + networks: + - ag_cloud + + + crosssensor-flink-jobmanager: + build: + context: ./services/Cross-Sensor System-Level Anomalies + dockerfile: Dockerfile.flink + container_name: crosssensor-flink-jobmanager + command: jobmanager + ports: + - "8086:8081" + environment: + - JOB_MANAGER_RPC_ADDRESS=crosssensor-flink-jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=sensors + - OUT_TOPIC=sensors_anomalies_modal + volumes: + - ./services/Cross-Sensor System-Level Anomalies/conf/flink-conf.yaml:/opt/flink/conf/flink-conf.yaml + - ./services/Cross-Sensor System-Level Anomalies/flink_job.py:/opt/app/flink_job.py + - ./services/Cross-Sensor System-Level Anomalies/models:/opt/models + depends_on: + kafka: + condition: service_healthy + networks: + - ag_cloud + restart: unless-stopped + + crosssensor-flink-taskmanager: + build: + context: ./services/Cross-Sensor System-Level Anomalies + dockerfile: Dockerfile.flink + container_name: crosssensor-flink-taskmanager + command: taskmanager + depends_on: + - crosssensor-flink-jobmanager + environment: + - JOB_MANAGER_RPC_ADDRESS=crosssensor-flink-jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=sensors + - OUT_TOPIC=sensors_anomalies_modal + volumes: + - ./services/Cross-Sensor System-Level Anomalies/conf/flink-conf.yaml:/opt/flink/conf/flink-conf.yaml + - ./services/Cross-Sensor System-Level Anomalies/flink_job.py:/opt/app/flink_job.py + - ./services/Cross-Sensor System-Level Anomalies/models:/opt/models + networks: + - ag_cloud + restart: unless-stopped + + edge-sensors: + build: + context: ./mqtt_and_kafka/Sensor_edge_device + dockerfile: Dockerfile.edge + container_name: edge-sensors + depends_on: + mosquitto: + condition: service_healthy + mqtt-router: + condition: service_healthy + environment: + - BROKER=mosquitto + - PORT=1883 + - TOPIC=sensors + networks: + - ag_cloud + restart: unless-stopped diff --git a/grafana/dashboards/dashboard-fruit.json b/grafana/dashboards/dashboard-fruit.json new file mode 100644 index 000000000..74a5eb859 --- /dev/null +++ b/grafana/dashboards/dashboard-fruit.json @@ -0,0 +1,161 @@ +{ + "uid": "fruit-metric", + "title": "Fruit Disease Monitoring — Pro Edition", + "timezone": "browser", + "schemaVersion": 36, + "version": 1, + "refresh": "10s", + + "panels": [ + + { + "type": "stat", + "title": "Total Disease Alerts — Since System Start", + "description": "Total number of fruit disease alerts generated since the monitoring system was activated.", + "id": 1, + "datasource": "Prometheus", + "targets": [ + { "expr": "fruit_alerts_total" } + ], + "options": { + "colorMode": "value", + "textMode": "value", + "reduceOptions": { "calcs": ["lastNotNull"] } + }, + "gridPos": { "x": 0, "y": 0, "w": 6, "h": 4 } + }, + + { + "type": "stat", + "title": "Active Disease Events — Real Time", + "description": "Number of live disease alerts currently active in the orchard.", + "id": 2, + "datasource": "Prometheus", + "targets": [ + { "expr": "fruit_alerts_active" } + ], + "options": { + "colorMode": "value", + "textMode": "value" + }, + "gridPos": { "x": 6, "y": 0, "w": 6, "h": 4 } + }, + + { + "type": "stat", + "title": "New Cases (Last 24h)", + "description": "How many new disease alerts appeared during the last 24 hours.", + "id": 3, + "datasource": "Prometheus", + "targets": [ + { "expr": "increase(fruit_alerts_total[24h])" } + ], + "options": { + "colorMode": "value", + "textMode": "value" + }, + "gridPos": { "x": 12, "y": 0, "w": 6, "h": 4 } + }, + + { + "type": "stat", + "title": "Critical Cases (Severity 4)", + "description": "Current number of high-severity alerts that require immediate attention.", + "id": 4, + "datasource": "Prometheus", + "targets": [ + { "expr": "fruit_alerts_by_severity{severity=\"4\"}" } + ], + "options": { + "colorMode": "value", + "textMode": "value" + }, + "gridPos": { "x": 18, "y": 0, "w": 6, "h": 4 } + }, + + { + "type": "timeseries", + "title": "Hourly Alert Growth — How Fast Are New Cases Appearing?", + "description": "Tracks the hour-over-hour increase in disease alerts. A spike indicates rapid disease spread.", + "id": 5, + "datasource": "Prometheus", + "targets": [ + { + "expr": "increase(fruit_alerts_total[1h])", + "legendFormat": "New Alerts Per Hour" + } + ], + "fieldConfig": { + "defaults": { + "color": { "mode": "palette-classic" }, + "custom": { "lineWidth": 2 } + } + }, + "options": { + "legend": { "displayMode": "list", "placement": "bottom" }, + "tooltip": { "mode": "single" } + }, + "gridPos": { "x": 0, "y": 4, "w": 12, "h": 8 } + }, + + { + "type": "timeseries", + "title": "Weekly Trend — This Week vs Last Week", + "description": "Clear comparison of disease alerts between this week and the same period last week. Helps identify worsening or improving field conditions.", + "id": 6, + "datasource": "Prometheus", + "targets": [ + { + "expr": "fruit_alerts_total", + "legendFormat": "This Week — Total Alerts" + }, + { + "expr": "fruit_alerts_total offset 7d", + "legendFormat": "Last Week — Total Alerts" + } + ], + "fieldConfig": { + "defaults": { + "color": { "mode": "palette-classic" }, + "custom": { "lineWidth": 3 } + } + }, + "options": { + "legend": { + "displayMode": "list", + "placement": "bottom" + }, + "tooltip": { + "mode": "single", + "sort": "none" + } + }, + "gridPos": { "x": 12, "y": 4, "w": 12, "h": 8 } + }, + + { + "type": "piechart", + "title": "Disease Severity Breakdown", + "description": "Distribution of disease alerts by severity level. Shows the current risk profile of the orchard.", + "id": 7, + "datasource": "Prometheus", + "targets": [ + { "expr": "fruit_alerts_by_severity" } + ], + "gridPos": { "x": 0, "y": 12, "w": 12, "h": 10 } + }, + + { + "type": "barchart", + "title": "Alerts Per Camera — Identifying Hot Zones", + "description": "Which camera detects the most disease activity? 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"values": false } + } + }, + { + "type": "timeseries", + "title": "🚨 Inference Error Rate (%)", + "targets": [ + { + "expr": "100 * sum(rate(inference_errors_total{service=~\"$service\"}[5m])) by (service) / sum(rate(inference_requests_total{service=~\"$service\"}[5m])) by (service)", + "legendFormat": "{{service}}" + } + ], + "gridPos": { "x": 12, "y": 7, "w": 12, "h": 6 }, + "fieldConfig": { + "defaults": { + "unit": "percent", + "color": { "mode": "continuous-GrYlRd" }, + "thresholds": { + "mode": "absolute", + "steps": [ + { "color": "green", "value": null }, + { "color": "orange", "value": 1 }, + { "color": "red", "value": 5 } + ] + } + } + }, + "options": { + "legend": { "displayMode": "list", "placement": "bottom" }, + "tooltip": { "mode": "multi" } + } + }, + { + "type": "timeseries", + "title": "⏱ Inference Latency (p50 & p90)", + "targets": [ + { + "expr": "histogram_quantile(0.5, sum(rate(inference_latency_seconds_bucket{service=~\"$service\"}[5m])) by (le, service))", + 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b/grafana/dashboards/sound_dashboard.json index c3aaa958d..3f78e3ac8 100644 --- a/grafana/dashboards/sound_dashboard.json +++ b/grafana/dashboards/sound_dashboard.json @@ -1,107 +1,62 @@ { "id": null, - "uid": "sound-dashboard", - "title": "Sound 1 – Grafana Dashboards", - "tags": [ - "sound", - "metrics", - "demo" - ], + "uid": "sound-combined", + "title": "Sound – Combined (Real MinIO Metrics)", + "tags": ["sound", "minio", "exporter"], "timezone": "browser", "schemaVersion": 38, "version": 1, - "refresh": "5s", - "panels": [ - { - "type": "timeseries", - "title": "🎚 Volume Trends (dB)", - "targets": [ - { - "expr": "sound_volume_db", - "legendFormat": "Mic Volume" - } - ], - "gridPos": { - "x": 0, - "y": 0, - "w": 12, - "h": 7 - } - }, - { - "type": "gauge", - "title": "🎯 Classifier Accuracy Rate", - "targets": [ - { - "expr": "classifier_rate" - } - ], - "fieldConfig": { - "defaults": { - "min": 0, - "max": 1, - "unit": "percentunit", - "thresholds": { - "mode": "absolute", - "steps": [ - { - "color": "red", - "value": null - }, - { - "color": "yellow", - "value": 0.7 - }, - { - "color": "green", - "value": 0.9 - } - ] - } - } - }, - "gridPos": { - "x": 12, - "y": 0, - "w": 12, - "h": 7 - } - }, + "refresh": "10s", + "templating": { + "list": [ { - "type": "stat", - "title": "⏱ Microphone Uptime (seconds)", - "targets": [ - { - "expr": "mic_uptime_seconds" - } - ], - "gridPos": { - "x": 0, - "y": 7, - "w": 12, - "h": 6 - }, - "fieldConfig": { - "defaults": { - "unit": "s" - } - } - }, - { - "type": "timeseries", - "title": "⚠️ Anomaly Counters", - "targets": [ - { - "expr": "anomaly_count", - "legendFormat": "Anomalies" - } - ], - "gridPos": { - "x": 12, - "y": 7, - "w": 12, - "h": 6 - } + "name": "mic_id", + "type": "query", + "datasource": "Prometheus", + "query": "label_values(sound_avg_volume, mic_id)", + "includeAll": true, + "multi": true, + "refresh": 1, + "current": {} } + ] + }, + "panels": [ + { + "type": "timeseries", + "title": "Average RMS (5m window)", + "targets": [{ "expr": "sound_avg_volume{mic_id=~\"$mic_id\"}" , "legendFormat": "{{mic_id}}" }], + "options": { "noDataOptions": { "noValue": "hide" } }, + "gridPos": { "x": 0, "y": 0, "w": 12, "h": 7 } + }, + { + "type": "timeseries", + "title": "STD of RMS (5m window)", + "targets": [{ "expr": "sound_std_volume{mic_id=~\"$mic_id\"}", "legendFormat": "{{mic_id}}" }], + "options": { "noDataOptions": { "noValue": "hide" } }, + "gridPos": { "x": 12, "y": 0, "w": 12, "h": 7 } + }, + { + "type": "timeseries", + "title": "Uptime Ratio (0..1)", + "targets": [{ "expr": "sound_mic_uptime_ratio{mic_id=~\"$mic_id\"}", "legendFormat": "{{mic_id}}" }], + "options": { "noDataOptions": { "noValue": "hide" } }, + "gridPos": { "x": 0, "y": 7, "w": 12, "h": 7 } + }, + { + "type": "timeseries", + "title": "Uptime (seconds, derived)", + "targets": [{ "expr": "mic_uptime_seconds{mic_id=~\"$mic_id\"}", "legendFormat": "{{mic_id}}" }], + "options": { "noDataOptions": { "noValue": "hide" } }, + "gridPos": { "x": 12, "y": 7, "w": 12, "h": 7 } + }, + { + "type": "timeseries", + "title": "Volume (dB, derived from RMS)", + "targets": [{ "expr": "sound_volume_db{mic_id=~\"$mic_id\"}", "legendFormat": "{{mic_id}}" }], + "options": { "noDataOptions": { "noValue": "hide" } }, + "gridPos": { "x": 0, "y": 14, "w": 24, "h": 7 } + } ] -} \ No newline at end of file + } + \ No newline at end of file diff --git a/grafana/provisioning/datasources/prometheus.yaml b/grafana/provisioning/datasources/prometheus.yaml index 168dd4594..c6229c97c 100644 --- a/grafana/provisioning/datasources/prometheus.yaml +++ b/grafana/provisioning/datasources/prometheus.yaml @@ -1,6 +1,7 @@ apiVersion: 1 datasources: - name: Prometheus + uid: prometheus type: prometheus access: proxy isDefault: true diff --git a/mqtt_and_kafka/Batch_reprocessing/daily_aggregator.py b/mqtt_and_kafka/Batch_reprocessing/daily_aggregator.py index b482705a8..ac91b5bbf 100644 --- a/mqtt_and_kafka/Batch_reprocessing/daily_aggregator.py +++ b/mqtt_and_kafka/Batch_reprocessing/daily_aggregator.py @@ -227,95 +227,3 @@ def read_5min_rows_between(cutoff_start_dt, cutoff_end_dt): finally: consumer.close() print("Consumer closed.") - - -# import csv -# import json -# from datetime import datetime, timedelta -# from confluent_kafka import Consumer - -# # Kafka consumer configuration -# conf = { -# 'bootstrap.servers': 'kafka:9092', -# 'group.id': 'daily-aggregator', -# 'auto.offset.reset': 'earliest' -# } - -# consumer = Consumer(conf) -# consumer.subscribe(['summaries.5m']) - -# # CSV file paths -# csv_5min = 'aggregated_5min.csv' -# csv_daily = 'aggregated_daily.csv' - -# # Window settings -# window_5min_start = datetime.utcnow() -# window_daily_start = datetime.utcnow() -# results_5min = [] - -# print("📥 Listening for messages... (CTRL+C to stop)") - -# try: -# while True: -# msg = consumer.poll(5.0) -# if msg is None: -# continue -# if msg.error(): -# print("Error:", msg.error()) -# continue - -# # Decode message -# data = json.loads(msg.value().decode('utf-8')) - -# # Append raw metrics to results list -# results_5min.append(data) - -# now = datetime.utcnow() - -# # Write to 5-min CSV if 5 minutes passed -# if now - window_5min_start >= timedelta(minutes=5): -# if results_5min: -# avg_volume = sum(r['metrics']['avg_volume_db'] for r in results_5min) / len(results_5min) -# max_volume = max(r['metrics']['max_volume_db'] for r in results_5min) -# total_anomalies = sum(r['metrics']['anomaly_count'] for r in results_5min) - -# result = { -# "mic_id": ", ".join(set(r["mic_id"] for r in results_5min)), -# "window_start": window_5min_start.isoformat(), -# "window_end": now.isoformat(), -# "avg_volume_db": round(avg_volume, 2), -# "max_volume_db": max_volume, -# "anomaly_count": total_anomalies -# } - -# # Write to CSV -# with open(csv_5min, mode='a', newline='') as f: -# writer = csv.DictWriter(f, fieldnames=result.keys()) -# if f.tell() == 0: -# writer.writeheader() -# writer.writerow(result) - -# print("5-min summary written:", result) - -# results_5min = [] -# window_5min_start = now - -# # Write daily summary every 15 minutes (testing) -# if now - window_daily_start >= timedelta(minutes=15): -# # פה אפשר להכניס חישוב יומי אמיתי, לדוגמה ממוצע כל מה שנאסף -# daily_summary = result # בדוגמה הזאת, פשוט חוזר על התוצאה האחרונה -# with open(csv_daily, mode='a', newline='') as f: -# writer = csv.DictWriter(f, fieldnames=daily_summary.keys()) -# if f.tell() == 0: -# writer.writeheader() -# writer.writerow(daily_summary) - -# print("Daily summary written:", daily_summary) -# window_daily_start = now - -# except KeyboardInterrupt: -# print("Stopping consumer...") - -# finally: -# consumer.close() -# print("Consumer closed.") diff --git a/mqtt_and_kafka/Sensor_edge_device/Crop_recommendationV2.csv 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/dev/null +++ b/mqtt_and_kafka/Sensor_edge_device/Dockerfile.edge @@ -0,0 +1,28 @@ +# ---------- Base image ---------- +FROM python:3.11-slim + +# ---------- Work directory ---------- +WORKDIR /app +COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt + + +RUN chmod 644 /usr/local/share/ca-certificates/netfree-ca.crt && update-ca-certificates + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PIP_CERT=/etc/ssl/certs/ca-certificates.crt \ + PIP_DISABLE_PIP_VERSION_CHECK=1 \ + PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 + +# ---------- Install dependencies ---------- +RUN pip install --no-cache-dir \ + --trusted-host pypi.org \ + --trusted-host files.pythonhosted.org \ + paho-mqtt pandas + +# ---------- Copy simulation scripts ---------- +COPY ./run_sim.py ./fill_system_with_fake_data.py ./Crop_recommendationV2.csv ./place.csv ./ + +# ---------- Default command ---------- +CMD ["python", "run_sim.py"] diff --git a/mqtt_and_kafka/Sensor_edge_device/fill_system_with_fake_data.py b/mqtt_and_kafka/Sensor_edge_device/fill_system_with_fake_data.py new file mode 100644 index 000000000..4237bfc9f --- /dev/null +++ b/mqtt_and_kafka/Sensor_edge_device/fill_system_with_fake_data.py @@ -0,0 +1,55 @@ +import pandas as pd +import random +from datetime import datetime, timezone + +def generate_sensor_data(): + df = pd.read_csv("Crop_recommendationV2.csv") + dfs = pd.read_csv("place.csv") + + row = df.sample(1).iloc[0] + place_row = dfs.sample(1).iloc[0] + + sensor_id = int(place_row["id"]) + plant_id = int(place_row["plant_id"]) + sensor = str(place_row["sensor_type"]) + value = float(place_row["value"]) + lat = float(place_row["lat"]) + lon = float(place_row["lon"]) + + data = { + "sid": f"sensor-{sensor_id}", + "sensor_id": sensor_id, + "timestamp": datetime.now(timezone.utc).isoformat(), + "msg_type": "telemetry", + "value": value, + "plant_id": plant_id, + "sensor_name": sensor, + "n": float(row["N"]), + "p": float(row["P"]), + "k": float(row["K"]), + "temperature": float(row["temperature"]), + "humidity": float(row["humidity"]), + "ph": float(row["ph"]), + "rainfall": float(row["rainfall"]), + "label": str(row["label"]), + "soil_moisture": float(row["soil_moisture"]), + "soil_type": int(row["soil_type"]), + "sunlight_exposure": float(row["sunlight_exposure"]), + "wind_speed": float(row["wind_speed"]), + "co2_concentration": float(row["co2_concentration"]), + "organic_matter": float(row["organic_matter"]), + "irrigation_frequency": float(row["irrigation_frequency"]), + "crop_density": float(row["crop_density"]), + "pest_pressure": float(row["pest_pressure"]), + "fertilizer_usage": float(row["fertilizer_usage"]), + "growth_stage": int(row["growth_stage"]), + "urban_area_proximity": float(row["urban_area_proximity"]), + "water_source_type": int(row["water_source_type"]), + "frost_risk": float(row["frost_risk"]), + "water_usage_efficiency": float(row["water_usage_efficiency"]), + "lat": lat, + "lon": lon, + "sensor_type": sensor + } + + return data diff --git a/mqtt_and_kafka/Sensor_edge_device/place.csv b/mqtt_and_kafka/Sensor_edge_device/place.csv new file mode 100644 index 000000000..8ea9d97a7 --- /dev/null +++ b/mqtt_and_kafka/Sensor_edge_device/place.csv @@ -0,0 +1,47 @@ +lat,lon,value,plant_id,id,sensor_type +32.045,34.835,12.3,1,1,Soil_Moisture +32.045,34.835,28.7,1,1,Soil_Moisture +32.045,34.835,62.4,1,1,Soil_Moisture +32.067,34.812,15.1,2,2,Ambient_Temperature +32.067,34.812,23.4,2,2,Ambient_Temperature +32.067,34.812,45.8,2,2,Ambient_Temperature +32.081,34.875,33.0,3,3,Humidity +32.081,34.875,56.7,3,3,Humidity +32.081,34.875,95.3,3,3,Humidity +32.052,34.885,10.8,4,4,Soil_Moisture +32.052,34.885,26.9,4,4,Soil_Moisture +32.052,34.885,75.1,4,4,Soil_Moisture +32.099,34.880,16.2,5,5,Ambient_Temperature +32.099,34.880,25.5,5,5,Ambient_Temperature +32.099,34.880,49.0,5,5,Ambient_Temperature +32.082,34.790,27.8,6,6,Humidity +32.082,34.790,58.9,6,6,Humidity +32.082,34.790,99.9,6,6,Humidity +32.020,34.760,11.7,7,7,Soil_Moisture +32.020,34.760,30.5,7,7,Soil_Moisture +32.020,34.760,65.2,7,7,Soil_Moisture +31.992,34.935,14.0,8,8,Ambient_Temperature +31.992,34.935,24.8,8,8,Ambient_Temperature +31.992,34.935,47.9,8,8,Ambient_Temperature +31.975,34.965,29.3,9,9,Humidity +31.975,34.965,53.5,9,9,Humidity +31.975,34.965,92.6,9,9,Humidity +31.980,34.910,9.5,10,10,Soil_Moisture +31.980,34.910,25.4,10,10,Soil_Moisture +31.980,34.910,71.2,10,10,Soil_Moisture +31.995,34.985,17.8,11,11,Ambient_Temperature +31.995,34.985,27.6,11,11,Ambient_Temperature +31.995,34.985,55.3,11,11,Ambient_Temperature +32.000,35.000,20.1,12,12,Humidity +32.000,35.000,59.4,12,12,Humidity +32.000,35.000,97.8,12,12,Humidity +32.040,34.915,13.9,13,13,Soil_Moisture +32.040,34.915,29.2,13,13,Soil_Moisture +32.040,34.915,78.5,13,13,Soil_Moisture +31.960,34.950,15.4,14,14,Ambient_Temperature +31.960,34.950,26.8,14,14,Ambient_Temperature +31.960,34.950,51.7,14,14,Ambient_Temperature +31.985,34.925,22.5,15,15,Humidity +31.985,34.925,55.9,15,15,Humidity +31.985,34.925,90.1,15,15,Humidity + diff --git a/mqtt_and_kafka/Sensor_edge_device/run_sim.py b/mqtt_and_kafka/Sensor_edge_device/run_sim.py new file mode 100644 index 000000000..74e4bb8b7 --- /dev/null +++ b/mqtt_and_kafka/Sensor_edge_device/run_sim.py @@ -0,0 +1,25 @@ +# run_sim.py +import time +import json +import paho.mqtt.client as mqtt +from fill_system_with_fake_data import generate_sensor_data + +BROKER = "mosquitto" +PORT = 1883 +TOPIC = "mqtt/sensors" + +def main(): + print("🚀 Simulation started... publishing sensor data to MQTT") + client = mqtt.Client() + client.connect(BROKER, PORT, 60) + + print("🚀 Simulation started... publishing sensor data to MQTT") + + while True: + data = generate_sensor_data() + payload = json.dumps(data) + client.publish(TOPIC, payload) + print(f"📤 Published to {TOPIC}: {payload}") + time.sleep(20) +if __name__ == "__main__": + main() diff --git a/mqtt_and_kafka/kafka/kafka-files/create-topics.sh b/mqtt_and_kafka/kafka/kafka-files/create-topics.sh index 5a5107bde..8b82a0999 100644 --- a/mqtt_and_kafka/kafka/kafka-files/create-topics.sh +++ b/mqtt_and_kafka/kafka/kafka-files/create-topics.sh @@ -72,7 +72,13 @@ TOPICS=( sound_new_sounds_connections inference.dispatched.sounds + inference.dispatched.camera + inference.dispatched.fruit dlq.inference.http + event_logs_sensors + sensors + sensors_anomalies_modal + aerial_images_keys ) # Idempotent creation with retention.ms diff --git a/mqtt_and_kafka/mqtt-router/Dockerfile b/mqtt_and_kafka/mqtt-router/Dockerfile index 5f0779ad7..55297f563 100644 --- a/mqtt_and_kafka/mqtt-router/Dockerfile +++ b/mqtt_and_kafka/mqtt-router/Dockerfile @@ -1,39 +1,39 @@ -FROM python:3.12-slim - -# ---- Build-time toggle for NetFree CA injection ---- -ARG USE_NETFREE=false - -# ---- System deps (CA, curl). librdkafka1 helps if confluent-kafka wheel is not fully static on your base ---- -RUN apt-get update && apt-get install -y --no-install-recommends \ - ca-certificates curl librdkafka1 \ - && rm -rf /var/lib/apt/lists/* - -WORKDIR /app - -# ---- Optional NetFree certificates (mount or COPY your certs/*.crt alongside the Dockerfile) ---- -# If you keep certs in repo, uncomment the next line: -# COPY certs/*.crt /app/certs/ -RUN if [ "$USE_NETFREE" = "true" ] && [ -d /app/certs ] && ls /app/certs/*.crt >/dev/null 2>&1; then \ - echo "Configuring NetFree certificates..."; \ - cp /app/certs/*.crt /usr/local/share/ca-certificates/ && update-ca-certificates; \ - else \ - echo "No NetFree certs applied (USE_NETFREE=$USE_NETFREE)."; \ - fi - -# ---- Make requests/libs use system CA (works both with and without NetFree) ---- -ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ - REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ - PIP_CERT=/etc/ssl/certs/ca-certificates.crt \ - PYTHONUNBUFFERED=1 - -# ---- Install Python deps ---- -COPY requirements.txt . -# When behind NetFree, trusted-host can help even אם אין צורך זה לא מזיק: -RUN python -m pip install --no-cache-dir \ - --trusted-host pypi.org --trusted-host files.pythonhosted.org \ - -r requirements.txt - -# ---- App code ---- -COPY app.py . - -ENTRYPOINT ["python", "app.py"] +FROM python:3.12-slim + +# ---- Build-time toggle for NetFree CA injection ---- +ARG USE_NETFREE=false + +# ---- System deps (CA, curl). librdkafka1 helps if confluent-kafka wheel is not fully static on your base ---- +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates curl librdkafka1 \ + && rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +# ---- Optional NetFree certificates (mount or COPY your certs/*.crt alongside the Dockerfile) ---- +# If you keep certs in repo, uncomment the next line: +# COPY certs/*.crt /app/certs/ +RUN if [ "$USE_NETFREE" = "true" ] && [ -d /app/certs ] && ls /app/certs/*.crt >/dev/null 2>&1; then \ + echo "Configuring NetFree certificates..."; \ + cp /app/certs/*.crt /usr/local/share/ca-certificates/ && update-ca-certificates; \ + else \ + echo "No NetFree certs applied (USE_NETFREE=$USE_NETFREE)."; \ + fi + +# ---- Make requests/libs use system CA (works both with and without NetFree) ---- +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PIP_CERT=/etc/ssl/certs/ca-certificates.crt \ + PYTHONUNBUFFERED=1 + +# ---- Install Python deps ---- +COPY requirements.txt . +# When behind NetFree, trusted-host can help even +RUN python -m pip install --no-cache-dir \ + --trusted-host pypi.org --trusted-host files.pythonhosted.org \ + -r requirements.txt + +# ---- App code ---- +COPY app.py . + +ENTRYPOINT ["python", "app.py"] diff --git a/mqtt_and_kafka/mqtt-router/app.py b/mqtt_and_kafka/mqtt-router/app.py index ac32bef86..3383671aa 100644 --- a/mqtt_and_kafka/mqtt-router/app.py +++ b/mqtt_and_kafka/mqtt-router/app.py @@ -1,154 +1,154 @@ -import os -import re -import signal -import sys -from typing import Optional - -import paho.mqtt.client as mqtt -from confluent_kafka import Producer, KafkaException, KafkaError -from confluent_kafka.admin import AdminClient, NewTopic - -# ---------- Env ---------- -MQTT_HOST = os.getenv("MQTT_HOST", "mosquitto") -MQTT_PORT = int(os.getenv("MQTT_PORT", "1883")) -MQTT_USERNAME = os.getenv("MQTT_USERNAME", "") -MQTT_PASSWORD = os.getenv("MQTT_PASSWORD", "") -MQTT_TOPIC_FILTER = os.getenv("MQTT_TOPIC_FILTER", "mqtt/#") - -KAFKA_BOOTSTRAP = os.getenv("KAFKA_BOOTSTRAP", "kafka:9092") -KAFKA_CLIENT_ID = os.getenv("KAFKA_CLIENT_ID", "mqtt-router") -CREATE_TOPICS = os.getenv("CREATE_TOPICS", "false").lower() == "true" -DEFAULT_PARTITIONS = int(os.getenv("DEFAULT_PARTITIONS", "1")) -DEFAULT_REPLICATION = int(os.getenv("DEFAULT_REPLICATION", "1")) - -# Optional security (set via env if needed) -KAFKA_SECURITY_PROTOCOL = os.getenv("KAFKA_SECURITY_PROTOCOL", "") # e.g. "SASL_PLAINTEXT", "SASL_SSL", "SSL" -KAFKA_SASL_MECHANISM = os.getenv("KAFKA_SASL_MECHANISM", "") # e.g. "PLAIN" -KAFKA_SASL_USERNAME = os.getenv("KAFKA_SASL_USERNAME", "") -KAFKA_SASL_PASSWORD = os.getenv("KAFKA_SASL_PASSWORD", "") - -# ---------- Topic mapping ---------- -# Allow arbitrary depth after "mqtt/" → replace "/" with "." -VALID_CHARS = re.compile(r'[^A-Za-z0-9._-]') - -def map_mqtt_to_kafka_topic(mqtt_topic: str) -> Optional[str]: - prefix = "mqtt/" - if not mqtt_topic.startswith(prefix): - return None - tail = mqtt_topic[len(prefix):].strip("/") - if not tail: - return None - parts = [seg for seg in tail.split("/") if seg] - dotted = "_".join(parts) - dotted = VALID_CHARS.sub("_", dotted) - return dotted[:249] if dotted else None - -# ---------- Kafka clients ---------- -producer_conf = { - "bootstrap.servers": KAFKA_BOOTSTRAP, - "client.id": KAFKA_CLIENT_ID, - - # Strong delivery semantics - "acks": "all", - "enable.idempotence": True, - - # Throughput tuning - "compression.type": os.getenv("KAFKA_COMPRESSION", "lz4"), - "linger.ms": int(os.getenv("KAFKA_LINGER_MS", "5")), - "batch.size": int(os.getenv("KAFKA_BATCH_SIZE", str(64 * 1024))), # bytes - - # Resilience - "socket.keepalive.enable": True, - "delivery.timeout.ms": int(os.getenv("KAFKA_DELIVERY_TIMEOUT_MS", "120000")), - "request.timeout.ms": int(os.getenv("KAFKA_REQUEST_TIMEOUT_MS", "30000")), -} - -# Optional security -if KAFKA_SECURITY_PROTOCOL: - producer_conf["security.protocol"] = KAFKA_SECURITY_PROTOCOL -if KAFKA_SASL_MECHANISM: - producer_conf["sasl.mechanism"] = KAFKA_SASL_MECHANISM -if KAFKA_SASL_USERNAME: - producer_conf["sasl.username"] = KAFKA_SASL_USERNAME -if KAFKA_SASL_PASSWORD: - producer_conf["sasl.password"] = KAFKA_SASL_PASSWORD - -p = Producer(producer_conf) -admin = AdminClient({"bootstrap.servers": KAFKA_BOOTSTRAP}) # kept for CREATE_TOPICS toggle - -def ensure_topic(topic: str): - if not CREATE_TOPICS: - return - try: - fs = admin.create_topics([NewTopic(topic, num_partitions=DEFAULT_PARTITIONS, - replication_factor=DEFAULT_REPLICATION)]) - fs[topic].result() - print(f"[router] Created topic: {topic}", flush=True) - except Exception as e: - msg = str(e) - if "exists" in msg.lower() or "TopicExistsError" in msg or "TOPIC_ALREADY_EXISTS" in msg: - return - print(f"[router] create_topics warning for {topic}: {e}", flush=True) - -def delivery_report(err, msg): - if err is not None: - print(f"[router] Delivery failed for {msg.topic()}: {err}", flush=True) - else: - print(f"[router] Delivered to {msg.topic()} [partition {msg.partition()} offset {msg.offset()}]", flush=True) - -# ---------- MQTT callbacks ---------- -def on_connect(client, userdata, flags, rc, properties=None): - if rc == 0: - print(f"[router] Connected MQTT {MQTT_HOST}:{MQTT_PORT}, subscribe: {MQTT_TOPIC_FILTER}", flush=True) - client.subscribe(MQTT_TOPIC_FILTER, qos=0) - else: - print(f"[router] MQTT connect failed: rc={rc}", flush=True) - -def on_message(client, userdata, msg): - src = msg.topic - dst = map_mqtt_to_kafka_topic(src) - if not dst: - print(f"[router] Skipping topic (no match): {src}", flush=True) - return - try: - ensure_topic(dst) - p.produce(dst, value=msg.payload, on_delivery=delivery_report) - # Poll to serve delivery callbacks; small 0 keeps loop snappy - p.poll(0) - except KafkaException as e: - # Helpful message when topics are not pre-created - kafka_err = e.args[0] if e.args else None - if isinstance(kafka_err, KafkaError) and kafka_err.code() == KafkaError.UNKNOWN_TOPIC_OR_PART: - print(f"[router] ERROR UnknownTopicOrPartition for '{dst}'. " - f"CREATE_TOPICS=false → please pre-create this topic.", flush=True) - else: - print(f"[router] Kafka produce error: {e}", flush=True) - -# ---------- Main ---------- -def main(): - client = mqtt.Client(client_id="mqtt-router", protocol=mqtt.MQTTv5) - if MQTT_USERNAME or MQTT_PASSWORD: - client.username_pw_set(MQTT_USERNAME, MQTT_PASSWORD) - - # Gentle reconnect backoff - client.reconnect_delay_set(min_delay=1, max_delay=30) - - client.on_connect = on_connect - client.on_message = on_message - - def handle_sigterm(signum, frame): - print("[router] SIGTERM received, flushing producer...", flush=True) - p.flush(10) - sys.exit(0) - - signal.signal(signal.SIGTERM, handle_sigterm) - signal.signal(signal.SIGINT, handle_sigterm) - - client.connect(MQTT_HOST, MQTT_PORT, keepalive=30) - print(f"[router] Boot: MQTT={MQTT_HOST}:{MQTT_PORT} Kafka={KAFKA_BOOTSTRAP} " - f"CREATE_TOPICS={CREATE_TOPICS}", flush=True) - client.loop_forever() - -if __name__ == "__main__": - main() - +import os +import re +import signal +import sys +from typing import Optional + +import paho.mqtt.client as mqtt +from confluent_kafka import Producer, KafkaException, KafkaError +from confluent_kafka.admin import AdminClient, NewTopic + +# ---------- Env ---------- +MQTT_HOST = os.getenv("MQTT_HOST", "mosquitto") +MQTT_PORT = int(os.getenv("MQTT_PORT", "1883")) +MQTT_USERNAME = os.getenv("MQTT_USERNAME", "") +MQTT_PASSWORD = os.getenv("MQTT_PASSWORD", "") +MQTT_TOPIC_FILTER = os.getenv("MQTT_TOPIC_FILTER", "mqtt/#") + +KAFKA_BOOTSTRAP = os.getenv("KAFKA_BOOTSTRAP", "kafka:9092") +KAFKA_CLIENT_ID = os.getenv("KAFKA_CLIENT_ID", "mqtt-router") +CREATE_TOPICS = os.getenv("CREATE_TOPICS", "false").lower() == "true" +DEFAULT_PARTITIONS = int(os.getenv("DEFAULT_PARTITIONS", "1")) +DEFAULT_REPLICATION = int(os.getenv("DEFAULT_REPLICATION", "1")) + +# Optional security (set via env if needed) +KAFKA_SECURITY_PROTOCOL = os.getenv("KAFKA_SECURITY_PROTOCOL", "") # e.g. "SASL_PLAINTEXT", "SASL_SSL", "SSL" +KAFKA_SASL_MECHANISM = os.getenv("KAFKA_SASL_MECHANISM", "") # e.g. "PLAIN" +KAFKA_SASL_USERNAME = os.getenv("KAFKA_SASL_USERNAME", "") +KAFKA_SASL_PASSWORD = os.getenv("KAFKA_SASL_PASSWORD", "") + +# ---------- Topic mapping ---------- +# Allow arbitrary depth after "mqtt/" → replace "/" with "." +VALID_CHARS = re.compile(r'[^A-Za-z0-9._-]') + +def map_mqtt_to_kafka_topic(mqtt_topic: str) -> Optional[str]: + prefix = "mqtt/" + if not mqtt_topic.startswith(prefix): + return None + tail = mqtt_topic[len(prefix):].strip("/") + if not tail: + return None + parts = [seg for seg in tail.split("/") if seg] + dotted = "_".join(parts) + dotted = VALID_CHARS.sub("_", dotted) + return dotted[:249] if dotted else None + +# ---------- Kafka clients ---------- +producer_conf = { + "bootstrap.servers": KAFKA_BOOTSTRAP, + "client.id": KAFKA_CLIENT_ID, + + # Strong delivery semantics + "acks": "all", + "enable.idempotence": True, + + # Throughput tuning + "compression.type": os.getenv("KAFKA_COMPRESSION", "lz4"), + "linger.ms": int(os.getenv("KAFKA_LINGER_MS", "5")), + "batch.size": int(os.getenv("KAFKA_BATCH_SIZE", str(64 * 1024))), # bytes + + # Resilience + "socket.keepalive.enable": True, + "delivery.timeout.ms": int(os.getenv("KAFKA_DELIVERY_TIMEOUT_MS", "120000")), + "request.timeout.ms": int(os.getenv("KAFKA_REQUEST_TIMEOUT_MS", "30000")), +} + +# Optional security +if KAFKA_SECURITY_PROTOCOL: + producer_conf["security.protocol"] = KAFKA_SECURITY_PROTOCOL +if KAFKA_SASL_MECHANISM: + producer_conf["sasl.mechanism"] = KAFKA_SASL_MECHANISM +if KAFKA_SASL_USERNAME: + producer_conf["sasl.username"] = KAFKA_SASL_USERNAME +if KAFKA_SASL_PASSWORD: + producer_conf["sasl.password"] = KAFKA_SASL_PASSWORD + +p = Producer(producer_conf) +admin = AdminClient({"bootstrap.servers": KAFKA_BOOTSTRAP}) # kept for CREATE_TOPICS toggle + +def ensure_topic(topic: str): + if not CREATE_TOPICS: + return + try: + fs = admin.create_topics([NewTopic(topic, num_partitions=DEFAULT_PARTITIONS, + replication_factor=DEFAULT_REPLICATION)]) + fs[topic].result() + print(f"[router] Created topic: {topic}", flush=True) + except Exception as e: + msg = str(e) + if "exists" in msg.lower() or "TopicExistsError" in msg or "TOPIC_ALREADY_EXISTS" in msg: + return + print(f"[router] create_topics warning for {topic}: {e}", flush=True) + +def delivery_report(err, msg): + if err is not None: + print(f"[router] Delivery failed for {msg.topic()}: {err}", flush=True) + else: + print(f"[router] Delivered to {msg.topic()} [partition {msg.partition()} offset {msg.offset()}]", flush=True) + +# ---------- MQTT callbacks ---------- +def on_connect(client, userdata, flags, rc, properties=None): + if rc == 0: + print(f"[router] Connected MQTT {MQTT_HOST}:{MQTT_PORT}, subscribe: {MQTT_TOPIC_FILTER}", flush=True) + client.subscribe(MQTT_TOPIC_FILTER, qos=0) + else: + print(f"[router] MQTT connect failed: rc={rc}", flush=True) + +def on_message(client, userdata, msg): + src = msg.topic + dst = map_mqtt_to_kafka_topic(src) + if not dst: + print(f"[router] Skipping topic (no match): {src}", flush=True) + return + try: + ensure_topic(dst) + p.produce(dst, value=msg.payload, on_delivery=delivery_report) + # Poll to serve delivery callbacks; small 0 keeps loop snappy + p.poll(0) + except KafkaException as e: + # Helpful message when topics are not pre-created + kafka_err = e.args[0] if e.args else None + if isinstance(kafka_err, KafkaError) and kafka_err.code() == KafkaError.UNKNOWN_TOPIC_OR_PART: + print(f"[router] ERROR UnknownTopicOrPartition for '{dst}'. " + f"CREATE_TOPICS=false → please pre-create this topic.", flush=True) + else: + print(f"[router] Kafka produce error: {e}", flush=True) + +# ---------- Main ---------- +def main(): + client = mqtt.Client(client_id="mqtt-router", protocol=mqtt.MQTTv5) + if MQTT_USERNAME or MQTT_PASSWORD: + client.username_pw_set(MQTT_USERNAME, MQTT_PASSWORD) + + # Gentle reconnect backoff + client.reconnect_delay_set(min_delay=1, max_delay=30) + + client.on_connect = on_connect + client.on_message = on_message + + def handle_sigterm(signum, frame): + print("[router] SIGTERM received, flushing producer...", flush=True) + p.flush(10) + sys.exit(0) + + signal.signal(signal.SIGTERM, handle_sigterm) + signal.signal(signal.SIGINT, handle_sigterm) + + client.connect(MQTT_HOST, MQTT_PORT, keepalive=30) + print(f"[router] Boot: MQTT={MQTT_HOST}:{MQTT_PORT} Kafka={KAFKA_BOOTSTRAP} " + f"CREATE_TOPICS={CREATE_TOPICS}", flush=True) + client.loop_forever() + +if __name__ == "__main__": + main() + diff --git a/mqtt_and_kafka/mqtt-router/requirements.txt b/mqtt_and_kafka/mqtt-router/requirements.txt index 40450e3b7..3d853480c 100644 --- a/mqtt_and_kafka/mqtt-router/requirements.txt +++ b/mqtt_and_kafka/mqtt-router/requirements.txt @@ -1,2 +1,2 @@ -paho-mqtt==2.1.0 -confluent-kafka>=2.4 +paho-mqtt==2.1.0 +confluent-kafka>=2.4 diff --git a/prometheus/prometheus.yml b/prometheus/prometheus.yml index 804405bbd..f74fe9d40 100644 --- a/prometheus/prometheus.yml +++ b/prometheus/prometheus.yml @@ -34,12 +34,25 @@ scrape_configs: - job_name: sound_metrics static_configs: - - targets: ['host.docker.internal:8005'] + - targets: ['sound_metrics:8005'] - job_name: 'pushgateway' honor_labels: true static_configs: - targets: ['pushgateway:9091'] + - job_name: 'fruit_metric' + static_configs: + - targets: ['fruit_metrics:8050'] + - job_name: 'security-models' + static_configs: + - targets: + - 'mega-detector:8007' + - 'animal-classifier:8008' + - 'anomalies-classifier:8011' + - 'mask-classifier:8012' + - job_name: "fruit_ripeness" + static_configs: + - targets: ["ripeness-exporter:9128"] diff --git a/pytest.ini b/pytest.ini new file mode 100644 index 000000000..4e7ce1af4 --- /dev/null +++ b/pytest.ini @@ -0,0 +1,17 @@ +; # AgCloud/pytest.ini +; [pytest] +; testpaths = services/rover_ingest/tests +; pythonpath = . +; addopts = -q + + +[pytest] +minversion = 8.0 +addopts = -ra +testpaths = + services/tests + services/mqtt_gateway/tests +pythonpath = + . +norecursedirs = + storage_with_mqtt diff --git a/services/Cross-Sensor System-Level Anomalies/.github/CODEOWNERS b/services/Cross-Sensor System-Level Anomalies/.github/CODEOWNERS new file mode 100644 index 000000000..3371c6fe8 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/.github/CODEOWNERS @@ -0,0 +1 @@ +* @KamaTechOrg @SaraShimon @hadasaGIT @tamarmar diff --git a/services/Cross-Sensor System-Level Anomalies/.gitignore b/services/Cross-Sensor System-Level Anomalies/.gitignore new file mode 100644 index 000000000..80522fd97 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/.gitignore @@ -0,0 +1,47 @@ +# Python +__pycache__/ +*.py[cod] +*.pyo +*.pyd +*.so + +# Virtual envs +.venv/ +env/ +venv/ + +# IDE +.vscode/ +.idea/ + +# Outputs & plots +out/ +*.png +*.svg + +# Data files : +*.csv +*.parquet +*.feather + +# Allow specific data files +!data/ +!data/Crop_recommendationV2.csv + + +private_*.py +local_*.py +scratch_*.ipynb + +# files +analyze_dataset.py +anomalies.py +check_25_consistency.py +diff_anomalies.py +export_anomalies.py + +# Ignore model artifacts +*.pkl +*.joblib +models/*.pkl +models/*.joblib \ No newline at end of file diff --git a/services/Cross-Sensor System-Level Anomalies/Dockerfile.flink b/services/Cross-Sensor System-Level Anomalies/Dockerfile.flink new file mode 100644 index 000000000..f599dbce7 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/Dockerfile.flink @@ -0,0 +1,68 @@ +# Dockerfile.flink +FROM flink:1.19.3-scala_2.12-java11 + +USER root + + + +COPY certs/*.crt /app/certs/ +RUN if [ -d ./certs ] && [ "$(ls ./certs/*.crt 2>/dev/null)" ]; then \ + echo "Configuring NetFree certificates..."; \ + cp ./certs/*.crt /usr/local/share/ca-certificates/; \ + update-ca-certificates; \ + fi +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV PIP_CERT=/etc/ssl/certs/ca-certificates.crt + +RUN apt-get update && apt-get install -y python3 python3-venv python3-pip +RUN curl -fSL https://repo1.maven.org/maven2/org/apache/kafka/kafka-clients/3.7.0/kafka-clients-3.7.0.jar \ + -o /opt/flink/lib/kafka-clients-3.7.0.jar + +RUN python3 -m venv /opt/venv +ENV PATH="/opt/venv/bin:${PATH}" + + +RUN printf "[global]\ntrusted-host = pypi.org\n files.pythonhosted.org\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf +RUN python -m pip install --no-cache-dir --upgrade pip setuptools wheel + +RUN apt-get update && apt-get install -y \ + build-essential \ + gfortran \ + libatlas-base-dev \ + && rm -rf /var/lib/apt/lists/* +RUN apt-get update && apt-get install -y --no-install-recommends \ + netcat-openbsd \ + && rm -rf /var/lib/apt/lists/* + +RUN pip install --no-cache-dir --prefer-binary \ + apache-flink \ + pandas \ + scikit-learn \ + joblib + + + +RUN curl -fSL \ + https://repo1.maven.org/maven2/org/apache/flink/flink-connector-kafka/3.2.0-1.19/flink-connector-kafka-3.2.0-1.19.jar \ + -o /opt/flink/lib/flink-connector-kafka-3.2.0-1.19.jar + +COPY conf/flink-conf.yaml /opt/flink/conf/flink-conf.yaml +WORKDIR /opt/app +COPY flink_job.py /opt/app/flink_job.py +COPY models/iforest_pca_artifacts.joblib /opt/models/iforest_pca_artifacts.joblib +COPY models/residuals_artifacts.joblib /opt/models/residuals_artifacts.joblib + + +ENV ART_IFOREST_PCA=/opt/models/iforest_pca_artifacts.joblib \ + ART_RESIDUALS=/opt/models/residuals_artifacts.joblib \ + KAFKA_BROKERS=kafka-single:9092 \ + IN_TOPIC=sensors \ + OUT_TOPIC=sensors_anomalies_modal \ + PYTHONPATH=/opt/app \ + PYFLINK_CLIENT_EXECUTABLE=/opt/venv/bin/python \ + PYFLINK_PYTHON=/opt/venv/bin/python + +COPY entrypoint.sh /entrypoint.sh +RUN chmod +x /entrypoint.sh +ENTRYPOINT ["/entrypoint.sh"] diff --git a/services/Cross-Sensor System-Level Anomalies/README.md b/services/Cross-Sensor System-Level Anomalies/README.md new file mode 100644 index 000000000..e12181bc4 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/README.md @@ -0,0 +1,137 @@ +# Cross-Sensor System-Level Anomalies + +# Model Artifacts + +This folder stores the model artifacts required for anomaly detection. + +The binary model files (**.pkl** / **.joblib**) are **not stored in the Git repository**, as they are large binary files that should not be tracked by Git. + +Instead, you can download all required model files from Google Drive: + +🔗 **Google Drive folder (all model artifacts):** +https://drive.google.com/drive/folders/1QKRW5jTv3K-NmQLjMjfKqwgVu6JwrZsf?usp=drive_link + +## How to use + +1. Download all four model files from the Drive link. +2. Place them inside this `models/` directory. +3. The application will load them from here during runtime. + +## Notes + +- Do **not** upload model files back into Git. +- To prevent accidental uploads, ensure `.gitignore` includes: + + +## Overview + +Unsupervised anomaly detection for agricultural sensor data using three complementary methods: + +1. Isolation Forest (tree-based outlier model) +2. PCA Reconstruction Error (distance-from-low-rank structure) +3. Residual-per-Feature (OOF) with a robust HuberRegressor + +We combine them into a hybrid decision: + +* UNION (sensitive, higher recall) +* INTERSECTION (strict, higher precision) +* Majority (2-of-3) — good balance for high-confidence alerts. + +Now fully integrated with Apache Flink streaming, consuming sensor JSON data from Kafka topics and producing anomaly alerts in real-time. + +## Project Layout + +docker-compose.yml # Build & run Flink + Kafka + job +flink_job.py # Flink job wrapping IF + PCA + Residual pipeline +detect_iforest_pca.py # Stage 1: IF + PCA + basic plots, intermediate CSV (used in batch mode) +detect_residuals_and_hybrid.py # Stage 2: Residual OOF + Hybrid + 2-of-3 + hybrid plot (used in batch mode) +tests/ # Pytest-based tests (synthetic data fixtures included) +data/Crop_recommendationV2.csv # Dataset (kept in repo) +out/ # Outputs (ignored by git) +Dockerfile # Build & run both stages +requirements.txt # Python dependencies +README.txt # This file + +## Why these models? + +* Isolation Forest: robust to high-dimensional mixed features; detects "few and different." +* PCA Recon Error: catches samples that don't fit global low-rank structure; complementary to IF. +* Residual-per-Feature (OOF): per-target predictive errors using KFold with no data leakage; highlights physically inconsistent sensor relationships (e.g., high soil moisture with very low rainfall). + +## No-Leakage Residuals (critical) + +Residuals are computed Out-Of-Fold: + +* For each fold, we fit imputer + scaler + HuberRegressor on train only, then score the validation split. +* This prevents information leakage and over-optimistic errors. + +## Streaming with Kafka & Flink + +1. Start Kafka with Docker Compose: + + ```bash + docker compose -f docker-compose.yml up -d + ``` + +2. Build and start Flink + job environment: + + ```bash + docker compose up -d + ``` + +3. Open Flink Web UI at [http://localhost:8084/](http://localhost:8084/) to monitor jobs. + +4. Submit the Flink job: + + ```bash + docker compose exec jobmanager flink run -py /opt/app/flink_job.py + ``` + +5. Open two terminals for Kafka: + + * Producer (send JSON sensor data): + + ```bash + docker exec -i kafka kafka-console-producer.sh --bootstrap-server localhost:9092 --topic sensors + ``` + * Consumer (receive anomaly results): + + ```bash + docker exec -it kafka kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic sensors_anomalies_modal --from-beginning + ``` + +6. Example JSON input to producer: + +```json +{"sid": "normal-01", "timestamp": 1690010100, "temperature": 24, "humidity": 55, "rainfall": 12, "soil_moisture": 45} +{"sid": "anomaly-01", "timestamp": 1690010150, "temperature": 100, "humidity": 0, "rainfall": 9999, "soil_moisture": 1000} +``` + +Consumer will output whether the sample is flagged as an anomaly or not. + +## Outputs + +out/dataset_with_iforest_pca.csv # IF + PCA features/flags +out/pca_iforest_anomalies.png # PCA scatter with IF anomalies +out/dataset_hybrid_iforest_pca_residual.csv # Final hybrid CSV with residual scores & flags +out/pca_hybrid_union.png # PCA scatter colored by hybrid union +out/top10_residual_rows.csv # Top-10 by residual_general_score (always created) + +## Interpreting Results + +* 'anomaly_union' is sensitive and best for broad monitoring. +* 'anomaly_2of3' is stricter and good as "high-confidence" alerting. +* Tune sensitivity via: + + * IsolationForest 'contamination' + * PCA reconstruction error quantile + * Residuals quantile (RES_Q) +* Choose thresholds to match your alert budget (~1–3% for 2-of-3 recommended). + +## Notes + +* Plots are saved headless (matplotlib Agg backend). +* The residual targets default to: soil_moisture, rainfall, temperature, humidity. +* top10_residual_rows.csv is always written (even if fewer than 10 rows exist). +* Streaming mode fully supports real-time detection via Flink and Kafka. +* Ensure Kafka is running before starting Flink jobs to avoid connectivity errors. diff --git a/services/Cross-Sensor System-Level Anomalies/check_models.py b/services/Cross-Sensor System-Level Anomalies/check_models.py new file mode 100644 index 000000000..db534a8cf --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/check_models.py @@ -0,0 +1,19 @@ +import joblib + +print("=== iforest_pca_artifacts.joblib ===") +try: + artifact_ifpca = joblib.load("models/iforest_pca_artifacts.joblib") + print("Model version:", artifact_ifpca.get("model_version")) + print("PCA threshold:", artifact_ifpca.get("pca_thr")) + print("Features:", artifact_ifpca.get("feature_cols", [])[:5], "...") +except Exception as e: + print("Error loading iforest_pca_artifacts.joblib:", e) + +print("\n=== residuals_artifacts.joblib ===") +try: + artifact_resid = joblib.load("models/residuals_artifacts.joblib") + print("Model version:", artifact_resid.get("model_version")) + print("Residual threshold:", artifact_resid.get("resid_thr")) + print("Targets:", list(artifact_resid.get("resid_models", {}).keys())) +except Exception as e: + print("Error loading residuals_artifacts.joblib:", e) diff --git a/services/Cross-Sensor System-Level Anomalies/conf/flink-conf.yaml b/services/Cross-Sensor System-Level Anomalies/conf/flink-conf.yaml new file mode 100644 index 000000000..18cf61e32 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/conf/flink-conf.yaml @@ -0,0 +1,15 @@ +blob.server.port: 6124 +taskmanager.memory.process.size: 4096m +taskmanager.bind-host: 0.0.0.0 +jobmanager.execution.failover-strategy: region +python.fn-execution.memory.managed: false +taskmanager.memory.task.off-heap.size: 512m +taskmanager.memory.jvm-metaspace.size: 256m +jobmanager.rpc.address: crosssensor-flink-jobmanager +jobmanager.memory.process.size: 2048m +jobmanager.rpc.port: 6123 +query.server.port: 6125 +jobmanager.bind-host: 0.0.0.0 +taskmanager.memory.framework.off-heap.size: 256m +parallelism.default: 4 +taskmanager.numberOfTaskSlots: 4 diff --git a/services/Cross-Sensor System-Level Anomalies/convert_model.py b/services/Cross-Sensor System-Level Anomalies/convert_model.py new file mode 100644 index 000000000..2cf8e5be4 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/convert_model.py @@ -0,0 +1,28 @@ +import joblib +import sys +from pathlib import Path + +def main(): + if len(sys.argv) < 2: + print("Usage: python convert_model.py ") + sys.exit(1) + + model_path = Path(sys.argv[1]) + if not model_path.exists(): + print(f"❌ File not found: {model_path}") + sys.exit(1) + + + print(f"📥 Loading model from {model_path} ...") + model = joblib.load(model_path) + + + new_path = model_path.with_name(model_path.stem + "_compat.pkl") + + + joblib.dump(model, new_path) + + print(f"✅ Model re-saved successfully as {new_path}") + +if __name__ == "__main__": + main() diff --git a/services/Cross-Sensor System-Level Anomalies/data/Crop_recommendationV2.csv b/services/Cross-Sensor System-Level Anomalies/data/Crop_recommendationV2.csv new file mode 100644 index 000000000..3de7ccc07 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/data/Crop_recommendationV2.csv @@ -0,0 +1,2201 @@ +N,P,K,temperature,humidity,ph,rainfall,label,soil_moisture,soil_type,sunlight_exposure,wind_speed,co2_concentration,organic_matter,irrigation_frequency,crop_density,pest_pressure,fertilizer_usage,growth_stage,urban_area_proximity,water_source_type,frost_risk,water_usage_efficiency 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+104,18,30,23.60301571,60.39647474,6.779832611,140.9370415,coffee,23.911727578408552,3,8.639741540157758,14.481756579084477,413.1237161382283,6.401993710119095,3,14.652123227033409,3.5741911097655232,175.10424061806972,3,26.784996183697135,2,47.27126705890273,2.758819113898633 diff --git a/services/Cross-Sensor System-Level Anomalies/detect_iforest_pca.py b/services/Cross-Sensor System-Level Anomalies/detect_iforest_pca.py new file mode 100644 index 000000000..ff3bd84d5 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/detect_iforest_pca.py @@ -0,0 +1,131 @@ +# detect_iforest_pca.py +from pathlib import Path +import numpy as np +import pandas as pd + +# WSL/Headless-safe plotting +import matplotlib +matplotlib.use("Agg") +import matplotlib.pyplot as plt +from sklearn.compose import ColumnTransformer +from sklearn.preprocessing import RobustScaler, OneHotEncoder +from sklearn.impute import SimpleImputer +from sklearn.pipeline import Pipeline +from sklearn.ensemble import IsolationForest +from sklearn.decomposition import PCA + +# -------------------- Config -------------------- +CSV_PATH = Path("data/Crop_recommendationV2.csv") +OUT_DIR = Path("out"); OUT_DIR.mkdir(exist_ok=True) + +CONTAMINATION = 0.15 # the proportion of anomalies in the data +N_ESTIMATORS = 300 +RANDOM_STATE = 42 + + +EXCLUDE_COLS = {"label","crop","target","index"} + +# -------------------- Load & normalize -------------------- +df = pd.read_csv(CSV_PATH) + +if "id" not in df.columns: + df.insert(0, "id", df.index.astype(str)) + +df.columns = (df.columns + .str.strip().str.lower() + .str.replace(" ", "_") + .str.replace("%", "pct") + .str.replace(r"[^0-9a-zA-Z_]", "", regex=True)) + +candidate_cols = [c for c in df.columns if c not in EXCLUDE_COLS] +num_cols = [c for c in candidate_cols if pd.api.types.is_numeric_dtype(df[c])] +cat_cols = [c for c in candidate_cols + if pd.api.types.is_object_dtype(df[c]) or pd.api.types.is_categorical_dtype(df[c])] + +numeric_pipeline = Pipeline([ + ("impute", SimpleImputer(strategy="median")), + ("scale", RobustScaler()) +]) +categorical_pipeline = Pipeline([ + ("impute", SimpleImputer(strategy="most_frequent")), + ("onehot", OneHotEncoder(handle_unknown="ignore", sparse_output=False)) +]) +pre = ColumnTransformer( + transformers=[ + ("num", numeric_pipeline, num_cols), + ("cat", categorical_pipeline, cat_cols) + ], + remainder="drop" +) + +X = pre.fit_transform(df) + +# -------------------- Isolation Forest -------------------- +iso = IsolationForest( + n_estimators=N_ESTIMATORS, + contamination=CONTAMINATION, + random_state=RANDOM_STATE +) +pred = iso.fit_predict(X) # 1=normal, -1=anomaly +score = -iso.decision_function(X) + +df["anomaly_iforest"] = (pred == -1).astype(int) +df["iforest_score"] = score + +# -------------------- PCA (2D) -------------------- +pca2 = PCA(n_components=2, random_state=RANDOM_STATE) +Z = pca2.fit_transform(X) +df["pca_x"] = Z[:,0]; df["pca_y"] = Z[:,1] + +plt.figure(figsize=(7,6)) +mask = df["anomaly_iforest"].astype(bool) +plt.scatter(df.loc[~mask,"pca_x"], df.loc[~mask,"pca_y"], s=12, alpha=0.25, label="normal") +plt.scatter(df.loc[mask,"pca_x"], df.loc[mask, "pca_y"], s=20, alpha=0.9, marker="x", label="anomaly") +plt.title("PCA (2D) projection with IsolationForest anomalies") +plt.xlabel("PC1"); plt.ylabel("PC2"); plt.legend(); plt.tight_layout() +plt.savefig(OUT_DIR/"pca_iforest_anomalies.png"); plt.close() + +# -------------------- PCA Reconstruction Error -------------------- +pca_full = PCA(n_components=0.90, svd_solver="full", random_state=RANDOM_STATE) +Zf = pca_full.fit_transform(X) +X_recon = pca_full.inverse_transform(Zf) +recon_err = np.mean((X - X_recon)**2, axis=1) + +df["pca_recon_error"] = recon_err +PCA_ERR_Q = 0.85 # top 5% will be anomalies +thr = np.quantile(recon_err, PCA_ERR_Q) +df["anomaly_pca_recon"] = (recon_err >= thr).astype(int) + +# -------------------- Union / Intersection -------------------- +df["anomaly_union"] = df[["anomaly_iforest","anomaly_pca_recon"]].max(axis=1) +df["anomaly_intersection"] = (df[["anomaly_iforest","anomaly_pca_recon"]].sum(axis=1) == 2).astype(int) + +# -------------------- Save -------------------- +out_csv = OUT_DIR/"dataset_with_iforest_pca.csv" +df.to_csv(out_csv, index=False) +print("[INFO] Saved CSV ->", out_csv.resolve()) +print("[INFO] Summary:") +for col in ["anomaly_iforest","anomaly_pca_recon","anomaly_union","anomaly_intersection"]: + print(f" {col}: {int(df[col].sum())} ({df[col].mean()*100:.1f}%)") +print("[INFO] Plots saved in:", OUT_DIR.resolve()) +# === Persist trained artifacts for streaming (Flink) === +import os +import joblib +import pathlib + +MODEL_VERSION = os.getenv("MODEL_VERSION_IFPCA", "ifpca-1") +pathlib.Path("models").mkdir(exist_ok=True) + +artifact_ifpca = { + "model_version": MODEL_VERSION, + "pre": pre, + "iforest": iso, + "pca": pca_full, + "pca_thr": float(thr), + "feature_cols": list(candidate_cols), + "num_cols": list(num_cols), +} + +out_path_ifpca = "models/iforest_pca_artifacts.joblib" +joblib.dump(artifact_ifpca, out_path_ifpca) +print(f"✅ saved: {out_path_ifpca} (version={MODEL_VERSION})") \ No newline at end of file diff --git a/services/Cross-Sensor System-Level Anomalies/detect_residuals_and_hybrid.py b/services/Cross-Sensor System-Level Anomalies/detect_residuals_and_hybrid.py new file mode 100644 index 000000000..f34982325 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/detect_residuals_and_hybrid.py @@ -0,0 +1,161 @@ +# detect_residuals_and_hybrid.py +# Residual-per-Feature (OOF) + Hybrid union/intersection + 2-of-3 majority +from pathlib import Path +import os +import numpy as np +import pandas as pd + +# Headless plotting (WSL/CI-safe) +import matplotlib +matplotlib.use("Agg") + +import matplotlib.pyplot as plt +from sklearn.model_selection import KFold +from sklearn.linear_model import HuberRegressor +from sklearn.impute import SimpleImputer +from sklearn.preprocessing import RobustScaler +from sklearn.pipeline import Pipeline + +# -------------------- Config -------------------- +IN_CSV = Path("out/dataset_with_iforest_pca.csv") # from detect_iforest_pca.py +OUT_DIR = Path("out"); OUT_DIR.mkdir(exist_ok=True) +RANDOM_STATE = 42 +N_SPLITS = 3 +RES_Q = 0.85 # top 5% will be anomalies (threshold quantile) + +# -------------------- Load -------------------- +df = pd.read_csv(IN_CSV) + + +drop_derived = { + "anomaly_iforest","iforest_score","pca_x","pca_y", + "pca_recon_error","anomaly_pca_recon","anomaly_union","anomaly_intersection","anomaly_2of3" +} + + +num_cols = [c for c in df.columns + if pd.api.types.is_numeric_dtype(df[c]) and c not in drop_derived] + +df_num = df[num_cols].copy() + +# -------------------- Targets -------------------- + +preferred_targets = [c for c in ["soil_moisture","rainfall","temperature","humidity"] if c in num_cols] +TARGETS = preferred_targets if len(preferred_targets) >= 2 else num_cols[: min(6, max(1, len(num_cols)))] + +print("[INFO] Residual targets:", TARGETS) + +# -------------------- Residual-per-Feature OOF -------------------- +kf = KFold(n_splits=N_SPLITS, shuffle=True, random_state=RANDOM_STATE) +residual_mat = pd.DataFrame(0.0, index=df.index, columns=[]) + +for target in TARGETS: + feats = [c for c in num_cols if c != target] + X_full = df_num[feats].values.astype("float32") + y_full = df_num[target].values.astype("float32") + + errs = np.zeros(len(df), dtype="float32") + + for tr, va in kf.split(X_full): + X_tr, X_va = X_full[tr], X_full[va] + y_tr, y_va = y_full[tr], y_full[va] + + imp = SimpleImputer(strategy="median").fit(X_tr) + X_tr = imp.transform(X_tr) + X_va = imp.transform(X_va) + + scaler = RobustScaler().fit(X_tr) + X_tr = scaler.transform(X_tr) + X_va = scaler.transform(X_va) + + model = HuberRegressor(max_iter=500) + model.fit(X_tr, y_tr) + pred = model.predict(X_va) + errs[va] = np.abs(pred - y_va) + + residual_mat[target] = errs + +# -------------------- Residual-general OOF -------------------- +general_score = residual_mat.max(axis=1) +df["residual_general_score"] = general_score + +thr = float(np.quantile(general_score, RES_Q)) +df["anomaly_residual_general"] = (general_score >= thr).astype(int) +print(f"[INFO] Residual-general anomalies: {int(df['anomaly_residual_general'].sum())} " + f"({df['anomaly_residual_general'].mean()*100:.1f}%), thr={thr:.6f}") + +# -------------------- Hybrid: Union / Intersection / 2-of-3 -------------------- +methods = [] +if "anomaly_iforest" in df.columns: methods.append("anomaly_iforest") +if "anomaly_pca_recon" in df.columns: methods.append("anomaly_pca_recon") +methods.append("anomaly_residual_general") + +df["anomaly_union"] = df[methods].max(axis=1) +df["anomaly_intersection"] = (df[methods].sum(axis=1) == len(methods)).astype(int) +votes = df[methods].sum(axis=1) +df["anomaly_2of3"] = (votes >= 2).astype(int) +print(f"[INFO] Hybrid 2-of-3: {int(df['anomaly_2of3'].sum())} ({df['anomaly_2of3'].mean()*100:.1f}%)") + +print("[INFO] Hybrid summary:") +for m in methods + ["anomaly_union","anomaly_intersection"]: + print(f" {m}: {int(df[m].sum())} ({df[m].mean()*100:.1f}%)") + +# -------------------- TOP-10 -------------------- +try: + top10_idx = df["residual_general_score"].nlargest(min(10, len(df))).index + cols_to_show = ["residual_general_score","anomaly_residual_general"] + \ + [c for c in ["soil_moisture","rainfall","temperature","humidity"] if c in df.columns] + top10 = df.loc[top10_idx, cols_to_show].copy() +except Exception: + top10 = pd.DataFrame(columns=["residual_general_score","anomaly_residual_general"]) +top10.to_csv(OUT_DIR/"top10_residual_rows.csv", index=False) + +# -------------------- Plot: PCA 2D colored by Hybrid union -------------------- +if {"pca_x","pca_y"}.issubset(df.columns): + plt.figure(figsize=(7,6)) + mask = df["anomaly_union"].astype(bool) + plt.scatter(df.loc[~mask,"pca_x"], df.loc[~mask,"pca_y"], s=12, alpha=0.25, label="normal") + plt.scatter(df.loc[mask, "pca_x"], df.loc[mask, "pca_y"], s=20, alpha=0.9, marker="x", label="anomaly (union)") + plt.title("PCA (2D) colored by HYBRID (union)") + plt.xlabel("PC1"); plt.ylabel("PC2"); plt.legend(); plt.tight_layout() + plt.savefig(OUT_DIR/"pca_hybrid_union.png"); plt.close() + +# -------------------- Save batch outputs -------------------- +out_csv = OUT_DIR/"dataset_hybrid_iforest_pca_residual.csv" +df.to_csv(out_csv, index=False) +print("[INFO] Saved CSV ->", out_csv.resolve()) +print("[INFO] Saved plots/results in:", OUT_DIR.resolve()) + +# -------------------- Build residual models for serving (Flink) -------------------- + +residual_models_by_target = {} +numeric_feature_names = list(num_cols) +for target in TARGETS: + feats = [c for c in num_cols if c != target] + X_full = df_num[feats].values.astype("float32") + y_full = df_num[target].values.astype("float32") + pipe = Pipeline([ + ("imp", SimpleImputer(strategy="median")), + ("sc", RobustScaler()), + ("hub", HuberRegressor(max_iter=500)) + ]) + pipe.fit(X_full, y_full) + residual_models_by_target[target] = [pipe] + +residual_error_threshold = float(thr) + +# -------------------- Persist artifacts for streaming (Flink) -------------------- +import joblib +MODEL_VERSION = os.getenv("MODEL_VERSION_RESID", "resid-1") +Path("models").mkdir(exist_ok=True) + +artifact_resid = { + "model_version": MODEL_VERSION, + "resid_models": residual_models_by_target, + "resid_thr": residual_error_threshold, + "num_cols": numeric_feature_names, +} + +out_path_resid = "models/residuals_artifacts.joblib" +joblib.dump(artifact_resid, out_path_resid) +print(f"✅ saved: {out_path_resid} (version={MODEL_VERSION})") \ No newline at end of file diff --git a/services/Cross-Sensor System-Level Anomalies/docker-compose.yml b/services/Cross-Sensor System-Level Anomalies/docker-compose.yml new file mode 100644 index 000000000..b2ca00545 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/docker-compose.yml @@ -0,0 +1,50 @@ +version: "3.9" + +services: + jobmanager: + build: + context: . + dockerfile: Dockerfile.flink + container_name: flink-jobmanager + command: jobmanager + ports: + - "8085:8081" + environment: + - JOB_MANAGER_RPC_ADDRESS=jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=sensors + - OUT_TOPIC=sensors_anomalies_modal + volumes: + - ./conf/flink-conf.yaml:/opt/flink/conf/flink-conf.yaml + - ./flink_job.py:/opt/app/flink_job.py + - ./models:/opt/models + networks: + - flink-net + - agcloud_ag_cloud + + taskmanager: + build: + context: . + dockerfile: Dockerfile.flink + container_name: flink-taskmanager + command: taskmanager + depends_on: + - jobmanager + environment: + - JOB_MANAGER_RPC_ADDRESS=jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=sensors + - OUT_TOPIC=sensors_anomalies_modal + volumes: + - ./conf/flink-conf.yaml:/opt/flink/conf/flink-conf.yaml + - ./flink_job.py:/opt/app/flink_job.py + - ./models:/opt/models + networks: + - flink-net + - agcloud_ag_cloud + +networks: + flink-net: + driver: bridge + agcloud_ag_cloud: + external: true diff --git a/services/Cross-Sensor System-Level Anomalies/dockerfile b/services/Cross-Sensor System-Level Anomalies/dockerfile new file mode 100644 index 000000000..6c15f7432 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/dockerfile @@ -0,0 +1,29 @@ +# Dockerfile +FROM python:3.11-slim + +COPY certs/*.crt /app/certs/ +RUN if [ -d ./certs ] && [ "$(ls ./certs/*.crt 2>/dev/null)" ]; then \ + echo "Configuring NetFree certificates..."; \ + cp ./certs/*.crt /usr/local/share/ca-certificates/; \ + update-ca-certificates; \ + fi +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV PIP_CERT=/etc/ssl/certs/ca-certificates.crt + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + MPLBACKEND=Agg + +WORKDIR /app + +COPY requirements.txt /app/requirements.txt +RUN pip install --no-cache-dir -r requirements.txt + + +COPY . /app + +RUN mkdir -p /app/out /app/data + + +CMD ["bash","-lc","python -u detect_iforest_pca.py && python -u detect_residuals_and_hybrid.py"] diff --git a/services/Cross-Sensor System-Level Anomalies/entrypoint.sh b/services/Cross-Sensor System-Level Anomalies/entrypoint.sh new file mode 100644 index 000000000..ddcf5180f --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/entrypoint.sh @@ -0,0 +1,22 @@ +#!/bin/bash +set -e + +if [ "$1" = "jobmanager" ]; then + echo ">>> Waiting for Kafka to be ready..." + + while ! timeout 2 bash -c "echo > /dev/tcp/kafka/9092" 2>/dev/null; do + echo "Kafka not ready yet. Waiting 5 seconds..." + sleep 5 + done + + echo ">>> Kafka is ready. Starting Flink JobManager..." + /opt/flink/bin/jobmanager.sh start-foreground & + sleep 10 + echo ">>> Submitting Flink job..." + flink run -py /opt/app/flink_job.py + tail -f /dev/null + +else + echo ">>> Starting Flink TaskManager..." + exec /opt/flink/bin/taskmanager.sh start-foreground +fi diff --git a/services/Cross-Sensor System-Level Anomalies/flink_job.py b/services/Cross-Sensor System-Level Anomalies/flink_job.py new file mode 100644 index 000000000..0c3e6b6c3 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/flink_job.py @@ -0,0 +1,147 @@ +import os +import json +import joblib +import pandas as pd +import numpy as np +from pyflink.common import Types +from pyflink.datastream import StreamExecutionEnvironment +from pyflink.datastream.connectors.kafka import KafkaSource, KafkaSink, KafkaRecordSerializationSchema +from pyflink.common.serialization import SimpleStringSchema +from pyflink.common.watermark_strategy import WatermarkStrategy +from pyflink.datastream.functions import MapFunction, RuntimeContext + + +# --- ENV VARS --- +KAFKA_BROKERS = os.getenv("KAFKA_BROKERS", "kafka:9092") +IN_TOPIC = os.getenv("IN_TOPIC", "sensors") +OUT_TOPIC = os.getenv("OUT_TOPIC", "sensors_anomalies_modal") + +ART_IFOREST_PCA = os.getenv("ART_IFOREST_PCA", "/opt/models/iforest_pca_artifacts.joblib") +ART_RESIDUALS = os.getenv("ART_RESIDUALS", "/opt/models/residuals_artifacts.joblib") + + +# --- MAIN MAPPER CLASS --- +class AnomalyMap(MapFunction): + def open(self, ctx: RuntimeContext): + print(">>> Loading models...") + self.ifp = joblib.load(ART_IFOREST_PCA) + self.res = joblib.load(ART_RESIDUALS) + + self.pre = self.ifp["pre"] + self.ifr = self.ifp["iforest"] + self.pca = self.ifp["pca"] + self.pthr = self.ifp["pca_thr"] + self.fcols = self.ifp["feature_cols"] + self.num = self.ifp.get("num_cols", self.res.get("num_cols", [])) + self.rmdl = self.res["resid_models"] + self.rthr = self.res["resid_thr"] + + print(f">>> Models loaded successfully with {len(self.fcols)} features.") + + def map(self, raw: str): + print("\n=== RAW MESSAGE START ===") + print(raw) + print("=== RAW MESSAGE END ===\n") + + try: + evt = json.loads(raw) + if isinstance(evt, str): + evt = json.loads(evt) + except Exception as e: + print(f"[warning] Failed parsing message: {e}, raw={raw!r}") + return None + + if not isinstance(evt, dict): + print(f"[warning] Unexpected event type: {type(evt)} => {evt}") + return None + + print("PARSED EVENT KEYS:", list(evt.keys())) + + try: + row = {c: evt.get(c, np.nan) for c in self.fcols} + df = pd.DataFrame([row]) + df = df.replace(["unknown", ""], np.nan) + + for c in self.num: + if c in df.columns: + df[c] = pd.to_numeric(df[c], errors="coerce") + else: + df[c] = np.nan + + for c in self.num: + if c in df.columns: + median = df[c].median() + df[c] = df[c].fillna(median) + + print("DEBUG >>>", df.dtypes.to_dict()) + print("HEAD >>>", df.head().to_dict(orient="records")) + + X = self.pre.transform(df) + iflag = int(self.ifr.predict(X)[0] == -1) + + # ------------------------------------------------ + # FIXED SENSOR ID HANDLING + # ------------------------------------------------ + sensor_id = evt.get("id") + + # Fallback: if only "sid": "sensor-12" exists + if sensor_id is None: + sid = evt.get("sid") + if isinstance(sid, str) and sid.startswith("sensor-"): + try: + sensor_id = int(sid.replace("sensor-", "")) + except: + sensor_id = None + + if sensor_id is None: + print("[warning] Missing valid sensor_id, event skipped") + return None + + result = { + "sensor_id": int(sensor_id), + "ts": evt.get("ts", evt.get("timestamp")), + "anomaly": iflag + } + + print("OUTPUT:", result) + return json.dumps(result) + + except Exception as e: + print(f"[error] Failed processing message: {e}, evt={evt}") + return None + + +# --- MAIN EXECUTION --- +def main(): + print("Brokers:", KAFKA_BROKERS) + print("In:", IN_TOPIC, "Out:", OUT_TOPIC) + + env = StreamExecutionEnvironment.get_execution_environment() + env.set_parallelism(2) + + source = KafkaSource.builder() \ + .set_bootstrap_servers(KAFKA_BROKERS) \ + .set_topics(IN_TOPIC) \ + .set_group_id("flink-anomaly") \ + .set_value_only_deserializer(SimpleStringSchema()) \ + .build() + + sink = KafkaSink.builder() \ + .set_bootstrap_servers(KAFKA_BROKERS) \ + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(OUT_TOPIC) + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ).build() + + ds = env.from_source(source, WatermarkStrategy.no_watermarks(), "kafka-in") + ds.map(AnomalyMap(), output_type=Types.STRING()) \ + .filter(lambda x: x is not None) \ + .sink_to(sink) + + env.execute("sensor-anomaly-stream") + + +if __name__ == "__main__": + main() diff --git a/services/Cross-Sensor System-Level Anomalies/requirements.txt b/services/Cross-Sensor System-Level Anomalies/requirements.txt new file mode 100644 index 000000000..f32d99731 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/requirements.txt @@ -0,0 +1,6 @@ +numpy>=2.0.0 +scipy>=1.11 +pandas>=2.2 +scikit-learn>=1.4 +matplotlib>=3.8 +joblib>=1.4 diff --git a/services/Cross-Sensor System-Level Anomalies/tests/conftest.py b/services/Cross-Sensor System-Level Anomalies/tests/conftest.py new file mode 100644 index 000000000..2ac86fa13 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/tests/conftest.py @@ -0,0 +1,71 @@ +# tests/conftest.py +import os, shutil, random +import numpy as np +import pandas as pd +import pytest +from pathlib import Path + +RNG = np.random.default_rng(42) + +def make_base_df(n=1000, inject_anoms=False, inject_rate=0.05): + + df = pd.DataFrame({ + "id": [str(i) for i in range(n)], + "n": RNG.integers(0, 150, size=n), + "p": RNG.integers(0, 150, size=n), + "k": RNG.integers(0, 150, size=n), + "temperature": RNG.normal(25, 5, size=n), + "humidity": RNG.normal(70, 10, size=n).clip(0, 100), + "ph": RNG.normal(6.5, 0.8, size=n).clip(3.5, 9.5), + "rainfall": RNG.normal(200, 60, size=n).clip(0, None), + "label": RNG.choice(["rice","wheat","maize","grapes","orange","chickpea","papaya"], size=n), + "soil_moisture": RNG.normal(20, 6, size=n).clip(0, 100), + "soil_type": RNG.integers(1, 3+1, size=n), + "sunlight_exposure": RNG.uniform(5, 12, size=n), + "wind_speed": RNG.uniform(0.2, 20, size=n), + "co2_concentration": RNG.normal(400, 40, size=n), + "organic_matter": RNG.normal(6, 2, size=n).clip(0, None), + "irrigation_frequency": RNG.integers(1, 6+1, size=n), + "crop_density": RNG.uniform(5, 100, size=n), + "pest_pressure": RNG.uniform(1, 100, size=n), + "fertilizer_usage": RNG.uniform(1, 200, size=n), + "growth_stage": RNG.integers(1, 3+1, size=n), + "urban_area_proximity": RNG.uniform(0, 50, size=n), + "water_source_type": RNG.integers(1, 3+1, size=n), + "frost_risk": RNG.integers(0, 3+1, size=n), + "water_usage_efficiency": RNG.uniform(1, 100, size=n), + }) + + injected_ids = set() + if inject_anoms: + m = max(1, int(inject_rate * n)) + idx = RNG.choice(n, size=m, replace=False) + injected_ids = set(df.loc[idx, "id"].astype(str)) + + df.loc[idx, "temperature"] += RNG.normal(15, 3, size=m) + df.loc[idx, "humidity"] += RNG.normal(25, 5, size=m) + df.loc[idx, "rainfall"] -= RNG.normal(120, 30, size=m) + df.loc[idx, "soil_moisture"] += RNG.normal(20, 5, size=m) + return df, injected_ids + +@pytest.fixture +def synthetic_dataset(tmp_path): + n = 1000 + df, injected_ids = make_base_df(n=n, inject_anoms=True, inject_rate=0.06) + + workdir = tmp_path + (workdir/"data").mkdir(parents=True, exist_ok=True) + csv_path = workdir/"data"/"Crop_recommendationV2.csv" + df.to_csv(csv_path, index=False) + + + return workdir, csv_path, n, injected_ids + +@pytest.fixture +def no_anomaly_dataset_tmpdir(tmp_path): + n = 600 + df, injected_ids = make_base_df(n=n, inject_anoms=False) + workdir = tmp_path + (workdir/"data").mkdir(parents=True, exist_ok=True) + df.to_csv(workdir/"data"/"Crop_recommendationV2.csv", index=False) + return workdir, n, injected_ids diff --git a/services/Cross-Sensor System-Level Anomalies/tests/test_detect_iforest_pca.py b/services/Cross-Sensor System-Level Anomalies/tests/test_detect_iforest_pca.py new file mode 100644 index 000000000..869c5da68 --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/tests/test_detect_iforest_pca.py @@ -0,0 +1,47 @@ +# tests/test_detect_iforest_pca.py +import subprocess +import sys +import pandas as pd +from pathlib import Path + +def run_script(script, cwd): + res = subprocess.run([sys.executable, "-u", script], + cwd=cwd, capture_output=True, text=True, timeout=180) + assert res.returncode == 0, f"Script failed:\nSTDOUT:\n{res.stdout}\nSTDERR:\n{res.stderr}" + return res.stdout + +def test_iforest_pca_pipeline(synthetic_dataset): + workdir, csv_path, n, injected_ids = synthetic_dataset + + root = Path.cwd() + assert (root / "detect_iforest_pca.py").exists() + assert (root / "detect_residuals_and_hybrid.py").exists() + + run_script(str(root / "detect_iforest_pca.py"), cwd=workdir) + + out_dir = workdir / "out" + assert out_dir.exists(), "out/ not created" + + out_csv = out_dir / "dataset_with_iforest_pca.csv" + pca_plot = out_dir / "pca_iforest_anomalies.png" + assert out_csv.exists(), "dataset_with_iforest_pca.csv not found" + assert pca_plot.exists(), "pca_iforest_anomalies.png not found" + + df_out = pd.read_csv(out_csv) + required_cols = { + "anomaly_iforest", "iforest_score", + "pca_x", "pca_y", + "pca_recon_error", "anomaly_pca_recon", + "anomaly_union", "anomaly_intersection" + } + assert required_cols.issubset(df_out.columns), f"Missing columns: {required_cols - set(df_out.columns)}" + assert len(df_out) == n, "Row count changed unexpectedly" + + + if_count = int(df_out["anomaly_iforest"].sum()) + expected = 0.10 * n + assert abs(if_count - expected) <= 0.05 * n, f"IF anomalies off expected ~10%: got {if_count}/{n}" + + + pca_count = int(df_out["anomaly_pca_recon"].sum()) + assert 1 <= pca_count <= 0.2 * n, f"PCA recon anomalies looks off: {pca_count}" diff --git a/services/Cross-Sensor System-Level Anomalies/tests/test_detect_residuals_and_hybrid.py b/services/Cross-Sensor System-Level Anomalies/tests/test_detect_residuals_and_hybrid.py new file mode 100644 index 000000000..a699f4efc --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/tests/test_detect_residuals_and_hybrid.py @@ -0,0 +1,42 @@ +# tests/test_detect_residuals_and_hybrid.py +import subprocess +import sys +import pandas as pd +from pathlib import Path + +def run_script(script, cwd): + res = subprocess.run([sys.executable, "-u", script], + cwd=cwd, capture_output=True, text=True, timeout=180) + assert res.returncode == 0, f"Script failed:\nSTDOUT:\n{res.stdout}\nSTDERR:\n{res.stderr}" + return res.stdout + +def test_residuals_and_hybrid(synthetic_dataset): + workdir, csv_path, n, injected_ids = synthetic_dataset + root = Path.cwd() + + run_script(str(root / "detect_iforest_pca.py"), cwd=workdir) + run_script(str(root / "detect_residuals_and_hybrid.py"), cwd=workdir) + + out_dir = workdir / "out" + final_csv = out_dir / "dataset_hybrid_iforest_pca_residual.csv" + top10_csv = out_dir / "top10_residual_rows.csv" + hybrid_plot = out_dir / "pca_hybrid_union.png" + + assert final_csv.exists(), "Final hybrid CSV not found" + assert top10_csv.exists(), "top10_residual_rows.csv not found" + assert hybrid_plot.exists(), "pca_hybrid_union.png not found" + + df_final = pd.read_csv(final_csv) + + for col in ["anomaly_residual_general", "residual_general_score", "anomaly_union", "anomaly_intersection", "anomaly_2of3"]: + assert col in df_final.columns, f"Missing column '{col}'" + + + union_count = int(df_final["anomaly_union"].sum()) + assert 1 <= union_count <= 0.5 * n, f"Union anomalies seems off: {union_count}/{n}" + + + assert "id" in df_final.columns, "id column expected" + df_anom = df_final[df_final["anomaly_union"] == 1] + caught = sum(1 for _id in df_anom["id"].astype(str).values if _id in injected_ids) + assert caught >= max(1, int(0.33 * len(injected_ids))), f"Union caught too few injected anomalies: {caught}/{len(injected_ids)}" diff --git a/services/Cross-Sensor System-Level Anomalies/tests/test_low_anomaly_rate.py b/services/Cross-Sensor System-Level Anomalies/tests/test_low_anomaly_rate.py new file mode 100644 index 000000000..08e5ec6ec --- /dev/null +++ b/services/Cross-Sensor System-Level Anomalies/tests/test_low_anomaly_rate.py @@ -0,0 +1,28 @@ +# tests/test_low_anomaly_rate.py +import subprocess, sys, pandas as pd +from pathlib import Path + +def run(script, cwd): + res = subprocess.run([sys.executable, "-u", script], + cwd=cwd, capture_output=True, text=True, timeout=180) + assert res.returncode == 0, f"Script failed:\nSTDOUT:\n{res.stdout}\nSTDERR:\n{res.stderr}" + return res.stdout + +def test_clean_dataset_has_low_flags(no_anomaly_dataset_tmpdir): + workdir, n, injected = no_anomaly_dataset_tmpdir + root = Path.cwd() + + run(str(root / "detect_iforest_pca.py"), cwd=workdir) + run(str(root / "detect_residuals_and_hybrid.py"), cwd=workdir) + + df = pd.read_csv(workdir / "out" / "dataset_hybrid_iforest_pca_residual.csv") + + if_rate = df["anomaly_iforest"].mean() + pca_rate = df["anomaly_pca_recon"].mean() + res_rate = df["anomaly_residual_general"].mean() + two_of_three_rate = df["anomaly_2of3"].mean() + + msg = (f"Too many 2/3 anomalies on a clean dataset: {two_of_three_rate:.3f} " + f"(IF={if_rate:.3f}, PCA={pca_rate:.3f}, RES={res_rate:.3f})") + + assert two_of_three_rate < 0.07, msg diff --git a/services/__init__.py b/services/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/air/.gitignore b/services/air/.gitignore new file mode 100644 index 000000000..a2661ad0d --- /dev/null +++ b/services/air/.gitignore @@ -0,0 +1 @@ +certs/ \ No newline at end of file diff --git a/services/air/Dockerfile.flink b/services/air/Dockerfile.flink new file mode 100644 index 000000000..c89ca99ae --- /dev/null +++ b/services/air/Dockerfile.flink @@ -0,0 +1,58 @@ +FROM flink:1.19.3-scala_2.12-java11 + +USER root + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV LANG=C.UTF-8 +ENV LC_ALL=C.UTF-8 + +RUN set -eux; \ + apt-get update; \ + apt-get install -y --no-install-recommends \ + python3 python3-venv python3-pip \ + ca-certificates wget curl libgomp1; \ + apt-get clean; \ + rm -rf /var/lib/apt/lists/* + +COPY certs /app/certs +RUN cp /app/certs/*.crt /usr/local/share/ca-certificates/ && \ + update-ca-certificates && \ + echo "✅ NetFree certificates installed successfully" + +RUN printf "[global]\ntrusted-host = pypi.org\n\tfiles.pythonhosted.org\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf + +RUN mkdir -p /opt/flink/lib && \ + curl -fSL https://repo1.maven.org/maven2/org/apache/kafka/kafka-clients/3.7.0/kafka-clients-3.7.0.jar \ + -o /opt/flink/lib/kafka-clients-3.7.0.jar && \ + curl -fSL https://repo1.maven.org/maven2/org/apache/flink/flink-connector-kafka/3.2.0-1.19/flink-connector-kafka-3.2.0-1.19.jar \ + -o /opt/flink/lib/flink-connector-kafka-3.2.0-1.19.jar + +WORKDIR /opt/app +RUN mkdir -p /opt/app/tmp && chmod 777 /opt/app/tmp + +RUN python3 -m venv /opt/venv +ENV PATH="/opt/venv/bin:${PATH}" +ENV PYFLINK_PYTHON=/opt/venv/bin/python +ENV PYFLINK_CLIENT_EXECUTABLE=/opt/venv/bin/python3 +ENV PYTHONPATH="/opt/venv/lib/python3.10/site-packages:${PYTHONPATH}" + +RUN /opt/venv/bin/pip install --no-cache-dir --default-timeout=1000 \ + apache-flink==1.19.3 \ + requests \ + Pillow \ + minio \ + kafka-python \ + "protobuf<=3.20.3" \ + google-cloud-storage \ + numpy + +COPY job.py /opt/app/job.py + +ENV KAFKA_BROKERS=kafka:9092 \ + IN_TOPIC=image.new.aerial \ + OUT_TOPIC_OBJECT=aerial_image_object_detections \ + OUT_TOPIC_ANOMALY=aerial_image_anomaly_detections \ + OUT_TOPIC_SEGMENTATION=aerial_image_segmentation \ + OUT_TOPIC_ALERTS=alerts \ + KAFKA_GROUP_ID=flink-air-device-pipeline diff --git a/services/air/README.md b/services/air/README.md new file mode 100644 index 000000000..1b32cd6a4 --- /dev/null +++ b/services/air/README.md @@ -0,0 +1,64 @@ +# 📦 Model Installation Guide + +This project requires **three machine-learning models** that are not stored in the repository due to size limits. +Please download them from the following Google Drive folder: + +👉 **Models Download Folder:** +https://drive.google.com/drive/folders/1F0iMHbm3ahGOuoOWGWKY3frFxPw0mzRm?usp=sharing + +The folder contains the following model files: + +| Model Type | File Name | Used By Service | +|----------------------|------------------------------|---------------------------| +| Object Detection | object_detection_api.pt | infer-api | +| Anomaly Detection | anomaly_detection_api.pt | anomaly-api | +| Segmentation | segmentation_api.pth | segmentation-api | + +--- + +## 📥 1. Download the Models + +Download all three files from the Google Drive folder: + +- object_detection_api.pt +- anomaly_detection_api.pt +- segmentation_api.pth + +--- + +## 📁 2. Copy Each Model to Its Required Directory + +### 🔹 Object Detection Model +Copy to: +`services/air/object_detection_api/model/` + +Expected final path: +`services/air/object_detection_api/model/object_detection_api.pt` + +--- + +### 🔹 Anomaly Detection Model +Copy to: +`services/air/anomaly_detection_api/models/` + +Expected final path: +`services/air/anomaly_detection_api/models/anomaly_detection_api.pt` + +--- + +### 🔹 Segmentation Model +Copy to: +`services/air/segmentation_api/model/` + +Expected final path: +`services/air/segmentation_api/model/segmentation_api.pth` + +--- + +## ✅ 3. Verify the Installation + +Ensure all three files exist in these exact locations: + +- `services/air/object_detection_api/model/object_detection_api.pt` +- `services/air/anomaly_detection_api/models/anomaly_detection_api.pt` +- `services/air/segmentation_api/model/segmentation_api.pth` diff --git a/services/air/anomaly_detection_api/.gitignore b/services/air/anomaly_detection_api/.gitignore new file mode 100644 index 000000000..12cfcc3f3 --- /dev/null +++ b/services/air/anomaly_detection_api/.gitignore @@ -0,0 +1,2 @@ +certs/ +models/ \ No newline at end of file diff --git a/services/air/anomaly_detection_api/Dockerfile.anomaly b/services/air/anomaly_detection_api/Dockerfile.anomaly new file mode 100644 index 000000000..32a0609de --- /dev/null +++ b/services/air/anomaly_detection_api/Dockerfile.anomaly @@ -0,0 +1,27 @@ +FROM python:3.11-slim + +RUN apt-get update && apt-get install -y --no-install-recommends \ + libgl1 libglib2.0-0 ca-certificates curl && \ + rm -rf /var/lib/apt/lists/* + +COPY certs /app/certs +RUN cp /app/certs/*.crt /usr/local/share/ca-certificates/ && \ + update-ca-certificates && \ + echo "✅ NetFree certificates installed successfully" + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt + +RUN printf "[global]\ntrusted-host = pypi.org\n\tfiles.pythonhosted.org\n\tpytorch.org\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf + +WORKDIR /app + +COPY service.py . +COPY models ./models + +RUN pip install --no-cache-dir \ + torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu && \ + pip install --no-cache-dir ultralytics fastapi uvicorn pillow python-multipart + +EXPOSE 8010 +CMD ["uvicorn", "service:app", "--host", "0.0.0.0", "--port", "8010"] diff --git a/services/air/anomaly_detection_api/readme.md b/services/air/anomaly_detection_api/readme.md new file mode 100644 index 000000000..e10e4ad7d --- /dev/null +++ b/services/air/anomaly_detection_api/readme.md @@ -0,0 +1,7 @@ +docker build -t anomaly-api . + +docker run -d -p 8010:8000 anomaly-api + +docker compose up -d + +http://localhost:8010/docs diff --git a/services/air/anomaly_detection_api/service.py b/services/air/anomaly_detection_api/service.py new file mode 100644 index 000000000..11a4dfb73 --- /dev/null +++ b/services/air/anomaly_detection_api/service.py @@ -0,0 +1,67 @@ +from fastapi import FastAPI, File, UploadFile +from fastapi.responses import JSONResponse +from ultralytics import YOLO +from PIL import Image +import io, time +import os + +# =================================================== +# Load YOLO model once +# =================================================== +MODEL_PATH = "models/anomaly_detection_api.pt" + +if not os.path.exists(MODEL_PATH): + raise FileNotFoundError(f"❌ Model weights not found at: {MODEL_PATH}") + +model = YOLO(MODEL_PATH) + +app = FastAPI(title="Anomaly Detection API", version="1.0") + + +def run_inference(file: UploadFile): + """Run YOLO inference in memory and return results.""" + image = Image.open(io.BytesIO(file.file.read())) + return model.predict(image, conf=0.4, iou=0.25, save=False) + + +@app.post("/predict") +async def predict(file: UploadFile = File(...)): + """Accepts an image, runs inference, and returns JSON with detections.""" + t0 = time.time() + results = run_inference(file) + + if not results or len(results[0].boxes) == 0: + return JSONResponse({ + "anomaly": False, + "description": "No anomaly detected.", + "inference_time_sec": round(time.time() - t0, 3) + }) + + h, w = results[0].orig_shape + detections = [] + for box in results[0].boxes: + cls = int(box.cls[0]) + detections.append({ + "label": model.names[cls], + "confidence": round(float(box.conf[0]), 3), + "bbox": [round(float(x), 1) for x in box.xyxy[0].tolist()], + "center_xy": [round(float(x), 1) for x in box.xywh[0][:2].tolist()], + "image_size": [w, h] + }) + + return JSONResponse({ + "anomaly": True, + "detections": detections, + "inference_time_sec": round(time.time() - t0, 3) + }) + + +@app.get("/health") +async def health(): + """Simple healthcheck endpoint.""" + return {"status": "ok", "model": MODEL_PATH} + + +if __name__ == "__main__": + import uvicorn + uvicorn.run("service:app", host="0.0.0.0", port=8010) diff --git a/services/air/job.py b/services/air/job.py new file mode 100644 index 000000000..aa12c2cab --- /dev/null +++ b/services/air/job.py @@ -0,0 +1,397 @@ +import os +import io +import json +import time +import logging +import imghdr +import requests +from requests.adapters import HTTPAdapter, Retry +from minio import Minio +from PIL import Image + +from pyflink.datastream import StreamExecutionEnvironment +from pyflink.common.serialization import SimpleStringSchema +from pyflink.common.typeinfo import Types +from pyflink.common import WatermarkStrategy +from pyflink.datastream.connectors.kafka import ( + KafkaSource, + KafkaSink, + KafkaRecordSerializationSchema, + KafkaOffsetsInitializer +) +from pyflink.datastream.functions import RuntimeContext, ProcessFunction + + +# =============================================================== +# LOGGER CONFIGURATION +# =============================================================== +def setup_logger(): + logger = logging.getLogger("FlinkJob") + logger.setLevel(logging.INFO) + handler = logging.StreamHandler() + handler.setFormatter(logging.Formatter("%(asctime)s | %(levelname)-8s | %(message)s", + "%Y-%m-%d %H:%M:%S")) + if logger.hasHandlers(): + logger.handlers.clear() + logger.addHandler(handler) + logger.propagate = False + return logger + +def upload_to_minio(file_path, bucket_name, object_name): + try: + endpoint = os.getenv("MINIO_ENDPOINT", "minio-hot:9000") + access_key = os.getenv("MINIO_ACCESS_KEY", "minioadmin") + secret_key = os.getenv("MINIO_SECRET_KEY", "minioadmin123") + use_ssl = False + client = Minio(endpoint, access_key=access_key, secret_key=secret_key, secure=use_ssl) + if not client.bucket_exists(bucket_name): + client.make_bucket(bucket_name) + logging.info(f"🪣 Created bucket '{bucket_name}'") + client.fput_object(bucket_name, object_name, file_path) + logging.info(f"✅ Uploaded {object_name} to bucket '{bucket_name}'") + except Exception as e: + logging.error(f"❌ MinIO upload failed: {e}") + + + +logger = setup_logger() + + +# =============================================================== +# DownloadAndInfer Process Function +# =============================================================== +class DownloadAndInfer(ProcessFunction): + """Kafka → MinIO → Segmentation API → Infer API → Anomaly API → Kafka""" + + def open(self, runtime_context: RuntimeContext): + self.minio_client = Minio( + endpoint=os.getenv("MINIO_ENDPOINT", "minio-hot:9000"), + access_key=os.getenv("MINIO_ACCESS_KEY", "minioadmin"), + secret_key=os.getenv("MINIO_SECRET_KEY", "minioadmin123"), + secure=False + ) + + self.segmentation_url = os.getenv("SEGMENTATION_URL", "http://segmentation-api:8500/infer") + self.infer_url = os.getenv("INFER_URL", "http://infer-api:8000/infer") + self.anomaly_url = os.getenv("ANOMALY_URL", "http://anomaly-api:8010/predict") + + self.conf = float(os.getenv("INFER_CONF", "0.25")) + self.iou = float(os.getenv("INFER_IOU", "0.45")) + self.tmp_dir = "/opt/app/tmp" + os.makedirs(self.tmp_dir, exist_ok=True) + + self.session = requests.Session() + retries = Retry(total=3, backoff_factor=0.5, status_forcelist=[502, 503, 504]) + self.session.mount("http://", HTTPAdapter(max_retries=retries)) + self.timeout = (5, 180) + + logger.info("✅ DownloadAndInfer ready (Segmentation + Object + Anomaly)") + + def process_element(self, value, ctx): + infer_results, anomaly_results, segmentation_results = [], [], [] + logger.info("\n" + "=" * 70) + logger.info(f"📥 Received message: {value}") + + total_start = time.time() + + # === Parse Kafka message === + try: + data = json.loads(value) + image_key = data.get("img_key") + if not image_key: + logger.warning("⚠️ Missing 'key' in Kafka message") + return [] + except Exception as e: + logger.warning(f"⚠️ Invalid JSON: {e}") + return [] + + bucket, *path_parts = image_key.strip("/").split("/") + object_path = "/".join(path_parts) + local_filename = os.path.basename(object_path) + local_path = os.path.join(self.tmp_dir, local_filename) + + # === Step 1: Download from MinIO === + try: + self.minio_client.fget_object(bucket, object_path, local_path) + logger.info(f"✅ Downloaded: {bucket}/{object_path}") + except Exception as e: + logger.error(f"❌ Failed to download from MinIO: {e}") + return [] + + # === Step 2: Detect MIME === + try: + with open(local_path, "rb") as f: + img_bytes = f.read() + image_type = imghdr.what(None, h=img_bytes) + if not image_type: + img = Image.open(io.BytesIO(img_bytes)) + image_type = img.format.lower() + mime_type = f"image/{'jpeg' if image_type == 'jpg' else image_type}" + file_name = f"image.{image_type}" + logger.info(f"🧾 Detected image type: {image_type.upper()}") + except Exception as e: + logger.error(f"❌ Invalid image: {e}") + return [] + + # === Step 3: Segmentation API === + try: + files = {"file": (file_name, img_bytes, mime_type)} + logger.info(f"🛰️ Sending to Segmentation API: {self.segmentation_url}") + t0 = time.time() + r_seg = self.session.post(self.segmentation_url, files=files, timeout=self.timeout) + t1 = time.time() - t0 + r_seg.raise_for_status() + + base_name = os.path.splitext(local_filename)[0] + mask_filename = f"{base_name}_mask.png" + mask_path = os.path.join(self.tmp_dir, mask_filename) + mask_bytes = r_seg.content + if not r_seg.content: + logger.warning(f"⚠️ Segmentation API returned empty mask for {image_key}") + with open(mask_path, "wb") as f: + f.write(mask_bytes) + logger.info(f"🖼️ Saved segmentation mask: {mask_path}") + + # === Step 3.1: Upload mask to MinIO === + try: + bucket_name = os.getenv("MINIO_BUCKET", "imagery") + mask_object_key = f"air_mask/{mask_filename}" + upload_to_minio(mask_path, bucket_name, mask_object_key) + logger.info(f"☁️ Uploaded mask to MinIO at {bucket_name}/{mask_object_key}") + except Exception as e: + logger.error(f"❌ Failed to upload mask to MinIO: {e}") + + header_data = r_seg.headers.get("X-Class-Distribution") + if header_data: + dist = json.loads(header_data.replace("'", '"')) + else: + dist = {} + + row = { + "img_key": image_key, + "mask_path": f"{bucket_name}/{mask_object_key}", + "other": dist.get("Other", 0), + "bareland": dist.get("Bareland", 0), + "rangeland": dist.get("Rangeland", 0), + "developed_space": dist.get("Developed space", 0), + "road": dist.get("Road", 0), + "tree": dist.get("Tree", 0), + "water": dist.get("Water", 0), + "agriculture": dist.get("Agriculture land", 0), + "building": dist.get("Building", 0), + } + + segmentation_results.append(row) + logger.info(f"🧩 Segmentation done for {image_key}: {json.dumps(row, indent=2)}") + + except Exception as e: + logger.exception(f"❌ Segmentation API error: {e}") + mask_path = None + + # === Step 4: Object Detection (Infer API) === + try: + files = {"image": (file_name, img_bytes, mime_type)} + + if mask_path and os.path.exists(mask_path): + with open(mask_path, "rb") as f: + mask_bytes = f.read() + files["mask"] = (os.path.basename(mask_path), mask_bytes, "image/png") + logger.info(f"🧠 Using segmentation mask for Infer API: {mask_path}") + + params = {"conf": self.conf, "iou": self.iou} + t0 = time.time() + r = self.session.post(self.infer_url, files=files, params=params, timeout=self.timeout) + t1 = time.time() - t0 + + r.raise_for_status() + infer_data = r.json() if r.status_code != 204 else {} + infer_detections = infer_data.get("result", {}).get("detections", []) or infer_data.get("detections", []) + for det in infer_detections: + x1, y1, x2, y2 = det.get("bbox", [0, 0, 0, 0]) + infer_results.append({ + "img_key": image_key, + "label": det.get("class_name"), + "confidence": float(det.get("confidence", 0)), + "bbox_x1": float(x1), + "bbox_y1": float(y1), + "bbox_x2": float(x2), + "bbox_y2": float(y2) + }) + logger.info(f"🧠 {image_key}: {len(infer_detections)} detections ({t1:.2f}s)") + except Exception as e: + logger.exception(f"❌ Infer API error: {e}") + + # === Step 5: Anomaly API === + res = {} + try: + files = {"file": (file_name, img_bytes, mime_type)} + t2 = time.time() + r2 = self.session.post(self.anomaly_url, files=files, timeout=self.timeout) + t3 = time.time() - t2 + + r2.raise_for_status() + res = r2.json() + if res.get("anomaly", False): + detections = res.get("detections", []) + for det in detections: + x1, y1, x2, y2 = det.get("bbox", [0, 0, 0, 0]) + anomaly_results.append({ + "img_key": image_key, + "label": det.get("label", "anomaly"), + "confidence": float(det.get("confidence", 0)), + "bbox_x1": float(x1), + "bbox_y1": float(y1), + "bbox_x2": float(x2), + "bbox_y2": float(y2) + }) + logger.info(f"⚠️ Anomaly detection: {len(detections)} anomalies ({t3:.2f}s)") + else: + logger.info("✅ No anomalies detected.") + except Exception as e: + logger.exception(f"❌ Anomaly API error: {e}") + + # === step 6: alerts ==== + alert_events = [] + + if res.get("anomaly", False): + detections = res.get("detections", []) + + # Extract device_id from filename + filename = os.path.basename(image_key) + device_id = filename.split("_")[0] + + alert = { + "alert_id": f"{time.time_ns()}", + "alert_type": "aerial_anomaly_detected", + "device_id": device_id, + "started_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()), + "confidence": max(d.get("confidence", 0) for d in detections), + "severity": 3, + "image_url": image_key, + "meta": { + "anomalies": detections + } + } + + alert_events.append((json.dumps(alert), "alert")) + logger.info(f"🚨 ALERT created: {json.dumps(alert, indent=2)}") + + # === Step 7: Clean temp === + try: + os.remove(local_path) + if mask_path and os.path.exists(mask_path): + os.remove(mask_path) + except Exception: + pass + + total_time = time.time() - total_start + + logger.info(f"📊 Summary: " + f"{len(segmentation_results)} segmentations, " + f"{len(infer_results)} detections, " + f"{len(anomaly_results)} anomalies") + + logger.info(f"⏱️ Total processing time for {image_key}: {total_time:.2f}s") + + return ([(json.dumps(r), "segmentation") for r in segmentation_results] + + [(json.dumps(r), "object") for r in infer_results] + + [(json.dumps(r), "anomaly") for r in anomaly_results]+ + alert_events) + + +# =============================================================== +# MAIN EXECUTION FUNCTION +# =============================================================== +def main(): + logger.info("🚀 Starting Kafka→MinIO→Segmentation→Infer→Anomaly→Kafka Job") + + bootstrap = os.getenv("KAFKA_BROKERS", "kafka:9092") + topic_in = os.getenv("IN_TOPIC", "image.new.aerial") + topic_out_segmentation = os.getenv("OUT_TOPIC_SEGMENTATION", "aerial_image_segmentation") + topic_out_objects = os.getenv("OUT_TOPIC_OBJECT", "aerial_image_object_detections") + topic_out_anomaly = os.getenv("OUT_TOPIC_ANOMALY", "aerial_image_anomaly_detections") + topic_out_alerts = os.getenv("OUT_TOPIC_ALERTS", "alerts") + group_id = os.getenv("KAFKA_GROUP_ID", f"flink-air-device-pipeline") + + env = StreamExecutionEnvironment.get_execution_environment() + env.set_parallelism(1) + + source = ( + KafkaSource.builder() + .set_bootstrap_servers(bootstrap) + .set_topics(topic_in) + .set_group_id(group_id) + .set_starting_offsets(KafkaOffsetsInitializer.earliest()) + .set_value_only_deserializer(SimpleStringSchema()) + .build() + ) + + sink_segmentation = ( + KafkaSink.builder() + .set_bootstrap_servers(bootstrap) + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(topic_out_segmentation) + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ) + .build() + ) + + sink_objects = ( + KafkaSink.builder() + .set_bootstrap_servers(bootstrap) + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(topic_out_objects) + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ) + .build() + ) + + sink_anomalies = ( + KafkaSink.builder() + .set_bootstrap_servers(bootstrap) + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(topic_out_anomaly) + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ) + .build() + ) + + sink_alerts = ( + KafkaSink.builder() + .set_bootstrap_servers(bootstrap) + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(topic_out_alerts) + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ) + .build() + ) + + + stream = env.from_source(source, WatermarkStrategy.no_watermarks(), "Kafka Source") + + processed = stream.process(DownloadAndInfer(), output_type=Types.TUPLE([Types.STRING(), Types.STRING()])) + + segmentation_stream = processed.filter(lambda x: x[1] == "segmentation").map(lambda x: x[0], output_type=Types.STRING()) + objects_stream = processed.filter(lambda x: x[1] == "object").map(lambda x: x[0], output_type=Types.STRING()) + anomalies_stream = processed.filter(lambda x: x[1] == "anomaly").map(lambda x: x[0], output_type=Types.STRING()) + alerts_stream = processed.filter(lambda x: x[1] == "alert").map(lambda x: x[0], output_type=Types.STRING()) + + segmentation_stream.sink_to(sink_segmentation) + objects_stream.sink_to(sink_objects) + anomalies_stream.sink_to(sink_anomalies) + alerts_stream.sink_to(sink_alerts) + + + env.execute("Kafka-MinIO-Segmentation-Infer-Anomaly-Job") + + +if __name__ == "__main__": + main() diff --git a/services/air/object_detection_api/.gitignore b/services/air/object_detection_api/.gitignore new file mode 100644 index 000000000..33534c66b --- /dev/null +++ b/services/air/object_detection_api/.gitignore @@ -0,0 +1,2 @@ +certs/ +model/ \ No newline at end of file diff --git a/services/air/object_detection_api/Dockerfile.infer b/services/air/object_detection_api/Dockerfile.infer new file mode 100644 index 000000000..2bcf7c91f --- /dev/null +++ b/services/air/object_detection_api/Dockerfile.infer @@ -0,0 +1,35 @@ +FROM python:3.10-slim + +RUN apt-get update && apt-get install -y --no-install-recommends \ + libgl1 libglib2.0-0 libsm6 libxext6 libxrender1 \ + curl ca-certificates \ + && rm -rf /var/lib/apt/lists/* + +COPY certs /app/certs + +RUN apt-get update && \ + apt-get install -y ca-certificates && \ + cp /app/certs/*.crt /usr/local/share/ca-certificates/ && \ + update-ca-certificates && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt + +RUN printf "[global]\ntrusted-host = pypi.org\n\tfiles.pythonhosted.org\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf + +WORKDIR /app + +RUN pip install --no-cache-dir --index-url https://download.pytorch.org/whl/cpu \ + torch torchvision torchaudio + +COPY requirements.txt /app/requirements.txt +RUN pip install --no-cache-dir --default-timeout=1000 -r /app/requirements.txt + +COPY app.py model_wrapper.py /app/ + +ENV WEIGHTS_PATH=/app/object_detection_api.pt + +EXPOSE 8000 +CMD ["uvicorn","app:app","--host","0.0.0.0","--port","8000","--workers","1"] diff --git a/services/air/object_detection_api/README.md b/services/air/object_detection_api/README.md new file mode 100644 index 000000000..78bd5bda6 --- /dev/null +++ b/services/air/object_detection_api/README.md @@ -0,0 +1,203 @@ +# Aerial Object Counter API + +A lightweight FastAPI service that runs an object-detection model on aerial images and returns **counts per category** plus a **human‑readable summary**. +Optionally, the service can **save annotated images** (with bounding boxes) to disk. + +> **Outputs are English-only.** Every response includes: +> +> - `counts` — a JSON dictionary of `{class_name: count}` +> - `summary_text` — a compact sentence (e.g., `177 buildings, 19 vehicles`) + +--- + +## Overview + +- **Model**: Ultralytics YOLO (weights file: `best.pt`). +- **Wrapper**: `model_wrapper.py` normalizes class names to singular, clean keys. +- **API**: `app.py` exposes two endpoints: + - `POST /infer` — single image + - `POST /infer_dir` — process an entire folder of images + +Class set (12): `agri equipment, agri infra, building, rail, vessel, aviation, construction site, crane, tower, vehicle, container, yard`. + +--- + +## Project Structure + +``` +object_counter_api/ +├─ app.py # FastAPI server + endpoints +├─ model_wrapper.py # YOLOv8 loader + inference + draw/save utils +└─ requirements.txt # dependencies +``` + +--- + +## Installation + +> Recommended on Windows inside a virtual environment. + +```bat +python -m venv .venv +.venv\Scripts\activate +pip install -r requirements.txt +``` + +Place your trained weights file `best.pt` next to `app.py` (or change `WEIGHTS_PATH` at the top of `app.py`). + +--- + +## Run the Server + +```bat +uvicorn app:app --host 0.0.0.0 --port 8000 --reload +``` + +Health check (should return `{"status":"ok", ...}`): +``` +http://127.0.0.1:8000/health +``` + +--- + +## Endpoints + +### 1) `POST /infer` — Single Image + +- **Always returns**: `counts` and `summary_text` +- **Optional**: save an annotated image to disk (`outputs/` by default) + +**Query parameters** + +| Name | Type | Default | Description | +|-------------|---------|---------|-------------------------------------------| +| `conf` | float | 0.25 | Confidence threshold | +| `iou` | float | 0.45 | NMS IoU threshold | +| `min_area` | int? | null | Filter out tiny detections by pixel area | +| `save_image`| bool | false | Save annotated image to disk | +| `save_name` | string? | null | Optional filename for saved image (PNG) | + +**Request (Windows CMD / Git Bash)** +```bash +curl -s -X POST "http://127.0.0.1:8000/infer?save_image=true&save_name=annotated_test.png" \ + -F "file=@C:/Users/USER/Desktop/only_yolo/dataset/xView_12cls_en/images/test/img_99_640_0.jpg" +``` + +**Response** +```json +{ + "counts": { "building": 177, "vehicle": 19 }, + "summary_text": "177 buildings, 19 vehicles" +} +``` + +If `save_image=true`, the annotated PNG is saved on the server (default folder `outputs/`), filename as provided via `save_name` or `annotated_.png`. + +--- + +### 2) `POST /infer_dir` — Entire Folder + +Runs inference over all supported images in a directory. +**Always returns**: aggregated `counts` and `summary_text`. +**Optional**: save annotated images for each file. + +**Body (JSON)** +```json +{ + "dir_path": "C:/path/to/images", + "recursive": true, + "save_images": true, + "save_dir": "C:/path/to/outputs/batch1", + "conf": 0.25, + "iou": 0.45, + "min_area": 400 +} +``` + +**Example (Windows PowerShell / CMD)** +```bash +curl -s -X POST "http://127.0.0.1:8000/infer_dir" ^ + -H "Content-Type: application/json" ^ + -d "{\"dir_path\":\"C:/Users/USER/Desktop/only_yolo/dataset/images\",\"recursive\":true,\"save_images\":true,\"save_dir\":\"C:/Users/USER/Desktop/only_yolo/dataset/outputs/batch1\"}" +``` + +**Response** +```json +{ + "counts": { "building": 5200, "vehicle": 430 }, + "summary_text": "5200 buildings, 430 vehicles" +} +``` + +**Notes** + +- Allowed extensions: `.jpg .jpeg .png .tif .tiff` +- If `save_images=true` and no detections found for a file, no image is saved for that file. + +--- + +## Labels + +``` +GET /labels +``` + +Returns the model’s id→name mapping (normalized to clean, singular names). + +--- + +## Configuration + +At the top of `app.py`: + +```python +WEIGHTS_PATH = "best.pt" # path to your trained weights +OUTPUT_DIR = Path("outputs") # where annotated images are stored +``` + +You can change these to absolute paths if preferred. + +--- + +## Troubleshooting + +- **`ModuleNotFoundError: ultralytics`** + Ensure you run the server with the same Python where packages were installed. On Windows, check: + ```bat + where python + python --version + ``` + Then reinstall if needed: + ```bat + python -m pip install ultralytics + ``` + +- **Different Python versions** (e.g., installed under Python 3.10 but server runs under 3.11) + Create a virtual env (see Installation) and run everything inside it. + +- **Weights not found** + Verify that `best.pt` path matches `WEIGHTS_PATH` or place the file next to `app.py`. + +--- + +## Security / Safety + +- The API accepts local file paths (for `/infer_dir`). Do **not** expose this server publicly without proper authentication and sandboxing. +- For public deployments, add authentication, request size limits, and path validation. + +--- + +## License + +This repository contains example code and is provided “as is”, without warranty. +Your trained model weights remain your property under your chosen license. + +--- + +## Quick Checklist + +- [ ] Put `best.pt` next to `app.py` (or change `WEIGHTS_PATH`). +- [ ] `pip install -r requirements.txt` in a virtual environment. +- [ ] `uvicorn app:app --host 0.0.0.0 --port 8000 --reload` +- [ ] Test single image with `/infer`. +- [ ] Test folder mode with `/infer_dir`. diff --git a/services/air/object_detection_api/app.py b/services/air/object_detection_api/app.py new file mode 100644 index 000000000..686d6edc2 --- /dev/null +++ b/services/air/object_detection_api/app.py @@ -0,0 +1,131 @@ +from fastapi import FastAPI, UploadFile, File, Query +from fastapi.responses import JSONResponse +from typing import Dict +from io import BytesIO +from PIL import Image +import numpy as np +import logging, os +from pathlib import Path + +from model_wrapper import ( + ModelWrapper, + mask_to_detections, + merge_detections, +) + +# ----------------------------------------------------------- +# Logger setup +# ----------------------------------------------------------- +logger = logging.getLogger("fusion_api") +logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s") + +# ----------------------------------------------------------- +# App initialization +# ----------------------------------------------------------- +app = FastAPI(title="YOLO + Segmentation Fusion API", version="2.2") + +WEIGHTS_PATH = os.getenv("WEIGHTS_PATH", "/app/object_detection_api.pt") +model = ModelWrapper(weights_path=WEIGHTS_PATH, conf=0.25, iou=0.45) + +OUTPUT_DIR = Path("outputs") +OUTPUT_DIR.mkdir(exist_ok=True) + +if not os.path.exists(WEIGHTS_PATH): + raise FileNotFoundError(f"❌ Model weights not found at: {WEIGHTS_PATH}") +# ----------------------------------------------------------- +# Utility: convert NumPy types to JSON serializable types +# ----------------------------------------------------------- +def convert_numpy(obj): + """Recursively convert NumPy data types to native Python types.""" + if isinstance(obj, np.integer): + return int(obj) + elif isinstance(obj, np.floating): + return float(obj) + elif isinstance(obj, np.ndarray): + return obj.tolist() + elif isinstance(obj, (list, tuple)): + return [convert_numpy(i) for i in obj] + elif isinstance(obj, dict): + return {k: convert_numpy(v) for k, v in obj.items()} + else: + return obj + + +# ----------------------------------------------------------- +# Count detections by class +# ----------------------------------------------------------- +def count_by_class(detections): + counts = {} + for _, name, _, *_ in detections: + counts[name] = counts.get(name, 0) + 1 + return counts + + +# ----------------------------------------------------------- +# Build readable summary text +# ----------------------------------------------------------- +def build_summary(counts: Dict[str, int]) -> str: + total = sum(counts.values()) + details = ", ".join([f"{v} {k}" for k, v in counts.items()]) + return f"Total: {total} detections — {details}" + + +# ----------------------------------------------------------- +# Health check +# ----------------------------------------------------------- +@app.get("/health") +def health(): + return {"status": "ok", "weights": str(WEIGHTS_PATH)} + + +# ----------------------------------------------------------- +# Inference route +# ----------------------------------------------------------- +@app.post("/infer") +async def infer( + image: UploadFile = File(...), + mask: UploadFile = File(...), + conf: float = Query(0.25, ge=0.0, le=1.0), + iou: float = Query(0.45, ge=0.0, le=1.0), +): + try: + img_data = await image.read() + mask_data = await mask.read() + pil_image = Image.open(BytesIO(img_data)).convert("RGB") + mask_image = Image.open(BytesIO(mask_data)).convert("RGB") + + logger.info(f"📸 Loaded image: {image.filename}, mask size: {mask_image.size}") + + model.conf = conf + model.iou = iou + yolo_dets = model.predict(pil_image) + logger.info(f"🔹 YOLO detections: {len(yolo_dets)}") + + mask_dets = mask_to_detections(mask_image) + logger.info(f"🔹 Mask detections: {len(mask_dets)}") + + final_dets = merge_detections(yolo_dets, mask_dets) + logger.info(f"🔸 After merge: {len(final_dets)} total detections") + + counts = count_by_class(final_dets) + summary_text = build_summary(counts) + + result = { + "summary": summary_text, + "counts_per_class": counts, + "detections": [ + { + "class_id": d[0], + "class_name": d[1], + "confidence": d[2], + "bbox": [d[3], d[4], d[5], d[6]] + } + for d in final_dets + ], + } + + return JSONResponse(content=convert_numpy(result)) + + except Exception as e: + logger.exception(f"❌ Error: {e}") + return JSONResponse(status_code=500, content={"error": str(e)}) \ No newline at end of file diff --git a/services/air/object_detection_api/model_wrapper.py b/services/air/object_detection_api/model_wrapper.py new file mode 100644 index 000000000..1a355887e --- /dev/null +++ b/services/air/object_detection_api/model_wrapper.py @@ -0,0 +1,154 @@ +from __future__ import annotations +from typing import Dict, List, Tuple +from pathlib import Path +import numpy as np +from ultralytics import YOLO +import cv2 + +# ============================================================== +# STRUCTURE AND MAPPINGS +# ============================================================== + +Detection = Tuple[int, str, float, int, int, int, int] + +RAW_ID2NAME: Dict[int, str] = { + 0: "Agri equipment", 1: "Agri infra", 2: "Buildings", 3: "Rail", + 4: "Vessels", 5: "Aviation", 6: "Construction site", 7: "Cranes", + 8: "Towers", 9: "Vehicles", 10: "Containers", 11: "Yards", +} + +PALETTE = { + (210, 180, 140): (12, "Bareland"), + (152, 251, 152): (13, "Rangeland"), + (128, 128, 128): (14, "Developed space"), + (255, 255, 255): (15, "Road"), + (0, 100, 0): (16, "Tree"), + (30, 144, 255): (17, "Water"), + (255, 215, 0): (18, "Agriculture"), + (178, 34, 34): (19, "Buildings"), + (0, 0, 0): (20, "Other"), +} + +MODEL_PRIORITY = { + "vehicles": "yolo", "cranes": "yolo", "towers": "yolo", "containers": "yolo", + "yards": "yolo", "buildings": "yolo", + "road": "mask", "tree": "mask", "water": "mask", "agriculture": "mask", + "bareland": "mask", "rangeland": "mask", "developed space": "mask", "other": "mask", +} + +# ============================================================== +# YOLO MODEL WRAPPER +# ============================================================== + +class ModelWrapper: + def __init__(self, weights_path: str = "best.pt", conf: float = 0.25, iou: float = 0.45): + wp = Path(weights_path) + if not wp.exists(): + raise FileNotFoundError(f"Weights not found: {wp.resolve()}") + self.model = YOLO(str(wp)) + self.id2name = {int(i): str(n) for i, n in self.model.names.items()} if hasattr(self.model, "names") else RAW_ID2NAME + self.conf = conf + self.iou = iou + + def labels(self) -> Dict[int, str]: + return {i: n for i, n in self.id2name.items()} + + def predict(self, image: Image.Image) -> List[Detection]: + results = self.model.predict(source=np.array(image), conf=self.conf, iou=self.iou, verbose=False) + dets: List[Detection] = [] + for r in results: + if r.boxes is None: + continue + xyxy = r.boxes.xyxy.cpu().numpy() + confs = r.boxes.conf.cpu().numpy() + clss = r.boxes.cls.cpu().numpy().astype(int) + for (x1, y1, x2, y2), conf, cls in zip(xyxy, confs, clss): + name = self.id2name.get(int(cls), f"class_{cls}") + dets.append((int(cls), name, float(conf), int(x1), int(y1), int(x2), int(y2))) + return dets + + +# ============================================================== +# SEGFORMER MASK PROCESSING +# ============================================================== + +def color_mask_to_class_map(mask_rgb: Image.Image) -> np.ndarray: + mask = np.array(mask_rgb.convert("RGB")) + class_map = np.zeros(mask.shape[:2], dtype=np.uint8) + for color, (cid, _) in PALETTE.items(): + match = np.all(mask == color, axis=-1) + class_map[match] = cid + return class_map + + +def mask_to_detections(mask_rgb: Image.Image) -> List[Detection]: + mask = color_mask_to_class_map(mask_rgb) + dets: List[Detection] = [] + GENERAL_MIN = 100 + ROAD_MIN = 1000 + for cid in np.unique(mask): + if cid == 0: + continue + binary = (mask == cid).astype(np.uint8) * 255 + contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + _, cname = next(v for v in PALETTE.values() if v[0] == cid) + for c in contours: + x, y, w, h = cv2.boundingRect(c) + area = w * h + if cname.lower() == "road" and area < ROAD_MIN: + continue + if area < GENERAL_MIN: + continue + dets.append((cid, cname, 1.0, x, y, x + w, y + h)) + return dets + + +# ============================================================== +# MERGING LOGIC (Smart) +# ============================================================== + +def iou(a: Detection, b: Detection) -> float: + xA, yA = max(a[3], b[3]), max(a[4], b[4]) + xB, yB = min(a[5], b[5]), min(a[6], b[6]) + inter = max(0, xB - xA) * max(0, yB - yA) + areaA = (a[5] - a[3]) * (a[6] - a[4]) + areaB = (b[5] - b[3]) * (b[6] - b[4]) + union = areaA + areaB - inter + return inter / union if union > 0 else 0.0 + + +def merge_detections(yolo_dets: List[Detection], mask_dets: List[Detection], iou_thresh=0.4) -> List[Detection]: + final = list(yolo_dets) + + for md in mask_dets: + m_name = md[1].lower() + x1, y1, x2, y2 = md[3:7] + area = (x2 - x1) * (y2 - y1) + + if m_name == "tree" and area > 10000: + md = (md[0], "Forest", md[2], x1, y1, x2, y2) + + overlap = False + + for yd in list(final): + y_name = yd[1].lower() + ov = iou(md, yd) + if ov > iou_thresh: + if y_name in ("building", "buildings") and m_name != "building": + final.remove(yd) + continue + + y_pri = MODEL_PRIORITY.get(y_name, "yolo") + m_pri = MODEL_PRIORITY.get(m_name, "mask") + if m_pri == "mask" and y_pri == "yolo": + final.remove(yd) + final.append(md) + overlap = True + break + else: + overlap = True + + if not overlap: + final.append(md) + + return final diff --git a/services/air/object_detection_api/requirements.txt b/services/air/object_detection_api/requirements.txt new file mode 100644 index 000000000..630c65412 --- /dev/null +++ b/services/air/object_detection_api/requirements.txt @@ -0,0 +1,9 @@ +fastapi==0.115.0 +uvicorn==0.30.6 +pillow==10.4.0 +numpy==2.1.1 +pydantic==1.10.15 +python-multipart==0.0.9 +ultralytics==8.3.29 +opencv-python-headless==4.10.0.84 + diff --git a/services/air/segmentation_api/.gitignore b/services/air/segmentation_api/.gitignore new file mode 100644 index 000000000..3a8be3108 Binary files /dev/null and b/services/air/segmentation_api/.gitignore differ diff --git a/services/air/segmentation_api/dockerfile.segmentation b/services/air/segmentation_api/dockerfile.segmentation new file mode 100644 index 000000000..b4d2f07e1 --- /dev/null +++ b/services/air/segmentation_api/dockerfile.segmentation @@ -0,0 +1,66 @@ +# ========================================================= +# 1️⃣ Base image – Lightweight Python 3.11 +# ========================================================= +FROM python:3.11-slim + +# ========================================================= +# 2️⃣ Environment setup +# ========================================================= +WORKDIR /app +ENV DEBIAN_FRONTEND=noninteractive +ENV PYTHONUNBUFFERED=1 + +# ========================================================= +# 3️⃣ Install system dependencies +# ========================================================= +RUN apt-get update && apt-get install -y \ + ca-certificates \ + libgl1 \ + libglib2.0-0 \ + curl \ + && rm -rf /var/lib/apt/lists/* + +# ========================================================= +# 4️⃣ Copy NetFree SSL certificates +#========================================================= +COPY certs /app/certs +RUN cp /app/certs/*.crt /usr/local/share/ca-certificates/ && \ + update-ca-certificates && \ + echo "✅ NetFree certificates installed successfully" + +# ========================================================= +# 5️⃣ Copy project files +# ========================================================= +COPY . /app + +# ========================================================= +# 6️⃣ Install Python dependencies +# ========================================================= +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt + +RUN pip install --no-cache-dir --upgrade pip && \ + pip config set global.cert /etc/ssl/certs/ca-certificates.crt && \ + pip install --no-cache-dir \ + fastapi \ + uvicorn[standard] \ + opencv-python-headless \ + numpy \ + pillow \ + transformers \ + scipy \ + python-multipart + +RUN pip install --no-cache-dir \ + torch==2.3.0+cpu \ + torchvision==0.18.0+cpu \ + --index-url https://download.pytorch.org/whl/cpu + +# ========================================================= +# 7️⃣ Expose port +# ========================================================= +EXPOSE 8500 + +# ========================================================= +# 8️⃣ Run the API +# ========================================================= +CMD ["uvicorn", "infer_api:app", "--host", "0.0.0.0", "--port", "8500"] diff --git a/services/air/segmentation_api/infer_api.py b/services/air/segmentation_api/infer_api.py new file mode 100644 index 000000000..d3e895bea --- /dev/null +++ b/services/air/segmentation_api/infer_api.py @@ -0,0 +1,329 @@ +from fastapi import FastAPI, UploadFile, File +from fastapi.responses import Response, JSONResponse +import torch, torch.nn.functional as F +import cv2, numpy as np, tempfile, math +from transformers import SegformerForSemanticSegmentation, SegformerConfig +from oem_palette import NUM_CLASSES, PALETTE +from scipy import ndimage +import json +import logging +import os + +logger = logging.getLogger("segformer_api") +logger.setLevel(logging.INFO) +formatter = logging.Formatter("%(asctime)s | %(levelname)-8s | %(message)s") +console_handler = logging.StreamHandler() +console_handler.setFormatter(formatter) +if not logger.hasHandlers(): + logger.addHandler(console_handler) + +logger.propagate = False + +# ========================================================= +# ⚙️ General Settings +# ========================================================= +app = FastAPI(title="🛰️ SegFormer-B3 Smart Inference API (Enhanced Road Logic)") + +@app.get("/health") +def health(): + return {"status": "ok"} + +MODEL_PATH = "model/segmentation_api.pth" +device = torch.device("cuda" if torch.cuda.is_available() else "cpu") +logger.info(f"✅ Using device: {device}") + +# ========================================================= +# 🧠 Model Loading +# ========================================================= +if not os.path.exists(MODEL_PATH): + raise FileNotFoundError(f"❌ Model not found at: {MODEL_PATH}") + +config = SegformerConfig( + backbone="mit_b3", + num_labels=NUM_CLASSES, + hidden_sizes=[64, 128, 320, 512], + depths=[3, 4, 18, 3], + decoder_hidden_size=768, + ignore_mismatched_sizes=True +) +model = SegformerForSemanticSegmentation(config) +state_dict = torch.load(MODEL_PATH, map_location=device) +model.load_state_dict(state_dict, strict=False) +model.to(device).eval() +logger.info("✅ SegFormer-B3 model loaded successfully!") + + +# ========================================================= +# 🎨 Helper Functions +# ========================================================= +def preprocess_image(img: np.ndarray): + img = cv2.resize(img, (512, 512)) + img = img.astype(np.float32) / 255.0 + img = img.transpose(2, 0, 1) + return torch.from_numpy(img).unsqueeze(0).to(device) + + +def predict_probs(img: np.ndarray): + inputs = preprocess_image(img) + with torch.no_grad(): + outputs = model(pixel_values=inputs) + logits = outputs.logits + logits = F.interpolate(logits, size=img.shape[:2], mode="bilinear", align_corners=False) + probs = torch.softmax(logits, dim=1)[0].cpu().numpy() + return probs + + +def compute_class_distribution(mask): + h, w = mask.shape + total = h * w + counts = {} + index_to_name = {v[0]: v[1] for v in PALETTE.values()} + for cls_idx, cls_name in index_to_name.items(): + cls_pixels = np.sum(mask == cls_idx) + percent = round(100 * cls_pixels / total, 2) + if percent > 0: + counts[cls_name] = percent + return counts + + +def colorize_mask(mask): + color_mask = np.zeros((mask.shape[0], mask.shape[1], 3), dtype=np.uint8) + for color, (cls_idx, _) in PALETTE.items(): + color_mask[mask == cls_idx] = color + return color_mask + + +def refine_water_only(mask, probs, water_conf_thresh=0.8): + refined_mask = mask.copy() + top2 = np.argsort(-probs, axis=2) + second_best = top2[:, :, 1] + best_conf = np.max(probs, axis=2) + + WATER_CLASS = next((v[0] for k, v in PALETTE.items() if v[1].lower() == "water"), None) + if WATER_CLASS is not None: + low_conf_water = (mask == WATER_CLASS) & (best_conf < water_conf_thresh) + refined_mask[low_conf_water] = second_best[low_conf_water] + logger.info(f"💧 Replaced {np.sum(low_conf_water)} low-confidence water pixels") + + return refined_mask + + +def remove_small_roads(mask, probs, min_road_area=600, debug_visualize=True): + refined_mask = mask.copy() + ROAD_CLASS = next((v[0] for k, v in PALETTE.items() if v[1].lower() == "road"), None) + if ROAD_CLASS is None: + logger.warning("⚠️ ROAD_CLASS not found in PALETTE") + return refined_mask + + road_mask = (refined_mask == ROAD_CLASS).astype(np.uint8) + num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(road_mask, connectivity=8) + + logger.info(f"🛣️ Found {num_labels - 1} road regions (min_road_area={min_road_area})") + + if debug_visualize: + color_debug = colorize_mask(mask).copy() + + removed = 0 + for i in range(1, num_labels): + area = stats[i, cv2.CC_STAT_AREA] + x, y = stats[i, cv2.CC_STAT_LEFT], stats[i, cv2.CC_STAT_TOP] + w, h = stats[i, cv2.CC_STAT_WIDTH], stats[i, cv2.CC_STAT_HEIGHT] + cx, cy = centroids[i] + region_mask = (labels == i) + + logger.info(f"🚗 Road #{i:02d} | area={area:7.1f}px | bbox=({x},{y},{w},{h})") + + color = (0, 255, 0) if area >= min_road_area else (0, 0, 255) + if debug_visualize: + cv2.rectangle(color_debug, (x, y), (x + w, y + h), color, 2) + cv2.putText(color_debug, f"{i}", (x + 5, y + 20), + cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2, cv2.LINE_AA) + + if area < min_road_area: + dilated = ndimage.binary_dilation(region_mask, iterations=10) + neighbors = refined_mask[dilated & (~region_mask)] + + if len(neighbors) > 0: + dominant_class = np.bincount(neighbors).argmax() + else: + dominant_class = 0 + + refined_mask[region_mask] = dominant_class + logger.info(f" 🧭 Replaced with surrounding class: {dominant_class}") + removed += 1 + + logger.info(f"✅ Finished checking all roads — removed {removed}/{num_labels - 1}") + + return refined_mask + +def connect_roads_perfect( + color_mask, + road_color=(255, 255, 255), + max_distance=200, + angle_threshold=35, + connection_angle_limit=45, + line_thickness=6, + min_area=50, + connect_extend=15, + debug=True +): + tolerance = 20 + low = np.array([max(0, c - tolerance) for c in road_color]) + high = np.array([min(255, c + tolerance) for c in road_color]) + road_mask = cv2.inRange(color_mask, low, high) + + kernel = np.ones((5, 5), np.uint8) + road_mask = cv2.morphologyEx(road_mask, cv2.MORPH_CLOSE, kernel, iterations=2) + + contours, _ = cv2.findContours(road_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + connected_mask = color_mask.copy() + directions = [] + + if debug: + logger.info(f"✅ Found {len(contours)} road segments") + + for idx, cnt in enumerate(contours): + area = cv2.contourArea(cnt) + if area < min_area: + directions.append(None) + continue + + data_pts = np.array(cnt[:, 0, :], dtype=np.float64) + _, eigenvectors = cv2.PCACompute(data_pts, mean=np.array([])) + vx, vy = eigenvectors[0] + angle = math.degrees(math.atan2(vy, vx)) + directions.append((vx, vy, angle)) + if debug: + logger.info(f" 🟡 Segment {idx}: area={area:.1f}, angle={angle:.1f}°") + + connections = 0 + + for i in range(len(contours)): + if directions[i] is None: + continue + for j in range(i + 1, len(contours)): + if directions[j] is None: + continue + + cnt1, cnt2 = contours[i], contours[j] + min_dist = 1e9 + pt1_min, pt2_min = None, None + + for p1 in cnt1: + for p2 in cnt2: + d = np.linalg.norm(p1[0] - p2[0]) + if d < min_dist: + min_dist = d + pt1_min, pt2_min = tuple(p1[0]), tuple(p2[0]) + + if min_dist > max_distance: + continue + + (vx1, vy1, angle1) = directions[i] + (vx2, vy2, angle2) = directions[j] + avg_angle = (angle1 + angle2) / 2 + diff_angle = abs(angle1 - angle2) + diff_angle = min(diff_angle, 180 - diff_angle) + + dx, dy = pt2_min[0] - pt1_min[0], pt2_min[1] - pt1_min[1] + length = math.hypot(dx, dy) + if length == 0: + continue + ux, uy = dx / length, dy / length + connection_angle = math.degrees(math.atan2(uy, ux)) + + def angle_between(vx, vy, ux, uy): + dot = vx * ux + vy * uy + cross = vx * uy - vy * ux + ang = abs(math.degrees(math.atan2(cross, dot))) + return min(ang, 180 - ang) + + ang_to_road1 = angle_between(vx1, vy1, ux, uy) + ang_to_road2 = angle_between(vx2, vy2, ux, uy) + + if debug: + logger.info(f"🔹 {i}↔{j} | dist={min_dist:.1f}px | Δdir={diff_angle:.1f}° | " + f"Δconn1={ang_to_road1:.1f}° | Δconn2={ang_to_road2:.1f}°") + + if ( + diff_angle < angle_threshold and + ang_to_road1 < connection_angle_limit and + ang_to_road2 < connection_angle_limit + ): + p1, p2 = np.array(pt1_min, np.float32), np.array(pt2_min, np.float32) + p1_ext = (p1 - np.array([ux, uy]) * connect_extend).astype(int) + p2_ext = (p2 + np.array([ux, uy]) * connect_extend).astype(int) + + cv2.line(connected_mask, tuple(p1_ext), tuple(p2_ext), + road_color, line_thickness, lineType=cv2.LINE_8) + connections += 1 + if debug: + logger.info(f" ✅ Connected {i}↔{j}") + + if debug: + logger.info(f"✅ Total valid connections: {connections}") + if connections == 0: + print("⚠️ No connections made — try increasing max_distance slightly.") + + return connected_mask + + +def apply_confidence_threshold(probs, mask, threshold=0.6): + best_conf = np.max(probs, axis=2) + low_conf_mask = best_conf < threshold + mask[low_conf_mask] = 0 + logger.info(f"⚙️ Converted {np.sum(low_conf_mask)} low-confidence pixels to class 0 (Other)") + return mask + + +@app.post("/infer") +async def infer_image(file: UploadFile = File(...), threshold: float = 0.3): + try: + with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp: + tmp.write(await file.read()) + tmp_path = tmp.name + + img = cv2.cvtColor(cv2.imread(tmp_path), cv2.COLOR_BGR2RGB) + os.remove(tmp_path) + probs = predict_probs(img) + mask = np.argmax(probs, axis=0) + probs = np.transpose(probs, (1, 2, 0)) + mask = apply_confidence_threshold(probs, mask, threshold=threshold) + + + mask = refine_water_only(mask, probs, water_conf_thresh=1) + + color_mask = colorize_mask(mask) + + logger.info("🚗 Connecting roads before removing small ones...") + connected_color = connect_roads_perfect( + color_mask, + max_distance=120, + angle_threshold=35, + debug=True + ) + + connected_mask = np.zeros(mask.shape, dtype=np.uint8) + + for color, (cls_idx, _) in PALETTE.items(): + lower = np.clip(np.array(color) - 20, 0, 255).astype(np.uint8) + upper = np.clip(np.array(color) + 20, 0, 255).astype(np.uint8) + mask_area = cv2.inRange(connected_color, lower, upper) + connected_mask[mask_area > 0] = cls_idx + + logger.info(f"🖼️ mask shape: {mask.shape}, unique values: {np.unique(mask)}") + logger.info(f"🖼️ connected_mask shape: {connected_mask.shape}, unique values: {np.unique(connected_mask)}") + logger.info("🚗 sending to remove_small_roads() ...") + + refined_mask = remove_small_roads(connected_mask, probs, min_road_area=1000) + + final_color_mask = colorize_mask(refined_mask) + dist = compute_class_distribution(refined_mask) + + _, buffer = cv2.imencode(".png", cv2.cvtColor(final_color_mask, cv2.COLOR_RGB2BGR)) + return Response(content=buffer.tobytes(), media_type="image/png", + headers={"X-Class-Distribution": json.dumps(dist)}) + + except Exception as e: + return JSONResponse(content={"error": str(e)}, status_code=500) + diff --git a/services/air/segmentation_api/oem_palette.py b/services/air/segmentation_api/oem_palette.py new file mode 100644 index 000000000..711b737b0 --- /dev/null +++ b/services/air/segmentation_api/oem_palette.py @@ -0,0 +1,14 @@ +NUM_CLASSES = 9 + +PALETTE = { + (0, 0, 0): (0, "Other"), + (210, 180, 140): (1, "Bareland"), + (152, 251, 152): (2, "Rangeland"), + (128, 128, 128): (3, "Developed space"), + (255, 255, 255): (4, "Road"), + (0, 100, 0): (5, "Tree"), + (30, 144, 255): (6, "Water"), + (255, 215, 0): (7, "Agriculture"), + (178, 34, 34): (8, "Building"), +} + diff --git a/services/alertmanager_service/compose/alertmanager.yml b/services/alertmanager_service/compose/alertmanager.yml index ae8fd8d32..84acb4590 100644 --- a/services/alertmanager_service/compose/alertmanager.yml +++ b/services/alertmanager_service/compose/alertmanager.yml @@ -15,16 +15,67 @@ route: matchers: - source="agcloud-alerts" - # # 2️⃣ Slack route - # - receiver: "slack" - # continue: false - # matchers: - # - source="agcloud-alerts" + # 2️⃣ Slack route + - receiver: "slack" + continue: false + matchers: + - source="agcloud-alerts" receivers: - name: "null" + - name: "gateway" webhook_configs: - url: "http://alerts-gateway:8000/internal/alert" send_resolved: true - + + - name: "slack" + slack_configs: + - api_url_file: /run/secrets/slack_webhook + channel: "all-agcloud" # FIXED (no "#") + send_resolved: true + username: "AgCloud Alerts" + icon_emoji: ":rotating_light:" + + title: >- + {{ if eq .Status "resolved" }} + ⚪ EVENT CLOSED: {{ .CommonLabels.alertname }} on {{ .CommonLabels.device }} + {{ else }} + 🔴 ACTIVE ALERT: {{ .CommonLabels.alertname }} on {{ .CommonLabels.device }} + {{ end }} + + text: |- + {{ if eq .Status "resolved" }} + *Event closed.* + + *Type:* {{ .CommonLabels.alertname }} + *Device:* {{ .CommonLabels.device }} + *Alert ID:* {{ .CommonLabels.alert_id }} + + *Duration:* {{ (index .Alerts 0).StartsAt }} → {{ (index .Alerts 0).EndsAt }} + + *Summary:* {{ .CommonAnnotations.summary }} + + _No further activity detected. The alert has been automatically closed._ + + {{ else }} + *Summary:* {{ .CommonAnnotations.summary }} + *Recommendation:* {{ .CommonAnnotations.recommendation }} + *Severity:* {{ .CommonAnnotations.severity }} + *Category:* {{ .CommonAnnotations.category }} + + {{- if .CommonAnnotations.image_url }} + <{{ .CommonAnnotations.image_url }}|📷 Image> + {{- end }} + + {{- if .CommonAnnotations.vod }} + | <{{ .CommonAnnotations.vod }}|🎞️ VOD> + {{- end }} + + {{- if .CommonAnnotations.hls }} + | <{{ .CommonAnnotations.hls }}|📺 HLS> + {{- end }} + + _🕒 ID: {{ .CommonLabels.alert_id }}_ + {{ end }} + diff --git a/services/alertmanager_service/src/Dockerfile b/services/alertmanager_service/src/Dockerfile index 7fc4608b2..76b1b51db 100644 --- a/services/alertmanager_service/src/Dockerfile +++ b/services/alertmanager_service/src/Dockerfile @@ -3,15 +3,48 @@ # ───────────────────────────────────────────── FROM python:3.11-slim +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 + WORKDIR /app +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates curl \ + && rm -rf /var/lib/apt/lists/* + +COPY certs/*.crt /usr/local/share/ca-certificates/ +RUN chmod 644 /usr/local/share/ca-certificates/*.crt \ + && update-ca-certificates + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PIP_CERT=/etc/ssl/certs/ca-certificates.crt + +RUN python -m pip install --upgrade --no-cache-dir pip setuptools wheel + # Copy code COPY . . +# If ./certs has any *.crt (at any depth) → add to system trust store; otherwise skip +RUN if [ -d /app/certs ] && [ -n "$(find /app/certs -type f -name '*.crt' -print -quit)" ]; then \ + find /app/certs -type f -name '*.crt' -exec cp {} /usr/local/share/ca-certificates/ \; && \ + update-ca-certificates; \ + else \ + echo "No extra CA certs found. Skipping CA update."; \ + fi + +# Ensure pip/requests use the system CA bundle (works with/without NetFree) +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PIP_CERT=/etc/ssl/certs/ca-certificates.crt \ + PIP_DISABLE_PIP_VERSION_CHECK=1 + +# Persist pip setting as fallback +RUN printf "[global]\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf + # Install deps RUN pip install --no-cache-dir fastapi "uvicorn[standard]" pyyaml aiohttp asyncpg - # Default port — can be overridden by compose EXPOSE 8090 @@ -20,6 +53,5 @@ ENV CFG_PATH=/app/templates.yml ENV ALERTMANAGER_URL=http://alertmanager:9093 ENV GATEWAY_URL=http://alerts-gateway:8000/internal/alert - # Default command (can be overridden in docker-compose) CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8090"] diff --git a/services/alerts_forwarder/Dockerfile.flink b/services/alerts_forwarder/Dockerfile.flink index fbb7026c4..11b18c593 100644 --- a/services/alerts_forwarder/Dockerfile.flink +++ b/services/alerts_forwarder/Dockerfile.flink @@ -14,12 +14,35 @@ ENV PIP_DISABLE_PIP_VERSION_CHECK=1 # Python & tools RUN apt-get update && apt-get install -y --no-install-recommends python3 python3-venv python3-pip curl ca-certificates && rm -rf /var/lib/apt/lists/* +# Optional extra CA certs (NetFree, etc.) from ./certs +# (If no certs exist, this block just prints a message and continues.) +COPY certs/ /tmp/certs + +RUN set -eux; \ + if [ -d /tmp/certs ] && ls /tmp/certs/*.crt >/dev/null 2>&1; then \ + echo "Adding extra CA certs from /tmp/certs ..."; \ + cp /tmp/certs/*.crt /usr/local/share/ca-certificates/; \ + chmod 644 /usr/local/share/ca-certificates/*.crt; \ + update-ca-certificates; \ + else \ + echo "No extra CA certs found for alerts_forwarder, skipping."; \ + fi + # Create venv and install pyflink RUN python3 -m venv /opt/venv ENV PATH="/opt/venv/bin:$PATH" # Install PyFlink (DataStream API) and requests -RUN pip install --upgrade pip certifi && pip install --prefer-binary apache-flink==2.1.0 requests urllib3 +# RUN pip install --upgrade pip certifi && pip install --prefer-binary apache-flink==2.1.0 requests urllib3 +# Install PyFlink (DataStream API) and requests stack +RUN pip install --no-cache-dir \ + --trusted-host pypi.org \ + --trusted-host pypi.python.org \ + --trusted-host files.pythonhosted.org \ + apache-flink==2.1.0 \ + requests \ + urllib3 \ + certifi # Kafka connector jar matching Flink 1.20 (connector v3 series) # Reference: flink-connector-kafka-3.x for Flink 1.20 diff --git a/services/compression/.coverage b/services/compression/.coverage deleted file mode 100644 index 61d94bc14..000000000 Binary files a/services/compression/.coverage and /dev/null differ diff --git a/services/compression/Dockerfile b/services/compression/Dockerfile index 44deed463..de3ebd8f2 100644 --- a/services/compression/Dockerfile +++ b/services/compression/Dockerfile @@ -12,7 +12,7 @@ COPY certs /app/certs # Install certificates RUN cp /app/certs/*.crt /usr/local/share/ca-certificates/ && \ - update-ca-certificates +update-ca-certificates # Copy requirements and install COPY requirements.txt . diff --git a/services/compression/src/minio_client.py b/services/compression/src/minio_client.py index 6e970881b..2133784fd 100644 --- a/services/compression/src/minio_client.py +++ b/services/compression/src/minio_client.py @@ -4,7 +4,7 @@ MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "localhost:9001") ACCESS_KEY = os.getenv("ACCESS_KEY", "minioadmin") SECRET_KEY = os.getenv("SECRET_KEY", "minioadmin123") -BUCKET_NAME = os.getenv("BUCKET_NAME", "telemetry") +BUCKET_NAME = os.getenv("BUCKET_NAME", "sound") client = Minio( MINIO_ENDPOINT, diff --git a/services/compression/src/prototype_lib.py b/services/compression/src/prototype_lib.py index d2ef512af..5d9b6b32d 100644 --- a/services/compression/src/prototype_lib.py +++ b/services/compression/src/prototype_lib.py @@ -9,7 +9,7 @@ # Supported audio formats for compression AUDIO_EXTS = {".wav", ".mp3", ".flac", ".ogg", ".m4a", ".aac", ".wma", ".opus"} -RAW_PREFIX = "sound/" +RAW_PREFIX = "" def is_audio_file(filename: str) -> bool: """Check if file is an audio file that should be compressed.""" diff --git a/services/db_api_service/.env.example b/services/db_api_service/.env.example index 41bcedb47..a8f7feb5c 100644 --- a/services/db_api_service/.env.example +++ b/services/db_api_service/.env.example @@ -4,6 +4,6 @@ PORT=8080 CONTRACTS_DIR=app/contracts -ALLOWED_TABLES=["event_logs_sensors","devices","image_new_aerial_connections","sound_new_sounds_connections","sound_new_plants_connections","aerial_images_metadata","aerial_image_object_detections","aerial_image_anomaly_detections","aerial_images_complete_metadata","field_polygons","aerial_image_segmentation"] +ALLOWED_TABLES=["event_logs_sensors","devices","image_new_aerial_connections","sound_new_sounds_connections","sounds_metadata","sounds_ultra_metadata","sound_new_plants_connections","aerial_images_metadata","aerial_image_object_detections","aerial_image_anomaly_detections","aerial_images_complete_metadata","field_polygons","aerial_image_segmentation","image_new_security_connections","alerts"] STRICT_UNKNOWN_FIELDS=true diff --git "a/services/db_api_service/\342\200\216.gitignore" b/services/db_api_service/.gitignore similarity index 89% rename from "services/db_api_service/\342\200\216.gitignore" rename to services/db_api_service/.gitignore index 593f4ef41..7f5d2fbc0 100644 --- "a/services/db_api_service/\342\200\216.gitignore" +++ b/services/db_api_service/.gitignore @@ -1,39 +1,38 @@ -# Byte-compiled / cache -__pycache__/ -*.py[cod] -*.pyo -*.pyd - -# Virtual environments -.venv/ -env/ -venv/ - -# Pytest / coverage -.pytest_cache/ -.coverage -htmlcov/ - -# IDE / editor -.vscode/ -.idea/ - -# OS metadata -.DS_Store -Thumbs.db - -# Certificates / secrets -*.crt -*.pem -*.key -.env -.env.* - -# Build / distribution -build/ -dist/ -*.egg-info/ - -# Logs -*.log - +# Virtual environments +.venv/ +env/ +venv/ + +# Byte-compiled / cache +__pycache__/ +*.py[cod] +*.pyo +*.pyd + +# Pytest / coverage +.pytest_cache/ +.coverage +htmlcov/ + +# IDE / editor +.vscode/ +.idea/ + +# OS metadata +.DS_Store +Thumbs.db + +# Certificates / secrets +*.crt +*.pem +*.key +.env +.env.* + +# Build / distribution +build/ +dist/ +*.egg-info/ + +# Logs +*.log diff --git a/services/db_api_service/app/auth.py b/services/db_api_service/app/auth.py index 3f57556b7..3995f9ee2 100644 --- a/services/db_api_service/app/auth.py +++ b/services/db_api_service/app/auth.py @@ -1,187 +1,187 @@ -# app/auth.py -from __future__ import annotations - -import os -import uuid -import hashlib -from datetime import datetime, timedelta, timezone -from typing import Optional, Tuple - -from fastapi import APIRouter, Depends, HTTPException, Request, status -from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm -from jose import jwt, JWTError -from passlib.context import CryptContext -from sqlalchemy.orm import Session -from pydantic import BaseModel - -from .db import session_scope -from .models import User, ServiceAccount, RefreshToken - -ENV = os.getenv("ENV", "dev") -JWT_SECRET = os.getenv("JWT_SECRET", "change-me-please-very-secret") -JWT_ALGO = os.getenv("JWT_ALGO", "HS256") -ACCESS_TTL_MIN = int(os.getenv("ACCESS_TTL_MIN", "15")) -REFRESH_TTL_DAYS = int(os.getenv("REFRESH_TTL_DAYS", "14")) - -DEV_ADMIN_USER = os.getenv("DEV_ADMIN_USER", "admin") -DEV_ADMIN_PASS = os.getenv("DEV_ADMIN_PASS", "admin123") -DEV_SA_NAME = os.getenv("DEV_SA_NAME", "db-api") - -pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto") -oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/auth/login", auto_error=False) -router = APIRouter(prefix="/auth", tags=["auth"]) - -def get_db(): - with session_scope() as s: - yield s - -# ---------- Hashing / Verify ---------- -def hash_password(raw: str) -> str: - return pwd_context.hash(raw) - -def verify_password(raw: str, hashed: str) -> bool: - return pwd_context.verify(raw, hashed) - -def hash_sa_token(raw: str) -> str: - return hashlib.sha256(raw.encode()).hexdigest() - -# ---------- JWT helpers ---------- -def _encode_token(payload: dict) -> str: - return jwt.encode(payload, JWT_SECRET, algorithm=JWT_ALGO) - -def _decode_token(token: str) -> dict: - return jwt.decode(token, JWT_SECRET, algorithms=[JWT_ALGO]) - -def create_access_token(sub: str, subject_type: str = "user") -> str: - now = datetime.now(timezone.utc) - exp = now + timedelta(minutes=ACCESS_TTL_MIN) - payload = {"sub": sub, "sub_type": subject_type, "iat": int(now.timestamp()), "exp": int(exp.timestamp())} - return _encode_token(payload) - -def create_refresh_token(user_id: int) -> tuple[str, datetime]: - token = str(uuid.uuid4()) - expires = datetime.now(timezone.utc) + timedelta(days=REFRESH_TTL_DAYS) - return token, expires - -# ---------- Guard: require_auth ---------- -def require_auth( - request: Request, - db: Session = Depends(get_db), - bearer_token: Optional[str] = Depends(oauth2_scheme), -) -> Tuple[str, object]: - raw_sa = request.headers.get("X-Service-Token") - if raw_sa: - h = hash_sa_token(raw_sa) - sa = db.query(ServiceAccount).filter(ServiceAccount.token_hash == h).first() - if not sa: - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid service token") - return ("service", sa) - - if not bearer_token: - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="missing token") - - try: - payload = _decode_token(bearer_token) - except JWTError: - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid token") - - if payload.get("sub_type") != "user": - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid subject type") - - user_id = int(payload["sub"]) if str(payload.get("sub", "")).isdigit() else None - if not user_id: - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid subject") - - user = db.query(User).filter(User.id == user_id).first() - if not user: - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="user not found") - - return ("user", user) - -# ---------- Endpoints ---------- -@router.post("/login") -def login(form: OAuth2PasswordRequestForm = Depends(), db: Session = Depends(get_db)): - user = db.query(User).filter(User.username == form.username).first() - if not user or not verify_password(form.password, user.password_hash): - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="bad credentials") - access = create_access_token(str(user.id), "user") - refresh_token, expires = create_refresh_token(user.id) - db.add(RefreshToken(user_id=user.id, token=refresh_token, expires_at=expires)) - return {"access_token": access, "token_type": "bearer", "refresh_token": refresh_token} - -class RefreshIn(BaseModel): - refresh_token: str - -@router.post("/refresh") -def refresh_token(body: RefreshIn, db: Session = Depends(get_db)): - rt = db.query(RefreshToken).filter(RefreshToken.token == body.refresh_token).first() - if not rt: - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid refresh token") - - user = rt.user - if not user.is_active: - raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="inactive user") - - if rt.expires_at < datetime.now(timezone.utc): - raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="refresh token expired") - - access = create_access_token(str(user.id), "user") - - # rotate refresh token - db.delete(rt) - new_refresh, new_expires = create_refresh_token(user.id) - db.add(RefreshToken(user_id=user.id, token=new_refresh, expires_at=new_expires)) - db.commit() - - return {"access_token": access, "refresh_token": new_refresh, "token_type": "bearer"} -class DevBootstrapIn(BaseModel): - service_name: str | None = None - rotate_if_exists: bool = False - -@router.post("/_dev_bootstrap", status_code=status.HTTP_201_CREATED) -def dev_bootstrap(body: DevBootstrapIn | None = None, db: Session = Depends(get_db)): - if ENV != "dev": - raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="for dev only") - - service_name = (body.service_name.strip() if body and body.service_name else DEV_SA_NAME).strip() - rotate = bool(body.rotate_if_exists) if body else False - if not service_name: - raise HTTPException(status_code=400, detail="service_name required") - - user = db.query(User).filter(User.username == DEV_ADMIN_USER).first() - created_user = False - if not user: - user = User(username=DEV_ADMIN_USER, password_hash=hash_password(DEV_ADMIN_PASS)) - db.add(user) - db.flush() - created_user = True - - sa = db.query(ServiceAccount).filter(ServiceAccount.name == service_name).first() - raw_sa_token: Optional[str] = None - - if not sa: - raw_sa_token = str(uuid.uuid4()) - sa = ServiceAccount(name=service_name, token_hash=hash_sa_token(raw_sa_token)) - db.add(sa) - else: - if rotate: - raw_sa_token = str(uuid.uuid4()) - sa.token_hash = hash_sa_token(raw_sa_token) - - access = create_access_token(str(user.id), "user") - refresh_token, expires = create_refresh_token(user.id) - db.add(RefreshToken(user_id=user.id, token=refresh_token, expires_at=expires)) - - return { - "created_user": created_user, - "service_account": { - "name": sa.name, - "raw_token": raw_sa_token or None, - "token": (raw_sa_token or "*** (already exists)"), - }, - "tokens": { - "access_token": access, - "refresh_token": refresh_token, - "token_type": "bearer", - }, - } +# app/auth.py +from __future__ import annotations + +import os +import uuid +import hashlib +from datetime import datetime, timedelta, timezone +from typing import Optional, Tuple + +from fastapi import APIRouter, Depends, HTTPException, Request, status +from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm +from jose import jwt, JWTError +from passlib.context import CryptContext +from sqlalchemy.orm import Session +from pydantic import BaseModel + +from .db import session_scope +from .models import User, ServiceAccount, RefreshToken + +ENV = os.getenv("ENV", "dev") +JWT_SECRET = os.getenv("JWT_SECRET", "change-me-please-very-secret") +JWT_ALGO = os.getenv("JWT_ALGO", "HS256") +ACCESS_TTL_MIN = int(os.getenv("ACCESS_TTL_MIN", "15")) +REFRESH_TTL_DAYS = int(os.getenv("REFRESH_TTL_DAYS", "14")) + +DEV_ADMIN_USER = os.getenv("DEV_ADMIN_USER", "admin") +DEV_ADMIN_PASS = os.getenv("DEV_ADMIN_PASS", "admin123") +DEV_SA_NAME = os.getenv("DEV_SA_NAME", "db-api") + +pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto") +oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/auth/login", auto_error=False) +router = APIRouter(prefix="/auth", tags=["auth"]) + +def get_db(): + with session_scope() as s: + yield s + +# ---------- Hashing / Verify ---------- +def hash_password(raw: str) -> str: + return pwd_context.hash(raw) + +def verify_password(raw: str, hashed: str) -> bool: + return pwd_context.verify(raw, hashed) + +def hash_sa_token(raw: str) -> str: + return hashlib.sha256(raw.encode()).hexdigest() + +# ---------- JWT helpers ---------- +def _encode_token(payload: dict) -> str: + return jwt.encode(payload, JWT_SECRET, algorithm=JWT_ALGO) + +def _decode_token(token: str) -> dict: + return jwt.decode(token, JWT_SECRET, algorithms=[JWT_ALGO]) + +def create_access_token(sub: str, subject_type: str = "user") -> str: + now = datetime.now(timezone.utc) + exp = now + timedelta(minutes=ACCESS_TTL_MIN) + payload = {"sub": sub, "sub_type": subject_type, "iat": int(now.timestamp()), "exp": int(exp.timestamp())} + return _encode_token(payload) + +def create_refresh_token(user_id: int) -> tuple[str, datetime]: + token = str(uuid.uuid4()) + expires = datetime.now(timezone.utc) + timedelta(days=REFRESH_TTL_DAYS) + return token, expires + +# ---------- Guard: require_auth ---------- +def require_auth( + request: Request, + db: Session = Depends(get_db), + bearer_token: Optional[str] = Depends(oauth2_scheme), +) -> Tuple[str, object]: + raw_sa = request.headers.get("X-Service-Token") + if raw_sa: + h = hash_sa_token(raw_sa) + sa = db.query(ServiceAccount).filter(ServiceAccount.token_hash == h).first() + if not sa: + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid service token") + return ("service", sa) + + if not bearer_token: + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="missing token") + + try: + payload = _decode_token(bearer_token) + except JWTError: + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid token") + + if payload.get("sub_type") != "user": + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid subject type") + + user_id = int(payload["sub"]) if str(payload.get("sub", "")).isdigit() else None + if not user_id: + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid subject") + + user = db.query(User).filter(User.id == user_id).first() + if not user: + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="user not found") + + return ("user", user) + +# ---------- Endpoints ---------- +@router.post("/login") +def login(form: OAuth2PasswordRequestForm = Depends(), db: Session = Depends(get_db)): + user = db.query(User).filter(User.username == form.username).first() + if not user or not verify_password(form.password, user.password_hash): + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="bad credentials") + access = create_access_token(str(user.id), "user") + refresh_token, expires = create_refresh_token(user.id) + db.add(RefreshToken(user_id=user.id, token=refresh_token, expires_at=expires)) + return {"access_token": access, "token_type": "bearer", "refresh_token": refresh_token} + +class RefreshIn(BaseModel): + refresh_token: str + +@router.post("/refresh") +def refresh_token(body: RefreshIn, db: Session = Depends(get_db)): + rt = db.query(RefreshToken).filter(RefreshToken.token == body.refresh_token).first() + if not rt: + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="invalid refresh token") + + user = rt.user + if not user.is_active: + raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="inactive user") + + if rt.expires_at < datetime.now(timezone.utc): + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="refresh token expired") + + access = create_access_token(str(user.id), "user") + + # rotate refresh token + db.delete(rt) + new_refresh, new_expires = create_refresh_token(user.id) + db.add(RefreshToken(user_id=user.id, token=new_refresh, expires_at=new_expires)) + db.commit() + + return {"access_token": access, "refresh_token": new_refresh, "token_type": "bearer"} +class DevBootstrapIn(BaseModel): + service_name: str | None = None + rotate_if_exists: bool = False + +@router.post("/_dev_bootstrap", status_code=status.HTTP_201_CREATED) +def dev_bootstrap(body: DevBootstrapIn | None = None, db: Session = Depends(get_db)): + if ENV != "dev": + raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="for dev only") + + service_name = (body.service_name.strip() if body and body.service_name else DEV_SA_NAME).strip() + rotate = bool(body.rotate_if_exists) if body else False + if not service_name: + raise HTTPException(status_code=400, detail="service_name required") + + user = db.query(User).filter(User.username == DEV_ADMIN_USER).first() + created_user = False + if not user: + user = User(username=DEV_ADMIN_USER, password_hash=hash_password(DEV_ADMIN_PASS)) + db.add(user) + db.flush() + created_user = True + + sa = db.query(ServiceAccount).filter(ServiceAccount.name == service_name).first() + raw_sa_token: Optional[str] = None + + if not sa: + raw_sa_token = str(uuid.uuid4()) + sa = ServiceAccount(name=service_name, token_hash=hash_sa_token(raw_sa_token)) + db.add(sa) + else: + if rotate: + raw_sa_token = str(uuid.uuid4()) + sa.token_hash = hash_sa_token(raw_sa_token) + + access = create_access_token(str(user.id), "user") + refresh_token, expires = create_refresh_token(user.id) + db.add(RefreshToken(user_id=user.id, token=refresh_token, expires_at=expires)) + + return { + "created_user": created_user, + "service_account": { + "name": sa.name, + "raw_token": raw_sa_token or None, + "token": (raw_sa_token or "*** (already exists)"), + }, + "tokens": { + "access_token": access, + "refresh_token": refresh_token, + "token_type": "bearer", + }, + } diff --git a/services/db_api_service/app/main.py b/services/db_api_service/app/main.py index 17ebb8c5f..0a5c6463b 100644 --- a/services/db_api_service/app/main.py +++ b/services/db_api_service/app/main.py @@ -1,34 +1,36 @@ -from fastapi import FastAPI -from app.auth import router as auth_router -from app.db import engine -from app.models import Base -from app.contracts.loader import ContractStore -from app.router import build_router -from app.tables.generic import repo -from .config import settings - -contract_store = ContractStore(settings.CONTRACTS_DIR) -repo.set_contract_store(contract_store) - -app = FastAPI(title="Storage DB API", version="1.1.0") - -@app.on_event("startup") -def load_contracts_on_startup(): - contract_store.load_all() - -@app.get("/healthz") -def healthz(): - return {"status": "ok"} - -@app.get("/ready") -def ready(): - Base.metadata.create_all(bind=engine) - return {"ready": True} - -app.include_router(auth_router) -app.include_router(build_router(contract_store)) - - - - - +# from app.router import api + +# app.include_router(api) + +from fastapi import FastAPI +from app.auth import router as auth_router +from app.db import engine +from app.models import Base +from app.contracts.loader import ContractStore +from app.router import build_router +from app.tables.generic import repo +from .config import settings + +contract_store = ContractStore(settings.CONTRACTS_DIR) +repo.set_contract_store(contract_store) + +app = FastAPI(title="Storage DB API", version="1.1.0") + +@app.on_event("startup") +def load_contracts_on_startup(): + contract_store.load_all() + +@app.get("/healthz") +def healthz(): + return {"status": "ok"} + +@app.get("/ready") +def ready(): + Base.metadata.create_all(bind=engine) + return {"ready": True} + +app.include_router(auth_router) + +app.include_router(build_router(contract_store)) + + diff --git a/services/db_api_service/app/router.py b/services/db_api_service/app/router.py index fa02955ed..f775341ef 100644 --- a/services/db_api_service/app/router.py +++ b/services/db_api_service/app/router.py @@ -1,27 +1,25 @@ -# app/router.py - -from fastapi import APIRouter, Depends -from app.auth import require_auth -from app.tables.files.router import router as files_router - -from app.tables.generic.router import build_generic_router -from app.tables.task_thresholds.router import router as task_thresholds_router -from app.tables.ripeness_weekly_rollups_ts.router import router as ripeness_weekly_router - - -def build_router(contract_store) -> APIRouter: - api = APIRouter( - prefix="/api", - tags=["api"], - dependencies=[Depends(require_auth)], - ) - - - api.include_router(files_router) - api.include_router(task_thresholds_router) - api.include_router(ripeness_weekly_router) - api.include_router(build_generic_router(contract_store)) - - return api - - +# app/router.py +# from app.auth import require_uth +from fastapi import APIRouter, Depends +from app.auth import require_auth +from app.tables.files.router import router as files_router + +from app.tables.generic.router import build_generic_router +from app.tables.task_thresholds.router import router as task_thresholds_router +from app.tables.ripeness_weekly_rollups_ts.router import router as ripeness_weekly_router + + +def build_router(contract_store) -> APIRouter: + api = APIRouter( + prefix="/api", + tags=["api"], + dependencies=[Depends(require_auth)], + ) + + + api.include_router(files_router) + api.include_router(task_thresholds_router) + api.include_router(ripeness_weekly_router) + api.include_router(build_generic_router(contract_store)) + + return api diff --git a/services/db_api_service/app/tables/files/repo.py b/services/db_api_service/app/tables/files/repo.py index acf4b1215..35fd28f1a 100644 --- a/services/db_api_service/app/tables/files/repo.py +++ b/services/db_api_service/app/tables/files/repo.py @@ -137,7 +137,7 @@ def get_file(bucket: str, object_key: str) -> Optional[Dict[str, Any]]: q = text(""" SELECT file_id, bucket, object_key, - object_key AS key, -- convenient alias + object_key AS key, content_type, size_bytes, etag, mission_id, device_id, tile_id, ST_AsText(footprint) AS footprint_wkt, @@ -151,28 +151,53 @@ def get_file(bucket: str, object_key: str) -> Optional[Dict[str, Any]]: return dict(row) if row else None +# def get_file_by_id(file_id: int) -> Optional[Dict[str, Any]]: +# """Fetch by numeric file_id.""" +# if DRY_RUN: +# return None + +# q = text(""" +# SELECT +# file_id, bucket, object_key, +# object_key AS key, +# content_type, size_bytes, etag, +# mission_id, device_id, tile_id, +# ST_AsText(footprint) AS footprint_wkt, +# metadata, created_at +# FROM files +# WHERE file_id = :file_id +# LIMIT 1; +# """) +# with session_scope() as s: +# row = s.execute(q, {"file_id": file_id}).mappings().first() +# return dict(row) if row else None def get_file_by_id(file_id: int) -> Optional[Dict[str, Any]]: - """New: fetch by numeric file_id.""" + """New: fetch file metadata by numeric file_id using sound_new_sounds_connections (no files table).""" if DRY_RUN: return None - q = text(""" SELECT - file_id, bucket, object_key, - object_key AS key, -- convenient alias - content_type, size_bytes, etag, - mission_id, device_id, tile_id, - ST_AsText(footprint) AS footprint_wkt, - metadata, created_at - FROM files - WHERE file_id = :file_id + snsc.id AS file_id, + snsc.key AS key, -- combined bucket + path, e.g. "my-bucket/path/to/file.wav" + split_part(snsc.key, '/', 1) AS bucket, + regexp_replace(snsc.key, '^[^/]+/', '') AS object_key, + COALESCE(sm.file_name, snsc.file_name) AS filename, + sm.device_id AS device_id, + sm.content_type AS content_type, + sm.duration_sec AS duration_sec, + COALESCE(sm.capture_time, snsc.linked_time) AS capture_time, + snsc.metadata AS metadata, + snsc.linked_time AS linked_time + FROM public.sound_new_sounds_connections snsc + LEFT JOIN public.sounds_metadata sm + ON sm.file_name = snsc.file_name + WHERE snsc.id = :file_id LIMIT 1; """) with session_scope() as s: row = s.execute(q, {"file_id": file_id}).mappings().first() return dict(row) if row else None - def list_files(bucket: Optional[str], device_id: Optional[str], limit: int) -> List[Dict[str, Any]]: if DRY_RUN: return [] @@ -193,7 +218,7 @@ def list_files(bucket: Optional[str], device_id: Optional[str], limit: int) -> L q = text(f""" SELECT file_id, bucket, object_key, - object_key AS key, -- convenient alias + object_key AS key, content_type, size_bytes, etag, mission_id, device_id, tile_id, ST_AsText(footprint) AS footprint_wkt, @@ -221,3 +246,17 @@ def delete_file(bucket: str, object_key: str) -> bool: with session_scope() as s: row = s.execute(q, {"bucket": bucket, "object_key": object_key}).first() return bool(row) + + +def db_query(query: str, params: Optional[Dict[str, Any]] = None) -> List[Dict[str, Any]]: + """ + Generic helper to execute raw SQL and return rows as dictionaries. + This is used by the audio-aggregates and plant-predictions endpoints. + """ + if DRY_RUN: + return [] + + with session_scope() as s: + result = s.execute(text(query), params or {}) + rows = result.mappings().all() + return [dict(r) for r in rows] \ No newline at end of file diff --git a/services/db_api_service/app/tables/files/router.py b/services/db_api_service/app/tables/files/router.py index 1d738f07b..7f85e62ba 100644 --- a/services/db_api_service/app/tables/files/router.py +++ b/services/db_api_service/app/tables/files/router.py @@ -1,47 +1,92 @@ # app/tables/files/router.py from typing import Optional, Any, Dict from urllib.parse import unquote, quote -import os -import json +import os, json from fastapi import APIRouter, HTTPException, Query from .schemas import FilesCreate, FilesUpdate from . import repo +import requests router = APIRouter(prefix="/files", tags=["files"]) +# PUBLIC_S3_BASE = os.getenv("PUBLIC_S3_BASE") +PUBLIC_S3_BASE = os.getenv("PUBLIC_S3_BASE", "http://localhost:9001") +MINIO_BASE = "http://minio-hot:9000" -PUBLIC_S3_BASE = os.getenv("PUBLIC_S3_BASE") # e.g., "http://minio:9000" or "https://cdn.example.com" - - -def _attach_url_if_possible(row: Dict[str, Any]) -> Dict[str, Any]: +def _check_if_compressed_in_minio(bucket: str, object_key: str) -> bool: """ - If metadata has 'url' or 's3_url', expose it as 'url'. - Else, if PUBLIC_S3_BASE is set and we have bucket/key, build a path-style URL. + Check in MinIO if the file is compressed (OPUS format) + Uses direct file path checking via MinIO container """ + try: + base_key = object_key.replace('.wav', '').replace('.opus', '') + + possible_extensions = ['.opus', '.wav', ''] + + print(f"[DEBUG] Checking MinIO for bucket={bucket}, base={base_key}") + + for ext in possible_extensions: + test_key = f"{base_key}{ext}" + + # MinIO S3 API endpoint format + url = f"{MINIO_BASE}/{bucket}/{test_key}" + + try: + print(f"[DEBUG] HEAD request to: {url}") + + response = requests.get(url, timeout=3, stream=True) + + if response.status_code == 200: + is_opus = test_key.lower().endswith('.opus') + print(f"[DEBUG] ✓ Found: {url} (OPUS={is_opus})") + response.close() + return is_opus + elif response.status_code == 404: + print(f"[DEBUG] Not found (404): {url}") + else: + print(f"[DEBUG] Status {response.status_code}: {url}") + + except requests.exceptions.Timeout: + print(f"[DEBUG] Timeout for: {url}") + continue + except requests.exceptions.ConnectionError as e: + print(f"[DEBUG] Connection error for {url}: {e}") + continue + except Exception as e: + print(f"[DEBUG] Error for {url}: {e}") + continue + + print(f"[DEBUG] ✗ No file found for {bucket}/{object_key}") + return False + + except Exception as e: + print(f"[ERROR] MinIO check failed: {e}") + import traceback + traceback.print_exc() + return False + +def _attach_url_if_possible(row: Dict[str, Any]) -> Dict[str, Any]: + """Attach a public URL to access the file from MinIO.""" if not row: return row - # Try metadata first + # Try to extract URL from metadata first meta = row.get("metadata") if isinstance(meta, str): try: meta = json.loads(meta) except Exception: meta = None - if isinstance(meta, dict): for k in ("url", "s3_url"): if meta.get(k): row.setdefault("url", meta[k]) return row - - # Build from PUBLIC_S3_BASE, if available if PUBLIC_S3_BASE and row.get("bucket") and (row.get("key") or row.get("object_key")): bucket = str(row["bucket"]) key = str(row.get("key") or row.get("object_key")) built = f"{PUBLIC_S3_BASE.rstrip('/')}/{quote(bucket, safe='')}/{quote(key, safe='/')}" row.setdefault("url", built) - return row @@ -50,9 +95,226 @@ def create_or_upsert_file(payload: FilesCreate): repo.upsert_file(payload.model_dump(by_alias=True)) return {"status": "ok"} +@router.get("/audio-aggregates/", summary="List audio file aggregates (environment sounds)") +def list_audio_aggregates( + run_id: Optional[str] = None, + type: Optional[str] = Query(None, description="Predicted label (noise type)"), + date_from: Optional[str] = Query(None, description="Start date (YYYY-MM-DD)"), + date_to: Optional[str] = Query(None, description="End date (YYYY-MM-DD)"), + search: Optional[str] = Query(None, description="Search by filename"), + device_ids: Optional[str] = Query(None, description="Comma-separated device IDs"), + sort_by: Optional[str] = Query("Date (Newest)", description="Sort field"), + limit: int = Query(100, ge=1, le=500), +): + conditions = [] + params: Dict[str, Any] = {} + + # Run filter + if run_id: + conditions.append("fa.run_id = :run_id") + params["run_id"] = run_id + + # Label filter + if type and type.lower() not in ("all types", "all signals"): + conditions.append("fa.head_pred_label ILIKE :type") + params["type"] = f"%{type}%" + + # Search filter on filename + if search: + conditions.append("snsc.file_name ILIKE :search") + params["search"] = f"%{search}%" + + # Device filter + if device_ids: + device_list = [d.strip() for d in device_ids.split(",") if d.strip()] + if device_list: + placeholders = ", ".join([f":dev_{i}" for i in range(len(device_list))]) + conditions.append(f"(split_part(snsc.file_name, '_', 1)) IN ({placeholders})") + for i, dev in enumerate(device_list): + params[f"dev_{i}"] = dev + + # Date filters + if date_from: + conditions.append("COALESCE(sm.capture_time, snsc.linked_time) >= CAST(:date_from AS timestamptz)") + params["date_from"] = date_from + + if date_to: + conditions.append("COALESCE(sm.capture_time, snsc.linked_time) < CAST(:date_to AS timestamptz) + INTERVAL '1 day'") + params["date_to"] = date_to + + where_clause = "WHERE " + " AND ".join(conditions) if conditions else "" + + # Sorting options + sort_map = { + "Date (Newest)": "COALESCE(sm.capture_time, snsc.linked_time) DESC", + "Date (Oldest)": "COALESCE(sm.capture_time, snsc.linked_time) ASC", + "Length": "sm.duration_sec DESC", + "Device": "snsc.file_name ASC", + "processing_ms": "fa.processing_ms DESC", + "filename": "snsc.file_name ASC", + } + order_clause = sort_map.get(sort_by, "COALESCE(sm.capture_time, snsc.linked_time) DESC") + + query = f""" + SELECT + fa.file_id, + snsc.key AS combined_key, + split_part(snsc.key, '/', 1) AS bucket, + regexp_replace(snsc.key, '^[^/]+/', '') AS object_key, + COALESCE(sm.file_name, snsc.file_name) AS filename, + sm.device_id AS device_id, + COALESCE(sm.capture_time, snsc.linked_time) AS capture_time, + fa.head_pred_label, + fa.head_pred_prob, + fa.agg_mode, + fa.num_windows + FROM agcloud_audio.file_aggregates fa + JOIN public.sound_new_sounds_connections snsc + ON fa.file_id = snsc.id + LEFT JOIN public.sounds_metadata sm + ON sm.file_name = snsc.file_name + {where_clause} + ORDER BY {order_clause} + LIMIT :limit; + """ + + params["limit"] = limit + + try: + print("===== SQL QUERY =====") + print(query) + print("===== PARAMS =====") + print(params) + + rows = repo.db_query(query, params) + results = [] + + for r in rows: + bucket = r.get("bucket") + object_key = r.get("object_key") + filename = r.get("filename", "") + + url = None + if bucket and object_key: + url = f"{PUBLIC_S3_BASE.rstrip('/')}/{quote(bucket, safe='')}/{quote(object_key, safe='/')}" + + is_compressed = False + if bucket and object_key: + is_compressed = _check_if_compressed_in_minio(bucket, object_key) + print(f"[DEBUG] File {filename}: is_compressed={is_compressed}") + + results.append({ + "file_id": r.get("file_id"), + "filename": filename, + "predicted_label": r.get("head_pred_label"), + "probability": r.get("head_pred_prob"), + "device_id": (filename or "").split("_")[0] if filename else "Unknown", + "url": url, + "is_compressed": is_compressed, + }) + + return results + + except Exception as e: + raise HTTPException(status_code=500, detail=f"Database error: {e}") + + +@router.get("/plant-predictions/", summary="List ultrasonic plant predictions") +def list_plant_predictions( + predicted_class: Optional[str] = Query(None, description="Filter by predicted class"), + date_from: Optional[str] = Query(None, description="Start date (YYYY-MM-DD)"), + date_to: Optional[str] = Query(None, description="End date (YYYY-MM-DD)"), + search: Optional[str] = Query(None, description="Search by filename"), + device_ids: Optional[str] = Query(None, description="Comma-separated device IDs"), + sort_by: Optional[str] = Query("Date (Newest)", description="Sort field"), + limit: int = Query(100, ge=1, le=500), +): + conditions = [] + params: Dict[str, Any] = {} + + if predicted_class and predicted_class.lower() not in ("all signals", "all types"): + conditions.append("upp.predicted_class ILIKE :pred_class") + params["pred_class"] = f"%{predicted_class}%" + + if search: + conditions.append("upp.file ILIKE :search") + params["search"] = f"%{search}%" + + if date_from: + conditions.append("upp.prediction_time >= CAST(:date_from AS timestamptz)") + params["date_from"] = date_from + if date_to: + conditions.append("upp.prediction_time < CAST(:date_to AS timestamptz) + INTERVAL '1 day'") + params["date_to"] = date_to -# -------- New: GET /files/{file_id} by numeric id (place this before the catch-all path route) -------- -@router.get("/{file_id:int}") + where_clause = "WHERE " + " AND ".join(conditions) if conditions else "" + + sort_map = { + "Date (Newest)": "upp.prediction_time DESC", + "Date (Oldest)": "upp.prediction_time ASC", + "filename": "upp.file ASC" + } + order_clause = sort_map.get(sort_by, "upp.prediction_time DESC") + + query = f""" + SELECT + upp.id, + upp.file, + upp.predicted_class, + upp.confidence, + upp.watering_status, + upp.status, + snpc.key AS combined_key, + split_part(snpc.key, '/', 1) AS bucket, + regexp_replace(snpc.key, '^[^/]+/', '') AS object_key, + COALESCE(sm.file_name, snpc.file_name) AS filename, + COALESCE(sm.capture_time, snpc.linked_time) AS capture_time + FROM public.ultrasonic_plant_predictions upp + LEFT JOIN public.sound_new_plants_connections snpc + ON snpc.file_name = upp.file + LEFT JOIN public.sounds_metadata sm + ON sm.file_name = snpc.file_name + {where_clause} + ORDER BY {order_clause} + LIMIT :limit; + """ + + params["limit"] = limit + + try: + rows = repo.db_query(query, params) + results = [] + + for r in rows: + bucket = r.get("bucket") + object_key = r.get("object_key") + filename = r.get("file", "") + + url = None + if bucket and object_key: + url = f"{PUBLIC_S3_BASE.rstrip('/')}/{quote(bucket, safe='')}/{quote(object_key, safe='/')}" + + is_compressed = False + if bucket and object_key: + is_compressed = _check_if_compressed_in_minio(bucket, object_key) + + results.append({ + "id": r.get("id"), + "file": filename, + "predicted_class": r.get("predicted_class"), + "confidence": r.get("confidence"), + "watering_status": r.get("watering_status"), + "status": r.get("status"), + "device_id": ((filename or "").split("_")[0] or "Unknown"), + "url": url, + "is_compressed": is_compressed, + }) + + return results + except Exception as e: + raise HTTPException(status_code=500, detail=f"Database error: {e}") + +@router.get("/{file_id:int}", summary="Get file by ID") def get_file_by_id(file_id: int): row = repo.get_file_by_id(file_id) if not row: @@ -60,17 +322,18 @@ def get_file_by_id(file_id: int): return _attach_url_if_possible(row) -@router.put("/{bucket}/{object_key:path}") -def update_file(bucket: str, object_key: str, payload: FilesUpdate): +@router.get("/{bucket}", summary="List files in bucket") +def list_files_in_bucket( + bucket: str, + device_id: Optional[str] = None, + limit: int = Query(50, ge=1, le=500), +): bucket = unquote(bucket) - object_key = unquote(object_key) - ok = repo.update_file(bucket, object_key, payload.model_dump(exclude_unset=True)) - if not ok: - raise HTTPException(status_code=404, detail="not found") - return {"status": "ok"} + rows = repo.list_files(bucket, device_id, limit) + return [_attach_url_if_possible(r) for r in rows] -@router.get("/{bucket}/{object_key:path}") +@router.get("/{bucket}/{object_key:path}", summary="Get file by bucket/key") def get_file(bucket: str, object_key: str): bucket = unquote(bucket) object_key = unquote(object_key) @@ -80,20 +343,17 @@ def get_file(bucket: str, object_key: str): return _attach_url_if_possible(row) -@router.get("") -def list_files( - bucket: Optional[str] = None, - device_id: Optional[str] = None, - limit: int = Query(50, ge=1, le=500), -): - if bucket is not None: - bucket = unquote(bucket) - rows = repo.list_files(bucket, device_id, limit) - # Optionally attach URL to each row (cheap for small lists) - return [_attach_url_if_possible(r) for r in rows] +@router.put("/{bucket}/{object_key:path}", summary="Update file metadata") +def update_file(bucket: str, object_key: str, payload: FilesUpdate): + bucket = unquote(bucket) + object_key = unquote(object_key) + ok = repo.update_file(bucket, object_key, payload.model_dump(exclude_unset=True)) + if not ok: + raise HTTPException(status_code=404, detail="not found") + return {"status": "ok"} -@router.delete("/{bucket}/{object_key:path}") +@router.delete("/{bucket}/{object_key:path}", summary="Delete file") def delete_file(bucket: str, object_key: str): bucket = unquote(bucket) object_key = unquote(object_key) diff --git a/services/db_api_service/app/tables/files/schemas.py b/services/db_api_service/app/tables/files/schemas.py index 7898ad1b5..e3d43810e 100644 --- a/services/db_api_service/app/tables/files/schemas.py +++ b/services/db_api_service/app/tables/files/schemas.py @@ -1,30 +1,30 @@ -# app/tables/files/schemas.py -from typing import Optional, Any, Dict -from pydantic import BaseModel, Field, NonNegativeInt - - -class FilesCreate(BaseModel): - bucket: str - object_key: str = Field(alias="object_key") - content_type: Optional[str] = None - size_bytes: Optional[NonNegativeInt] = None - etag: Optional[str] = None - mission_id: Optional[int] = None - device_id: Optional[str] = None - tile_id: Optional[str] = None - footprint: Optional[str] = None # WKT - metadata: Optional[Dict[str, Any]] = None - - class Config: - populate_by_name = True - - -class FilesUpdate(BaseModel): - content_type: Optional[str] = None - size_bytes: Optional[NonNegativeInt] = None - etag: Optional[str] = None - mission_id: Optional[int] = None - device_id: Optional[str] = None - tile_id: Optional[str] = None - footprint: Optional[str] = None - metadata: Optional[Dict[str, Any]] = None +# app/tables/files/schemas.py +from typing import Optional, Any, Dict +from pydantic import BaseModel, Field, NonNegativeInt + + +class FilesCreate(BaseModel): + bucket: str + object_key: str = Field(alias="object_key") + content_type: Optional[str] = None + size_bytes: Optional[NonNegativeInt] = None + etag: Optional[str] = None + mission_id: Optional[int] = None + device_id: Optional[str] = None + tile_id: Optional[str] = None + footprint: Optional[str] = None # WKT + metadata: Optional[Dict[str, Any]] = None + + class Config: + populate_by_name = True + + +class FilesUpdate(BaseModel): + content_type: Optional[str] = None + size_bytes: Optional[NonNegativeInt] = None + etag: Optional[str] = None + mission_id: Optional[int] = None + device_id: Optional[str] = None + tile_id: Optional[str] = None + footprint: Optional[str] = None + metadata: Optional[Dict[str, Any]] = None diff --git a/services/db_api_service/app/tables/generic/repo.py b/services/db_api_service/app/tables/generic/repo.py index 5b19aa6e2..0306b5172 100644 --- a/services/db_api_service/app/tables/generic/repo.py +++ b/services/db_api_service/app/tables/generic/repo.py @@ -234,9 +234,28 @@ def list_rows( stmt = stmt.order_by(asc(col) if order_dir.lower().startswith("asc") else desc(col)) # filters (only allow known columns) if filters: + contract = _load_contract(resource) + props = contract.get("properties", {}) for k, v in filters.items(): if k not in allowed_cols: raise ValidationFailed("invalid filter key", {"key": k}) + # Cast filter value to correct type based on contract + prop = props.get(k, {}) + t = (prop.get("type") or "string").lower() + fmt = (prop.get("format") or "").lower() + try: + if t == "integer": + v = int(v) + elif t == "number": + v = float(v) + elif t == "boolean": + if isinstance(v, str): + v = v.lower() in ("true", "1", "yes") + else: + v = bool(v) + # Add more type conversions if needed + except Exception: + raise ValidationFailed(f"Failed to cast filter value for {k} to {t}", {"value": v}) stmt = stmt.where(table.c[k] == v) try: diff --git a/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/repo.py b/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/repo.py index 0f96921c0..4060d1d26 100644 --- a/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/repo.py +++ b/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/repo.py @@ -1,40 +1,40 @@ -from typing import Optional, Dict, Any, List -from sqlalchemy import text -from app.db import session_scope -from datetime import datetime - - -def list_rollups(from_ts: str | None = None, to_ts: str | None = None) -> List[Dict[str, Any]]: - q = """ - SELECT * FROM ripeness_weekly_rollups_ts - WHERE 1=1 - """ - params: Dict[str, Any] = {} - - if from_ts: - q += " AND ts >= :from_ts" - params["from_ts"] = parse_ts(from_ts) - if to_ts: - q += " AND ts <= :to_ts" - params["to_ts"] = parse_ts(to_ts) - - q += " ORDER BY ts DESC" - - with session_scope() as s: - rows = s.execute(text(q), params).mappings().all() - return [dict(r) for r in rows] - - -def get_rollup(id: int) -> Optional[Dict[str, Any]]: - """ - Retrieve a single rollup entry by ID. - """ - sql = text(""" - SELECT id, ts, window_start, window_end, fruit_type, device_id, - run_id, cnt_total, cnt_ripe, cnt_unripe, cnt_overripe, pct_ripe - FROM public.ripeness_weekly_rollups_ts - WHERE id = :id - """) - with session_scope() as s: - row = s.execute(sql, {"id": id}).mappings().first() - return dict(row) if row else None +from typing import Optional, Dict, Any, List +from sqlalchemy import text +from app.db import session_scope +from datetime import datetime + + +def list_rollups(from_ts: str | None = None, to_ts: str | None = None) -> List[Dict[str, Any]]: + q = """ + SELECT * FROM ripeness_weekly_rollups_ts + WHERE 1=1 + """ + params: Dict[str, Any] = {} + + if from_ts: + q += " AND ts >= :from_ts" + params["from_ts"] = parse_ts(from_ts) + if to_ts: + q += " AND ts <= :to_ts" + params["to_ts"] = parse_ts(to_ts) + + q += " ORDER BY ts DESC" + + with session_scope() as s: + rows = s.execute(text(q), params).mappings().all() + return [dict(r) for r in rows] + + +def get_rollup(id: int) -> Optional[Dict[str, Any]]: + """ + Retrieve a single rollup entry by ID. + """ + sql = text(""" + SELECT id, ts, window_start, window_end, fruit_type, device_id, + run_id, cnt_total, cnt_ripe, cnt_unripe, cnt_overripe, pct_ripe + FROM public.ripeness_weekly_rollups_ts + WHERE id = :id + """) + with session_scope() as s: + row = s.execute(sql, {"id": id}).mappings().first() + return dict(row) if row else None diff --git a/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/router.py b/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/router.py index 9a222b4d2..c0a11db18 100644 --- a/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/router.py +++ b/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/router.py @@ -1,33 +1,33 @@ - -from typing import Optional, List -from fastapi import APIRouter, HTTPException, Query -from . import schemas, repo - -router = APIRouter(prefix="/ripeness_weekly_rollups_ts", tags=["ripeness_weekly_rollups_ts"]) - -@router.get("", response_model=List[schemas.RipenessWeeklyRollupRead]) -def list_rollups( - from_ts: Optional[str] = Query(None, description="Filter from timestamp (ISO8601)"), - to_ts: Optional[str] = Query(None, description="Filter to timestamp (ISO8601)"), -): - """ - Retrieve weekly ripeness rollups by time range. - """ - try: - rows = repo.list_rollups(from_ts=from_ts, to_ts=to_ts) - return rows - except Exception as e: - print(f"[ERROR][router] list_rollups failed: {e}") - raise HTTPException(status_code=400, detail=str(e)) - - -@router.get("/{id}", response_model=schemas.RipenessWeeklyRollupOut) -def get_rollup(id: int): - """ - Retrieve a specific rollup entry by ID. - """ - row = repo.get_rollup(id) - if not row: - raise HTTPException(status_code=404, detail="Rollup not found") - return row - + +from typing import Optional, List +from fastapi import APIRouter, HTTPException, Query +from . import schemas, repo + +router = APIRouter(prefix="/ripeness_weekly_rollups_ts", tags=["ripeness_weekly_rollups_ts"]) + +@router.get("", response_model=List[schemas.RipenessWeeklyRollupRead]) +def list_rollups( + from_ts: Optional[str] = Query(None, description="Filter from timestamp (ISO8601)"), + to_ts: Optional[str] = Query(None, description="Filter to timestamp (ISO8601)"), +): + """ + Retrieve weekly ripeness rollups by time range. + """ + try: + rows = repo.list_rollups(from_ts=from_ts, to_ts=to_ts) + return rows + except Exception as e: + print(f"[ERROR][router] list_rollups failed: {e}") + raise HTTPException(status_code=400, detail=str(e)) + + +@router.get("/{id}", response_model=schemas.RipenessWeeklyRollupOut) +def get_rollup(id: int): + """ + Retrieve a specific rollup entry by ID. + """ + row = repo.get_rollup(id) + if not row: + raise HTTPException(status_code=404, detail="Rollup not found") + return row + diff --git a/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/schemas.py b/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/schemas.py index a4f899a32..5fbbbfce4 100644 --- a/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/schemas.py +++ b/services/db_api_service/app/tables/ripeness_weekly_rollups_ts/schemas.py @@ -1,36 +1,36 @@ -from datetime import datetime -from typing import Optional -from uuid import UUID -from pydantic import BaseModel, Field, conint, confloat - - -class RipenessWeeklyRollupBase(BaseModel): - """Base schema for weekly ripeness rollups table.""" - ts: Optional[datetime] = Field(None, description="Insertion timestamp") - window_start: datetime = Field(..., description="Start of weekly window") - window_end: datetime = Field(..., description="End of weekly window") - fruit_type: str = Field(..., description="Type of fruit analyzed") - device_id: Optional[str] = Field(None, description="Source device ID") - run_id: UUID = Field(..., description="Unique identifier for the run") # ? UUID instead of str - cnt_total: conint(ge=0) = Field(..., description="Total fruit count in window") - cnt_ripe: conint(ge=0) = Field(..., description="Ripe fruit count") - cnt_unripe: conint(ge=0) = Field(..., description="Unripe fruit count") - cnt_overripe: conint(ge=0) = Field(..., description="Overripe fruit count") - pct_ripe: confloat(ge=0, le=1) = Field(..., description="Ripe ratio (0-1)") - - -class RipenessWeeklyRollupCreate(RipenessWeeklyRollupBase): - """Schema used for POST inserts (single or batch).""" - pass - - -class RipenessWeeklyRollupRead(RipenessWeeklyRollupBase): - """Schema used for GET responses (includes DB ID).""" - id: int = Field(..., description="Primary key ID") - - class Config: - orm_mode = True - -class RipenessWeeklyRollupOut(RipenessWeeklyRollupBase): - id: int - +from datetime import datetime +from typing import Optional +from uuid import UUID +from pydantic import BaseModel, Field, conint, confloat + + +class RipenessWeeklyRollupBase(BaseModel): + """Base schema for weekly ripeness rollups table.""" + ts: Optional[datetime] = Field(None, description="Insertion timestamp") + window_start: datetime = Field(..., description="Start of weekly window") + window_end: datetime = Field(..., description="End of weekly window") + fruit_type: str = Field(..., description="Type of fruit analyzed") + device_id: Optional[str] = Field(None, description="Source device ID") + run_id: UUID = Field(..., description="Unique identifier for the run") # ? UUID instead of str + cnt_total: conint(ge=0) = Field(..., description="Total fruit count in window") + cnt_ripe: conint(ge=0) = Field(..., description="Ripe fruit count") + cnt_unripe: conint(ge=0) = Field(..., description="Unripe fruit count") + cnt_overripe: conint(ge=0) = Field(..., description="Overripe fruit count") + pct_ripe: confloat(ge=0, le=1) = Field(..., description="Ripe ratio (0-1)") + + +class RipenessWeeklyRollupCreate(RipenessWeeklyRollupBase): + """Schema used for POST inserts (single or batch).""" + pass + + +class RipenessWeeklyRollupRead(RipenessWeeklyRollupBase): + """Schema used for GET responses (includes DB ID).""" + id: int = Field(..., description="Primary key ID") + + class Config: + orm_mode = True + +class RipenessWeeklyRollupOut(RipenessWeeklyRollupBase): + id: int + diff --git a/services/db_api_service/app/tables/task_thresholds/repo.py b/services/db_api_service/app/tables/task_thresholds/repo.py index 010335f8e..3105e4c24 100644 --- a/services/db_api_service/app/tables/task_thresholds/repo.py +++ b/services/db_api_service/app/tables/task_thresholds/repo.py @@ -1,8 +1,40 @@ from __future__ import annotations -from typing import Any, Dict, List, Tuple +from typing import Any, Dict, List, Tuple,Optional from sqlalchemy import text from app.db import session_scope +def list_all() -> list[dict]: + q = text(""" + SELECT + task::text AS task, + label, + threshold, + updated_by, + updated_at + FROM task_thresholds + ORDER BY task, label; + """) + with session_scope() as s: + rows = s.execute(q).mappings().all() + return [dict(r) for r in rows] + +def get_one(task: str, label: Optional[str] = "") -> Optional[dict]: + # If you maintain a unique (task, label) pair – keep label; otherwise label can be ignored + q = text(""" + SELECT + task::text AS task, + label, + threshold, + updated_by, + updated_at + FROM task_thresholds + WHERE task = CAST(:task AS task_type_enum) + AND label = :label + LIMIT 1; + """) + with session_scope() as s: + row = s.execute(q, {"task": task, "label": label or ""}).mappings().first() + return dict(row) if row else None def upsert_one(task: str, label: str, threshold: float, updated_by: str | None) -> None: @@ -24,7 +56,7 @@ def upsert_one(task: str, label: str, threshold: float, updated_by: str | None) def upsert_batch(items: List[Dict[str, Any]]) -> Dict[str, Any]: """ items: [{"task": "...", "label": "", "threshold": 0.8, "updated_by": "gui"}, ...] - מחזיר {"ok": [[task,label], ...], "fail": [[[task,label], "reason"], ...]} + {"ok": [[task,label], ...], "fail": [[[task,label], "reason"], ...]} """ ok: List[List[str]] = [] fail: List[List[Any]] = [] diff --git a/services/db_api_service/app/tables/task_thresholds/router.py b/services/db_api_service/app/tables/task_thresholds/router.py index 4ef374511..da842e66b 100644 --- a/services/db_api_service/app/tables/task_thresholds/router.py +++ b/services/db_api_service/app/tables/task_thresholds/router.py @@ -4,6 +4,21 @@ router = APIRouter(prefix="/task_thresholds", tags=["task_thresholds"]) +@router.get("", response_model=List[dict]) +def list_thresholds(): + try: + return repo.list_all() # returns [{task, label, threshold, updated_by, ...}, ...] + except Exception as e: + print("[ERROR] list_thresholds failed:", e, flush=True) + raise HTTPException(status_code=500, detail=str(e)) + +@router.get("/{task}", response_model=dict) +def get_threshold(task: str): + row = repo.get_one(task) + if not row: + raise HTTPException(status_code=404, detail="task not found") + return row + @router.post("", status_code=201) def upsert_threshold( task: str, diff --git a/services/db_api_service/requirements.txt b/services/db_api_service/requirements.txt index 662d455a3..b37f0a4b6 100644 --- a/services/db_api_service/requirements.txt +++ b/services/db_api_service/requirements.txt @@ -1,15 +1,14 @@ - -python-multipart==0.0.9 -python-dotenv>=1.0.0 -fastapi==0.115.0 -uvicorn[standard]==0.30.6 -SQLAlchemy==2.0.36 -psycopg[binary]==3.2.1 -python-jose==3.3.0 -passlib==1.7.4 -bcrypt==4.0.1 -pydantic>=2.7 -pydantic-settings>=2.0 -pathlib -jsonschema - +python-multipart==0.0.9 +python-dotenv>=1.0.0 +fastapi==0.115.0 +uvicorn[standard]==0.30.6 +SQLAlchemy==2.0.36 +psycopg[binary]==3.2.1 +python-jose==3.3.0 +passlib==1.7.4 +bcrypt==4.0.1 +pydantic>=2.7 +pydantic-settings>=2.0 +pathlib +jsonschema>=4.18,<5 +requests>=2.31.0 diff --git a/services/db_api_service/tests/conftest.py b/services/db_api_service/tests/conftest.py index 1ebb58510..15b704bfe 100644 --- a/services/db_api_service/tests/conftest.py +++ b/services/db_api_service/tests/conftest.py @@ -31,7 +31,6 @@ def client_overridden_auth(): app.dependency_overrides[auth_mod.require_auth] = lambda: ("service", SimpleNamespace(name="tests")) try: with TestClient(app) as c: - # גם כאן נוודא מוכנות (ליתר בטחון) r0 = c.get("/ready") assert r0.status_code == 200 and r0.json().get("ready") is True yield c diff --git a/services/fence_hole_detector/weights/best.onnx b/services/fence_hole_detector/weights/best.onnx new file mode 100644 index 000000000..fddf21ac1 Binary files /dev/null and b/services/fence_hole_detector/weights/best.onnx differ diff --git a/services/flink_writer_db/app.py b/services/flink_writer_db/app.py index 7e5d1eb92..ff13cf371 100644 --- a/services/flink_writer_db/app.py +++ b/services/flink_writer_db/app.py @@ -1,27 +1,33 @@ -import os, json, pathlib, requests +import os, json, pathlib, requests, queue, threading from pyflink.common import Types from pyflink.datastream import StreamExecutionEnvironment from pyflink.datastream.connectors.kafka import KafkaSource from pyflink.common.serialization import SimpleStringSchema from pyflink.common.watermark_strategy import WatermarkStrategy +from pyflink.common import Configuration from requests.adapters import HTTPAdapter from urllib3.util.retry import Retry -# ---------- ENV ---------- +# ------------------------- ENV ------------------------- + DB_API_BASE = os.getenv("DB_API_BASE", "http://db_api_service:8001") -DB_API_AUTH_MODE = os.getenv("DB_API_AUTH_MODE", "service") +DB_API_AUTH_MODE = os.getenv("DB_API_AUTH_MODE", "service") DB_API_TOKEN_FILE = os.getenv("DB_API_TOKEN_FILE", "/opt/app/secrets/db_api_token") DB_API_SERVICE_NAME = os.getenv("DB_API_SERVICE_NAME", "flink-writer-db") DUMMY_DB = int(os.getenv("DUMMY_DB", "0")) == 1 KAFKA_BROKERS = os.getenv("KAFKA_BROKERS", "kafka:9092") -TOPICS = [t.strip() for t in os.getenv("TOPICS", "sensor_anomalies,alerts,image_new_aerial_connections,sound_new_sounds_connections,sound_new_plants_connections").split(",") if t.strip()] +TOPICS = [t.strip() for t in os.getenv( + "TOPICS", + "sensor_anomalies,alerts,image_new_aerial_connections,sound_new_sounds_connections," + "sound_new_plants_connections,sounds_metadata,sounds_ultra_metadata" +).split(",") if t.strip()] + +# ------------------------- TOKEN BOOTSTRAP ------------------------- -# ---------- Token Bootstrap ---------- def _safe_join_url(base: str, path: str) -> str: return f"{base.rstrip('/')}/{path.lstrip('/')}" - def _read_token_from_file(path: str) -> str | None: try: p = pathlib.Path(path) @@ -32,13 +38,11 @@ def _read_token_from_file(path: str) -> str | None: pass return None - def _write_token_to_file(path: str, token: str) -> None: p = pathlib.Path(path) p.parent.mkdir(parents=True, exist_ok=True) p.write_text(token, encoding="utf-8") - def _fetch_token_via_dev_bootstrap(base: str, retries: int = 3, backoff: float = 0.8) -> str | None: url = _safe_join_url(base, "/auth/_dev_bootstrap") payload = {"service_name": DB_API_SERVICE_NAME, "rotate_if_exists": True} @@ -46,93 +50,162 @@ def _fetch_token_via_dev_bootstrap(base: str, retries: int = 3, backoff: float = try: r = requests.post(url, json=payload, timeout=10) if r.status_code not in (200, 201): - import time - time.sleep(backoff * attempt) + import time; time.sleep(backoff * attempt) continue data = r.json() - raw = (data.get("service_account", {}) or {}).get("raw_token") \ + raw = ( + (data.get("service_account", {}) or {}).get("raw_token") or (data.get("service_account", {}) or {}).get("token") + ) if raw and isinstance(raw, str) and raw.strip() and "***" not in raw: return raw.strip() except Exception: - import time - time.sleep(backoff * attempt) + import time; time.sleep(backoff * attempt) return None - def get_or_bootstrap_token() -> str | None: token = _read_token_from_file(DB_API_TOKEN_FILE) if token: return token if not DB_API_BASE: - print("[BOOTSTRAP][WARN] DB_API_BASE not set; cannot bootstrap token.", flush=True) + print("[BOOTSTRAP][WARN] DB_API_BASE not set", flush=True) return None token = _fetch_token_via_dev_bootstrap(DB_API_BASE) if token: _write_token_to_file(DB_API_TOKEN_FILE, token) print(f"[BOOTSTRAP] wrote service token to {DB_API_TOKEN_FILE}", flush=True) return token - print("[BOOTSTRAP][ERROR] Failed to obtain service token (dev bootstrap).", flush=True) + print("[BOOTSTRAP][ERROR] Failed to obtain service token", flush=True) return None +# ------------------------- SHARED HEADERS ------------------------- -# ---------- HTTP client ---------- -_http = requests.Session() -svc_token = get_or_bootstrap_token() -if svc_token: +shared_headers = {"Content-Type": "application/json"} +token_value = get_or_bootstrap_token() + +if token_value: if DB_API_AUTH_MODE == "service": - _http.headers.update({"X-Service-Token": svc_token}) + shared_headers["X-Service-Token"] = token_value else: - _http.headers.update({"Authorization": f"Bearer {svc_token}"}) -_http.headers.update({"Content-Type": "application/json"}) -_http.mount("http://", HTTPAdapter(max_retries=Retry(total=5, backoff_factor=0.5, status_forcelist=[500, 502, 503, 504]))) -_http.mount("https://", HTTPAdapter(max_retries=Retry(total=5, backoff_factor=0.5, status_forcelist=[500, 502, 503, 504]))) + shared_headers["Authorization"] = f"Bearer {token_value}" + +# ------------------------- PER-TOPIC WORKERS ------------------------- + +topic_workers = {} +topic_queues = {} +topic_worker_counts = {} +topic_scale_locks = {} + +MAX_WORKERS_PER_TOPIC = 5 +MIN_WORKERS_PER_TOPIC = 1 +SCALE_UP_THRESHOLD = 8000 +SCALE_DOWN_THRESHOLD = 2000 + +def build_retry_session(headers: dict): + s = requests.Session() + s.headers.update(headers) + + retry_cfg = Retry( + total=5, + backoff_factor=0.5, + status_forcelist=[500, 502, 503, 504] + ) + adapter = HTTPAdapter(max_retries=retry_cfg) + s.mount("http://", adapter) + s.mount("https://", adapter) + s.headers.update(headers) + return s + +def start_topic_worker(topic: str): + if topic not in topic_worker_counts: + topic_worker_counts[topic] = 0 + topic_scale_locks[topic] = threading.Lock() + + if topic not in topic_queues: + topic_queues[topic] = queue.Queue(maxsize=30000) + + q = topic_queues[topic] + + def spawn_worker(): + session = build_retry_session(shared_headers) + base = DB_API_BASE.rstrip("/") + url = f"{base}/api/tables/{topic}" + + def worker_loop(): + while True: + payload = q.get() + try: + r = session.post(url, json=payload, timeout=10) + if not (200 <= r.status_code < 300): + print(f"[DB][{topic}] Error {r.status_code}: {r.text[:150]}") + except Exception as e: + print(f"[DB][{topic}] Exception: {e}") + finally: + q.task_done() + + t = threading.Thread(target=worker_loop, daemon=True) + t.start() + topic_worker_counts[topic] += 1 + + if topic_worker_counts[topic] == 0: + spawn_worker() + + if topic not in topic_workers: + def autoscaler(): + while True: + size = q.qsize() + with topic_scale_locks[topic]: + if size > SCALE_UP_THRESHOLD and topic_worker_counts[topic] < MAX_WORKERS_PER_TOPIC: + spawn_worker() + + if size < SCALE_DOWN_THRESHOLD and topic_worker_counts[topic] > MIN_WORKERS_PER_TOPIC: + topic_worker_counts[topic] = max(topic_worker_counts[topic] - 1, MIN_WORKERS_PER_TOPIC) + import time + time.sleep(2) -# ---------- DB Writer ---------- -def write_to_db_api(table: str, payload: dict) -> bool: + t = threading.Thread(target=autoscaler, daemon=True) + t.start() + topic_workers[topic] = t + +def enqueue_for_db(topic: str, payload: dict) -> bool: if DUMMY_DB: - print(f"[DB-DUMMY] would POST to {DB_API_BASE or 'N/A'}/api/{table}: {json.dumps(payload, ensure_ascii=False)[:250]}", flush=True) + print(f"[DB-DUMMY] {topic}: {json.dumps(payload)[:200]}") return True - if not DB_API_BASE: - print("[DB][WARN] DB_API_BASE not set; skipping DB write.", flush=True) - return False + start_topic_worker(topic) + q = topic_queues[topic] - base = DB_API_BASE.rstrip("/") try: - r = _http.post(f"{base}/api/tables/{table}", json=payload, timeout=10) - if 200 <= r.status_code < 300: - print(f"[DB] wrote to {table} ", flush=True) - return True - print(f"[DB] POST failed ({table}): {r.status_code} {r.text[:200]}", flush=True) + q.put_nowait(payload) + return True + except queue.Full: + print(f"[WARN][{topic}] queue full - dropping") return False - except requests.ConnectionError as e: - print(f"[DB][WARN] API not reachable ({base}): {e}", flush=True) - except requests.Timeout as e: - print(f"[DB][WARN] API timeout ({base}): {e}", flush=True) - except requests.RequestException as e: - print(f"[DB][ERROR] {e}", flush=True) - return False +# ------------------------- MESSAGE HANDLER ------------------------- -# ---------- Flink Job ---------- def handle_message(topic: str, raw: str) -> bool: try: data = json.loads(raw) except json.JSONDecodeError: - print(f"[WARN] skip invalid JSON on topic={topic}: {raw[:150]!r}", flush=True) + print(f"[WARN] invalid JSON on topic={topic}") return False - ok = write_to_db_api(topic, data) - return ok + return enqueue_for_db(topic, data) +# ------------------------- MAIN FLINK JOB ------------------------- def main(): - env = StreamExecutionEnvironment.get_execution_environment() + conf = Configuration() + conf.set_string("restart-strategy", "fixed-delay") + conf.set_string("restart-strategy.fixed-delay.attempts", "9999") + conf.set_string("restart-strategy.fixed-delay.delay", "5 s") + + env = StreamExecutionEnvironment.get_execution_environment(conf) env.set_parallelism(int(os.getenv("FLINK_PARALLELISM", "1"))) for topic in TOPICS: - print(f"[FLINK] Listening on topic: {topic}", flush=True) + print(f"[FLINK] Listening on: {topic}", flush=True) source = ( KafkaSource.builder() @@ -140,14 +213,23 @@ def main(): .set_topics(topic) .set_group_id(f"flink-writer-db-{topic}") .set_value_only_deserializer(SimpleStringSchema()) + .set_property("allow.auto.create.topics", "true") + .set_property("metadata.max.age.ms", "10000") .build() ) - ds = env.from_source(source, WatermarkStrategy.no_watermarks(), f"kafka-{topic}") - ds.map(lambda raw, t=topic: handle_message(t, raw), output_type=Types.BOOLEAN()).print() + ds = env.from_source( + source, + WatermarkStrategy.no_watermarks(), + f"kafka-{topic}" + ) + + ds.map( + lambda raw, t=topic: handle_message(t, raw), + output_type=Types.BOOLEAN() + ).print() env.execute("flink-writer-db") - if __name__ == "__main__": - main() \ No newline at end of file + main() diff --git a/services/flink_writer_db/docker-compose.yml b/services/flink_writer_db/docker-compose.yml index 2951df5ec..376c39b88 100644 --- a/services/flink_writer_db/docker-compose.yml +++ b/services/flink_writer_db/docker-compose.yml @@ -9,7 +9,7 @@ services: container_name: flink_writer_db environment: - KAFKA_BROKERS=kafka:9092 - - TOPICS=files,image_new_aerial_connections,sound_new_sounds_connections,sound_new_plants_connections + - TOPICS=files,image_new_aerial_connections,sound_new_sounds_connections,sound_new_plants_connections,sounds_metadata,sounds_ultra_metadata,alerts - DB_API_BASE=http://db_api_service:8001 - DB_API_AUTH_MODE=service - DB_API_SERVICE_NAME=flink-writer-db diff --git a/services/fruit-orchestration/Dockerfile.airflow b/services/fruit-orchestration/Dockerfile.airflow new file mode 100644 index 000000000..7f5e87016 --- /dev/null +++ b/services/fruit-orchestration/Dockerfile.airflow @@ -0,0 +1,29 @@ +# Dockerfile.airflow (Option A: bake scripts into the image) +FROM apache/airflow:2.9.3-python3.11 + +USER root + +# 1) Base setup: certificates + dos2unix (useful for Windows) +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates dos2unix \ + && rm -rf /var/lib/apt/lists/* + +# 2) Netfree certificate (optional) — if file is missing, skip without failing +COPY certs/netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt +RUN test -s /usr/local/share/ca-certificates/netfree-ca.crt \ + && update-ca-certificates || echo "No Netfree CA - skipping" + +# 3) Create directories and set permissions +RUN mkdir -p /opt/airflow/dags /opt/airflow/scripts /opt/airflow/plugins /opt/airflow/logs \ + && chown -R airflow:0 /opt/airflow \ + && chmod -R g=u /opt/airflow + +# 4) Copy project scripts into the image +# Note: source path is ./scripts/ (not airflow/scripts) +COPY --chown=airflow:0 scripts/ /opt/airflow/scripts/ + +# 5) Convert CRLF to LF and make scripts executable +RUN dos2unix /opt/airflow/scripts/*.sh || true \ + && chmod +x /opt/airflow/scripts/*.sh || true + +USER airflow diff --git a/services/fruit-orchestration/dags/ag_compose_scheduler.py b/services/fruit-orchestration/dags/ag_compose_scheduler.py new file mode 100644 index 000000000..643eda5d5 --- /dev/null +++ b/services/fruit-orchestration/dags/ag_compose_scheduler.py @@ -0,0 +1,191 @@ +# dags/run_external_composes.py + +from airflow import DAG +from airflow.operators.bash import BashOperator +from airflow.operators.empty import EmptyOperator +from airflow.operators.python import BranchPythonOperator, get_current_context +from airflow.models import Variable +from datetime import datetime +import pendulum + +# Use Israel local timezone for correct weekday calculation +TZ = pendulum.timezone("Asia/Jerusalem") + +default_args = {"owner": "airflow"} + +with DAG( + dag_id="run_external_composes", + start_date=datetime(2024, 1, 1, tzinfo=TZ), + schedule="@daily", + catchup=False, + default_args=default_args, +) as dag: + + # ---------- Helpers to run docker compose (down / up-detached / curl / batch) ---------- + + def compose_down_task(task_id, service_dir, project, compose_file="docker-compose.yml"): + # Runs "docker compose down" via docker/compose image; also removes default network if left over + cmd = f""" + set -euo pipefail + cd {service_dir} + COMPOSE_IMAGE="docker/compose:latest" + + docker run --rm \ + -v /var/run/docker.sock:/var/run/docker.sock \ + --volumes-from "$HOSTNAME" \ + -w "{service_dir}" \ + $COMPOSE_IMAGE \ + -f {compose_file} -p {project} down -v --remove-orphans || true + + docker network rm {project}_default || true + """ + return BashOperator(task_id=task_id, bash_command=cmd) + + def compose_up_detached_task(task_id, service_dir, project, env_file=None, compose_file="docker-compose.yml"): + # Brings services up in detached mode after cleaning previous resources + env_part = f"--env-file {env_file}" if env_file else "" + cmd = f""" + set -euo pipefail + cd {service_dir} + export DOCKER_BUILDKIT=1 + COMPOSE_IMAGE="docker/compose:latest" + + docker run --rm -v /var/run/docker.sock:/var/run/docker.sock --volumes-from "$HOSTNAME" -w "{service_dir}" $COMPOSE_IMAGE -f {compose_file} -p {project} down -v --remove-orphans || true + docker network rm {project}_default || true + + docker run --rm \ + -v /var/run/docker.sock:/var/run/docker.sock \ + --volumes-from "$HOSTNAME" \ + -w "{service_dir}" \ + $COMPOSE_IMAGE \ + -f {compose_file} -p {project} {env_part} up -d --build + """ + return BashOperator(task_id=task_id, bash_command=cmd) + + def compose_run_batch_task(task_id, service_dir, project, service_name, env_file=None, compose_file="docker-compose.yml"): + # Runs a single service as a batch job; waits for completion and propagates its exit code + env_part = f"--env-file {env_file}" if env_file else "" + cmd = f""" + set -euo pipefail + cd {service_dir} + export DOCKER_BUILDKIT=1 + COMPOSE_IMAGE="docker/compose:latest" + + # Clean before run + docker run --rm -v /var/run/docker.sock:/var/run/docker.sock --volumes-from "$HOSTNAME" -w "{service_dir}" $COMPOSE_IMAGE -f {compose_file} -p {project} down -v --remove-orphans || true + docker network rm {project}_default || true + + # Run batch (non-detached) and return the service exit code to Airflow + docker run --rm \ + -v /var/run/docker.sock:/var/run/docker.sock \ + --volumes-from "$HOSTNAME" \ + -w "{service_dir}" \ + $COMPOSE_IMAGE \ + -f {compose_file} -p {project} {env_part} up --build --abort-on-container-exit --exit-code-from {service_name} + rc=$? + + # Cleanup after batch + docker run --rm -v /var/run/docker.sock:/var/run/docker.sock --volumes-from "$HOSTNAME" -w "{service_dir}" $COMPOSE_IMAGE -f {compose_file} -p {project} down -v --remove-orphans + exit $rc + """ + return BashOperator(task_id=task_id, bash_command=cmd) + + def curl_inside_network_task(task_id, url, docker_network): + # Waits for a known HTTP endpoint inside a Docker network, then performs the POST + cmd = f""" + set -euo pipefail + + # Wait for service health check (max ~120 seconds) + for i in $(seq 1 60); do + if docker run --rm --network {docker_network} curlimages/curl:8.10.1 -fsS http://ripeness-api:8088/healthz >/dev/null; then + echo "ripeness-api is healthy" + break + fi + echo "waiting for ripeness-api..." + sleep 2 + done + + # Actual POST request + docker run --rm --network {docker_network} curlimages/curl:8.10.1 \ + --retry 5 --retry-delay 2 --fail-with-body \ + -X POST {url} + echo + """ + return BashOperator(task_id=task_id, bash_command=cmd) + + # ---------- Daily classifier job (runs normally every day) ---------- + run_classifier = BashOperator( + task_id="run_classifier_compose", + bash_command=""" + set -euo pipefail + cd /opt/services/classifier + export DOCKER_BUILDKIT=1 + COMPOSE_IMAGE="docker/compose:latest" + + docker run --rm -v /var/run/docker.sock:/var/run/docker.sock --volumes-from "$HOSTNAME" -w "/opt/services/classifier" $COMPOSE_IMAGE -f docker-compose.yml -p classifier_job down -v --remove-orphans || true + docker network rm classifier_job_default || true + + # Run batch (not detached, wait for completion) + docker run --rm -v /var/run/docker.sock:/var/run/docker.sock --volumes-from "$HOSTNAME" -w "/opt/services/classifier" $COMPOSE_IMAGE -f docker-compose.yml -p classifier_job --env-file .env up --build --abort-on-container-exit --exit-code-from batch + rc=$? + + # Cleanup after batch + docker run --rm -v /var/run/docker.sock:/var/run/docker.sock --volumes-from "$HOSTNAME" -w "/opt/services/classifier" $COMPOSE_IMAGE -f docker-compose.yml -p classifier_job down -v --remove-orphans + exit $rc + """ + ) + + # ---------- Weekly branch: only continue on specific weekday ---------- + def should_post(): + """Run the weekly chain only on the selected weekday; otherwise skip.""" + ctx = get_current_context() + now_local = ctx["logical_date"].in_timezone(TZ) + + # Variable allows custom weekday (1=Mon .. 7=Sun), default=2 (Tuesday) + target_dow = int(Variable.get("ripeness_weekly_dow", default_var="3")) + print(f"[weekly_gate] logical_date={now_local}, isoweekday={now_local.isoweekday()}, target={target_dow}") + return "ripeness_up" if now_local.isoweekday() == target_dow else "skip_weekly" + + weekly_gate = BranchPythonOperator( + task_id="weekly_gate", + python_callable=should_post, + ) + + skip_weekly = EmptyOperator(task_id="skip_weekly") + + # ---------- Ripeness chain (runs only on the weekly day) ---------- + ripeness_up = compose_up_detached_task( + task_id="ripeness_up", + service_dir="/opt/services/ripeness", + project="ripeness_job", + env_file=".env", + compose_file="docker-compose.yml" + ) + + ripeness_call = curl_inside_network_task( + task_id="ripeness_call_predict_last_week", + url="http://ripeness-api:8088/predict-last-week", + docker_network="ag_cloud" # Must match the external Docker network name + ) + + ripeness_down = compose_down_task( + task_id="ripeness_down", + service_dir="/opt/services/ripeness", + project="ripeness_job", + compose_file="docker-compose.yml" + ) + + # ---------- Fruit ripeness alert (weekly batch run, runs AFTER ripeness chain) ---------- + alerts_run = compose_run_batch_task( + task_id="alerts_run", + service_dir="/opt/services/fruit_ripeness_alert", + project="fruit_ripeness_alert_job", + service_name="fruit_ripeness_alert", # Service name from the compose file + env_file=None, # Set ".env" if you store secrets there + compose_file="docker-compose.yml" + ) + + # ---------- Dependencies ---------- + run_classifier >> weekly_gate + weekly_gate >> ripeness_up >> ripeness_call >> ripeness_down >> alerts_run + weekly_gate >> skip_weekly diff --git a/services/fruit-orchestration/docker-compose.yml b/services/fruit-orchestration/docker-compose.yml new file mode 100644 index 000000000..7c1786778 --- /dev/null +++ b/services/fruit-orchestration/docker-compose.yml @@ -0,0 +1,104 @@ +version: "3.8" + +services: + postgres: + image: postgres:15 + container_name: fruit-postgres + environment: + POSTGRES_USER: ${POSTGRES_USER} + POSTGRES_PASSWORD: ${POSTGRES_PASSWORD} + POSTGRES_DB: ${POSTGRES_DB} + volumes: + - postgres-db-volume:/var/lib/postgresql/data + healthcheck: + test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER} -d ${POSTGRES_DB}"] + interval: 5s + timeout: 5s + retries: 20 + networks: + - default + - agcloud_net + + airflow-init: + build: + context: . + dockerfile: Dockerfile.airflow + args: + ADD_NETFREE_CA: ${ADD_NETFREE_CA} + depends_on: + postgres: + condition: service_healthy + environment: + AIRFLOW__CORE__EXECUTOR: LocalExecutor + AIRFLOW__CORE__LOAD_EXAMPLES: "false" + AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: ${AIRFLOW__DATABASE__SQL_ALCHEMY_CONN} + AIRFLOW__WEBSERVER__SECRET_KEY: ${AIRFLOW__WEBSERVER__SECRET_KEY} + AIRFLOW__CORE__FERNET_KEY: ${AIRFLOW__CORE__FERNET_KEY} + _AIRFLOW_WWW_USER_USERNAME: ${_AIRFLOW_WWW_USER_USERNAME} + _AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD} + volumes: + - ./dags:/opt/airflow/dags + - ./services:/opt/services:ro + - ./scripts:/opt/airflow/scripts:ro + - ./plugins:/opt/airflow/plugins + - ./logs:/opt/airflow/logs + - /var/run/docker.sock:/var/run/docker.sock + command: > + bash -lc "airflow db migrate && airflow users create --username ${_AIRFLOW_WWW_USER_USERNAME} --firstname Admin --lastname User --role Admin --email admin@example.org --password ${_AIRFLOW_WWW_USER_PASSWORD} || true" + + airflow-webserver: + build: + context: . + dockerfile: Dockerfile.airflow + args: + ADD_NETFREE_CA: ${ADD_NETFREE_CA} + depends_on: + postgres: + condition: service_healthy + environment: + AIRFLOW__CORE__EXECUTOR: LocalExecutor + AIRFLOW__CORE__LOAD_EXAMPLES: "false" + AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: ${AIRFLOW__DATABASE__SQL_ALCHEMY_CONN} + AIRFLOW__WEBSERVER__SECRET_KEY: ${AIRFLOW__WEBSERVER__SECRET_KEY} + AIRFLOW__CORE__FERNET_KEY: ${AIRFLOW__CORE__FERNET_KEY} + ports: + - "8085:8080" + volumes: + - ./dags:/opt/airflow/dags + - ./services:/opt/services + - ./scripts:/opt/airflow/scripts + - ./plugins:/opt/airflow/plugins + - ./logs:/opt/airflow/logs + - /var/run/docker.sock:/var/run/docker.sock + command: webserver + + airflow-scheduler: + build: + context: . + dockerfile: Dockerfile.airflow + args: + ADD_NETFREE_CA: ${ADD_NETFREE_CA} + depends_on: + postgres: + condition: service_healthy + environment: + AIRFLOW__CORE__EXECUTOR: LocalExecutor + AIRFLOW__CORE__LOAD_EXAMPLES: "false" + AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: ${AIRFLOW__DATABASE__SQL_ALCHEMY_CONN} + AIRFLOW__CORE__FERNET_KEY: ${AIRFLOW__CORE__FERNET_KEY} + volumes: + - ./dags:/opt/airflow/dags + - ./scripts:/opt/airflow/scripts + - /var/run/docker.sock:/var/run/docker.sock + - ./services:/opt/services + - ./plugins:/opt/airflow/plugins + - ./logs:/opt/airflow/logs + command: scheduler + +volumes: + postgres-db-volume: + +networks: + agcloud_net: + external: true + name: agcloud_ag_cloud diff --git a/services/fruit-orchestration/scripts/run_classifier.sh b/services/fruit-orchestration/scripts/run_classifier.sh new file mode 100644 index 000000000..cf5e93ffe --- /dev/null +++ b/services/fruit-orchestration/scripts/run_classifier.sh @@ -0,0 +1,14 @@ +#!/usr/bin/env bash +set -euo pipefail + +HOST_DATA_DIR="${HOST_DATA_DIR:-/data}" +IMAGES_DIR="${IMAGES_DIR:-/data/images}" +RUN_ID="${RUN_ID:-manual}" + +echo "[run_classifier] start | RUN_ID=${RUN_ID} | IMAGES_DIR=${IMAGES_DIR}" + +echo "[run_classifier] processing images under ${IMAGES_DIR} ..." +sleep 1 +echo "[run_classifier] done." + +exit 0 diff --git a/services/fruit-orchestration/scripts/run_ripeness.sh b/services/fruit-orchestration/scripts/run_ripeness.sh new file mode 100644 index 000000000..ae098fd5b --- /dev/null +++ b/services/fruit-orchestration/scripts/run_ripeness.sh @@ -0,0 +1,4 @@ +#!/usr/bin/env bash +set -euo pipefail +cd "${AIRFLOW_HOME}/services/ripeness" +docker compose up --build --abort-on-container-exit --exit-code-from ripeness diff --git a/services/fruit-orchestration/services/classifier/.dockerignore b/services/fruit-orchestration/services/classifier/.dockerignore new file mode 100644 index 000000000..77b0c25d3 --- /dev/null +++ b/services/fruit-orchestration/services/classifier/.dockerignore @@ -0,0 +1,12 @@ +.git +__pycache__ +*.pyc +*.pyo +*.log +*.DS_Store +venv +.venv +node_modules +dist +build +samples diff --git a/services/fruit-orchestration/services/classifier/.gitignore b/services/fruit-orchestration/services/classifier/.gitignore new file mode 100644 index 000000000..09568e037 --- /dev/null +++ b/services/fruit-orchestration/services/classifier/.gitignore @@ -0,0 +1,2 @@ +.env +.netfree-ca.crt \ No newline at end of file diff --git a/services/fruit-orchestration/services/classifier/Dockerfile b/services/fruit-orchestration/services/classifier/Dockerfile new file mode 100644 index 000000000..48234e0cc --- /dev/null +++ b/services/fruit-orchestration/services/classifier/Dockerfile @@ -0,0 +1,76 @@ +# ========================= +# Stage 1: Build Python wheels +# ========================= +FROM python:3.11-slim AS builder + +ARG HTTP_PROXY +ARG HTTPS_PROXY +ARG NO_PROXY +ARG TORCH_INDEX_URL="https://download.pytorch.org/whl/cpu" + +ENV PYTHONUNBUFFERED=1 \ + PYTHONDONTWRITEBYTECODE=1 \ + TZ=UTC + +WORKDIR /app + +RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates curl && \ + rm -rf /var/lib/apt/lists/* + +# <<< Add: Organization CA certificate >>> +COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt +RUN update-ca-certificates + +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt + +COPY requirements.txt . + +RUN pip install --upgrade pip +RUN pip install --no-cache-dir --index-url ${TORCH_INDEX_URL} \ + torch==2.3.1 torchvision==0.18.1 + +# Exclude torch and torchvision from the second requirements installation +RUN grep -viE '^(torch|torchvision)=' requirements.txt > req-no-torch.txt && \ + pip wheel --no-cache-dir --wheel-dir=/wheels -r req-no-torch.txt + + +# ========================= +# Stage 2: Runtime environment +# ========================= +FROM python:3.11-slim + +ARG HTTP_PROXY +ARG HTTPS_PROXY +ARG NO_PROXY + +ENV PYTHONUNBUFFERED=1 \ + PYTHONDONTWRITEBYTECODE=1 \ + TZ=UTC \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt + +WORKDIR /app + +RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates && \ + rm -rf /var/lib/apt/lists/* + +# <<< Add: Same CA certificate in runtime stage >>> +COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt +RUN update-ca-certificates + +# Install dependencies from Stage 1 (including torch) + wheels +COPY --from=builder /usr/local/lib/python3.11/site-packages /usr/local/lib/python3.11/site-packages +COPY --from=builder /wheels /wheels +RUN pip install --no-cache-dir /wheels/* && rm -rf /wheels + + +# Copy project files +COPY . /app + +# Create non-root user +RUN useradd -m appuser +USER appuser + +# Default command: run the batch inference +CMD ["python", "-m", "inference.infer_minio_batch"] diff --git a/services/fruit-orchestration/services/classifier/README.md b/services/fruit-orchestration/services/classifier/README.md new file mode 100644 index 000000000..bc4853e6a --- /dev/null +++ b/services/fruit-orchestration/services/classifier/README.md @@ -0,0 +1,85 @@ +🥭 Fruit Classification – Inference Service + +This service performs batch inference for fruit classification using a trained PyTorch model. +It connects to MinIO for input images and logs results into PostgreSQL. + +⚙️ 1. Environment Configuration + +Create a .env file in the project root with the following variables: + +# --- MinIO Connection --- +S3_ENDPOINT=http://host.docker.internal:9000 +S3_ACCESS_KEY=minioadmin +S3_SECRET_KEY=minioadmin +S3_SECURE=false +S3_BUCKET=classification +S3_PREFIX=samples + +# --- Model & Config Paths --- +WEIGHTS_PATH=models/best.pt +LABELS_PATH=models/labels.json +CFG_PATH=configs/fruit_cls.yaml + +# --- Database Connection --- +DATABASE_URL=postgresql://missions_user:pg123@host.docker.internal:5432/missions_db?sslmode=disable + + +🧠 Tip: +If your PostgreSQL or MinIO services run on external servers, update host.docker.internal to the relevant hostname or IP. + +🔒 2. Certificates (Optional) + +If your environment requires SSL interception (e.g., behind filtered networks like NetFree), +add the certificate file (e.g. netfree-ca.crt) to the project root — +it will be installed into the Docker image automatically. + +🐳 3. Build the Docker Image +docker compose build + +▶️ 4. Run the Service +docker compose up + + +This will: + +Load the model and configuration. + +Fetch images from MinIO (s3://classification/samples/...). + +Perform inference. + +Write classification results to the PostgreSQL inference_logs table. + +✅ 5. Prerequisites Checklist + +Before running the service, make sure you have: + +Component Requirement +PostgreSQL A database named missions_db containing a table inference_logs. +MinIO Bucket: classification, prefix: samples/. +Data Folder Structure samples//// containing image files. + +Example MinIO path: + +classification/ + └── samples/ + └── 2025/ + └── 10/ + └── 15/ + ├── apple1.png + ├── freshGrape (7).jpg + └── ... + +🧩 Example Output +[INFO] s3://classification/samples/2025/10/15/ | secure=False +{"object": "samples/2025/10/15/apple1.png", "fruit_type": "Apple", "score": 0.9258} +{"object": "samples/2025/10/15/freshOrange.png", "fruit_type": "Orange", "score": 0.9123} +[DONE] processed=25 | date=2025-10-15 + +🛠️ Notes + +The service automatically retries MinIO connections. + +Database inserts are skipped if the connection fails (with a warning). + +To rebuild dependencies or configuration, use docker compose up --build. \ No newline at end of file diff --git a/services/fruit-orchestration/services/classifier/configs/fruit_cls.yaml b/services/fruit-orchestration/services/classifier/configs/fruit_cls.yaml new file mode 100644 index 000000000..ef0495fc2 --- /dev/null +++ b/services/fruit-orchestration/services/classifier/configs/fruit_cls.yaml @@ -0,0 +1,46 @@ +seed: 42 +device: cpu # 'cpu' or 'cuda' if available +num_workers: 4 + +# Data +image_size: 224 +batch_size: 64 +val_batch_size: 128 +train_split: 0.9 # if building split from MinIO set + +# Model +backbone: mobilenet_v3_small # options: mobilenet_v3_small, efficientnet_b0, clip_mini +pretrained: true +freeze_backbone: false +num_epochs: 15 +learning_rate: 0.001 +weight_decay: 0.0001 +label_smoothing: 0.1 + +# Augmentations (baseline: torchvision) +augment: + brightness: 0.3 + contrast: 0.3 + saturation: 0.2 + hue: 0.05 + random_resized_crop_scale: [0.7, 1.0] + random_erasing_p: 0.25 + horizontal_flip_p: 0.5 + color_jitter_p: 0.8 + +# MinIO / dataset +s3: + endpoint: ${S3_ENDPOINT} + access_key: ${S3_ACCESS_KEY} + secret_key: ${S3_SECRET_KEY} + secure: ${S3_SECURE} + bucket: ${S3_BUCKET} + prefix: ${S3_PREFIX} + artifacts_bucket: ${ARTIFACTS_BUCKET} + artifacts_prefix: ${ARTIFACTS_PREFIX} + data_cache_dir: ${DATA_CACHE_DIR} + +# Few-shot add-class (optional, classification via nearest-centroid in embedding space) +few_shot: + enabled: false + shots_per_class: 5 diff --git a/services/fruit-orchestration/services/classifier/docker-compose.yml b/services/fruit-orchestration/services/classifier/docker-compose.yml new file mode 100644 index 000000000..43ae27229 --- /dev/null +++ b/services/fruit-orchestration/services/classifier/docker-compose.yml @@ -0,0 +1,16 @@ +version: "3.8" +services: + batch: + build: + context: . + dockerfile: Dockerfile + args: + TORCH_INDEX_URL: "https://download.pytorch.org/whl/cpu" + container_name: fruit-batch + env_file: .env + # volumes: + # - .:/app + restart: "no" + command: ["python", "-m", "inference.infer_minio_batch", "--limit", "100"] + + diff --git a/services/fruit-orchestration/services/classifier/inference/infer_minio_batch.py b/services/fruit-orchestration/services/classifier/inference/infer_minio_batch.py new file mode 100644 index 000000000..00df42eeb --- /dev/null +++ b/services/fruit-orchestration/services/classifier/inference/infer_minio_batch.py @@ -0,0 +1,202 @@ +import argparse +import io +import json +import os +from datetime import date, datetime +from pathlib import Path +from typing import Iterable, Tuple + +import torch +import torch.nn.functional as F +from PIL import Image +from dotenv import load_dotenv +from minio import Minio +from minio.deleteobjects import DeleteObject +from time import perf_counter + + +from inference.utils_infer import build_infer_transforms, load_model + +# Optional: DB logging (graceful if missing) +try: + from metrics_db.db import insert_inference_log + DB_AVAILABLE = True +except Exception: + DB_AVAILABLE = False + + +def make_minio_client(endpoint: str, access_key: str, secret_key: str, + secure: bool) -> Minio: + ep = endpoint.replace("http://", "").replace("https://", "") + return Minio(ep, access_key=access_key, secret_key=secret_key, secure=secure) + + +def list_images(client: Minio, bucket: str, prefix: str) -> Iterable[str]: + exts = {".jpg", ".jpeg", ".png", ".bmp", ".webp"} + for obj in client.list_objects(bucket, prefix=prefix, recursive=True): + name = obj.object_name + if Path(name).suffix.lower() in exts: + yield name + + +def load_labels(labels_path: str) -> Tuple[dict, dict]: + with open(labels_path, "r", encoding="utf-8") as f: + labels_map = json.load(f) + if all(isinstance(k, str) for k in labels_map.keys()): + idx_to_class = {int(v): str(k) for k, v in labels_map.items()} + else: + idx_to_class = {int(k): str(v) for k, v in labels_map.items()} + return labels_map, idx_to_class + + +def build_cfg(cfg_path: str) -> dict: + import yaml + with open(cfg_path, "r", encoding="utf-8") as f: + return yaml.safe_load(f) + + +def classify_bytes(model, tfms, idx_to_class: dict, file_bytes: bytes): + + img = Image.open(io.BytesIO(file_bytes)).convert("RGB") + x = tfms(img).unsqueeze(0) + model.eval() + with torch.no_grad(): + logits = model(x) + probs = F.softmax(logits, dim=1) + score, pred = probs.max(dim=1) + return idx_to_class[int(pred.item())], float(score.item()) + + +def build_prefix(base_prefix: str, dt: date) -> str: + yyyy = f"{dt.year:04d}" + mm = f"{dt.month:02d}" + dd = f"{dt.day:02d}" + return f"{base_prefix.strip('/')}/{yyyy}/{mm}/{dd}/" + + +def build_minio_url(endpoint: str, bucket: str, object_name: str) -> str: + ep = endpoint if endpoint.startswith("http") else f"http://{endpoint}" + return f"{ep.rstrip('/')}/{bucket}/{object_name}" + + +def main(): + load_dotenv() + + p = argparse.ArgumentParser( + description="Batch inference from MinIO by YYYY/MM/DD folder" + ) + p.add_argument("--date", type=str, default=date.today().isoformat(), + help="YYYY-MM-DD (default: today)") + p.add_argument("--year", type=int, help="Alternative to --date: year") + p.add_argument("--month", type=int, help="Alternative to --date: month") + p.add_argument("--day", type=int, help="Alternative to --date: day") + p.add_argument("--dry-run", action="store_true", + help="Print only, do not write DB") + p.add_argument("--limit", type=int, default=0, + help="Limit number of images (0 = no limit)") + p.add_argument("--delete-ok", action="store_true", + help="Delete images from MinIO after success") + p.add_argument("--weights", type=str, + default=os.getenv("WEIGHTS_PATH", "models/best.pt")) + p.add_argument("--labels", type=str, + default=os.getenv("LABELS_PATH", "models/labels.json")) + p.add_argument("--cfg", type=str, + default=os.getenv("CFG_PATH", "configs/fruit_cls.yaml")) + args = p.parse_args() + + # Load cfg/model + cfg = build_cfg(args.cfg) + res = load_model(args.weights, args.labels, + backbone=cfg.get("backbone", "mobilenet_v3_small")) + model = res[0] if isinstance(res, tuple) else res + _, idx_to_class = load_labels(args.labels) + tfms = build_infer_transforms(cfg.get("image_size", 224)) + + # MinIO settings (ENV > YAML) + endpoint = os.getenv("S3_ENDPOINT", cfg["s3"]["endpoint"]) + access_key = os.getenv("S3_ACCESS_KEY", cfg["s3"]["access_key"]) + secret_key = os.getenv("S3_SECRET_KEY", cfg["s3"]["secret_key"]) + secure = str(os.getenv("S3_SECURE", cfg["s3"].get("secure", False)) + ).lower() == "true" + bucket = os.getenv("S3_BUCKET", cfg["s3"]["bucket"]) + base_prefix = os.getenv("S3_PREFIX", cfg["s3"].get("base_prefix", "images")) + + # Pick date + if args.year and args.month and args.day: + run_date = date(args.year, args.month, args.day) + else: + run_date = datetime.strptime(args.date, "%Y-%m-%d").date() + + day_prefix = build_prefix(base_prefix, run_date) + client = make_minio_client(endpoint, access_key, secret_key, secure) + + print(f"[INFO] s3://{bucket}/{day_prefix} | secure={secure}") + count, to_delete = 0, [] + + for object_name in list_images(client, bucket, day_prefix): + if args.limit and count >= args.limit: + break + + # Download + try: + resp = client.get_object(bucket, object_name) + data = resp.read() + resp.close() + resp.release_conn() + except Exception as e: + print(f"[WARN] download failed: {object_name} | {e}") + continue + + + try: + # Classify + + t0 = perf_counter() + cls, score = classify_bytes(model, tfms, idx_to_class, data) + t_ms = (perf_counter() - t0) * 1000.0 + + cls, score = classify_bytes(model, tfms, idx_to_class, data) + print(json.dumps({ + "object": object_name, + "fruit_type": cls, + "score": round(score, 4), + })) + + # DB log + if DB_AVAILABLE and not args.dry_run and os.getenv("DATABASE_URL"): + try: + image_url = build_minio_url(endpoint, bucket, object_name) + insert_inference_log( + model_backbone=cfg.get("backbone", "mobilenet_v3_small"), + image_size=cfg.get("image_size", 224), + fruit_type=str(cls), + score=float(score), + latency_ms=float(t_ms), + client_ip=f"minio-batch:{run_date.isoformat()}", + error=None, + image_url=image_url, + ) + + except Exception as db_e: + print(f"[WARN] DB insert failed: {db_e}") + + # Delete after success if requested + if args.delete_ok: + to_delete.append(DeleteObject(object_name)) + + except Exception as e: + print(f"[ERR] classify failed: {object_name} | {e}") + + count += 1 + + # Bulk delete + if to_delete: + errors = client.remove_objects(bucket, to_delete) + for err in errors: + print(f"[WARN] delete failed: {err.object_name}: {err}") + + print(f"[DONE] processed={count} | date={run_date.isoformat()}") + + +if __name__ == "__main__": + main() diff --git a/services/fruit-orchestration/services/classifier/inference/service.py b/services/fruit-orchestration/services/classifier/inference/service.py new file mode 100644 index 000000000..5aea706e7 --- /dev/null +++ b/services/fruit-orchestration/services/classifier/inference/service.py @@ -0,0 +1,137 @@ +import os +import io +import json +import time +from typing import Tuple + +import torch +import torch.nn.functional as F +from PIL import Image + +from fastapi import FastAPI, UploadFile, File, HTTPException +from fastapi.responses import Response +from prometheus_client import Counter, Histogram, Gauge, generate_latest, CONTENT_TYPE_LATEST + +from dotenv import load_dotenv +load_dotenv() + +REQS = Counter("inference_requests_total", "Total inference requests") +ERRS = Counter("inference_errors_total", "Total inference errors") +LATENCY = Histogram("inference_latency_seconds", "Inference latency per image (seconds)") +LOADED = Gauge("model_loaded", "Model loaded (1=yes)") + +from inference.utils_infer import build_infer_transforms, load_model +from metrics_db.db import insert_inference_log + +app = FastAPI() + +MODEL = None +LABELS = None +TFMS = None +CFG = None + +def _load_labels(labels_path: str): + with open(labels_path, "r", encoding="utf-8") as f: + d = json.load(f) + idx_to_class = {int(v): k for k, v in d.items()} + return d, idx_to_class + +def preprocess_image(file_bytes: bytes) -> torch.Tensor: + img = Image.open(io.BytesIO(file_bytes)).convert("RGB") + x = TFMS(img) # [C,H,W] + x = x.unsqueeze(0) # [1,C,H,W] + return x + +def run_inference(model: torch.nn.Module, x: torch.Tensor, idx_to_class: dict) -> Tuple[str, float]: + model.eval() + with torch.no_grad(): + logits = model(x) + probs = F.softmax(logits, dim=1) + score, pred = probs.max(dim=1) # [1] + cls_idx = int(pred.item()) + cls_name = idx_to_class[cls_idx] + return cls_name, float(score.item()) + +@app.on_event("startup") +def on_startup(): + """ + Load config, model, labels, and transforms once at startup. + Supports load_model(...) returning either: + - model + - (model, labels_map) where labels_map is {class_name: idx} or {idx: class_name} + """ + global MODEL, LABELS, TFMS, CFG + + weights_path = os.environ["WEIGHTS_PATH"] + labels_path = os.environ["LABELS_PATH"] + cfg_path = os.environ["CFG_PATH"] + + import yaml + with open(cfg_path, "r", encoding="utf-8") as f: + CFG = yaml.safe_load(f) + + # --- load model (support both signatures) --- + res = load_model(weights_path, labels_path, backbone=CFG.get("backbone", "mobilenet_v3_small")) + if isinstance(res, tuple): + MODEL, labels_map = res + else: + MODEL = res + # fallback: load labels_map from file + with open(labels_path, "r", encoding="utf-8") as lf: + labels_map = json.load(lf) + + # labels_map can be {class_name: idx} OR {idx: class_name}. + # Normalize to idx_to_class: {int(idx): class_name} + if all(isinstance(k, str) for k in labels_map.keys()): + # assume {class_name: idx} + idx_to_class = {int(v): str(k) for k, v in labels_map.items()} + else: + # assume {idx: class_name} + idx_to_class = {int(k): str(v) for k, v in labels_map.items()} + + LABELS = labels_map + app.state.idx_to_class = idx_to_class + + # --- transforms --- + TFMS = build_infer_transforms(image_size=CFG.get("image_size", 224)) + + # ready + LOADED.set(1) + print("Startup OK | model loaded:", type(MODEL).__name__, + "| classes:", len(app.state.idx_to_class)) + + +@app.post("/infer") +async def infer(file: UploadFile = File(...)): + start = time.time() + try: + raw = await file.read() + x = preprocess_image(raw) + pred, score = run_inference(MODEL, x, app.state.idx_to_class) + REQS.inc() + latency_ms = (time.time() - start) * 1000.0 + LATENCY.observe(latency_ms / 1000.0) + + + try: + insert_inference_log( + model_backbone=CFG.get("backbone", "mobilenet_v3_small"), + image_size=CFG.get("image_size", 224), + fruit_type=str(pred), + score=float(score), + latency_ms=float(latency_ms), + client_ip="127.0.0.1", + error=None, + ) + except Exception as db_e: + print(f"[WARN] DB insert failed: {db_e}") + + return {"fruit_type": pred, "score": score, "latency_ms": round(latency_ms, 2)} + + except Exception as e: + ERRS.inc() + raise HTTPException(status_code=500, detail=f"Inference failed: {e}") + +@app.get("/metrics") +def metrics(): + return Response(generate_latest(), media_type=CONTENT_TYPE_LATEST) diff --git a/services/fruit-orchestration/services/classifier/inference/utils_infer.py b/services/fruit-orchestration/services/classifier/inference/utils_infer.py new file mode 100644 index 000000000..ef39c5bef --- /dev/null +++ b/services/fruit-orchestration/services/classifier/inference/utils_infer.py @@ -0,0 +1,46 @@ +import io +import json +from pathlib import Path +from typing import Dict, Tuple + +import torch +from PIL import Image +from torchvision import models, transforms + +def build_infer_transforms(image_size: int): + return transforms.Compose([ + transforms.Resize(int(image_size * 1.14)), + transforms.CenterCrop(image_size), + transforms.ToTensor(), + transforms.Normalize(mean=[0.485, 0.456, 0.406], + std=[0.229, 0.224, 0.225]), + ]) + +def load_model(weights_path: Path, labels_json: Path, backbone: str, device: str = "cpu"): + with open(labels_json, "r", encoding="utf-8") as f: + class_to_idx = json.load(f) + idx_to_class = {v: k for k, v in class_to_idx.items()} + + if backbone == "mobilenet_v3_small": + m = models.mobilenet_v3_small() + m.classifier[-1] = torch.nn.Linear(m.classifier[-1].in_features, len(idx_to_class)) + elif backbone == "efficientnet_b0": + m = models.efficientnet_b0() + m.classifier[-1] = torch.nn.Linear(m.classifier[-1].in_features, len(idx_to_class)) + else: + raise ValueError(f"Unsupported backbone: {backbone}") + + state = torch.load(weights_path, map_location=device) + m.load_state_dict(state["model"]) + m.eval().to(device) + return m, idx_to_class + +def infer_image_bytes(model, idx_to_class: Dict[int, str], img_bytes: bytes, + tfms, device: str = "cpu") -> Tuple[str, float]: + img = Image.open(io.BytesIO(img_bytes)).convert("RGB") + x = tfms(img).unsqueeze(0).to(device) + with torch.no_grad(): + logits = model(x) + probs = torch.softmax(logits, dim=1).cpu().numpy()[0] + idx = int(probs.argmax()) + return idx_to_class[idx], float(probs[idx]) diff --git a/services/fruit-orchestration/services/classifier/metrics_db/__init__.py b/services/fruit-orchestration/services/classifier/metrics_db/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/fruit-orchestration/services/classifier/metrics_db/db.py b/services/fruit-orchestration/services/classifier/metrics_db/db.py new file mode 100644 index 000000000..5170bb6d0 --- /dev/null +++ b/services/fruit-orchestration/services/classifier/metrics_db/db.py @@ -0,0 +1,110 @@ +# metrics_db/db.py +import os +from typing import Any, Dict, Optional +import psycopg2 +from psycopg2.extensions import connection as PGConnection +from dotenv import load_dotenv + + +def _get_conn() -> PGConnection: + """ + Open a PostgreSQL connection. No DDL here. + Priority: + 1) DATABASE_URL + 2) discrete env vars (DB_HOST, DB_PORT, ...) + """ + load_dotenv() + + dsn = (os.environ.get("DATABASE_URL") or "").strip() + if dsn: + return psycopg2.connect(dsn) + + host = os.environ.get("DB_HOST", "localhost") + port = int(os.environ.get("DB_PORT", "5432")) + name = os.environ.get("DB_NAME", "fruitdb") + user = os.environ.get("DB_USER", "fruituser") + password = os.environ.get("DB_PASSWORD", "fruitpass") + sslmode = os.environ.get("DB_SSLMODE", "disable") # prod: require/verify-full + + return psycopg2.connect( + host=host, + port=port, + dbname=name, + user=user, + password=password, + sslmode=sslmode, + application_name=os.environ.get("DB_APP_NAME", "metrics_service"), + connect_timeout=int(os.environ.get("DB_CONNECT_TIMEOUT", "10")), + ) + + +def insert_training_run(rec: Dict[str, Any]) -> None: + """ + Expects keys: + backbone, image_size, num_epochs, train_split, top1_acc, best_top1_acc, + artifacts_bucket, artifacts_prefix, labels_object, best_ckpt_object, + metrics_object, cm_object, seed + All columns must already exist in table training_runs. + """ + sql = """ + INSERT INTO training_runs ( + backbone, image_size, num_epochs, train_split, top1_acc, best_top1_acc, + artifacts_bucket, artifacts_prefix, labels_object, best_ckpt_object, + metrics_object, cm_object, seed + ) + VALUES (%(backbone)s, %(image_size)s, %(num_epochs)s, %(train_split)s, + %(top1_acc)s, %(best_top1_acc)s, %(artifacts_bucket)s, + %(artifacts_prefix)s, %(labels_object)s, %(best_ckpt_object)s, + %(metrics_object)s, %(cm_object)s, %(seed)s) + """ + with _get_conn() as conn, conn.cursor() as cur: + cur.execute(sql, rec) + conn.commit() + + +def insert_inference_log( + *, + model_backbone: str, + image_size: int, + fruit_type: str, + score: float, + latency_ms: Optional[float] = None, + client_ip: Optional[str] = None, + error: Optional[str] = None, + image_url: Optional[str] = None, +) -> None: + """ + Inserts a single inference log record. Table 'inference_logs' must exist. + """ + sql = """ + INSERT INTO inference_logs ( + fruit_type, score, latency_ms, model_backbone, image_size, + client_ip, error, image_url + ) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s) + """ + with _get_conn() as conn, conn.cursor() as cur: + cur.execute( + sql, + ( + fruit_type, + score, + latency_ms, + model_backbone, + image_size, + client_ip, + error, + image_url, + ), + ) + conn.commit() + + +def db_healthcheck() -> bool: + """Simple reachability check.""" + try: + with _get_conn() as conn, conn.cursor() as cur: + cur.execute("SELECT 1;") + return cur.fetchone() == (1,) + except Exception: + return False diff --git a/services/fruit-orchestration/services/classifier/models/best.pt b/services/fruit-orchestration/services/classifier/models/best.pt new file mode 100644 index 000000000..81a91795b Binary files /dev/null and b/services/fruit-orchestration/services/classifier/models/best.pt differ diff --git a/services/fruit-orchestration/services/classifier/models/labels.json b/services/fruit-orchestration/services/classifier/models/labels.json new file mode 100644 index 000000000..83b09546f --- /dev/null +++ b/services/fruit-orchestration/services/classifier/models/labels.json @@ -0,0 +1,15 @@ +{ + "Apple": 0, + "Banana": 1, + "Grape": 2, + "Guava": 3, + "Jujube": 4, + "Mango": 5, + "Orange": 6, + "Pomegranate": 7, + "Strawberry": 8, + "lemon": 9, + "peach": 10, + "pear": 11, + "plum": 12 +} \ No newline at end of file diff --git a/services/fruit-orchestration/services/classifier/requirements.txt b/services/fruit-orchestration/services/classifier/requirements.txt new file mode 100644 index 000000000..13d19cd80 --- /dev/null +++ b/services/fruit-orchestration/services/classifier/requirements.txt @@ -0,0 +1,19 @@ +torch==2.3.1 +torchvision==0.18.1 +numpy==1.26.4 +pyyaml==6.0.2 +pillow==10.4.0 +tqdm==4.66.4 +scikit-learn==1.5.1 +matplotlib==3.9.0 +minio==7.2.10 +fastapi==0.115.0 +uvicorn[standard]==0.30.6 +prometheus-client==0.20.0 +onnx==1.16.0 +psycopg2-binary +python-multipart==0.0.9 + +python-dotenv==1.0.1 + +onnxruntime==1.18.1 diff --git a/services/fruit-orchestration/services/fruit_ripeness_alert/Dockerfile b/services/fruit-orchestration/services/fruit_ripeness_alert/Dockerfile new file mode 100644 index 000000000..cc211d8d7 --- /dev/null +++ b/services/fruit-orchestration/services/fruit_ripeness_alert/Dockerfile @@ -0,0 +1,18 @@ +FROM python:3.11-slim + +RUN apt-get update \ + && apt-get install -y --no-install-recommends ca-certificates \ + && rm -rf /var/lib/apt/lists/* + +COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt +RUN update-ca-certificates + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt + +WORKDIR /app +COPY requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt + +COPY . . +CMD ["python", "app.py"] diff --git a/services/fruit-orchestration/services/fruit_ripeness_alert/app.py b/services/fruit-orchestration/services/fruit_ripeness_alert/app.py new file mode 100644 index 000000000..4a3d07217 --- /dev/null +++ b/services/fruit-orchestration/services/fruit_ripeness_alert/app.py @@ -0,0 +1,175 @@ +#!/usr/bin/env python3 +import os, json, uuid, requests +from datetime import datetime, timedelta, timezone +from kafka import KafkaProducer +from token_bootstrap import get_service_token + +# === Environment === +DB_API_BASE = os.getenv("DB_API_BASE", "http://db_api_service:8001") +DB_API_TOKEN_FILE = os.getenv("DB_API_TOKEN_FILE", "/app/secret/db_api_token") +KAFKA_BROKER = os.getenv("KAFKA_BROKER", "kafka:9092") +ALERT_TOPIC = os.getenv("ALERT_TOPIC", "alerts") +WINDOW_HOURS = int(os.getenv("WINDOW_HOURS", "168")) # default = 7 days + + +def now_utc() -> datetime: + return datetime.now(timezone.utc) + +def iso(ts: datetime) -> str: + return ts.replace(tzinfo=timezone.utc).isoformat() + +def get_threshold(task_name="ripeness", headers=None): + url = f"{DB_API_BASE}/api/task_thresholds" + try: + r = requests.get(url, headers=headers, timeout=15) + if r.status_code >= 500: + print(f"[WARN] thresholds API {r.status_code}, using default 0.8") + return 0.8 + r.raise_for_status() + try: + data = r.json() + except ValueError as je: + print(f"[WARN] thresholds response is not JSON: {je}; text={r.text[:200]!r}") + return 0.8 + except Exception as e: + print(f"[WARN] thresholds fetch failed: {e}; using default 0.8") + return 0.8 + + # Supports both list and dict responses (rows/items/data) + if isinstance(data, list): + rows = data + elif isinstance(data, dict): + rows = data.get("rows") or data.get("items") or data.get("data") or [] + if not isinstance(rows, list): + rows = [] + else: + rows = [] + + if not rows: + print(f"[WARN] No thresholds found at all, using default 0.8") + return 0.8 + + match = next((row for row in rows if row.get("task") == task_name), None) + if not match: + print(f"[WARN] No threshold for task={task_name}, using default 0.8") + return 0.8 + + try: + return float(match.get("threshold", 0.8)) + except Exception: + return 0.8 + + +from datetime import datetime, timezone + +def get_rollups(window_start, window_end, headers=None): + """ + Fetch data from ripeness_weekly_rollups_ts table and filter by time window. + Works with both list response and dict response containing {"rows": [...]}. + """ + url = f"{DB_API_BASE}/api/ripeness_weekly_rollups_ts" + print(f"[DEBUG] Fetching from {url}", flush=True) + + try: + r = requests.get(url, headers=headers, timeout=60) + r.raise_for_status() + try: + data = r.json() + except ValueError as je: + print(f"[ERROR] response is not JSON: {je}; text={r.text[:300]}", flush=True) + return [] + except requests.exceptions.HTTPError as e: + print(f"[ERROR] HTTP {r.status_code}: {r.text}", flush=True) + return [] + except Exception as e: + print(f"[ERROR] failed to fetch rollups: {e}", flush=True) + return [] + + # --- Normalize response structure --- + if isinstance(data, dict): + rows = data.get("rows") or data.get("items") or data.get("data") or [] + if not isinstance(rows, list): + print(f"[WARN] unexpected dict shape, using empty list; keys={list(data.keys())}", flush=True) + rows = [] + elif isinstance(data, list): + rows = data + else: + print(f"[WARN] unexpected JSON type: {type(data).__name__}", flush=True) + rows = [] + + # --- Parse timestamps and filter by time window --- + def parse_ts(ts_str: str) -> datetime: + try: + return datetime.fromisoformat(ts_str.replace("Z", "+00:00")) + except Exception: + return datetime.min.replace(tzinfo=timezone.utc) + + filtered = [] + for row in rows: + ts = parse_ts(str(row.get("ts", ""))) + if window_start <= ts <= window_end: + filtered.append(row) + + print(f"[INFO] Retrieved {len(filtered)} rollups after filtering (out of {len(rows)} total)") + return filtered + + +def send_kafka_alert(producer, device_id, ratio, threshold, run_id, rollup_id): + alert = { + "alert_id": str(uuid.uuid4()), + "alert_type": "fruit_ripeness_high", + "device_id": "device_id", + "started_at": iso(now_utc()), + "confidence": float(ratio), + "severity": 3, + "meta": { # 👈 Additional metadata is included here + "run_id": str(run_id), + "threshold": threshold, # Save the threshold value as well + "rollup_id": str(rollup_id), + "description": f"{ratio*100:.1f}% ripe/overripe fruits" + } + } + + producer.send(ALERT_TOPIC, json.dumps(alert).encode("utf-8")) + producer.flush() + print(f"[ALERT] sent for {device_id}: {ratio*100:.1f}%") + + +def main(): + print("ello!") + token = get_service_token() + headers = {"Content-Type": "application/json"} + if token: + headers["X-Service-Token"] = token + + window_end = now_utc() + window_start = window_end - timedelta(hours=WINDOW_HOURS) + print(f"[INFO] Checking rollups {window_start} → {window_end}") + + threshold = get_threshold("ripeness", headers) + print(f"[INFO] Using ripeness threshold: {threshold:.2f}") + rows = get_rollups(window_start, window_end, headers) + print(f"[INFO] Fetched {rows} rollup records") + if not rows: + print("[INFO] No data found.") + return + + producer = KafkaProducer(bootstrap_servers=[KAFKA_BROKER]) + + # Iterate through each device + for row in rows: + rollup_id = row.get("id") + device_id = row.get("device_id") + run_id = row.get("run_id") + pct = row.get("pct_ripe", 0.0) + if pct >= threshold: + send_kafka_alert(producer, device_id, pct, threshold, run_id, rollup_id) + else: + print(f"[INFO] {device_id}: below threshold {pct:.2f} < {threshold:.2f}") + + producer.close() + print("[DONE] process complete.") + + +if __name__ == "__main__": + main() diff --git a/services/fruit-orchestration/services/fruit_ripeness_alert/docker-compose.yml b/services/fruit-orchestration/services/fruit_ripeness_alert/docker-compose.yml new file mode 100644 index 000000000..9fa01c2f4 --- /dev/null +++ b/services/fruit-orchestration/services/fruit_ripeness_alert/docker-compose.yml @@ -0,0 +1,28 @@ +version: "3.8" # docker-compose v1 parser requires explicit version + +services: + fruit_ripeness_alert: + build: . + working_dir: /app + command: ["python", "app.py"] # run the built-in app from the image + environment: + - DB_API_BASE=http://db_api_service:8001 + - DB_API_SERVICE_NAME=fruit_ripeness_alert + - DB_ADMIN_USER=admin + - DB_ADMIN_PASS=admin123 + - DB_API_TOKEN_FILE=/app/secret/db_api_token + - KAFKA_BROKER=kafka:9092 + - ALERT_TOPIC=alerts + - WINDOW_HOURS=168 + volumes: + + - /opt/services/fruit_ripeness_alert/secret:/app/secret + networks: + + - ag_cloud + +networks: + + ag_cloud: + external: true + name: ag_cloud diff --git a/services/fruit-orchestration/services/fruit_ripeness_alert/requirements.txt b/services/fruit-orchestration/services/fruit_ripeness_alert/requirements.txt new file mode 100644 index 000000000..d9e23d1df --- /dev/null +++ b/services/fruit-orchestration/services/fruit_ripeness_alert/requirements.txt @@ -0,0 +1,2 @@ +requests +kafka-python diff --git a/services/fruit-orchestration/services/fruit_ripeness_alert/secret/db_api_token b/services/fruit-orchestration/services/fruit_ripeness_alert/secret/db_api_token new file mode 100644 index 000000000..f5d3b3f0d --- /dev/null +++ b/services/fruit-orchestration/services/fruit_ripeness_alert/secret/db_api_token @@ -0,0 +1 @@ +cf7bba69-678a-4708-829b-cb6e01c9b454 \ No newline at end of file diff --git a/services/fruit-orchestration/services/fruit_ripeness_alert/token_bootstrap.py b/services/fruit-orchestration/services/fruit_ripeness_alert/token_bootstrap.py new file mode 100644 index 000000000..cf3af7531 --- /dev/null +++ b/services/fruit-orchestration/services/fruit_ripeness_alert/token_bootstrap.py @@ -0,0 +1,62 @@ +import os, pathlib, time, requests + +DB_API_BASE = os.getenv("DB_API_BASE", "").strip() +DB_API_TOKEN_FILE = os.getenv("DB_API_TOKEN_FILE", "/app/secret/db_api_token") +DB_API_SERVICE_NAME = os.getenv("DB_API_SERVICE_NAME", "fruit_ripeness_alert").strip() or "fruit_ripeness_alert" + +def _safe_join_url(base: str, path: str) -> str: + return f"{base.rstrip('/')}/{path.lstrip('/')}" + +def _read_token(path: str) -> str | None: + p = pathlib.Path(path) + if p.exists(): + t = p.read_text(encoding="utf-8").strip() + if t and "***" not in t: + return t + return None + +def _write_token(path: str, token: str) -> None: + p = pathlib.Path(path) + p.parent.mkdir(parents=True, exist_ok=True) + p.write_text(token, encoding="utf-8") + +def _try_dev_bootstrap(): + """Try to get token using /auth/_dev_bootstrap (new API).""" + url = _safe_join_url(DB_API_BASE, "/auth/_dev_bootstrap") + payload = {"service_name": DB_API_SERVICE_NAME, "rotate_if_exists": True} + try: + r = requests.post(url, json=payload, timeout=10) + if r.status_code in (200, 201): + data = r.json() + sa = data.get("service_account") or {} + token = sa.get("raw_token") or sa.get("token") + if token and "***" not in token: + print("[BOOTSTRAP] obtained token via /auth/_dev_bootstrap") + return token.strip() + print(f"[BOOTSTRAP][WARN] _dev_bootstrap returned {r.status_code}: {r.text[:100]}") + except Exception as e: + print(f"[BOOTSTRAP][ERROR] {e}") + return None + +def get_service_token() -> str | None: + """Get or create a service token automatically.""" + if not DB_API_BASE: + print("[BOOTSTRAP][WARN] DB_API_BASE not set") + return None + + # Try existing file + token = _read_token(DB_API_TOKEN_FILE) + if token: + print(f"[BOOTSTRAP] using existing token from {DB_API_TOKEN_FILE}") + return token + + # Try bootstrap (new unified API) + print(f"[BOOTSTRAP] fetching new service token from {DB_API_BASE}") + token = _try_dev_bootstrap() + if token: + _write_token(DB_API_TOKEN_FILE, token) + print(f"[BOOTSTRAP] wrote token to {DB_API_TOKEN_FILE}") + return token + + print("[BOOTSTRAP][ERROR] Could not obtain service token.") + return None \ No newline at end of file diff --git a/services/fruit-orchestration/services/ripeness/.gitignore b/services/fruit-orchestration/services/ripeness/.gitignore new file mode 100644 index 000000000..17751b717 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/.gitignore @@ -0,0 +1,7 @@ +__pycache__/ +*.onnx +datasets/ +*.png +.venv/ +venv/ +ENV/ \ No newline at end of file diff --git a/services/fruit-orchestration/services/ripeness/Dockerfile b/services/fruit-orchestration/services/ripeness/Dockerfile new file mode 100644 index 000000000..d700be237 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/Dockerfile @@ -0,0 +1,59 @@ +FROM python:3.11-slim + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + PIP_NO_CACHE_DIR=1 + +WORKDIR /app + +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates openssl libpq-dev build-essential gcc \ + && rm -rf /var/lib/apt/lists/* + +COPY certs/ /usr/local/share/ca-certificates/ +RUN set -eux; \ + for f in /usr/local/share/ca-certificates/*.cer; do \ + [ -f "$f" ] && openssl x509 -inform der -in "$f" -out "${f%.cer}.crt" && rm -f "$f" || true; \ + done; \ + update-ca-certificates + +RUN printf "[global]\n\ +cert = /etc/ssl/certs/ca-certificates.crt\n\ +index-url = https://pypi.org/simple\n\ +trusted-host =\n\ + pypi.org\n\ + files.pythonhosted.org\n\ + download.pytorch.org\n" > /etc/pip.conf + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt + +COPY requirements.txt /app/ +RUN pip install --no-cache-dir --timeout 120 --index-url https://download.pytorch.org/whl/cpu \ + --trusted-host pypi.org --trusted-host pypi.python.org --trusted-host files.pythonhosted.org \ + torch==2.3.1 torchvision==0.18.1 \ + && pip install --no-cache-dir -r /app/requirements.txt \ + && pip install --no-cache-dir fastapi "uvicorn[standard]" +COPY api/ /app/api/ +COPY model/ /app/model +COPY jobs/ /app/jobs/ +COPY configs/ /app/configs/ +# Create models directory and copy model file +RUN mkdir -p /app/models +COPY checkpoints/mobilenet_v3_large/best_conditional.pt /app/models/best_conditional.pt + +# Create __init__.py files for Python modules +RUN touch /app/model/__init__.py \ + && touch /app/model/architecture/__init__.py \ + && touch /app/model/data/__init__.py \ + && touch /app/jobs/__init__.py \ + && touch /app/api/__init__.py + +ENV PYTHONPATH=/app + +EXPOSE 8088 +ENV MODEL_PATH=/app/models/best_conditional.pt \ + MODEL_NAME=best_conditional \ + BATCH_LIMIT=500 + +CMD ["uvicorn", "api.ripeness_api:app", "--host", "0.0.0.0", "--port", "8088", "--reload"] diff --git a/services/fruit-orchestration/services/ripeness/README.md b/services/fruit-orchestration/services/ripeness/README.md new file mode 100644 index 000000000..19de71518 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/README.md @@ -0,0 +1,226 @@ +# Ripeness ML – API & Weekly Job + +A small **FastAPI** service that: +- Predicts fruit ripeness (**ripe / unripe / overripe**) for new images from **MinIO** based on the trained conditional model, and writes results to **Postgres**. +- Creates a **weekly rollup snapshot** (with TS window) per fruit. + +--- + +## 🧩 Repo layout (service) + +``` +services/ripeness-ml/ +├─ api/ +│ └─ ripeness_api.py # FastAPI endpoints (predict + rollup) +├─ jobs/ +│ └─ weekly_ripeness_job.py # model/minio/db helpers reused by the API +├─ model/ +│ ├─ architecture/ +│ │ └─ mobilenet_v3_large_head.py # Model architecture definition +│ └─ data/ +│ └─ data_multitask.py # Data loading and preprocessing +├─ checkpoints/ +│ └─ mobilenet_v3_large/ +│ └─ best_conditional.pt # trained model weights +├─ deploy/ +│ ├─ Dockerfile +│ └─ docker-compose.ripeness.yml +├─ configs/ +│ └─ config.yaml # Model and training configuration +├─ requirements.txt +└─ .env (optional) +``` + +--- + +## ⚙️ Requirements + +- Docker Desktop +- External Docker network: **agcloud_ag_cloud** (same as your existing stack) + +**Running services on that network:** +- Postgres (`postgres:5432`, DB: `missions_db`, user: `missions_user`) +- MinIO (`minio-hot:9000`) + +--- + +## 🌍 Environment variables + +Set via `docker-compose.ripeness.yml` or `.env`: + +| Name | Default | Notes | +|------|----------|-------| +| `PGHOST` | postgres | DB host (inside Docker network) | +| `PGPORT` | 5432 | | +| `PGDATABASE` | missions_db | | +| `PGUSER` | missions_user | | +| `PGPASSWORD` | pg123 | | +| `MINIO_ENDPOINT` | minio-hot:9000 | S3 API port is 9000 inside Docker | +| `MINIO_SECURE` | false | set true if TLS to MinIO | +| `MINIO_ACCESS_KEY` | minioadmin | | +| `MINIO_SECRET_KEY` | minioadmin | | +| `MODEL_PATH` | /models/best_conditional.pt | mounted from host | +| `MODEL_NAME` | best_conditional | stored in DB | +| `BATCH_LIMIT` | 500 | safety cap per run | +| `FRUITS` (optional) | Apple,Orange,Grape,Strawberry | if enabled in code | + +If you’re behind **NetFree/proxy**, copy your CA file to `deploy/certs/` and use the Dockerfile section that installs CA + `update-ca-certificates`. + +--- + +## 🐳 Build & Run (Docker) + +From `services/ripeness-ml/`: + +```bash +docker compose -f docker-compose.ripeness.yml build ripeness-api +docker compose -f docker-compose.ripeness.yml up -d ripeness-api +``` + +**Health check:** + +```bash +curl http://localhost:8088/healthz +``` + +# **logs** +```bash +docker logs -n 200 ripeness-api +``` + +--- + +## 🔌 API + +**Base URL:** `http://localhost:8088` + +### POST `/predict-last-week` +Runs prediction for images from the last 7 days that don’t have a record yet in `ripeness_predictions`. + +```bash +curl -X POST http://localhost:8088/predict-last-week +# -> {"processed": 17} +``` + +### POST `/predict-batch` +Run for a custom time window and limit. + +**Request body (JSON):** +```json +{ + "since_ts": "2025-10-01T00:00:00", + "limit": 1000 +} +``` + +**Example:** +```bash +curl -X POST http://localhost:8088/predict-batch -H "Content-Type: application/json" -d '{"since_ts":"2025-10-01T00:00:00","limit":1000}' +``` + +### POST `/rollup/weekly` +Creates a weekly snapshot into `ripeness_weekly_rollups_ts` for the last 7 days (creates the table if missing). + +```bash +curl -X POST http://localhost:8088/rollup/weekly +# -> {"ok": true} +``` + +--- + +## 🧮 Database schema + +### Predictions table +```sql +CREATE TABLE IF NOT EXISTS ripeness_predictions ( + id BIGSERIAL PRIMARY KEY, + inference_log_id BIGINT NOT NULL REFERENCES inference_logs(id) ON DELETE CASCADE, + ts TIMESTAMPTZ NOT NULL DEFAULT now(), + ripeness_label TEXT NOT NULL CHECK (ripeness_label IN ('ripe','unripe','overripe')), + ripeness_score DOUBLE PRECISION NOT NULL, + model_name TEXT NOT NULL, + UNIQUE (inference_log_id) +); +``` + +### Weekly rollups +```sql +CREATE TABLE IF NOT EXISTS ripeness_weekly_rollups_ts ( + id BIGSERIAL PRIMARY KEY, + ts TIMESTAMPTZ NOT NULL DEFAULT now(), -- snapshot time + window_start TIMESTAMPTZ NOT NULL, + window_end TIMESTAMPTZ NOT NULL, + fruit_type TEXT NOT NULL, + cnt_total INTEGER NOT NULL, + cnt_ripe INTEGER NOT NULL, + cnt_unripe INTEGER NOT NULL, + cnt_overripe INTEGER NOT NULL, + pct_ripe DOUBLE PRECISION NOT NULL +); +``` + +--- + +## 🔍 Useful queries + +**Show latest predictions joined with inference logs:** +```sql +SELECT il.id, il.fruit_type, il.image_url, rp.ripeness_label, rp.ripeness_score, rp.model_name, rp.ts +FROM inference_logs il +JOIN ripeness_predictions rp ON rp.inference_log_id = il.id +ORDER BY rp.ts DESC +LIMIT 20; +``` + +**Show rollup snapshots:** +```sql +SELECT ts::date AS snapshot_day, fruit_type, cnt_total, +cnt_ripe, cnt_unripe, cnt_overripe, +ROUND(pct_ripe*100,2) AS pct_ripe_pct +FROM ripeness_weekly_rollups_ts +ORDER BY ts DESC, fruit_type; +``` + +**From Docker (network agcloud_ag_cloud):** +```bash +docker run --rm --network agcloud_ag_cloud -e PGPASSWORD=pg123 postgres:16-alpine psql -h postgres -U missions_user -d missions_db -c "SELECT ts::date AS snapshot_day, fruit_type, cnt_total, cnt_ripe, cnt_unripe, cnt_overripe, ROUND(pct_ripe*100,2) AS pct_ripe_pct + FROM ripeness_weekly_rollups_ts + ORDER BY ts DESC, fruit_type;" +``` + +--- + +## 🕒 Scheduling (Windows Task Scheduler) + +Create a weekly job that first predicts, then rolls up. + +**run_weekly.ps1:** +```powershell +Invoke-RestMethod -Method Post -Uri "http://localhost:8088/predict-last-week" +# note: /predict-last-week now triggers the weekly rollup automatically, +# so a single call is sufficient (no duplicate predictions are inserted). +``` + +**Register task:** +```bash +schtasks /Create /TN "RipenessWeekly" /TR "powershell.exe -ExecutionPolicy Bypass -File C:\path\run_weekly.ps1" /SC WEEKLY /D MON /ST 03:00 +``` + +--- + +## 🧰 Troubleshooting + +- **MinIO errors / 9000 vs 9001:** inside Docker network always use `minio-hot:9000` (S3 API). + Ports 9001/9002 are host-exposed console/proxy. +- **SignatureDoesNotMatch:** wrong `MINIO_ACCESS_KEY`/`SECRET_KEY` or endpoint (should be the S3 API). +- **Model FRUITS mismatch:** ensure the FRUITS list in code matches the model checkpoint (e.g. include Grape if trained). +- **SSL to PyPI (NetFree/proxy):** add your CA to the image and run `update-ca-certificates`. +- **No rows processed:** endpoint processes only inference logs without an existing prediction; expand window with `/predict-batch`. + +--- + +## 👩‍💻 Maintainer + +**Name:** Ayala +**Service name:** ripeness-api +**Ports:** 8088/tcp diff --git a/services/fruit-orchestration/services/ripeness/api/ripeness_api.py b/services/fruit-orchestration/services/ripeness/api/ripeness_api.py new file mode 100644 index 000000000..12fe8f5fb --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/api/ripeness_api.py @@ -0,0 +1,175 @@ +# scripts/ripeness_api.py +from fastapi import FastAPI +from pydantic import BaseModel +from datetime import datetime, timedelta +import sys, os +sys.path.append(os.path.join(os.path.dirname(__file__), "")) + +from jobs.weekly_ripeness_job import ( + get_conn, + fetch_from_minio, + load_image_for_model, + predict_ripeness, +) + +app = FastAPI(title="Ripeness Service") + + +class BatchRequest(BaseModel): + since_ts: datetime | None = None + limit: int = 500 + + +def run_batch(since_ts: datetime | None, limit: int) -> int: + if since_ts is None: + since_ts = datetime.utcnow() - timedelta(days=7) + with get_conn() as conn, conn.cursor() as cur: + cur.execute(""" + SELECT il.id, il.ts, il.fruit_type, il.image_url + FROM inference_logs il + LEFT JOIN ripeness_predictions rp ON rp.inference_log_id = il.id + WHERE il.ts >= %s + AND rp.id IS NULL + ORDER BY il.id ASC + LIMIT %s; + """, (since_ts, limit)) + rows = cur.fetchall() + + processed = 0 + # Generate a new run_id for this batch (once per batch) + with get_conn() as conn, conn.cursor() as cur: + cur.execute("SELECT gen_random_uuid()") + run_id = cur.fetchone()[0] + + for inflog_id, ts, fruit_type, image_url in rows: + try: + img_bytes = fetch_from_minio(image_url) + tensor = load_image_for_model(img_bytes) + label, score = predict_ripeness(tensor, fruit_type) + + # Parse bucket and object_key from image_url (expects format minio://bucket/object_key) + device_id = None + if image_url.startswith("minio://"): + path = image_url[len("minio://"):] + if "/" in path: + bucket, object_key = path.split("/", 1) + with get_conn() as conn, conn.cursor() as cur: + cur.execute(""" + SELECT device_id FROM files + WHERE bucket = %s AND object_key = %s + """, (bucket, object_key)) + res = cur.fetchone() + device_id = res[0] if res else None + + with get_conn() as conn, conn.cursor() as cur: + cur.execute(""" + INSERT INTO ripeness_predictions + (inference_log_id, ts, ripeness_label, ripeness_score, model_name, run_id, device_id) + VALUES (%s, now(), %s, %s, %s, %s, %s) + ON CONFLICT (inference_log_id) DO NOTHING; + """, (inflog_id, label, score, os.getenv("MODEL_NAME", "best_conditional"), run_id, device_id)) + processed += 1 + except Exception as e: + print(f"[ERR] inflog_id={inflog_id} :: {e}") + return processed + + +@app.get("/healthz") +def healthz(): + return {"ok": True} + + +@app.post("/predict-batch") +def predict_batch(req: BatchRequest): + n = run_batch(req.since_ts, req.limit) + return {"processed": n} + + +@app.post("/predict-last-week") +def predict_last_week(): + n = run_batch(None, int(os.getenv("BATCH_LIMIT", "500"))) + # After predicting new images, immediately create the weekly rollup + # This keeps the workflow to a single endpoint call (no duplicates because + # predictions use ON CONFLICT DO NOTHING) + try: + insert_weekly_rollup() + return {"processed": n, "rollup": True} + except Exception as e: + # Log the error but still return the number of processed items + print(f"[ERR] rollup: {e}") + return {"processed": n, "rollup": False, "error": str(e)} + + +def insert_weekly_rollup(): + ddl = """ + CREATE TABLE IF NOT EXISTS ripeness_weekly_rollups_ts ( + id BIGSERIAL PRIMARY KEY, + ts TIMESTAMPTZ NOT NULL DEFAULT now(), + window_start TIMESTAMPTZ NOT NULL, + window_end TIMESTAMPTZ NOT NULL, + fruit_type TEXT NOT NULL, + device_id TEXT, + run_id UUID, + cnt_total INTEGER NOT NULL, + cnt_ripe INTEGER NOT NULL, + cnt_unripe INTEGER NOT NULL, + cnt_overripe INTEGER NOT NULL, + pct_ripe DOUBLE PRECISION NOT NULL + ); + CREATE INDEX IF NOT EXISTS ix_rwrt_ts ON ripeness_weekly_rollups_ts(ts); + CREATE INDEX IF NOT EXISTS ix_rwrt_fruit_ts ON ripeness_weekly_rollups_ts(fruit_type, ts); + CREATE INDEX IF NOT EXISTS ix_rwrt_device ON ripeness_weekly_rollups_ts(device_id); + CREATE INDEX IF NOT EXISTS ix_rwrt_run ON ripeness_weekly_rollups_ts(run_id); + """ + + # optional filter by fruits from environment (comma-separated) + fruits_env = os.getenv("FRUITS") + fruits = None + fruit_where = "" + if fruits_env: + fruits = [f.strip() for f in fruits_env.split(",") if f.strip()] + # use = ANY(%s) with a TEXT[] parameter + fruit_where = "WHERE il.fruit_type = ANY(%s)" + + sql = """ + WITH w AS ( + SELECT now() - interval '7 days' AS ws, now() AS we + ), + agg AS ( + SELECT + il.fruit_type, + rp.device_id, + rp.run_id, + COUNT(*) AS cnt_total, + SUM(CASE WHEN rp.ripeness_label='ripe' THEN 1 ELSE 0 END) AS cnt_ripe, + SUM(CASE WHEN rp.ripeness_label='unripe' THEN 1 ELSE 0 END) AS cnt_unripe, + SUM(CASE WHEN rp.ripeness_label='overripe' THEN 1 ELSE 0 END) AS cnt_overripe + FROM ripeness_predictions rp + JOIN inference_logs il ON il.id = rp.inference_log_id + JOIN w ON rp.ts >= w.ws AND rp.ts < w.we + """ + ("\n " + fruit_where if fruit_where else "") + """ + GROUP BY il.fruit_type, rp.device_id, rp.run_id + ) + INSERT INTO ripeness_weekly_rollups_ts + (ts, window_start, window_end, fruit_type, device_id, run_id, cnt_total, cnt_ripe, cnt_unripe, cnt_overripe, pct_ripe) + SELECT + now(), (SELECT ws FROM w), (SELECT we FROM w), + fruit_type, device_id, run_id, cnt_total, cnt_ripe, cnt_unripe, cnt_overripe, + CASE WHEN cnt_total>0 THEN (cnt_ripe+cnt_overripe)::double precision/cnt_total ELSE 0 END + FROM agg; + """ + + with get_conn() as conn, conn.cursor() as cur: + cur.execute(ddl) + if fruits: + # psycopg2 adapts Python list to SQL array + cur.execute(sql, (fruits,)) + else: + cur.execute(sql) + return True + + +@app.post("/rollup/weekly") +def rollup_weekly(): + insert_weekly_rollup() + return {"ok": True} diff --git a/services/fruit-orchestration/services/ripeness/checkpoints/eval/classification_report.txt b/services/fruit-orchestration/services/ripeness/checkpoints/eval/classification_report.txt new file mode 100644 index 000000000..f2e2f5a54 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/checkpoints/eval/classification_report.txt @@ -0,0 +1,13 @@ + precision recall f1-score support + + unripe 1.0000 0.9981 0.9990 1041 + ripe 0.9983 1.0000 0.9991 1164 + overripe 1.0000 1.0000 1.0000 1534 + + accuracy 0.9995 3739 + macro avg 0.9994 0.9994 0.9994 3739 +weighted avg 0.9995 0.9995 0.9995 3739 + + +Accuracy: 0.9995 +Macro-F1: 0.9994 diff --git a/services/fruit-orchestration/services/ripeness/checkpoints/eval/metrics.json b/services/fruit-orchestration/services/ripeness/checkpoints/eval/metrics.json new file mode 100644 index 000000000..00bdd6890 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/checkpoints/eval/metrics.json @@ -0,0 +1,9 @@ +{ + "accuracy": 0.9994650976196844, + "macro_f1": 0.9993933641465831, + "per_class_f1": { + "unripe": 0.9990384615384615, + "ripe": 0.9991416309012876, + "overripe": 1.0 + } +} \ No newline at end of file diff --git a/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional.pt b/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional.pt new file mode 100644 index 000000000..0637d2fd0 Binary files /dev/null and b/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional.pt differ diff --git a/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional_frozen.pt b/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional_frozen.pt new file mode 100644 index 000000000..29b9cfb1c Binary files /dev/null and b/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional_frozen.pt differ diff --git a/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional_unfrozen.pt b/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional_unfrozen.pt new file mode 100644 index 000000000..c9ef651e1 Binary files /dev/null and b/services/fruit-orchestration/services/ripeness/checkpoints/mobilenet_v3_large/best_conditional_unfrozen.pt differ diff --git a/services/fruit-orchestration/services/ripeness/configs/config.yaml b/services/fruit-orchestration/services/ripeness/configs/config.yaml new file mode 100644 index 000000000..bfd6c7863 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/configs/config.yaml @@ -0,0 +1,25 @@ +seed: 42 +classes: ["unripe", "ripe", "overripe"] +img_size: 224 +batch_size: 32 +num_workers: 0 +epochs_frozen: 5 +epochs_unfrozen: 10 +lr: 0.0003 +weight_decay: 0.0001 +label_smoothing: 0.05 +use_class_weights: true +train_dir: "data/train" +val_dir: "data/val" +test_dir: "data/test" +checkpoint_dir: "checkpoints/mobilenet_v3_large" +best_metric: "f1_macro" + +fruits: ["apple","banana","orange"] +ripeness: ["unripe","ripe","overripe"] + +csv: + train: "data_mt_train/train.csv" + val: "data_mt_train/val.csv" + test: "data_mt_test/test.csv" + diff --git a/services/fruit-orchestration/services/ripeness/docker-compose.yml b/services/fruit-orchestration/services/ripeness/docker-compose.yml new file mode 100644 index 000000000..6ac2eca11 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/docker-compose.yml @@ -0,0 +1,48 @@ +version: "3.8" + +services: + ripeness-api: + build: + context: . + dockerfile: Dockerfile + image: ripeness-api:latest + container_name: ripeness-api + + environment: + PGHOST: postgres + PGPORT: "5432" + PGDATABASE: missions_db + PGUSER: missions_user + PGPASSWORD: pg123 + + MINIO_ENDPOINT: minio-hot:9000 + MINIO_SECURE: "false" + MINIO_ACCESS_KEY: minioadmin + MINIO_SECRET_KEY: minioadmin123 + + MODEL_NAME: best_conditional + BATCH_LIMIT: "500" + FRUITS: "Apple,Banana,Orange" + + + volumes: + - ./checkpoints:/app/checkpoints + - ./configs:/app/configs + # - ./model:/app/model + + networks: + - agcloud_net + - ag_cloud + + ports: + - "8091:8088" + restart: unless-stopped + +networks: + agcloud_net: + external: true + name: agcloud_ag_cloud + + ag_cloud: + external: true + name: ag_cloud diff --git a/services/fruit-orchestration/services/ripeness/jobs/weekly_ripeness_job.py b/services/fruit-orchestration/services/ripeness/jobs/weekly_ripeness_job.py new file mode 100644 index 000000000..387b7c034 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/jobs/weekly_ripeness_job.py @@ -0,0 +1,167 @@ +# file: services/weekly_ripeness_job.py +import io +import time +import torch +import psycopg2 +import datetime as dt +from urllib.parse import urlparse +from minio import Minio +from PIL import Image +import sys, os +sys.path.append(os.path.join(os.path.dirname(__file__), "..")) # so "models" is importable +from model.architecture.mobilenet_v3_large_head import build_conditional +from tqdm.auto import tqdm + + +from pathlib import Path +try: + from dotenv import load_dotenv + env_path = Path(__file__).resolve().parents[1] / ".env" + if env_path.exists(): + load_dotenv(env_path.as_posix()) +except Exception: + pass + +# ---- ENV ---- +PGHOST = os.getenv("PGHOST", "db") +PGPORT = int(os.getenv("PGPORT", "5432")) +PGDATABASE = os.getenv("PGDATABASE", "missions_db") +PGUSER = os.getenv("PGUSER", "missions_user") +PGPASSWORD = os.getenv("PGPASSWORD", "pg123") + +MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "127.0.0.1:9000") +MINIO_SECURE = os.getenv("MINIO_SECURE", "false").lower() == "true" +MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "minioadmin") +MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "minioadmin") + +MODEL_PATH = os.getenv("MODEL_PATH", "/models/best_conditional.pt") +MODEL_NAME = os.getenv("MODEL_NAME", "best_conditional") +BATCH_LIMIT = int(os.getenv("BATCH_LIMIT", "200")) + +# ----- labels & fruits mapping ----- +LABELS = ["unripe", "ripe", "overripe"] +FRUITS = ["Apple", "Banana", "Orange", "."] +FRUIT2IDX = {name.lower(): i for i, name in enumerate(FRUITS)} + +# ----- build model & load weights ----- +device = "cuda" if torch.cuda.is_available() else "cpu" +num_ripeness = len(LABELS) +num_fruits = len(FRUITS) + +model = build_conditional(num_ripeness=num_ripeness, num_fruits=num_fruits, embed_dim=16).to(device) + +ckpt = torch.load(MODEL_PATH, map_location=device) +state = ckpt["state_dict"] if (isinstance(ckpt, dict) and "state_dict" in ckpt) else ckpt + +assert state["fruit_embed.weight"].shape[0] == num_fruits, \ + f"Checkpoint expects {state['fruit_embed.weight'].shape[0]} fruits, but FRUITS has {num_fruits}" + +model.load_state_dict(state, strict=True) +model.eval() + +def load_image_for_model(img_bytes): + im = Image.open(io.BytesIO(img_bytes)).convert("RGB") + from torchvision import transforms + preprocess = transforms.Compose([ + transforms.Resize((224, 224)), + transforms.ToTensor(), + transforms.Normalize(mean=[0.485,0.456,0.406], std=[0.229,0.224,0.225]) + ]) + return preprocess(im).unsqueeze(0).to(device) + +@torch.no_grad() +def predict_ripeness(img_tensor, fruit_type: str): + idx = FRUIT2IDX.get(fruit_type.lower()) + if idx is None: + raise KeyError(f"skip: fruit '{fruit_type}' not in trained set {FRUITS}") + fruit_idx_tensor = torch.tensor([idx], dtype=torch.long, device=device) + logits = model(img_tensor, fruit_idx_tensor) + probs = torch.softmax(logits, dim=1).squeeze(0).cpu().numpy() + j = int(probs.argmax()) + return LABELS[j], float(probs[j]) + +# ---- MINIO ---- +minio_client = Minio(MINIO_ENDPOINT, MINIO_ACCESS_KEY, MINIO_SECRET_KEY, secure=MINIO_SECURE) + +def fetch_from_minio(image_url: str) -> bytes: + p = urlparse(image_url) + path = p.path.lstrip("/") + bucket, *rest = path.split("/", 1) + if not rest: + raise ValueError(f"Invalid URL path for MinIO: {image_url}") + obj = rest[0] + resp = minio_client.get_object(bucket, obj) + data = resp.read() + resp.close() + resp.release_conn() + return data + +# ---- DB ---- +def get_conn(): + return psycopg2.connect( + host=PGHOST, port=PGPORT, dbname=PGDATABASE, user=PGUSER, password=PGPASSWORD + ) + +def main(): + with get_conn() as conn, conn.cursor() as cur: + cur.execute(""" + SELECT il.id, il.ts, il.fruit_type, il.image_url + FROM inference_logs il + LEFT JOIN ripeness_predictions rp ON rp.inference_log_id = il.id + WHERE il.ts >= now() - interval '7 days' + AND rp.id IS NULL + ORDER BY il.id ASC + LIMIT %s; + """, (BATCH_LIMIT,)) + rows = cur.fetchall() + + processed = 0 + + # generate a single run_id for this batch + with get_conn() as conn, conn.cursor() as cur: + cur.execute("SELECT gen_random_uuid()") + run_id = cur.fetchone()[0] + + for inflog_id, ts, fruit_type, image_url in tqdm(rows, desc="Predicting ripeness"): + try: + if processed % 20 == 0: + print(f"...processed {processed} so far") + img_bytes = fetch_from_minio(image_url) + tensor = load_image_for_model(img_bytes) + try: + label, score = predict_ripeness(tensor, fruit_type) + except KeyError as skip: + print(f"[SKIP] inflog_id={inflog_id} :: {skip}") + continue + + # derive bucket/object_key and lookup device_id + device_id = None + try: + p = urlparse(image_url) + path = p.path.lstrip('/') + if '/' in path: + bucket, object_key = path.split('/', 1) + with get_conn() as conn, conn.cursor() as cur: + cur.execute("SELECT device_id FROM files WHERE bucket = %s AND object_key = %s", (bucket, object_key)) + res = cur.fetchone() + device_id = res[0] if res else None + except Exception: + # keep device_id as None if parsing/lookup fails + device_id = None + + with get_conn() as conn, conn.cursor() as cur: + cur.execute(""" + INSERT INTO ripeness_predictions + (inference_log_id, ts, ripeness_label, ripeness_score, model_name, run_id, device_id) + VALUES (%s, now(), %s, %s, %s, %s, %s) + ON CONFLICT (inference_log_id) DO NOTHING; + """, (inflog_id, label, score, MODEL_NAME, run_id, device_id)) + processed += 1 + print(f"[OK] inflog_id={inflog_id} -> {label} ({score:.4f})") + except Exception as e: + print(f"[ERR] inflog_id={inflog_id} url={image_url} :: {e}") + + print(f"Done. processed={processed}") + +if __name__ == "__main__": + main() diff --git a/services/fruit-orchestration/services/ripeness/model/architecture/mobilenet_v3_large_head.py b/services/fruit-orchestration/services/ripeness/model/architecture/mobilenet_v3_large_head.py new file mode 100644 index 000000000..3457d6953 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/model/architecture/mobilenet_v3_large_head.py @@ -0,0 +1,34 @@ +import torch.nn as nn +import torch +from torchvision.models import mobilenet_v3_large, MobileNet_V3_Large_Weights + +class RipenessModelConditional(nn.Module): + """ + Image -> MobileNetV3 backbone + Fruit type (idx) -> Embedding + Concatenate -> Linear -> ripeness logits + """ + def __init__(self, num_ripeness: int, num_fruits: int, embed_dim: int = 16): + super().__init__() + weights = MobileNet_V3_Large_Weights.IMAGENET1K_V2 + self.backbone = mobilenet_v3_large(weights=weights) + in_feats = self.backbone.classifier[-1].in_features + self.backbone.classifier[-1] = nn.Identity() + self.fruit_embed = nn.Embedding(num_fruits, embed_dim) + self.head = nn.Linear(in_feats + embed_dim, num_ripeness) + + def forward(self, x, fruit_idx): + feats = self.backbone(x) # [B, in_feats] + fvec = self.fruit_embed(fruit_idx) # [B, embed_dim] + out = torch.cat([feats, fvec], dim=1) # [B, in_feats+embed_dim] + return self.head(out) # [B, num_ripeness] + +def build_conditional(num_ripeness: int, num_fruits: int, embed_dim: int = 16) -> nn.Module: + return RipenessModelConditional(num_ripeness, num_fruits, embed_dim) + +def build_model(num_classes: int) -> nn.Module: + weights = MobileNet_V3_Large_Weights.IMAGENET1K_V2 + model = mobilenet_v3_large(weights=weights) + in_feats = model.classifier[-1].in_features + model.classifier[-1] = nn.Linear(in_feats, num_classes) + return model diff --git a/services/fruit-orchestration/services/ripeness/model/data/data_multitask.py b/services/fruit-orchestration/services/ripeness/model/data/data_multitask.py new file mode 100644 index 000000000..9b01959a3 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/model/data/data_multitask.py @@ -0,0 +1,48 @@ +from torch.utils.data import Dataset, DataLoader +from PIL import Image +from torchvision import transforms +import pandas as pd + +IMAGENET_MEAN=(0.485,0.456,0.406); IMAGENET_STD=(0.229,0.224,0.225) + +def build_transforms(img_size=224): + from torchvision import transforms as T + t_train = T.Compose([ + T.RandomResizedCrop(img_size, scale=(0.7,1.0)), + T.RandomHorizontalFlip(), + T.ColorJitter(0.2,0.2,0.2,0.05), + T.ToTensor(), T.Normalize(IMAGENET_MEAN, IMAGENET_STD), + ]) + t_val = T.Compose([ + T.Resize(int(img_size*1.15)), T.CenterCrop(img_size), + T.ToTensor(), T.Normalize(IMAGENET_MEAN, IMAGENET_STD), + ]) + return t_train, t_val + +class CSVConditional(Dataset): + def __init__(self, csv_path, fruit_to_idx, ripeness_to_idx, transform=None): + self.df = pd.read_csv(csv_path) + self.fruit_to_idx = fruit_to_idx + self.ripeness_to_idx = ripeness_to_idx + self.transform = transform + + def __len__(self): return len(self.df) + + def __getitem__(self, i): + row = self.df.iloc[i] + img = Image.open(row["path"]).convert("RGB") + if self.transform: img = self.transform(img) + fruit_idx = self.fruit_to_idx[row["fruit"]] + ripeness_idx = self.ripeness_to_idx[row["ripeness"]] + return img, fruit_idx, ripeness_idx + +def make_loaders(csv_train, csv_val, img_size, batch_size, num_workers, fruits, ripeness): + t_train, t_val = build_transforms(img_size) + f2i = {f:i for i,f in enumerate(fruits)} + r2i = {r:i for i,r in enumerate(ripeness)} + dtr = CSVConditional(csv_train, f2i, r2i, t_train) + dva = CSVConditional(csv_val, f2i, r2i, t_val) + from torch.utils.data import DataLoader + ltr = DataLoader(dtr, batch_size=batch_size, shuffle=True, num_workers=num_workers, pin_memory=True) + lva = DataLoader(dva, batch_size=batch_size, shuffle=False, num_workers=num_workers, pin_memory=True) + return ltr, lva, f2i, r2i diff --git a/services/fruit-orchestration/services/ripeness/model/data/transforms.py b/services/fruit-orchestration/services/ripeness/model/data/transforms.py new file mode 100644 index 000000000..a8f2c4b5b --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/model/data/transforms.py @@ -0,0 +1,18 @@ +from torchvision import transforms +IMAGENET_MEAN=(0.485,0.456,0.406); IMAGENET_STD=(0.229,0.224,0.225) + +def build_transforms(img_size=224): + t_train = transforms.Compose([ + transforms.RandomResizedCrop(img_size, scale=(0.7,1.0)), + transforms.RandomHorizontalFlip(), + transforms.ColorJitter(0.2,0.2,0.2,0.05), + transforms.ToTensor(), + transforms.Normalize(IMAGENET_MEAN, IMAGENET_STD), + ]) + t_val = transforms.Compose([ + transforms.Resize(int(img_size*1.15)), + transforms.CenterCrop(img_size), + transforms.ToTensor(), + transforms.Normalize(IMAGENET_MEAN, IMAGENET_STD), + ]) + return t_train, t_val diff --git a/services/fruit-orchestration/services/ripeness/model/training/evaluate_conditional.py b/services/fruit-orchestration/services/ripeness/model/training/evaluate_conditional.py new file mode 100644 index 000000000..e10977e01 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/model/training/evaluate_conditional.py @@ -0,0 +1,138 @@ +# -*- coding: utf-8 -*- +# Evaluate the conditional ripeness model on test/val CSVs. +# Outputs: +# - metrics.json (accuracy, macro_f1, per-class F1) +# - classification_report.txt +# - confusion_matrix.png + +import os, sys, json, yaml +from pathlib import Path +import numpy as np +import torch +from sklearn.metrics import accuracy_score, f1_score, classification_report, confusion_matrix +import matplotlib.pyplot as plt + +# --- make 'models' & 'training' importable when running as a script --- +PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) +if PROJECT_ROOT not in sys.path: + sys.path.insert(0, PROJECT_ROOT) + +from model.architecture.mobilenet_v3_large_head import build_conditional +from data.data_multitask import CSVConditional, build_transforms + +IMAGENET_MEAN=(0.485,0.456,0.406) +IMAGENET_STD=(0.229,0.224,0.225) + +def softmax(x): + x = x - x.max(axis=1, keepdims=True) + e = np.exp(x) + return e / e.sum(axis=1, keepdims=True) + +def load_cfg(): + return yaml.safe_load(open(os.path.join(PROJECT_ROOT, "configs/config.yaml"), "r", encoding="utf-8")) + +def make_loader(csv_path, fruits, ripeness, img_size=224, batch_size=64, num_workers=0): + _, t_val = build_transforms(img_size) + f2i = {f:i for i,f in enumerate(fruits)} + r2i = {r:i for i,r in enumerate(ripeness)} + ds = CSVConditional(csv_path, f2i, r2i, transform=t_val) + from torch.utils.data import DataLoader + return DataLoader(ds, batch_size=batch_size, shuffle=False, num_workers=num_workers, pin_memory=True) + +def plot_confusion_matrix(cm, classes, out_png): + fig = plt.figure(figsize=(5.5, 4.5)) + ax = fig.add_subplot(111) + im = ax.imshow(cm, interpolation='nearest') + ax.set_title('Confusion Matrix') + fig.colorbar(im) + tick_marks = np.arange(len(classes)) + ax.set_xticks(tick_marks); ax.set_xticklabels(classes, rotation=45, ha="right") + ax.set_yticks(tick_marks); ax.set_yticklabels(classes) + ax.set_ylabel('True'); ax.set_xlabel('Predicted') + # write counts + thresh = cm.max() / 2.0 if cm.size else 0.5 + for i in range(cm.shape[0]): + for j in range(cm.shape[1]): + ax.text(j, i, format(cm[i, j], 'd'), + ha="center", va="center", + color="white" if cm[i, j] > thresh else "black") + fig.tight_layout() + fig.savefig(out_png, dpi=160) + plt.close(fig) + +if __name__ == "__main__": + cfg = load_cfg() + device = "cuda" if torch.cuda.is_available() else "cpu" + + fruits = cfg["fruits"] + ripeness = cfg["ripeness"] + + # choose CSV: prefer test.csv; if missing/empty -> use val.csv + csv_test = Path(cfg["csv"].get("test", "data_mt/test.csv")) + csv_val = Path(cfg["csv"].get("val", "data_mt/val.csv")) + csv_path = csv_test if csv_test.exists() and csv_test.stat().st_size > 50 else csv_val + if not csv_path.exists(): + raise SystemExit(f"CSV not found: {csv_path}. Run ingest to create it.") + + # dataloader + loader = make_loader( + str(csv_path), fruits, ripeness, + img_size=cfg.get("img_size", 224), + batch_size=cfg.get("batch_size", 32), + num_workers=cfg.get("num_workers", 0) + ) + + # model + ckpt_dir = cfg["checkpoint_dir"] + ckpt = os.path.join(ckpt_dir, "best_conditional.pt") + if not os.path.exists(ckpt): + raise SystemExit(f"Checkpoint not found: {ckpt}") + + model = build_conditional(num_ripeness=len(ripeness), num_fruits=len(fruits)) + model.load_state_dict(torch.load(ckpt, map_location="cpu")) + model.eval().to(device) + + # predict + y_true, y_pred = [], [] + probs_all = [] + with torch.no_grad(): + for x, fidx, ridx in loader: + x = x.to(device) + fidx = torch.as_tensor(fidx, device=device) + logits = model(x, fidx).cpu().numpy() + prob = softmax(logits) + preds = prob.argmax(1) + y_pred.extend(preds.tolist()) + y_true.extend(ridx.numpy().tolist()) + probs_all.append(prob) + + y_true = np.array(y_true) + y_pred = np.array(y_pred) + probs = np.concatenate(probs_all, axis=0) if probs_all else np.empty((0,len(ripeness))) + + # metrics + acc = float(accuracy_score(y_true, y_pred)) + macro_f1 = float(f1_score(y_true, y_pred, average="macro")) + per_class_f1 = f1_score(y_true, y_pred, average=None) + per_class = {ripeness[i]: float(per_class_f1[i]) for i in range(len(ripeness))} + report = classification_report(y_true, y_pred, target_names=ripeness, digits=4) + cm = confusion_matrix(y_true, y_pred) + + # outputs + out_dir = os.path.join(PROJECT_ROOT, "checkpoints", "eval") + os.makedirs(out_dir, exist_ok=True) + # confusion matrix PNG + cm_png = os.path.join(out_dir, "confusion_matrix.png") + plot_confusion_matrix(cm, ripeness, cm_png) + # classification report + with open(os.path.join(out_dir, "classification_report.txt"), "w", encoding="utf-8") as f: + f.write(report + "\n") + f.write(f"\nAccuracy: {acc:.4f}\nMacro-F1: {macro_f1:.4f}\n") + # json metrics + with open(os.path.join(out_dir, "metrics.json"), "w", encoding="utf-8") as f: + json.dump({"accuracy": acc, "macro_f1": macro_f1, "per_class_f1": per_class}, f, indent=2) + + print(f"Evaluated on: {csv_path}") + print(f"Accuracy: {acc:.4f} | Macro-F1: {macro_f1:.4f}") + print("Per-class F1:", per_class) + print(f"Saved: {cm_png} and classification_report.txt, metrics.json") diff --git a/services/fruit-orchestration/services/ripeness/model/training/train_conditional.py b/services/fruit-orchestration/services/ripeness/model/training/train_conditional.py new file mode 100644 index 000000000..c2bf56357 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/model/training/train_conditional.py @@ -0,0 +1,114 @@ +import os, yaml, torch +from torch import nn +from sklearn.metrics import accuracy_score, f1_score + +from model.architecture.mobilenet_v3_large_head import build_conditional +from data.data_multitask import make_loaders + + +def evaluate(model, loader, device): + model.eval() + y_true, y_pred = [], [] + with torch.no_grad(): + for x, fidx, ridx in loader: + x = x.to(device) + fidx = torch.as_tensor(fidx, device=device) + logits = model(x, fidx) + y_pred.extend(logits.argmax(1).cpu().numpy()) + y_true.extend(ridx.numpy()) + acc = accuracy_score(y_true, y_pred) + f1 = f1_score(y_true, y_pred, average="macro") + return acc, f1 + + +def train_phase(model, ltr, lva, device, epochs, lr, wd, ckpt_dir, tag, ce, patience=2): + from torch.optim import AdamW + from torch.optim.lr_scheduler import CosineAnnealingLR + + os.makedirs(ckpt_dir, exist_ok=True) + opt = AdamW(filter(lambda p: p.requires_grad, model.parameters()), lr=lr, weight_decay=wd) + sch = CosineAnnealingLR(opt, T_max=epochs) + + best_f1 = -1.0 + best_state = None + no_improve = 0 + + try: + for ep in range(1, epochs + 1): + model.train() + for x, fidx, ridx in ltr: + x = x.to(device) + fidx = torch.as_tensor(fidx, device=device) + ridx = torch.as_tensor(ridx, device=device) + + logits = model(x, fidx) + loss = ce(logits, ridx) + + opt.zero_grad() + loss.backward() + opt.step() + + acc, f1 = evaluate(model, lva, device) + sch.step() + print(f"[{tag} Epoch {ep}] val_acc={acc:.3f} val_f1={f1:.3f}") + + if f1 > best_f1 + 1e-4: + best_f1 = f1 + best_state = {k: v.cpu() for k, v in model.state_dict().items()} + torch.save(best_state, os.path.join(ckpt_dir, f"best_conditional_{tag}.pt")) + no_improve = 0 + else: + no_improve += 1 + if no_improve >= patience: + print(f"Early stopping ({tag}) — no improvement for {patience} epochs") + break + + except KeyboardInterrupt: + print("KeyboardInterrupt — saving best checkpoint so far...") + + finally: + if best_state is not None: + model.load_state_dict(best_state) + return model, best_f1 + + +if __name__ == "__main__": + cfg = yaml.safe_load(open("configs/config.yaml", "r", encoding="utf-8")) + device = "cuda" if torch.cuda.is_available() else "cpu" + + train_csv = cfg["csv"]["train"] + val_csv = cfg["csv"]["val"] + fruits = cfg["fruits"] + ripeness = cfg["ripeness"] + + ltr, lva, f2i, r2i = make_loaders( + train_csv, val_csv, + cfg["img_size"], cfg["batch_size"], cfg["num_workers"], + fruits, ripeness + ) + + model = build_conditional(num_ripeness=len(ripeness), num_fruits=len(fruits)).to(device) + ce = nn.CrossEntropyLoss() + + for p in model.backbone.features.parameters(): + p.requires_grad = False + + model, _ = train_phase( + model, ltr, lva, device, + cfg["epochs_frozen"], cfg["lr"], cfg["weight_decay"], + cfg["checkpoint_dir"], tag="frozen", ce=ce, patience=2 + + ) + + for p in model.parameters(): + p.requires_grad = True + + model, best_f1 = train_phase( + model, ltr, lva, device, + cfg["epochs_unfrozen"], cfg["lr"]/3, cfg["weight_decay"], + cfg["checkpoint_dir"], tag="unfrozen", ce=ce, patience=2 + ) + + os.makedirs(cfg["checkpoint_dir"], exist_ok=True) + torch.save(model.state_dict(), os.path.join(cfg["checkpoint_dir"], "best_conditional.pt")) + print("Saved:", os.path.join(cfg["checkpoint_dir"], "best_conditional.pt"), "| best F1:", best_f1) diff --git a/services/fruit-orchestration/services/ripeness/model/training/utils.py b/services/fruit-orchestration/services/ripeness/model/training/utils.py new file mode 100644 index 000000000..23e47edc7 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/model/training/utils.py @@ -0,0 +1,14 @@ +# import torch, random, numpy as np +# from collections import Counter + +# def set_seed(s=42): +# random.seed(s); np.random.seed(s); torch.manual_seed(s); torch.cuda.manual_seed_all(s) + +# def load_class_weights(trainloader, use=True): +# if not use: return None +# counts = Counter() +# for _,y in trainloader: +# for i in y.numpy(): counts[int(i)]+=1 +# total = sum(counts.values()) +# weights = [total/counts[i] for i in range(len(counts))] +# return torch.tensor(weights, dtype=torch.float32) diff --git a/services/fruit-orchestration/services/ripeness/requirements.txt b/services/fruit-orchestration/services/ripeness/requirements.txt new file mode 100644 index 000000000..0aa2be591 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/requirements.txt @@ -0,0 +1,16 @@ +torch==2.3.1 +torchvision==0.18.1 +# timm==1.0.9 +# scikit-learn==1.5.1 +matplotlib==3.9.0 +pillow==10.4.0 +pyyaml==6.0.2 +tqdm==4.66.4 +pandas==2.2.2 +onnx==1.16.0 +onnxruntime==1.18.1 +fastapi==0.115.0 +uvicorn[standard]==0.30.6 +minio==7.2.10 +python-dotenv==1.0.1 +psycopg2-binary diff --git a/services/fruit-orchestration/services/ripeness/tools/data_prep/ingest_kaggle_multitask.py b/services/fruit-orchestration/services/ripeness/tools/data_prep/ingest_kaggle_multitask.py new file mode 100644 index 000000000..46daeed76 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/tools/data_prep/ingest_kaggle_multitask.py @@ -0,0 +1,79 @@ + +import argparse, csv, random +from pathlib import Path + +IMG_EXT = {".jpg",".jpeg",".png",".bmp",".tif",".tiff",".webp"} + +RIPENESS_MAP = { + "unripe": "unripe", + "fresh": "ripe", + "ripe": "ripe", + "rotten": "overripe", +} + +FRUIT_KEYS = ["apple", "banana", "orange", "pineapple"] + +def detect_from_path(p: Path): + names = [pp.name.lower().replace(" ", "").replace("_","") for pp in [p] + list(p.parents)] + fruit = None + ripeness = None + + for n in names: + for fk in FRUIT_KEYS: + if fk in n: + fruit = fk + break + for key, mapped in RIPENESS_MAP.items(): + if key in n: + ripeness = mapped + break + if fruit and ripeness: + return fruit, ripeness + return fruit, ripeness + +def gather(root: Path): + rows = [] # (path, fruit, ripeness) + for fp in root.rglob("*"): + if fp.is_file() and fp.suffix.lower() in IMG_EXT: + fruit, ripeness = detect_from_path(fp) + if fruit and ripeness: + rows.append((fp.resolve().as_posix(), fruit, ripeness)) + return rows + +def write_csv(path: Path, rows): + path.parent.mkdir(parents=True, exist_ok=True) + with open(path, "w", newline="", encoding="utf-8") as f: + w = csv.writer(f) + w.writerow(["path","fruit","ripeness"]) + w.writerows(rows) + +if __name__ == "__main__": + ap = argparse.ArgumentParser(description="Create CSVs (train/val/test) with path,fruit,ripeness from Kaggle folders") + ap.add_argument("--src", required=True, help="path to .../dataset (the folder that contains train/ and test/)") + ap.add_argument("--outdir", default="data_mt", help="output folder for CSVs") + ap.add_argument("--split", default="0.8,0.2,0.0", help="train,val,test ratios") + ap.add_argument("--seed", type=int, default=42) + args = ap.parse_args() + + root = Path(args.src).resolve() + all_rows = gather(root) + if not all_rows: + raise SystemExit(f"No images found under: {root}. Check --src path.") + + random.seed(args.seed) + random.shuffle(all_rows) + + tr, va, te = [float(x) for x in args.split.split(",")] + assert abs(tr+va+te - 1.0) < 1e-6, "--split must sum to 1.0" + n = len(all_rows); ntr = int(tr*n); nv = int(va*n) + rows_tr = all_rows[:ntr]; rows_va = all_rows[ntr:ntr+nv]; rows_te = all_rows[ntr+nv:] + + out = Path(args.outdir) + write_csv(out/"train.csv", rows_tr) + write_csv(out/"val.csv", rows_va) + write_csv(out/"test.csv", rows_te) + + print(f"Saved CSVs in {out.resolve()}") + print(f" train.csv: {len(rows_tr)}") + print(f" val.csv: {len(rows_va)}") + print(f" test.csv: {len(rows_te)}") diff --git a/services/fruit-orchestration/services/ripeness/tools/data_prep/prepare_from_minio.py b/services/fruit-orchestration/services/ripeness/tools/data_prep/prepare_from_minio.py new file mode 100644 index 000000000..0afb84c54 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/tools/data_prep/prepare_from_minio.py @@ -0,0 +1,161 @@ +# AGCLOUD/services/ripeness-ml/scripts/prepare_from_minio.py +import os, io, csv, argparse, sys, re, datetime as dt +from pathlib import Path +from typing import Dict, List, Tuple, Optional +from minio import Minio +from minio.error import S3Error +from tqdm import tqdm +import random + +def parse_args(): + p = argparse.ArgumentParser(description="Sync labeled images from MinIO into local data/train|val|test/") + p.add_argument("--minio-url", required=True, help="e.g. http://127.0.0.1:9000") + p.add_argument("--access-key", required=False, default=os.getenv("MINIO_ACCESS_KEY","minioadmin")) + p.add_argument("--secret-key", required=False, default=os.getenv("MINIO_SECRET_KEY","minioadmin")) + p.add_argument("--secure", action="store_true", help="use HTTPS") + p.add_argument("--bucket", required=True, help="e.g. classification") + p.add_argument("--prefix", required=True, help="e.g. samples/2025/ or samples/") + p.add_argument("--outdir", default="data", help="local output root") + p.add_argument("--split", default="0.7,0.15,0.15", help="train,val,test ratios") + p.add_argument("--labels-csv", help="path to labels.csv (local file) OR object path in bucket (starts without leading /)") + p.add_argument("--infer-label-from-folder", action="store_true", help="take class name from folder under prefix") + p.add_argument("--from-date", help="YYYY-MM-DD (inclusive)") + p.add_argument("--to-date", help="YYYY-MM-DD (inclusive)") + p.add_argument("--last-days", type=int, help="Use only last N days under prefix (overrides from/to)") + p.add_argument("--dry-run", action="store_true") + return p.parse_args() + +def list_objects(client: Minio, bucket: str, prefix: str): + return client.list_objects(bucket, prefix=prefix, recursive=True) + +DATE_RE = re.compile(r"/(\d{4})/(\d{2})/(\d{2})(?:/|$)") + +def object_date(obj_name: str) -> Optional[dt.date]: + m = DATE_RE.search("/"+obj_name.strip("/")) + if not m: return None + y, mth, d = map(int, m.groups()) + return dt.date(y, mth, d) + +def load_labels_from_csv_local(csv_path: str) -> Dict[str, str]: + mapping = {} + with open(csv_path, "r", newline="", encoding="utf-8") as f: + r = csv.DictReader(f) + for row in r: + mapping[row["object"].strip()] = row["label"].strip() + return mapping + +def load_labels_from_csv_minio(client: Minio, bucket: str, obj_path: str) -> Dict[str, str]: + resp = client.get_object(bucket, obj_path) + data = resp.read().decode("utf-8") + mapping = {} + for row in csv.DictReader(io.StringIO(data)): + mapping[row["object"].strip()] = row["label"].strip() + return mapping + +def ensure_dirs(root: Path, classes: List[str]): + for split in ["train","val","test"]: + for c in classes: + (root/split/c).mkdir(parents=True, exist_ok=True) + +def main(): + args = parse_args() + tr, va, te = [float(x) for x in args.split.split(",")] + assert abs(tr+va+te - 1.0) < 1e-6, "--split must sum to 1.0" + + secure = args.secure or args.minio_url.startswith("https://") + endpoint = args.minio_url.replace("http://","").replace("https://","") + client = Minio(endpoint, access_key=args.access_key, secret_key=args.secret_key, secure=secure) + + # python arg names can't contain hyphen; fallback + access = getattr(args, "access_key", getattr(args, "access-key", None)) + secret = getattr(args, "secret_key", getattr(args, "secret-key", None)) + client = Minio(endpoint, access_key=access, secret_key=secret, secure=secure) + + # gather all candidate objects under prefix + objs = list(list_objects(client, args.bucket, args.prefix)) + if len(objs)==0: + print("No objects under prefix:", args.prefix); sys.exit(1) + + # filter by date + if args.last_days: + cutoff = dt.date.today() - dt.timedelta(days=args.last_days) + objs = [o for o in objs if (object_date(o.object_name) or dt.date.min) >= cutoff] + else: + dfrom = dt.date.fromisoformat(args.from_date) if args.from_date else None + dto = dt.date.fromisoformat(args.to_date) if args.to_date else None + if dfrom or dto: + def inrange(o): + od = object_date(o.object_name) + if not od: return False + if dfrom and od < dfrom: return False + if dto and od > dto: return False + return True + objs = [o for o in objs if inrange(o)] + + # Build label mapping + label_map: Dict[str,str] = {} + classes: set = set() + + if args.labels_csv: + if os.path.exists(args.labels_csv): + label_map = load_labels_from_csv_local(args.labels_csv) + else: + label_map = load_labels_from_csv_minio(client, args.bucket, args.labels_csv) + classes = set(label_map.values()) + candidates = [(o.object_name, label_map.get(o.object_name)) for o in objs if o.object_name in label_map] + elif args.infer_label_from_folder: + # Expect ...//... somewhere AFTER prefix + pref = args.prefix.strip("/") + candidates = [] + for o in objs: + rel = o.object_name[len(pref):].strip("/") + parts = rel.split("/") + if len(parts)>=2: + cls = parts[0] + candidates.append((o.object_name, cls)) + classes.add(cls) + if not classes: + print("Could not infer classes from folders; provide --labels-csv", file=sys.stderr) + sys.exit(2) + else: + print("Provide either --labels-csv or --infer-label-from-folder", file=sys.stderr) + sys.exit(2) + + classes = sorted(list(classes)) + print("Classes:", classes, "| samples:", len(candidates)) + root = Path(args.outdir) + ensure_dirs(root, classes) + + # stratified split by class + by_cls: Dict[str, List[str]] = {c: [] for c in classes} + for obj, lab in candidates: + if lab in by_cls: + by_cls[lab].append(obj) + for c in classes: random.shuffle(by_cls[c]) + + plan: List[Tuple[str, str]] = [] # (object_name, target_path) + for c in classes: + items = by_cls[c] + n = len(items); ntr = int(tr*n); nv = int(va*n) + tr_items = items[:ntr]; va_items = items[ntr:ntr+nv]; te_items = items[ntr+nv:] + for src in tr_items: + plan.append((src, str(root/ "train"/c/ Path(src).name))) + for src in va_items: + plan.append((src, str(root/ "val"/c/ Path(src).name))) + for src in te_items: + plan.append((src, str(root/ "test"/c/ Path(src).name))) + + if args.dry_run: + print(f"DRY-RUN: would download {len(plan)} files.") + return + + # download + for src, dst in tqdm(plan, desc="Downloading"): + dpath = Path(dst) + if dpath.exists(): continue + dpath.parent.mkdir(parents=True, exist_ok=True) + client.fget_object(args.bucket, src, dst) + print("Done. Data prepared under:", root.resolve()) + +if __name__ == "__main__": + main() diff --git a/services/fruit-orchestration/services/ripeness/tools/export/export_onnx_conditional.py b/services/fruit-orchestration/services/ripeness/tools/export/export_onnx_conditional.py new file mode 100644 index 000000000..1431ea0e6 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/tools/export/export_onnx_conditional.py @@ -0,0 +1,25 @@ +import torch, yaml, os +from model.architecture.mobilenet_v3_large_head import build_conditional + +if __name__ == "__main__": + cfg = yaml.safe_load(open("configs/config.yaml")) + fruits = cfg["fruits"] + ripeness = cfg["ripeness"] + + model = build_conditional(num_ripeness=len(ripeness), num_fruits=len(fruits)) + ckpt_path = os.path.join(cfg["checkpoint_dir"], "best_conditional.pt") + model.load_state_dict(torch.load(ckpt_path, map_location="cpu")) + model.eval() + + dummy_x = torch.randn(1, 3, cfg["img_size"], cfg["img_size"]) + dummy_f = torch.zeros(1, dtype=torch.long) # example fruit index + torch.onnx.export( + model, (dummy_x, dummy_f), + "ripeness_conditional.onnx", + input_names=["image", "fruit_idx"], + output_names=["ripeness_logits"], + dynamic_axes={"image": {0: "batch"}, "ripeness_logits": {0: "batch"}}, + opset_version=13 + ) + + print("✅ Exported: ripeness_conditional.onnx") diff --git a/services/fruit-orchestration/services/ripeness/tools/inference/infer_minio_batch.py b/services/fruit-orchestration/services/ripeness/tools/inference/infer_minio_batch.py new file mode 100644 index 000000000..0206a3791 --- /dev/null +++ b/services/fruit-orchestration/services/ripeness/tools/inference/infer_minio_batch.py @@ -0,0 +1,193 @@ +# AGCLOUD/services/ripeness-ml/scripts/infer_minio_batch.py +import argparse, os, sys, csv, json +from io import BytesIO +from pathlib import Path + +import numpy as np +from PIL import Image +from minio import Minio +from tqdm import tqdm +import onnxruntime as ort +from torchvision import transforms + +# ---- Configurable defaults ---- +IMAGENET_MEAN = (0.485, 0.456, 0.406) +IMAGENET_STD = (0.229, 0.224, 0.225) +IMG_TFM = transforms.Compose([ + transforms.Resize(256), + transforms.CenterCrop(224), + transforms.ToTensor(), + transforms.Normalize(IMAGENET_MEAN, IMAGENET_STD), +]) + +DEFAULT_FRUITS = ["apple", "banana", "orange", "pineapple"] # order matters! +RIPENESS = ["unripe", "ripe", "overripe"] + +IMG_EXTS = (".jpg", ".jpeg", ".png", ".bmp", ".tif", ".tiff", ".webp") + + +def parse_args(): + p = argparse.ArgumentParser( + description="Batch inference from MinIO prefix with conditional ONNX model (image + fruit_idx)." + ) + p.add_argument("--minio-url", required=True, help="http://127.0.0.1:9001") + p.add_argument("--access-key", default=os.getenv("MINIO_ACCESS_KEY", "minioadmin")) + p.add_argument("--secret-key", default=os.getenv("MINIO_SECRET_KEY", "minioadmin")) + p.add_argument("--secure", action="store_true", help="Use HTTPS") + + p.add_argument("--bucket", required=True, help="MinIO bucket name") + p.add_argument("--prefix", help="Prefix to scan, e.g. samples/2025/10/15 (ignored if --pairs-csv is used)") + + p.add_argument("--onnx", default="ripeness_conditional.onnx", help="Path to conditional ONNX model") + p.add_argument("--providers", nargs="*", default=None, help="ONNX Runtime providers list (default: CPU)") + + # Fruit specification + p.add_argument("--fruit", help="Fruit for ALL objects (apple|banana|orange|pineapple)") + p.add_argument("--pairs-csv", help="CSV file with columns: object,fruit (mapping per object)") + + # Fruits list order (so fruit_idx matches training) + p.add_argument("--fruits", default=None, + help='Fruits list in order, e.g. \'["apple","banana","orange","pineapple"]\' or "apple,banana,orange,pineapple"') + + # Output + p.add_argument("--out-csv", help="Optional: write results to CSV (object,fruit,label,prob_unripe,prob_ripe,prob_overripe)") + p.add_argument("--quiet", action="store_true", help="Do not print JSON lines to stdout") + + args = p.parse_args() + + if not args.pairs_csv and not (args.prefix and args.fruit): + p.error("Provide either --pairs-csv OR both --prefix and --fruit.") + + return args + + +def parse_fruits_list(fruits_arg): + if not fruits_arg: + return DEFAULT_FRUITS + s = fruits_arg.strip() + if s.startswith("["): + # JSON-ish + try: + import json as _json + lst = _json.loads(s) + return [x.strip().lower() for x in lst] + except Exception: + pass + # comma separated + return [x.strip().lower() for x in s.split(",") if x.strip()] + + +def softmax(x): + x = x - x.max(axis=1, keepdims=True) + e = np.exp(x) + return e / e.sum(axis=1, keepdims=True) + + +def is_image(name: str) -> bool: + return name.lower().endswith(IMG_EXTS) + + +def load_pairs_csv(path: str): + mapping = {} + with open(path, "r", newline="", encoding="utf-8") as f: + r = csv.DictReader(f) + if "object" not in r.fieldnames or "fruit" not in r.fieldnames: + raise SystemExit("pairs CSV must have columns: object,fruit") + for row in r: + obj = row["object"].strip() + fruit = row["fruit"].strip().lower() + mapping[obj] = fruit + return mapping + + +def open_minio(args): + secure = args.secure or args.minio_url.startswith("https://") + endpoint = args.minio_url.replace("http://", "").replace("https://", "") + return Minio(endpoint, access_key=args.access_key, secret_key=args.secret_key, secure=secure) + + +def main(): + args = parse_args() + fruits = parse_fruits_list(args.fruits) + + # Validate fruit names + fruit_set = set(fruits) + + # Prepare ONNX Runtime session + providers = args.providers or ["CPUExecutionProvider"] + sess = ort.InferenceSession(args.onnx, providers=providers) + + client = open_minio(args) + + # Prepare iterator over (object_name, fruit) + if args.pairs_csv: + mapping = load_pairs_csv(args.pairs_csv) + # Only iterate the keys present in the CSV (no MinIO list needed) + iterator = [(obj, mapping[obj]) for obj in mapping] + else: + fixed_fruit = args.fruit.lower() + if fixed_fruit not in fruit_set: + raise SystemExit(f"--fruit must be one of {fruits}; got {fixed_fruit}") + iterator = [] + for obj in client.list_objects(args.bucket, prefix=args.prefix, recursive=True): + if is_image(obj.object_name): + iterator.append((obj.object_name, fixed_fruit)) + + # Output CSV writer (optional) + csv_writer = None + if args.out_csv: + Path(args.out_csv).parent.mkdir(parents=True, exist_ok=True) + fcsv = open(args.out_csv, "w", newline="", encoding="utf-8") + csv_writer = csv.writer(fcsv) + csv_writer.writerow(["object", "fruit", "label", "prob_unripe", "prob_ripe", "prob_overripe"]) + + # Run predictions + for obj_name, fruit in tqdm(iterator, desc="Predicting"): + if fruit not in fruit_set: + # Unknown fruit -> skip + if not args.quiet: + print(json.dumps({"object": obj_name, "error": f"unknown fruit '{fruit}' (allowed {fruits})"}, ensure_ascii=False)) + continue + + # Fetch image bytes + if args.pairs_csv: + # object names in CSV must be full paths in bucket + resp = client.get_object(args.bucket, obj_name) + else: + resp = client.get_object(args.bucket, obj_name) + + try: + img = Image.open(BytesIO(resp.read())).convert("RGB") + finally: + resp.close(); resp.release_conn() + + x = IMG_TFM(img).unsqueeze(0).numpy() + fidx = np.array([fruits.index(fruit)], dtype=np.int64) + + logits = sess.run(["ripeness_logits"], {"images": x, "fruit_idx": fidx})[0] + prob = softmax(logits)[0] + idx = int(prob.argmax()) + label = RIPENESS[idx] + + record = { + "object": obj_name, + "fruit": fruit, + "label": label, + "probs": {RIPENESS[i]: float(prob[i]) for i in range(len(RIPENESS))} + } + + if not args.quiet: + print(json.dumps(record, ensure_ascii=False)) + + if csv_writer: + csv_writer.writerow([ + obj_name, fruit, label, + f"{prob[0]:.6f}", f"{prob[1]:.6f}", f"{prob[2]:.6f}" + ]) + + if csv_writer: + fcsv.close() + + +if __name__ == "__main__": + main() diff --git a/services/fruit_alert_generator/Dockerfile b/services/fruit_alert_generator/Dockerfile new file mode 100644 index 000000000..34f8ecff7 --- /dev/null +++ b/services/fruit_alert_generator/Dockerfile @@ -0,0 +1,6 @@ + +FROM python:3.12-slim +WORKDIR /app +RUN pip install psycopg2-binary +COPY generator.py /app/generator.py +CMD ["python", "generator.py"] diff --git a/services/fruit_alert_generator/README.txt b/services/fruit_alert_generator/README.txt new file mode 100644 index 000000000..25472b151 --- /dev/null +++ b/services/fruit_alert_generator/README.txt @@ -0,0 +1,16 @@ + +Fruit Alert Generator +===================== + +A small service that inserts random fruit alerts into the 'alerts' table every 30 seconds. + +Devices used: +- fruit-camera-01 +- fruit-camera-02 +- fruit-camera-03 + +How to build: + docker compose build fruit_alert_generator + +How to run: + docker compose up -d fruit_alert_generator diff --git a/services/fruit_alert_generator/generator.py b/services/fruit_alert_generator/generator.py new file mode 100644 index 000000000..16db3af98 --- /dev/null +++ b/services/fruit_alert_generator/generator.py @@ -0,0 +1,85 @@ + +import psycopg2 +from datetime import datetime, timedelta, timezone +import uuid, random, json, time, os + +DB_HOST = os.getenv("PGHOST", "postgres") +DB_PORT = os.getenv("PGPORT", "5432") +DB_USER = os.getenv("PGUSER", "missions_user") +DB_PASS = os.getenv("PGPASSWORD", "pg123") +DB_NAME = os.getenv("PGDATABASE", "missions_db") + +def get_conn(): + return psycopg2.connect( + host=DB_HOST, + port=DB_PORT, + user=DB_USER, + password=DB_PASS, + dbname=DB_NAME + ) + +# updated device list +devices = ["fruit-camera-01", "fruit-camera-02", "fruit-camera-03"] +severities = [1,2,3,4] + +def insert_alert(): + conn = get_conn() + cur = conn.cursor() + + alert_id = str(uuid.uuid4()) + alert_type = "fruit_defect_detected" + device_id = random.choice(devices) + started_at = datetime.now(timezone.utc) + + ended_at = (started_at + timedelta(minutes=random.randint(1,5))) if random.random() < 0.3 else None + severity = random.choice(severities) + confidence = round(random.uniform(0.4, 0.99), 2) + + lat = 31.751 + random.uniform(-0.005, 0.005) + lon = 35.022 + random.uniform(-0.005, 0.005) + image_url = f"https://minio-hot:9000/fake/{alert_id}.jpg" + + meta = {"generator": "fruit_alert_generator"} + + cur.execute( + ''' + INSERT INTO alerts ( + alert_id, alert_type, device_id, started_at, ended_at, + confidence, severity, image_url, lat, lon, area, meta, + created_at, updated_at + ) + VALUES ( + %(alert_id)s, %(alert_type)s, %(device_id)s, %(started_at)s, %(ended_at)s, + %(confidence)s, %(severity)s, %(image_url)s, %(lat)s, %(lon)s, + %(area)s, %(meta)s, now(), now() + ) + ''', + { + "alert_id": alert_id, + "alert_type": alert_type, + "device_id": device_id, + "started_at": started_at, + "ended_at": ended_at, + "confidence": confidence, + "severity": severity, + "image_url": image_url, + "lat": lat, + "lon": lon, + "area": None, + "meta": json.dumps(meta) + } + ) + + conn.commit() + cur.close() + conn.close() + print(f"[GENERATOR] Inserted alert {alert_id} device={device_id} severity={severity}") + +def main(): + print("Fruit Alert Generator started.") + while True: + insert_alert() + time.sleep(30) + +if __name__ == "__main__": + main() diff --git a/services/fruit_defect_sink/Dockerfile b/services/fruit_defect_sink/Dockerfile new file mode 100644 index 000000000..c4889df5c --- /dev/null +++ b/services/fruit_defect_sink/Dockerfile @@ -0,0 +1,5 @@ +FROM python:3.11-slim +RUN pip install --no-cache-dir confluent-kafka psycopg2-binary +WORKDIR /app +COPY fruit_defect_sink.py ./ +CMD ["python","-u","fruit_defect_sink.py"] diff --git a/services/fruit_defect_sink/fruit_defect_sink.py b/services/fruit_defect_sink/fruit_defect_sink.py new file mode 100644 index 000000000..a6d0108be --- /dev/null +++ b/services/fruit_defect_sink/fruit_defect_sink.py @@ -0,0 +1,400 @@ +#!/usr/bin/env python3 +import os +import sys +import json +import signal +import logging +from datetime import datetime, timezone +from uuid import uuid4 + +from confluent_kafka import Consumer, Producer +import psycopg2 +import psycopg2.extras + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s [%(levelname)s] %(message)s", + stream=sys.stdout, +) + +# ========================== +# Config from environment +# ========================== + +KAFKA_BOOTSTRAP_SERVERS = os.getenv("KAFKA_BOOTSTRAP_SERVERS", "kafka:9092") +CONSUME_TOPIC = os.getenv("FRUIT_DISPATCHED_TOPIC", "inference.dispatched.fruit") +ALERTS_TOPIC = os.getenv("ALERTS_TOPIC", "alerts") +KAFKA_GROUP_ID = os.getenv("KAFKA_GROUP_ID", "fruit-defect-sink") + +PG_HOST = os.getenv("PGHOST", "postgres") +PG_PORT = int(os.getenv("PGPORT", "5432")) +PG_DB = os.getenv("PGDATABASE", "missions_db") +PG_USER = os.getenv("PGUSER", "missions_user") +PG_PASSWORD = os.getenv("PGPASSWORD", "pg123") + + +# ========================== +# Postgres helpers +# ========================== + +def get_pg_conn(): + logging.info( + "connecting to Postgres: host=%s db=%s user=%s", + PG_HOST, + PG_DB, + PG_USER, + ) + conn = psycopg2.connect( + host=PG_HOST, + port=PG_PORT, + dbname=PG_DB, + user=PG_USER, + password=PG_PASSWORD, + ) + conn.autocommit = True + return conn + + +INSERT_SQL = """ +INSERT INTO public.fruit_defect_predictions ( + ts, + bucket, + object_key, + image_uri, + label, + score, + confidence, + latency_ms_http, + latency_ms_model, + device_id, + idem_key, + corr_id, + extra +) +VALUES ( + %(ts)s, + %(bucket)s, + %(object_key)s, + %(image_uri)s, + %(label)s, + %(score)s, + %(confidence)s, + %(latency_ms_http)s, + %(latency_ms_model)s, + %(device_id)s, + %(idem_key)s, + %(corr_id)s, + %(extra)s +) +ON CONFLICT (idem_key) DO UPDATE +SET + ts = EXCLUDED.ts, + bucket = EXCLUDED.bucket, + object_key = EXCLUDED.object_key, + image_uri = EXCLUDED.image_uri, + label = EXCLUDED.label, + score = EXCLUDED.score, + confidence = EXCLUDED.confidence, + latency_ms_http = EXCLUDED.latency_ms_http, + latency_ms_model = EXCLUDED.latency_ms_model, + device_id = EXCLUDED.device_id, + corr_id = EXCLUDED.corr_id, + extra = EXCLUDED.extra; +""" + + +# ========================== +# Kafka + processing +# ========================== + +def parse_timestamp(ts_str: str | None) -> datetime: + """ + Try to parse an ISO timestamp from the message. + Falls back to 'now' in UTC if not provided / invalid. + """ + if not ts_str: + return datetime.now(timezone.utc) + try: + # handle "Z" + if ts_str.endswith("Z"): + ts_str = ts_str.replace("Z", "+00:00") + return datetime.fromisoformat(ts_str) + except Exception: + return datetime.now(timezone.utc) + + +def handle_message(envelope: dict, conn, producer: Producer): + """ + Process a single message envelope: upsert to Postgres and maybe send alert. + """ + # basic sanity + if not envelope.get("ok", True): + logging.warning("skipping message with ok=false: %s", envelope) + return + + status = envelope.get("status") + if status and status != 200: + logging.warning("skipping message with non-200 status: %s", envelope) + return + + body_raw = envelope.get("body") + if not body_raw: + logging.warning("no 'body' field in message, skipping") + return + + # Support dict or string JSON + if isinstance(body_raw, dict): + body = body_raw + else: + try: + body = json.loads(body_raw) + except Exception as e: + logging.error("failed to parse body JSON: %s; error=%s", body_raw, e) + return + # Parse result — can be missing (fruit-ok detection) + result = body.get("result", {}) or {} + + event = envelope.get("event", {}) or {} + + # Extract bucket/key from body first + bucket = body.get("bucket") + object_key = body.get("key") + + # If missing — try event (legacy) + if not bucket: + bucket = event.get("bucket") + if not object_key: + object_key = event.get("key") + + # If still missing — try MinIO Key format: "imagery/fruit/tree/...jpg" + minio_key = event.get("Key") + if minio_key and (not bucket or not object_key): + parts = minio_key.split("/", 1) + if len(parts) == 2: + bucket = bucket or parts[0] + object_key = object_key or parts[1] + + image_uri = body.get("image_uri") + if not image_uri and bucket and object_key: + image_uri = f"s3://{bucket}/{object_key}" + + label = result.get("label") or body.get("label") + score = result.get("score") + confidence = result.get("confidence") + + try: + score = float(score) if score is not None else None + except (TypeError, ValueError): + score = None + + try: + confidence = float(confidence) if confidence is not None else None + except (TypeError, ValueError): + confidence = None + + latency_ms_model = result.get("latency_ms_model") or body.get("latency_ms_model") + latency_ms_http = body.get("latency_ms") + + device_id = ( + event.get("device_id") + or body.get("device_id") + or envelope.get("device_id") + ) + + idem_key = body.get("idempotency_key") or envelope.get("event_id") or str(uuid4()) + corr_id = body.get("correlation_id") or envelope.get("event_id") + + ts_str = body.get("timestamp") or envelope.get("timestamp") + ts = parse_timestamp(ts_str) + + extra = { + "envelope": envelope, + "body_parsed": body, + } + + params = { + "ts": ts, + "bucket": bucket, + "object_key": object_key, + "image_uri": image_uri, + "label": label, + "score": score, + "confidence": confidence, + "latency_ms_http": latency_ms_http, + "latency_ms_model": latency_ms_model, + "device_id": device_id, + "idem_key": idem_key, + "corr_id": corr_id, + "extra": json.dumps(extra), + } + + # ========================== + # Insert / upsert to Postgres + # ========================== + with conn.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur: + cur.execute(INSERT_SQL, params) + + logging.info( + "[sink] upserted fruit_defect_predictions idem_key=%s label=%s bucket=%s key=%s", + idem_key, + label, + bucket, + object_key, + ) + + # ========================== + # Send alert if needed + # ========================== + maybe_send_alert( + producer=producer, + label=label, + confidence=confidence, + ts=ts, + device_id=device_id, + bucket=bucket, + object_key=object_key, + image_uri=image_uri, + latency_ms_model=latency_ms_model, + idem_key=idem_key, + ) + + +def maybe_send_alert( + producer: Producer, + label: str | None, + confidence: float | None, + ts: datetime, + device_id: str | None, + bucket: str | None, + object_key: str | None, + image_uri: str | None, + latency_ms_model: float | None, + idem_key: str, +): + """ + Send an alert to the alerts topic if the label indicates a defect. + """ + + if label != "defect": + return + + alert_id = idem_key or str(uuid4()) + + alert = { + # --- Required fields --- + "alert_id": alert_id, + "alert_type": "fruit_defect_detected", + "device_id": device_id or "unknown-device", + "started_at": ts.astimezone(timezone.utc).isoformat(), + + # --- Optional / dynamic fields --- + "ended_at": None, + "confidence": confidence, + # "severity": 3, + # "area": None, + # "lat": None, + # "lon": None, + "image_url": image_uri, + # "vod": None, + # "hls": None, + "meta": { + "bucket": bucket, + "object_key": object_key, + "latency_ms_model": latency_ms_model, + "alert_source": "fruit_defect_sink", + }, + } + + payload = json.dumps(alert).encode("utf-8") + producer.produce(ALERTS_TOPIC, payload) + producer.flush() + + logging.info( + "[sink] sent alert to topic '%s' alert_id=%s device_id=%s label=%s", + ALERTS_TOPIC, + alert_id, + device_id, + label, + ) + + +# ========================== +# Main +# ========================== + +running = True + + +def _handle_sig(signum, frame): + global running + logging.info("received signal %s, shutting down...", signum) + running = False + + +def main(): + global running + + signal.signal(signal.SIGINT, _handle_sig) + signal.signal(signal.SIGTERM, _handle_sig) + + consumer_conf = { + "bootstrap.servers": KAFKA_BOOTSTRAP_SERVERS, + "group.id": KAFKA_GROUP_ID, + "auto.offset.reset": "earliest", + "enable.auto.commit": True, + } + + consumer = Consumer(consumer_conf) + producer = Producer({"bootstrap.servers": KAFKA_BOOTSTRAP_SERVERS}) + + conn = get_pg_conn() + + logging.info( + "[sink] listening on %s → Postgres.fruit_defect_predictions + alerts", + CONSUME_TOPIC, + ) + consumer.subscribe([CONSUME_TOPIC]) + + try: + while running: + msg = consumer.poll(1.0) + if msg is None: + continue + + if msg.error(): + logging.error("Kafka error: %s", msg.error()) + continue + + try: + envelope = json.loads(msg.value().decode("utf-8")) + except Exception as e: + logging.error("failed to decode message value: %s", e) + continue + + try: + handle_message(envelope, conn, producer) + except psycopg2.Error as e: + logging.error("Postgres error: %s", e) + try: + conn.close() + except Exception: + pass + conn = get_pg_conn() + except Exception as e: + logging.exception("processing error: %s", e) + + finally: + logging.info("closing consumer and postgres connection...") + try: + consumer.close() + except Exception: + pass + try: + conn.close() + except Exception: + pass + + +if __name__ == "__main__": + main() + diff --git a/services/fruit_metrics/Dockerfile b/services/fruit_metrics/Dockerfile new file mode 100644 index 000000000..cda6f0bd6 --- /dev/null +++ b/services/fruit_metrics/Dockerfile @@ -0,0 +1,11 @@ +FROM python:3.12-slim + +WORKDIR /app + +COPY requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt + +COPY fruit_metrics.py . + +EXPOSE 8050 +CMD ["uvicorn", "fruit_metrics:app", "--host", "0.0.0.0", "--port", "8050"] diff --git a/services/fruit_metrics/fruit_metrics.py b/services/fruit_metrics/fruit_metrics.py new file mode 100644 index 000000000..81e0886a7 --- /dev/null +++ b/services/fruit_metrics/fruit_metrics.py @@ -0,0 +1,106 @@ +from fastapi import FastAPI +from starlette.responses import Response +from prometheus_client import Gauge, CollectorRegistry, generate_latest, CONTENT_TYPE_LATEST +import psycopg2 +import psycopg2.extras +import threading +import time +import os + +REFRESH_EVERY = 10 # seconds + +# ───────────────────────────────────────────── +# Connect to PostgreSQL directly +# ───────────────────────────────────────────── +def get_db_connection(): + return psycopg2.connect( + host="postgres", + port=5432, + user="missions_user", + password="pg123", + dbname="missions_db" + ) + +# ───────────────────────────────────────────── +# Create Prometheus registry +# ───────────────────────────────────────────── +reg = CollectorRegistry() + +g_total = Gauge("fruit_alerts_total", "Total fruit alerts", registry=reg) +g_active = Gauge("fruit_alerts_active", "Active fruit alerts", registry=reg) +g_by_type = Gauge("fruit_alerts_by_type", "Alerts by type", ["type"], registry=reg) +g_by_severity = Gauge("fruit_alerts_by_severity", "Alerts by severity", ["severity"], registry=reg) +g_by_device = Gauge("fruit_alerts_by_device", "Alerts by device", ["device"], registry=reg) + +# ───────────────────────────────────────────── +# Query the database +# ───────────────────────────────────────────── +def fetch_alerts(): + try: + conn = get_db_connection() + cur = conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) + cur.execute("SELECT * FROM alerts") + rows = cur.fetchall() + cur.close() + conn.close() + return rows + except Exception as e: + print("DB ERROR:", e) + return [] + +# ───────────────────────────────────────────── +# Metrics refresher loop +# ───────────────────────────────────────────── +def refresh_loop(): + while True: + alerts = fetch_alerts() + + types = {} + severities = {} + devices = {} + + total = len(alerts) + active = 0 + + for a in alerts: + # count active alerts + if a.get("ended_at") is None: + active += 1 + + # count by type + t = a.get("alert_type") or "unknown" + types[t] = types.get(t, 0) + 1 + + # count by severity + sev = str(a.get("severity") or 1) + severities[sev] = severities.get(sev, 0) + 1 + + # count by device + dev = a.get("device_id") or "unknown" + devices[dev] = devices.get(dev, 0) + 1 + + # update gauges + g_total.set(total) + g_active.set(active) + + for t, count in types.items(): + g_by_type.labels(t).set(count) + + for sev, count in severities.items(): + g_by_severity.labels(sev).set(count) + + for dev, count in devices.items(): + g_by_device.labels(dev).set(count) + + time.sleep(REFRESH_EVERY) + +threading.Thread(target=refresh_loop, daemon=True).start() + +# ───────────────────────────────────────────── +# FastAPI endpoint for Prometheus +# ───────────────────────────────────────────── +app = FastAPI() + +@app.get("/metrics") +def metrics(): + return Response(generate_latest(reg), media_type=CONTENT_TYPE_LATEST) diff --git a/services/fruit_metrics/requirements.txt b/services/fruit_metrics/requirements.txt new file mode 100644 index 000000000..a45218664 --- /dev/null +++ b/services/fruit_metrics/requirements.txt @@ -0,0 +1,5 @@ +fastapi +uvicorn +prometheus_client +starlette +psycopg2-binary diff --git a/services/fruit_ripeness_alert/Dockerfile b/services/fruit_ripeness_alert/Dockerfile index 9ce14035e..0603b1cba 100644 --- a/services/fruit_ripeness_alert/Dockerfile +++ b/services/fruit_ripeness_alert/Dockerfile @@ -1,18 +1,18 @@ -FROM python:3.11-slim - -# --- System setup --- -WORKDIR /app -ENV PYTHONUNBUFFERED=1 \ - PYTHONDONTWRITEBYTECODE=1 \ - TZ=UTC - -# --- Dependencies --- -COPY requirements.txt . -RUN pip install --no-cache-dir -r requirements.txt - -# --- App --- -COPY . . - - -# --- Default command --- -CMD ["python", "-u", "app.py"] +FROM python:3.11-slim + +# --- System setup --- +WORKDIR /app +ENV PYTHONUNBUFFERED=1 \ + PYTHONDONTWRITEBYTECODE=1 \ + TZ=UTC + +# --- Dependencies --- +COPY requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt + +# --- App --- +COPY . . + + +# --- Default command --- +CMD ["python", "-u", "app.py"] diff --git a/services/fruit_ripeness_alert/app.py b/services/fruit_ripeness_alert/app.py index 2be5af652..eff4c84c7 100644 --- a/services/fruit_ripeness_alert/app.py +++ b/services/fruit_ripeness_alert/app.py @@ -1,126 +1,121 @@ -#!/usr/bin/env python3 -import os, json, uuid, requests -from datetime import datetime, timedelta, timezone -from kafka import KafkaProducer -from token_bootstrap import get_service_token - -# === Environment === -DB_API_BASE = os.getenv("DB_API_BASE", "http://db_api_service:8001") -DB_API_TOKEN_FILE = os.getenv("DB_API_TOKEN_FILE", "/app/secret/db_api_token") -KAFKA_BROKER = os.getenv("KAFKA_BROKER", "kafka:9092") -ALERT_TOPIC = os.getenv("ALERT_TOPIC", "alerts") -WINDOW_HOURS = int(os.getenv("WINDOW_HOURS", "168")) - - -def now_utc() -> datetime: - return datetime.now(timezone.utc) - -def iso(ts: datetime) -> str: - return ts.replace(tzinfo=timezone.utc).isoformat() - -def get_threshold(task_name="ripeness", headers=None): - """שולף את אחוז הסף מהטבלה task_thresholds לפי שם המשימה.""" - url = f"{DB_API_BASE}/api/tables/task_thresholds" - r = requests.get(url, headers=headers, timeout=15) - r.raise_for_status() - rows = r.json().get("rows", []) - if not rows: - print(f"[WARN] No thresholds found at all, using default 0.8") - return 0.8 - - match = next((row for row in rows if row.get("task") == task_name), None) - if not match: - print(f"[WARN] No threshold found for task={task_name}, using default 0.8") - return 0.8 - - threshold = float(match.get("threshold", 0.8)) - print(f"[INFO] Task '{task_name}' threshold: {threshold*100:.1f}%") - return threshold -from datetime import datetime, timezone - -def get_rollups(window_start, window_end, headers=None): - """ - שולפת את כל הרשומות מהטבלה ripeness_weekly_rollups_ts - ואז מסננת לפי טווח התאריכים (window_start → window_end) בפייתון. - """ - url = f"{DB_API_BASE}/api/tables/ripeness_weekly_rollups_ts" - print(f"[DEBUG] Fetching full table from {url}", flush=True) - - try: - # שולף את כל הנתונים (בלי פילטרים) - r = requests.get(url, headers=headers, timeout=60) - r.raise_for_status() - except requests.exceptions.HTTPError as e: - print(f"[ERROR] HTTP {r.status_code}: {r.text}", flush=True) - return [] - except Exception as e: - print(f"[ERROR] failed to fetch rollups: {e}", flush=True) - return [] - - data = r.json() - rows = data.get("rows", data) - - - def parse_ts(ts_str: str) -> datetime: - try: - return datetime.fromisoformat(ts_str.replace("Z", "+00:00")) - except Exception: - return datetime.min.replace(tzinfo=timezone.utc) - - filtered = [] - for row in rows: - ts = parse_ts(row.get("ts", "")) - if window_start <= ts <= window_end: - filtered.append(row) - - print(f"[INFO] Retrieved {len(filtered)} rollups after filtering (out of {len(rows)} total)") - return filtered - -def send_kafka_alert(producer, device_id, ratio, threshold): - alert = { - "alert_id": str(uuid.uuid4()), - "alert_type": "fruit_ripeness_high", - "device_id": device_id, - "started_at": iso(now_utc()), - "confidence": float(ratio), - "severity": 3, - "threshold": threshold, - "description": f"{ratio*100:.1f}% ripe/overripe fruits", # <── וגם את זה - } - - producer.send(ALERT_TOPIC, json.dumps(alert).encode("utf-8")) - producer.flush() - print(f"[ALERT] sent for {device_id}: {ratio*100:.1f}%") - -def main(): - token = get_service_token() - headers = {"Content-Type": "application/json"} - if token: - headers["X-Service-Token"] = token - - window_end = now_utc() - window_start = window_end - timedelta(hours=WINDOW_HOURS) - print(f"[INFO] Checking rollups {window_start} → {window_end}") - - threshold = get_threshold("ripeness", headers) - rows = get_rollups(window_start, window_end, headers) - if not rows: - print("[INFO] No data found.") - return - - producer = KafkaProducer(bootstrap_servers=[KAFKA_BROKER]) - - # iterate each device - for row in rows: - device_id = row.get("device_id") - pct = row.get("pct_ripe", 0.0) - if pct >= threshold: - send_kafka_alert(producer, device_id, pct, threshold) - else: - print(f"[INFO] {device_id}: below threshold {pct:.2f} < {threshold:.2f}") - - producer.close() - print("[DONE] process complete.") - -if __name__ == "__main__": - main() +#!/usr/bin/env python3 +import os, json, uuid, requests +from datetime import datetime, timedelta, timezone +from kafka import KafkaProducer +from token_bootstrap import get_service_token + +# === Environment === +DB_API_BASE = os.getenv("DB_API_BASE", "http://db_api_service:8001") +DB_API_TOKEN_FILE = os.getenv("DB_API_TOKEN_FILE", "/app/secret/db_api_token") +KAFKA_BROKER = os.getenv("KAFKA_BROKER", "kafka:9092") +ALERT_TOPIC = os.getenv("ALERT_TOPIC", "alerts") +WINDOW_HOURS = int(os.getenv("WINDOW_HOURS", "168")) + + +def now_utc() -> datetime: + return datetime.now(timezone.utc) + +def iso(ts: datetime) -> str: + return ts.replace(tzinfo=timezone.utc).isoformat() + +def get_threshold(task_name="ripeness", headers=None): + url = f"{DB_API_BASE}/api/tables/task_thresholds" + r = requests.get(url, headers=headers, timeout=15) + r.raise_for_status() + rows = r.json().get("rows", []) + if not rows: + print(f"[WARN] No thresholds found at all, using default 0.8") + return 0.8 + + match = next((row for row in rows if row.get("task") == task_name), None) + if not match: + print(f"[WARN] No threshold found for task={task_name}, using default 0.8") + return 0.8 + + threshold = float(match.get("threshold", 0.8)) + print(f"[INFO] Task '{task_name}' threshold: {threshold*100:.1f}%") + return threshold +from datetime import datetime, timezone + +def get_rollups(window_start, window_end, headers=None): + + url = f"{DB_API_BASE}/api/tables/ripeness_weekly_rollups_ts" + print(f"[DEBUG] Fetching full table from {url}", flush=True) + + try: + r = requests.get(url, headers=headers, timeout=60) + r.raise_for_status() + except requests.exceptions.HTTPError as e: + print(f"[ERROR] HTTP {r.status_code}: {r.text}", flush=True) + return [] + except Exception as e: + print(f"[ERROR] failed to fetch rollups: {e}", flush=True) + return [] + + data = r.json() + rows = data.get("rows", data) + + + def parse_ts(ts_str: str) -> datetime: + try: + return datetime.fromisoformat(ts_str.replace("Z", "+00:00")) + except Exception: + return datetime.min.replace(tzinfo=timezone.utc) + + filtered = [] + for row in rows: + ts = parse_ts(row.get("ts", "")) + if window_start <= ts <= window_end: + filtered.append(row) + + print(f"[INFO] Retrieved {len(filtered)} rollups after filtering (out of {len(rows)} total)") + return filtered + +def send_kafka_alert(producer, device_id, ratio, threshold): + alert = { + "alert_id": str(uuid.uuid4()), + "alert_type": "fruit_ripeness_high", + "device_id": device_id, + "started_at": iso(now_utc()), + "confidence": float(ratio), + "severity": 3, + "threshold": threshold, + "description": f"{ratio*100:.1f}% ripe/overripe fruits", + } + + producer.send(ALERT_TOPIC, json.dumps(alert).encode("utf-8")) + producer.flush() + print(f"[ALERT] sent for {device_id}: {ratio*100:.1f}%") + +def main(): + token = get_service_token() + headers = {"Content-Type": "application/json"} + if token: + headers["X-Service-Token"] = token + + window_end = now_utc() + window_start = window_end - timedelta(hours=WINDOW_HOURS) + print(f"[INFO] Checking rollups {window_start} → {window_end}") + + threshold = get_threshold("ripeness", headers) + rows = get_rollups(window_start, window_end, headers) + if not rows: + print("[INFO] No data found.") + return + + producer = KafkaProducer(bootstrap_servers=[KAFKA_BROKER]) + + # iterate each device + for row in rows: + device_id = row.get("device_id") + pct = row.get("pct_ripe", 0.0) + if pct >= threshold: + send_kafka_alert(producer, device_id, pct, threshold) + else: + print(f"[INFO] {device_id}: below threshold {pct:.2f} < {threshold:.2f}") + + producer.close() + print("[DONE] process complete.") + +if __name__ == "__main__": + main() diff --git a/services/fruit_ripeness_alert/docker-compose.yml b/services/fruit_ripeness_alert/docker-compose.yml index 7b38bd72c..7a6966ee9 100644 --- a/services/fruit_ripeness_alert/docker-compose.yml +++ b/services/fruit_ripeness_alert/docker-compose.yml @@ -1,23 +1,23 @@ -services: - fruit_ripeness_alert: - build: . - container_name: fruit_ripeness_alert - environment: - - DB_API_BASE=http://db_api_service:8001 - - DB_API_SERVICE_NAME=fruit_ripeness_alert - - DB_ADMIN_USER=admin - - DB_ADMIN_PASS=admin123 - - DB_API_TOKEN_FILE=/app/secret/db_api_token - - KAFKA_BROKER=kafka:9092 - - ALERT_TOPIC=alerts - - WINDOW_HOURS=168 - volumes: - - .:/app - - ./secret:/app/secret - command: ["sleep", "infinity"] - networks: - - ag_cloud - -networks: - ag_cloud: - external: true +services: + fruit_ripeness_alert: + build: . + container_name: fruit_ripeness_alert + environment: + - DB_API_BASE=http://db_api_service:8001 + - DB_API_SERVICE_NAME=fruit_ripeness_alert + - DB_ADMIN_USER=admin + - DB_ADMIN_PASS=admin123 + - DB_API_TOKEN_FILE=/app/secret/db_api_token + - KAFKA_BROKER=kafka:9092 + - ALERT_TOPIC=alerts + - WINDOW_HOURS=168 + volumes: + - .:/app + - ./secret:/app/secret + command: ["sleep", "infinity"] + networks: + - ag_cloud + +networks: + ag_cloud: + external: true diff --git a/services/fruit_ripeness_alert/requirements.txt b/services/fruit_ripeness_alert/requirements.txt index ff4cc1b07..d9e23d1df 100644 --- a/services/fruit_ripeness_alert/requirements.txt +++ b/services/fruit_ripeness_alert/requirements.txt @@ -1,2 +1,2 @@ -requests -kafka-python +requests +kafka-python diff --git a/services/fruit_ripeness_alert/token_bootstrap.py b/services/fruit_ripeness_alert/token_bootstrap.py index 2bcd5ab40..a1dee593b 100644 --- a/services/fruit_ripeness_alert/token_bootstrap.py +++ b/services/fruit_ripeness_alert/token_bootstrap.py @@ -1,62 +1,62 @@ -import os, pathlib, time, requests - -DB_API_BASE = os.getenv("DB_API_BASE", "").strip() -DB_API_TOKEN_FILE = os.getenv("DB_API_TOKEN_FILE", "/app/secret/db_api_token") -DB_API_SERVICE_NAME = os.getenv("DB_API_SERVICE_NAME", "fruit_ripeness_alert").strip() or "fruit_ripeness_alert" - -def _safe_join_url(base: str, path: str) -> str: - return f"{base.rstrip('/')}/{path.lstrip('/')}" - -def _read_token(path: str) -> str | None: - p = pathlib.Path(path) - if p.exists(): - t = p.read_text(encoding="utf-8").strip() - if t and "***" not in t: - return t - return None - -def _write_token(path: str, token: str) -> None: - p = pathlib.Path(path) - p.parent.mkdir(parents=True, exist_ok=True) - p.write_text(token, encoding="utf-8") - -def _try_dev_bootstrap(): - """Try to get token using /auth/_dev_bootstrap (new API).""" - url = _safe_join_url(DB_API_BASE, "/auth/_dev_bootstrap") - payload = {"service_name": DB_API_SERVICE_NAME, "rotate_if_exists": True} - try: - r = requests.post(url, json=payload, timeout=10) - if r.status_code in (200, 201): - data = r.json() - sa = data.get("service_account") or {} - token = sa.get("raw_token") or sa.get("token") - if token and "***" not in token: - print("[BOOTSTRAP] obtained token via /auth/_dev_bootstrap") - return token.strip() - print(f"[BOOTSTRAP][WARN] _dev_bootstrap returned {r.status_code}: {r.text[:100]}") - except Exception as e: - print(f"[BOOTSTRAP][ERROR] {e}") - return None - -def get_service_token() -> str | None: - """Get or create a service token automatically.""" - if not DB_API_BASE: - print("[BOOTSTRAP][WARN] DB_API_BASE not set") - return None - - # Try existing file - token = _read_token(DB_API_TOKEN_FILE) - if token: - print(f"[BOOTSTRAP] using existing token from {DB_API_TOKEN_FILE}") - return token - - # Try bootstrap (new unified API) - print(f"[BOOTSTRAP] fetching new service token from {DB_API_BASE}") - token = _try_dev_bootstrap() - if token: - _write_token(DB_API_TOKEN_FILE, token) - print(f"[BOOTSTRAP] wrote token to {DB_API_TOKEN_FILE}") - return token - - print("[BOOTSTRAP][ERROR] Could not obtain service token.") - return None +import os, pathlib, time, requests + +DB_API_BASE = os.getenv("DB_API_BASE", "").strip() +DB_API_TOKEN_FILE = os.getenv("DB_API_TOKEN_FILE", "/app/secret/db_api_token") +DB_API_SERVICE_NAME = os.getenv("DB_API_SERVICE_NAME", "fruit_ripeness_alert").strip() or "fruit_ripeness_alert" + +def _safe_join_url(base: str, path: str) -> str: + return f"{base.rstrip('/')}/{path.lstrip('/')}" + +def _read_token(path: str) -> str | None: + p = pathlib.Path(path) + if p.exists(): + t = p.read_text(encoding="utf-8").strip() + if t and "***" not in t: + return t + return None + +def _write_token(path: str, token: str) -> None: + p = pathlib.Path(path) + p.parent.mkdir(parents=True, exist_ok=True) + p.write_text(token, encoding="utf-8") + +def _try_dev_bootstrap(): + """Try to get token using /auth/_dev_bootstrap (new API).""" + url = _safe_join_url(DB_API_BASE, "/auth/_dev_bootstrap") + payload = {"service_name": DB_API_SERVICE_NAME, "rotate_if_exists": True} + try: + r = requests.post(url, json=payload, timeout=10) + if r.status_code in (200, 201): + data = r.json() + sa = data.get("service_account") or {} + token = sa.get("raw_token") or sa.get("token") + if token and "***" not in token: + print("[BOOTSTRAP] obtained token via /auth/_dev_bootstrap") + return token.strip() + print(f"[BOOTSTRAP][WARN] _dev_bootstrap returned {r.status_code}: {r.text[:100]}") + except Exception as e: + print(f"[BOOTSTRAP][ERROR] {e}") + return None + +def get_service_token() -> str | None: + """Get or create a service token automatically.""" + if not DB_API_BASE: + print("[BOOTSTRAP][WARN] DB_API_BASE not set") + return None + + # Try existing file + token = _read_token(DB_API_TOKEN_FILE) + if token: + print(f"[BOOTSTRAP] using existing token from {DB_API_TOKEN_FILE}") + return token + + # Try bootstrap (new unified API) + print(f"[BOOTSTRAP] fetching new service token from {DB_API_BASE}") + token = _try_dev_bootstrap() + if token: + _write_token(DB_API_TOKEN_FILE, token) + print(f"[BOOTSTRAP] wrote token to {DB_API_TOKEN_FILE}") + return token + + print("[BOOTSTRAP][ERROR] Could not obtain service token.") + return None diff --git a/services/image-linker/Dockerfile.flink b/services/image-linker/Dockerfile.flink index dd05fc18d..3e9a58b41 100644 --- a/services/image-linker/Dockerfile.flink +++ b/services/image-linker/Dockerfile.flink @@ -4,9 +4,18 @@ FROM flink:1.19.3-scala_2.12-java11 USER root -# Add local CA (place netfree-ca.crt next to this Dockerfile before building) -COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt -RUN chmod 644 /usr/local/share/ca-certificates/netfree-ca.crt && update-ca-certificates +# Optional local CA (NetFree or others) - works with or without certs +COPY certs/ /tmp/certs + +RUN if [ -n "$(ls /tmp/certs/*.crt 2>/dev/null)" ]; then \ + echo "Configuring extra CA certificates from /tmp/certs..."; \ + cp /tmp/certs/*.crt /usr/local/share/ca-certificates/ && \ + chmod 644 /usr/local/share/ca-certificates/*.crt && \ + update-ca-certificates; \ + else \ + echo "No extra CA certificates found, skipping CA setup."; \ + fi + ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt diff --git a/services/inference_http/Dockerfile b/services/inference_http/Dockerfile index 3cca0c0e6..fe091eb58 100644 --- a/services/inference_http/Dockerfile +++ b/services/inference_http/Dockerfile @@ -3,61 +3,47 @@ # ============================================================ FROM python:3.11-slim - - ENV PIP_NO_CACHE_DIR=1 \ PIP_DISABLE_PIP_VERSION_CHECK=1 \ PIP_DEFAULT_TIMEOUT=1200 - WORKDIR /app +# System deps (keep all original runtime + dev packages for other teams) RUN apt-get update && apt-get install -y --no-install-recommends \ - libglib2.0-0 \ - libglib2.0-dev \ - libsm6 \ - libxrender1 \ - libxext6 \ - libgl1 \ - libopenblas-dev \ - liblapack-dev \ + ca-certificates curl \ + libglib2.0-0 libglib2.0-dev \ + libsm6 libxrender1 libxext6 libgl1 \ + libopenblas-dev liblapack-dev \ && rm -rf /var/lib/apt/lists/* -RUN python -m pip install --upgrade pip setuptools wheel --only-binary=:all: && \ - pip install --no-cache-dir numpy==1.26.4 --only-binary=:all: && \ - pip install --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu \ - torch==2.1.2 torchvision==0.16.2 --only-binary=:all: --upgrade-strategy only-if-needed - - -ENV PIP_NO_CACHE_DIR=1 \ - PIP_DEFAULT_TIMEOUT=1200 \ - PIP_DISABLE_PIP_VERSION_CHECK=1 - -WORKDIR /app - -# Copy certs dir (may be empty) and trust *.crt if present -RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates curl && \ - rm -rf /var/lib/apt/lists/* && \ - if [ -d /tmp/certs ] && ls /tmp/certs/*.crt >/dev/null 2>&1; then \ - cp /tmp/certs/*.crt /usr/local/share/ca-certificates/ && \ - chmod 644 /usr/local/share/ca-certificates/*.crt && \ - update-ca-certificates; \ +# --- Trust enterprise CAs BEFORE any pip install (works with/without certs folder) --- +# If ./certs exists in build context, copy it (may be empty) and trust *.crt silently. +COPY certs/ /tmp/certs/ +RUN if [ -d /tmp/certs ] && ls /tmp/certs/*.crt >/dev/null 2>&1; then \ + cp /tmp/certs/*.crt /usr/local/share/ca-certificates/ && \ + chmod 644 /usr/local/share/ca-certificates/*.crt && \ + update-ca-certificates; \ else \ - echo "No extra CA certs found. Skipping CA update."; \ + echo "No extra CA certs found. Skipping CA update."; \ fi +# Make pip/requests/curl use the system trust store ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ CURL_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ PIP_CERT=/etc/ssl/certs/ca-certificates.crt RUN printf "[global]\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf -# Python deps -RUN python -m pip install --upgrade pip setuptools wheel certifi && \ - pip install --no-cache-dir numpy==1.26.4 --only-binary=:all: +RUN python -m pip install --upgrade pip setuptools wheel --only-binary=:all: && \ + pip install --no-cache-dir numpy==1.26.4 --only-binary=:all: && \ + pip install --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu \ + torch==2.1.2 torchvision==0.16.2 --only-binary=:all: --upgrade-strategy only-if-needed + -RUN pip install --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu \ - torch==2.1.2 torchvision==0.16.2 --only-binary=:all: --upgrade-strategy only-if-needed +ENV PIP_NO_CACHE_DIR=1 \ + PIP_DEFAULT_TIMEOUT=1200 \ + PIP_DISABLE_PIP_VERSION_CHECK=1 COPY requirements.txt /app/requirements.txt @@ -77,7 +63,7 @@ COPY app.py model_registry.py /app/ COPY adapters /app/adapters COPY models /app/models COPY weights /app/weights - +COPY models/soil_moisture/artifacts /app/artifacts EXPOSE 8004 diff --git a/services/inference_http/adapters/fruit_defect_runner.py b/services/inference_http/adapters/fruit_defect_runner.py index 5a1cd00eb..8b51ebf24 100644 --- a/services/inference_http/adapters/fruit_defect_runner.py +++ b/services/inference_http/adapters/fruit_defect_runner.py @@ -1,3 +1,42 @@ +# import os, io +# from pathlib import Path +# from typing import Any, Dict, Optional + +# from PIL import Image +# import torch + +# # Core code imported from your fruit-defect module +# from models.fruit_defect.inference.infer_fruit_defect import ( +# load_model, get_preprocess, infer_single +# ) + +# # Local weights only +# WEIGHTS_PATH = Path(os.getenv("WEIGHTS_PATH", "/app/weights/fruit_cls_best.ts")) + +# def _ensure_local_weights(p: Path) -> Path: +# if not p.exists(): +# raise FileNotFoundError(f"Local weights not found at: {p}") +# return p + +# class FruitDefectRunner: +# def __init__(self, model_tag: Optional[str] = None): +# # Allows selecting a different weights file in future via extra/model_tag +# weights_path = _ensure_local_weights(WEIGHTS_PATH) +# self.model = load_model(weights_path) +# self.preprocess = get_preprocess() +# self.device = "cuda" if torch.cuda.is_available() else "cpu" +# self.model = self.model.to(self.device).eval() + +# def run(self, image_bytes: bytes, model_tag=None, extra=None) -> Dict[str, Any]: +# img = Image.open(io.BytesIO(image_bytes)).convert("RGB") +# result = infer_single(self.model, img, self.preprocess, device=self.device) +# # Normalize to standard HTTP response structure +# return { +# "label": result.get("status"), +# "score": result.get("prob_defect"), +# "confidence": result.get("confidence"), +# "latency_ms_model": result.get("latency_ms_model"), +# } import os, io from pathlib import Path from typing import Any, Dict, Optional @@ -27,13 +66,33 @@ def __init__(self, model_tag: Optional[str] = None): self.device = "cuda" if torch.cuda.is_available() else "cpu" self.model = self.model.to(self.device).eval() + # def run(self, image_bytes: bytes, model_tag=None, extra=None) -> Dict[str, Any]: + # img = Image.open(io.BytesIO(image_bytes)).convert("RGB") + # result = infer_single(self.model, img, self.preprocess, device=self.device) + # # Normalize to standard HTTP response structure + # return { + # "label": result.get("status"), + # "score": result.get("prob_defect"), + # "confidence": result.get("confidence"), + # "latency_ms_model": result.get("latency_ms_model"), + # } + def run(self, image_bytes: bytes, model_tag=None, extra=None) -> Dict[str, Any]: img = Image.open(io.BytesIO(image_bytes)).convert("RGB") result = infer_single(self.model, img, self.preprocess, device=self.device) - # Normalize to standard HTTP response structure + bucket = extra.get("bucket") if extra else None + key = extra.get("key") if extra else None + device_id = extra.get("device_id") if extra else None + timestamp = extra.get("timestamp") if extra else None + return { + "ok": True, "label": result.get("status"), "score": result.get("prob_defect"), "confidence": result.get("confidence"), "latency_ms_model": result.get("latency_ms_model"), + "bucket": bucket, + "key": key, + "device_id": device_id, + "timestamp": timestamp, } diff --git a/services/inference_http/adapters/fruit_segmentation_runner.py b/services/inference_http/adapters/fruit_segmentation_runner.py index 7df623a8d..621a23362 100644 --- a/services/inference_http/adapters/fruit_segmentation_runner.py +++ b/services/inference_http/adapters/fruit_segmentation_runner.py @@ -1,4 +1,8 @@ -import os, io, tempfile, hashlib, cv2, numpy as np, boto3, torch +import os, tempfile, hashlib, cv2, numpy as np, boto3, torch, json +import re +from datetime import datetime +from kafka import KafkaProducer +import psycopg2 def allow_unrestricted_torch_load(): _original_load = torch.load @@ -12,7 +16,7 @@ def patched_load(*args, **kwargs): import time from typing import Any, Dict, Optional -from datetime import datetime, timezone +from datetime import datetime from ultralytics import YOLO def sha256_hex(path: str) -> str: @@ -37,6 +41,69 @@ def __init__(self, weights_path: Optional[str] = None, model_tag: Optional[str] aws_access_key_id=os.getenv("MINIO_ACCESS_KEY", "minioadmin"), aws_secret_access_key=os.getenv("MINIO_SECRET_KEY", "minioadmin123") ) + self.producer = KafkaProducer( + bootstrap_servers=os.getenv("KAFKA_BOOTSTRAP", "kafka:9092"), + value_serializer=lambda v: json.dumps(v).encode("utf-8") + ) + self.output_topic = "flink-dispatcher-fruit" + self.db = psycopg2.connect( + host=os.getenv("PGHOST", "postgres"), + port=os.getenv("PGPORT", "5432"), + dbname=os.getenv("PGDATABASE", "missions_db"), + user=os.getenv("PGUSER", "missions_user"), + password=os.getenv("PGPASSWORD", "pg123") + ) + self.db.autocommit = True + + + + def publish_event(self, data: dict): + """Publish fruit metadata to Kafka topic.""" + try: + self.producer.send(self.output_topic, data) + self.producer.flush() + except Exception as e: + print(f"[ERROR] failed to publish event: {e}", flush=True) + + def write_fruit_record( + self, + original_key, + cropped_key, + bucket, + device_id, + timestamp_str, + x1, y1, x2, y2, + label, + latency + ): + cur = self.db.cursor() + cur.execute( + """ + INSERT INTO fruit_detections ( + original_key, + cropped_key, + bucket, + device_id, + timestamp, + x1, y1, x2, y2, + label, + latency_ms_model + ) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s); + """, + ( + original_key, + cropped_key, + bucket, + device_id, + timestamp_str, + x1, y1, x2, y2, + label, + latency + ) + ) + cur.close() + + def run(self, image_bytes: bytes | None = None, model_tag=None, extra=None) -> Dict[str, Any]: """Main inference entrypoint for HTTP""" bucket_in = extra.get("bucket") if extra else "imagery" @@ -77,16 +144,51 @@ def run(self, image_bytes: bytes | None = None, model_tag=None, extra=None) -> D crop = img[y1:y2, x1:x2] if crop.size == 0: continue - out_name = f"{os.path.splitext(os.path.basename(key))[0]}_fruit_{i+1}.jpg" - out_key = f"segments/{out_name}" + + base_name = os.path.splitext(os.path.basename(key))[0] + match = re.match(r"([a-zA-Z0-9-]+)_(\d{8}T\d{6}Z)", base_name) + if match: + device_id, timestamp_str = match.groups() + timestamp = datetime.strptime(timestamp_str, "%Y%m%dT%H%M%SZ") + date_part = timestamp.strftime("%Y-%m-%d") + else: + device_id = "unknown_device" + date_part = "unknown_date" + count += 1 + out_name = f"{base_name}.jpg" + out_key = f"fruit/fruits/{device_id}/{date_part}/{out_name}" out_path = os.path.join(tmpdir, out_name) cv2.imwrite(out_path, crop) + self.s3.upload_file(out_path, bucket_in, out_key) - count += 1 - - return { - "label": "fruit", - "count": count, - "latency_ms_model": latency_ms, - "bucket_out": bucket_in - } + + event = { + "ok": True, + "team": "camera", + "bucket": bucket_in, + "key": out_key, + "label": "fruit", + "device_id": device_id, + "timestamp": timestamp_str, + "latency_ms_model": latency_ms, + "original_key": key, + "bbox": { + "x1": int(x1), + "y1": int(y1), + "x2": int(x2), + "y2": int(y2) + } + } + self.publish_event(event) + self.write_fruit_record( + original_key=key, + cropped_key=out_key, + bucket=bucket_in, + device_id=device_id, + timestamp_str=timestamp_str, + x1=x1, y1=y1, x2=x2, y2=y2, + label="fruit", + latency=latency_ms + ) + + pass \ No newline at end of file diff --git a/services/inference_http/adapters/rover_runner.py b/services/inference_http/adapters/rover_runner.py new file mode 100644 index 000000000..c5bfefaef --- /dev/null +++ b/services/inference_http/adapters/rover_runner.py @@ -0,0 +1,178 @@ +# services/inference_http/adapters/rover_runner.py +# Bridge between unified HTTP /infer_json and fence_hole_detector service logic. + +from __future__ import annotations + +from typing import Any, Dict, Optional +from datetime import datetime +import json +import logging + +from models.fence_hole_detector.service import InferenceInput, infer_from_minio + +logger = logging.getLogger(__name__) + + +def _to_plain_dict(obj: Any) -> Any: + """Best-effort conversion of arbitrary objects to a plain dict or JSON-like object.""" + if isinstance(obj, (dict, str, bytes, bytearray)): + return obj + + # Pydantic v2 models + if hasattr(obj, "model_dump"): + try: + return obj.model_dump() + except Exception: + pass + + # Pydantic v1 or similar objects + if hasattr(obj, "dict"): + try: + return obj.dict() + except Exception: + pass + + # Generic Python objects with __dict__ + if hasattr(obj, "__dict__"): + try: + return vars(obj) + except Exception: + pass + + return obj + + +def _search_bucket_key(node: Any) -> Optional[Dict[str, Any]]: + """ + Recursively search for a dict that contains both 'bucket' and 'key'. + + This walks nested dicts and lists/tuples and returns the first match. + """ + node = _to_plain_dict(node) + + if isinstance(node, dict): + if "bucket" in node and "key" in node: + return node + + for value in node.values(): + found = _search_bucket_key(value) + if found is not None: + return found + + elif isinstance(node, (list, tuple)): + for item in node: + found = _search_bucket_key(item) + if found is not None: + return found + + return None + + +def _extract_payload(obj: Any) -> Dict[str, Any]: + """ + Normalize a generic event/envelope into a flat dict with bucket/key. + + Supports: + - {"bucket": "...", "key": "...", ...} + - {"event": {...}}, {"data": {...}}, etc. + - Pydantic models, nested dicts, lists + - JSON strings/bytes + """ + obj = _to_plain_dict(obj) + + # If this is a JSON string or bytes, try to parse it. + if isinstance(obj, (str, bytes, bytearray)): + try: + obj = json.loads(obj) + except Exception: + logger.warning("rover_runner: failed to json.loads extra payload: %r", obj) + return {} + + # For dicts/lists/tuples, search for bucket/key recursively. + if isinstance(obj, (dict, list, tuple)): + found = _search_bucket_key(obj) + if isinstance(found, dict): + return found + + # As a fallback, if this is a dict without bucket/key, just return it. + if isinstance(obj, dict): + return obj + + return {} + + +class RoverRunner: + """ + Adapter that executes the fence_hole_detector service logic. + + The unified HTTP layer usually: + 1. Parses the JSON body into a dict. + 2. Downloads the image bytes from MinIO. + 3. Calls runner.run(image_bytes, extra=parsed_body). + + We ignore the image bytes and call infer_from_minio again using bucket/key + from the extra payload, so the existing service code does not need changes. + """ + + def __init__(self, weights_path: Optional[str] = None, + model_tag: Optional[str] = None) -> None: + # Weights are controlled via FENCE_ONNX_PATH env var inside the service. + self.model_tag = model_tag or "yolov8n-onnx" + + def run( + self, + image_bytes: Optional[bytes] = None, + model_tag: Optional[str] = None, + extra: Optional[Dict[str, Any]] = None, + ) -> Dict[str, Any]: + """ + Main entrypoint for the unified /infer_json service. + + Expected call pattern: + run(image_bytes=, extra=) + + We: + - Extract bucket/key (and optional metadata) from extra. + - Build InferenceInput and call infer_from_minio(). + - Attach a standard 'model' field to the result. + """ + logger.info( + "RoverRunner.run: got image_bytes_type=%s extra=%r", + type(image_bytes), + extra, + ) + + payload: Dict[str, Any] = _extract_payload(extra or {}) + logger.info("RoverRunner.run: extracted payload=%r", payload) + + # Accept common alternative field names as a backup. + bucket = payload.get("bucket") or payload.get("s3_bucket") + key = payload.get("key") or payload.get("s3_key") or payload.get("object_key") + + if not bucket or not key: + msg = f"Missing required fields: bucket/key in payload={payload!r}" + logger.error("RoverRunner.run: %s", msg) + raise ValueError(msg) + + # Optional metadata: timestamp and geo / device info. + ts = payload.get("captured_at") + captured_at: Optional[datetime] = None + if ts: + try: + captured_at = datetime.fromisoformat(str(ts).replace("Z", "+00:00")) + except Exception: + captured_at = None + + inp = InferenceInput( + bucket=bucket, + key=key, + captured_at=captured_at, + device_id=payload.get("device_id"), + area=payload.get("area"), + lat=payload.get("lat"), + lon=payload.get("lon"), + ) + + result = infer_from_minio(inp) + result["model"] = self.model_tag + return result diff --git a/services/inference_http/adapters/soil_moisture_runner.py b/services/inference_http/adapters/soil_moisture_runner.py new file mode 100644 index 000000000..7c1624c70 --- /dev/null +++ b/services/inference_http/adapters/soil_moisture_runner.py @@ -0,0 +1,158 @@ + +""" +Adapter for soil moisture inference in the generic HTTP inference flow. +Uses the shared inference logic from the soil-moisture service. +""" + +import os +import base64 +import logging +import sys +from typing import Any, Dict, Optional +from PIL import Image +from io import BytesIO +import numpy as np +import cv2 +import time +import re + +logger = logging.getLogger(__name__) + + +class SoilMoistureRunner: + """ + Adapter that wraps the soil moisture inference logic. + """ + + def __init__(self, weights_path: Optional[str] = None, model_tag: Optional[str] = None): + self.model_tag = model_tag + self.weights_path = weights_path + + try: + # Add models directory to path + models_dir = os.path.join(os.path.dirname(__file__), '..', 'models') + if models_dir not in sys.path: + sys.path.insert(0, models_dir) + + # Import soil moisture components + from soil_moisture.src.app.config import Settings, load_zones + from soil_moisture.src.app.inference import Inferencer + from soil_moisture.src.app.db import DB + from soil_moisture.src.app.inference_logic import SoilMoistureInferenceLogic + + logger.info("Initializing SoilMoistureRunner...") + + # Initialize components + self.settings = Settings() + + # Load zones config if available + if hasattr(self.settings, 'zones_file') and self.settings.zones_file: + if os.path.exists(self.settings.zones_file): + self.zones_cfg = load_zones(self.settings.zones_file) + else: + logger.warning(f"zones_file not found: {self.settings.zones_file}") + self.zones_cfg = {} + else: + self.zones_cfg = {} + + self.db = DB(self.settings.pg_dsn) + self.inferencer = Inferencer(self.settings, self.db) + + # Initialize Kafka producer (optional) + producer = None + try: + from soil_moisture.src.app.kafka_producer import ControlProducer + producer = ControlProducer( + self.settings.kafka_brokers, + self.settings.kafka_topic, + self.settings.kafka_dlt + ) + except Exception as e: + logger.warning(f"Kafka producer init failed: {e}") + + # Initialize shared inference logic + self.inference_logic = SoilMoistureInferenceLogic( + settings=self.settings, + db=self.db, + inferencer=self.inferencer, + producer=producer + ) + + logger.info("SoilMoistureRunner initialized successfully!") + + except Exception as e: + logger.error(f"Failed to initialize SoilMoistureRunner: {e}", exc_info=True) + raise + + def run(self, image_bytes: Any, model_tag: Optional[str] = None, + extra: Optional[Dict] = None) -> Dict: + """ + Run soil moisture inference using the shared inference logic. + """ + start_time = time.time() + + try: + bucket_in = extra.get("bucket") if extra else "imagery" + key = extra.get("key") if extra else None + if not key: + return {"error": "missing key"} + + # --- Extract device_id from the key (pattern: path/to/image/dev-id_ts.jpg) --- + def extract_device_id_from_key(key: str) -> str: + filename = key.split("/")[-1] # get "dev-id_ts.jpg" + match = re.match(r"([^_]+)_", filename) # capture part before "_" + if match: + return match.group(1) + return "unknown" + + # --- Decode image --- + img_array = np.frombuffer(image_bytes, np.uint8) + img = cv2.imdecode(img_array, cv2.IMREAD_COLOR) + if img is None: + return {"error": "failed to decode image from bytes"} + + # --- Determine device_id --- + device_id = "unknown" + if extra: + if "device_id" in extra: + device_id = extra["device_id"] + elif "filename" in extra: + device_id = self.inference_logic.extract_device_id(extra["filename"]) + elif "key" in extra: + device_id = extract_device_id_from_key(extra["key"]) + + # --- Convert input to PIL Image --- + if isinstance(image_bytes, bytes): + img = Image.open(BytesIO(image_bytes)) + elif isinstance(image_bytes, str): + img_bytes = base64.b64decode(image_bytes) + img = Image.open(BytesIO(img_bytes)) + elif isinstance(image_bytes, Image.Image): + img = image_bytes + else: + raise ValueError(f"Unsupported input type: {type(image_bytes)}") + + # --- Run inference --- + result = self.inference_logic.infer_from_image(img, device_id) + + return { + "device_id": result["device_id"], + "dry_ratio": result["dry_ratio"], + "decision": result["decision"], + "confidence": result["confidence"], + "patch_count": result["patch_count"], + "duration_min": result.get("duration_min", 0), + "latency_ms_model": result.get("latency_ms", 0), + "ts": result.get("ts"), + "idempotency_key": result.get("idempotency_key"), + "debug": result.get("debug") + } + + except Exception as e: + logger.error(f"Inference failed: {e}", exc_info=True) + latency_ms = int((time.time() - start_time) * 1000) + return { + "error": str(e), + "device_id": locals().get("device_id", "unknown"), + "latency_ms_model": latency_ms + } \ No newline at end of file diff --git a/services/inference_http/app.py b/services/inference_http/app.py index ec6b984e9..b01e91831 100644 --- a/services/inference_http/app.py +++ b/services/inference_http/app.py @@ -72,8 +72,8 @@ def infer_json( latency_ms = int((time.perf_counter() - started) * 1000) return { "ok": True, - "team": TEAM, - "result": result, + **result, + "team": TEAM, "image_uri": s3_uri, "latency_ms": latency_ms, "idempotency_key": idem_key, @@ -81,4 +81,4 @@ def infer_json( } except Exception as e: - raise HTTPException(status_code=500, detail=f"inference failed: {e}") + raise HTTPException(status_code=500, detail=f"inference failed: {e}") \ No newline at end of file diff --git a/services/inference_http/model_registry.py b/services/inference_http/model_registry.py index 12cf00e6b..c5a150586 100644 --- a/services/inference_http/model_registry.py +++ b/services/inference_http/model_registry.py @@ -1,10 +1,17 @@ from adapters.fruit_defect_runner import FruitDefectRunner from adapters.fruit_segmentation_runner import FruitSegmentationRunner +from adapters.soil_moisture_runner import SoilMoistureRunner +from adapters.rover_runner import RoverRunner + def get_model_runner(team: str): t = (team or "").lower() - if t == "fruit_defect": + if t == "fruit": return FruitDefectRunner() if t == "camera": return FruitSegmentationRunner() + if t == "soil_moisture": + return SoilMoistureRunner() + if t == "rover": + return RoverRunner() raise ValueError(f"unknown TEAM {t}") diff --git a/services/inference_http/models/fence_hole_detector/.env.example b/services/inference_http/models/fence_hole_detector/.env.example new file mode 100644 index 000000000..96eeac6b8 --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/.env.example @@ -0,0 +1,20 @@ +# Model +FENCE_ONNX_PATH=runs_fence/y8n_cpu_v1/weights/best.onnx +FENCE_CONF=0.30 +FENCE_ROI=none +FENCE_MIN_OVERLAP=0.30 +FENCE_VOTE_N=1 +FENCE_VOTE_M=1 +FENCE_VOTE_COOLDOWN=0 +FENCE_IMG_SIZE=640 + +# MinIO +MINIO_ENDPOINT=127.0.0.1:9000 +MINIO_ACCESS_KEY=minioadmin +MINIO_SECRET_KEY=minioadmin +MINIO_BUCKET=rover-images +MINIO_SECURE=false + +# Alert Manager +ALERT_MANAGER_URL= +ALERT_ENABLE_AUTO_POST=false diff --git a/services/inference_http/models/fence_hole_detector/Dockerfile b/services/inference_http/models/fence_hole_detector/Dockerfile new file mode 100644 index 000000000..86e65a336 --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/Dockerfile @@ -0,0 +1,41 @@ +# Base image +FROM python:3.11-slim + +# System deps for OpenCV wheels + SSL + curl +RUN apt-get update && apt-get install -y --no-install-recommends \ + libgl1 libglib2.0-0 ca-certificates curl && \ + rm -rf /var/lib/apt/lists/* + +# Trust store (optional org CAs) +WORKDIR /app +COPY certs/ /app/certs/ +RUN if ls /app/certs/*.crt >/dev/null 2>&1; then \ + cp /app/certs/*.crt /usr/local/share/ca-certificates/ && update-ca-certificates; \ + else \ + echo "No custom CA certs found, skipping."; \ + fi +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt + +# Install Python deps early for better layer caching +COPY requirements.txt /tmp/requirements.txt +RUN python -m pip install --upgrade pip && \ + pip install --no-cache-dir -r /tmp/requirements.txt + +# Copy service sources into a package path: /app/services/fence_hole_detector +# This preserves the import path 'services.fence_hole_detector.*' +COPY . /app/services/fence_hole_detector + +# Ensure these are packages (PEP420 usually ok, but we make it explicit) +RUN mkdir -p /app/services && \ + touch /app/services/__init__.py && \ + touch /app/services/fence_hole_detector/__init__.py + +# Make sure Python can import from /app +ENV PYTHONPATH=/app + +EXPOSE 8088 + +# Run FastAPI app (module path) +CMD ["uvicorn", "services.fence_hole_detector.app:app", \ + "--host", "0.0.0.0", "--port", "8088", "--log-level", "info"] diff --git a/services/inference_http/models/fence_hole_detector/__init__.py b/services/inference_http/models/fence_hole_detector/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/inference_http/models/fence_hole_detector/alert_client.py b/services/inference_http/models/fence_hole_detector/alert_client.py new file mode 100644 index 000000000..eb9e9d905 --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/alert_client.py @@ -0,0 +1,129 @@ +import json +import os +import uuid +from datetime import datetime, timezone + +from kafka import KafkaProducer +from kafka.admin import KafkaAdminClient, NewTopic +from kafka.errors import TopicAlreadyExistsError, NoBrokersAvailable + +# --- Configuration (env-first) --- +_BOOTSTRAP = os.getenv("KAFKA_BOOTSTRAP", "kafka:9092") +_TOPIC = os.getenv("ALERTS_TOPIC", "alerts") +_ALERT_TYPE = os.getenv("ALERT_TYPE", "fence_hole") + +# You can tune these if you want faster failures during dev. +_PRODUCER_KW = dict( + bootstrap_servers=_BOOTSTRAP, + value_serializer=lambda v: json.dumps(v, ensure_ascii=False).encode("utf-8"), + linger_ms=50, + retries=5, + request_timeout_ms=10_000, + metadata_max_age_ms=15_000, +) + +_admin = None +_producer = None + + +def _iso(ts: datetime | None) -> str: + """Return RFC3339/ISO-8601 UTC string without microseconds (…Z).""" + return ( + (ts or datetime.now(timezone.utc)) + .astimezone(timezone.utc) + .replace(microsecond=0) + .isoformat() + .replace("+00:00", "Z") + ) + + +def _get_admin() -> KafkaAdminClient: + """Create a singleton admin client.""" + global _admin + if _admin is None: + _admin = KafkaAdminClient(bootstrap_servers=_BOOTSTRAP, request_timeout_ms=10_000) + return _admin + + +def _ensure_topic(topic: str, num_partitions: int = 1, replication_factor: int = 1) -> None: + """ + Idempotently create the topic if it doesn't exist. + This is required because auto-create is disabled on the broker. + """ + try: + admin = _get_admin() + new_topic = NewTopic(name=topic, num_partitions=num_partitions, + replication_factor=replication_factor) + admin.create_topics([new_topic], validate_only=False) + except TopicAlreadyExistsError: + # OK: topic already present. + return + except NoBrokersAvailable as e: + # Bubble up; the caller will log and continue the request flow. + raise e + except Exception: + # For repeated concurrent creates we may see unknown errors from the broker; + # treat them as non-fatal if the topic exists by the time we send. + pass + + +def _get_producer() -> KafkaProducer: + """Create a singleton producer.""" + global _producer + if _producer is None: + _producer = KafkaProducer(**_PRODUCER_KW) + return _producer + + +def post_alert( + *, + device_id: str, + started_at: datetime, + confidence: float, + image_url: str | None, + area: str | None = None, + lat: float | None = None, + lon: float | None = None, + severity: int | None = None, + extra: dict | None = None, +) -> str: + """ + Build and send an alert message to Kafka in the agreed schema. + Returns the generated alert_id (UUID string). + Raises if the broker is not reachable. + """ + # Ensure topic exists (safe to call on every send). + _ensure_topic(_TOPIC) + + alert_id = str(uuid.uuid4()) + payload = { + # Required + "alert_id": alert_id, + "alert_type": _ALERT_TYPE, + "device_id": device_id, + "started_at": _iso(started_at), + + # Optional/metadata + "confidence": round(float(confidence), 3), + } + if severity is not None: + payload["severity"] = int(severity) + if area: + payload["area"] = area + if lat is not None: + payload["lat"] = float(lat) + if lon is not None: + payload["lon"] = float(lon) + if image_url: + payload["image_url"] = image_url + if extra: + payload["meta"] = extra + + # Send + producer = _get_producer() + fut = producer.send(_TOPIC, payload) + # Block until acknowledged (fail fast in dev) + fut.get(timeout=10.0) + producer.flush(timeout=5.0) + + return alert_id diff --git a/services/inference_http/models/fence_hole_detector/app.py b/services/inference_http/models/fence_hole_detector/app.py new file mode 100644 index 000000000..0cee99a35 --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/app.py @@ -0,0 +1,177 @@ +# services/fence_hole_detector/app.py +from fastapi import FastAPI, HTTPException +from pydantic import BaseModel, Field +from typing import Optional +import os, io, cv2, numpy as np +from minio import Minio +from datetime import datetime, timezone +from dotenv import load_dotenv + +from .infer import OnnxDetector +from .alert_client import post_alert # used only if alerts are enabled + +# Load .env next to this file if present +load_dotenv(dotenv_path=os.path.join(os.path.dirname(__file__), ".env")) + +# --- Config (env-first) --- +ONNX_PATH = os.getenv("FENCE_ONNX_PATH", "best.onnx") +CONF = float(os.getenv("FENCE_CONF", "0.30")) + +MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "localhost:9000") +MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "") +MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "") +MINIO_BUCKET = os.getenv("MINIO_BUCKET", "rover-images") +MINIO_SECURE = os.getenv("MINIO_SECURE", "false").lower() == "true" +PUBLIC_BASE_URL = os.getenv("MINIO_PUBLIC_BASE_URL", "").rstrip("/") + +DEFAULT_DEVICE_ID = os.getenv("DEFAULT_DEVICE_ID", "camera-01") +DEFAULT_AREA = os.getenv("DEFAULT_AREA", "north_field") +DEFAULT_SEVERITY = int(os.getenv("DEFAULT_SEVERITY", "3")) + +# Critical: alerts flag (0/1). When 0, service will never talk to Kafka. +ALERT_ENABLED = os.getenv("ALERT_ENABLED", "0") == "1" + +# --- App objects --- +app = FastAPI(title="fence_hole_detector") + +detector = OnnxDetector( + onnx_path=ONNX_PATH, + conf=CONF, + roi=os.getenv("FENCE_ROI", "none"), + vote_n=int(os.getenv("FENCE_VOTE_N", "1")), + vote_m=int(os.getenv("FENCE_VOTE_M", "1")), + cooldown=int(os.getenv("FENCE_VOTE_COOLDOWN", "0")), +) + +minio_client = Minio( + MINIO_ENDPOINT, + access_key=MINIO_ACCESS_KEY, + secret_key=MINIO_SECRET_KEY, + secure=MINIO_SECURE, +) + +# --- Schemas --- +class ProcessReq(BaseModel): + bucket: str = Field(default_factory=lambda: MINIO_BUCKET) + key: str + captured_at: Optional[datetime] = None # ISO, e.g. "2025-10-29T14:32:12Z" + device_id: Optional[str] = None + area: Optional[str] = None + lat: Optional[float] = None + lon: Optional[float] = None + +class ProcessResp(BaseModel): + detected_boxes: int + fired_alert: int + max_conf: float + alert_id: Optional[str] = None + image_url: Optional[str] = None + +# --------------------------------------------------------------------------- +# Compatibility wrapper for the generic Flink HTTP dispatcher: +# Exposes /infer_json to match the expected contract in the README. +# It simply converts the input to ProcessReq and delegates to /process_minio. +# --------------------------------------------------------------------------- + +class InferJsonReq(BaseModel): + """Generic request schema expected by Flink HTTP dispatcher (/infer_json).""" + bucket: str + key: str + # Optional metadata (passthrough to alerts, if enabled) + captured_at: Optional[datetime] = None + device_id: Optional[str] = None + area: Optional[str] = None + lat: Optional[float] = None + lon: Optional[float] = None + +@app.post("/infer_json", response_model=ProcessResp) +def infer_json(req: InferJsonReq): + """ + Thin wrapper to keep a stable endpoint name for the Flink dispatcher. + Internally it reuses the exact same inference flow as /process_minio. + """ + # Convert to the internal request model and call the existing logic. + internal = ProcessReq( + bucket=req.bucket, + key=req.key, + captured_at=req.captured_at, + device_id=req.device_id, + area=req.area, + lat=req.lat, + lon=req.lon, + ) + return process_minio(internal) + +# --- Helpers --- +def read_minio_image(bucket: str, key: str): + try: + resp = minio_client.get_object(bucket, key) + data = resp.read() + resp.close(); resp.release_conn() + except Exception as e: + raise HTTPException(status_code=404, detail=f"MinIO get_object failed: {e}") + img_array = np.frombuffer(data, np.uint8) + img = cv2.imdecode(img_array, cv2.IMREAD_COLOR) + if img is None: + raise HTTPException(status_code=415, detail="Failed to decode image") + return img + +def build_image_url(bucket: str, key: str) -> str: + # Prefer a public base URL if provided, else use presigned URL for 24h + if PUBLIC_BASE_URL: + return f"{PUBLIC_BASE_URL}/{key}" + try: + return minio_client.get_presigned_url("GET", bucket, key, expires=24*60*60) + except Exception: + scheme = "https" if MINIO_SECURE else "http" + return f"{scheme}://{MINIO_ENDPOINT}/{bucket}/{key}" + +# --- Health --- +@app.get("/health") +def health(): + return {"status": "ok"} + +# --- Main endpoint: Flink -> HTTP --- +@app.post("/process_minio", response_model=ProcessResp) +def process_minio(req: ProcessReq): + bucket = req.bucket or MINIO_BUCKET + key = req.key + if not key: + raise HTTPException(400, "key is required") + + # 1) Read image from MinIO + img = read_minio_image(bucket, key) + + # 2) Inference + det, detected, fired, max_conf = detector.infer_image(img) + + # 3) Optional alert + alert_id = None + image_url = build_image_url(bucket, key) if detected else None + + if detected and ALERT_ENABLED: + try: + started_at = req.captured_at or datetime.now(timezone.utc) + alert_id = post_alert( + device_id=req.device_id or DEFAULT_DEVICE_ID, + started_at=started_at, + confidence=max_conf, + image_url=image_url, + area=req.area or DEFAULT_AREA, + lat=req.lat, lon=req.lon, + severity=DEFAULT_SEVERITY, + extra={"bucket": bucket, "key": key}, + ) + except Exception as e: + # Never fail the request because of the alert pipeline + # (log prints will appear in the Uvicorn console) + print(f"[WARN] alert send failed: {e}") + + # Note: fired_alert == 1 means "detected now" (no voting when camera batches) + return ProcessResp( + detected_boxes=int(len(det)), + fired_alert=int(1 if detected else 0), + max_conf=float(max_conf), + alert_id=alert_id, + image_url=image_url, + ) diff --git a/services/inference_http/models/fence_hole_detector/config.py b/services/inference_http/models/fence_hole_detector/config.py new file mode 100644 index 000000000..3ea5e60d4 --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/config.py @@ -0,0 +1,26 @@ +import os + +# --- Model / Inference --- +ONNX_PATH = os.getenv("FENCE_ONNX_PATH", "runs_fence/y8n_cpu_v1/weights/best.onnx") +CONF = float(os.getenv("FENCE_CONF", "0.30")) + +# ROI: "none" or "ymin-ymax" ("0.20-0.85") +ROI = os.getenv("FENCE_ROI", "none") +MIN_OVERLAP = float(os.getenv("FENCE_MIN_OVERLAP", "0.20")) + +VOTE_N = int(os.getenv("FENCE_VOTE_N", "1")) +VOTE_M = int(os.getenv("FENCE_VOTE_M", "1")) +VOTE_COOLDOWN = int(os.getenv("FENCE_VOTE_COOLDOWN", "0")) + +IMG_SIZE = int(os.getenv("FENCE_IMG_SIZE", "640")) + +# --- MinIO --- +MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "") +MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "") +MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "") +MINIO_BUCKET = os.getenv("MINIO_BUCKET", "") +MINIO_SECURE = os.getenv("MINIO_SECURE", "false").lower() == "true" + +# --- Alert Manager --- +ALERT_MANAGER_URL = os.getenv("ALERT_MANAGER_URL", "") # http://localhost:9093/api/v2/alerts +ALERT_ENABLE_AUTO_POST = os.getenv("ALERT_ENABLE_AUTO_POST", "false").lower() == "true" diff --git a/services/inference_http/models/fence_hole_detector/infer.py b/services/inference_http/models/fence_hole_detector/infer.py new file mode 100644 index 000000000..cfc4873ee --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/infer.py @@ -0,0 +1,253 @@ +import cv2 +import numpy as np +import onnxruntime as ort +from collections import deque +from typing import List, Tuple +from .config import ( + CONF, ROI, MIN_OVERLAP, VOTE_N, VOTE_M, VOTE_COOLDOWN, IMG_SIZE, ONNX_PATH +) + +# ----------------------- image utilities ----------------------- # + +def letterbox(im: np.ndarray, new_shape: int = 640, color=(114, 114, 114)) -> np.ndarray: + """ + Resize with unchanged aspect ratio (scale) and pad to a square canvas. + Padding is placed on the right/bottom only (top-left anchored). + Returns a (new_shape, new_shape, 3) uint8 image. + """ + h, w = im.shape[:2] + r = min(new_shape / h, new_shape / w) + nh, nw = int(round(h * r)), int(round(w * r)) + im_resized = cv2.resize(im, (nw, nh), interpolation=cv2.INTER_LINEAR) + canvas = np.full((new_shape, new_shape, 3), color, dtype=np.uint8) + canvas[:nh, :nw] = im_resized + return canvas + +def xywh_to_xyxy(xywh: np.ndarray) -> np.ndarray: + """Convert [x, y, w, h] to [x1, y1, x2, y2].""" + x, y, w, h = np.split(xywh, 4, axis=1) + x1 = x - w / 2.0 + y1 = y - h / 2.0 + x2 = x + w / 2.0 + y2 = y + h / 2.0 + return np.concatenate([x1, y1, x2, y2], axis=1) + +# ----------------------- ONNX output normalization ----------------------- # + +def _to_xywh_conf_cls(raw: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: + """ + Normalize raw ONNX output to (A, 5 or more) and return: + - xywh_conf: (A, 5) float32 = [x, y, w, h, conf] + - cls_idx: (A, 1) float32 = best class id (0 when single-class) + Supports typical Ultralytics shapes: + (1, 5, 8400), (1, 6, 8400), (1, 84, 8400), (A, 5/6/84) and post-NMS (N, 6). + """ + arr = raw + + # If it is already post-NMS of shape (N, 6): [x1,y1,x2,y2,conf,cls] -> convert back to xywh for uniformity + if arr.ndim == 2 and arr.shape[1] == 6 and (arr.dtype == np.float32 or arr.dtype == np.float64): + # We will treat it specially in the caller (no further NMS required). + # Return a marker by sending empty xywh; caller detects via None. + return None, None # type: ignore[return-value] + + # Squeeze batch dim if present + if arr.ndim == 3 and arr.shape[0] == 1: + arr = np.squeeze(arr, axis=0) # (C, A) + elif arr.ndim == 4 and arr.shape[0] == 1: + arr = np.squeeze(arr, axis=0) + + # If layout is (C, A), transpose to (A, C) + if arr.ndim == 2 and arr.shape[0] in (5, 6, 84): + arr = arr.T # (A, C) + + if arr.ndim != 2: + raise ValueError(f"Unexpected ONNX output shape {raw.shape}") + + A, C = arr.shape + arr = arr.astype(np.float32) + + if C == 5: + # [x,y,w,h,conf] single-class + xywh_conf = arr[:, :5] + cls_idx = np.zeros((A, 1), dtype=np.float32) + elif C == 6: + # Either [x,y,w,h,obj,cls] for single-class or already has 2 confidences. + obj = arr[:, 4:5] + cls_score = arr[:, 5:6] + conf = obj * cls_score + xywh_conf = np.concatenate([arr[:, :4], conf], axis=1) + cls_idx = np.zeros((A, 1), dtype=np.float32) # single-class + elif C > 6: + # [x,y,w,h,obj, cls0..clsN] + obj = arr[:, 4:5] + cls_scores = arr[:, 5:] + cls_idx = np.argmax(cls_scores, axis=1, keepdims=True).astype(np.float32) + max_cls = np.max(cls_scores, axis=1, keepdims=True) + conf = obj * max_cls + xywh_conf = np.concatenate([arr[:, :4], conf], axis=1) + else: + raise ValueError(f"Unsupported channel count C={C} in ONNX output") + + return xywh_conf, cls_idx + +# ----------------------- NMS utilities ----------------------- # + +def _iou_xyxy(box: np.ndarray, boxes: np.ndarray) -> np.ndarray: + """Compute IoU between one box [x1,y1,x2,y2] and many boxes.""" + x1 = np.maximum(box[0], boxes[:, 0]) + y1 = np.maximum(box[1], boxes[:, 1]) + x2 = np.minimum(box[2], boxes[:, 2]) + y2 = np.minimum(box[3], boxes[:, 3]) + + inter = np.maximum(0.0, x2 - x1) * np.maximum(0.0, y2 - y1) + area1 = (box[2] - box[0]) * (box[3] - box[1]) + area2 = (boxes[:, 2] - boxes[:, 0]) * (boxes[:, 3] - boxes[:, 1]) + union = np.maximum(area1 + area2 - inter, 1e-9) + return inter / union + +def nms_xyxy(boxes: np.ndarray, scores: np.ndarray, iou_th: float = 0.45, topk: int = 300) -> List[int]: + """ + Greedy NMS. boxes: (N,4) in xyxy, scores: (N,) + Returns list of kept indices. + """ + idxs = scores.argsort()[::-1] + keep: List[int] = [] + while idxs.size > 0: + i = int(idxs[0]) + keep.append(i) + if len(keep) >= topk or idxs.size == 1: + break + ious = _iou_xyxy(boxes[i], boxes[idxs[1:]]) + idxs = idxs[1:][ious < iou_th] + return keep + +# ----------------------- ROI helpers ----------------------- # + +def overlap_ratio_with_roi(box: np.ndarray, H: int, ymin_frac: float, ymax_frac: float) -> float: + x1, y1, x2, y2 = box + box_h = max(0.0, y2 - y1) + if box_h <= 0: + return 0.0 + roi_y1 = ymin_frac * H + roi_y2 = ymax_frac * H + inter_h = max(0.0, min(y2, roi_y2) - max(y1, roi_y1)) + return inter_h / (box_h + 1e-9) + +def filter_boxes_by_roi(boxes: np.ndarray, H: int, ymin_frac: float, ymax_frac: float, + min_overlap: float = 0.20) -> np.ndarray: + # boxes: ndarray [N,6] = x1,y1,x2,y2,conf,cls + keep = [] + for b in boxes: + if overlap_ratio_with_roi(b[:4], H, ymin_frac, ymax_frac) >= min_overlap: + keep.append(b) + return np.array(keep, dtype=np.float32) if keep else np.empty((0, 6), dtype=np.float32) + +# ----------------------- vote logic ----------------------- # + +class VoteNM: + def __init__(self, N=2, M=3, cooldown_frames=10): + self.N = N + self.M = M + self.buf = deque(maxlen=M) + self.curr = 0 + self.cooldown = cooldown_frames + + def update(self, detected: bool) -> bool: + if self.curr > 0: + self.curr -= 1 + self.buf.append(1 if detected else 0) + if len(self.buf) == self.M and sum(self.buf) >= self.N and self.curr == 0: + self.curr = self.cooldown + return True + return False + +# ----------------------- detector ----------------------- # + +class OnnxDetector: + def __init__( + self, + onnx_path=ONNX_PATH, + img_size=IMG_SIZE, + conf=CONF, + roi=ROI, + min_overlap=MIN_OVERLAP, + vote_n=VOTE_N, + vote_m=VOTE_M, + cooldown=VOTE_COOLDOWN, + ): + self.session = ort.InferenceSession(onnx_path, providers=["CPUExecutionProvider"]) + self.img_size = int(img_size) + self.conf = float(conf) + self.voter = VoteNM(vote_n, vote_m, cooldown) + self.use_roi = False + self.ymin = self.ymax = 0.0 + if isinstance(roi, str) and roi.lower() != "none": + y0, y1 = map(float, roi.split("-")) + self.use_roi = True + self.ymin = y0 + self.ymax = y1 + + self.input_name = self.session.get_inputs()[0].name + self.out_name = self.session.get_outputs()[0].name # usually "output0" + + def infer_image(self, img_bgr: np.ndarray) -> Tuple[np.ndarray, bool, bool, float]: + H, W = img_bgr.shape[:2] + canvas = letterbox(img_bgr, self.img_size) + + # Build input blob (NCHW, normalized to [0,1]) + x = canvas.transpose(2, 0, 1)[None].astype(np.float32) / 255.0 + + # ONNX forward + raw = self.session.run([self.out_name], {self.input_name: x})[0] + + # Detect whether output is already post-NMS (N,6). If yes, use it directly. + det: np.ndarray + if raw.ndim == 2 and raw.shape[1] == 6: + det = raw.astype(np.float32) + # det currently in canvas coordinates; we will rescale below. + else: + # Normalize to (A,5) and best class id + xywh_conf, cls_idx = _to_xywh_conf_cls(raw) + # Confidence filter + mask = xywh_conf[:, 4] >= self.conf + xywh_conf = xywh_conf[mask] + cls_idx = cls_idx[mask] + if xywh_conf.size == 0: + det = np.empty((0, 6), dtype=np.float32) + else: + # Convert to xyxy + xyxy = xywh_to_xyxy(xywh_conf[:, :4]) + scores = xywh_conf[:, 4] + + # NMS + keep = nms_xyxy(xyxy, scores, iou_th=0.45, topk=300) + xyxy = xyxy[keep] + scores = scores[keep] + cls_idx = cls_idx[keep] + + det = np.concatenate( + [xyxy.astype(np.float32), + scores.reshape(-1, 1).astype(np.float32), + cls_idx.astype(np.float32)], + axis=1 + ) # (N, 6) + + # Map boxes from canvas (img_size) back to original (H, W) + if det.size > 0: + r = min(self.img_size / H, self.img_size / W) # same ratio used in letterbox() + det[:, [0, 2]] = det[:, [0, 2]] / r + det[:, [1, 3]] = det[:, [1, 3]] / r + # Clip to image bounds + det[:, 0::2] = np.clip(det[:, 0::2], 0, W - 1e-3) + det[:, 1::2] = np.clip(det[:, 1::2], 0, H - 1e-3) + + # Optional ROI filtering on original image scale + if self.use_roi and det.size > 0: + det = filter_boxes_by_roi(det, H, self.ymin, self.ymax, min_overlap=MIN_OVERLAP) + + detected = det.size > 0 + fired = self.voter.update(detected) + max_conf = float(det[:, 4].max()) if detected else 0.0 + + # Return: boxes [x1,y1,x2,y2,conf,cls], detected flag, fired flag, max confidence + return det.astype(np.float32), detected, fired, max_conf diff --git a/services/inference_http/models/fence_hole_detector/minio_io.py b/services/inference_http/models/fence_hole_detector/minio_io.py new file mode 100644 index 000000000..456e79860 --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/minio_io.py @@ -0,0 +1,25 @@ +from minio import Minio +from io import BytesIO +import cv2 +import numpy as np +from config import MINIO_ENDPOINT, MINIO_ACCESS_KEY, MINIO_SECRET_KEY, MINIO_SECURE + +def get_minio_client(): + return Minio( + MINIO_ENDPOINT, + access_key=MINIO_ACCESS_KEY, + secret_key=MINIO_SECRET_KEY, + secure=MINIO_SECURE + ) + +def load_image_from_minio(bucket: str, key: str) -> np.ndarray: + client = get_minio_client() + resp = client.get_object(bucket, key) + data = resp.read() + resp.close() + resp.release_conn() + arr = np.frombuffer(data, np.uint8) + img = cv2.imdecode(arr, cv2.IMREAD_COLOR) + if img is None: + raise RuntimeError("Failed to decode image from MinIO object") + return img diff --git a/services/inference_http/models/fence_hole_detector/requirements.txt b/services/inference_http/models/fence_hole_detector/requirements.txt new file mode 100644 index 000000000..5a0ccb8cb --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/requirements.txt @@ -0,0 +1,9 @@ +fastapi>=0.110,<0.116 +uvicorn[standard]>=0.23,<0.32 +kafka-python>=2.0.2,<3 +minio>=7.1.17,<8 +python-dotenv>=1.0.1,<2 +pydantic>=2.6,<3 +numpy>=1.26,<2 +opencv-python-headless>=4.8.0.76,<4.10 +onnxruntime>=1.17,<1.20 diff --git a/services/inference_http/models/fence_hole_detector/service.py b/services/inference_http/models/fence_hole_detector/service.py new file mode 100644 index 000000000..eb6c0f566 --- /dev/null +++ b/services/inference_http/models/fence_hole_detector/service.py @@ -0,0 +1,136 @@ +# services/inference_http/models/fence_hole_detector/service.py +# Purpose: pure-Python service entrypoints used by both the model's local FastAPI +# and the unified inference_http adapter. No web-specific code here. + +from __future__ import annotations +import os +from dataclasses import dataclass +from typing import Optional, Dict, Any +import numpy as np +import cv2 +from minio import Minio +from datetime import datetime, timezone +from dotenv import load_dotenv + +from .infer import OnnxDetector # reuses the existing ONNX runtime code +from .alert_client import post_alert + +# Load .env next to this file so ALERT_ENABLED / KAFKA_BOOTSTRAP etc. are set. +BASE_DIR = os.path.dirname(__file__) +load_dotenv(os.path.join(BASE_DIR, ".env")) + +# ---- Config (env-first) ----------------------------------------------------- +# We keep model path under models/<...>/weights/best.onnx inside the image. +DEFAULT_ONNX = "/app/models/fence_hole_detector/weights/best.onnx" +FENCE_ONNX_PATH = os.getenv("FENCE_ONNX_PATH", DEFAULT_ONNX) +FENCE_CONF = float(os.getenv("FENCE_CONF", "0.30")) +FENCE_ROI = os.getenv("FENCE_ROI", "none") +FENCE_VOTE_N = int(os.getenv("FENCE_VOTE_N", "1")) +FENCE_VOTE_M = int(os.getenv("FENCE_VOTE_M", "1")) +FENCE_VOTE_COOLDOWN = int(os.getenv("FENCE_VOTE_COOLDOWN", "0")) + +MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "minio-hot:9000") +MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "minioadmin") +MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "minioadmin123") +MINIO_SECURE = os.getenv("MINIO_SECURE", "0") == "1" + +# Public base URL for building image_url in alerts +MINIO_PUBLIC_BASE_URL = os.getenv( + "MINIO_PUBLIC_BASE_URL", f"http://{MINIO_ENDPOINT}" +).rstrip("/") + +DEFAULT_DEVICE_ID = os.getenv("DEFAULT_DEVICE_ID", "camera-01") +DEFAULT_AREA = os.getenv("DEFAULT_AREA", "north_field") +DEFAULT_SEVERITY = int(os.getenv("DEFAULT_SEVERITY", "3")) +# Flag: enable/disable Kafka alerts +ALERT_ENABLED = os.getenv("ALERT_ENABLED", "0") == "1" + +# ---- Singletons -------------------------------------------------------------- +_detector = OnnxDetector( + onnx_path=FENCE_ONNX_PATH, + conf=FENCE_CONF, + roi=FENCE_ROI, + vote_n=FENCE_VOTE_N, + vote_m=FENCE_VOTE_M, + cooldown=FENCE_VOTE_COOLDOWN, +) + +_minio = Minio( + MINIO_ENDPOINT, + access_key=MINIO_ACCESS_KEY, + secret_key=MINIO_SECRET_KEY, + secure=MINIO_SECURE, +) + +# ---- Types ------------------------------------------------------------------- +@dataclass +class InferenceInput: + bucket: str + key: str + captured_at: Optional[datetime] = None + device_id: Optional[str] = None + area: Optional[str] = None + lat: Optional[float] = None + lon: Optional[float] = None + +def _read_minio_image(bucket: str, key: str) -> np.ndarray: + """Download object from MinIO and decode as BGR image.""" + resp = _minio.get_object(bucket, key) + data = resp.read() + resp.close(); resp.release_conn() + arr = np.frombuffer(data, np.uint8) + img = cv2.imdecode(arr, cv2.IMREAD_COLOR) + if img is None: + raise ValueError("Failed to decode image from MinIO") + return img + +# ---- Main entrypoint used by adapter ---------------------------------------- +def infer_from_minio(inp: InferenceInput) -> Dict[str, Any]: + """ + Perform inference from a MinIO key and return a normalized dict. + + This function is used by the unified inference_http adapter. + It may also optionally send a Kafka alert when a hole is detected. + """ + # 1) Load image from MinIO + img = _read_minio_image(inp.bucket, inp.key) + + # 2) Run model inference + det, detected, fired, max_conf = _detector.infer_image(img) + + # 3) Build base result for HTTP / Flink + result: Dict[str, Any] = { + "detected_boxes": int(len(det)), + "fired_alert": int(1 if detected else 0), + "max_conf": float(max_conf), + "device_id": inp.device_id or DEFAULT_DEVICE_ID, + "area": inp.area or DEFAULT_AREA, + "bucket": inp.bucket, + "key": inp.key, + "captured_at": ( + inp.captured_at or datetime.now(timezone.utc) + ).isoformat().replace("+00:00", "Z"), + } + + # 4) Optionally send Kafka alert (same behavior as old FastAPI service) + if detected and ALERT_ENABLED: + try: + image_url = f"{MINIO_PUBLIC_BASE_URL}/{inp.bucket}/{inp.key}" + alert_id = post_alert( + device_id=result["device_id"], + started_at=inp.captured_at or datetime.now(timezone.utc), + confidence=max_conf, + image_url=image_url, + area=result["area"], + lat=inp.lat, + lon=inp.lon, + severity=DEFAULT_SEVERITY, + extra={"bucket": inp.bucket, "key": inp.key}, + ) + result["alert_id"] = alert_id + result["image_url"] = image_url + except Exception as exc: + # Never fail inference because of alert pipeline + print(f"[WARN] alert send failed: {exc}", flush=True) + + return result \ No newline at end of file diff --git a/services/inference_http/models/fence_hole_detector/weights/best.onnx b/services/inference_http/models/fence_hole_detector/weights/best.onnx new file mode 100644 index 000000000..fddf21ac1 Binary files /dev/null and b/services/inference_http/models/fence_hole_detector/weights/best.onnx differ diff --git a/services/inference_http/models/fruit_defect/Docs/DATASET_SPEC.md b/services/inference_http/models/fruit_defect/Docs/DATASET_SPEC.md index ac1e7375c..346e553a0 100644 --- a/services/inference_http/models/fruit_defect/Docs/DATASET_SPEC.md +++ b/services/inference_http/models/fruit_defect/Docs/DATASET_SPEC.md @@ -8,9 +8,7 @@ - `defect` (rotten/decayed/moldy) ## Local Path (outside git) -``` -C:/Users/משתמש/Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten -``` + Inside this folder: ``` diff --git a/services/inference_http/models/fruit_defect/Docs/USAGE.md b/services/inference_http/models/fruit_defect/Docs/USAGE.md index e5cb8eec6..6e341ddd7 100644 --- a/services/inference_http/models/fruit_defect/Docs/USAGE.md +++ b/services/inference_http/models/fruit_defect/Docs/USAGE.md @@ -2,7 +2,7 @@ ## Project Path ``` -C:/Users/משתמש/Desktop/vectordb_efrat/AgCloud/fruit-defect +C:/Users//Desktop/vectordb_efrat/AgCloud/fruit-defect ``` ## Install @@ -18,9 +18,9 @@ Edit `configs/fruit_defect.yaml` with your dataset paths: ```yaml data: - train_dir: "C:/Users/משתמש/Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/train" - val_dir: "C:/Users/משתמש/Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/val" - test_dir: "C:/Users/משתמש/Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/test" + train_dir: "C:/Users//Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/train" + val_dir: "C:/Users//Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/val" + test_dir: "C:/Users//Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/test" model: backbone: "mobilenet_v3_small" diff --git a/services/inference_http/models/fruit_defect/configs/fruit_defect.yaml b/services/inference_http/models/fruit_defect/configs/fruit_defect.yaml index b415ebaa1..ca6f2e41a 100644 --- a/services/inference_http/models/fruit_defect/configs/fruit_defect.yaml +++ b/services/inference_http/models/fruit_defect/configs/fruit_defect.yaml @@ -1,7 +1,7 @@ data: - train_dir: "C:/Users/משתמש/Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/train" - val_dir: "C:/Users/משתמש/Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/val" - test_dir: "C:/Users/משתמש/Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/test" + train_dir: "C:/Users//Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/train" + val_dir: "C:/Users//Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/val" + test_dir: "C:/Users//Desktop/vectordb_efrat/Datasets/Fruit and Vegetable Disease - Healthy vs Rotten/test" model: backbone: "mobilenet_v3_small" diff --git a/services/inference_http/models/fruit_defect/inference/infer_fruit_defect.py b/services/inference_http/models/fruit_defect/inference/infer_fruit_defect.py index 530146c78..0c7ef1662 100644 --- a/services/inference_http/models/fruit_defect/inference/infer_fruit_defect.py +++ b/services/inference_http/models/fruit_defect/inference/infer_fruit_defect.py @@ -24,7 +24,6 @@ except Exception: TQDM_AVAILABLE = False -# --- קונפיג דרך ENV (ברירות מחדל מותאמות לסטאק שלך) --- MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "localhost:9001") MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "minioadmin") MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "minioadmin123") @@ -32,8 +31,8 @@ BUCKET_INPUT = os.getenv("MINIO_BUCKET_INPUT", "imagery") BUCKET_OUTPUT = os.getenv("MINIO_BUCKET_OUTPUT", "telemetry") -INPUT_PREFIX = os.getenv("MINIO_INPUT_PREFIX", "inputs/batch1/") # מאיפה לקרוא תמונות -OUTPUT_PREFIX = os.getenv("MINIO_OUTPUT_PREFIX", "results/batch1/") # לאן להעלות תוצאות +INPUT_PREFIX = os.getenv("MINIO_INPUT_PREFIX", "inputs/batch1/") +OUTPUT_PREFIX = os.getenv("MINIO_OUTPUT_PREFIX", "results/batch1/") WEIGHTS_BUCKET = os.getenv("MINIO_BUCKET_WEIGHTS","imagery") WEIGHTS_PREFIX = os.getenv("MINIO_WEIGHTS_PREFIX","models/") @@ -41,11 +40,11 @@ LOCAL_WEIGHTS_PT = os.getenv("MODEL_PT_LOCAL", "./outputs/fruit_cls_best.pt") IMG_SIZE = int(os.getenv("IMG_SIZE", "192")) -THRESHOLD = float(os.getenv("CLS_THRESHOLD", "0.5")) # סף בינארי defect/ok +THRESHOLD = float(os.getenv("CLS_THRESHOLD", "0.5")) DL_WORKERS = int(os.getenv("DL_WORKERS", "8")) BATCH_SIZE = int(os.getenv("BATCH_SIZE", "8")) -HEARTBEAT_PERIOD = int(os.getenv("HEARTBEAT_PERIOD", "30")) # שניות +HEARTBEAT_PERIOD = int(os.getenv("HEARTBEAT_PERIOD", "30")) # --- logging config --- logging.basicConfig( @@ -139,7 +138,7 @@ def fetch_weights_if_missing() -> Path: log.info(f"Found local PT weights: {pt_local}") return pt_local - # נעדיף TorchScript + # TorchScript log.info(f"Attempting to download weights from MinIO: {WEIGHTS_BUCKET}/{ts_obj} or .pt") try: download_object(WEIGHTS_BUCKET, ts_obj, ts_local) @@ -147,7 +146,7 @@ def fetch_weights_if_missing() -> Path: return ts_local except Exception as e: log.info(f"TorchScript not found in MinIO ({e}), trying PT fallback...") - # fallback ל-pt + # fallback-pt download_object(WEIGHTS_BUCKET, pt_obj, pt_local) log.info(f"Downloaded PT weights: {pt_local}") return pt_local diff --git a/services/inference_http/models/fruit_defect/scripts/extract_mistakes.py b/services/inference_http/models/fruit_defect/scripts/extract_mistakes.py index e43cec53d..05422a802 100644 --- a/services/inference_http/models/fruit_defect/scripts/extract_mistakes.py +++ b/services/inference_http/models/fruit_defect/scripts/extract_mistakes.py @@ -14,7 +14,7 @@ def gt_from_path(p: Path) -> str: def main(): infer_json = Path("outputs/infer_results.json") if not infer_json.exists(): - raise SystemExit("לא נמצא outputs/infer_results.json. תריצי קודם את האינפרנס: python inference/infer_fruit_defect.py") + raise SystemExit("outputs/infer_results.json: python inference/infer_fruit_defect.py") with open(infer_json, "r", encoding="utf-8") as f: results = json.load(f) diff --git a/services/inference_http/models/soil_moisture/.gitignore b/services/inference_http/models/soil_moisture/.gitignore new file mode 100644 index 000000000..62d87daf0 --- /dev/null +++ b/services/inference_http/models/soil_moisture/.gitignore @@ -0,0 +1 @@ +samples/ \ No newline at end of file diff --git a/services/inference_http/models/soil_moisture/Dockerfile b/services/inference_http/models/soil_moisture/Dockerfile new file mode 100644 index 000000000..9b1bb644d --- /dev/null +++ b/services/inference_http/models/soil_moisture/Dockerfile @@ -0,0 +1,44 @@ + +FROM python:3.10-slim + +WORKDIR /app + +# --- 1) installing ca-certificates --- +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates curl \ + && rm -rf /var/lib/apt/lists/* + +# --- 2) copying NetFree certificate and adding it to the system --- +COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt +RUN chmod 644 /usr/local/share/ca-certificates/netfree-ca.crt && \ + update-ca-certificates + +# Setting to ensure the updated certificate is used +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV PIP_CERT=/etc/ssl/certs/ca-certificates.crt + +# --- 3) System dependencies required for FastAPI etc. --- +RUN apt-get update && apt-get install -y --no-install-recommends \ + libglib2.0-0 libsm6 libxrender1 libxext6 \ + && rm -rf /var/lib/apt/lists/* + +# --- 4) Installing dependencies --- +COPY requirements-api.txt . +# RUN pip install --trusted-host pypi.org --trusted-host pypi.python.org \ +# --trusted-host files.pythonhosted.org --no-cache-dir -r requirements-api.txt + +RUN pip config set global.require-hashes false && \ + pip install --trusted-host pypi.org --trusted-host pypi.python.org \ + --trusted-host files.pythonhosted.org --no-cache-dir -r requirements-api.txt +# --- 5) Copying code --- +COPY src ./src +COPY configs ./configs +COPY artifacts ./artifacts +COPY src/sql/init_db.sql /initdb/init_db.sql + +ENV PYTHONPATH=/app +ENV SCHEDULE_UPDATE=1 +RUN pip install python-multipart + +CMD ["uvicorn", "src.app.service:app", "--host", "0.0.0.0", "--port", "8000"] \ No newline at end of file diff --git a/services/inference_http/models/soil_moisture/README.md b/services/inference_http/models/soil_moisture/README.md new file mode 100644 index 000000000..0aacb3f61 --- /dev/null +++ b/services/inference_http/models/soil_moisture/README.md @@ -0,0 +1,119 @@ +# Soil Moisture DL Pipeline – Real-Time Irrigation Control (ONNX Inference) + +This repository delivers an end-to-end **deep learning** pipeline to detect soil moisture state +(**wet / dry**) from ground-level RGB images and trigger **real-time irrigation** actions. + +## Highlights +- **Training (PyTorch)**: MobileNetV3-small (transfer learning) + augmentations. +- **Export** to **ONNX** for light-weight **CPU/Jetson** inference. +- **Inference Service (FastAPI)**: + - Tiling into patches + - Per-patch ONNX inference + - Zone policy with hysteresis (dry_ratio_high / dry_ratio_low / min_patches) + - **Kafka** publish to `irrigation.control` (idempotent) + DLQ + - **Postgres** persistence in `soil_moisture_events` (+ optional schedule UPSERT + audit) + - **Prometheus** metrics + health/ready endpoints + +--- + +## Run + +```bash +docker compose up -d api +``` + +The API will be available at: [http://localhost:8000](http://localhost:8000) + +--- + +## Endpoints + +| Method | Path | Description | +|--------|------|-------------| +| `GET` | `/health` | Basic health check | +| `GET` | `/ready` | Checks DB connectivity | +| `GET` | `/metrics` | Prometheus metrics | +| `POST` | `/infer` | Run inference on uploaded image | + +### Example request + +```bash +curl -X POST "http://localhost:8000/infer" -F "zone_id=zone1" -F "image=@sample.jpg" +``` + +Response: +```json +{ + "device_id": "zone1", + "dry_ratio": 0.42, + "decision": "stop", + "confidence": 0.87, + "patch_count": 48, + "ts": "2025-10-29T09:41:00Z", + "idempotency_key": "zone1:345621" +} +``` + +--- + +## Environment Variables + +| Name | Description | Example | +|------|--------------|----------| +| `PG_DSN` | Postgres connection string | `postgresql://user:pass@host.docker.internal:5432/missions_db` | +| `KAFKA_BROKERS` | Kafka brokers | `kafka:9092` | +| `KAFKA_TOPIC` | Kafka topic for irrigation control | `irrigation.control` | +| `KAFKA_DLT` | Kafka DLQ topic | `irrigation.control.dlq` | +| `ZONES_FILE` | Path to zone configuration | `/app/configs/zones.yaml` | +| `SCHEDULE_UPDATE` | Enables schedule table update | `1` | +| `DECISION_WINDOW_SEC` | Time window for decision hysteresis | `3` | + +--- + +## Notes +- The service depends on Postgres and Kafka within the `ag_cloud` Docker network. +- If Kafka is unreachable, messages are logged but not published. +- Duplicate inferences are prevented using an idempotency key per decision window. +- Metrics exposed for Prometheus under `/metrics`. + +--- + +## Example Compose Context + +```yaml +services: + api: + build: + context: . + dockerfile: Dockerfile + environment: + PG_DSN: postgresql://missions_user:pg123@host.docker.internal:5432/missions_db + KAFKA_BROKERS: kafka:9092 + KAFKA_TOPIC: irrigation.control + KAFKA_DLT: irrigation.control.dlq + ZONES_FILE: /app/configs/zones.yaml + DECISION_WINDOW_SEC: 3 + PATCH_SIZE: 256 + PATCH_STRIDE: 256 + SCHEDULE_UPDATE: 1 + volumes: + - ./configs:/app/configs + - ./artifacts:/app/artifacts + ports: + - "8000:8000" + networks: + - ag_cloud +``` + +--- + +## Testing + +```bash +pytest -v +``` + +--- + +## License +Internal AgCloud component – for research and development use only. diff --git a/services/inference_http/models/soil_moisture/artifacts/best.pt b/services/inference_http/models/soil_moisture/artifacts/best.pt new file mode 100644 index 000000000..4fbed017d Binary files /dev/null and b/services/inference_http/models/soil_moisture/artifacts/best.pt differ diff --git a/services/inference_http/models/soil_moisture/artifacts/label_mapping.json b/services/inference_http/models/soil_moisture/artifacts/label_mapping.json new file mode 100644 index 000000000..7b688603a --- /dev/null +++ b/services/inference_http/models/soil_moisture/artifacts/label_mapping.json @@ -0,0 +1,4 @@ +{ + "0": "dry", + "1": "wet" +} \ No newline at end of file diff --git a/services/inference_http/models/soil_moisture/artifacts/model.onnx b/services/inference_http/models/soil_moisture/artifacts/model.onnx new file mode 100644 index 000000000..6052e846e Binary files /dev/null and b/services/inference_http/models/soil_moisture/artifacts/model.onnx differ diff --git a/services/inference_http/models/soil_moisture/configs/zones.yaml b/services/inference_http/models/soil_moisture/configs/zones.yaml new file mode 100644 index 000000000..fa76afbb7 --- /dev/null +++ b/services/inference_http/models/soil_moisture/configs/zones.yaml @@ -0,0 +1,12 @@ +zones: + ZONE_A: + dry_ratio_high: 0.35 + dry_ratio_low: 0.25 + min_patches: 2 + duration_min: 10 + + ZONE_B: + dry_ratio_high: 0.40 + dry_ratio_low: 0.30 + min_patches: 2 + duration_min: 12 \ No newline at end of file diff --git a/services/inference_http/models/soil_moisture/docker-compose.yml b/services/inference_http/models/soil_moisture/docker-compose.yml new file mode 100644 index 000000000..c23e6b3e3 --- /dev/null +++ b/services/inference_http/models/soil_moisture/docker-compose.yml @@ -0,0 +1,30 @@ +networks: + worktree-main_ag_cloud: + external: true + +services: + api: + build: + context: . + dockerfile: Dockerfile + container_name: soil_api + environment: + PG_DSN: postgresql://missions_user:pg123@host.docker.internal:5432/missions_db + KAFKA_BROKERS: kafka:9092 # host.docker.internal:29092 + KAFKA_TOPIC: irrigation.control + KAFKA_DLT: irrigation.control.dlq + ZONES_FILE: /app/configs/zones.yaml + DECISION_WINDOW_SEC: 3 + PATCH_SIZE: 256 + PATCH_STRIDE: 256 + SCHEDULE_UPDATE: 1 + volumes: + - ./configs:/app/configs + - ./artifacts:/app/artifacts + ports: + - "8000:8000" + + networks: + - worktree-main_ag_cloud + + diff --git a/services/inference_http/models/soil_moisture/requirements-api.txt b/services/inference_http/models/soil_moisture/requirements-api.txt new file mode 100644 index 000000000..6e3ae713a --- /dev/null +++ b/services/inference_http/models/soil_moisture/requirements-api.txt @@ -0,0 +1,14 @@ +fastapi==0.114.2 +uvicorn==0.30.6 +onnxruntime==1.20.0 +numpy==2.1.1 +Pillow==10.4.0 +opencv-python==4.10.0.84 +kafka-python==2.0.2 +psycopg2-binary==2.9.10 +prometheus_client==0.21.0 +PyYAML==6.0.2 +python-dotenv==1.0.1 +requests==2.32.3 +python-multipart==0.0.6 +confluent_kafka==2.12.0 \ No newline at end of file diff --git a/services/inference_http/models/soil_moisture/requirements-train.txt b/services/inference_http/models/soil_moisture/requirements-train.txt new file mode 100644 index 000000000..21a78fde4 --- /dev/null +++ b/services/inference_http/models/soil_moisture/requirements-train.txt @@ -0,0 +1,9 @@ +torch>=2.2.0 +torchvision==0.23.0 +numpy==2.1.1 +Pillow==10.4.0 +opencv-python==4.10.0.84 +scikit-learn==1.5.2 +tqdm==4.66.5 +PyYAML==6.0.2 +onnx==1.19.0 diff --git a/services/inference_http/models/soil_moisture/src/.dockerignore b/services/inference_http/models/soil_moisture/src/.dockerignore new file mode 100644 index 000000000..f5bddaa38 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/.dockerignore @@ -0,0 +1,2 @@ +models/soil_moisture/samples/ +models/soil_moisture/tests/ \ No newline at end of file diff --git a/services/inference_http/models/soil_moisture/src/app/__init__.py b/services/inference_http/models/soil_moisture/src/app/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/inference_http/models/soil_moisture/src/app/config.py b/services/inference_http/models/soil_moisture/src/app/config.py new file mode 100644 index 000000000..719e03fa3 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/config.py @@ -0,0 +1,21 @@ +import os +import yaml +from dataclasses import dataclass +from typing import Dict, Any +from dotenv import load_dotenv +load_dotenv() + +@dataclass +class Settings: + kafka_brokers: str = os.getenv("KAFKA_BROKERS", "localhost:9092") + kafka_topic: str = os.getenv("KAFKA_TOPIC", "irrigation.control") + kafka_dlt: str = os.getenv("KAFKA_DLT", "irrigation.control.dlq") + pg_dsn: str = os.getenv("PG_DSN", "postgresql://postgres:postgres@localhost:5432/soil") + zones_file: str = os.getenv("ZONES_FILE", "configs/zones.yaml") + decision_window_sec: int = int(os.getenv("DECISION_WINDOW_SEC", "1")) + patch_size: int = int(os.getenv("PATCH_SIZE", "256")) + patch_stride: int = int(os.getenv("PATCH_STRIDE", "256")) + +def load_zones(path: str) -> Dict[str, Any]: + with open(path, "r", encoding="utf-8") as f: + return yaml.safe_load(f) diff --git a/services/inference_http/models/soil_moisture/src/app/db.py b/services/inference_http/models/soil_moisture/src/app/db.py new file mode 100644 index 000000000..356f523b2 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/db.py @@ -0,0 +1,134 @@ + +import json +from typing import Optional, Dict, Any +import psycopg2 +import psycopg2.extras +from contextlib import contextmanager + +class DB: + def __init__(self, dsn: str): + self.dsn = dsn + + @contextmanager + def conn(self): + conn = psycopg2.connect(self.dsn) + try: + yield conn + finally: + conn.close() + + def init_ok(self) -> bool: + try: + with self.conn() as c: + with c.cursor() as cur: + cur.execute("SELECT 1") + return True + except Exception: + return False + + def log_event(self, device_id: str, ts_iso: str, dry_ratio: float, + decision: str, confidence: float, patch_count: int, + idem_key: str, extra: Optional[Dict[str, Any]]=None) -> bool: + q = ''' + INSERT INTO soil_moisture_events + (device_id, ts, dry_ratio, decision, confidence, patch_count, idempotency_key, extra) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s) + ON CONFLICT (idempotency_key) DO NOTHING + ''' + with self.conn() as c: + with c.cursor() as cur: + cur.execute(q, ( + device_id, + ts_iso, + dry_ratio, + decision, + confidence, + patch_count, + idem_key, + json.dumps(extra or {}) + )) + c.commit() + return cur.rowcount > 0 + + def load_device_policy(self, device_id: str) -> dict: + try: + with self.conn() as c: + with c.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur: + cur.execute(""" + SELECT prev_state, dry_ratio_high, dry_ratio_low, + min_patches, duration_min + FROM irrigation_policies + WHERE device_id = %s + """, (device_id,)) + row = cur.fetchone() + if not row: + print(f"No row found for device_id={device_id}") + raise ValueError("not found") + print(f"Loaded from DB: {dict(row)}") + return dict(row) + except Exception as e: + print(f"Falling back to defaults because: {e}") + # fallback defaults + return { + "prev_state": "stop", + "dry_ratio_high": 0.35, + "dry_ratio_low": 0.25, + "min_patches": 2, + "duration_min": 10 + } + + + def upsert_schedule(self, device_id: str, next_run_at: str, duration_min: int, + updated_by: str, update_reason: str) -> None: + with self.conn() as c: + with c.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur: + cur.execute("SELECT next_run_at, duration_min FROM irrigation_schedule WHERE device_id=%s", (device_id,)) + prev = cur.fetchone() + cur.execute(''' + INSERT INTO irrigation_schedule(device_id, next_run_at, duration_min, updated_by, update_reason) + VALUES (%s, %s, %s, %s, %s) + ON CONFLICT (device_id) DO UPDATE SET + next_run_at=EXCLUDED.next_run_at, + duration_min=EXCLUDED.duration_min, + updated_by=EXCLUDED.updated_by, + update_reason=EXCLUDED.update_reason, + updated_at=NOW() + ''', (device_id, next_run_at, duration_min, updated_by, update_reason)) + cur.execute(''' + INSERT INTO irrigation_schedule_audit(device_id, prev_next_run_at, prev_duration_min, + next_run_at, duration_min, updated_by, update_reason) + VALUES (%s, %s, %s, %s, %s, %s, %s) + ''', (device_id, + prev["next_run_at"] if prev else None, + prev["duration_min"] if prev else None, + next_run_at, duration_min, updated_by, update_reason)) + c.commit() + + def update_prev_state(self, device_id: str, new_state: str) -> None: + # default values for other new fields + default_policy = { + "dry_ratio_high": 0.35, + "dry_ratio_low": 0.25, + "min_patches": 2, + "duration_min": 10 + } + + with self.conn() as c: + with c.cursor() as cur: + cur.execute(""" + INSERT INTO irrigation_policies + (device_id, prev_state, dry_ratio_high, dry_ratio_low, min_patches, duration_min) + VALUES (%s, %s, %s, %s, %s, %s) + ON CONFLICT (device_id) DO UPDATE + SET prev_state = EXCLUDED.prev_state, + updated_at = NOW() + """, ( + device_id, + new_state, + default_policy["dry_ratio_high"], + default_policy["dry_ratio_low"], + default_policy["min_patches"], + default_policy["duration_min"] + )) + c.commit() + diff --git a/services/inference_http/models/soil_moisture/src/app/inference.py b/services/inference_http/models/soil_moisture/src/app/inference.py new file mode 100644 index 000000000..95c4d948c --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/inference.py @@ -0,0 +1,106 @@ +from typing import Dict, Any, Tuple +from PIL import Image +import numpy as np +import os, time, logging +from .config import Settings +from .utils import normalize_lighting, tile_image, preprocess_onnx +from .metrics import METRICS +from .onnx_model import ONNXMoistureModel +from .db import DB + +logger = logging.getLogger("soil_api") + +DRY_LABEL = "dry" + +class Inferencer: + def __init__(self, settings: Settings, db: DB, + model_path: str = "artifacts/model.onnx", + label_map_path: str = "artifacts/label_mapping.json"): + self.settings = settings + self.db = db + self.model = ONNXMoistureModel(model_path, label_map_path) + self.classes = [self.model.label_map[str(i)] for i in range(len(self.model.label_map))] + + def decision_window_bucket(self, ts: float) -> int: + return int(ts // self.settings.decision_window_sec) * self.settings.decision_window_sec + + def infer_image(self, img: Image.Image, device_id: str) -> Tuple[Dict[str, Any], Dict[str, Any]]: + + t0 = time.time() + img_n = normalize_lighting(img) + patches = tile_image(img_n, self.settings.patch_size, self.settings.patch_stride) + + dry_votes = 0 + probs = [] + + logger.info("infer_image start device_id=%s patch_size=%d stride=%d total_patches=%d",device_id, self.settings.patch_size, self.settings.patch_stride, len(patches)) + + try: + dry_idx = self.classes.index(DRY_LABEL) + except ValueError: + logger.warning("DRY_LABEL '%s' not found in classes %s", DRY_LABEL, self.classes) + dry_idx = None + + for idx, p in enumerate(patches): + try: + proba = self.model.predict_proba_patch(p) + except Exception as e: + logger.exception("model.predict_proba_patch failed for patch idx=%d: %s", idx, e) + proba = np.zeros(len(self.classes), dtype=float) + + probs.append(proba) + arg = int(proba.argmax()) if proba.size else -1 + arg_label = self.classes[arg] if (arg >= 0 and arg < len(self.classes)) else "unknown" + maxp = float(proba.max()) if proba.size else 0.0 + logger.debug("patch idx=%d arg=%d label=%s maxp=%.4f", idx, arg, arg_label, maxp) + + if dry_idx is not None and arg == dry_idx: + dry_votes += 1 + + mean_confidence = float(np.mean([max(x) for x in probs])) if probs else 0.0 + + patch_count = len(patches) + dry_ratio = dry_votes / max(1, patch_count) + + # Policy / hysteresis + policy = self.db.load_device_policy(device_id) + prev_state = policy.get("prev_state") or "stop" + high = policy.get("dry_ratio_high") or 0.35 + low = policy.get("dry_ratio_low") or 0.25 + min_patches = policy.get("min_patches") or 2 + duration_min = policy.get("duration_min") or 10 + + logger.info("decision inputs prev_state=%s dry_votes=%d patch_count=%d dry_ratio=%.4f high=%.4f low=%.4f min_patches=%d", + prev_state, dry_votes, patch_count, dry_ratio, high, low, min_patches) + + decision = "noop" + if patch_count >= min_patches: + if prev_state != "run" and dry_ratio >= high: + decision = "run" + elif prev_state != "stop" and dry_ratio <= low: + decision = "stop" + else: + logger.debug("hysteresis conditions not met (prev_state=%s)", prev_state) + else: + logger.debug("not enough patches for decision: patch_count=%d min_patches=%d", patch_count, min_patches) + + new_state = decision if decision in ("run", "stop") else prev_state + logger.info("decision result=%s updated_state=%s duration_min=%d confidence=%.4f", + decision, new_state, duration_min, mean_confidence) + + METRICS["inference_latency_ms"].observe((time.time() - t0) * 1000.0) + + result = { + "dry_ratio": float(dry_ratio), + "decision": decision, + "confidence": float(mean_confidence), + "patch_count": int(patch_count), + "duration_min": duration_min + } + debug = { + "probs_shape": (len(probs), len(probs[0]) if probs else 0) + } + if new_state != prev_state: + self.db.update_prev_state(device_id, new_state) + + return result, debug diff --git a/services/inference_http/models/soil_moisture/src/app/inference_logic.py b/services/inference_http/models/soil_moisture/src/app/inference_logic.py new file mode 100644 index 000000000..8da8bae44 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/inference_logic.py @@ -0,0 +1,171 @@ +""" +Shared inference logic that can be used by both the API and adapters. +""" +import logging +import time +import datetime as dt +from typing import Dict, Any, Tuple, Optional +from PIL import Image + +logger = logging.getLogger(__name__) + + +class SoilMoistureInferenceLogic: + """ + Encapsulates the inference logic for soil moisture detection. + This can be used by both the FastAPI service and the Flink adapter. + """ + + def __init__(self, settings, db, inferencer, producer=None): + self.settings = settings + self.db = db + self.inferencer = inferencer + self.producer = producer + + def extract_device_id(self, filename: str) -> str: + """ + Extract device ID from filename in the format device_ts + (For example dev-f_20251106T1030.jpg) + """ + import os + base = os.path.basename(filename) + device_id = base.split("_")[0] + if not device_id: + raise ValueError(f"Invalid filename format: {filename}") + return device_id + + def build_idem_key(self, device_id: str, ts_unix: float) -> str: + """Build idempotency key""" + bucket = self.inferencer.decision_window_bucket(ts_unix) + return f"{device_id}:{int(bucket)}" + + def publish_and_persist( + self, + device_id: str, + decision: str, + duration_min: int, + confidence: float, + dry_ratio: float, + patch_count: int, + idem: str, + ts_iso: str + ) -> bool: + """ + Publish to Kafka and persist to database. + Returns True if saved successfully, False if duplicate. + """ + import json + import os + + payload = { + "device_id": device_id, + "command": decision if decision in ("run", "stop") else "noop", + "reason": "soil_dry", + "duration_min": duration_min if decision == "run" else None, + "confidence": confidence, + "ts": ts_iso, + "idempotency_key": idem + } + + saved = self.db.log_event( + device_id, ts_iso, dry_ratio, payload["command"], + confidence, patch_count, idem, + extra={"dry_ratio": dry_ratio} + ) + + if not saved: + logger.info(json.dumps({ + "msg": "duplicate_idempotency", + "device_id": device_id, + "idem": idem + })) + return False + + # Schedule update + schedule_update = os.getenv('SCHEDULE_UPDATE', '1') == '1' + if schedule_update and decision == 'run': + try: + self.db.upsert_schedule( + device_id, ts_iso, duration_min, + updated_by='soil_api', + update_reason='soil_dry' + ) + except Exception as e: + logger.warning('schedule update failed: %s', e) + + # Publish to Kafka + if self.producer: + self.producer.publish(payload) + else: + logger.warning( + "Kafka producer unavailable; skipping publish. payload=%s", + payload + ) + + return True + + def infer_from_image( + self, + img: Image.Image, + device_id: str, + ts_unix: Optional[float] = None + ) -> Dict[str, Any]: + """ + Run inference on an image and return results. + + Args: + img: PIL Image object + device_id: Device identifier + ts_unix: Unix timestamp (optional, defaults to current time) + + Returns: + Dictionary with inference results including: + - device_id + - dry_ratio + - decision + - confidence + - patch_count + - duration_min + - ts + - idempotency_key + - latency_ms + """ + if ts_unix is None: + ts_unix = time.time() + + start_time = time.time() + ts_iso = dt.datetime.utcfromtimestamp(ts_unix).isoformat() + "Z" + + # Run inference + result, debug = self.inferencer.infer_image(img, device_id) + + # Build idempotency key + idem = self.build_idem_key(device_id, ts_unix) + + # Publish and persist + saved = self.publish_and_persist( + device_id=device_id, + decision=result["decision"], + duration_min=result["duration_min"], + confidence=result["confidence"], + dry_ratio=result["dry_ratio"], + patch_count=result["patch_count"], + idem=idem, + ts_iso=ts_iso + ) + + latency_ms = int((time.time() - start_time) * 1000) + + return { + "device_id": device_id, + "dry_ratio": result["dry_ratio"], + "decision": result["decision"], + "confidence": result["confidence"], + "patch_count": result["patch_count"], + "duration_min": result.get("duration_min", 0), + "ts": ts_iso, + "idempotency_key": idem, + "latency_ms": latency_ms, + "saved": saved, + "debug": debug + } \ No newline at end of file diff --git a/services/inference_http/models/soil_moisture/src/app/kafka_producer.py b/services/inference_http/models/soil_moisture/src/app/kafka_producer.py new file mode 100644 index 000000000..b6052accd --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/kafka_producer.py @@ -0,0 +1,39 @@ +import json +import logging +from confluent_kafka import Producer, KafkaError +from .metrics import METRICS + +logger = logging.getLogger("soil_api") + +class ControlProducer: + def __init__(self, brokers: str, topic: str, dlt: str): + self.topic = topic + self.dlt = dlt + self.producer = Producer({"bootstrap.servers": brokers}) + + def publish(self, payload: dict) -> None: + try: + self.producer.produce( + self.topic, + value=json.dumps(payload).encode("utf-8"), + on_delivery=self._delivery_report + ) + self.producer.flush(2) + METRICS["alerts_sent_total"].labels(decision=payload.get("command", "unknown")).inc() + except Exception as e: + logger.warning("Kafka publish failed: %s", e) + METRICS["kafka_publish_errors_total"].labels(reason=type(e).__name__).inc() + # try send to DLT + try: + dlt_payload = dict(payload) + dlt_payload["error"] = str(e) + self.producer.produce(self.dlt, value=json.dumps(dlt_payload).encode("utf-8")) + self.producer.flush(2) + except Exception as e2: + logger.error("DLT publish failed: %s", e2) + + def _delivery_report(self, err, msg): + if err is not None: + logger.warning("Delivery failed for record %s: %s", msg.key(), err) + else: + logger.debug("Record delivered to %s [%d] @ %d", msg.topic(), msg.partition(), msg.offset()) diff --git a/services/inference_http/models/soil_moisture/src/app/metrics.py b/services/inference_http/models/soil_moisture/src/app/metrics.py new file mode 100644 index 000000000..ce38f34de --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/metrics.py @@ -0,0 +1,11 @@ +from prometheus_client import Counter, Histogram + +METRICS = { + "alerts_sent_total": Counter("alerts_sent_total", "Total alerts sent", ["decision"]), + "kafka_publish_errors_total": Counter("kafka_publish_errors_total", "Kafka publish errors", ["reason"]), + "inference_latency_ms": Histogram( + "inference_latency_ms", + "Inference latency (ms)", + buckets=(5,10,20,50,100,200,500,1000,2000) + ), +} diff --git a/services/inference_http/models/soil_moisture/src/app/onnx_model.py b/services/inference_http/models/soil_moisture/src/app/onnx_model.py new file mode 100644 index 000000000..c78db3f26 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/onnx_model.py @@ -0,0 +1,22 @@ +import json +import numpy as np +import onnxruntime as ort +from typing import List +from PIL import Image +from .utils import preprocess_onnx + +class ONNXMoistureModel: + def __init__(self, model_path: str, label_map_path: str): + self.sess = ort.InferenceSession(model_path, providers=['CPUExecutionProvider']) + with open(label_map_path, "r", encoding="utf-8") as f: + self.label_map = json.load(f) # index -> label + self.input_name = self.sess.get_inputs()[0].name + self.output_name = self.sess.get_outputs()[0].name + + def predict_proba_patch(self, patch: Image.Image): + x = preprocess_onnx(patch, size=224) + logits = self.sess.run([self.output_name], {self.input_name: x})[0] + # softmax on logits + e = np.exp(logits - logits.max(axis=1, keepdims=True)) + proba = e / e.sum(axis=1, keepdims=True) + return proba[0] diff --git a/services/inference_http/models/soil_moisture/src/app/schemas.py b/services/inference_http/models/soil_moisture/src/app/schemas.py new file mode 100644 index 000000000..336e7c323 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/schemas.py @@ -0,0 +1,14 @@ +from pydantic import BaseModel + +class InferRequest(BaseModel): + device_id: str + image_b64: str # base64-encoded RGB image + +class InferResponse(BaseModel): + device_id: str + dry_ratio: float + decision: str + confidence: float + patch_count: int + ts: str + idempotency_key: str diff --git a/services/inference_http/models/soil_moisture/src/app/service.py b/services/inference_http/models/soil_moisture/src/app/service.py new file mode 100644 index 000000000..36e09cc20 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/service.py @@ -0,0 +1,103 @@ +""" +FastAPI service for soil moisture inference. +Delegates business logic to inference_logic.py +""" +import base64 +import logging +from fastapi import FastAPI, UploadFile, File, HTTPException +from fastapi.responses import PlainTextResponse +from prometheus_client import generate_latest, CONTENT_TYPE_LATEST + +from .config import Settings, load_zones +from .schemas import InferRequest, InferResponse +from .inference import Inferencer +from .kafka_producer import ControlProducer +from .db import DB +from .metrics import METRICS +from .utils import load_image_from_b64 +from .inference_logic import SoilMoistureInferenceLogic + +logging.basicConfig(level=logging.DEBUG, format='%(message)s') +logger = logging.getLogger("soil_api") + +# Initialize components +settings = Settings() +zones_cfg = load_zones(settings.zones_file) +db = DB(settings.pg_dsn) +inferencer = Inferencer(settings, db) + +# Initialize Kafka producer +producer = None +try: + from kafka import KafkaProducer + producer = ControlProducer( + settings.kafka_brokers, + settings.kafka_topic, + settings.kafka_dlt + ) +except Exception as e: + import traceback + logger.warning("Kafka init failed: %s\n%s", e, traceback.format_exc()) + +# Initialize shared inference logic +inference_logic = SoilMoistureInferenceLogic( + settings=settings, + db=db, + inferencer=inferencer, + producer=producer +) + +app = FastAPI(title="Soil Moisture DL API", version="1.0.0") + + +@app.get("/health", response_class=PlainTextResponse) +def health(): + return "ok" + + +@app.get("/ready", response_class=PlainTextResponse) +def ready(): + if not db.init_ok(): + raise HTTPException(status_code=503, detail="DB not ready") + return "ready" + + +@app.get("/metrics") +def metrics(): + return PlainTextResponse(generate_latest(), media_type=CONTENT_TYPE_LATEST) + + +@app.post("/infer", response_model=InferResponse) +async def infer(image: UploadFile = File(None), body: InferRequest | None = None): + """ + Run inference on a soil moisture image. + Accepts either multipart form data (file upload) or JSON with base64 image. + """ + # Parse input + if body is not None: + img = load_image_from_b64(body.image_b64) + device_id = inference_logic.extract_device_id(body.filename) + else: + if image is None: + raise HTTPException( + status_code=400, + detail="Provide multipart (file) or JSON (image_b64)" + ) + filename = image.filename + device_id = inference_logic.extract_device_id(filename) + content = await image.read() + img = load_image_from_b64(base64.b64encode(content).decode("utf-8")) + + # Run inference using shared logic + result = inference_logic.infer_from_image(img, device_id) + + # Return response + return InferResponse( + device_id=result["device_id"], + dry_ratio=result["dry_ratio"], + decision=result["decision"], + confidence=result["confidence"], + patch_count=result["patch_count"], + ts=result["ts"], + idempotency_key=result["idempotency_key"] + ) \ No newline at end of file diff --git a/services/inference_http/models/soil_moisture/src/app/utils.py b/services/inference_http/models/soil_moisture/src/app/utils.py new file mode 100644 index 000000000..2853c5250 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/app/utils.py @@ -0,0 +1,29 @@ +import base64, io +from PIL import Image, ImageOps +import numpy as np +from typing import List + +def load_image_from_b64(b64: str) -> Image.Image: + data = base64.b64decode(b64) + return Image.open(io.BytesIO(data)).convert("RGB") + +def normalize_lighting(img: Image.Image) -> Image.Image: + r, g, b = img.split() + r, g, b = ImageOps.equalize(r), ImageOps.equalize(g), ImageOps.equalize(b) + return Image.merge("RGB", (r, g, b)) + +def tile_image(img: Image.Image, patch_size: int, stride: int) -> List[Image.Image]: + w, h = img.size + patches = [] + for y in range(0, h - patch_size + 1, stride): + for x in range(0, w - patch_size + 1, stride): + patches.append(img.crop((x, y, x + patch_size, y + patch_size))) + if not patches: + patches.append(img.resize((patch_size, patch_size))) + return patches + +def preprocess_onnx(pil_img: Image.Image, size: int = 224) -> np.ndarray: + img = pil_img.resize((size, size)) + arr = np.asarray(img).astype("float32") / 255.0 + arr = arr.transpose(2,0,1) # HWC -> CHW + return arr[None, :, :, :] # NCHW diff --git a/services/inference_http/models/soil_moisture/src/scripts/consume_once.py b/services/inference_http/models/soil_moisture/src/scripts/consume_once.py new file mode 100644 index 000000000..b035f4017 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/scripts/consume_once.py @@ -0,0 +1,40 @@ +import argparse +import json +from kafka import KafkaConsumer, errors + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument("--brokers", default="localhost:29092", help="Broker list, e.g. localhost:29092 or kafka:9092") + parser.add_argument("--topic", default="irrigation.control") + parser.add_argument("--group", default="debug-consumer") + parser.add_argument("--from-beginning", action="store_true", help="Read from earliest offset") + args = parser.parse_args() + + print(f"Connecting to Kafka brokers: {args.brokers}") + try: + consumer = KafkaConsumer( + args.topic, + bootstrap_servers=args.brokers.split(","), + group_id=args.group, + enable_auto_commit=False, + auto_offset_reset="earliest" if args.from_beginning else "latest", + value_deserializer=lambda v: json.loads(v.decode("utf-8")), + consumer_timeout_ms=0 + ) + print(f"Listening on topic '{args.topic}' (group={args.group})...") + except errors.NoBrokersAvailable: + print("❌ Cannot connect to Kafka. Check host/port and Docker networking.") + return + + try: + for message in consumer: + print("\n--- New message ---") + print(json.dumps(message.value, indent=2)) + except KeyboardInterrupt: + print("\nStopped by user.") + finally: + consumer.close() + print("Consumer closed.") + +if __name__ == "__main__": + main() diff --git a/services/inference_http/models/soil_moisture/src/scripts/demo_feed.py b/services/inference_http/models/soil_moisture/src/scripts/demo_feed.py new file mode 100644 index 000000000..3be42924a --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/scripts/demo_feed.py @@ -0,0 +1,48 @@ +import argparse, os, base64, time, json, glob +import requests + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument("--images-dir", required=True) + ap.add_argument("--api", default="http://localhost:8000") + args = ap.parse_args() + + # Collect all images + imgs = [] + for ext in ("*.jpg", "*.jpeg", "*.png", "*.bmp"): + imgs += glob.glob(os.path.join(args.images_dir, '**', ext), recursive=True) + imgs = sorted(imgs) + + if not imgs: + print("No images found in", args.images_dir) + return + + for path in imgs: + filename = os.path.basename(path) + + # IMPORTANT: The device_id must be encoded inside the filename, + # e.g. device123_20250101T1030.jpg + print(f"Sending {filename} ...") + + try: + with open(path, "rb") as f: + files = {"image": (filename, f)} + r = requests.post( + args.api + "/infer", + files=files, + timeout=60 + ) + + if r.status_code != 200: + print("Error:", r.status_code, r.text) + else: + print(json.dumps(r.json(), indent=2)) + + except Exception as e: + print("Request failed:", e) + + time.sleep(0.4) + + +if __name__ == "__main__": + main() diff --git a/services/inference_http/models/soil_moisture/src/scripts/eval_test_set.py b/services/inference_http/models/soil_moisture/src/scripts/eval_test_set.py new file mode 100644 index 000000000..875834dea --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/scripts/eval_test_set.py @@ -0,0 +1,42 @@ +# src/scripts/eval_test_onnx.py +import json, numpy as np, onnxruntime as ort +from pathlib import Path +from torchvision import transforms +from torchvision.datasets import ImageFolder +from torch.utils.data import DataLoader + +def load_label_mapping(path="artifacts/label_mapping.json"): + with open(path,"r") as f: + return json.load(f) + +def preprocess_pil(img): + tf = transforms.Compose([transforms.Resize((224,224)), transforms.ToTensor()]) + t = tf(img).numpy() + return np.expand_dims(t, axis=0).astype(np.float32) + +def run_onnx_eval(onnx_path="artifacts/model.onnx", test_dir="samples/test", batch_size=16): + label_map = load_label_mapping() + classes = [label_map[str(i)] for i in range(len(label_map))] + ds = ImageFolder(test_dir, transform=None) # we'll read PIL ourselves + loader = DataLoader(ds, batch_size=batch_size, shuffle=False) + + sess = ort.InferenceSession(onnx_path, providers=['CPUExecutionProvider']) + input_name = sess.get_inputs()[0].name + output_name = sess.get_outputs()[0].name + + y_true, y_pred = [], [] + from PIL import Image + for path, label in ds.samples: + img = Image.open(path).convert("RGB") + x = preprocess_pil(img) + logits = sess.run([output_name], {input_name: x})[0] + pred = int(np.argmax(logits, axis=1)[0]) + y_true.append(label) + y_pred.append(pred) + + from sklearn.metrics import classification_report, confusion_matrix + print(classification_report(y_true, y_pred, target_names=classes, digits=4)) + print(confusion_matrix(y_true, y_pred)) + +if __name__ == "__main__": + run_onnx_eval() diff --git a/services/inference_http/models/soil_moisture/src/scripts/print_db_events.py b/services/inference_http/models/soil_moisture/src/scripts/print_db_events.py new file mode 100644 index 000000000..07b41b875 --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/scripts/print_db_events.py @@ -0,0 +1,24 @@ +import argparse, psycopg2, psycopg2.extras, json + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument("--dsn", default="postgresql://missions_user:pg123@127.0.0.1:5432/missions_db") + ap.add_argument("--limit", type=int, default=10) + args = ap.parse_args() + + conn = psycopg2.connect(args.dsn) + try: + cur = conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) + cur.execute(""" + SELECT id, device_id, ts, dry_ratio, decision, confidence, patch_count, idempotency_key + FROM soil_moisture_events + ORDER BY id DESC + LIMIT %s + """, (args.limit,)) + rows = cur.fetchall() + print(json.dumps(rows, indent=2, default=str)) + finally: + conn.close() + +if __name__ == "__main__": + main() diff --git a/services/inference_http/models/soil_moisture/src/sql/init_db.sql b/services/inference_http/models/soil_moisture/src/sql/init_db.sql new file mode 100644 index 000000000..1476755fc --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/sql/init_db.sql @@ -0,0 +1,47 @@ +CREATE TABLE IF NOT EXISTS soil_moisture_events ( + id SERIAL PRIMARY KEY, + device_id TEXT NOT NULL, + ts TIMESTAMPTZ NOT NULL DEFAULT NOW(), + dry_ratio REAL NOT NULL, + decision TEXT NOT NULL, + confidence REAL NOT NULL, + patch_count INT NOT NULL, + idempotency_key TEXT NOT NULL, + extra JSONB DEFAULT '{}'::jsonb +); + +CREATE UNIQUE INDEX IF NOT EXISTS idx_events_idem ON soil_moisture_events (idempotency_key); + +CREATE TABLE IF NOT EXISTS irrigation_schedule ( + device_id TEXT PRIMARY KEY, + next_run_at TIMESTAMPTZ NOT NULL, + duration_min INT NOT NULL, + updated_by TEXT NOT NULL, + update_reason TEXT NOT NULL, + updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW() +); + +CREATE TABLE IF NOT EXISTS irrigation_schedule_audit ( + id SERIAL PRIMARY KEY, + device_id TEXT NOT NULL, + prev_next_run_at TIMESTAMPTZ, + prev_duration_min INT, + next_run_at TIMESTAMPTZ NOT NULL, + duration_min INT NOT NULL, + updated_by TEXT NOT NULL, + update_reason TEXT NOT NULL, + updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW() +); +CREATE TABLE irrigation_policies ( + device_id TEXT NOT NULL, + prev_state TEXT, + dry_ratio_high REAL, + dry_ratio_low REAL, + min_patches INT, + duration_min INT, + updated_at TIMESTAMP DEFAULT NOW(), + PRIMARY KEY (device_id), + CONSTRAINT fk_device + FOREIGN KEY (device_id) REFERENCES devices(device_id) + ON DELETE CASCADE +); diff --git a/services/inference_http/models/soil_moisture/src/train/train_torch.py b/services/inference_http/models/soil_moisture/src/train/train_torch.py new file mode 100644 index 000000000..db7c89d9a --- /dev/null +++ b/services/inference_http/models/soil_moisture/src/train/train_torch.py @@ -0,0 +1,110 @@ +import argparse, os, json +from pathlib import Path +import numpy as np +from PIL import Image +import torch +import torch.nn as nn +import torch.optim as optim +from torch.utils.data import DataLoader +from torchvision import datasets, transforms, models +from tqdm import tqdm + +def build_dataloaders(train_dir, val_dir, batch_size): + aug = transforms.Compose([ + transforms.RandomResizedCrop(224, scale=(0.7, 1.0)), + transforms.RandomHorizontalFlip(), + transforms.ColorJitter(brightness=0.2, contrast=0.2, saturation=0.2), + transforms.ToTensor() + ]) + val_tf = transforms.Compose([ + transforms.Resize((224,224)), + transforms.ToTensor() + ]) + train_ds = datasets.ImageFolder(train_dir, transform=aug) + val_ds = datasets.ImageFolder(val_dir, transform=val_tf) + train_loader = DataLoader(train_ds, batch_size=batch_size, shuffle=True, num_workers=2, pin_memory=True) + val_loader = DataLoader(val_ds, batch_size=batch_size, shuffle=False, num_workers=2, pin_memory=True) + return train_loader, val_loader, train_ds.classes + +@torch.no_grad() +def evaluate(model, loader, device): + model.eval() + correct, total = 0, 0 + for x, y in loader: + x, y = x.to(device), y.to(device) + logits = model(x) + pred = logits.argmax(1) + correct += (pred == y).sum().item() + total += y.numel() + return correct / max(1,total) + +def export_onnx(model, out_path, device): + model.eval() + dummy = torch.randn(1,3,224,224, device=device) + out_dir = os.path.dirname(out_path) + os.makedirs(out_dir, exist_ok=True) + torch.onnx.export( + model, dummy, out_path, + input_names=["input"], output_names=["logits"], + opset_version=17, dynamic_axes=None + ) + print("Exported ONNX to", out_path) + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument("--train-dir", required=True) + ap.add_argument("--val-dir", required=True) + ap.add_argument("--epochs", type=int, default=15) + ap.add_argument("--batch-size", type=int, default=64) + ap.add_argument("--lr", type=float, default=3e-4) + ap.add_argument("--out", required=True) # ONNX output path + args = ap.parse_args() + + device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + train_loader, val_loader, classes = build_dataloaders(args.train_dir, args.val_dir, args.batch_size) + + # MobileNetV3-small transfer learning + model = models.mobilenet_v3_small(weights=models.MobileNet_V3_Small_Weights.DEFAULT) + in_features = model.classifier[3].in_features + model.classifier[3] = nn.Linear(in_features, len(classes)) + model.to(device) + + criterion = nn.CrossEntropyLoss() + optimizer = optim.AdamW(model.parameters(), lr=args.lr) + + best_acc = 0.0 + best_pt = "artifacts/best.pt" + os.makedirs("artifacts", exist_ok=True) + + for epoch in range(1, args.epochs+1): + model.train() + pbar = tqdm(train_loader, desc=f"Epoch {epoch}/{args.epochs}") + for x, y in pbar: + x, y = x.to(device), y.to(device) + logits = model(x) + loss = criterion(logits, y) + optimizer.zero_grad() + loss.backward() + optimizer.step() + pbar.set_postfix(loss=float(loss.item())) + + acc = evaluate(model, val_loader, device) + print(f"Val acc: {acc:.4f}") + if acc > best_acc: + best_acc = acc + torch.save(model.state_dict(), best_pt) + + # Export ONNX from best weights + model.load_state_dict(torch.load(best_pt, map_location=device)) + export_onnx(model, args.out, device=device) + + # Save label mapping + lbl_path = os.path.join(os.path.dirname(args.out), "label_mapping.json") + label_mapping = {str(i): cls for i, cls in enumerate(classes)} + with open(lbl_path, "w", encoding="utf-8") as f: + json.dump(label_mapping, f, indent=2) + print("Saved label mapping:", lbl_path) + print("Best val acc:", best_acc) + +if __name__ == "__main__": + main() diff --git a/services/inference_http/models/soil_moisture/tests/conftest.py b/services/inference_http/models/soil_moisture/tests/conftest.py new file mode 100644 index 000000000..5cfe605bc --- /dev/null +++ b/services/inference_http/models/soil_moisture/tests/conftest.py @@ -0,0 +1,10 @@ +import os +import sys + + +# Ensure `app` package (under src/) is importable when running tests +TEST_DIR = os.path.dirname(__file__) +SRC_DIR = os.path.abspath(os.path.join(TEST_DIR, "..", "src")) +if SRC_DIR not in sys.path: + sys.path.insert(0, SRC_DIR) + diff --git a/services/inference_http/models/soil_moisture/tests/test_config_and_schemas.py b/services/inference_http/models/soil_moisture/tests/test_config_and_schemas.py new file mode 100644 index 000000000..0fb9abae9 --- /dev/null +++ b/services/inference_http/models/soil_moisture/tests/test_config_and_schemas.py @@ -0,0 +1,43 @@ +import os +from app.config import load_zones, Settings +from app.schemas import InferRequest, InferResponse + + +def test_load_zones_file_exists_and_parses(): + # Use the repo's zones.yaml + base_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "..")) + zones_path = os.path.join(base_dir, "configs", "zones.yaml") + data = load_zones(zones_path) + assert isinstance(data, dict) + assert "zones" in data + assert isinstance(data["zones"], dict) + + +def test_settings_defaults_are_present(): + s = Settings() + # Ensure critical fields exist and are strings/ints + assert isinstance(s.kafka_brokers, str) + assert isinstance(s.kafka_topic, str) + assert isinstance(s.pg_dsn, str) + assert isinstance(s.decision_window_sec, int) + assert isinstance(s.patch_size, int) + assert isinstance(s.patch_stride, int) + + +def test_schemas_models_construction(): + req = InferRequest(device_id="zone-a", image_b64="abcd==") + assert req.device_id == "zone-a" + assert isinstance(req.image_b64, str) + + resp = InferResponse( + device_id="zone-a", + dry_ratio=0.5, + decision="run", + confidence=0.9, + patch_count=4, + ts="2024-01-01T00:00:00Z", + idempotency_key="zone-a:12345", + ) + assert resp.decision in {"run", "stop", "noop"} + assert resp.patch_count == 4 + diff --git a/services/inference_http/models/soil_moisture/tests/test_inference.py b/services/inference_http/models/soil_moisture/tests/test_inference.py new file mode 100644 index 000000000..5906bacfe --- /dev/null +++ b/services/inference_http/models/soil_moisture/tests/test_inference.py @@ -0,0 +1,96 @@ +import sys +import types +import numpy as np +from PIL import Image + +# Pre-inject a lightweight stub for app.onnx_model to avoid importing onnxruntime +stub_mod = types.ModuleType("app.onnx_model") +class _StubONNX: + def __init__(self, *a, **k): + # minimal surface to satisfy Inferencer init + self.label_map = {"0": "dry", "1": "wet"} + def predict_proba_patch(self, patch): + return np.array([0.5, 0.5], dtype=float) +stub_mod.ONNXMoistureModel = _StubONNX +sys.modules.setdefault("app.onnx_model", stub_mod) + +from app.config import Settings +from app import inference as infmod + + +class _FakeDryModel: + def __init__(self, *args, **kwargs): + # emulates label_map: index->label + self.label_map = {"0": "dry", "1": "wet"} + + def predict_proba_patch(self, patch): + # Always predict class 0 (dry) with high confidence + return np.array([0.9, 0.1], dtype=float) + + +class _FakeWetModel: + def __init__(self, *args, **kwargs): + self.label_map = {"0": "dry", "1": "wet"} + + def predict_proba_patch(self, patch): + # Always predict class 1 (wet) + return np.array([0.1, 0.9], dtype=float) + + +def _make_inferencer(monkeypatch, model_cls): + # Replace ONNX model with a lightweight fake + monkeypatch.setattr(infmod, "ONNXMoistureModel", lambda *a, **k: model_cls()) + + s = Settings() + s.patch_size = 10 + s.patch_stride = 10 + s.decision_window_sec = 300 + return infmod.Inferencer(s) + + +def _make_image(w=20, h=10): + return Image.new("RGB", (w, h), color=(128, 128, 128)) + + +def test_decision_run_when_dry_ratio_high(monkeypatch): + inf = _make_inferencer(monkeypatch, _FakeDryModel) + # 20x10 with 10x10 patches & stride 10 => 2 patches + img = _make_image(20, 10) + zone_cfg = {"_state": "stop", "dry_ratio_high": 0.5, "dry_ratio_low": 0.3, "min_patches": 2, "duration_min": 7} + + result, debug = inf.infer_image(img, zone_cfg) + assert result["patch_count"] == 2 + assert result["dry_ratio"] == 1.0 + assert result["decision"] == "run" + assert zone_cfg["_state"] == "run" + + +def test_decision_stop_when_dry_ratio_low_and_prev_run(monkeypatch): + inf = _make_inferencer(monkeypatch, _FakeWetModel) + img = _make_image(20, 10) # 2 patches + zone_cfg = {"_state": "run", "dry_ratio_high": 0.6, "dry_ratio_low": 0.25, "min_patches": 2, "duration_min": 5} + + result, _ = inf.infer_image(img, zone_cfg) + assert result["patch_count"] == 2 + assert result["dry_ratio"] == 0.0 + assert result["decision"] == "stop" + assert zone_cfg["_state"] == "stop" + + +def test_noop_when_not_enough_patches(monkeypatch): + inf = _make_inferencer(monkeypatch, _FakeDryModel) + img = _make_image(20, 10) # 2 patches + zone_cfg = {"_state": "stop", "dry_ratio_high": 0.5, "dry_ratio_low": 0.3, "min_patches": 3, "duration_min": 7} + + result, _ = inf.infer_image(img, zone_cfg) + assert result["patch_count"] == 2 + assert result["decision"] == "noop" + # State remains unchanged + assert zone_cfg["_state"] == "stop" + + +def test_decision_window_bucket_rounds_down(monkeypatch): + inf = _make_inferencer(monkeypatch, _FakeDryModel) + # With window 300s, 1234 -> bucket start 1200 + bucket = inf.decision_window_bucket(1234.0) + assert bucket == 1200 diff --git a/services/inference_http/models/soil_moisture/tests/test_utils.py b/services/inference_http/models/soil_moisture/tests/test_utils.py new file mode 100644 index 000000000..a45ea10e4 --- /dev/null +++ b/services/inference_http/models/soil_moisture/tests/test_utils.py @@ -0,0 +1,58 @@ +import base64 +import io +from PIL import Image +import numpy as np + +from app.utils import ( + load_image_from_b64, + normalize_lighting, + tile_image, + preprocess_onnx, +) + + +def make_rgb_image(w=8, h=6, color=(120, 100, 80)): + return Image.new("RGB", (w, h), color=color) + + +def test_load_image_from_b64_roundtrip(): + img = make_rgb_image(5, 7, (10, 20, 30)) + buf = io.BytesIO() + img.save(buf, format="PNG") + b64 = base64.b64encode(buf.getvalue()).decode("utf-8") + + out = load_image_from_b64(b64) + assert out.mode == "RGB" + assert out.size == (5, 7) + + +def test_normalize_lighting_basic_properties(): + img = make_rgb_image(10, 10, (50, 100, 150)) + out = normalize_lighting(img) + assert out.mode == "RGB" + assert out.size == img.size + + +def test_tile_image_regular_grid(): + img = make_rgb_image(5, 5, (0, 0, 0)) + patches = tile_image(img, patch_size=3, stride=2) + # Positions: x in {0,2}, y in {0,2} => 4 patches + assert len(patches) == 4 + assert all(p.size == (3, 3) for p in patches) + + +def test_tile_image_small_image_resizes_to_single_patch(): + img = make_rgb_image(2, 2, (0, 0, 0)) + patches = tile_image(img, patch_size=4, stride=4) + assert len(patches) == 1 + assert patches[0].size == (4, 4) + + +def test_preprocess_onnx_output_shape_and_range(): + img = make_rgb_image(6, 6, (255, 128, 0)) + arr = preprocess_onnx(img, size=8) + assert arr.shape == (1, 3, 8, 8) + assert arr.dtype == np.float32 + assert np.isfinite(arr).all() + assert arr.min() >= 0.0 and arr.max() <= 1.0 + diff --git a/services/inference_http/requirements.txt b/services/inference_http/requirements.txt index 69006df50..2aa5e14e7 100644 --- a/services/inference_http/requirements.txt +++ b/services/inference_http/requirements.txt @@ -1,4 +1,3 @@ - fastapi uvicorn pydantic @@ -11,3 +10,12 @@ ultralytics==8.2.34 boto3 pillow numpy==1.26.4 +onnxruntime==1.20.0 +kafka-python==2.0.2 +psycopg2-binary==2.9.10 +prometheus_client==0.21.0 +PyYAML==6.0.2 +python-dotenv==1.0.1 +requests==2.32.3 +python-multipart==0.0.6 +confluent_kafka==2.12.0 diff --git a/services/mqtt_gateway/Dockerfile b/services/mqtt_gateway/Dockerfile new file mode 100644 index 000000000..4a0d1c1ad --- /dev/null +++ b/services/mqtt_gateway/Dockerfile @@ -0,0 +1,42 @@ +# syntax=docker/dockerfile:1 +FROM python:3.12-slim + +ARG USE_NETFREE=true + +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates curl libc6 libsasl2-2 libssl3 librdkafka1 \ + && rm -rf /var/lib/apt/lists/* + +# (Optional) import NetFree cert if present in build context +RUN if [ "$USE_NETFREE" = "true" ] && [ -f ./netfree-ca.crt ]; then \ + cp ./netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt && \ + chmod 644 /usr/local/share/ca-certificates/netfree-ca.crt && \ + update-ca-certificates; \ + fi + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PIP_DISABLE_PIP_VERSION_CHECK=1 + +WORKDIR /app +# COPY services/mqtt_gateway/requirements.txt . +COPY requirements.txt . +RUN pip install --no-cache-dir --trusted-host pypi.org --trusted-host files.pythonhosted.org -r requirements.txt + +# COPY services/mqtt_gateway /app/services/mqtt_gateway +COPY . /app/services/mqtt_gateway + + +# Default envs (override in deployment) +ENV MINIO_ENDPOINT=http://minio:9000 \ + MINIO_ACCESS_KEY=minioadmin \ + MINIO_SECRET_KEY=minioadmin \ + MINIO_BUCKET=rover-images \ + KAFKA_BOOTSTRAP=kafka:9092 \ + KAFKA_TOPIC=rover.images.meta.v1 \ + MQTT_HOST=mosquitto \ + MQTT_PORT=1883 \ + MQTT_TOPIC=MQTT/imagery/# \ + MQTT_CLIENT_ID=mqtt-gateway + +CMD ["python", "-m", "services.mqtt_gateway.main"] diff --git a/services/mqtt_gateway/adapters/kafka_producer.py b/services/mqtt_gateway/adapters/kafka_producer.py new file mode 100644 index 000000000..4703085b3 --- /dev/null +++ b/services/mqtt_gateway/adapters/kafka_producer.py @@ -0,0 +1,32 @@ +# services/mqtt_gateway/adapters/kafka_producer.py +# Confluent Kafka producer adapter with lazy imports for unit-test friendliness. + +from __future__ import annotations +import json, importlib +from typing import Optional + +from services.mqtt_gateway.io import EventBusProducer + + +class ConfluentEventBusProducer(EventBusProducer): + """ + Thin wrapper over confluent_kafka. Handles JSON serialization and delivery errors. + Lazy-imports confluent_kafka to keep unit tests independent of that binary dep. + """ + + def __init__(self, bootstrap_servers: str, client_id: str = "mqtt-gateway") -> None: + if not bootstrap_servers: + raise ValueError("bootstrap_servers required") + ck = importlib.import_module("confluent_kafka") + self._Producer = ck.Producer + self._p = self._Producer({"bootstrap.servers": bootstrap_servers, "client.id": client_id}) + + def _delivery(self, err, msg) -> None: + if err is not None: + raise RuntimeError(f"kafka delivery failed: {err.str()}") + + def send(self, topic: str, key: str, value: dict) -> None: + payload = json.dumps(value, ensure_ascii=False).encode("utf-8") + self._p.produce(topic=topic, key=key, value=payload, callback=self._delivery) + self._p.poll(0) + self._p.flush(5) diff --git a/services/mqtt_gateway/adapters/minio_store.py b/services/mqtt_gateway/adapters/minio_store.py new file mode 100644 index 000000000..ab9074e85 --- /dev/null +++ b/services/mqtt_gateway/adapters/minio_store.py @@ -0,0 +1,77 @@ +# services/mqtt_gateway/adapters/minio_store.py +# Boto3-based ImageStore adapter with lazy imports for unit-test friendliness. + +from __future__ import annotations +from typing import Tuple +import io, hashlib, importlib + +from services.mqtt_gateway.io import ImageStore + + +def _sha256_hex(b: bytes) -> str: + h = hashlib.sha256(); h.update(b); return h.hexdigest() + + +class Boto3ImageStore(ImageStore): + """ + Uploads bytes to S3-compatible storage (MinIO). + Lazy-imports boto3/botocore to avoid hard dependency during unit tests. + """ + + def __init__( + self, + endpoint_url: str, + access_key: str, + secret_key: str, + *, + addressing_style: str = "path", + multipart_threshold: int = 5 * 1024 * 1024, + multipart_chunksize: int = 5 * 1024 * 1024, + max_concurrency: int = 16, + retries: int = 3, + ) -> None: + # Lazy imports (so importing this module won't require boto3 installed) + boto3 = importlib.import_module("boto3") + botocore_config = importlib.import_module("botocore.config") + s3_transfer = importlib.import_module("boto3.s3.transfer") + + BotoConfig = botocore_config.Config + TransferConfig = s3_transfer.TransferConfig + + self._s3 = boto3.client( + "s3", + endpoint_url=endpoint_url, + aws_access_key_id=access_key, + aws_secret_access_key=secret_key, + config=BotoConfig( + signature_version="s3v4", + s3={"addressing_style": addressing_style}, + max_pool_connections=max(64, max_concurrency * 2), + retries={"max_attempts": retries, "mode": "standard"}, + ), + ) + self._tx = TransferConfig( + multipart_threshold=multipart_threshold, + multipart_chunksize=multipart_chunksize, + max_concurrency=max_concurrency, + use_threads=True, + ) + + def put_object(self, bucket: str, key: str, data: bytes, content_type: str) -> Tuple[str, int]: + if not bucket or not key: + raise ValueError("bucket/key must be non-empty") + if data is None: + raise ValueError("data must not be None") + ctype = content_type or "application/octet-stream" + + sha = _sha256_hex(data) + size = len(data) + extra = {"ContentType": ctype, "Metadata": {"checksum-sha256": sha}} + + if size >= self._tx.multipart_threshold: + bio = io.BytesIO(data) + self._s3.upload_fileobj(bio, bucket, key, ExtraArgs=extra, Config=self._tx) + else: + self._s3.put_object(Bucket=bucket, Key=key, Body=data, **extra) + + return sha, size diff --git a/services/mqtt_gateway/config.py b/services/mqtt_gateway/config.py new file mode 100644 index 000000000..126c75ee8 --- /dev/null +++ b/services/mqtt_gateway/config.py @@ -0,0 +1,45 @@ +# services/mqtt_gateway/config.py +# Purpose: centralize and validate service configuration (12-factor style). + +from __future__ import annotations +from pydantic import BaseModel, Field, AnyUrl, ValidationError +import os + +class GatewayConfig(BaseModel): + # Storage + minio_endpoint: str = Field(default="http://minio:9000") + minio_access_key: str = Field(default="minioadmin", min_length=1) + minio_secret_key: str = Field(default="minioadmin", min_length=1) + minio_bucket: str = Field(default="rover-images", min_length=1) + + # Kafka + kafka_bootstrap: str = Field(default="kafka:9092", min_length=1) + kafka_topic: str = Field(default="rover.images.meta.v1", min_length=1) + + # MQTT + mqtt_host: str = Field(default="mosquitto") + mqtt_port: int = Field(default=1883, ge=1) + mqtt_topic: str = Field(default="MQTT/imagery/#") + mqtt_client_id: str = Field(default="mqtt-gateway") + + # Server/metrics + metrics_port: int = Field(default=9110, ge=1024, le=65535) + +def load_config() -> GatewayConfig: + env = os.getenv + try: + return GatewayConfig( + minio_endpoint=env("MINIO_ENDPOINT", "http://minio:9000"), + minio_access_key=env("MINIO_ACCESS_KEY", "minioadmin"), + minio_secret_key=env("MINIO_SECRET_KEY", "minioadmin"), + minio_bucket=env("MINIO_BUCKET", "rover-images"), + kafka_bootstrap=env("KAFKA_BOOTSTRAP", "kafka:9092"), + kafka_topic=env("KAFKA_TOPIC", "rover.images.meta.v1"), + mqtt_host=env("MQTT_HOST", "mosquitto"), + mqtt_port=int(env("MQTT_PORT", "1883")), + mqtt_topic=env("MQTT_TOPIC", "MQTT/imagery/#"), + mqtt_client_id=env("MQTT_CLIENT_ID", "mqtt-gateway"), + metrics_port=int(env("METRICS_PORT", "9110")), + ) + except ValidationError as ve: + raise SystemExit(f"[config] invalid env: {ve}") from ve diff --git a/services/mqtt_gateway/docs/contracts.md b/services/mqtt_gateway/docs/contracts.md new file mode 100644 index 000000000..42dc6f280 --- /dev/null +++ b/services/mqtt_gateway/docs/contracts.md @@ -0,0 +1,33 @@ +# MQTT → MinIO → Kafka Data Contract + +> Purpose: a stable, versioned contract for image ingestion events. +> Scope: mapping from publisher topic to MinIO object key and Kafka event. + +## Example publisher file name +`garage_cam_01_20251027_121530.jpg` + +## Kafka topic (value JSON published to this topic) +`rover.images.meta.v1` + +## Kafka message (value) +```json +{ + "version": 1, + "event_id": "8b0a6f2b-1f95-4b28-9870-5f7f1d4a6a11", + "sensor_id": "camera-01", + "captured_ts": 1761548130123, + "image": { + "bucket": "rover-images", + "key": "images/camera-01/2025/10/27/camera-01_1761548130123.jpg", + "size_bytes": 531245, + "sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", + "content_type": "image/jpeg" + }, + "telemetry": { + "lat": 32.061, + "lon": 34.772, + "heading": 182.4, + "speed_mps": 2.1 + }, + "producer": "mqtt-gateway" +} diff --git a/services/mqtt_gateway/io.py b/services/mqtt_gateway/io.py new file mode 100644 index 000000000..d0b9f3c4d --- /dev/null +++ b/services/mqtt_gateway/io.py @@ -0,0 +1,40 @@ +# services/mqtt_gateway/io.py +# Purpose: IO interfaces (protocols) used by the service for testability. + +from __future__ import annotations +from typing import Protocol, Optional, runtime_checkable + + +@runtime_checkable +class ImageStore(Protocol): + def put_object( + self, + bucket: str, + key: str, + data: bytes, + content_type: str, + ) -> tuple[str, int]: + """ + Uploads bytes to object storage. + Returns: (sha256_hex, size_bytes) + Must raise an exception on failure. + """ + + +@runtime_checkable +class EventBusProducer(Protocol): + def send(self, topic: str, key: str, value: dict) -> None: + """ + Publishes a message to an event bus (e.g., Kafka). + Must raise an exception on failure. + """ + + +class Clock(Protocol): + def now_ms(self) -> int: + """Epoch milliseconds (used mostly for timestamps in logs/metrics).""" + + +class IdGenerator(Protocol): + def new_event_id(self) -> str: + """Return a new UUID string for event_id.""" diff --git a/services/mqtt_gateway/main.py b/services/mqtt_gateway/main.py new file mode 100644 index 000000000..612f8f8f3 --- /dev/null +++ b/services/mqtt_gateway/main.py @@ -0,0 +1,189 @@ +# services/mqtt_gateway/main.py +# MQTT consumer → build ImageInfo → process via IngestService. +# Designed for Docker. All configuration by env vars. +from __future__ import annotations + +from prometheus_client import Counter, Histogram, start_http_server +import logging +from services.mqtt_gateway.config import load_config + +import os, signal, sys, time, pathlib +from typing import Tuple +from paho.mqtt.client import Client, MQTTv5, CallbackAPIVersion +import paho.mqtt.client as mqtt +import json, threading +from typing import Optional, Dict, Tuple as _Tuple + +from services.mqtt_gateway.models import ImageInfo +from services.mqtt_gateway.service import ( + ServiceConfig, Deps, IngestService, DefaultClock, DefaultIds +) +from services.mqtt_gateway.adapters.minio_store import Boto3ImageStore +from services.mqtt_gateway.adapters.kafka_producer import ConfluentEventBusProducer + +TELEMETRY_TOPIC = os.getenv("MQTT_TOPIC_TEL", "MQTT/telemetry/#") +TELEMETRY_TTL_SEC = int(os.getenv("TELEMETRY_TTL_SEC", "10")) # seconds + +# --------- Metrics & Logging --------- +INGEST_OK = Counter("gateway_ingest_success_total", "successful publishes") +INGEST_FAIL = Counter("gateway_ingest_fail_total", "failed publishes") +INGEST_LAT = Histogram("gateway_ingest_latency_ms", "ingest latency (ms)") +logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s %(message)s") +log = logging.getLogger("mqtt-gateway") + + +# --------- Topic parser (mirrors your existing convention) --------- +def parse_topic(topic: str, filename_fallback: str = "image.jpg") -> Tuple[str, int, str, str]: + """ + Returns (sensor_id, ts_ms, content_type, filename) + Topic format: MQTT/imagery/{camera}/{ts_ms}/{ctype_safe}/{filename} + """ + parts = [p for p in topic.split("/") if p] + try: + i = parts.index("imagery") + except ValueError: + return ("unknown", int(time.time() * 1000), "application/octet-stream", filename_fallback) + + sensor = parts[i + 1] if len(parts) > i + 1 else "unknown" + ts_ms = int(parts[i + 2]) if len(parts) > i + 2 and parts[i + 2].isdigit() else int(time.time() * 1000) + ctype = (parts[i + 3] if len(parts) > i + 3 else "application_octet-stream").replace("_", "/") + fname = parts[i + 4] if len(parts) > i + 4 else filename_fallback + return (sensor, ts_ms, ctype, fname) + +# sensor_id -> (ts_ms, telemetry_dict) +_telemetry_cache: Dict[str, _Tuple[int, dict]] = {} +_telemetry_lock = threading.Lock() + +def parse_tel_topic(topic: str) -> _Tuple[str, int]: + """ + Parse telemetry topic: MQTT/telemetry/{sensor_id}/{ts_ms} + Returns (sensor_id, ts_ms). + """ + parts = [p for p in topic.split("/") if p] + try: + i = parts.index("telemetry") + except ValueError: + return ("unknown", int(time.time() * 1000)) + sensor = parts[i + 1] if len(parts) > i + 1 else "unknown" + ts_ms = int(parts[i + 2]) if len(parts) > i + 2 and parts[i + 2].isdigit() else int(time.time() * 1000) + return (sensor, ts_ms) + +def put_telemetry(sensor_id: str, ts_ms: int, tel: dict) -> None: + """Store latest telemetry per sensor (monotonic by ts_ms).""" + with _telemetry_lock: + prev = _telemetry_cache.get(sensor_id) + if (not prev) or ts_ms >= prev[0]: + _telemetry_cache[sensor_id] = (ts_ms, tel) + +def get_telemetry_for(sensor_id: str, captured_ts: int) -> Optional[dict]: + """ + Return telemetry if within TTL window relative to captured_ts. + """ + with _telemetry_lock: + row = _telemetry_cache.get(sensor_id) + if not row: + return None + ts_ms, tel = row + if abs(captured_ts - ts_ms) <= TELEMETRY_TTL_SEC * 1000: + return tel + return None + +def make_service_from_cfg(cfg) -> IngestService: + store = Boto3ImageStore( + endpoint_url=cfg.minio_endpoint, + access_key=cfg.minio_access_key, + secret_key=cfg.minio_secret_key, + ) + producer = ConfluentEventBusProducer(bootstrap_servers=cfg.kafka_bootstrap) + s_cfg = ServiceConfig(bucket=cfg.minio_bucket, kafka_topic=cfg.kafka_topic) + deps = Deps(image_store=store, producer=producer, clock=DefaultClock(), ids=DefaultIds()) + return IngestService(s_cfg, deps) + +def main() -> None: + cfg = load_config() + start_http_server(cfg.metrics_port, addr="0.0.0.0") + log.info("metrics server started on :%d", cfg.metrics_port) + service = make_service_from_cfg(cfg) + + client = mqtt.Client(CallbackAPIVersion.VERSION2, client_id=cfg.mqtt_client_id, protocol=MQTTv5) + stop = False + + def on_connect(c, u, flags, rc, props): + if rc == 0: + log.info("mqtt connected, subscribing %s", cfg.mqtt_topic) + c.subscribe(cfg.mqtt_topic, qos=1) + c.subscribe(TELEMETRY_TOPIC, qos=0) + else: + print(f"[mqtt] connect failed rc={rc}") + + def on_message(c, u, msg): + # if "/telemetry/" in msg.topic: + # try: + # sensor, ts_ms, ctype, fname = parse_topic(msg.topic) + # tel = json.loads(msg.payload.decode("utf-8")) + # put_telemetry(sensor, ts_ms, tel) + # log.debug("telemetry cached sensor=%s ts=%d", sensor, ts_ms) + # except Exception as e: + # log.warning("bad telemetry message: %s", e, exc_info=False) + # return + if "/telemetry/" in msg.topic: + try: + sensor, ts_ms = parse_tel_topic(msg.topic) + tel = json.loads(msg.payload.decode("utf-8")) + put_telemetry(sensor, ts_ms, tel) + log.debug("telemetry cached sensor=%s ts=%d", sensor, ts_ms) + except Exception as e: + log.warning("bad telemetry message: %s", e, exc_info=False) + return + + # ---- image branch ---- + with INGEST_LAT.time(): + try: + # ✅ parse the image topic to get required fields + sensor, ts_ms, ctype, fname = parse_topic(msg.topic) + + # build ImageInfo from topic + payload mime + info = ImageInfo( + sensor_id=sensor, + captured_ts=ts_ms, + filename=fname, + content_type=ctype, + ) + + # match last telemetry (if within TTL) + tel = get_telemetry_for(sensor, ts_ms) + + # pass telemetry down to the service + _m, _e = service.process_image(info, msg.payload, telemetry=tel) + + INGEST_OK.inc() + log.info( + "ingest ok sensor=%s ts=%s key=%s tel=%s", + sensor, ts_ms, _m.key, "yes" if tel else "no" + ) + except Exception as e: + INGEST_FAIL.inc() + log.error("ingest error: %s", e, exc_info=False) + + client.on_connect = on_connect + client.on_message = on_message + client.reconnect_delay_set(min_delay=1, max_delay=8) + client.connect(cfg.mqtt_host, cfg.mqtt_port, keepalive=60) + client.loop_start() + + def _stop(*_): + nonlocal stop + stop = True + client.loop_stop() + client.disconnect() + + signal.signal(signal.SIGINT, _stop) + signal.signal(signal.SIGTERM, _stop) + + log.info("gateway running…") + while not stop: + time.sleep(0.5) + log.info("gateway stopped.") + +if __name__ == "__main__": + main() diff --git a/services/mqtt_gateway/mapper.py b/services/mqtt_gateway/mapper.py new file mode 100644 index 000000000..c8d77b359 --- /dev/null +++ b/services/mqtt_gateway/mapper.py @@ -0,0 +1,87 @@ +# services/mqtt_gateway/mapper.py +# Purpose: pure functions to compute MinIO object key & Kafka event from MQTT topic parts. +# No network. Easy to unit-test. + +from __future__ import annotations +from datetime import datetime, timezone +from typing import Tuple, Optional +from uuid import uuid4 +import os + +from .models import MinioObject, ImageInfo, KafkaEvent + + +def safe_ext(filename: str, default: str = ".jpg") -> str: + """Return a safe file extension with dot. Fallback to default if missing/invalid.""" + _, ext = os.path.splitext(filename) + ext = (ext or "").strip().lower() + if not ext or len(ext) > 8 or any(c in ext for c in " \t/\\"): + return default + return ext + + +def date_parts_from_epoch_ms(ts_ms: int) -> Tuple[str, str, str]: + dt = datetime.fromtimestamp(ts_ms / 1000.0, tz=timezone.utc) + return f"{dt.year:04d}", f"{dt.month:02d}", f"{dt.day:02d}" + + +# def build_minio_key(sensor_id: str, ts_ms: int, filename: str) -> str: +# """images/{sensor}/{YYYY}/{MM}/{DD}/{sensor}_{ts}{ext}""" +# y, m, d = date_parts_from_epoch_ms(ts_ms) +# ext = safe_ext(filename) +# base = f"{sensor_id}_{ts_ms}{ext}" +# return f"images/{sensor_id}/{y}/{m}/{d}/{base}" + +def build_minio_key( + sensor_id: str, + ts_ms: int, + filename: str, + *, + incident_id: str, + rover_type: str = "rover-car", + prefix: str = "security/incidents", +) -> str: + """ + Build canonical S3 key: + imagery/security/incidents///_ + + Notes: + - `incident_id` must be provided by the caller (stable folder per incident). + - `rover_type` has a sensible default ("rover-car") but can be overridden. + """ + ext = safe_ext(filename, default=".jpg") + base = f"{sensor_id}_{ts_ms}{ext}" + return f"{prefix}/{rover_type}/{incident_id}/{base}" + + +def map_to_objects( + bucket: str, + info: ImageInfo, + *, + sha256: Optional[str] = None, + size_bytes: Optional[int] = None, + event_id: Optional[str] = None, + telemetry: Optional[dict] = None +) -> Tuple[MinioObject, KafkaEvent]: + """ + Given input image info → compute MinIO object + Kafka event. + Pure function: no IO. Easy to unit test. + """ + key = build_minio_key(info.sensor_id, info.captured_ts, info.filename, incident_id=event_id or str(uuid4())) + mobj = MinioObject( + bucket=bucket, + key=key, + content_type=info.content_type, + size_bytes=size_bytes, + sha256=sha256, + ) + kev = KafkaEvent( + version=1, + event_id=(event_id or str(uuid4())), + sensor_id=info.sensor_id, + captured_ts=info.captured_ts, + image=mobj, + # telemetry=None, + telemetry=telemetry, + ) + return mobj, kev diff --git a/services/mqtt_gateway/models.py b/services/mqtt_gateway/models.py new file mode 100644 index 000000000..327ed9f2b --- /dev/null +++ b/services/mqtt_gateway/models.py @@ -0,0 +1,46 @@ +# services/mqtt_gateway/models.py +# Purpose: Typed, validated data contracts for MQTT→MinIO/Kafka mapping. +# Clean, testable models used across the service. + +from __future__ import annotations +from pydantic import BaseModel, Field, ConfigDict, field_validator +from typing import Optional + + +class MinioObject(BaseModel): + model_config = ConfigDict(extra="forbid") + bucket: str = Field(min_length=1) + key: str = Field(min_length=1) + content_type: str = Field(min_length=1) + size_bytes: Optional[int] = Field(default=None, ge=0) + sha256: Optional[str] = None + + +class ImageInfo(BaseModel): + model_config = ConfigDict(extra="forbid") + sensor_id: str = Field(min_length=1) + captured_ts: int = Field(ge=0, description="epoch milliseconds") + filename: str = Field(min_length=1) + content_type: str = Field(min_length=1) + + @field_validator("content_type") + @classmethod + def normalize_ctype(cls, v: str) -> str: + return v.strip().lower() + + +class KafkaEvent(BaseModel): + model_config = ConfigDict(extra="forbid") + version: int = 1 + event_id: str + sensor_id: str + captured_ts: int + image: MinioObject + telemetry: Optional[dict] = None + producer: str = "mqtt-gateway" + + @property + def key(self) -> str: + """Kafka message key (partitioning & idempotency hint).""" + return f"{self.sensor_id}:{self.captured_ts}" + diff --git a/services/mqtt_gateway/requirements.txt b/services/mqtt_gateway/requirements.txt new file mode 100644 index 000000000..3bdb4f438 --- /dev/null +++ b/services/mqtt_gateway/requirements.txt @@ -0,0 +1,8 @@ +pydantic>=2.7,<3 +pytest>=8,<9 +boto3>=1.34 +confluent-kafka>=2.5 +paho-mqtt>=2.1 +prometheus-client>=0.20 +Pillow>=10 +piexif>=1.1 \ No newline at end of file diff --git a/services/mqtt_gateway/service.py b/services/mqtt_gateway/service.py new file mode 100644 index 000000000..a7e4a70f5 --- /dev/null +++ b/services/mqtt_gateway/service.py @@ -0,0 +1,117 @@ +# services/mqtt_gateway/service.py +# Purpose: Orchestrates the ingestion of an image payload: +# parse → store in MinIO (via ImageStore) → build Kafka event → publish (EventBusProducer). +# Pure business logic, with IO abstracted behind interfaces for unit testing. + +from __future__ import annotations +from dataclasses import dataclass +from typing import Optional, Tuple +from uuid import uuid4 +import hashlib + +from .models import ImageInfo, MinioObject, KafkaEvent +from .mapper import build_minio_key, map_to_objects +from .io import ImageStore, EventBusProducer, Clock, IdGenerator +import logging +log = logging.getLogger("ingest-service") + +def _sha256_hex(b: bytes) -> str: + h = hashlib.sha256() + h.update(b) + return h.hexdigest() + + +@dataclass(frozen=True) +class ServiceConfig: + bucket: str + kafka_topic: str + + +@dataclass +class Deps: + image_store: ImageStore + producer: EventBusProducer + clock: Clock + ids: IdGenerator + + +class DefaultClock(Clock): + def now_ms(self) -> int: + import time + return int(time.time() * 1000) + + +class DefaultIds(IdGenerator): + def new_event_id(self) -> str: + return str(uuid4()) + + +class IngestService: + """ + Public API: + - process_image(info, payload) -> (MinioObject, KafkaEvent) + + Notes: + - No direct imports of storage/kafka SDKs here. Only interfaces. + - Idempotency is enforced downstream by keying on (sensor_id, captured_ts). + """ + + def __init__(self, cfg: ServiceConfig, deps: Deps) -> None: + self.cfg = cfg + self.deps = deps + + def _retry(self, fn, attempts=3): + last = None + for i in range(1, attempts + 1): + try: + return fn() + except Exception as e: + last = e + if i == attempts: + raise + raise last + + def process_image(self, info: ImageInfo, payload: bytes, telemetry: Optional[dict] = None) -> Tuple[MinioObject, KafkaEvent]: + + # 1) Compute MinIO object key (stable contract) + # key = build_minio_key(info.sensor_id, info.captured_ts, info.filename) + event_id = self.deps.ids.new_event_id() # single source for both event & incident + incident_id = event_id # reuse; replace if you have a real incident id + key = build_minio_key( + info.sensor_id, info.captured_ts, info.filename, + incident_id=incident_id, + rover_type="rover-car" # adjust if needed + ) + + # 2) Upload to object storage + sha, size = self._retry(lambda: self.deps.image_store.put_object( + bucket=self.cfg.bucket, key=key, data=payload, content_type=info.content_type + )) + + # 3) Build event (add sha/size and deterministic IDs) + mobj, kev = map_to_objects( + bucket=self.cfg.bucket, + info=info, + sha256=sha, + size_bytes=size, + event_id=event_id, + telemetry=telemetry, + ) + + if telemetry is not None: + kev.telemetry = telemetry + + # 4) Publish to event bus + + try: + self._retry(lambda: self.deps.producer.send( + topic=self.cfg.kafka_topic, key=kev.key, value=kev.model_dump() + )) + except Exception as e: + # Do not raise — MinIO write already succeeded. Log and continue. + log.warning( + "kafka publish failed (topic=%s, key=%s): %s", + self.cfg.kafka_topic, kev.key, e + ) + + return mobj, kev diff --git a/services/mqtt_gateway/tests/fixtures/sample_event.json b/services/mqtt_gateway/tests/fixtures/sample_event.json new file mode 100644 index 000000000..b291d7530 --- /dev/null +++ b/services/mqtt_gateway/tests/fixtures/sample_event.json @@ -0,0 +1,15 @@ +{ + "version": 1, + "event_id": "00000000-0000-0000-0000-000000000000", + "sensor_id": "camera-01", + "captured_ts": 1761548130123, + "image": { + "bucket": "rover-images", + "key": "images/camera-01/2025/10/27/camera-01_1761548130123.jpg", + "size_bytes": 531245, + "sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", + "content_type": "image/jpeg" + }, + "telemetry": { "lat": 32.061, "lon": 34.772, "heading": 182.4, "speed_mps": 2.1 }, + "producer": "mqtt-gateway" +} diff --git a/services/mqtt_gateway/tests/test_adapters_unit.py b/services/mqtt_gateway/tests/test_adapters_unit.py new file mode 100644 index 000000000..19c9a4122 --- /dev/null +++ b/services/mqtt_gateway/tests/test_adapters_unit.py @@ -0,0 +1,52 @@ +# services/mqtt_gateway/tests/test_adapters_unit.py +from __future__ import annotations +from unittest.mock import Mock, patch +import types + +def test_minio_store_put_object_calls_boto3_correctly(): + # Fake boto3 + botocore modules + fake_s3_client = Mock() + fake_s3_client.put_object = Mock() + fake_s3_client.upload_fileobj = Mock() + + def fake_import(name): + if name == "boto3": + # expose client() that returns our fake client + m = types.SimpleNamespace(client=lambda *a, **k: fake_s3_client) + return m + if name == "botocore.config": + class _Cfg: + def __init__(self, **kwargs): pass + return types.SimpleNamespace(Config=_Cfg) + if name == "boto3.s3.transfer": + class _Tx: + def __init__(self, multipart_threshold, multipart_chunksize, max_concurrency, use_threads): + self.multipart_threshold = multipart_threshold + return types.SimpleNamespace(TransferConfig=_Tx) + raise ImportError(name) + + with patch("services.mqtt_gateway.adapters.minio_store.importlib.import_module", side_effect=fake_import): + from services.mqtt_gateway.adapters.minio_store import Boto3ImageStore + store = Boto3ImageStore(endpoint_url="http://minio:9000", access_key="a", secret_key="s") + sha, size = store.put_object("bkt", "key", b"1234", "image/jpeg") + # For small payload (4 bytes) → put_object path + fake_s3_client.put_object.assert_called_once() + assert sha and size == 4 + +def test_kafka_producer_json_serialization(): + fake_prod = Mock() + + def fake_import(name): + if name == "confluent_kafka": + return types.SimpleNamespace(Producer=lambda conf: fake_prod) + raise ImportError(name) + + with patch("services.mqtt_gateway.adapters.kafka_producer.importlib.import_module", side_effect=fake_import): + from services.mqtt_gateway.adapters.kafka_producer import ConfluentEventBusProducer + k = ConfluentEventBusProducer("kafka:9092") + k.send("t", "k1", {"a": 1}) + fake_prod.produce.assert_called_once() + args, kwargs = fake_prod.produce.call_args + assert kwargs["topic"] == "t" + assert kwargs["key"] == "k1" + assert isinstance(kwargs["value"], (bytes, bytearray)) diff --git a/services/mqtt_gateway/tests/test_mapper.py b/services/mqtt_gateway/tests/test_mapper.py new file mode 100644 index 000000000..598e62c7a --- /dev/null +++ b/services/mqtt_gateway/tests/test_mapper.py @@ -0,0 +1,33 @@ +# services/mqtt_gateway/tests/test_mapper.py +# Purpose: Unit tests for pure mapping logic (no MinIO/Kafka). +# Run: pytest -q + +from services.mqtt_gateway.models import ImageInfo +from services.mqtt_gateway.mapper import build_minio_key, map_to_objects + + +def test_build_minio_key_happy(): + key = build_minio_key("camera-01", 1761548130123, "foo.jpg") + assert key.startswith("images/camera-01/2025/10/27/") + assert key.endswith("camera-01_1761548130123.jpg") + + +def test_build_minio_key_ext_fallback(): + key = build_minio_key("s1", 1000, "noext") + assert key.endswith("s1_1000.jpg") + + +def test_map_to_objects_event_and_key(): + info = ImageInfo( + sensor_id="camera-01", + captured_ts=1761548130123, + filename="garage_cam_01_20251027_121530.jpg", + content_type="image/jpeg", + ) + mobj, kev = map_to_objects("rover-images", info, sha256="abc", size_bytes=123) + assert mobj.bucket == "rover-images" + assert mobj.key.endswith("camera-01_1761548130123.jpg") + assert mobj.sha256 == "abc" + assert kev.image.key == mobj.key + assert kev.key == "camera-01:1761548130123" + assert kev.version == 1 diff --git a/services/mqtt_gateway/tests/test_service.py b/services/mqtt_gateway/tests/test_service.py new file mode 100644 index 000000000..1a7278b92 --- /dev/null +++ b/services/mqtt_gateway/tests/test_service.py @@ -0,0 +1,105 @@ +# services/mqtt_gateway/tests/test_service.py +# Purpose: Unit tests for the orchestration service using mocks for IO. + +from __future__ import annotations +from unittest.mock import Mock +import pytest + +from services.mqtt_gateway.models import ImageInfo +from services.mqtt_gateway.service import ( + ServiceConfig, Deps, IngestService, DefaultClock, DefaultIds +) + + +def make_info(): + return ImageInfo( + sensor_id="camera-01", + captured_ts=1761548130123, + filename="garage_cam_01_20251027_121530.jpg", + content_type="image/jpeg", + ) + + +def test_process_image_happy_path(): + # Arrange + cfg = ServiceConfig(bucket="rover-images", kafka_topic="rover.images.meta.v1") + + image_store = Mock() + image_store.put_object.return_value = ("abc123", 531245) + + producer = Mock() + + clock = DefaultClock() + ids = Mock() + ids.new_event_id.return_value = "11111111-1111-1111-1111-111111111111" + + service = IngestService(cfg, Deps(image_store=image_store, producer=producer, clock=clock, ids=ids)) + info = make_info() + payload = b"\xff\xd8\xff\xdb\x00..." # fake jpeg bytes + + # Act + mobj, kev = service.process_image(info, payload) + + # Assert: storage call + image_store.put_object.assert_called_once() + args, kwargs = image_store.put_object.call_args + assert kwargs["bucket"] == "rover-images" + assert kwargs["content_type"] == "image/jpeg" + assert kwargs["data"] == payload + assert kwargs["key"].endswith("camera-01_1761548130123.jpg") + + # Assert: event produced + producer.send.assert_called_once() + p_args, p_kwargs = producer.send.call_args + assert p_kwargs["topic"] == "rover.images.meta.v1" + assert p_kwargs["key"] == "camera-01:1761548130123" + val = p_kwargs["value"] + assert val["event_id"] == "11111111-1111-1111-1111-111111111111" + assert val["image"]["bucket"] == "rover-images" + assert val["image"]["key"].endswith("camera-01_1761548130123.jpg") + assert val["image"]["sha256"] == "abc123" + assert val["image"]["size_bytes"] == 531245 + + +def test_process_image_store_failure(): + cfg = ServiceConfig(bucket="rover-images", kafka_topic="rover.images.meta.v1") + + image_store = Mock() + image_store.put_object.side_effect = RuntimeError("store down") + + producer = Mock() + clock = DefaultClock() + ids = DefaultIds() + + service = IngestService(cfg, Deps(image_store=image_store, producer=producer, clock=clock, ids=ids)) + info = make_info() + payload = b"data" + + with pytest.raises(RuntimeError): + service.process_image(info, payload) + + # Ensure producer not called when store fails + producer.send.assert_not_called() + + +def test_process_image_producer_failure(): + cfg = ServiceConfig(bucket="rover-images", kafka_topic="rover.images.meta.v1") + + image_store = Mock() + image_store.put_object.return_value = ("sha-ok", 10) + + producer = Mock() + producer.send.side_effect = RuntimeError("kafka down") + + clock = DefaultClock() + ids = DefaultIds() + + service = IngestService(cfg, Deps(image_store=image_store, producer=producer, clock=clock, ids=ids)) + info = make_info() + payload = b"data" + + with pytest.raises(RuntimeError): + service.process_image(info, payload) + + # Ensure we DID upload but failed on publish + image_store.put_object.assert_called_once() diff --git a/services/mqtt_gateway/tests/test_service_retry.py b/services/mqtt_gateway/tests/test_service_retry.py new file mode 100644 index 000000000..5571fed97 --- /dev/null +++ b/services/mqtt_gateway/tests/test_service_retry.py @@ -0,0 +1,36 @@ +from unittest.mock import Mock +import pytest + +from services.mqtt_gateway.models import ImageInfo +from services.mqtt_gateway.service import ServiceConfig, Deps, IngestService, DefaultClock, DefaultIds + +def make_info(): + return ImageInfo(sensor_id="s1", captured_ts=1000, filename="a.jpg", content_type="image/jpeg") + +def test_retry_on_store_once_then_success(): + cfg = ServiceConfig(bucket="b", kafka_topic="t") + store = Mock() + store.put_object.side_effect = [RuntimeError("flaky"), ("sha", 3)] + prod = Mock() + svc = IngestService(cfg, Deps(store, prod, DefaultClock(), DefaultIds())) + m, e = svc.process_image(make_info(), b"xxx") + assert prod.send.called + +def test_retry_on_producer_once_then_success(): + cfg = ServiceConfig(bucket="b", kafka_topic="t") + store = Mock() + store.put_object.return_value = ("sha", 3) + prod = Mock() + prod.send.side_effect = [RuntimeError("flaky"), None] + svc = IngestService(cfg, Deps(store, prod, DefaultClock(), DefaultIds())) + m, e = svc.process_image(make_info(), b"xxx") + assert prod.send.call_count == 2 + +def test_retry_exhaust_raises(): + cfg = ServiceConfig(bucket="b", kafka_topic="t") + store = Mock() + store.put_object.side_effect = RuntimeError("down") + prod = Mock() + svc = IngestService(cfg, Deps(store, prod, DefaultClock(), DefaultIds())) + with pytest.raises(RuntimeError): + svc.process_image(make_info(), b"xxx") diff --git a/services/plant_stress/Dockerfile b/services/plant_stress/Dockerfile index 097ca9a18..d456611aa 100644 --- a/services/plant_stress/Dockerfile +++ b/services/plant_stress/Dockerfile @@ -1,90 +1,45 @@ -# FROM python:3.11-slim - -# ENV PYTHONDONTWRITEBYTECODE=1 \ -# PYTHONUNBUFFERED=1 - -# RUN apt-get update && apt-get install -y --no-install-recommends \ -# libsndfile1 ffmpeg gcc \ -# && rm -rf /var/lib/apt/lists/* - -# WORKDIR /app - -# # COPY certs /app/certs - -# # RUN if [ -f /app/certs/netfree-ca.crt ]; then \ -# # echo "Installing NetFree certificate..."; \ -# # cp /app/certs/netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt && \ -# # update-ca-certificates; \ -# # else \ -# # echo "⚠️ WARNING: netfree-ca.crt not found, continuing without it."; \ -# # fi - -# ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ -# REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ -# PIP_CERT=/etc/ssl/certs/ca-certificates.crt - -# COPY requirements.txt ./ -# RUN pip install --no-cache-dir -r requirements.txt \ -# --trusted-host pypi.org \ -# --trusted-host pypi.python.org \ -# --trusted-host files.pythonhosted.org - -# COPY src/ /app/ - -# ENV INPUT_DIR=/data/inbox \ -# MODEL_DIR=/models \ -# PERIOD_DAYS=7 \ -# CONF_THRESHOLD=0.0 \ -# POSTGRES_DSN="postgresql://postgres:pg123@host.docker.internal:5432/missions_db" - -# CMD ["python", "/app/app.py"] - FROM python:3.11-slim ENV PYTHONDONTWRITEBYTECODE=1 \ - PYTHONUNBUFFERED=1 + PYTHONUNBUFFERED=1 \ + TZ=Asia/Jerusalem RUN apt-get update && apt-get install -y --no-install-recommends \ - libsndfile1 ffmpeg tzdata \ + cron tzdata ca-certificates curl libsndfile1 ffmpeg \ && rm -rf /var/lib/apt/lists/* -WORKDIR /app +RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone -# COPY certs /app/certs +COPY certs/ /usr/local/share/ca-certificates/ -# RUN if [ -f /app/certs/netfree-ca.crt ]; then \ -# echo "Installing NetFree certificate..."; \ -# cp /app/certs/netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt && \ -# update-ca-certificates; \ -# else \ -# echo "⚠️ WARNING: netfree-ca.crt not found, continuing without it."; \ -# fi +RUN if find /usr/local/share/ca-certificates -maxdepth 1 -type f \ + \( -name '*.crt' -o -name '*.cer' -o -name '*.pem' \) \ + -print -quit | grep -q .; then \ + echo "Installing custom certificates from /usr/local/share/ca-certificates..."; \ + update-ca-certificates; \ + else \ + echo "No custom cert files found under /usr/local/share/ca-certificates, continuing without extra certificates."; \ + fi ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ - REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ - PIP_CERT=/etc/ssl/certs/ca-certificates.crt + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt + +WORKDIR /app -COPY requirements.txt ./ -RUN pip install --no-cache-dir -r requirements.txt \ - --trusted-host pypi.org \ - --trusted-host pypi.python.org \ - --trusted-host files.pythonhosted.org +COPY requirements.txt /app/requirements.txt +RUN pip install --no-cache-dir -r /app/requirements.txt -# Copy your source code -COPY src/ /app/ +COPY src /app/src +COPY models /models +ENV MODEL_DIR=/models -# Copy model files if needed -# COPY models/ /models/ +COPY cronjob /etc/cron.d/plant-stress-cron +COPY run_job.sh /app/run_job.sh +COPY entrypoint.sh /entrypoint.sh -ENV MODEL_DIR=/models \ - TIMEZONE=Asia/Jerusalem \ - MINIO_ENDPOINT=minio:9000 \ - MINIO_ACCESS_KEY=minioadmin \ - MINIO_SECRET_KEY=minioadmin123 \ - MINIO_BUCKET=sound \ - MINIO_PREFIX=plants/ \ - MINIO_SECURE=false \ - POSTGRES_DSN=postgresql://missions_user:pg123@postgres:5432/missions_db \ - CONFIDENCE_THRESHOLD=0.60 +RUN sed -i 's/\r$//' /etc/cron.d/plant-stress-cron /entrypoint.sh /app/run_job.sh \ + && chmod 0644 /etc/cron.d/plant-stress-cron \ + && chmod +x /entrypoint.sh /app/run_job.sh \ + && touch /var/log/cron.log -CMD ["python", "/app/predict_minio_daily.py"] +CMD ["/entrypoint.sh"] diff --git a/services/plant_stress/README.md b/services/plant_stress/README.md index e69de29bb..78a071d61 100644 --- a/services/plant_stress/README.md +++ b/services/plant_stress/README.md @@ -0,0 +1,12 @@ +# Plant Stress Daily Job +This service runs **once per day**. +It loads a pre-trained ML model, reads audio files from MinIO, predicts plant stress, writes results to PostgreSQL, **and if stress is detected, it sends an alert message to Kafka**. + + +--- + + +## Download Model Files +Download the required model files from: +https://drive.google.com/drive/folders/17iXRnP-a5_6wt_tS4ieLKkUlUlU5IhDT?usp=sharing +Place all files in a folder named **`AgCloud/services/plant_stress/models/`** in the project root. \ No newline at end of file diff --git a/services/plant_stress/cronjob b/services/plant_stress/cronjob new file mode 100644 index 000000000..de3cd28ab --- /dev/null +++ b/services/plant_stress/cronjob @@ -0,0 +1,4 @@ +SHELL=/bin/bash +PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin +CRON_TZ=Asia/Jerusalem +39 14 * * * root /app/run_job.sh >> /var/log/cron.log 2>&1 diff --git a/services/plant_stress/entrypoint.sh b/services/plant_stress/entrypoint.sh new file mode 100644 index 000000000..41727b16f --- /dev/null +++ b/services/plant_stress/entrypoint.sh @@ -0,0 +1,4 @@ +#!/usr/bin/env bash +set -euo pipefail +cron +tail -F /var/log/cron.log \ No newline at end of file diff --git a/services/plant_stress/run_job.sh b/services/plant_stress/run_job.sh new file mode 100644 index 000000000..f6de17b98 --- /dev/null +++ b/services/plant_stress/run_job.sh @@ -0,0 +1,6 @@ +#!/usr/bin/env bash +set -euo pipefail + +echo "[$(date -Iseconds)] [plant_stress_daily] starting job..." +python -u /app/src/predict_minio_daily.py +echo "[$(date -Iseconds)] [plant_stress_daily] finished job." diff --git a/services/plant_stress/src/predict_minio_daily.py b/services/plant_stress/src/predict_minio_daily.py index 24c6e7778..0345af93a 100644 --- a/services/plant_stress/src/predict_minio_daily.py +++ b/services/plant_stress/src/predict_minio_daily.py @@ -1,106 +1,199 @@ -import os, sys, time, pickle, datetime as dt +import os +import sys +import time +import pickle +import datetime as dt from pathlib import Path import re import uuid import json +from io import BytesIO + import numpy as np import librosa import tensorflow as tf -import psycopg2, psycopg2.extras +import psycopg2 +import psycopg2.extras import pytz -from io import BytesIO import soundfile as sf from minio import Minio # ======== Environment ======== -MODEL_DIR = os.getenv("MODEL_DIR", "/models") -POSTGRES_DSN = os.getenv("POSTGRES_DSN", "postgresql://postgres:postgres@localhost:5432/postgres") + +MODEL_DIR = os.getenv("MODEL_DIR", "/models") +POSTGRES_DSN = os.getenv( + "POSTGRES_DSN", + "postgresql://missions_user:pg123@postgres:5432/missions_db", +) # MinIO -MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "minio:9000") -MINIO_ACCESS = os.getenv("MINIO_ACCESS_KEY", "minioadmin") -MINIO_SECRET = os.getenv("MINIO_SECRET_KEY", "minioadmin123") -MINIO_BUCKET = os.getenv("MINIO_BUCKET", "sound") -MINIO_PREFIX = os.getenv("MINIO_PREFIX", "plants/") -MINIO_SECURE = os.getenv("MINIO_SECURE", "false").lower() == "true" - -# Defaults for required GUI fields +MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "minio-hot:9000") +MINIO_ACCESS = os.getenv("MINIO_ACCESS_KEY", "minioadmin") +MINIO_SECRET = os.getenv("MINIO_SECRET_KEY", "minioadmin123") +MINIO_BUCKET = os.getenv("MINIO_BUCKET", "sound") +MINIO_PREFIX = os.getenv("MINIO_PREFIX", "plants/") +MINIO_SECURE = os.getenv("MINIO_SECURE", "false").lower() == "true" + DEFAULT_AREA = os.getenv("DEFAULT_AREA", "unknown").strip() -DEFAULT_LAT = os.getenv("DEFAULT_LAT", "0.0").strip() -DEFAULT_LON = os.getenv("DEFAULT_LON", "0.0").strip() +DEFAULT_LAT = os.getenv("DEFAULT_LAT", "0.0").strip() +DEFAULT_LON = os.getenv("DEFAULT_LON", "0.0").strip() DEFAULT_IMAGE_URL = os.getenv("DEFAULT_IMAGE_URL", "https://example.com/placeholder.jpg").strip() -DEFAULT_VOD = os.getenv("DEFAULT_VOD", "https://example.com/placeholder.mp4").strip() -DEFAULT_HLS = os.getenv("DEFAULT_HLS", "https://example.com/placeholder.m3u8").strip() +DEFAULT_VOD = os.getenv("DEFAULT_VOD", "https://example.com/placeholder.mp4").strip() +DEFAULT_HLS = os.getenv("DEFAULT_HLS", "https://example.com/placeholder.m3u8").strip() + +# ======== Date / TZ ======== -# Date / TZ -TIMEZONE = os.getenv("TIMEZONE", "Asia/Jerusalem") -PROCESS_DATE = os.getenv("PROCESS_DATE", "").strip() # YYYY-MM-DD (optional backfill) +TIMEZONE = os.getenv("TIMEZONE", "Asia/Jerusalem") +PROCESS_DATE = os.getenv("PROCESS_DATE", "").strip() + +# ======== Confidence ======== -# Confidence CONFIDENCE_THRESHOLD = float(os.getenv("CONFIDENCE_THRESHOLD", "0.60")) -# ======== Audio Params (2ms @ 500kHz) ======== +# ======== Audio Params ======== + SAMPLE_RATE = 500_000 DURATION_MS = 2 -N_SAMPLES = int(SAMPLE_RATE * DURATION_MS / 1000) # 1000 samples -N_FFT = 256 -HOP_LENGTH = 64 -N_MELS = 64 +N_SAMPLES = SAMPLE_RATE * DURATION_MS // 1000 +N_FFT = 256 +HOP_LENGTH = 64 +N_MELS = 64 + +# ======== Status mapping ======== -# ======== Watering Status Mapping ======== CLASS_TO_STATUS = { - "Drought_Tomato": "Watering required", - "Drought_Tobacco": "Watering required", - "Control_Empty": "Normal / Empty", + "Drought_Tomato": "Watering required", + "Drought_Tobacco": "Watering required", + "Control_Empty": "Normal / Empty", "Control_Greenhouse": "Greenhouse noise / Normal", } -# ======== Alerts / Kafka ======== +# ======== Kafka ======== + ENABLE_ALERTS = os.getenv("ENABLE_ALERTS", "true").lower() == "true" -ALERT_TOPIC = os.getenv("ALERT_TOPIC", "alerts") -ALERT_TYPE = os.getenv("ALERT_TYPE", "plant_drought_detected") -ALERT_AREA = os.getenv("ALERT_AREA", "").strip() -ALERT_LAT = os.getenv("ALERT_LAT", "").strip() -ALERT_LON = os.getenv("ALERT_LON", "").strip() -ALERT_IMAGE_URL = os.getenv("ALERT_IMAGE_URL", "").strip() -ALERT_VOD = os.getenv("ALERT_VOD", "").strip() -ALERT_HLS = os.getenv("ALERT_HLS", "").strip() +ALERT_TOPIC = os.getenv("ALERT_TOPIC", "alerts") +ALERT_TYPE = os.getenv("ALERT_TYPE", "plant_drought_detected") + +ALERT_IMAGE_URL = os.getenv("ALERT_IMAGE_URL", "") +ALERT_VOD = os.getenv("ALERT_VOD", "") +ALERT_HLS = os.getenv("ALERT_HLS", "") KAFKA_BOOTSTRAP = os.getenv("KAFKA_BOOTSTRAP", "kafka:9092") KAFKA_CLIENT_ID = os.getenv("KAFKA_CLIENT_ID", "plant-stress-producer") -KAFKA_SECURITY_PROTOCOL = os.getenv("KAFKA_SECURITY_PROTOCOL", "").strip() -KAFKA_SASL_MECHANISM = os.getenv("KAFKA_SASL_MECHANISM", "").strip() -KAFKA_SASL_USERNAME = os.getenv("KAFKA_SASL_USERNAME", "").strip() -KAFKA_SASL_PASSWORD = os.getenv("KAFKA_SASL_PASSWORD", "").strip() -KAFKA_SSL_CA = os.getenv("KAFKA_SSL_CA", "").strip() -KAFKA_SSL_CERT = os.getenv("KAFKA_SSL_CERT", "").strip() -KAFKA_SSL_KEY = os.getenv("KAFKA_SSL_KEY", "").strip() - -# ======== Load model/scaler/encoder ======== -model_path = os.path.join(MODEL_DIR, "ultrasonic_plant_cnn.keras") -scaler_path = os.path.join(MODEL_DIR, "scaler_params.npz") -le_path = os.path.join(MODEL_DIR, "label_encoder.pkl") -print(f"MODEL_DIR={MODEL_DIR}") -print(f"POSTGRES_DSN={POSTGRES_DSN}") -print(f"MINIO {MINIO_ENDPOINT=} {MINIO_BUCKET=} {MINIO_PREFIX=} {MINIO_SECURE=}") -print(f"ALERTS enable={ENABLE_ALERTS} topic={ALERT_TOPIC} bootstrap={KAFKA_BOOTSTRAP}") +# ======== Load Model & Scaler ======== + +model_path = os.path.join(MODEL_DIR, "ultrasonic_plant_cnn.keras") +scaler_path = os.path.join(MODEL_DIR, "scaler_params.npz") +le_path = os.path.join(MODEL_DIR, "label_encoder.pkl") try: import keras MODEL = keras.saving.load_model(model_path, compile=False) -except Exception as e_keras3: - print(f"[!] Keras 3 load failed: {e_keras3} -- falling back to tf.keras") +except Exception: MODEL = tf.keras.models.load_model(model_path, compile=False) sc = np.load(scaler_path) -SCALER_MEAN = sc["mean"] +SCALER_MEAN = sc["mean"] SCALER_SCALE = sc["scale"] with open(le_path, "rb") as f: LABEL_ENCODER = pickle.load(f) -# ======== Kafka Producer (lazy, dual-impl) ======== +# ======== Filename Regex ======== + +FILENAME_RE = re.compile( + r"(?P[^/_]+)_(?P\d{8})T(?P\d{2})(?P\d{2})(?P\d{2})Z\.wav$", + re.IGNORECASE, +) + +def _tz(): + return pytz.timezone(TIMEZONE) + +def parse_from_name(key: str): + m = FILENAME_RE.search(key) + if not m: + return None, None + + sensor = m.group("sensor") + y = int(m.group("date")[0:4]) + mth = int(m.group("date")[4:6]) + d = int(m.group("date")[6:8]) + hh = int(m.group("hour")) + mm = int(m.group("minute")) + ss = int(m.group("second")) + + dt_local = _tz().localize(dt.datetime(y, mth, d, hh, mm, ss)) + return sensor, dt_local + +# ======== NEW FUNCTION ======== + +def get_meta_for_alert(conn, device_id: str, file_name: str): + area = None + lat = None + lon = None + + short = file_name.split("/")[-1] + + try: + with conn.cursor() as cur: + cur.execute(""" + SELECT + (gis_origin->>'area') AS area, + (gis_origin->>'latitude')::double precision AS lat, + (gis_origin->>'longitude')::double precision AS lon + FROM public.sounds_ultra_metadata + WHERE device_id = %s + AND file_name = %s + ORDER BY created_at DESC + LIMIT 1; + """, (device_id, short)) + row = cur.fetchone() + if row: + area, lat, lon = row + except Exception as e: + print(f"[meta] error from metadata: {e}") + + if area is None or lat is None or lon is None: + try: + with conn.cursor() as cur: + cur.execute(""" + SELECT owner, location_lat, location_lon + FROM public.devices + WHERE device_id = %s + LIMIT 1; + """, (device_id,)) + row = cur.fetchone() + if row: + owner, dlat, dlon = row + if area is None: + area = owner + if lat is None: + lat = dlat + if lon is None: + lon = dlon + except Exception as e: + print(f"[meta] error from devices: {e}") + + if area is None: + area = DEFAULT_AREA + if lat is None: + lat = float(DEFAULT_LAT) + if lon is None: + lon = float(DEFAULT_LON) + + return area, lat, lon +# ======== Kafka Producer (dual impl) ======== + +KAFKA_SECURITY_PROTOCOL = os.getenv("KAFKA_SECURITY_PROTOCOL", "").strip() +KAFKA_SASL_MECHANISM = os.getenv("KAFKA_SASL_MECHANISM", "").strip() +KAFKA_SASL_USERNAME = os.getenv("KAFKA_SASL_USERNAME", "").strip() +KAFKA_SASL_PASSWORD = os.getenv("KAFKA_SASL_PASSWORD", "").strip() +KAFKA_SSL_CA = os.getenv("KAFKA_SSL_CA", "").strip() +KAFKA_SSL_CERT = os.getenv("KAFKA_SSL_CERT", "").strip() +KAFKA_SSL_KEY = os.getenv("KAFKA_SSL_KEY", "").strip() + + class _KafkaProducer: def __init__(self): self.impl = None @@ -110,16 +203,30 @@ def __init__(self): def _init_producer(self): if not ENABLE_ALERTS: return + + # Try confluent-kafka try: from confluent_kafka import Producer - conf = {"bootstrap.servers": KAFKA_BOOTSTRAP, "client.id": KAFKA_CLIENT_ID} - if KAFKA_SECURITY_PROTOCOL: conf["security.protocol"] = KAFKA_SECURITY_PROTOCOL - if KAFKA_SASL_MECHANISM: conf["sasl.mechanisms"] = KAFKA_SASL_MECHANISM - if KAFKA_SASL_USERNAME: conf["sasl.username"] = KAFKA_SASL_USERNAME - if KAFKA_SASL_PASSWORD: conf["sasl.password"] = KAFKA_SASL_PASSWORD - if KAFKA_SSL_CA: conf["ssl.ca.location"] = KAFKA_SSL_CA - if KAFKA_SSL_CERT: conf["ssl.certificate.location"]= KAFKA_SSL_CERT - if KAFKA_SSL_KEY: conf["ssl.key.location"] = KAFKA_SSL_KEY + + conf: dict[str, object] = { + "bootstrap.servers": KAFKA_BOOTSTRAP, + "client.id": KAFKA_CLIENT_ID, + } + if KAFKA_SECURITY_PROTOCOL: + conf["security.protocol"] = KAFKA_SECURITY_PROTOCOL + if KAFKA_SASL_MECHANISM: + conf["sasl.mechanisms"] = KAFKA_SASL_MECHANISM + if KAFKA_SASL_USERNAME: + conf["sasl.username"] = KAFKA_SASL_USERNAME + if KAFKA_SASL_PASSWORD: + conf["sasl.password"] = KAFKA_SASL_PASSWORD + if KAFKA_SSL_CA: + conf["ssl.ca.location"] = KAFKA_SSL_CA + if KAFKA_SSL_CERT: + conf["ssl.certificate.location"] = KAFKA_SSL_CERT + if KAFKA_SSL_KEY: + conf["ssl.key.location"] = KAFKA_SSL_KEY + self.impl = Producer(conf) self.mode = "confluent" print("[Kafka] Using confluent-kafka Producer") @@ -127,23 +234,31 @@ def _init_producer(self): except Exception as e: print(f"[Kafka] confluent-kafka unavailable: {e}") + # Fallback: kafka-python try: from kafka import KafkaProducer - kwargs = { + + kwargs: dict[str, object] = { "bootstrap_servers": KAFKA_BOOTSTRAP, "client_id": KAFKA_CLIENT_ID, "value_serializer": lambda v: json.dumps(v).encode("utf-8"), "linger_ms": 10, "acks": "all", } - if KAFKA_SECURITY_PROTOCOL: kwargs["security_protocol"] = KAFKA_SECURITY_PROTOCOL - if KAFKA_SASL_MECHANISM: kwargs["sasl_mechanism"] = KAFKA_SASL_MECHANISM + if KAFKA_SECURITY_PROTOCOL: + kwargs["security_protocol"] = KAFKA_SECURITY_PROTOCOL + if KAFKA_SASL_MECHANISM: + kwargs["sasl_mechanism"] = KAFKA_SASL_MECHANISM if KAFKA_SASL_USERNAME and KAFKA_SASL_PASSWORD: kwargs["sasl_plain_username"] = KAFKA_SASL_USERNAME kwargs["sasl_plain_password"] = KAFKA_SASL_PASSWORD - if KAFKA_SSL_CA: kwargs["ssl_cafile"] = KAFKA_SSL_CA - if KAFKA_SSL_CERT: kwargs["ssl_certfile"] = KAFKA_SSL_CERT - if KAFKA_SSL_KEY: kwargs["ssl_keyfile"] = KAFKA_SSL_KEY + if KAFKA_SSL_CA: + kwargs["ssl_cafile"] = KAFKA_SSL_CA + if KAFKA_SSL_CERT: + kwargs["ssl_certfile"] = KAFKA_SSL_CERT + if KAFKA_SSL_KEY: + kwargs["ssl_keyfile"] = KAFKA_SSL_KEY + self.impl = KafkaProducer(**kwargs) self.mode = "kafka-python" print("[Kafka] Using kafka-python Producer") @@ -152,9 +267,10 @@ def _init_producer(self): self.impl = None self.mode = None - def send(self, topic: str, value: dict): + def send(self, topic: str, value: dict) -> bool: if not ENABLE_ALERTS or self.impl is None: return False + if self.mode == "confluent": try: self.impl.produce(topic, value=json.dumps(value).encode("utf-8")) @@ -171,6 +287,7 @@ def send(self, topic: str, value: dict): except Exception as e: print(f"[Kafka] produce error (kafka-python): {e}") return False + return False def flush(self): @@ -182,222 +299,287 @@ def flush(self): except Exception: pass + KAFKA_PRODUCER = _KafkaProducer() -# ======== Helpers ======== -FILENAME_RE = re.compile( - r'(?P[^/_]+)_(?P\d{4}-\d{2}-\d{2})_(?P\d{2})-(?P\d{2})\.wav$', - re.IGNORECASE -) -def _tz(): - return pytz.timezone(TIMEZONE) - -def _today_date(): +def _today_date() -> dt.date: if PROCESS_DATE: return dt.datetime.strptime(PROCESS_DATE, "%Y-%m-%d").date() return dt.datetime.now(_tz()).date() -def parse_from_name(key: str): - """ - mic1_2025-09-03_12-05.wav -> (sensor_id, aware-local-datetime) or (None, None) - """ - m = FILENAME_RE.search(key) - if not m: - return None, None - sensor = m.group("sensor") - y, mon, dd = map(int, m.group("date").split("-")) - hh = int(m.group("hour")); mm = int(m.group("minute")) - local_dt = _tz().localize(dt.datetime(y, mon, dd, hh, mm, 0)) - return sensor, local_dt -def list_minio_wavs_for_date(client: Minio, bucket: str, prefix: str, the_date: dt.date): +# ======== MinIO listing & audio loading ======== + +def list_minio_wavs_for_date( + client: Minio, bucket: str, prefix: str, the_date: dt.date +): selected = [] for obj in client.list_objects(bucket, prefix=prefix, recursive=True): key = obj.object_name if not key.lower().endswith(".wav"): continue + sensor, rec_local = parse_from_name(key) - if rec_local is not None: - if rec_local.date() == the_date: - selected.append((obj, sensor, rec_local)) + if rec_local is not None and rec_local.date() == the_date: + selected.append((obj, sensor, rec_local)) continue + lm_local = obj.last_modified.astimezone(_tz()) if lm_local.date() == the_date: selected.append((obj, sensor, lm_local)) + return selected + def load_audio_from_minio(client: Minio, bucket: str, key: str): resp = client.get_object(bucket, key) try: data = resp.read() finally: - resp.close(); resp.release_conn() + resp.close() + resp.release_conn() + bio = BytesIO(data) audio, sr = sf.read(bio, dtype="float32", always_2d=False) + if isinstance(audio, np.ndarray) and audio.ndim == 2: audio = audio.mean(axis=1) + if sr != SAMPLE_RATE: audio = librosa.resample(audio, orig_sr=sr, target_sr=SAMPLE_RATE) sr = SAMPLE_RATE + if len(audio) > N_SAMPLES: start = (len(audio) - N_SAMPLES) // 2 audio = audio[start:start + N_SAMPLES] elif len(audio) < N_SAMPLES: pad = N_SAMPLES - len(audio) - audio = np.pad(audio, (0, pad), mode='constant') + audio = np.pad(audio, (0, pad), mode="constant") + return audio.astype(np.float32), sr + +# ======== Feature extraction ======== + def extract_ultrasonic_features(audio: np.ndarray, sr: int): - feats = [] - feats.extend([np.mean(audio), np.std(audio), np.max(audio), np.min(audio), - np.var(audio), np.median(audio)]) + feats: list[float] = [] + + feats.extend( + [ + float(np.mean(audio)), + float(np.std(audio)), + float(np.max(audio)), + float(np.min(audio)), + float(np.var(audio)), + float(np.median(audio)), + ] + ) + zcr = librosa.feature.zero_crossing_rate(audio, hop_length=HOP_LENGTH)[0] - feats.extend([np.mean(zcr), np.std(zcr), np.max(zcr)]) - fft = np.abs(np.fft.fft(audio))[:len(audio)//2] - feats.extend([np.mean(fft), np.std(fft), np.max(fft), np.argmax(fft)]) + feats.extend( + [ + float(np.mean(zcr)), + float(np.std(zcr)), + float(np.max(zcr)), + ] + ) + + fft = np.abs(np.fft.fft(audio))[: len(audio) // 2] + feats.extend( + [ + float(np.mean(fft)), + float(np.std(fft)), + float(np.max(fft)), + float(np.argmax(fft)), + ] + ) + try: - sc = librosa.feature.spectral_centroid(y=audio, sr=sr, hop_length=HOP_LENGTH)[0] - ro = librosa.feature.spectral_rolloff(y=audio, sr=sr, hop_length=HOP_LENGTH)[0] - feats.extend([np.mean(sc), np.mean(ro)]) + sc = librosa.feature.spectral_centroid( + y=audio, sr=sr, hop_length=HOP_LENGTH + )[0] + ro = librosa.feature.spectral_rolloff( + y=audio, sr=sr, hop_length=HOP_LENGTH + )[0] + feats.extend([float(np.mean(sc)), float(np.mean(ro))]) except Exception: feats.extend([0.0, 0.0]) + rms = librosa.feature.rms(y=audio, hop_length=HOP_LENGTH)[0] - feats.extend([np.mean(rms), np.std(rms)]) + feats.extend( + [ + float(np.mean(rms)), + float(np.std(rms)), + ] + ) + return np.array(feats, dtype=np.float32) + def create_spectrogram_features(audio: np.ndarray, sr: int): mel = librosa.feature.melspectrogram( - y=audio, sr=sr, n_fft=N_FFT, hop_length=HOP_LENGTH, - n_mels=N_MELS, fmax=sr//2 + y=audio, + sr=sr, + n_fft=N_FFT, + hop_length=HOP_LENGTH, + n_mels=N_MELS, + fmax=sr // 2, ) - mel_db = librosa.power_to_db(mel, ref=np.max) + mel_db = librosa.power_to_db(mel, ref=np.max) mel_norm = (mel_db - mel_db.min()) / (mel_db.max() - mel_db.min() + 1e-8) return mel_norm.astype(np.float32) + def normalize_features(x: np.ndarray): return (x - SCALER_MEAN) / SCALER_SCALE -# ======== DB ======== +# ======== DB: Tables & Inserts ======== + def ensure_predictions_table(conn): - """Match your schema exactly: no sensor_id, no recording_time.""" + """ + Create ultrasonic_plant_predictions (no device_id/recording_time). + """ with conn.cursor() as cur: cur.execute(""" - CREATE TABLE IF NOT EXISTS ultrasonic_plant_predictions ( - id BIGSERIAL PRIMARY KEY, - file TEXT, - predicted_class TEXT, - confidence DOUBLE PRECISION, - watering_status TEXT, - status TEXT, - prediction_time TIMESTAMPTZ DEFAULT now() - ); + CREATE TABLE IF NOT EXISTS ultrasonic_plant_predictions ( + id BIGSERIAL PRIMARY KEY, + file TEXT, + predicted_class TEXT, + confidence DOUBLE PRECISION, + watering_status TEXT, + status TEXT, + prediction_time TIMESTAMPTZ DEFAULT now() + ); """) - cur.execute("CREATE INDEX IF NOT EXISTS idx_upp_pred_time ON ultrasonic_plant_predictions(prediction_time DESC);") - cur.execute("CREATE INDEX IF NOT EXISTS idx_upp_class ON ultrasonic_plant_predictions(predicted_class);") + cur.execute( + "CREATE INDEX IF NOT EXISTS idx_upp_pred_time ON ultrasonic_plant_predictions (prediction_time DESC);" + ) + cur.execute( + "CREATE INDEX IF NOT EXISTS idx_upp_class ON ultrasonic_plant_predictions (predicted_class);" + ) conn.commit() + def ensure_alerts_table(conn): + """ + Create alerts table + updated_at trigger + """ with conn.cursor() as cur: cur.execute(""" - CREATE TABLE IF NOT EXISTS alerts ( - alert_id TEXT PRIMARY KEY, - alert_type TEXT, - device_id TEXT, - started_at TIMESTAMPTZ, - ended_at TIMESTAMPTZ, - confidence DOUBLE PRECISION, - area TEXT, - lat DOUBLE PRECISION, - lon DOUBLE PRECISION, - severity INT DEFAULT 1, - image_url TEXT, - vod TEXT, - hls TEXT, - ack BOOLEAN DEFAULT FALSE, - meta JSONB, - created_at TIMESTAMPTZ DEFAULT now(), - updated_at TIMESTAMPTZ DEFAULT now() - ); + CREATE TABLE IF NOT EXISTS alerts ( + alert_id TEXT PRIMARY KEY, + alert_type TEXT, + device_id TEXT, + started_at TIMESTAMPTZ, + ended_at TIMESTAMPTZ, + confidence DOUBLE PRECISION, + area TEXT, + lat DOUBLE PRECISION, + lon DOUBLE PRECISION, + severity INT DEFAULT 1, + image_url TEXT, + vod TEXT, + hls TEXT, + ack BOOLEAN DEFAULT FALSE, + meta JSONB, + created_at TIMESTAMPTZ DEFAULT now(), + updated_at TIMESTAMPTZ DEFAULT now() + ); """) + + # Trigger for updated_at cur.execute(""" - DO $$ - BEGIN - IF NOT EXISTS (SELECT 1 FROM pg_proc WHERE proname = 'set_updated_at') THEN - CREATE OR REPLACE FUNCTION set_updated_at() RETURNS trigger AS $f$ + DO $$ BEGIN - NEW.updated_at = now(); - RETURN NEW; - END; - $f$ LANGUAGE plpgsql; - END IF; - END$$; + IF NOT EXISTS (SELECT 1 FROM pg_proc WHERE proname = 'set_updated_at') THEN + CREATE OR REPLACE FUNCTION set_updated_at() RETURNS trigger AS $f$ + BEGIN + NEW.updated_at = now(); + RETURN NEW; + END; + $f$ LANGUAGE plpgsql; + END IF; + END$$; """) + cur.execute(""" - DO $$ - BEGIN - IF NOT EXISTS (SELECT 1 FROM pg_trigger WHERE tgname = 'trg_alerts_updated_at') THEN - CREATE TRIGGER trg_alerts_updated_at - BEFORE UPDATE ON alerts - FOR EACH ROW - EXECUTE PROCEDURE set_updated_at(); - END IF; - END$$; + DO $$ + BEGIN + IF NOT EXISTS (SELECT 1 FROM pg_trigger WHERE tgname = 'trg_alerts_updated_at') THEN + CREATE TRIGGER trg_alerts_updated_at + BEFORE UPDATE ON alerts + FOR EACH ROW + EXECUTE PROCEDURE set_updated_at(); + END IF; + END$$; """) + conn.commit() + def insert_prediction_rows(conn, rows): """ - rows: iterable of tuples shaped exactly as the table: - (file, predicted_class, confidence, watering_status, status, prediction_time) + rows: List of tuples (file, predicted_class, confidence, + watering_status, status, prediction_time) """ sql = """ - INSERT INTO ultrasonic_plant_predictions - (file, predicted_class, confidence, watering_status, status, prediction_time) - VALUES %s + INSERT INTO ultrasonic_plant_predictions + (file, predicted_class, confidence, watering_status, status, prediction_time) + VALUES %s """ with conn.cursor() as cur: psycopg2.extras.execute_values(cur, sql, rows, page_size=500) conn.commit() -def insert_alert_row(conn, alert: dict, started_at_dt: dt.datetime, ended_at_dt: dt.datetime | None = None, ack: bool = False): + +def insert_alert_row(conn, alert: dict, + started_at_dt: dt.datetime, + ended_at_dt: dt.datetime | None = None, + ack: bool = False): from psycopg2.extras import Json + sql = """ - INSERT INTO alerts ( - alert_id, alert_type, device_id, started_at, ended_at, - confidence, area, lat, lon, severity, - image_url, vod, hls, ack, meta - ) - VALUES ( - %(alert_id)s, %(alert_type)s, %(device_id)s, %(started_at)s, %(ended_at)s, - %(confidence)s, %(area)s, %(lat)s, %(lon)s, %(severity)s, - %(image_url)s, %(vod)s, %(hls)s, %(ack)s, %(meta)s - ) - ON CONFLICT (alert_id) DO UPDATE - SET updated_at = now() + INSERT INTO alerts ( + alert_id, alert_type, device_id, started_at, ended_at, + confidence, area, lat, lon, severity, + image_url, vod, hls, ack, meta + ) + VALUES ( + %(alert_id)s, %(alert_type)s, %(device_id)s, + %(started_at)s, %(ended_at)s, + %(confidence)s, %(area)s, %(lat)s, %(lon)s, %(severity)s, + %(image_url)s, %(vod)s, %(hls)s, %(ack)s, %(meta)s + ) + ON CONFLICT (alert_id) + DO UPDATE SET updated_at = now() """ + params = { - "alert_id": alert["alert_id"], + "alert_id": alert["alert_id"], "alert_type": alert.get("alert_type"), - "device_id": alert.get("device_id"), + "device_id": alert.get("device_id"), "started_at": started_at_dt, - "ended_at": ended_at_dt, + "ended_at": ended_at_dt, "confidence": alert.get("confidence"), - "area": alert.get("area"), - "lat": alert.get("lat"), - "lon": alert.get("lon"), - "severity": alert.get("severity"), - "image_url": alert.get("image_url"), - "vod": alert.get("vod"), - "hls": alert.get("hls"), - "ack": ack, - "meta": Json(alert.get("meta", {})), + "area": alert.get("area"), + "lat": alert.get("lat"), + "lon": alert.get("lon"), + "severity": alert.get("severity"), + "image_url": alert.get("image_url"), + "vod": alert.get("vod"), + "hls": alert.get("hls"), + "ack": ack, + "meta": Json(alert.get("meta", {})), } + with conn.cursor() as cur: cur.execute(sql, params) conn.commit() -# ======== Alert helpers ======== + +# ======== Severity ======== + def _severity_from_confidence(conf: float) -> int: if conf >= 0.95: return 5 if conf >= 0.90: return 4 @@ -405,41 +587,43 @@ def _severity_from_confidence(conf: float) -> int: if conf >= 0.70: return 2 return 1 -def _iso_utc(dt_aware) -> str: + +def _iso_utc(dt_aware): return dt_aware.astimezone(pytz.UTC).strftime("%Y-%m-%dT%H:%M:%SZ") + +# ======== Build Alert Payload (NOW USING DB META) ======== + def build_alert_payload( alert_type: str, device_id: str, started_at_utc: dt.datetime, confidence: float, s3url: str, - area: str = "", - lat: str = "", - lon: str = "", + area: str | None, + lat: float | None, + lon: float | None, image_url: str = "", vod: str = "", hls: str = "", extra_meta: dict | None = None, ) -> dict: - def _to_float_or_default(v, default_s: str): - try: - if v is None or (isinstance(v, str) and v.strip() == ""): - return float(default_s) - return float(v) - except Exception: - return float(default_s) - def _non_empty(value: str, default_value: str) -> str: - v = (value or "").strip() - return v if v else default_value + # Backups only if missing + final_area = area if area else DEFAULT_AREA + try: + final_lat = float(lat) if lat is not None else float(DEFAULT_LAT) + except: + final_lat = float(DEFAULT_LAT) - area_f = _non_empty(area, DEFAULT_AREA) - lat_f = _to_float_or_default(lat, DEFAULT_LAT) - lon_f = _to_float_or_default(lon, DEFAULT_LON) - image_f = _non_empty(image_url, DEFAULT_IMAGE_URL) - vod_f = _non_empty(vod, DEFAULT_VOD) - hls_f = _non_empty(hls, DEFAULT_HLS) + try: + final_lon = float(lon) if lon is not None else float(DEFAULT_LON) + except: + final_lon = float(DEFAULT_LON) + + image_f = image_url if image_url else DEFAULT_IMAGE_URL + vod_f = vod if vod else DEFAULT_VOD + hls_f = hls if hls else DEFAULT_HLS payload = { "alert_id": str(uuid.uuid4()), @@ -448,9 +632,9 @@ def _non_empty(value: str, default_value: str) -> str: "started_at": _iso_utc(started_at_utc), "confidence": round(confidence, 6), "severity": _severity_from_confidence(confidence), - "area": area_f, - "lat": lat_f, - "lon": lon_f, + "area": final_area, + "lat": final_lat, + "lon": final_lon, "image_url": image_f, "vod": vod_f, "hls": hls_f, @@ -459,21 +643,34 @@ def _non_empty(value: str, default_value: str) -> str: "file": s3url, }, } + if extra_meta: payload["meta"].update(extra_meta) + return payload -# ======== Main ======== +# ======== MAIN PROCESSING LOOP ======== + def main(): the_date = _today_date() print(f"[i] Processing MinIO objects for date={the_date} (TZ={TIMEZONE})") - client = Minio(MINIO_ENDPOINT, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) + # MinIO client + client = Minio( + MINIO_ENDPOINT, + access_key=MINIO_ACCESS, + secret_key=MINIO_SECRET, + secure=MINIO_SECURE + ) + + # List WAV files objs = list_minio_wavs_for_date(client, MINIO_BUCKET, MINIO_PREFIX, the_date) + if not objs: - print("No WAV objects for that date. Exiting.") + print("[i] No WAV files for this date. Exiting.") return 0 + # DB try: conn = psycopg2.connect(POSTGRES_DSN) ensure_alerts_table(conn) @@ -483,59 +680,77 @@ def main(): return 2 batch = [] - ok, fail = 0, 0 + ok = 0 + fail = 0 t0 = time.time() + # Process each file for (obj, sensor, rec_local_dt) in objs: key = obj.object_name s3url = f"s3://{MINIO_BUCKET}/{key}" + try: + # If parsing didn't get sensor -> extract from file name if sensor is None: sensor, _ = parse_from_name(key) if sensor is None: sensor = key.split("/")[-1].split("_")[0] + # ===== Load audio ===== audio, sr = load_audio_from_minio(client, MINIO_BUCKET, key) - feats = extract_ultrasonic_features(audio, sr) - spec = create_spectrogram_features(audio, sr) + # ===== Compute features ===== + feats = extract_ultrasonic_features(audio, sr) + spec = create_spectrogram_features(audio, sr) feats_norm = normalize_features(feats) + feats_batch = feats_norm[np.newaxis, :] - spec_batch = spec[np.newaxis, ..., np.newaxis] + spec_batch = spec[np.newaxis, ..., np.newaxis] + # ===== Prediction ===== probs = MODEL.predict([feats_batch, spec_batch], verbose=0)[0] - idx = int(np.argmax(probs)) + idx = int(np.argmax(probs)) pred_class = LABEL_ENCODER.classes_[idx] - conf = float(probs[idx]) + conf = float(probs[idx]) watering_status = CLASS_TO_STATUS.get(pred_class, "Undefined") if conf < CONFIDENCE_THRESHOLD: watering_status = f"{watering_status} (Uncertain)" - # Save prediction row (schema: no sensor_id/recording_time) + # Save prediction row batch.append(( - s3url, # file - str(pred_class), # predicted_class - conf, # confidence - watering_status, # watering_status - "Success", # status + s3url, + pred_class, + conf, + watering_status, + "Success", dt.datetime.utcnow() )) ok += 1 - print(f"OK {s3url} [{sensor} @ {rec_local_dt.isoformat()}] -> {pred_class} ({conf:.3f})") - # Alerts for drought classes + print(f"[OK] {s3url} -> {pred_class} ({conf:.3f}) [{sensor}]") + + # ===== ALERTS ===== if ENABLE_ALERTS and pred_class in ("Drought_Tomato", "Drought_Tobacco"): - rec_utc = rec_local_dt.astimezone(pytz.UTC) if rec_local_dt.tzinfo else pytz.UTC.localize(rec_local_dt) + # normalize time to UTC + rec_utc = ( + rec_local_dt.astimezone(pytz.UTC) + if rec_local_dt.tzinfo + else pytz.UTC.localize(rec_local_dt) + ) + + # Load area/lat/lon from DB metadata or devices + area_db, lat_db, lon_db = get_meta_for_alert(conn, str(sensor), key) + alert = build_alert_payload( alert_type=ALERT_TYPE, device_id=str(sensor), started_at_utc=rec_utc, confidence=conf, s3url=s3url, - area=ALERT_AREA, - lat=ALERT_LAT, - lon=ALERT_LON, + area=area_db, # ← from DB + lat=lat_db, # ← from DB + lon=lon_db, # ← from DB image_url=ALERT_IMAGE_URL, vod=ALERT_VOD, hls=ALERT_HLS, @@ -548,56 +763,60 @@ def main(): "n_mels": N_MELS } ) + try: insert_alert_row(conn, alert, started_at_dt=rec_utc, ended_at_dt=None, ack=False) - print(f"[Alert][DB] upsert alert_id={alert['alert_id']} device={alert['device_id']} severity={alert['severity']}") + print(f"[Alert][DB] inserted alert_id={alert['alert_id']} device={sensor} severity={alert['severity']}") except Exception as e: print(f"[Alert][DB] insert failed: {e}") - # Send to Kafka (best effort) + # Kafka send (optional) try: - ok_send = KAFKA_PRODUCER.send(ALERT_TOPIC, alert) - if ok_send: - print(f"[Alert] sent to topic={ALERT_TOPIC}: {alert['alert_id']}") + sent = KAFKA_PRODUCER.send(ALERT_TOPIC, alert) + if sent: + print(f"[Alert][Kafka] sent alert_id={alert['alert_id']}") else: - print(f"[Alert] FAILED to send alert to topic={ALERT_TOPIC}") + print(f"[Alert][Kafka] FAILED sending alert") except Exception as e: - print(f"[Alert] send exception: {e}") + print(f"[Alert][Kafka] send exception: {e}") except Exception as e: fail += 1 print(f"[ERR] {s3url} -> {e}") batch.append(( - s3url, # file - "", # predicted_class - None, # confidence - "", # watering_status - f"Error: {e}", # status + s3url, + "", + None, + "", + f"Error: {e}", dt.datetime.utcnow() )) + # Insert prediction batch try: if batch: insert_prediction_rows(conn, batch) - print(f"Inserted {len(batch)} rows.") + print(f"[i] Inserted {len(batch)} prediction rows.") except Exception as e: - print(f"[!] Insert error: {e}") + print(f"[!] Error inserting predictions: {e}") return 3 - finally: - try: - conn.close() - except: - pass + + # Close DB + try: + conn.close() + except: + pass # Flush Kafka try: KAFKA_PRODUCER.flush() - except Exception: + except: pass dt_sec = time.time() - t0 print(f"Done. processed={len(objs)} ok={ok} fail={fail} elapsed_sec={dt_sec:.1f}") return 0 + if __name__ == "__main__": sys.exit(main()) diff --git a/services/ripeness-baseline/.env b/services/ripeness-baseline/.env deleted file mode 100644 index 32c2f7c3b..000000000 --- a/services/ripeness-baseline/.env +++ /dev/null @@ -1,10 +0,0 @@ -PGHOST=localhost -PGPORT=5432 -PGDATABASE=missions_db -PGUSER=missions_user - -PGPASSWORD=pg123 - -SAMPLES_DIR=./samples -# FRUIT_TYPE=apple -LOOKBACK_DAYS=7 diff --git a/services/ripeness-baseline/deploy/certs/corp-root.crt b/services/ripeness-baseline/deploy/certs/corp-root.crt deleted file mode 100644 index 228d8b91e..000000000 --- a/services/ripeness-baseline/deploy/certs/corp-root.crt +++ /dev/null @@ -1,23 +0,0 @@ ------BEGIN CERTIFICATE----- -MIIDwzCCAqugAwIBAgIJAJvSq+oh8F6+MA0GCSqGSIb3DQEBCwUAMHgxCzAJBgNV -BAYTAklMMQ8wDQYDVQQIDAZpc3JhZWwxEjAQBgNVBAcMCUplcnVzYWxlbTEQMA4G -A1UECgwHTmV0RnJlZTEVMBMGA1UECwwMbmV0ZnJlZS5saW5rMRswGQYDVQQDDBJO -ZXRGcmVlIFNpZ24gLCAwMTkwHhcNMTYwNDIxMTAyNzA1WhcNMjYwMjI4MTAyNzA1 -WjB4MQswCQYDVQQGEwJJTDEPMA0GA1UECAwGaXNyYWVsMRIwEAYDVQQHDAlKZXJ1 -c2FsZW0xEDAOBgNVBAoMB05ldEZyZWUxFTATBgNVBAsMDG5ldGZyZWUubGluazEb -MBkGA1UEAwwSTmV0RnJlZSBTaWduICwgMDE5MIIBIjANBgkqhkiG9w0BAQEFAAOC -AQ8AMIIBCgKCAQEA5Wq8zAqW7KGANXfbg9Ck8rx4nPjSkerlSPS/yNEVa/L8HulD -q/GVMRaPaL+RqI4GQt6LeQAmj1FZS01rQQITNRsg6MhNrPhENhg48rjFNIxuEnMv -IfydKGGU2mFXcMtQ9IoRSe4OYE3CKDG0pYzfXhh+TW0H4KKqjO6mjPmMcNjbstpK -vOPFg6Xu5em6hvtQCKC0V551WKWmNQiHOpwRdVIdbWBv3S5xiO5tZVigGpEJ1gLe -8W+Zn2ozcpvh+m38QSZ0A1DVP5Te/7q9L3+BPub8kz3C6GnNK547ucM5HBmOzNwN -luZHVUsehCLc0I965Wd4ZRUXXeeo7BibjRI6mQIDAQABo1AwTjAdBgNVHQ4EFgQU -tLpJD3JS6YPg7VQl2gKrPJByEycwHwYDVR0jBBgwFoAUtLpJD3JS6YPg7VQl2gKr -PJByEycwDAYDVR0TBAUwAwEB/zANBgkqhkiG9w0BAQsFAAOCAQEAThhIvkN/HsFG -7jaHl8yyH3IyvHX+LrItJyhRaQ4xALzGllGCLWvN15e2SWITdXncd4nMU7VRVG1k -CiX6H55Jh1U/DmZHmUI2HBhf/2liFNKXKDOeHg4u+FIzgzuIc0z+RvwPpw9IVLio -Pe6lbaIc5+80kO/mwJwQZoEaqTyL1Ujn69cosiZpiYF3xtxkfBWEWe7XkLunLqqV -DoMEGMq+MUxO+Jngv0j/7dSi1/1eovNnrV4YeF2Flvq2xY1aCKO/cocv5v7w5wEm -8fMFQwKcT7QcCx+/nkx3r0tDHxO7og7xr8petCK+ULqwL28ha4U0l+kLF0ZRiG5H -Ni6Hj6Oi9A== ------END CERTIFICATE----- diff --git a/services/ripeness-baseline/eval/apple_argmax/confusion_matrix.png b/services/ripeness-baseline/eval/apple_argmax/confusion_matrix.png deleted file mode 100644 index 7bb489f5c..000000000 Binary files a/services/ripeness-baseline/eval/apple_argmax/confusion_matrix.png and /dev/null 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73c713113..000000000 Binary files a/services/ripeness-baseline/eval/orange_test/confusion_matrix.png and /dev/null differ diff --git a/services/ripeness-baseline/eval/orange_tuned/confusion_matrix.png b/services/ripeness-baseline/eval/orange_tuned/confusion_matrix.png deleted file mode 100644 index 4b4789c31..000000000 Binary files a/services/ripeness-baseline/eval/orange_tuned/confusion_matrix.png and /dev/null differ diff --git a/services/ripeness_exporter/Dockerfile b/services/ripeness_exporter/Dockerfile new file mode 100644 index 000000000..a2e91e0f9 --- /dev/null +++ b/services/ripeness_exporter/Dockerfile @@ -0,0 +1,10 @@ +FROM python:3.12-slim + +WORKDIR /app + +COPY requirements.txt /app/ +RUN pip install --no-cache-dir -r requirements.txt + +COPY ripeness_exporter.py /app/ + +CMD ["python", "ripeness_exporter.py"] diff --git a/services/ripeness_exporter/requirements.txt b/services/ripeness_exporter/requirements.txt new file mode 100644 index 000000000..416c12aa4 --- /dev/null +++ b/services/ripeness_exporter/requirements.txt @@ -0,0 +1,2 @@ +prometheus_client +psycopg2-binary diff --git a/services/ripeness_exporter/ripeness_exporter.py b/services/ripeness_exporter/ripeness_exporter.py new file mode 100644 index 000000000..60f42215b --- /dev/null +++ b/services/ripeness_exporter/ripeness_exporter.py @@ -0,0 +1,165 @@ +#!/usr/bin/env python3 +import time +import psycopg2 +from prometheus_client import start_http_server, Gauge +import signal +import sys + +# ====== CONFIG ====== +DB_HOST = "postgres" +DB_PORT = 5432 +DB_USER = "missions_user" +DB_PASS = "pg123" +DB_NAME = "missions_db" + +SCRAPE_INTERVAL = 30 # seconds +THRESHOLD_TASK = "ripeness" +THRESHOLD_LABEL = "" # empty label as defined +PROMETHEUS_PORT = 9128 + +# ====== METRICS ====== + +# Ripeness weekly rollups +g_pct = Gauge("fruit_ripeness_pct", "Weekly ripeness pct (0-1)", ["device"]) +g_cnt_ripe = Gauge("fruit_ripeness_cnt_ripe", "Count ripe", ["device"]) +g_cnt_unripe = Gauge("fruit_ripeness_cnt_unripe", "Count unripe", ["device"]) +g_cnt_overripe = Gauge("fruit_ripeness_cnt_overripe", "Count overripe", ["device"]) +g_cnt_total = Gauge("fruit_ripeness_cnt_total", "Total fruits counted", ["device"]) + +# Threshold + alert state (based on rollup) +g_alert_state = Gauge("fruit_ripeness_alert_state", "1 if below threshold", ["device"]) +g_threshold = Gauge("fruit_ripeness_threshold", "Ripeness threshold global") + +# ====== NEW ALERT METRICS (From alerts table) ====== + +g_alerts_total = Gauge( + "fruit_ripeness_alerts_total", + "Total number of ripeness alerts for a device", + ["device"] +) + +g_alert_last_pct = Gauge( + "fruit_ripeness_alert_last_pct", + "pct_ripe from the last ripeness alert", + ["device"] +) + +g_alert_active = Gauge( + "fruit_ripeness_alert_active", + "1 if device currently has a ripeness alert (based on alerts table)", + ["device"] +) + + +# ====== DB CONNECT ====== +def get_conn(): + return psycopg2.connect( + host=DB_HOST, + port=DB_PORT, + user=DB_USER, + password=DB_PASS, + dbname=DB_NAME, + ) + + +# ====== MAIN LOOP ====== +def run_loop(): + while True: + try: + conn = get_conn() + cur = conn.cursor() + + # ======================= + # FETCH threshold + # ======================= + cur.execute(""" + SELECT threshold + FROM task_thresholds + WHERE task = %s AND label = %s + LIMIT 1; + """, (THRESHOLD_TASK, THRESHOLD_LABEL)) + row = cur.fetchone() + threshold = float(row[0]) if row else 0.75 + g_threshold.set(threshold) + + # ======================= + # FETCH latest weekly rollups + # ======================= + cur.execute(""" + SELECT device_id, pct_ripe, cnt_ripe, cnt_unripe, + cnt_overripe, cnt_total + FROM ripeness_weekly_rollups_ts + WHERE window_end = ( + SELECT MAX(window_end) + FROM ripeness_weekly_rollups_ts + ); + """) + rows = cur.fetchall() + + for device_id, pct, c_r, c_u, c_o, c_t in rows: + dev = device_id or "unknown" + + # SET rollup metrics + g_pct.labels(dev).set(pct) + g_cnt_ripe.labels(dev).set(c_r) + g_cnt_unripe.labels(dev).set(c_u) + g_cnt_overripe.labels(dev).set(c_o) + g_cnt_total.labels(dev).set(c_t) + + # SET alert state from rollup + alert_state = 1 if pct < threshold else 0 + g_alert_state.labels(dev).set(alert_state) + + # ======================= + # ALERTS TABLE → Prometheus + # ======================= + + # 1) Count alerts + cur.execute(""" + SELECT COUNT(*) + FROM alerts + WHERE alert_type LIKE 'ripeness%%' + AND device_id = %s; + """, (dev,)) + alert_count = cur.fetchone()[0] + g_alerts_total.labels(dev).set(alert_count) + + # 2) Last alert pct_ripe + cur.execute(""" + SELECT meta->>'pct_ripe' + FROM alerts + WHERE alert_type LIKE 'ripeness%%' + AND device_id = %s + ORDER BY started_at DESC + LIMIT 1; + """, (dev,)) + last_alert = cur.fetchone() + + if last_alert and last_alert[0] is not None: + g_alert_last_pct.labels(dev).set(float(last_alert[0])) + g_alert_active.labels(dev).set(1) + else: + g_alert_last_pct.labels(dev).set(0) + g_alert_active.labels(dev).set(0) + + cur.close() + conn.close() + + except Exception as e: + print("ERROR:", e) + + time.sleep(SCRAPE_INTERVAL) + + +def shutdown(sig, frame): + print("Shutting down exporter...") + sys.exit(0) + + +if __name__ == "__main__": + signal.signal(signal.SIGINT, shutdown) + signal.signal(signal.SIGTERM, shutdown) + + print(f"Starting Prometheus exporter on port {PROMETHEUS_PORT} ...") + start_http_server(PROMETHEUS_PORT) + run_loop() diff --git a/services/security/.dockerignore b/services/security/.dockerignore new file mode 100644 index 000000000..139597f9c --- /dev/null +++ b/services/security/.dockerignore @@ -0,0 +1,2 @@ + + diff --git a/services/security/.gitignore b/services/security/.gitignore new file mode 100644 index 000000000..092b0f3d7 --- /dev/null +++ b/services/security/.gitignore @@ -0,0 +1,60 @@ +# ---- Python cache / build artefacts ---- +__pycache__/ +*.py[cod] +*$py.class + +# Distribution / packaging +build/ +dist/ +*.egg-info/ +.eggs/ + +# Virtual environments +.venv/ +venv/ +env/ +ENV/ +.conda/ +*.conda +*.ipynb_checkpoints + +# PyInstaller / py2exe artefacts +*.manifest +*.spec + +# Unit test / coverage reports +.pytest_cache/ +.coverage +coverage.xml +htmlcov/ +.tox/ +.nox/ +.mypy_cache/ +.dmypy.json +.pyre/ +.pytype/ + +# Logs +*.log + +# IDE / editor settings +.vscode/ +.idea/ +*.swp +*.swo + +# OS generated files +.DS_Store +Thumbs.db +desktop.ini + +# Jupyter notebooks (if you create some later) +.ipynb_checkpoints/ + +# Temporary files +*.tmp +*.bak +*.orig + + + diff --git a/services/security/README.md b/services/security/README.md new file mode 100644 index 000000000..e178059e1 --- /dev/null +++ b/services/security/README.md @@ -0,0 +1,58 @@ +# AgGuard Model Weights + +This directory contains the model weight files required for the AgGuard Security service. + +The weights **are not stored in Git** because they are large. +You must download them manually from Google Drive and place them directly in this folder. + +--- + +## 📥 1. Download Model Weights + +Download the following files from our shared Google Drive folder: + +🔗 **Google Drive (AgGuard Models)** +https://drive.google.com/drive/u/0/folders/1Qu7F4eG2XcINoUWFZt-1qpBQmRiPECPG + +Files you should download: + +``` +mask_yolov8.onnx +yolov8n-cls.pt +``` + +--- + +## 📁 2. Copy Files Into This Folder + +After downloading, copy BOTH files into: + +``` +services/security/weights/ +``` + +The final structure must look exactly like this: + +``` +services/security/weights/ +│ +├── mask_yolov8.onnx +└── yolov8n-cls.pt +``` + +No subfolders. +No renaming. + +--- + +## ⚠️ Important + +- Do **not** commit these files to Git. +- Do **not** rename the files. +- Anytime a new or updated weight is added to Google Drive, download it again and replace it here. + +--- + +## ❓ Need help? + +Ask Yehudit or the AgGuard developers if you are unsure about any of the required weight files. diff --git a/services/security/agguard/__init__.py b/services/security/agguard/__init__.py new file mode 100644 index 000000000..883256898 --- /dev/null +++ b/services/security/agguard/__init__.py @@ -0,0 +1,9 @@ +# __all__ = [ +# "logging_utils", +# "types", +# "roi", +# "motion", +# "detector", +# "tracker", +# "dispatch", +# ] diff --git a/services/security/agguard/adapters/__init__.py b/services/security/agguard/adapters/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/adapters/s3_client.py b/services/security/agguard/adapters/s3_client.py new file mode 100644 index 000000000..905bca200 --- /dev/null +++ b/services/security/agguard/adapters/s3_client.py @@ -0,0 +1,107 @@ +from __future__ import annotations +from dataclasses import dataclass +from typing import Optional +import cv2, numpy as np +import botocore +import boto3 +from botocore.config import Config as BotoConfig + +@dataclass(frozen=True) +class S3Config: + # For AWS S3 you usually set only region_name; credentials come from env/role. + region_name: str = "us-east-1" + # Optional explicit creds (otherwise rely on IAM role, env vars, or shared config) + aws_access_key_id: Optional[str] = None + aws_secret_access_key: Optional[str] = None + aws_session_token: Optional[str] = None + + # Optional: only if you still want to talk to a non-AWS S3-compatible endpoint (e.g., MinIO) + endpoint_url: Optional[str] = None + # Optional knobs + connect_timeout: float = 3.0 + read_timeout: float = 10.0 + max_attempts: int = 3 # boto retries on transient errors + + +class S3Client: + def __init__(self, cfg: S3Config): + self.cfg = cfg + boto_cfg = BotoConfig( + region_name=cfg.region_name, + s3={"addressing_style": "path"}, # AWS default + retries={"max_attempts": cfg.max_attempts, "mode": "standard"}, + connect_timeout=cfg.connect_timeout, + read_timeout=cfg.read_timeout, + # s3={"addressing_style": "path"}, + ) + session = boto3.Session( + aws_access_key_id=cfg.aws_access_key_id, + aws_secret_access_key=cfg.aws_secret_access_key, + aws_session_token=cfg.aws_session_token, + region_name=cfg.region_name, + ) + self.s3 = session.client("s3", endpoint_url=cfg.endpoint_url, config=boto_cfg) + + def fetch_image_bgr(self, bucket: str, object_key: str) -> np.ndarray: + """GET s3://bucket/object_key and decode as BGR numpy image.""" + try: + resp = self.s3.get_object(Bucket=bucket, Key=object_key) + data: bytes = resp["Body"].read() + except self.s3.exceptions.NoSuchKey: + raise FileNotFoundError(f"s3://{bucket}/{object_key} not found (NoSuchKey)") + except self.s3.exceptions.NoSuchBucket: + raise FileNotFoundError(f"s3://{bucket} does not exist (NoSuchBucket)") + except botocore.exceptions.EndpointConnectionError as e: + raise RuntimeError(f"S3 endpoint unreachable: {e}") + except botocore.exceptions.ClientError as e: + # surface 403/404/etc with context + code = e.response.get("Error", {}).get("Code") + msg = e.response.get("Error", {}).get("Message") + raise RuntimeError(f"S3 get_object failed ({code}): {msg}") from e + + arr = np.frombuffer(data, dtype=np.uint8) + img = cv2.imdecode(arr, cv2.IMREAD_COLOR) + if img is None: + raise ValueError(f"Failed to decode image bytes from s3://{bucket}/{object_key}") + return img + # add inside class S3Client: + + def put_file(self, bucket: str, key: str, local_path: str, content_type: Optional[str] = None) -> None: + extra = {"ContentType": content_type} if content_type else {} + self.s3.upload_file(local_path, bucket, key, ExtraArgs=extra or None) + + def delete_object(self, bucket: str, key: str) -> None: + self.s3.delete_object(Bucket=bucket, Key=key) + + def delete_prefix(self, bucket: str, prefix: str) -> None: + # batch delete up to 1000 keys per call + token = None + while True: + resp = self.s3.list_objects_v2(Bucket=bucket, Prefix=prefix, ContinuationToken=token) \ + if token else self.s3.list_objects_v2(Bucket=bucket, Prefix=prefix) + contents = resp.get("Contents", []) + if contents: + objects = [{"Key": obj["Key"]} for obj in contents] + self.s3.delete_objects(Bucket=bucket, Delete={"Objects": objects}) + if resp.get("IsTruncated"): + token = resp.get("NextContinuationToken") + else: + break + + + def get_object_stream(self, bucket: str, key: str, range_header: Optional[str] = None): + """Return boto3 get_object response (Body is a stream).""" + params = {"Bucket": bucket, "Key": key} + print(params) + if range_header: + params["Range"] = range_header + return self.s3.get_object(**params) + + # in agguard/adapters/s3_client.py + def put_bytes(self, bucket: str, key: str, data: bytes, content_type: str = "application/octet-stream"): + import io + bio = io.BytesIO(data) + self.client.upload_fileobj(bio, bucket, key, ExtraArgs={"ContentType": content_type}) + + + diff --git a/services/security/agguard/app/Dockerfile b/services/security/agguard/app/Dockerfile new file mode 100644 index 000000000..c7a526983 --- /dev/null +++ b/services/security/agguard/app/Dockerfile @@ -0,0 +1,22 @@ +FROM python:3.12-slim + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 + +# Install basic dependencies +RUN apt-get update && apt-get install -y --no-install-recommends \ + libglib2.0-0 libgl1 ca-certificates curl \ + && rm -rf /var/lib/apt/lists/* + +# Copy app +WORKDIR /app +COPY agguard/app/requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt + +COPY agguard ./agguard +COPY configs ./configs + +EXPOSE 8080 +HEALTHCHECK CMD curl -f http://localhost:8080/ || exit 1 + +CMD ["uvicorn", "agguard.app.media_proxy:app", "--host", "0.0.0.0", "--port", "8080"] diff --git a/services/security/agguard/app/__init__.py b/services/security/agguard/app/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/app/media_proxy.py b/services/security/agguard/app/media_proxy.py new file mode 100644 index 000000000..43311b564 --- /dev/null +++ b/services/security/agguard/app/media_proxy.py @@ -0,0 +1,232 @@ +# agguard/app/media_proxy.py +from __future__ import annotations +import os, re, mimetypes +from typing import Optional +from fastapi import FastAPI, Header, HTTPException, Request +from botocore.exceptions import ClientError +from fastapi.responses import Response, StreamingResponse +import yaml + +from agguard.adapters.s3_client import S3Client, S3Config + +app = FastAPI(title="AgGuard Media Proxy", version="1.0") + +# ---------- load config ---------- +CFG_PATH = os.getenv("AGGUARD_CFG", "/app/configs/default.yaml") +with open(CFG_PATH, "r", encoding="utf-8") as f: + _cfg = yaml.safe_load(f) or {} + +_s3cfg = _cfg.get("s3", {}) or {} +_vcfg = _cfg.get("video", {}) or {} +BUCKET = _vcfg.get("bucket") +PREFIX = (_vcfg.get("prefix") or "security/incidents").strip("/") + +if not BUCKET: + raise RuntimeError("video.bucket is not configured in your YAML (configs/default.yaml)") + +s3 = S3Client(S3Config( + region_name=_s3cfg.get("region_name", "us-east-1"), + aws_access_key_id=_s3cfg.get("aws_access_key_id"), + aws_secret_access_key=_s3cfg.get("aws_secret_access_key"), + aws_session_token=_s3cfg.get("aws_session_token"), + endpoint_url=_s3cfg.get("endpoint_url"), + connect_timeout=float(_s3cfg.get("connect_timeout", 3.0)), + read_timeout=float(_s3cfg.get("read_timeout", 10.0)), + max_attempts=int(_s3cfg.get("max_attempts", 3)), +)) + +MEDIA_AUTH_TOKEN = os.getenv("MEDIA_AUTH_TOKEN") or _cfg.get("media_auth_token") # optional + +_M3U8_CT = "application/vnd.apple.mpegurl" +_TS_CT = "video/MP2T" +_MP4_CT = "video/mp4" + +SAFE_NAME = re.compile(r"^[A-Za-z0-9_.-]+$") # prevent path traversal + +def _require_auth(req: Request) -> None: + """Simple Bearer check. If MEDIA_AUTH_TOKEN unset, auth is disabled (dev).""" + print("in") + if not MEDIA_AUTH_TOKEN: + return + auth = req.headers.get("Authorization", "") + if auth.lower().startswith("bearer "): + token = auth[7:].strip() + else: + token = None + if token != MEDIA_AUTH_TOKEN: + print("unauthorazied") + raise HTTPException(status_code=401, detail="Unauthorized") + +def _ct_for_name(name: str) -> str: + if name.endswith(".m3u8"): return _M3U8_CT + if name.endswith(".ts"): return _TS_CT + if name.endswith(".mp4"): return _MP4_CT + if name.endswith(".m4s"): return _MP4_CT + return mimetypes.guess_type(name)[0] or "application/octet-stream" + +def _object_key_for_hls(camera: str, incident: str, name: str) -> str: + # e.g., security/incidents///segment_00001.ts + return f"{PREFIX}/{camera}/{incident}/{name}" + + + + +import time +from botocore.exceptions import ClientError + +def _exists(bucket: str, key: str) -> bool: + try: + s3.head_object(bucket, key) # implement head_object in your S3Client + return True + except Exception: + return False + +def _wait_for_key(bucket: str, key: str, timeout=3.0, interval=0.2) -> bool: + t0 = time.time() + while time.time() - t0 < timeout: + if _exists(bucket, key): + return True + time.sleep(interval) + return False + +@app.get("/hls/{camera}/{incident}/index.m3u8") +def get_playlist(camera: str, incident: str, request: Request): + _require_auth(request) + names = ["index.m3u8", "master.m3u8", "playlist.m3u8"] + for name in names: + key = _object_key_for_hls(camera, incident, name) + print("key: ",key) + if True:#_wait_for_key(BUCKET, key, timeout=8.0, interval=0.2): + # print(key) + obj = s3.get_object_stream(BUCKET, key) + body = obj["Body"].read() + return Response( + content=body, + media_type=_M3U8_CT, + headers={ + "Cache-Control": "no-store, must-revalidate", + "Pragma": "no-cache", + }, + ) + raise HTTPException(status_code=404, detail="playlist not found (not ready)") + +# ---------- SEGMENTS (and CMAF init.mp4) ---------- +@app.get("/hls/{camera}/{incident}/{name}") +def get_segment(camera: str, incident: str, name: str, request: Request, range: Optional[str] = Header(default=None)): + _require_auth(request) + if "/" in name or ".." in name or not SAFE_NAME.match(name): + raise HTTPException(status_code=400, detail="bad segment name") + key = _object_key_for_hls(camera, incident, name) + try: + obj = s3.get_object_stream(BUCKET, key, range_header=range) + except Exception: + raise HTTPException(status_code=404, detail="segment not found") + + headers = {"Accept-Ranges": "bytes", "Content-Type": _ct_for_name(name)} + status = 200 + cr = obj.get("ContentRange") or obj.get("Content-Range") + if cr: + headers["Content-Range"] = cr + status = 206 + return StreamingResponse(obj["Body"].iter_chunks(), headers=headers, status_code=status, media_type=headers["Content-Type"]) +# ---------- FINAL MP4 (VOD) ---------- +@app.get("/vod/{camera}/{incident}/final.mp4") +def get_final_mp4( + camera: str, + incident: str, + request: Request, + range: Optional[str] = Header(default=None) +): + _require_auth(request) + key = _object_key_for_hls(camera, incident, "final.mp4") + + + + try: + obj = s3.get_object_stream(BUCKET, key, range_header=range) + + except ClientError as e: + code = e.response["Error"]["Code"] + + # File NOT found → real 404 + if code in ("NoSuchKey", "404"): + raise HTTPException(status_code=404, detail="VOD not found") + + # VLC requests ranges beyond file end → MUST return 416, NOT 404 + if code == "InvalidRange": + raise HTTPException(status_code=416, detail="Invalid Range") + + # Any other S3 problem is a server issue + raise HTTPException(status_code=502, detail=f"S3 error: {code}") + + # Non-S3 exceptions (timeout, disconnect, etc.) + except Exception as e: + raise HTTPException(status_code=502, detail=f"Internal proxy error: {type(e).__name__}") + + + body = obj["Body"] + content_length = obj.get("ContentLength") + content_range = obj.get("ContentRange") or obj.get("Content-Range") + + headers = { + "Accept-Ranges": "bytes", + "Content-Type": _MP4_CT, + } + + # Important for VLC + if "ContentLength" in obj: + headers["Content-Length"] = str(obj["ContentLength"]) + + + status = 200 + if content_range: + headers["Content-Range"] = content_range + status = 206 + if content_length and status == 200: + headers["Content-Length"] = str(content_length) + + # --- SAFE STREAMING GENERATOR --- + def stream_body(): + try: + while True: + chunk = body.read(256 * 1024) + + # S3 can return b'' BEFORE true EOF → retry once + if chunk == b"": + more = body.read(256 * 1024) + if more == b"": + break + yield more + continue + + if not chunk: + break + + yield chunk + + except Exception as e: + print("[MEDIA_PROXY][STREAM ERROR]", e) + + return StreamingResponse( + stream_body(), + headers=headers, + status_code=status, + media_type=_MP4_CT, + ) + +@app.get("/img/{camera}/{incident}/{filename}") +def get_image(camera: str, incident: str, filename: str, request: Request): + _require_auth(request) + if "/" in filename or ".." in filename or not SAFE_NAME.match(filename): + raise HTTPException(status_code=400, detail="bad filename") + + key = f"{PREFIX}/{camera}/{incident}/{filename}" + try: + obj = s3.get_object_stream(BUCKET, key) + except Exception: + raise HTTPException(status_code=404, detail="image not found") + + mime = _ct_for_name(filename) + headers = {"Cache-Control": "no-store, must-revalidate"} + return StreamingResponse(obj["Body"].iter_chunks(), headers=headers, media_type=mime) + diff --git a/services/security/agguard/app/requirements.txt b/services/security/agguard/app/requirements.txt new file mode 100644 index 000000000..df7b90ec6 --- /dev/null +++ b/services/security/agguard/app/requirements.txt @@ -0,0 +1,17 @@ +fastapi==0.115.2 +uvicorn[standard]==0.32.0 + +# AWS SDK for S3 access +boto3==1.35.29 +botocore==1.35.29 + +# Streaming + YAML parsing +PyYAML==6.0.2 + +# Optional: for your adapters +requests>=2.32.3 + +# If S3Client uses aiohttp for async streams +aiohttp>=3.10.5 + +opencv-python-headless<5 diff --git a/services/security/agguard/core/__init__.py b/services/security/agguard/core/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/core/events/__init__.py b/services/security/agguard/core/events/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/core/events/aggregator.py b/services/security/agguard/core/events/aggregator.py new file mode 100644 index 000000000..01150e869 --- /dev/null +++ b/services/security/agguard/core/events/aggregator.py @@ -0,0 +1,698 @@ +# agguard/events/aggregator.py +from __future__ import annotations +from typing import Dict, List, Tuple, Optional, Any +from dataclasses import dataclass, field +import uuid, datetime as _dt +import cv2, numpy as np, time, threading + +from .models import Rule, Incident, Box +from agguard.media.hls_recorder import HlsRecorder, HlsConfig +from agguard.media.mp4_recorder import Mp4Recorder +import logging +log = logging.getLogger(__name__) + + +@dataclass +class IncidentEvent: + opened_incident_id: str | None = None + updated_incident_id: str | None = None + closed_incident_id: str | None = None + opened_data: Optional[Any] = None + closed_data: Optional[Any] = None + + +@dataclass +class _EventState: + consec: int = 0 + cooldown_left: int = 0 + open_incident: Optional[Incident] = None + last_seen_frame: int = -1 + last_seen_ts: float = 0.0 + + # detections for the *current* frame (for record_frame): list of dicts + # {"x1": int, "y1": int, "x2": int, "y2": int, "conf": float|None} + detections: List[Dict[str, Any]] = field(default_factory=list) + + # For severity = mean tracks per frame during the incident + total_tracks: int = 0 + total_frames: int = 0 + subject: Optional[str] = None + + +def _iou(a: Box, b: Box) -> float: + x1, y1, x2, y2 = a + X1, Y1, X2, Y2 = b + ix1, iy1 = max(x1, X1), max(y1, Y1) + ix2, iy2 = min(x2, X2), min(y2, Y2) + inter = max(0, ix2 - ix1) * max(0, iy2 - iy1) + union = (x2 - x1) * (y2 - y1) + (X2 - X1) * (Y2 - Y1) - inter + return inter / max(union, 1e-6) + + +def _clamp_box(box: Box, w: int, h: int) -> Box: + x1, y1, x2, y2 = box + x1 = max(0, min(w - 1, int(x1))) + y1 = max(0, min(h - 1, int(y1))) + x2 = max(0, min(w - 1, int(x2))) + y2 = max(0, min(h - 1, int(y2))) + if x2 < x1: + x1, x2 = x2, x1 + if y2 < y1: + y1, y2 = y2, y1 + return (x1, y1, x2, y2) + + +class IncidentAggregator: + """ + Aggregates evidence PER (camera_id, rule.name). + Computes severity as mean tracks per frame. + Persists ALL detections (bbox+conf) per frame in a single DB row. + """ + + def __init__( + self, + rules: List[Rule], + camera_id: Optional[str] = None, + roi_pixels: Optional[List[Tuple[int, int]]] = None, + assoc_iou: float = 0.3, + sample_every: int = 1, + s3=None, video_bucket=None, video_prefix="security/incidents", + fps=12, hls_segment_time=3.0, hls_list_size=20, hls_use_cmaf=False, + draw_thickness=2, media_base: Optional[str] = None, media_token: Optional[str] = None + ): + + self.rules = rules + self.camera_id = camera_id + self.roi_pixels = roi_pixels + self.assoc_iou = float(assoc_iou) + self.sample_every = int(sample_every) + # key: (camera_id, rule.name) -> _EventState + self._states: Dict[Tuple[str, str], _EventState] = {} + self.s3 = s3 + self.video_bucket = video_bucket + self.video_prefix = video_prefix.strip("/") + self.fps = int(max(1, fps)) + self._hls_cfg = HlsConfig( + fps=self.fps, segment_time=hls_segment_time, list_size=hls_list_size, + use_cmaf=hls_use_cmaf, preset="veryfast", crf=23, gop_segments=2, upload_interval_sec=0.25 + ) + self.draw_thickness = int(max(1, draw_thickness)) + + self.media_base = (media_base or "").rstrip("/") + self.media_token = media_token or "" + + # helper for drawing (add this method inside the class) + def _render_frame_with_boxes(self, frame_bgr, dets): + out = frame_bgr.copy() + t = self.draw_thickness + for d in dets or []: + x1, y1, x2, y2 = int(d["x1"]), int(d["y1"]), int(d["x2"]), int(d["y2"]) + cv2.rectangle(out, (x1, y1), (x2, y2), (0, 255, 0), t) + tid = d.get("track_id") + if tid is not None: + cv2.putText( + out, + str(tid), + (x1, max(0, y1 - 5)), + cv2.FONT_HERSHEY_SIMPLEX, + 0.5, + (0, 255, 0), + 1, + cv2.LINE_AA, + ) + return out + + # helper to compute s3 prefix + def _hls_prefix(self, inc): + cam = self.camera_id or "unknown" + return f"{self.video_prefix}/{cam}/{inc.incident_id}" + + # ------------- convenience setters ------------- + + def set_camera(self, camera_id: Optional[str]) -> None: + self.camera_id = camera_id + + def set_roi_pixels(self, roi_pixels: Optional[List[Tuple[int, int]]]) -> None: + self.roi_pixels = roi_pixels + + # ------------- internals ------------- + + def _key(self, rule: Rule) -> Tuple[str, str]: + cam = self.camera_id or "unknown" + return (cam, rule.name) + + def _state(self, rule: Rule) -> _EventState: + k = self._key(rule) + if k not in self._states: + self._states[k] = _EventState() + return self._states[k] + + @staticmethod + def _class_match(t_cls: Any, rule: Rule) -> bool: + """ + True if track class matches rule by name or id (if provided). + If rule doesn't restrict class, accept all. + """ + t_name = str(t_cls).lower() + by_name = (rule.target_cls and t_name == str(rule.target_cls).lower()) + by_id = (rule.target_cls_id is not None and str(t_cls) == str(rule.target_cls_id)) + return bool(by_name or by_id) if (rule.target_cls or rule.target_cls_id is not None) else True + + def _match_classes(self, rule: Rule, preds: List) -> bool: + """ + Return True if any prediction class name matches one of rule.match_classes. + Includes detailed debug logging for diagnosis. + """ + if not preds: + log.info("[_match_classes] ⚠️ No predictions passed for rule '%s'", rule.name) + return False + + classes = [c.lower().strip() for c in (rule.match_classes or [])] + if not classes: + log.info("[_match_classes] 🟢 Rule '%s' has empty match_classes → treating as always True", rule.name) + return True + + log.info( + "[_match_classes] 🔍 Evaluating rule='%s' | match_classes=%s | min_conf=%.2f", + rule.name, + classes, + float(rule.min_conf or 0.0), + ) + + matched = False + for idx, p in enumerate(preds): + try: + # Handle dict-style predictions + if isinstance(p, dict): + cls_name = str( + p.get("label") or p.get("cls") or p.get("class_name") or "" + ).strip().lower() + conf = float(p.get("confidence", p.get("conf", 0.0))) + # Handle object-style (protobuf / custom) + elif hasattr(p, "label") or hasattr(p, "cls") or hasattr(p, "class_name"): + cls_name = str( + getattr(p, "label", getattr(p, "cls", getattr(p, "class_name", ""))) + ).strip().lower() + conf = float(getattr(p, "confidence", getattr(p, "conf", 0.0))) + else: + log.warning("[_match_classes] 🚫 Unsupported prediction type %s → skipping", type(p)) + continue + + log.info("[_match_classes] • Pred #%d → label='%s' conf=%.3f", idx, cls_name, conf) + + # Check confidence + if conf < float(rule.min_conf or 0.0): + log.info( + "[_match_classes] ↳ below min_conf=%.2f → SKIP", + float(rule.min_conf or 0.0), + ) + continue + + # Check class match + for c in classes: + if c == cls_name: + log.info("[_match_classes] ✅ EXACT MATCH '%s' for rule '%s'", cls_name, rule.name) + matched = True + break + elif c in cls_name or cls_name in c: + log.info( + "[_match_classes] ⚡ PARTIAL MATCH '%s' ~ '%s' for rule '%s'", + cls_name, + c, + rule.name, + ) + matched = True + break + + except Exception as e: + log.exception("[_match_classes] ❌ Error parsing prediction #%d: %s", idx, e) + + if not matched: + log.info( + "[_match_classes] ❌ No matches found for rule '%s'. Predictions checked: %d", + rule.name, + len(preds), + ) + + return matched + + # ------------- HLS deletion scheduler ------------- + + def _schedule_hls_deletion(self, hls_recorder, delay_sec: float = 120.0) -> None: + """ + Delete HLS content after a delay (default 2 minutes), in a background thread. + """ + if not hls_recorder: + return + + def _worker(): + try: + log.info( + "[_schedule_hls_deletion] Sleeping %.1f seconds before deleting HLS...", + delay_sec, + ) + time.sleep(delay_sec) + + try: + hls_recorder.delete_remote_hls() + except Exception as e: + log.exception("[_schedule_hls_deletion] remote delete error: %s", e) + + try: + hls_recorder.delete_hls_files_only() + except Exception as e: + log.exception("[_schedule_hls_deletion] local delete error: %s", e) + + log.info("[_schedule_hls_deletion] HLS cleanup finished.") + except Exception as e: + log.exception("[_schedule_hls_deletion] Unexpected error: %s", e) + + threading.Thread(target=_worker, daemon=True).start() + + # ------------- open / close incidents ------------- + + def _open_incident( + self, + st: _EventState, + rule: Rule, + ts_sec: float, + frame_idx: int, + frame_bgr, + ) -> dict: + log.info( + "[_open_incident] Opening new incident for rule '%s' at frame %d ts=%.3f", + rule.name, + frame_idx, + ts_sec, + ) + inc = Incident( + incident_id=str(uuid.uuid4()), + kind=rule.name, + camera_id=self.camera_id, + started_ts=ts_sec, + frame_start=frame_idx, + roi=self.roi_pixels, + severity=getattr(rule, "severity", 0), + ) + st.open_incident = inc + st.cooldown_left = int(rule.cooldown) + st.total_tracks = 0 + st.total_frames = 0 + + # Start HLS recorder immediately (so index.m3u8 appears fast) + if self.s3 and self.video_bucket: + # --- Live HLS recorder --- + st._hls = HlsRecorder( + s3=self.s3, + bucket=self.video_bucket, + prefix=self._hls_prefix(inc), + cfg=self._hls_cfg, + ) + H, W = frame_bgr.shape[:2] + st._hls.start((H, W)) + st._hls.write_bgr(self._render_frame_with_boxes(frame_bgr, st.detections)) + + # --- MP4 recorder (for final video only) --- + st._mp4 = Mp4Recorder( + s3=self.s3, + bucket=self.video_bucket, + prefix=self._hls_prefix(inc), + cfg=self._hls_cfg, + ) + st._mp4.start((H, W)) + st._mp4.write_bgr(self._render_frame_with_boxes(frame_bgr, st.detections)) + + # Only notify external world once the playlist definitely exists + if self.media_base and hasattr(st, "_hls") and st._hls: + log.info("[_open_incident] Waiting for playlist readiness...") + st._hls.wait_ready(timeout=6.0) # usually quick (first segment_time) + camera = inc.camera_id + incident_id = inc.incident_id + hls_url = f"{camera}/{incident_id}/index.m3u8" + vod_url = f"{camera}/{incident_id}/final.mp4" + anomaly = inc.kind or "unknown" + sev = "info" + log.info( + "[_open_incident] Sending alert to Alertmanager for incident_id=%s hls_url=%s", + incident_id, + hls_url, + ) + else: + hls_url = None + vod_url = None + + opened_data = { + "incident_id": inc.incident_id, + "camera_id": inc.camera_id, + "kind": rule.name, + "ts_iso": _dt.datetime.utcfromtimestamp(ts_sec).isoformat() + "Z", + "frame_start": frame_idx, + "roi": self.roi_pixels, + "severity": getattr(rule, "severity", 0), + "hls": hls_url, + "subject": getattr(st, "subject", None), + } + return opened_data + + def _close_incident( + self, + key: Tuple[str, str], + st: _EventState, + ts_sec: float, + frame_idx: int, + ) -> dict: + inc = st.open_incident + if not inc: + log.info("[_close_incident] No open incident to close for key=%s", key) + return + + log.info("[_close_incident] Closing incident %s (rule=%s)", inc.incident_id, key[1]) + + inc.ended_ts = ts_sec + inc.frame_end = frame_idx + inc.duration_sec = max(0.0, inc.ended_ts - inc.started_ts) + + # severity = mean tracks per frame during the incident + severity = round(float(st.total_tracks) / max(st.total_frames, 1)) + log.info( + "[_close_incident] Computed severity=%.3f (tracks=%d frames=%d)", + severity, + st.total_tracks, + st.total_frames, + ) + + mp4_key = None + + if self.s3 and self.video_bucket and hasattr(st, "_hls") and st._hls: + try: + log.info( + "[_close_incident] Finalizing HLS to MP4 for incident_id=%s", + inc.incident_id, + ) + + if st._hls: + try: + # 1️⃣ Stop ffmpeg FIRST — always + st._hls.stop() + log.info( + "[DEBUG] ffmpeg alive? %s", + st._hls._proc and st._hls._proc.poll() is None, + ) + + time.sleep(0.2) + + # 2️⃣ Finalize MP4 — now safe + mp4_key = st._mp4.finalize() if hasattr(st, "_mp4") and st._mp4 else None + log.info( + "[_close_incident] finalize_to_mp4() returned mp4_key=%s", + mp4_key, + ) + + # 3️⃣ Schedule HLS deletion in 2 minutes + self._schedule_hls_deletion(st._hls, delay_sec=120.0) + + except Exception as e: + log.exception("[_close_incident] Cleanup error: %s", e) + except Exception as e: + log.exception("[_close_incident] Error finalizing MP4: %s", e) + else: + log.info( + "[_close_incident] Skipping MP4 finalization — missing s3/video_bucket or no _hls" + ) + + # Reset state for this (camera, rule) + self._states[key] = _EventState() + + closed_data = { + "incident_id": inc.incident_id, + "kind": inc.kind, + "ended_at_iso": _dt.datetime.utcfromtimestamp(ts_sec).isoformat() + "Z", + "ts_iso": _dt.datetime.utcfromtimestamp(inc.started_ts).isoformat() + "Z", + "duration_sec": inc.duration_sec, + "frame_end": frame_idx, + "severity": inc.severity + severity, + "vod": f"{inc.camera_id}/{inc.incident_id}/final.mp4", + "subject": getattr(st, "subject", None), + } + return closed_data + + # ------------- public API ------------- + + def update( + self, + frame_idx: int, + ts_sec: float, + frame_bgr, + tracks: List, + outputs: Dict[str, List], + ) -> IncidentEvent: + """ + Evaluate evidence per (camera_id, rule). Maintain incident state. + Also captures ALL detections (bbox + conf) for record_frame(). + Returns IncidentEvent to signal opens/updates/closes to the caller. + """ + log.info( + "[update] frame_idx=%d ts=%.3f num_tracks=%d num_outputs=%d", + frame_idx, + ts_sec, + len(tracks), + len(outputs or {}), + ) + + H, W = frame_bgr.shape[:2] + by_cls = outputs or {} + evt = IncidentEvent() + + for rule in self.rules: + # Only skip 'intruding animal' if climbing_fence truly matched + if rule.name == "intruding animal": + cf_preds = by_cls.get("climbing_fence", []) + climbing_rule = next( + (r for r in self.rules if r.name == "climbing_fence"), + None, + ) + + if climbing_rule and self._match_classes(climbing_rule, cf_preds): + log.info( + "[update] Valid climbing_fence detected → suppressing intruding animal." + ) + continue + + log.info( + "[update] Evaluating rule '%s' (target_cls=%s cooldown=%s)", + rule.name, + getattr(rule, "target_cls", None), + getattr(rule, "cooldown", None), + ) + + candidate_tracks = [t for t in tracks if self._class_match(t.cls, rule)] + preds = by_cls.get(rule.name, []) or by_cls.get(rule.target_cls, []) + + st = self._state(rule) + + # 🧠 Prefer subject propagated from "intruding animal" (via outputs["_subject"]) + if "_subject" in outputs and outputs["_subject"]: + st.subject = outputs["_subject"][0] # e.g. "bear" + conf_val = None # no confidence value for propagated subject + log.info( + "[update] 🐾 Propagated subject from intruding animal: %s", + st.subject, + ) + + # 🐾 Otherwise, derive subject from current rule's predictions + elif preds: + best_pred = max( + preds, + key=lambda p: getattr( + p, + "confidence", + p.get("confidence", 0.0) if isinstance(p, dict) else 0.0, + ), + ) + + if isinstance(best_pred, dict): + st.subject = best_pred.get("label") + conf_val = best_pred.get("confidence", 0.0) + else: + st.subject = getattr(best_pred, "label", None) + conf_val = getattr(best_pred, "confidence", 0.0) + + log.info( + "[update] 🐾 Subject detected for rule '%s': %s (conf=%.2f)", + rule.name, + st.subject, + conf_val, + ) + else: + st.subject = None + conf_val = 0.0 + + log.info( + "[update] Found %d candidate tracks and %d predictions for rule '%s'", + len(candidate_tracks), + len(preds), + rule.name, + ) + + evidence = False + frame_detections: List[Dict[str, Any]] = [] + + for t in candidate_tracks: + bx = _clamp_box(tuple(map(int, t.bbox)), W, H) + if self._match_classes(rule, preds): + evidence = True + log.info( + "[update] Evidence matched for rule '%s' on track_id=%s bbox=%s", + rule.name, + getattr(t, "track_id", None), + bx, + ) + + x1, y1, x2, y2 = bx + try: + conf_val = float(t.conf) + except Exception: + conf_val = None + frame_detections.append( + { + "track_id": int(t.track_id) + if getattr(t, "track_id", None) is not None + else None, + "x1": x1, + "y1": y1, + "x2": x2, + "y2": y2, + "conf": conf_val, + } + ) + + st = self._state(rule) + key = self._key(rule) + log.info( + "[update] Current state for key=%s consec=%d cooldown_left=%d open_incident=%s", + key, + st.consec, + st.cooldown_left, + getattr(st.open_incident, "incident_id", None), + ) + + # If recording, write current frame (with boxes) continuously + if st.open_incident is not None: + rendered = self._render_frame_with_boxes(frame_bgr, st.detections) + if hasattr(st, "_hls") and st._hls: + st._hls.write_bgr(rendered) # continuous live feed + if hasattr(st, "_mp4") and st._mp4: + st._mp4.write_bgr(rendered) # only called when new frames arrive + + st.total_tracks += len(frame_detections) + st.total_frames += 1 + log.info( + "[update] Recorded frame for active incident=%s total_tracks=%d total_frames=%d", + st.open_incident.incident_id, + st.total_tracks, + st.total_frames, + ) + + st.last_seen_frame = frame_idx + st.last_seen_ts = ts_sec + st.detections = frame_detections + + prev_consec = st.consec + st.consec = st.consec + 1 if evidence else 0 + log.info( + "[update] Consecutive evidence count changed from %d -> %d (rule='%s')", + prev_consec, + st.consec, + rule.name, + ) + + if st.open_incident is None and st.consec >= int(rule.min_consec or 1): + log.info("[update] Triggering _open_incident for rule '%s'", rule.name) + opened_data = self._open_incident( + st, + rule, + ts_sec, + frame_idx, + frame_bgr, + ) + evt.opened_incident_id = st.open_incident.incident_id + evt.opened_data = opened_data + log.info( + "[update] Opened new incident_id=%s for rule='%s'", + evt.opened_incident_id, + rule.name, + ) + + if st.open_incident is not None: + # sample a representative bbox to append to incident trail + if ( + self.sample_every > 0 + and (frame_idx % self.sample_every == 0) + and st.detections + ): + bx = max( + ( + (d["x2"] - d["x1"]) * (d["y2"] - d["y1"]), + d, + ) + for d in st.detections + )[1] + st.open_incident.boxes.append( + (bx["x1"], bx["y1"], bx["x2"], bx["y2"]) + ) + st.open_incident.confs.append(1.0) + log.info( + "[update] Appended sample bbox=%s to incident trail for %s", + bx, + st.open_incident.incident_id, + ) + + # cooldown logic + prev_cooldown = st.cooldown_left + st.cooldown_left = ( + int(rule.cooldown) if evidence else (st.cooldown_left - 1) + ) + log.info( + "[update] Cooldown changed %d -> %d (evidence=%s)", + prev_cooldown, + st.cooldown_left, + evidence, + ) + + if not evidence and st.cooldown_left <= 0: + closed_id = st.open_incident.incident_id + log.info( + "[update] Closing incident %s (cooldown expired)", + closed_id, + ) + closed_data = self._close_incident( + key, + st, + ts_sec, + frame_idx, + ) + evt.closed_incident_id = closed_id + evt.closed_data = closed_data + + else: + evt.updated_incident_id = st.open_incident.incident_id + log.info( + "[update] Updating active incident %s (evidence=%s cooldown=%d)", + st.open_incident.incident_id, + evidence, + st.cooldown_left, + ) + + log.info( + "[update] Returning IncidentEvent opened=%s updated=%s closed=%s", + evt.opened_incident_id, + evt.updated_incident_id, + evt.closed_incident_id, + ) + return evt + + def flush(self, ts_sec: float, frame_idx: int): + """Close any open incidents across all cameras/rules.""" + for key, st in list(self._states.items()): + if st.open_incident is not None: + self._close_incident(key, st, ts_sec, frame_idx) diff --git a/services/security/agguard/core/events/models.py b/services/security/agguard/core/events/models.py new file mode 100644 index 000000000..307719827 --- /dev/null +++ b/services/security/agguard/core/events/models.py @@ -0,0 +1,43 @@ +from dataclasses import dataclass, field, asdict +from typing import List, Tuple, Dict, Optional, Union +from datetime import datetime + +Box = Tuple[int,int,int,int] + +@dataclass +class Rule: + name: str + target_cls: str # e.g. "person" + target_cls_id: Optional[Union[str,int]] = None # e.g. 0, "0" + match_classes: List[str] = field(default_factory=list) # ← new field + severity: int = 3 + min_conf: float = 0.6 + min_consec: int = 5 + cooldown: int = 12 + + +@dataclass +class Incident: + incident_id: str + kind: str + camera_id: Optional[str] = None + started_ts: float = 0.0 + ended_ts: float = 0.0 + duration_sec: float = 0.0 + frame_start: int = 0 + frame_end: int = 0 + severity: int = 1 + track_id: Optional[int] = None + roi: Optional[List[Tuple[int,int]]] = None + boxes: List[Box] = field(default_factory=list) + confs: List[float] = field(default_factory=list) + classes: List[str] = field(default_factory=list) + snapshot_path: Optional[str] = None + artifacts: Dict[str,str] = field(default_factory=dict) + meta: Dict[str, str|int|float] = field(default_factory=dict) + + def to_dict(self) -> Dict: + d = asdict(self) + d["started_iso"] = datetime.utcfromtimestamp(self.started_ts).isoformat()+"Z" + d["ended_iso"] = datetime.utcfromtimestamp(self.ended_ts).isoformat()+"Z" + return d diff --git a/services/security/agguard/core/motion.py b/services/security/agguard/core/motion.py new file mode 100644 index 000000000..41ebccb8d --- /dev/null +++ b/services/security/agguard/core/motion.py @@ -0,0 +1,198 @@ +from __future__ import annotations +from dataclasses import dataclass +from typing import List, Tuple, Optional +import numpy as np +import cv2 +import logging +from .roi import Roi + +log = logging.getLogger(__name__) + +@dataclass +class ChangeReading: + score: float + area_px: int + total_px: int + fgmask: np.ndarray + bboxes: List[Tuple[int, int, int, int]] + +def _iou(a, b): + ax1, ay1, ax2, ay2 = a; bx1, by1, bx2, by2 = b + ix1, iy1 = max(ax1, bx1), max(ay1, by1); ix2, iy2 = min(ax2, bx2), min(ay2, by2) + iw, ih = max(0, ix2 - ix1 + 1), max(0, iy2 - iy1 + 1) + inter = iw * ih + if inter <= 0: + return 0.0 + aA = (ax2 - ax1 + 1) * (ay2 - ay1 + 1); bA = (bx2 - bx1 + 1) * (by2 - by1 + 1) + return inter / float(aA + bA - inter) + +def _merge_overlapping(boxes, iou_thresh=0.35, max_iters=5): + boxes = boxes[:] + for _ in range(max_iters): + merged, used = [], [False] * len(boxes) + for i in range(len(boxes)): + if used[i]: + continue + cur, changed = boxes[i], True + while changed: + changed = False + for j in range(i + 1, len(boxes)): + if used[j]: + continue + if _iou(cur, boxes[j]) >= iou_thresh: + x1 = min(cur[0], boxes[j][0]); y1 = min(cur[1], boxes[j][1]) + x2 = max(cur[2], boxes[j][2]); y2 = max(cur[3], boxes[j][3]) + cur = (x1, y1, x2, y2) + used[j] = True + changed = True + used[i] = True + merged.append(cur) + if len(merged) == len(boxes): + return merged + boxes = merged + return boxes + +class MotionGate: + """ + Same API/output intent as your original: MOG2 on BGR + ROI + morphology + CC + merge, + but runs on a downscaled frame for speed. Kernels and min-area are scaled so the + *effective* behavior matches full-res. + """ + + def __init__( + self, + roi: Roi, + history: int = 300, + var_threshold: float = 16.0, + shadow: bool = True, # keep your default + min_blob_area: int = 80, + morph_open: int = 3, + smooth_alpha: float = 0.2, + dilate_px: int = 2, + morph_close: int = 5, + merge_iou: float = 0.35, + target_max_dim: int = 480, # downscale max side; set to 0/None to disable + ): + self.roi = roi + self.min_blob_area = int(min_blob_area) + self.morph_open = int(morph_open) + self.smooth_alpha = float(smooth_alpha) + self.dilate_px = int(dilate_px) + self.morph_close = int(morph_close) + self.merge_iou = float(merge_iou) + self.target_max_dim = int(target_max_dim) if target_max_dim else 0 + + self._ema: Optional[float] = None + self._roi_mask = roi.mask() # full-res mask + self._roi_mask_small: Optional[np.ndarray] = None + self._bg_size: Optional[Tuple[int, int]] = None + + self._bg_shadow = bool(shadow) + self._history = int(history) + self._var_threshold = float(var_threshold) + self.bg = None # created lazily when small size is known + + def _ensure_background(self, sh: int, sw: int): + if self._bg_size != (sh, sw): + self.bg = cv2.createBackgroundSubtractorMOG2( + history=self._history, + varThreshold=self._var_threshold, + detectShadows=self._bg_shadow, + ) + self._bg_size = (sh, sw) + + def _ensure_small_roi_mask(self, h: int, w: int, sh: int, sw: int): + if (w, h) != self.roi.size: + self.roi.size = (w, h) + self._roi_mask = self.roi.mask() + self._roi_mask_small = None + if self._roi_mask_small is None or self._roi_mask_small.shape != (sh, sw): + self._roi_mask_small = cv2.resize( + self._roi_mask, (sw, sh), interpolation=cv2.INTER_NEAREST + ) + + def update(self, frame_bgr: np.ndarray) -> ChangeReading: + h, w = frame_bgr.shape[:2] + + # scale factor (downscale for speed; 1.0 means no downscale) + if self.target_max_dim and max(h, w) > self.target_max_dim: + scale = max(h, w) / float(self.target_max_dim) + sw, sh = int(round(w / scale)), int(round(h / scale)) + else: + scale = 1.0 + sw, sh = w, h + + # prepare small BGR (keep BGR like your original) + small = frame_bgr if scale == 1.0 else cv2.resize(frame_bgr, (sw, sh), interpolation=cv2.INTER_AREA) + + self._ensure_background(sh, sw) + self._ensure_small_roi_mask(h, w, sh, sw) + + # ---- MOG2 on BGR (like original) ---- + fg = self.bg.apply(small) # if detectShadows=True, returns 0/127/255 + if self._bg_shadow: + # keep your original binarying step + _, fg = cv2.threshold(fg, 200, 255, cv2.THRESH_BINARY) + + # ROI on small + fg = cv2.bitwise_and(fg, self._roi_mask_small) + + # ---- scale morphology kernels to preserve behavior ---- + def k_odd(x: int) -> int: + return x if x % 2 == 1 else max(1, x - 1) + + # kernels shrink by ~1/scale on the small image + dilate_small = max(0, int(round(self.dilate_px / scale))) + close_small = max(0, int(round(self.morph_close / scale))) + open_small = max(0, int(round(self.morph_open / scale))) + + if dilate_small > 0: + k = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (k_odd(2*dilate_small + 1), k_odd(2*dilate_small + 1))) + fg = cv2.dilate(fg, k, iterations=1) + if close_small > 0: + k = cv2.getStructuringElement(cv2.MORPH_RECT, (k_odd(close_small), k_odd(close_small))) + fg = cv2.morphologyEx(fg, cv2.MORPH_CLOSE, k, iterations=1) + if open_small > 0: + k = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (k_odd(open_small), k_odd(open_small))) + fg = cv2.morphologyEx(fg, cv2.MORPH_OPEN, k, iterations=1) + + # CC on small; area threshold scaled by 1/scale^2 + min_area_small = max(1, int(round(self.min_blob_area / (scale * scale)))) + num, labels, stats, _ = cv2.connectedComponentsWithStats(fg, connectivity=8) + + boxes_small: List[Tuple[int, int, int, int]] = [] + clean_small = np.zeros_like(fg) + for i in range(1, num): + x, y, w0, h0, area = stats[i] + if area < min_area_small: + continue + x1, y1, x2, y2 = x, y, x + w0 - 1, y + h0 - 1 + boxes_small.append((x1, y1, x2, y2)) + clean_small[y : y + h0, x : x + w0] = 255 + + if len(boxes_small) > 1 and self.merge_iou > 0: + boxes_small = _merge_overlapping(boxes_small, iou_thresh=self.merge_iou) + + # map back to full-res + if scale != 1.0: + bboxes = [ + (int(round(x1 * scale)), int(round(y1 * scale)), + int(round(x2 * scale)), int(round(y2 * scale))) + for (x1, y1, x2, y2) in boxes_small + ] + clean = cv2.resize(clean_small, (w, h), interpolation=cv2.INTER_NEAREST) + else: + bboxes = boxes_small + clean = clean_small + + moving = int((clean == 255).sum()) + total = int((self._roi_mask == 255).sum()) + raw = float(moving) / float(max(total, 1)) + if self.smooth_alpha > 0: + self._ema = raw if self._ema is None else (1 - self.smooth_alpha) * self._ema + self.smooth_alpha * raw + score = float(self._ema) + else: + score = raw + + log.debug("MotionGate: score=%.3f, blobs=%d, area=%d/%d", score, len(bboxes), moving, total) + return ChangeReading(score=score, area_px=moving, total_px=total, fgmask=clean, bboxes=bboxes) diff --git a/services/security/agguard/core/roi.py b/services/security/agguard/core/roi.py new file mode 100644 index 000000000..0b7f3a07d --- /dev/null +++ b/services/security/agguard/core/roi.py @@ -0,0 +1,49 @@ +from __future__ import annotations +from dataclasses import dataclass +from typing import Sequence, Tuple +import numpy as np +import cv2 + +Point = Tuple[float, float] + +def _ensure_np(arr: Sequence[Point]) -> np.ndarray: + a = np.asarray(arr, dtype=np.float32) + if a.ndim != 2 or a.shape[1] != 2: + raise ValueError("Expected Nx2 points") + return a + +@dataclass +class Roi: + """Polygonal ROI stored in normalized coords [0,1] and sized in pixels.""" + poly_norm: np.ndarray + size: Tuple[int, int] # (w, h) + + @staticmethod + def from_normalized(poly_norm: Sequence[Point], frame_size: Tuple[int, int]) -> "Roi": + pn = _ensure_np(poly_norm) + if (pn < 0).any() or (pn > 1).any(): + raise ValueError("ROI must be normalized to [0,1]") + return Roi(pn, frame_size) + + @staticmethod + def from_pixels(poly_px: Sequence[Point], frame_size: Tuple[int, int]) -> "Roi": + w, h = frame_size + pp = _ensure_np(poly_px) + pn = np.stack([pp[:, 0] / w, pp[:, 1] / h], axis=1) + return Roi(pn, frame_size) + + @property + def poly_px(self) -> np.ndarray: + w, h = self.size + pn = self.poly_norm + pp = np.stack([pn[:, 0] * w, pn[:, 1] * h], axis=1).astype(np.float32) + return pp + + def as_cv2(self) -> np.ndarray: + return self.poly_px.reshape((-1, 1, 2)).astype(np.int32) + + def mask(self) -> np.ndarray: + w, h = self.size + m = np.zeros((h, w), dtype=np.uint8) + cv2.fillPoly(m, [self.as_cv2()], 255) + return m diff --git a/services/security/agguard/core/tracker.py b/services/security/agguard/core/tracker.py new file mode 100644 index 000000000..df92e44cc --- /dev/null +++ b/services/security/agguard/core/tracker.py @@ -0,0 +1,56 @@ +from .types import Track + +import numpy as np +from dataclasses import dataclass +from boxmot import ByteTrack + +@dataclass +class Track: + track_id: int + cls: str + conf: float + bbox: tuple # (x1, y1, x2, y2) + + +class BoxMOTWrapper: + def __init__(self, method="bytetrack", class_map=None, **kwargs): + """ + class_map: dict[str,int] — e.g. {"animal":1, "person":2, "vehicle":3} + """ + self.trk = ByteTrack(**kwargs) + self.class_map = class_map or {"animal": 1, "person": 2, "vehicle": 3} + self.inv_class_map = {v: k for k, v in self.class_map.items()} + + def update(self, dets, frame): + if not dets: + self.trk.update(np.empty((0,6), dtype=float), frame) + return [] + + # normalize detections (supports both Detection objects and tuples) + norm_dets = [] + for d in dets: + if isinstance(d, tuple) and len(d) == 3: + cls, conf, bbox = d + else: + cls, conf, bbox = getattr(d, "cls", None), getattr(d, "conf", None), getattr(d, "bbox", None) + if bbox is None: + continue + norm_dets.append((cls, conf, bbox)) + + if not norm_dets: + return [] + + boxes = np.array([b for _, _, b in norm_dets], dtype=float) + confs = np.array([[float(c or 0.0)] for _, c, _ in norm_dets]) + clss = np.array([[self.class_map.get(c, 0)] for c, _, _ in norm_dets], dtype=float) + + detections = np.concatenate([boxes, confs, clss], axis=1) + tracks = self.trk.update(detections, frame) + + results = [] + for t in tracks: + x1, y1, x2, y2, tid, conf, cls_id = map(float, t[:7]) + cls_name = self.inv_class_map.get(int(cls_id), str(int(cls_id))) + results.append(Track(track_id=int(tid), cls=cls_name, conf=conf, bbox=(x1, y1, x2, y2))) + + return results diff --git a/services/security/agguard/core/types.py b/services/security/agguard/core/types.py new file mode 100644 index 000000000..cee091213 --- /dev/null +++ b/services/security/agguard/core/types.py @@ -0,0 +1,20 @@ +from __future__ import annotations +from dataclasses import dataclass +from typing import Tuple + +BBox = Tuple[int, int, int, int] # x1, y1, x2, y2 + +@dataclass +class Detection: + cls: str + conf: float + bbox: BBox + +@dataclass +class Track: + track_id: int + cls: str # change to str to match aggregator expectations + conf: float + bbox: tuple # (x1, y1, x2, y2) + hits: int = 0 + miss: int = 0 diff --git a/services/security/agguard/logging_utils.py b/services/security/agguard/logging_utils.py new file mode 100644 index 000000000..b1154e2c8 --- /dev/null +++ b/services/security/agguard/logging_utils.py @@ -0,0 +1,12 @@ +import logging +from logging.handlers import RotatingFileHandler +from typing import Optional + +def setup_logging(level: str = "INFO", log_file: Optional[str] = None) -> None: + fmt = "%(asctime)s | %(levelname)s | %(name)s | %(message)s" + logging.basicConfig(level=getattr(logging, level.upper(), logging.INFO), format=fmt) + if log_file: + handler = RotatingFileHandler(log_file, maxBytes=5_000_000, backupCount=3) + handler.setLevel(getattr(logging, level.upper(), logging.INFO)) + handler.setFormatter(logging.Formatter(fmt)) + logging.getLogger().addHandler(handler) diff --git a/services/security/agguard/media/hls_recorder.py b/services/security/agguard/media/hls_recorder.py new file mode 100644 index 000000000..2a91a95c7 --- /dev/null +++ b/services/security/agguard/media/hls_recorder.py @@ -0,0 +1,626 @@ +# agguard/media/hls_recorder.py +from __future__ import annotations + +import os +import time +import shutil +import tempfile +import subprocess +import pathlib +import threading +import re +from dataclasses import dataclass, field +from typing import Optional, Tuple +from urllib.parse import urlparse + +import numpy as np # for blank/held frames + +_CT = { + ".m3u8": "application/vnd.apple.mpegurl", + ".ts": "video/MP2T", + ".m4s": "video/mp4", + ".mp4": "video/mp4", +} + + +@dataclass +class HlsConfig: + # Fixed cadence; 4–6 fps works well for security UIs + fps: int = 5 + # 1.0s segments: good LIVE smoothness + 1s DVR seeks + segment_time: float = 1.0 + # Event playlist grows; proxy trims for LIVE + list_size: int = 240 + # Stick to TS for VLC; switch True for CMAF if wanted + use_cmaf: bool = False + # x264 knobs + preset: str = "veryfast" + crf: int = 23 + # one GOP per segment => clean random access + gop_segments: int = 1 + # S3 mirror cadence + upload_interval_sec: float = 0.02 + # Optional downscale (keeps aspect) + target_width: Optional[int] = None + # Some players behave better with silent audio + add_silent_audio: bool = True + + +@dataclass +class HlsRecorder: + s3: any + bucket: str + prefix: str + cfg: HlsConfig = field(default_factory=HlsConfig) + + # Minimum delay between stop() and any delete_*() + MIN_DELETE_DELAY: float = 120.0 # seconds + + _tmpdir: Optional[str] = None + _proc: Optional[subprocess.Popen] = None + + # Uploader state + _sync_thread: Optional[threading.Thread] = None + _stop_evt: threading.Event = field(default_factory=threading.Event) + _uploaded_keys: set = field(default_factory=set) + _ready_evt: threading.Event = field(default_factory=threading.Event) + + # Pacing/feeder state + _feeder_thread: Optional[threading.Thread] = None + _feeder_stop: threading.Event = field(default_factory=threading.Event) + _last_frame: Optional[np.ndarray] = None + _last_frame_lock: threading.Lock = field(default_factory=threading.Lock) + _frame_shape: Optional[Tuple[int, int]] = None + _first_frame_evt: threading.Event = field(default_factory=threading.Event) + + # State after stop() + _stopped_tmpdir: Optional[str] = None + _stopped_at: Optional[float] = None + + # ──────────────────────────────────────────────────────────────────────── + # Public API + # ──────────────────────────────────────────────────────────────────────── + def start(self, frame_size: Tuple[int, int]) -> None: + """ + Start ffmpeg HLS writer + background uploader + paced feeder. + This variant waits for the FIRST call to write_bgr() before feeding, + so we don't encode initial black frames. + """ + H, W = frame_size + self._frame_shape = (H, W) + self._tmpdir = tempfile.mkdtemp(prefix="hls_") + out = pathlib.Path(self._tmpdir) + + # reset stop metadata on reuse + self._stopped_tmpdir = None + self._stopped_at = None + + seg_ext = ".m4s" if self.cfg.use_cmaf else ".ts" + seg_pattern = str(out / f"segment_%05d{seg_ext}") + m3u8_path = str(out / "index.m3u8") + + fps = max(1, int(self.cfg.fps)) + seg_time = float(self.cfg.segment_time) + g_exact = max(1, int(round(fps * seg_time * max(1, self.cfg.gop_segments)))) + + vf_parts = [] + if self.cfg.target_width and W > self.cfg.target_width: + vf_parts.append(f"scale={self.cfg.target_width}:-2") + vf_parts.append("format=yuv420p") + vf = ",".join(vf_parts) + + cmd = [ + "ffmpeg", + "-loglevel", "warning", + # raw BGR frames on stdin; feeder will pace these + "-f", "rawvideo", + "-pix_fmt", "bgr24", + "-s:v", f"{W}x{H}", + "-r", str(fps), + "-i", "pipe:0", + ] + + # Optional silent audio (improves compatibility) + if self.cfg.add_silent_audio: + cmd += [ + "-f", "lavfi", + "-i", "anullsrc=channel_layout=stereo:sample_rate=48000", + ] + map_args = ["-map", "0:v:0", "-map", "1:a:0"] + else: + map_args = ["-map", "0:v:0"] + + cmd += [ + *map_args, + "-vf", vf, + "-c:v", "libx264", + "-preset", self.cfg.preset, + "-crf", str(self.cfg.crf), + "-profile:v", "main", + "-level:v", "4.1", + "-tune", "zerolatency", + "-g", str(g_exact), + "-keyint_min", str(g_exact), + "-sc_threshold", "0", + "-force_key_frames", f"expr:gte(t,n_forced*{seg_time})", + ] + + if not self.cfg.use_cmaf: + # Make TS segments self-contained + cmd += ["-mpegts_flags", "resend_headers+initial_discontinuity"] + + if self.cfg.add_silent_audio: + cmd += ["-c:a", "aac", "-ar", "48000", "-b:a", "128k"] + + # HLS muxing — EVENT playlist (grows); we’ll freeze it at finalize + hls_flags = "append_list+program_date_time+independent_segments+temp_file+split_by_time" + cmd += [ + "-f", "hls", + "-hls_time", str(seg_time), + "-hls_list_size", str(self.cfg.list_size), + "-hls_flags", hls_flags, + "-hls_segment_filename", seg_pattern, + "-hls_playlist_type", "event", + "-mpegts_flags", "resend_headers+initial_discontinuity", + "-movflags", "faststart", + m3u8_path, + ] + + if self.cfg.use_cmaf: + cmd += [ + "-hls_segment_type", "fmp4", + "-hls_fmp4_init_filename", "init.mp4", + "-hls_part_size", "0.2", + ] + + # Launch ffmpeg + self._proc = subprocess.Popen(cmd, stdin=subprocess.PIPE, cwd=self._tmpdir) + + # We have not received any real frame yet + self._first_frame_evt.clear() + + # Start uploader (mirrors local files to S3 fast) + self._stop_evt.clear() + self._sync_thread = threading.Thread(target=self._sync_loop, daemon=True) + self._sync_thread.start() + + # Start paced feeder + self._feeder_stop.clear() + self._feeder_thread = threading.Thread(target=self._feeder_loop, daemon=True) + self._feeder_thread.start() + + def write_bgr(self, frame_bgr) -> None: + """Update the latest processed frame; feeder thread handles pacing.""" + if frame_bgr is None: + return + with self._last_frame_lock: + self._last_frame = np.ascontiguousarray(frame_bgr) + # If the feeder was waiting for the first frame, release it immediately + if not self._first_frame_evt.is_set(): + self._first_frame_evt.set() + + # ──────────────────────────────────────────────────────────────────────── + # Internals + # ──────────────────────────────────────────────────────────────────────── + def _feeder_loop(self): + """Write frames into ffmpeg stdin at a fixed cadence; hold last frame when idle.""" + fps = max(1, int(self.cfg.fps)) + period = 1.0 / float(fps) + + # Wait for the first real frame to avoid initial black. + self._first_frame_evt.wait(timeout=3.0) + + # If absolutely nothing arrived, we can still fall back to blank. + blank = None + if self._frame_shape: + H, W = self._frame_shape + blank = np.zeros((H, W, 3), dtype=np.uint8) + + while not self._feeder_stop.is_set(): + t0 = time.perf_counter() + with self._last_frame_lock: + frame = self._last_frame + if frame is None: + frame = blank + if frame is not None and self._proc and self._proc.poll() is None: + try: + self._proc.stdin.write(frame.tobytes()) + except BrokenPipeError: + self._feeder_stop.set() + break + except Exception: + pass + dt = time.perf_counter() - t0 + time.sleep(max(0.0, period - dt)) + + def _parse_tail_refs(self, m3u8_path: pathlib.Path) -> list[str]: + """ + Return the list of segment filenames (URIs) in order, last item is the freshest. + Works for both TS and CMAF (fMP4) playlists produced by ffmpeg. + """ + try: + txt = m3u8_path.read_text(encoding="utf-8", errors="ignore") + except Exception: + return [] + uris = [] + for line in txt.splitlines(): + s = line.strip() + if not s or s.startswith("#"): + continue + # keep raw line (local filename) + uris.append(os.path.basename(s)) + return uris + + def _make_publishable_index(self, m3u8_path: pathlib.Path, exist_names: set[str]) -> Optional[pathlib.Path]: + """ + Create a temp 'index.publish.m3u8' that is identical to the local m3u8 + but with any trailing (#EXTINF, URI) pairs removed if their URI file + does not exist in 'exist_names'. Keeps headers & MAP intact. + Returns path to the temp publishable file, or None if nothing to publish yet. + """ + try: + lines = m3u8_path.read_text(encoding="utf-8", errors="ignore").splitlines() + except Exception: + return None + + headers: list[str] = [] + body_pairs: list[tuple[str, str]] = [] # (extinf, uri) + pending_extinf: Optional[str] = None + map_line: Optional[str] = None + + for raw in lines: + s = raw.strip() + if not s: + continue + if s.startswith("#"): + if s.startswith("#EXTINF:"): + pending_extinf = s + elif s.startswith("#EXT-X-MAP:"): + map_line = s + elif s.startswith("#EXT-X-ENDLIST"): + # drop ENDLIST for live/event publishing + continue + else: + headers.append(s) + else: + # media URI + uri = os.path.basename(s) + if pending_extinf is None: + # defensive: if EXTINF missing, synthesize a 1s tag + pending_extinf = "#EXTINF:1.000," + body_pairs.append((pending_extinf, uri)) + pending_extinf = None + + # Trim from the tail until last URI exists + while body_pairs and body_pairs[-1][1] not in exist_names: + body_pairs.pop() + + if not body_pairs: + return None + + out: list[str] = ["#EXTM3U"] + # normalize a few important headers; keep original others + have_version = any(h.startswith("#EXT-X-VERSION:") for h in headers) + have_indep = any(h.startswith("#EXT-X-INDEPENDENT-SEGMENTS") for h in headers) + have_target = any(h.startswith("#EXT-X-TARGETDURATION:") for h in headers) + + if not have_version: + out.append("#EXT-X-VERSION:6") + for h in headers: + out.append(h) + if not have_indep: + out.append("#EXT-X-INDEPENDENT-SEGMENTS") + if not have_target: + out.append("#EXT-X-TARGETDURATION:1") + + if map_line: + out.append(map_line) + + for extinf, uri in body_pairs: + out.append(extinf) + out.append(uri) + + tmp = m3u8_path.parent / "index.publish.m3u8" + tmp.write_text("\n".join(out) + "\n", encoding="utf-8") + return tmp + + def _sync_loop(self) -> None: + """Continuously mirror new/changed local HLS files to S3 in a safe order. + + Order: + 1) init.mp4 (if CMAF) + 2) segments (.ts or .m4s) + 3) audio files (rare) + 4) index.m3u8 (LAST, and only after newest referenced segment is uploaded) + """ + if not self._tmpdir: + return + root = pathlib.Path(self._tmpdir) + seen: dict[str, tuple[int, int]] = {} + have_index = False + have_init = not self.cfg.use_cmaf + + interval = float(max(0.005, self.cfg.upload_interval_sec)) + while not self._stop_evt.is_set(): + try: + # Snapshot current files + files = [p for p in root.iterdir() if p.is_file()] + # Partition by type + init_files = [p for p in files if p.name == "init.mp4"] + seg_files_ts = [p for p in files if p.suffix.lower() == ".ts"] + seg_files_m4s = [p for p in files if p.suffix.lower() == ".m4s"] + audio_files = [p for p in files if p.suffix.lower() in (".aac", ".mp3", ".wav")] + m3u8_files = [p for p in files if p.name == "index.m3u8"] + + # 1) init.mp4 first (CMAF) + for p in init_files: + stat = p.stat() + sig = (stat.st_size, getattr(stat, "st_mtime_ns", int(stat.st_mtime * 1e9))) + key = f"{self.prefix}/{p.name}" + if seen.get(key) != sig: + self.s3.put_file(self.bucket, key, str(p), _CT.get(".mp4", "video/mp4")) + seen[key] = sig + self._uploaded_keys.add(key) + have_init = True + + # 2) segments, sorted by name (sequence) + segs = sorted(seg_files_ts + seg_files_m4s, key=lambda x: x.name) + for p in segs: + stat = p.stat() + sig = (stat.st_size, getattr(stat, "st_mtime_ns", int(stat.st_mtime * 1e9))) + key = f"{self.prefix}/{p.name}" + if seen.get(key) == sig: + continue + self.s3.put_file(self.bucket, key, str(p), _CT.get(p.suffix.lower(), "application/octet-stream")) + seen[key] = sig + self._uploaded_keys.add(key) + + # 3) any audio + for p in audio_files: + stat = p.stat() + sig = (stat.st_size, getattr(stat, "st_mtime_ns", int(stat.st_mtime * 1e9))) + key = f"{self.prefix}/{p.name}" + if seen.get(key) != sig: + self.s3.put_file(self.bucket, key, str(p), _CT.get(p.suffix.lower(), "application/octet-stream")) + seen[key] = sig + self._uploaded_keys.add(key) + + # 4) finally index.m3u8 — publish a trimmed version so it never points ahead + for p in m3u8_files: + stat = p.stat() + if stat.st_size <= 0: + continue + + existing = {q.name for q in segs} + if self.cfg.use_cmaf: + existing |= {q.name for q in init_files} + + publishable = self._make_publishable_index(p, existing) + if not publishable: + continue + + pub_stat = publishable.stat() + sig = (pub_stat.st_size, getattr(pub_stat, "st_mtime_ns", int(pub_stat.st_mtime * 1e9))) + key = f"{self.prefix}/index.m3u8" + if seen.get(key) != sig: + self.s3.put_file(self.bucket, key, str(publishable), _CT[".m3u8"]) + seen[key] = sig + self._uploaded_keys.add(key) + have_index = True + + if have_index and have_init and not self._ready_evt.is_set(): + self._ready_evt.set() + + except Exception: + # best-effort sync + pass + + time.sleep(interval) + + def wait_ready(self, timeout: float = 6.0) -> bool: + """Block until the playlist (+ init for CMAF) has been uploaded once (or timeout).""" + return self._ready_evt.wait(timeout) + + def _cleanup_local(self) -> None: + try: + if self._tmpdir and os.path.isdir(self._tmpdir): + shutil.rmtree(self._tmpdir, ignore_errors=True) + finally: + self._tmpdir = None + + # ──────────────────────────────────────────────────────────────────────── + # Stop + # ──────────────────────────────────────────────────────────────────────── + def stop(self): + """Stop all threads and kill ffmpeg reliably (no deletion here).""" + try: + # Stop feeder + self._feeder_stop.set() + if self._feeder_thread and self._feeder_thread.is_alive(): + self._feeder_thread.join(timeout=0.5) + + # Stop uploader + self._stop_evt.set() + if self._sync_thread and self._sync_thread.is_alive(): + self._sync_thread.join(timeout=0.5) + + # Close ffmpeg stdin + if self._proc and self._proc.stdin: + try: + self._proc.stdin.close() + except Exception: + pass + + # HARD kill ffmpeg no matter what + if self._proc: + try: + self._proc.terminate() + self._proc.wait(timeout=0.5) + except Exception: + pass + finally: + try: + self._proc.kill() + self._proc.wait(timeout=0.5) + except Exception: + pass + + finally: + # Always mark tmpdir as stopped + self._stopped_tmpdir = self._tmpdir + self._stopped_at = time.time() + self._tmpdir = None + self._proc = None + print(f"[HlsRecorder] stop() called; _stopped_at={self._stopped_at:.3f}, dir={self._stopped_tmpdir}") + + # ──────────────────────────────────────────────────────────────────────── + # Playlist freezing / reconstruction for finalize (unchanged) + # ──────────────────────────────────────────────────────────────────────── + def _freeze_local_playlist(self, m3u8_path: pathlib.Path, workdir: pathlib.Path) -> pathlib.Path: + def _maybe_localize_uri(uri: str) -> str: + m = re.search(r"[?&]u=([^&]+)", uri) + inner = m.group(1) if m else uri + u = urlparse(inner) + candidate = os.path.basename(u.path if u.scheme in ("http", "https") else inner) + return candidate # ffmpeg will read from cwd + + lines = m3u8_path.read_text(encoding="utf-8", errors="ignore").splitlines() + + version = 6 + target = 1 + have_independent = False + + body: list[str] = [] + for line in lines: + s = line.strip() + if not s: + continue + if s.startswith("#"): + if s.startswith("#EXT-X-VERSION:"): + version = 6 # normalize + elif s.startswith("#EXT-X-TARGETDURATION:"): + try: + target = max(target, int(float(s.split(":", 1)[1]))) + except Exception: + pass + elif s.startswith("#EXT-X-INDEPENDENT-SEGMENTS"): + have_independent = True + elif s.startswith("#EXT-X-MAP:"): + m = re.search(r'URI="([^"]+)"', s) + if m: + body.append(f'#EXT-X-MAP:URI="{_maybe_localize_uri(m.group(1))}"') + elif s.startswith("#EXTINF:"): + body.append(s) + continue + body.append(_maybe_localize_uri(s)) + + frozen = ["#EXTM3U", f"#EXT-X-VERSION:{version}"] + if not have_independent: + frozen.append("#EXT-X-INDEPENDENT-SEGMENTS") + frozen.append(f"#EXT-X-TARGETDURATION:{max(1, int(target))}") + frozen.extend(body) + frozen.append("#EXT-X-ENDLIST") + + out_path = workdir / "finalize.m3u8" + out_path.write_text("\n".join(frozen) + "\n", encoding="utf-8") + return out_path + + # ──────────────────────────────────────────────────────────────────────── + # Deletion helpers (with hard guard) + # ──────────────────────────────────────────────────────────────────────── + def _can_delete(self, kind: str) -> bool: + """ + Common guard: we only allow delete if stop() was called and at least + MIN_DELETE_DELAY seconds have passed. + """ + if self._stopped_at is None: + print(f"[HlsRecorder] ⛔ {kind}: stop() was never called → NOT deleting.") + return False + + dt = time.time() - self._stopped_at + if dt < self.MIN_DELETE_DELAY: + print( + f"[HlsRecorder] ⏳ {kind}: only {dt:.1f}s since stop " + f"(need {self.MIN_DELETE_DELAY}s) → NOT deleting." + ) + return False + + print(f"[HlsRecorder] ✅ {kind}: {dt:.1f}s since stop → OK to delete.") + return True + + def delete_hls_files_only(self) -> None: + """ + Delete all HLS-related files (.ts, .m3u8, .m4s, .aac, .wav, .mp3, .tmp) + from the directory where HLS was recorded. + """ + if not self._can_delete("local delete"): + return + + base = self._stopped_tmpdir or self._tmpdir + if not base or not os.path.isdir(base): + print("[HLS DEBUG] No directory to clean:", base) + return + + base_dir = pathlib.Path(base) + + exts_to_delete = {".ts", ".m3u8", ".m4s", ".aac", ".wav", ".mp3", ".tmp"} + + print("\n[HLS DEBUG] BEFORE DELETE (local):") + for p in base_dir.iterdir(): + print(" -", p.name) + + for p in base_dir.iterdir(): + if not p.is_file(): + continue + suffix = p.suffix.lower() + if suffix in exts_to_delete or p.name.endswith(".tmp") or p.name == "init.mp4": + try: + p.unlink() + except Exception as e: + print(f"[HlsRecorder] ⚠️ Failed to delete {p}: {e}") + + print("\n[HLS DEBUG] AFTER DELETE (local):") + for p in base_dir.iterdir(): + print(" -", p.name) + + print(f"[HlsRecorder] ✅ Deleted HLS files in {base}") + + def delete_remote_hls(self): + """ + Delete ALL uploaded HLS fragments from S3/MinIO except final.mp4. + Uses the underlying boto client for efficiency. + """ + if not self._can_delete("remote delete"): + return + + prefix = self.prefix.rstrip("/") + "/" + + print("[HLS] Deleting remote HLS under prefix:", prefix) + + try: + resp = self.s3.s3.list_objects_v2(Bucket=self.bucket, Prefix=prefix) + except Exception as e: + print("[HLS] ❌ Failed to list remote objects:", e) + return + + objects = resp.get("Contents", []) + if not objects: + print("[HLS] (no remote objects found)") + return + + to_delete = [] + for obj in objects: + key = obj["Key"] + name = key.split("/")[-1] + if name != "final.mp4": + to_delete.append({"Key": key}) + + if not to_delete: + print("[HLS] No HLS fragments to delete (only final.mp4 exists).") + return + + try: + self.s3.s3.delete_objects(Bucket=self.bucket, Delete={"Objects": to_delete}) + print(f"[HLS] ✅ Deleted {len(to_delete)} remote HLS objects.") + except Exception as e: + print("[HLS] ❌ Failed remote batch delete:", e) diff --git a/services/security/agguard/media/mp4_recorder.py b/services/security/agguard/media/mp4_recorder.py new file mode 100644 index 000000000..2d9f26712 --- /dev/null +++ b/services/security/agguard/media/mp4_recorder.py @@ -0,0 +1,80 @@ +from __future__ import annotations + +import os +import time +import shutil +import tempfile +import subprocess +import pathlib +import threading +import re +from dataclasses import dataclass, field +from typing import Optional, Tuple +from urllib.parse import urlparse +from agguard.media.hls_recorder import HlsConfig + +import numpy as np # for blank/held frames +@dataclass +class Mp4Recorder: + """Simpler recorder used to build final MP4 only from new frames.""" + s3: any + bucket: str + prefix: str + cfg: HlsConfig = field(default_factory=HlsConfig) + _tmpdir: Optional[str] = None + _proc: Optional[subprocess.Popen] = None + + def start(self, frame_size: Tuple[int, int]) -> None: + H, W = frame_size + self._tmpdir = tempfile.mkdtemp(prefix="mp4_") + out_path = pathlib.Path(self._tmpdir) / "frames_pipe.mp4" + + cmd = [ + "ffmpeg", + "-y", + "-loglevel", "warning", + "-f", "rawvideo", + "-pix_fmt", "bgr24", + "-s:v", f"{W}x{H}", + "-r", str(self.cfg.fps), + "-i", "pipe:0", + "-c:v", "libx264", + "-preset", "veryfast", + "-crf", "23", + "-movflags", "+faststart", + str(out_path), + ] + + self._proc = subprocess.Popen(cmd, stdin=subprocess.PIPE, cwd=self._tmpdir) + + def write_bgr(self, frame_bgr) -> None: + if self._proc and self._proc.poll() is None and frame_bgr is not None: + try: + self._proc.stdin.write(frame_bgr.tobytes()) + except BrokenPipeError: + pass + + def finalize(self) -> str: + if self._proc: + try: + if self._proc.stdin: + self._proc.stdin.close() + self._proc.wait(timeout=10) + except Exception: + pass + tmp = pathlib.Path(self._tmpdir or ".") + out_mp4 = tmp / "final.mp4" + + # Rename if needed (ffmpeg already wrote to frames_pipe.mp4) + pipe_out = tmp / "frames_pipe.mp4" + if pipe_out.exists(): + pipe_out.rename(out_mp4) + + mp4_key = f"{self.prefix}/final.mp4" + try: + self.s3.put_file(self.bucket, mp4_key, str(out_mp4), content_type="video/mp4") + except Exception: + pass + + shutil.rmtree(self._tmpdir, ignore_errors=True) + return mp4_key diff --git a/services/security/agguard/metrics/__init__.py b/services/security/agguard/metrics/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/metrics/monitoring.py b/services/security/agguard/metrics/monitoring.py new file mode 100644 index 000000000..829ed9fed --- /dev/null +++ b/services/security/agguard/metrics/monitoring.py @@ -0,0 +1,142 @@ + +from prometheus_client import Counter, Histogram, Gauge, start_http_server +import threading, os, time, psutil + +# Optional torch + NVML for GPU monitoring +try: + import torch +except ImportError: + torch = None +try: + from pynvml import ( + nvmlInit, nvmlDeviceGetHandleByIndex, + nvmlDeviceGetUtilizationRates, nvmlDeviceGetMemoryInfo, + nvmlDeviceGetCount + ) + nvmlInit() +except Exception: + nvmlDeviceGetCount = None + + +# ───────────────────────────────────────────── +# Shared Prometheus metrics +# ───────────────────────────────────────────── +INFER_REQUESTS = Counter( + "inference_requests_total", + "Total inference requests", + ["service"] +) + +INFER_ERRORS = Counter( + "inference_errors_total", + "Total inference errors", + ["service"] +) + +INFER_LATENCY = Histogram( + "inference_latency_seconds", + "Inference latency in seconds", + ["service"] +) + +MODEL_LOAD_SEC = Gauge( + "model_load_seconds", + "Model load time in seconds", + ["service"] +) + +# ───────────────────────────────────────────── +# System / GPU metrics +# ───────────────────────────────────────────── +CPU_USAGE_PERCENT = Gauge( + "system_cpu_usage_percent", + "System CPU utilization percentage", +) + +PROC_CPU_PERCENT = Gauge( + "process_cpu_usage_percent", + "This process's CPU utilization percentage", +) + +PROC_MEM_MB = Gauge( + "process_memory_megabytes", + "This process's resident memory (MB)", +) + +GPU_USAGE_PERCENT = Gauge( + "gpu_utilization_percent", + "GPU utilization percentage per device", + ["gpu_id"] +) + +GPU_MEM_USED_MB = Gauge( + "gpu_memory_used_megabytes", + "GPU memory used (MB per device)", + ["gpu_id"] +) + +GPU_MEM_TOTAL_MB = Gauge( + "gpu_memory_total_megabytes", + "GPU total memory (MB per device)", + ["gpu_id"] +) + + +# ───────────────────────────────────────────── +# Background collector for system metrics +# ───────────────────────────────────────────── +def _collect_system_metrics(interval: int = 5): + """Continuously update CPU, memory, GPU metrics.""" + process = psutil.Process(os.getpid()) + while True: + try: + # System + process CPU/mem + CPU_USAGE_PERCENT.set(psutil.cpu_percent(interval=None)) + PROC_CPU_PERCENT.set(process.cpu_percent(interval=None)) + PROC_MEM_MB.set(process.memory_info().rss / (1024 * 1024)) + + # GPU metrics + if torch and torch.cuda.is_available(): + num_gpus = torch.cuda.device_count() + for i in range(num_gpus): + used = torch.cuda.memory_allocated(i) / (1024 * 1024) + total = torch.cuda.get_device_properties(i).total_memory / (1024 * 1024) + GPU_MEM_USED_MB.labels(gpu_id=str(i)).set(used) + GPU_MEM_TOTAL_MB.labels(gpu_id=str(i)).set(total) + GPU_USAGE_PERCENT.labels(gpu_id=str(i)).set((used / total) * 100) + elif nvmlDeviceGetCount: + for i in range(nvmlDeviceGetCount()): + handle = nvmlDeviceGetHandleByIndex(i) + util = nvmlDeviceGetUtilizationRates(handle) + mem = nvmlDeviceGetMemoryInfo(handle) + GPU_USAGE_PERCENT.labels(gpu_id=str(i)).set(util.gpu) + GPU_MEM_USED_MB.labels(gpu_id=str(i)).set(mem.used / (1024 * 1024)) + GPU_MEM_TOTAL_MB.labels(gpu_id=str(i)).set(mem.total / (1024 * 1024)) + else: + # No GPU — clear gauges + GPU_USAGE_PERCENT.clear() + GPU_MEM_USED_MB.clear() + GPU_MEM_TOTAL_MB.clear() + + except Exception as e: + print(f"[Metrics] ⚠️ System metrics update failed: {e}") + + time.sleep(interval) + + +# ───────────────────────────────────────────── +# Helper to start background /metrics server +# ───────────────────────────────────────────── +def start_metrics_server(): + """Start Prometheus metrics endpoint and background collector.""" + port = int(os.getenv("METRICS_PORT", "8000")) + threading.Thread(target=start_http_server, args=(port,), daemon=True).start() + threading.Thread(target=_collect_system_metrics, daemon=True).start() + print(f"[Metrics] 📊 Prometheus metrics exposed on :{port}/metrics") + + + + + + + diff --git a/services/security/agguard/pipeline/Dockerfile b/services/security/agguard/pipeline/Dockerfile new file mode 100644 index 000000000..c3543193f --- /dev/null +++ b/services/security/agguard/pipeline/Dockerfile @@ -0,0 +1,127 @@ + +# syntax=docker/dockerfile:1.6 + +############################################################ +# Stage 1 — Build Python virtual environment inside Flink base +############################################################ +FROM flink:1.19.3-scala_2.12-java11 AS builder + +USER root + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + PIP_NO_CACHE_DIR=1 \ + OMP_NUM_THREADS=1 \ + OPENBLAS_NUM_THREADS=1 \ + MKL_NUM_THREADS=1 \ + OPENCV_OPENCL_RUNTIME=disabled + +# ─── System dependencies (for OpenCV, Torch, gRPC build) ─── +RUN apt-get update && apt-get install -y --no-install-recommends \ + python3 python3-venv python3-pip build-essential \ + libglib2.0-0 libgl1 libstdc++6 libgomp1 ffmpeg \ + ca-certificates curl wget && \ + rm -rf /var/lib/apt/lists/* + +WORKDIR /opt + +# ─── Create virtual environment ─── +RUN python3 -m venv /opt/venv +ENV PATH="/opt/venv/bin:${PATH}" + +# ─── Install Python dependencies with caching ─── +RUN --mount=type=cache,target=/root/.cache/pip \ + pip install --upgrade pip && \ + pip install \ + "numpy<2.0" apache-flink==1.19.0 \ + boto3 pyyaml opencv-python-headless \ + grpcio grpcio-tools requests Pillow minio kafka-python protobuf \ + google-cloud-storage \ + torch==2.2.2+cpu torchvision==0.17.2+cpu \ + onnx boxmot ffmpeg-python \ + --extra-index-url https://download.pytorch.org/whl/cpu + + + +# ─── Copy application source ─── +WORKDIR /opt/app +COPY agguard ./agguard +COPY configs ./configs + +# ─── Compile gRPC stubs ─── +RUN /opt/venv/bin/python -m grpc_tools.protoc \ + -I agguard/proto \ + --python_out=agguard/proto \ + --grpc_python_out=agguard/proto \ + agguard/proto/ingest.proto \ + agguard/proto/mask_classifier.proto \ + agguard/proto/mega_detector.proto + +# ─── Patch imports in generated stubs ─── +RUN /opt/venv/bin/python - <<'PY' +from pathlib import Path; import re +for p in Path("agguard/proto").glob("*_pb2_grpc.py"): + s = p.read_text() + s2 = re.sub(r'(?m)^import (\w+_pb2)\b', r'from . import \1', s) + if s != s2: + p.write_text(s2) + print("✅ patched:", p) +PY + + +############################################################ +# Stage 2 — Runtime image (Flink + PyFlink) +############################################################ +FROM flink:1.19.3-scala_2.12-java11 + +USER root + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + OMP_NUM_THREADS=1 \ + OPENBLAS_NUM_THREADS=1 \ + MKL_NUM_THREADS=1 \ + OPENCV_OPENCL_RUNTIME=disabled + +# ─── Minimal runtime dependencies ─── +RUN apt-get update && apt-get install -y --no-install-recommends \ + python3 python3-venv libglib2.0-0 libgl1 libstdc++6 libgomp1 \ + ffmpeg ca-certificates curl wget && \ + rm -rf /var/lib/apt/lists/* + +# ─── Copy prebuilt environment and app ─── +COPY --from=builder /opt/venv /opt/venv +COPY --from=builder /opt/app /opt/app + +# ─── Environment variables for Flink + Python ─── +ENV PATH="/opt/venv/bin:${PATH}" \ + PYFLINK_PYTHON=/opt/venv/bin/python \ + PYFLINK_CLIENT_EXECUTABLE=/opt/venv/bin/python \ + PYTHONPATH="/opt/app:/opt/venv/lib/python3.*/site-packages" + +# ─── Kafka connectors (Flink 1.19) ─── +RUN mkdir -p /opt/flink/lib && \ + wget -q --tries=5 --retry-connrefused --waitretry=5 \ + https://repo1.maven.org/maven2/org/apache/kafka/kafka-clients/3.7.0/kafka-clients-3.7.0.jar \ + -O /opt/flink/lib/kafka-clients-3.7.0.jar && \ + wget -q --tries=5 --retry-connrefused --waitretry=5 \ + https://repo1.maven.org/maven2/org/apache/flink/flink-connector-kafka/3.2.0-1.19/flink-connector-kafka-3.2.0-1.19.jar \ + -O /opt/flink/lib/flink-connector-kafka-3.2.0-1.19.jar + +# ─── Runtime environment ─── +ENV KAFKA_BROKERS=kafka:9092 \ + IN_TOPIC=dev-security-images-keys \ + OUT_TOPIC=alerts \ + PIPELINE_CFG=/opt/app/configs/default.yaml \ + PYTHONPATH=/opt/app \ + GRPC_HOST=security:50052 + +EXPOSE 50051 + +USER flink +WORKDIR /opt/app + +CMD ["flink", "run", "-py", "agguard/pipeline/flink_job.py"] + + + diff --git a/services/security/agguard/pipeline/__init__.py b/services/security/agguard/pipeline/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/pipeline/flink_job.py b/services/security/agguard/pipeline/flink_job.py new file mode 100644 index 000000000..ce835db7c --- /dev/null +++ b/services/security/agguard/pipeline/flink_job.py @@ -0,0 +1,222 @@ +import os, json, boto3, cv2, numpy as np, yaml, logging + +from pyflink.datastream import StreamExecutionEnvironment, RuntimeContext +from pyflink.datastream.functions import KeyedProcessFunction +from pyflink.datastream.connectors.kafka import ( + KafkaSource, + KafkaSink, + KafkaOffsetsInitializer, + KafkaRecordSerializationSchema, # ✅ add this +) +from pyflink.common import WatermarkStrategy, Types +from pyflink.common.serialization import SimpleStringSchema +from pyflink.datastream.connectors.kafka import DeliveryGuarantee + + + +from agguard.pipeline.flink_manager import FlinkPipelineManager +from agguard.core.events.models import Rule + +log = logging.getLogger("flink") + +# ---- Force all Python logs to stdout so Flink sees them ---- +import logging, sys + +import sys, logging + +# ---- Force all Python logs to go to stdout (captured by Flink) ---- +root = logging.getLogger() +root.setLevel(logging.DEBUG) + +# Remove any default handlers (Beam might pre-configure one that discards logs) +for h in list(root.handlers): + root.removeHandler(h) + +# Create stdout handler +stdout_handler = logging.StreamHandler(sys.stdout) +stdout_handler.setFormatter(logging.Formatter( + "%(asctime)s [%(levelname)s] %(name)s: %(message)s" +)) +root.addHandler(stdout_handler) + +# Make sure every library logger propagates up to root +logging.captureWarnings(True) # also capture warnings.warn() calls +logging.getLogger().propagate = True +logging.getLogger("pyflink").setLevel(logging.DEBUG) +logging.getLogger("agguard").setLevel(logging.DEBUG) +logging.getLogger("botocore").setLevel(logging.WARNING) +logging.getLogger("urllib3").setLevel(logging.WARNING) + +# Optional: sanity check line +logging.getLogger("flink").info("[Init] Global stdout logger initialized.") + + + +class CameraOperator(KeyedProcessFunction): + def open(self, ctx: RuntimeContext): + # Load the same config as gRPC server + cfg_path = os.getenv("PIPELINE_CFG", "/app/configs/default.yaml") + cfg = yaml.safe_load(open(cfg_path, "r", encoding="utf-8")) + + # ---- Setup logging ---- + log_level = cfg.get("logging", {}).get("level", "INFO") + logging.basicConfig(level=getattr(logging, log_level.upper(), logging.INFO)) + + # ---- Create S3 client ---- + from agguard.adapters.s3_client import S3Client, S3Config + s3_cfg = cfg.get("s3", {}) + self.s3 = S3Client(S3Config( + region_name=s3_cfg.get("region_name", "us-east-1"), + aws_access_key_id=s3_cfg.get("aws_access_key_id"), + aws_secret_access_key=s3_cfg.get("aws_secret_access_key"), + endpoint_url=s3_cfg.get("endpoint_url"), + connect_timeout=float(s3_cfg.get("connect_timeout", 3.0)), + read_timeout=float(s3_cfg.get("read_timeout", 10.0)), + max_attempts=int(s3_cfg.get("max_attempts", 3)), + )) + + # ---- Rules (same as in grpc_server) ---- + from agguard.core.events.models import Rule + rules = [ + Rule( + name="intruding animal", + target_cls="animal", + target_cls_id=1, + match_classes=[ "fox","red_fox","kit_fox", "grey_fox", "brown_bear","bear", "American_black_bear", "wild_boar"], + severity=3, + min_conf=0.25, + min_consec=2, + cooldown=10, + ), + Rule( + name="climbing_fence", + target_cls="animal", + target_cls_id=1, + match_classes=["fox climbing a fence", "bear climbing a fence"], + severity=2, + min_conf=0.5, + min_consec=2, + cooldown=10, + ), + Rule( + name="masked_person", + target_cls="person", + target_cls_id=2, + match_classes=["mask"], + min_conf=0.5, + severity=6, + min_consec=2, + cooldown=6, + ), + + + ] + + + # ---- Create pipeline manager ---- + from agguard.pipeline.flink_manager import FlinkPipelineManager + self.pm = FlinkPipelineManager(cfg, self.s3, rules) + + log.info("[Flink] Initialized CameraOperator with %d rules and S3 at %s", + len(rules), s3_cfg.get("endpoint_url")) + + + def process_element(self, msg, ctx): + data = json.loads(msg) + + full_key = data["key"] # e.g. "security/imagery/air/2025-10-29/123/drone-01_20251029T093413Z.jpg" + file_name = data["file_name"] # e.g. "drone-01_20251029T093413Z.jpg" + linked_time = data.get("linked_time") + + # Split key → bucket + object path + parts = full_key.split("/", 1) + if len(parts) != 2: + log.error(f"Invalid key format (expected 'bucket/path'): {full_key}") + return + bucket, object_key = parts + + # Derive camera_id from the *first part* of the filename + camera_id = file_name.split("_")[0] # "drone-01" + + # Parse ISO 8601 time → seconds since epoch + from datetime import datetime + ts_sec = 0.0 + if linked_time: + try: + ts_sec = datetime.fromisoformat(linked_time.replace("Z", "+00:00")).timestamp() + except Exception as e: + log.warning(f"Invalid linked_time format: {linked_time} ({e})") + + # Fetch image from S3 + frame = self.s3.fetch_image_bgr(bucket, object_key) + + # Process frame through pipeline + evt = self.pm.process( + camera_id=camera_id, + ts_sec=ts_sec, + frame_idx=0, + frame_bgr=frame, + ) + + # Emit alert if there’s one + if evt: + out_json = json.dumps(evt) + log.info(f"[CameraOperator] Emitting alert for {evt.get('alert_id')} ({file_name})") + yield out_json + else: + log.debug(f"[CameraOperator] No alert emitted for {file_name}") + + + + + +def main(): + bootstrap = os.getenv("KAFKA_BROKERS", "kafka:9092") + topic_in = os.getenv("IN_TOPIC", "image_new_security_connections") + topic_out = os.getenv("OUT_TOPIC", "alerts") + + + env = StreamExecutionEnvironment.get_execution_environment() + env.set_parallelism(1) + + source = ( + KafkaSource.builder() + .set_bootstrap_servers(bootstrap) + .set_topics(topic_in) + .set_group_id("flink-camera-pipeline") + .set_starting_offsets(KafkaOffsetsInitializer.latest()) + .set_value_only_deserializer(SimpleStringSchema()) + .build() + ) + + from pyflink.datastream.connectors.kafka import KafkaRecordSerializationSchema + + sink = ( + KafkaSink.builder() + .set_bootstrap_servers(bootstrap) + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(topic_out) # static topic, from OUT_TOPIC + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ) + .set_delivery_guarantee(DeliveryGuarantee.AT_LEAST_ONCE) + .build() +) + + + + stream = ( + env.from_source(source, WatermarkStrategy.no_watermarks(), "CameraFrames") + .key_by(lambda m: json.loads(m)["file_name"].split("_")[0]) + .process(CameraOperator(), output_type=Types.STRING()) + .sink_to(sink) +) + + + + env.execute("AgGuard Flink Pipeline") + + +if __name__ == "__main__": + main() diff --git a/services/security/agguard/pipeline/flink_manager.py b/services/security/agguard/pipeline/flink_manager.py new file mode 100644 index 000000000..3f22b9a0a --- /dev/null +++ b/services/security/agguard/pipeline/flink_manager.py @@ -0,0 +1,152 @@ +from __future__ import annotations +import time, logging +from typing import Dict, Any, List, Optional, Tuple +import numpy as np + +from agguard.core.roi import Roi +from agguard.core.motion import MotionGate +from agguard.specialists.clients.megadetector import MegaDetectorClient +from agguard.core.tracker import BoxMOTWrapper +from agguard.specialists.dispatch import ClassDispatch +from agguard.core.events.aggregator import IncidentAggregator +from agguard.core.events.models import Rule + +log = logging.getLogger(__name__) + + + +class FlinkPipelineManager: + """ + Stateful per-camera pipeline for Flink. + Does NOT talk to DB or S3; emits events to be sent to Kafka. + """ + def __init__(self, cfg: Dict[str, Any],s3, rules: List[Rule]): + self.cfg = cfg + self.rules = rules + self.det = MegaDetectorClient(cfg.get("detector", {})) + self.router = ClassDispatch(cfg.get("specialists", [])) + self.change_thresh = float(cfg.get("change_thresh", 0.02)) + self._states: Dict[str, Dict[str, Any]] = {} + #added + self.s3=s3 + + + def _get_or_create(self, camera_id: str, frame_shape) -> Dict[str, Any]: + if camera_id in self._states: + return self._states[camera_id] + h, w = frame_shape[:2] + roi_poly = Roi.from_normalized([(0,0),(1,0),(1,1),(0,1)], (w,h)) + gate = MotionGate(roi_poly) + trk = BoxMOTWrapper() + + video_bucket = self.cfg.get("video_bucket", "imagery") + media_base = self.cfg.get("media_base", "http://media-proxy:8080") + + aggregator = IncidentAggregator( + rules=self.rules, + camera_id=camera_id, + s3=self.s3, # ✅ your S3 client (already passed into manager) + video_bucket=video_bucket, # ✅ bucket for uploads + video_prefix="security/incidents", + media_base=media_base, # ✅ Base URL for HLS/VOD + ) + + self._states[camera_id] = { + "roi": roi_poly, "gate": gate, "trk": trk, + "aggregator": aggregator, "fps_ema": None, "prev": time.perf_counter() + } + return self._states[camera_id] + + def process(self, camera_id: str, ts_sec: float, + frame_idx: Optional[int], frame_bgr: np.ndarray) -> Optional[Dict[str,Any]]: + + # Start timing for the whole frame + start_time = time.perf_counter() + log.info("[FlinkPipeline] ▶ START frame_idx=%s cam=%s", frame_idx, camera_id) + + p = self._get_or_create(camera_id, frame_bgr.shape) + gate, trk, aggregator = p["gate"], p["trk"], p["aggregator"] + + # ---- 1. Motion gate check ---- + reading = gate.update(frame_bgr) + if reading.score < self.change_thresh: + log.debug("[FlinkPipeline] frame_idx=%s cam=%s — skipped (static frame, score=%.4f)", + frame_idx, camera_id, reading.score) + return None + + # ---- 2. Detection ---- + t_det = time.perf_counter() + dets = self.det.detect(frame_bgr) + log.debug("[FlinkPipeline] frame_idx=%s cam=%s — detected %d objects in %.3fs", + frame_idx, camera_id, len(dets), time.perf_counter() - t_det) + + # ---- 3. Tracking ---- + t_trk = time.perf_counter() + tracks = trk.update(dets, frame_bgr) + # tracks = trk.update([(d.cls, d.conf, d.bbox) for d in dets], frame_bgr) + log.debug("[FlinkPipeline] frame_idx=%s cam=%s — tracker updated %d tracks in %.3fs", + frame_idx, camera_id, len(tracks), time.perf_counter() - t_trk) + + # ---- 4. Specialists (dispatchers) ---- + t_spec = time.perf_counter() + outs = self.router.run(frame_bgr, dets) + log.debug("[FlinkPipeline] frame_idx=%s cam=%s — all specialists done in %.3fs, outputs=%s", + frame_idx, camera_id, time.perf_counter() - t_spec, + {k: len(v) for k, v in outs.items()}) + + # ---- 5. Aggregation ---- + t_agg = time.perf_counter() + evt = aggregator.update(frame_idx, ts_sec, frame_bgr, tracks, outs) + log.debug("[FlinkPipeline] frame_idx=%s cam=%s — aggregator done in %.3fs", + frame_idx, camera_id, time.perf_counter() - t_agg) + + total_time = time.perf_counter() - start_time + log.info("[FlinkPipeline] ✅ DONE frame_idx=%s cam=%s total=%.3fs evt=%s", + frame_idx, camera_id, total_time, + "none" if evt is None else ("open" if evt.opened_incident_id else "close" if evt.closed_incident_id else "other")) + + + + if not evt: + return None + + if not (evt.opened_incident_id or evt.closed_incident_id): + return None + # Prefer closed_data (has more fields), else opened_data + data = evt.closed_data or evt.opened_data or {} + + # Build alert dictionary (only non-None fields) + alert = {} + + # Core identifiers + alert_id = evt.opened_incident_id or evt.closed_incident_id + if alert_id: + alert["alert_id"] = alert_id + else: + alert["alert_id"] = f"alert-{int(time.time()*1000)}" + + # Conditionally add non-empty fields + def put_if_value(key, value): + if value is not None: + alert[key] = value + + put_if_value("alert_type", data.get("kind")) + put_if_value("device_id", camera_id) + put_if_value("started_at", data.get("ts_iso")) + put_if_value("ended_at", data.get("ended_at_iso")) + put_if_value("severity", data.get("severity")) + put_if_value("vod", data.get("vod")) + put_if_value("hls", data.get("hls")) + # Optionally extend later: + + + meta = {"category": "security"} + subject = data.get("subject") + if subject: + meta["subject"] = subject + alert["meta"] = meta + print(alert) + return alert # return dict, not JSON string + + + diff --git a/services/security/agguard/proto/__init__.py b/services/security/agguard/proto/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/proto/ingest.proto b/services/security/agguard/proto/ingest.proto new file mode 100644 index 000000000..4685d4160 --- /dev/null +++ b/services/security/agguard/proto/ingest.proto @@ -0,0 +1,50 @@ +syntax = "proto3"; +package agguard.ingest; + +// Basic detection box for optional echo/telemetry +message BBox { + int32 x1 = 1; + int32 y1 = 2; + int32 x2 = 3; + int32 y2 = 4; + string cls = 5; + float conf = 6; + int32 track_id = 7; // -1 if not tracked +} + +message ProcessImageRequest { + // Source location (REQUIRED): the image must already be in S3/MinIO + string s3_bucket = 10; + string s3_key = 11; + + // Metadata (used to keep per-camera state + DB persistence) + string camera_id = 2; // required for tracking continuity + int64 ts_millis = 3; // event time (ms since epoch) + int64 frame_idx = 4; // monotonically increasing per camera, if known + + // Optional toggles + bool return_detections = 20; // echo detections in response +} + +message ProcessImageResponse { + // Quick telemetry for the caller + string camera_id = 1; + int64 frame_idx = 2; + double change_score = 3; // MotionGate score used for gating + int32 num_detections = 4; + int32 num_tracks = 5; + double fps_estimate = 6; + + // Incident state (if IncidentAggregator opened/updated/closed an incident) + // These fields are best-effort signals; you still persist via DbRepository. + string opened_incident_id = 20; // empty if none + string updated_incident_id = 21; // empty if none + string closed_incident_id = 22; // empty if none + + // Optional detailed output (only if requested) + repeated BBox boxes = 30; +} + +service ImageIngestor { + rpc ProcessImage (ProcessImageRequest) returns (ProcessImageResponse); +} diff --git a/services/security/agguard/proto/mask_classifier.proto b/services/security/agguard/proto/mask_classifier.proto new file mode 100644 index 000000000..134eaa5f6 --- /dev/null +++ b/services/security/agguard/proto/mask_classifier.proto @@ -0,0 +1,39 @@ +syntax = "proto3"; +package agguard.classifiers; + +option go_package = "agguard/classifiers"; +option java_multiple_files = true; + +message Crop { + // JPEG-encoded RGB crop for one detected face/person-region. + bytes jpeg = 1; + // Original box on the full frame, for traceability. + int32 x1 = 2; + int32 y1 = 3; + int32 x2 = 4; + int32 y2 = 5; + string subject = 6; +} + +message ClassifyRequest { + // For future classifiers (e.g., "mask", "helmet", "balaclava") + string model_name = 1; + repeated Crop crops = 2; +} + +message Prediction { + int32 x1 = 1; + int32 y1 = 2; + int32 x2 = 3; + int32 y2 = 4; + string label = 5; // lowercased label + float confidence = 6; // 0..1 +} + +message ClassifyResponse { + repeated Prediction preds = 1; +} + +service ClassifierService { + rpc Classify(ClassifyRequest) returns (ClassifyResponse); +} diff --git a/services/security/agguard/proto/mega_detector.proto b/services/security/agguard/proto/mega_detector.proto new file mode 100644 index 000000000..4477399d9 --- /dev/null +++ b/services/security/agguard/proto/mega_detector.proto @@ -0,0 +1,26 @@ +syntax = "proto3"; + +package agguard.proto; + +message ImageRequest { + string image_path = 1; // path in mounted volume, e.g., /data/frames/dev_a/frame_00116.jpg + bytes image_bytes = 2; // optional inline bytes +} + +message Detection { + string cls = 1; + float conf = 2; + float x1 = 3; + float y1 = 4; + float x2 = 5; + float y2 = 6; +} + +message DetectionResponse { + repeated Detection detections = 1; + double inference_time = 2; +} + +service MegaDetector { + rpc Detect (ImageRequest) returns (DetectionResponse); +} diff --git a/services/security/agguard/proto_gen/__init__.py b/services/security/agguard/proto_gen/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/specialists/__init__.py b/services/security/agguard/specialists/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/specialists/animal_service/Dockerfile.animal-classifier b/services/security/agguard/specialists/animal_service/Dockerfile.animal-classifier new file mode 100644 index 000000000..a4e70176e --- /dev/null +++ b/services/security/agguard/specialists/animal_service/Dockerfile.animal-classifier @@ -0,0 +1,97 @@ +############################ +# Animal Classifier — YOLO-CLS gRPC microservice +# Auto-builds gRPC stubs (reusing mask-classifier.proto) +############################ +FROM python:3.12-slim + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + PIP_NO_CACHE_DIR=1 \ + OMP_NUM_THREADS=1 \ + OPENBLAS_NUM_THREADS=1 \ + MKL_NUM_THREADS=1 \ + OPENCV_OPENCL_RUNTIME=disabled + +# ──────────────────────────────── +# System libs for OpenCV / PyTorch +# ──────────────────────────────── +RUN apt-get update && apt-get install -y --no-install-recommends \ + libglib2.0-0 \ + libgl1 \ + libstdc++6 \ + ca-certificates \ + && rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +# ──────────────────────────────── +# Python dependencies +# ──────────────────────────────── +# Your requirements.txt should include: +# torch, ultralytics, opencv-python-headless, pillow, +# grpcio, grpcio-tools, protobuf, numpy, etc. +COPY agguard/specialists/animal_service/requirements.txt . + +RUN --mount=type=cache,target=/root/.cache/pip \ + python -m pip install --upgrade pip==25.0.1 && \ + pip install --no-cache-dir -r requirements.txt \ + --extra-index-url https://download.pytorch.org/whl/cpu + + + +# ──────────────────────────────── +# App source code +# ──────────────────────────────── +COPY agguard ./agguard + +# ──────────────────────────────── +# Weights (YOLO-CLS) +# ──────────────────────────────── +RUN mkdir -p /app/weights +# Optional: copy pretrained YOLO-CLS weights if stored locally +COPY weights/yolov8n-cls.pt /app/weights/yolov8n-cls.pt +RUN test -f /app/weights/yolov8n-cls.pt && echo "✅ YOLO-CLS weights present" || echo "ℹ️ YOLO-CLS weights will be mounted at runtime" + +# ──────────────────────────────── +# gRPC stub generation +# ──────────────────────────────── +RUN mkdir -p agguard/proto && touch agguard/proto/__init__.py + +# Generate stubs from mask-classifier.proto (shared proto) +RUN python -m grpc_tools.protoc \ + -I agguard/proto \ + --python_out=agguard/proto \ + --grpc_python_out=agguard/proto \ + mask_classifier.proto + +# Patch imports to be package-relative (so "from . import X_pb2") +RUN python - <<'PY' +from pathlib import Path +import re +p = Path("agguard/proto/mask_classifier_pb2_grpc.py") +if p.exists(): + s = p.read_text(encoding="utf-8") + s2 = re.sub(r'(?m)^import (\w+_pb2)\b', r'from . import \1', s) + if s2 != s: + p.write_text(s2, encoding="utf-8") + print("patched", p) + else: + print("no patch needed", p) +else: + print("mask_classifier_pb2_grpc.py not found; proto may be missing") +PY + +# ──────────────────────────────── +# Service defaults +# ──────────────────────────────── +ENV PORT=50064 \ + MODEL_PATH=/app/weights/yolov8n-cls.pt \ + DEVICE=cpu \ + MODEL_NAME=yolo-cls + +EXPOSE 50064 + +# ──────────────────────────────── +# Entrypoint +# ──────────────────────────────── +CMD ["python", "-m", "agguard.specialists.animal_service.server"] diff --git a/services/security/agguard/specialists/animal_service/requirements.txt b/services/security/agguard/specialists/animal_service/requirements.txt new file mode 100644 index 000000000..fdeb34e04 --- /dev/null +++ b/services/security/agguard/specialists/animal_service/requirements.txt @@ -0,0 +1,15 @@ +# ─── Core deep learning and vision ─── +torch==2.2.2+cpu +torchvision==0.17.2+cpu +ultralytics==8.3.0 +pillow==10.4.0 + +# ─── gRPC and protobuf ─── +grpcio==1.62.2 +grpcio-tools==1.62.2 +protobuf==4.25.3 + +prometheus_client +psutil + + diff --git a/services/security/agguard/specialists/animal_service/server.py b/services/security/agguard/specialists/animal_service/server.py new file mode 100644 index 000000000..2a2782df5 --- /dev/null +++ b/services/security/agguard/specialists/animal_service/server.py @@ -0,0 +1,135 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Animal Classifier microservice — reusing mask-classifier.proto. +Maps model class names (e.g., "american_black_bear", "sloth_bear") +to unified labels (e.g., "bear"). Unrecognized classes → "other". +Now includes Prometheus metrics and system monitoring. +""" + +from __future__ import annotations +import io, os, time, grpc +from concurrent import futures +from PIL import Image +from ultralytics import YOLO +from agguard.proto import mask_classifier_pb2 as pb2 +from agguard.proto import mask_classifier_pb2_grpc as pb2_grpc + +# ───────────────────────────────────────────── +# Prometheus metrics import +# ───────────────────────────────────────────── +from agguard.metrics.monitoring import ( + start_metrics_server, + INFER_REQUESTS, INFER_ERRORS, INFER_LATENCY, MODEL_LOAD_SEC +) + + +class AnimalClassifierServicer(pb2_grpc.ClassifierServiceServicer): + def __init__(self): + model_path = os.getenv("MODEL_PATH", "/app/weights/yolov8n-cls.pt") + print(f"[AnimalClassifier] 🔹 Loading {model_path} ...") + t0 = time.time() + + self.model = YOLO(model_path) + load_time = time.time() - t0 + MODEL_LOAD_SEC.labels(service="animal_classifier").set(load_time) + print(f"[AnimalClassifier] ✅ Model loaded in {load_time:.1f}s") + + # ───────────────────────────────────────────── + # Class mapping + # ───────────────────────────────────────────── + self.label_map = { + # Bears + "american_black_bear": "bear", + "sloth_bear": "bear", + "brown_bear": "bear", + "gibbon": "bear", + "siamang": "bear", + "velvet": "bear", + "colobus": "bear", + "indri": "bear", + "howler_monkey": "bear", + "capuchin":"bear", + # Foxes + "red_fox": "fox", + "grey_fox": "fox", + "kit_fox": "fox", + "white_wolf": "fox", + "kuvasz": "fox", + "dugong": "fox", + "arctic_fox": "fox", + "fox_squirrel": "fox", + "hog": "fox", + "tusker": "fox", + "mink": "fox", + "jay": "fox", + # Others + "wild_boar": "boar", + "wolf": "wolf", + "deer": "deer", + "rabbit": "rabbit", + } + self.intruding = set(self.label_map.values()) + + def _predict(self, jpeg: bytes): + img = Image.open(io.BytesIO(jpeg)).convert("RGB") + res = self.model.predict(img, verbose=False)[0] + idx = res.probs.top1 + conf = float(res.probs.top1conf.item()) + raw_label = res.names[idx].lower().strip() + + label = self.label_map.get(raw_label, "other") + if label not in self.intruding: + label = "other" + + print(f"[AnimalClassifier] raw={raw_label}, mapped={label}, conf={conf:.3f}") + return label, conf + + def Classify(self, request, context): + INFER_REQUESTS.labels(service="animal_classifier").inc() + t0 = time.time() + preds = [] + try: + for crop in request.crops: + try: + label, conf = self._predict(crop.jpeg) + except Exception as e: + INFER_ERRORS.labels(service="animal_classifier").inc() + context.set_code(grpc.StatusCode.INTERNAL) + context.set_details(f"Failed to classify crop: {e}") + return pb2.ClassifyResponse() + preds.append(pb2.Prediction( + label=label, + confidence=conf, + x1=crop.x1, y1=crop.y1, x2=crop.x2, y2=crop.y2, + )) + except Exception as e: + INFER_ERRORS.labels(service="animal_classifier").inc() + context.set_code(grpc.StatusCode.INTERNAL) + context.set_details(str(e)) + return pb2.ClassifyResponse() + + dt = time.time() - t0 + INFER_LATENCY.labels(service="animal_classifier").observe(dt) + + print(f"[AnimalClassifier] → {len(preds)} predictions in {dt:.2f}s") + return pb2.ClassifyResponse(preds=preds) + + +def serve(): + port = int(os.getenv("PORT", "50064")) + metrics_port = int(os.getenv("METRICS_PORT", "8008")) + + start_metrics_server() + print(f"[AnimalClassifier] 📊 Metrics exposed on :{metrics_port}/metrics") + + server = grpc.server(futures.ThreadPoolExecutor(max_workers=2)) + pb2_grpc.add_ClassifierServiceServicer_to_server(AnimalClassifierServicer(), server) + server.add_insecure_port(f"[::]:{port}") + print(f"[AnimalClassifier] 🚀 gRPC server running on port {port}") + server.start() + server.wait_for_termination() + + +if __name__ == "__main__": + serve() diff --git a/services/security/agguard/specialists/anomalies_service/Dockerfile.anomalies-classifier b/services/security/agguard/specialists/anomalies_service/Dockerfile.anomalies-classifier new file mode 100644 index 000000000..a92b67060 --- /dev/null +++ b/services/security/agguard/specialists/anomalies_service/Dockerfile.anomalies-classifier @@ -0,0 +1,72 @@ +# Dockerfile.anomalies-classifier + +FROM python:3.12-slim + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + PIP_NO_CACHE_DIR=1 \ + OMP_NUM_THREADS=1 + +WORKDIR /app + +# System libs (OpenCV runtime deps) +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates libglib2.0-0 libgl1 \ + && rm -rf /var/lib/apt/lists/* + +# --- Python deps --- +# 1) Pin NumPy to 1.x BEFORE torch/open_clip to avoid ABI mismatch +# 2) Then base libs, then torch CPU wheels, then open_clip_torch +# 3) FINAL GUARD: force-reinstall numpy==1.26.4 and fail build if not 1.26.x +RUN --mount=type=cache,target=/root/.cache/pip \ + python -m pip install --upgrade pip && \ + pip install --no-cache-dir "numpy==1.26.4" && \ + pip install --no-cache-dir \ + grpcio grpcio-tools "protobuf>=4.24" \ + pillow \ + opencv-python-headless \ + psutil prometheus-client && \ + pip install --no-cache-dir \ + torch==2.2.2+cpu torchvision==0.17.2+cpu --index-url https://download.pytorch.org/whl/cpu && \ + pip install --no-cache-dir open_clip_torch && \ + pip install --no-cache-dir --upgrade --force-reinstall "numpy==1.26.4" && \ + python -c "import numpy as np, sys; print('NumPy(final)=', np.__version__); sys.exit(0 if np.__version__.startswith('1.26.') else 1)" + +# --- App code & proto sources --- +COPY agguard agguard +COPY agguard/proto agguard/proto + +# Ensure packages are importable +RUN mkdir -p agguard && touch agguard/__init__.py && touch agguard/proto/__init__.py + +# Compile stubs using the EXISTING generic proto (shared Crop→Prediction schema) +RUN python -m grpc_tools.protoc \ + -I agguard/proto \ + --python_out=agguard/proto \ + --grpc_python_out=agguard/proto \ + agguard/proto/mask_classifier.proto && \ + python -c "from pathlib import Path; import re; p=Path('agguard/proto/mask_classifier_pb2_grpc.py'); s=p.read_text(); s2=re.sub(r'(?m)^import (\\w+_pb2)\\b', r'from . import \\1', s); p.write_text(s2)" + +# --- Service configuration (override in docker-compose if desired) --- +# --- Service configuration (override in docker-compose if desired) --- +ENV PORT=50062 \ + DEVICE=cpu \ + CLIP_MODEL=RN50 \ + CLIP_PRETRAINED=openai \ + CLIP_INPUT_SIZE=224 \ + CLIP_BATCH=32 \ + CLIP_AGGREGATE=meanmax \ + CLIP_LABELS="normal activity,climbing a fence" \ + CLIP_TEMPLATES="a CCTV frame of {},a surveillance video of {},a low-resolution photo of {},a person {},an action of {},a person is {}" \ + CLIP_THRESHOLDS="normal activity:0.30,climbing a fence:0.50" \ + ENABLE_MKLDNN=1 \ + NUM_THREADS=6 \ + CHANNELS_LAST=1 \ + PREPROCESS_CLAHE=1 \ + PREPROCESS_UNSHARP=1 + + +EXPOSE 50062 + +# Entry point (matches the copied server file) +CMD ["python", "-m", "agguard.specialists.anomalies_service.server"] diff --git a/services/security/agguard/specialists/anomalies_service/server.py b/services/security/agguard/specialists/anomalies_service/server.py new file mode 100644 index 000000000..3af07421a --- /dev/null +++ b/services/security/agguard/specialists/anomalies_service/server.py @@ -0,0 +1,197 @@ + + +from __future__ import annotations +import os, logging, warnings, time +from concurrent import futures +from typing import List, Tuple, Dict + +import numpy as np +import cv2 +import grpc +from PIL import Image +import torch +import open_clip + +from agguard.proto import mask_classifier_pb2 as pb +from agguard.proto import mask_classifier_pb2_grpc as pbrpc + +# ───────────────────────────────────────────── +# Prometheus metrics import +# ───────────────────────────────────────────── +from agguard.metrics.monitoring import ( + start_metrics_server, + INFER_REQUESTS, INFER_ERRORS, INFER_LATENCY, MODEL_LOAD_SEC +) + +log = logging.getLogger(__name__) +logging.basicConfig(level=os.environ.get("LOG_LEVEL", "INFO")) + +Box = Tuple[int, int, int, int] + +# --- tolerate either service name in generated stubs (ClassifierService|Classifier) --- +ServicerBase = getattr(pbrpc, "ClassifierServiceServicer", + getattr(pbrpc, "ClassifierServicer", None)) +if ServicerBase is None: + raise ImportError("No Classifier{Service}Servicer in mask_classifier_pb2_grpc.py") + +add_servicer = getattr(pbrpc, "add_ClassifierServiceServicer_to_server", + getattr(pbrpc, "add_ClassifierServicer_to_server", None)) +if add_servicer is None: + raise ImportError("No add_Classifier{Service}Servicer_to_server in mask_classifier_pb2_grpc.py") + + +def _jpeg_to_pil(jpeg_bytes: bytes, size: int) -> Image.Image: + """Decode JPEG -> RGB PIL image resized to model input.""" + arr = np.frombuffer(jpeg_bytes, dtype=np.uint8) + bgr = cv2.imdecode(arr, cv2.IMREAD_COLOR) + if bgr is None: + raise ValueError("Failed to decode JPEG") + bgr = cv2.resize(bgr, (size, size), interpolation=cv2.INTER_AREA) + rgb = cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB) + return Image.fromarray(rgb) + + +class ClipClassifierServicer(ServicerBase): + """ + gRPC service using OpenCLIP RN50 to estimate the probability that a given subject is climbing a fence. + Includes Prometheus monitoring. + """ + + def __init__(self): + service_name = "clip_classifier" + + # --- Environment configuration --- + self.model_name = os.environ.get("CLIP_MODEL", "RN50") + self.pretrained = os.environ.get("CLIP_PRETRAINED", "openai") + self.input_size = int(os.environ.get("CLIP_INPUT_SIZE", "224")) + self.temperature = float(os.environ.get("CLIP_TEMPERATURE", "100.0")) + self.batch_size = int(os.environ.get("CLIP_BATCH", "32")) + + device_env = os.environ.get("DEVICE") + self.device = torch.device(device_env if device_env else ("cuda" if torch.cuda.is_available() else "cpu")) + + # Optional performance flags + enable_mkldnn = os.environ.get("ENABLE_MKLDNN", "1").lower() not in ("0", "false") + num_threads = os.environ.get("NUM_THREADS") + if enable_mkldnn and self.device.type == "cpu": + torch.backends.mkldnn.enabled = True + if num_threads and self.device.type == "cpu": + torch.set_num_threads(int(num_threads)) + + warnings.filterwarnings("ignore", message="QuickGELU mismatch.*") + + # --- Load CLIP model --- + log.info("[CLIPClassifier] 🔹 Loading OpenCLIP model %s/%s ...", self.model_name, self.pretrained) + t0 = time.time() + self.model, _, self.preprocess = open_clip.create_model_and_transforms( + self.model_name, pretrained=self.pretrained + ) + self.tokenizer = open_clip.get_tokenizer(self.model_name) + self.model = self.model.to(self.device).eval() + load_time = time.time() - t0 + MODEL_LOAD_SEC.labels(service=service_name).set(load_time) + log.info("[CLIPClassifier] ✅ Model loaded in %.1fs on %s", load_time, self.device) + + self._emb_dim = getattr(self.model.visual, "output_dim", 1024) + self.service_name = service_name + + # ===================================================== + # 🔹 Encode helper + # ===================================================== + def _encode_images(self, images: List[Image.Image]) -> torch.Tensor: + if not images: + return torch.empty(0, self._emb_dim, device=self.device) + xs = [self.preprocess(im).unsqueeze(0) for im in images] + x = torch.cat(xs, dim=0).to(self.device) + with torch.inference_mode(): + feats = [] + for i in range(0, len(x), self.batch_size): + z = self.model.encode_image(x[i:i + self.batch_size]) + z = z / z.norm(dim=-1, keepdim=True) + feats.append(z) + return torch.cat(feats, dim=0) + + # ===================================================== + # 🔹 Classification logic + # ===================================================== + def _classify_one(self, image_emb: torch.Tensor, subject: str) -> float: + subj = (subject or "object").strip().lower() + positive_prompt = f"a {subj} climbing a fence" + negative_prompt = f"an image of a {subj} not climbing a fence" + + text_tokens = self.tokenizer([positive_prompt, negative_prompt]).to(self.device) + with torch.inference_mode(): + text_features = self.model.encode_text(text_tokens) + text_features /= text_features.norm(dim=-1, keepdim=True) + logits = (self.temperature * image_emb @ text_features.T).softmax(dim=-1) + prob_climbing = float(logits[0, 0].item()) + return prob_climbing + + # ===================================================== + # 🔹 gRPC entrypoint + # ===================================================== + def Classify(self, request: pb.ClassifyRequest, context) -> pb.ClassifyResponse: + INFER_REQUESTS.labels(service=self.service_name).inc() + t0 = time.time() + + try: + images: List[Image.Image] = [] + boxes: List[Box] = [] + subjects: List[str] = [] + + for c in request.crops: + try: + im = _jpeg_to_pil(c.jpeg, self.input_size) + images.append(im) + boxes.append((c.x1, c.y1, c.x2, c.y2)) + subj = getattr(c, "subject", "") or "object" + subjects.append(subj) + except Exception as e: + log.warning("[CLIPClassifier] Failed to decode crop: %s", e) + + resp = pb.ClassifyResponse() + if not images: + return resp + + img_emb = self._encode_images(images) + + for j, box in enumerate(boxes): + prob = self._classify_one(img_emb[j:j+1], subjects[j]) + label = f"{subjects[j]} climbing a fence" + resp.preds.add( + x1=box[0], y1=box[1], x2=box[2], y2=box[3], + label=label, + confidence=prob + ) + + dt = time.time() - t0 + INFER_LATENCY.labels(service=self.service_name).observe(dt) + log.info("[CLIPClassifier] → %d predictions in %.2fs", len(resp.preds), dt) + return resp + + except Exception as e: + INFER_ERRORS.labels(service=self.service_name).inc() + context.set_code(grpc.StatusCode.INTERNAL) + context.set_details(str(e)) + log.exception("[CLIPClassifier] Inference failed: %s", e) + return pb.ClassifyResponse() + + +def serve(): + port = int(os.environ.get("PORT", "50062")) + metrics_port = int(os.environ.get("METRICS_PORT", "8011")) + + # Start Prometheus metrics server + start_metrics_server() + log.info("[CLIPClassifier] 📊 Prometheus metrics exposed on :%d/metrics", metrics_port) + + server = grpc.server(futures.ThreadPoolExecutor(max_workers=2)) + add_servicer(ClipClassifierServicer(), server) + server.add_insecure_port(f"[::]:{port}") + log.info("[CLIPClassifier] 🚀 gRPC server listening on :%d", port) + server.start() + server.wait_for_termination() + + +if __name__ == "__main__": + serve() diff --git a/services/security/agguard/specialists/clients/animal.py b/services/security/agguard/specialists/clients/animal.py new file mode 100644 index 000000000..042e8ab19 --- /dev/null +++ b/services/security/agguard/specialists/clients/animal.py @@ -0,0 +1,114 @@ +from __future__ import annotations +import logging +from typing import List, Tuple, Optional +import cv2, numpy as np, grpc + +from agguard.proto import mask_classifier_pb2 as pb +from agguard.proto import mask_classifier_pb2_grpc as pbrpc + +log = logging.getLogger(__name__) +Box = Tuple[int, int, int, int] + +StubClass = getattr(pbrpc, "ClassifierServiceStub", + getattr(pbrpc, "ClassifierStub", None)) +if StubClass is None: + raise ImportError("mask_classifier_pb2_grpc missing ClassifierServiceStub/ClassifierStub") + + +class GrpcAnimalClassifierClient: + def __init__(self, address: str, model_name: str = "yolo-cls", + timeout_sec: float = 12.0, jpeg_quality: int = 85): + self.address = address + self.model_name = model_name + self.timeout = float(timeout_sec) + self.jpeg_quality = int(jpeg_quality) + + self._chan = grpc.insecure_channel(self.address, options=[ + ("grpc.max_send_message_length", 32 * 1024 * 1024), + ("grpc.max_receive_message_length", 32 * 1024 * 1024), + ]) + self._stub = StubClass(self._chan) + + log.info("GrpcAnimalClassifierClient -> %s (model=%s)", + self.address, self.model_name) + + # ─────────────────────────────────────────────── + # Padded crop extractor (20% padding) + # ─────────────────────────────────────────────── + @staticmethod + def _safe_crop(frame_bgr: np.ndarray, box: Box, + pad_ratio: float = 0.2) -> Optional[np.ndarray]: + """ + Return the crop with padding around the box (20% by default). + Clamps to frame boundaries. + """ + H, W = frame_bgr.shape[:2] + x1, y1, x2, y2 = map(int, box) + + # Original width/height + w = max(0, x2 - x1) + h = max(0, y2 - y1) + if w < 1 or h < 1: + return None + + # Compute padding + pad_x = int(w * pad_ratio) + pad_y = int(h * pad_ratio) + + # Expand bounding box + nx1 = max(0, x1 - pad_x) + ny1 = max(0, y1 - pad_y) + nx2 = min(W, x2 + pad_x) + ny2 = min(H, y2 + pad_y) + + if nx2 <= nx1 or ny2 <= ny1: + return None + + return frame_bgr[ny1:ny2, nx1:nx2] + + # ─────────────────────────────────────────────── + # Classify crops + # ─────────────────────────────────────────────── + def classify(self, frame_bgr: np.ndarray, boxes: List[Box]): + crops: List[pb.Crop] = [] + + for b in boxes: + # Use padded crop + crop = self._safe_crop(frame_bgr, b, pad_ratio=0.2) + if crop is None: + continue + + rgb = cv2.cvtColor(crop, cv2.COLOR_BGR2RGB) + ok, buf = cv2.imencode(".jpg", rgb, + [int(cv2.IMWRITE_JPEG_QUALITY), + self.jpeg_quality]) + if not ok: + continue + + # IMPORTANT: send original box (not padded box) + crops.append(pb.Crop( + jpeg=buf.tobytes(), + x1=b[0], y1=b[1], x2=b[2], y2=b[3] + )) + + if not crops: + return [] + + req = pb.ClassifyRequest(model_name=self.model_name, crops=crops) + + try: + resp = self._stub.Classify(req, timeout=self.timeout) + except Exception as e: + log.warning("gRPC classify failed (%s): %s", self.address, e) + return [] + + out = [] + for p in resp.preds: + out.append({ + "box": (p.x1, p.y1, p.x2, p.y2), + "label": p.label, + "confidence": p.confidence, + }) + + return out + diff --git a/services/security/agguard/specialists/clients/anomalies.py b/services/security/agguard/specialists/clients/anomalies.py new file mode 100644 index 000000000..025a9619a --- /dev/null +++ b/services/security/agguard/specialists/clients/anomalies.py @@ -0,0 +1,109 @@ + +from __future__ import annotations +from typing import List, Tuple, Optional +import cv2 +import grpc +from agguard.proto import mask_classifier_pb2 as pb +from agguard.proto import mask_classifier_pb2_grpc as pbrpc + +BBox = Tuple[int, int, int, int] + + +class GrpcClipClassifierClient: + """ + Client for the CLIP climbing classifier microservice. + + classify(frame_bgr, boxes, subjects=None) -> List[pb.Pred] + """ + + def __init__( + self, + address: str, + timeout_sec: float = 1.5, + jpeg_quality: int = 85, + padding_ratio: float = 0.8, # <── added padding support + ): + self.address = address + self.timeout = float(timeout_sec) + self.jpeg_quality = int(jpeg_quality) + self.padding_ratio = float(padding_ratio) + + self.channel = grpc.insecure_channel(address) + self.stub = ( + pbrpc.ClassifierServiceStub(self.channel) + if hasattr(pbrpc, "ClassifierServiceStub") + else pbrpc.ClassifierStub(self.channel) + ) + + # ------------------------------------------------------------- + # 🔹 Encode crop with proportional padding + # ------------------------------------------------------------- + def _encode_crop(self, frame_bgr, box: BBox) -> bytes: + h, w = frame_bgr.shape[:2] + x1, y1, x2, y2 = box + + bw = x2 - x1 + bh = y2 - y1 + + # proportional padding + pad_w = int(bw * self.padding_ratio) + pad_h = int(bh * self.padding_ratio) + + # padded box + px1 = max(0, x1 - pad_w) + py1 = max(0, y1 - pad_h) + px2 = min(w, x2 + pad_w) + py2 = min(h, y2 + pad_h) + + crop = frame_bgr[py1:py2, px1:px2] + if crop.size == 0: + return b"" + + ok, buf = cv2.imencode( + ".jpg", crop, + [int(cv2.IMWRITE_JPEG_QUALITY), self.jpeg_quality] + ) + return bytes(buf) if ok else b"" + + # ------------------------------------------------------------- + # 🔹 gRPC call wrapper + # ------------------------------------------------------------- + def classify(self, frame_bgr, boxes: List[BBox], subjects: Optional[List[str]] = None): + req = pb.ClassifyRequest() + subs = list(subjects) if subjects else ["object"] * len(boxes) + + # ensure equal length + if len(subs) < len(boxes): + subs += ["object"] * (len(boxes) - len(subs)) + elif len(subs) > len(boxes): + subs = subs[:len(boxes)] + + for i, b in enumerate(boxes): + jpeg = self._encode_crop(frame_bgr, b) + if not jpeg: + continue + + c = req.crops.add( + x1=int(b[0]), y1=int(b[1]), + x2=int(b[2]), y2=int(b[3]), + jpeg=jpeg + ) + + if hasattr(c, "subject"): + setattr(c, "subject", subs[i]) + + resp = self.stub.Classify(req, timeout=self.timeout) + + # tolerate any response field name + if hasattr(resp, "detections"): + preds = list(resp.detections) + elif hasattr(resp, "preds"): + preds = list(resp.preds) + elif hasattr(resp, "results"): + preds = list(resp.results) + else: + import logging + logging.warning(f"[GrpcClipClassifierClient] Unknown response fields: {resp}") + preds = [] + + return preds diff --git a/services/security/agguard/specialists/clients/mask.py b/services/security/agguard/specialists/clients/mask.py new file mode 100644 index 000000000..3d016766d --- /dev/null +++ b/services/security/agguard/specialists/clients/mask.py @@ -0,0 +1,74 @@ +from __future__ import annotations +import logging +from typing import List, Tuple, Optional, Any, Dict +from dataclasses import dataclass +import cv2, numpy as np, grpc + +from agguard.proto import mask_classifier_pb2 as pb +from agguard.proto import mask_classifier_pb2_grpc as pbrpc +from agguard.specialists.mask_service.mask_classifier import MaskPrediction + +log = logging.getLogger(__name__) +Box = Tuple[int, int, int, int] + + +# tolerate either service name in compiled stubs +StubClass = getattr(pbrpc, "ClassifierServiceStub", getattr(pbrpc, "ClassifierStub", None)) +if StubClass is None: + raise ImportError("mask_classifier_pb2_grpc missing ClassifierServiceStub/ClassifierStub") + +class GrpcMaskClassifierClient: + def __init__(self, address: str, model_name: str = "mask", + timeout_sec: float = 1.5, jpeg_quality: int = 85): + self.address = address + self.model_name = model_name + self.timeout = float(timeout_sec) + self.jpeg_quality = int(jpeg_quality) + self._chan = grpc.insecure_channel(self.address, options=[ + ("grpc.max_send_message_length", 32 * 1024 * 1024), + ("grpc.max_receive_message_length", 32 * 1024 * 1024), + ]) + self._stub = StubClass(self._chan) + log.info("GrpcMaskClassifierClient -> %s (model=%s)", self.address, self.model_name) + + @staticmethod + def _safe_crop(frame_bgr: np.ndarray, box: Box) -> Optional[np.ndarray]: + h, w = frame_bgr.shape[:2] + x1, y1, x2, y2 = map(int, box) + x1 = max(0, min(w-1, x1)); x2 = max(0, min(w-1, x2)) + y1 = max(0, min(h-1, y1)); y2 = max(0, min(h-1, y2)) + if x2 <= x1 or y2 <= y1: + return None + return frame_bgr[y1:y2, x1:x2] + + def classify(self, frame_bgr: np.ndarray, boxes: List[Box]) -> List[MaskPrediction]: + crops: List[pb.Crop] = [] + for b in boxes: + crop = self._safe_crop(frame_bgr, b) + if crop is None: + continue + rgb = cv2.cvtColor(crop, cv2.COLOR_BGR2RGB) + ok, buf = cv2.imencode(".jpg", rgb, [int(cv2.IMWRITE_JPEG_QUALITY), self.jpeg_quality]) + if not ok: + continue + crops.append(pb.Crop(jpeg=buf.tobytes(), x1=b[0], y1=b[1], x2=b[2], y2=b[3])) + + if not crops: + return [] + + req = pb.ClassifyRequest(model_name=self.model_name, crops=crops) + try: + resp = self._stub.Classify(req, timeout=self.timeout) + except Exception as e: + log.warning("gRPC classify failed (%s): %s", self.address, e) + return [] + + out: List[MaskPrediction] = [] + for p in resp.preds: + out.append(MaskPrediction( + box=(p.x1, p.y1, p.x2, p.y2), + label=p.label.lower().strip(), + confidence=float(p.confidence), + raw={} + )) + return out diff --git a/services/security/agguard/specialists/clients/megadetector.py b/services/security/agguard/specialists/clients/megadetector.py new file mode 100644 index 000000000..b41ad5cd7 --- /dev/null +++ b/services/security/agguard/specialists/clients/megadetector.py @@ -0,0 +1,38 @@ +from __future__ import annotations +import time, grpc, cv2 +import numpy as np +from agguard.core.types import Detection +from agguard.proto import mega_detector_pb2 as pb2 +from agguard.proto import mega_detector_pb2_grpc as pb2_grpc + + +class MegaDetectorClient: + def __init__(self, cfg: dict): + self.host = cfg.get("host", "mega-detector:50063") + self.timeout = float(cfg.get("timeout", 30.0)) + self.channel = grpc.insecure_channel(self.host) + self.stub = pb2_grpc.MegaDetectorStub(self.channel) + print(f"[MegaDetectorClient] Connected to {self.host}") + + def detect(self, frame_bgr: np.ndarray, roi_mask: np.ndarray | None = None): + if roi_mask is not None: + frame_bgr = cv2.bitwise_and(frame_bgr, frame_bgr, mask=roi_mask.astype(np.uint8)) + ok, buf = cv2.imencode(".jpg", frame_bgr) + if not ok: + return [] + + req = pb2.ImageRequest(image_bytes=buf.tobytes()) + try: + t0 = time.time() + resp = self.stub.Detect(req, timeout=self.timeout) + dt = time.time() - t0 + except grpc.RpcError as e: + print(f"[MegaDetectorClient] gRPC failed: {e.code().name} - {e.details()}") + return [] + + dets = [ + Detection(d.cls, d.conf, (int(d.x1), int(d.y1), int(d.x2), int(d.y2))) + for d in resp.detections + ] + print(f"[MegaDetectorClient] {len(dets)} detections in {dt:.2f}s") + return dets diff --git a/services/security/agguard/specialists/dispatch.py b/services/security/agguard/specialists/dispatch.py new file mode 100644 index 000000000..a01c70e68 --- /dev/null +++ b/services/security/agguard/specialists/dispatch.py @@ -0,0 +1,158 @@ +from __future__ import annotations +from typing import Dict, List, Callable, Any +import importlib +import logging + +from agguard.core.types import Detection, BBox + +log = logging.getLogger(__name__) + +# (frame_bgr, boxes, subjects=None) -> predictions +Specialist = Callable[[object, List[BBox], List[str] | None], object] + + +def _load(dotted_path: str): + mod, obj = dotted_path.rsplit(".", 1) + return getattr(importlib.import_module(mod), obj) + + +class ClassDispatch: + """ + Map class name -> [specialist callables]. + Each class can have multiple specialists (gRPC or local). + The dispatcher will call them all and unify their predictions. + """ + + def __init__(self, specs_cfg: List[dict]): + self._by_class: Dict[str, List[Specialist]] = {} + + for spec in specs_cfg or []: + cls_name = str(spec["for_class"]).lower() + + if "grpc" in spec: + grpc_cfg = spec["grpc"] or {} + kind = str(grpc_cfg.get("kind", "mask")).lower().strip() + address = grpc_cfg.get("address", "127.0.0.1:50061") + timeout = float(grpc_cfg.get("timeout_sec", 1.5)) + jpeg_q = int(grpc_cfg.get("jpeg_quality", 85)) + + if kind == "anomalies": + from agguard.specialists.clients.anomalies import GrpcClipClassifierClient + client = GrpcClipClassifierClient( + address=address, + timeout_sec=timeout, + jpeg_quality=jpeg_q, + ) + fn: Specialist = lambda frame, boxes, subjects=None, _c=client, _cls=cls_name: \ + _c.classify(frame, boxes, subjects or ([_cls])) + elif kind == "mask": + from agguard.specialists.clients.mask import GrpcMaskClassifierClient + client = GrpcMaskClassifierClient( + address=address, + model_name="mask", + timeout_sec=timeout, + jpeg_quality=jpeg_q, + ) + fn: Specialist = lambda frame, boxes, subjects=None, _c=client: \ + _c.classify(frame, boxes) + elif kind == "animal": + from agguard.specialists.clients.animal import GrpcAnimalClassifierClient + client = GrpcAnimalClassifierClient( + address=address, + model_name="yolo-cls", + timeout_sec=timeout, + jpeg_quality=jpeg_q, + ) + fn: Specialist = lambda frame, boxes, subjects=None, _c=client: \ + _c.classify(frame, boxes) + + self._by_class.setdefault(cls_name, []).append(fn) + log.info( + "Registered gRPC specialist for class '%s' -> %s (%s)", + cls_name, address, kind + ) + + + + else: + dotted = spec["dotted_path"] + ctor = _load(dotted) + inst = ctor(**(spec.get("kwargs") or {})) + + def _call(frame, boxes, subjects=None, _inst=inst): + try: + return _inst.classify(frame, boxes, subjects=subjects) + except TypeError: + return _inst.classify(frame, boxes) + + self._by_class.setdefault(cls_name, []).append(_call) + log.info( + "Registered local specialist for class '%s' -> %s", + cls_name, dotted + ) + + def run(self, frame_bgr, dets: List[Detection]) -> Dict[str, object]: + """ + For each detection class: + - Group boxes by class + - Call all specialists registered for that class + - Merge all their outputs into a unified list + """ + buckets: Dict[str, List[BBox]] = {} + for d in dets: + key = str(d.cls).lower() + if key in self._by_class: + buckets.setdefault(key, []).append(d.bbox) + + outputs: Dict[str, Any] = {} + for key, boxes in buckets.items(): + merged = [] + subjects = None#[key] * len(boxes) + + for fn in self._by_class.get(key, []): + try: + preds = fn(frame_bgr, boxes, subjects) or [] + if isinstance(preds, list): + merged.extend(preds) + else: + merged.append(preds) + except Exception as e: + log.exception("Specialist for '%s' failed: %s", key, e) + + # Unified merged predictions for that class + outputs[key] = merged + + + # ───────────────────────────────────────────── + # 🧩 CONDITIONAL SECOND-STAGE CALL + # ───────────────────────────────────────────── + if "animal" in outputs and outputs["animal"]: + intruding_preds = [ + p for p in outputs["animal"] + if isinstance(p, dict) and p.get("label") != "other" + ] + if intruding_preds: + subjects = [p["label"] for p in intruding_preds] + log.info("[ClassDispatch] Intruding animal(s): %s → checking climbing_fence", subjects) + + # 🧠 Call CLIP classifier only if configured + if "intruding animal" in self._by_class: + for fn in self._by_class["intruding animal"]: + try: + preds = fn(frame_bgr, [p["box"] for p in intruding_preds], subjects) + if preds: + # Store CLIP results under 'climbing_fence' + outputs["climbing_fence"] = preds + # Also propagate subjects so aggregator knows which animal climbed + outputs["_subject"] = subjects + log.info("[ClassDispatch] climbing_fence predictions: %s", preds) + except Exception as e: + log.exception("intruding-animal specialist failed: %s", e) + else: + log.debug("[ClassDispatch] No 'intruding animal' specialist configured.") + + + + return outputs + + diff --git a/services/security/agguard/specialists/mask_service/Dockerfile.mask-classifier b/services/security/agguard/specialists/mask_service/Dockerfile.mask-classifier new file mode 100644 index 000000000..a3e8e52e8 --- /dev/null +++ b/services/security/agguard/specialists/mask_service/Dockerfile.mask-classifier @@ -0,0 +1,82 @@ + +############################ +# Single-stage runtime (like your security Dockerfile's Stage 2) +############################ +FROM python:3.12-slim + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + PIP_NO_CACHE_DIR=1 \ + OMP_NUM_THREADS=1 \ + OPENBLAS_NUM_THREADS=1 \ + MKL_NUM_THREADS=1 \ + OPENCV_OPENCL_RUNTIME=disabled + +# System libs for OpenCV +RUN apt-get update && apt-get install -y --no-install-recommends \ + libglib2.0-0 \ + libgl1 \ + libstdc++6 \ + ca-certificates \ + && rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +# -------- Python deps -------- +# Your requirements.txt should include: onnxruntime, opencv-python-headless, numpy, +# grpcio, grpcio-tools, protobuf, etc. (same file as security uses) +COPY agguard/specialists/mask_service/requirements.txt . +RUN --mount=type=cache,target=/root/.cache/pip \ + python -m pip install --upgrade pip && \ + python -m pip install --no-cache-dir -r requirements.txt + +# -------- App sources -------- +COPY agguard agguard + +# -------- Weights (optional copy; you can also mount via compose) -------- +RUN mkdir -p /app/weights +# If you keep your mask model here in the repo, copy it in (adjust filename as needed) +# Otherwise, this line can stay and simply be ignored if the file doesn't exist at build time. +# To fail build when missing, keep the COPY; to ignore, comment it out. +# Example assumes you keep: weights/mask_yolov8.onnx +COPY weights/mask_yolov8.onnx /app/weights/mask_yolov8.onnx +# Optional build-time sanity check (won't fail if file absent; comment out '|| true' to enforce) +RUN test -f /app/weights/mask_yolov8.onnx && echo "✅ mask ONNX present" || echo "ℹ️ mask ONNX will be mounted at runtime" + +# -------- gRPC stubs (proto -> agguard/proto) -------- +RUN mkdir -p agguard/proto && touch agguard/proto/__init__.py + +# Generate stubs INTO the same package (like your security image) +RUN python -m grpc_tools.protoc \ + -I agguard/proto \ + --python_out=agguard/proto \ + --grpc_python_out=agguard/proto \ + mask_classifier.proto + +# Patch generated imports to be package-relative (X_pb2_grpc -> .X_pb2) +RUN python - <<'PY' +from pathlib import Path +import re +p = Path("agguard/proto/mask_classifier_pb2_grpc.py") +s = p.read_text(encoding="utf-8") +s2 = re.sub(r'(?m)^import (\w+_pb2)\b', r'from . import \1', s) +if s2 != s: + p.write_text(s2, encoding="utf-8") + print("patched", p) +else: + print("no patch needed", p) +PY + +# -------- Service defaults -------- +# Match server.py env usage; you can override via docker-compose +ENV PORT=50061 \ + BACKEND=onnx \ + MODEL_PATH=/app/weights/mask_yolov8.onnx \ + CLASSES="no_mask,mask" \ + IMGSZ=224 \ + DEVICE=cpu + +EXPOSE 50061 + +# Run the gRPC server (module path style, like your security CMD) +CMD ["python", "-m", "agguard.specialists.mask_service.server"] diff --git a/services/security/agguard/specialists/mask_service/mask_classifier.py b/services/security/agguard/specialists/mask_service/mask_classifier.py new file mode 100644 index 000000000..3298cbc48 --- /dev/null +++ b/services/security/agguard/specialists/mask_service/mask_classifier.py @@ -0,0 +1,260 @@ +# agguard/specialists/mask_service/mask_classifier.py +from __future__ import annotations +from dataclasses import dataclass +from typing import List, Tuple, Optional, Dict, Any +import os +import logging +import numpy as np +import cv2 + +log = logging.getLogger(__name__) + +Box = Tuple[int, int, int, int] + + +@dataclass(frozen=True) +class MaskPrediction: + box: Box + label: str # lowercased class name from the model + confidence: float # probability of that class + raw: Dict[str, Any] # backend-specific details (e.g., full probs) + + +def _ensure_rgb(bgr: np.ndarray) -> np.ndarray: + if bgr.ndim == 2: + bgr = cv2.cvtColor(bgr, cv2.COLOR_GRAY2BGR) + return cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB) + + +def _resize_square(img: np.ndarray, size: int) -> np.ndarray: + return cv2.resize(img, (size, size), interpolation=cv2.INTER_LINEAR) + + +def _softmax(x: np.ndarray, axis: int = -1) -> np.ndarray: + x = x - np.max(x, axis=axis, keepdims=True) + e = np.exp(x) + s = np.sum(e, axis=axis, keepdims=True) + return e / np.maximum(s, 1e-12) + + +class FaceMaskClassifier: + """ + Per-person classifier using a YOLOv8-cls model. + + Backends (must be specified explicitly): + - backend="torch": uses Ultralytics YOLO (expects *.pt) + - backend="onnx": uses onnxruntime (expects *.onnx) + + REQUIRED kwargs: + - model_path: str + - backend: "torch" | "onnx" + + OPTIONAL kwargs: + - imgsz: int (default 224) + - device: str (default "cpu") + - class_names: List[str] (REQUIRED for ONNX unless your app supplies a sidecar) + For torch, names are read from the YOLO model. + + API: + classify(frame_bgr, boxes) -> List[MaskPrediction] + """ + + def __init__( + self, + model_path: str, + backend: str, + imgsz: int = 224, + device: str = "cpu", + class_names: Optional[List[str]] = None, + ): + self.model_path = model_path + self.backend = backend.strip().lower() + self.imgsz = int(imgsz) + self.device = device + self._torch_model = None + self._onnx_session = None + self._onnx_input_name = None + self._class_names = class_names # For ONNX, you must pass this (or ship a sidecar & adjust code) + + if self.backend == "torch": + self._init_torch() + elif self.backend == "onnx": + self._init_onnx() + else: + raise ValueError("backend must be 'torch' or 'onnx' (no auto).") + + if not self._class_names or len(self._class_names) < 2: + raise ValueError( + "class_names must be resolvable. " + "For torch, they come from the Ultralytics model; " + "for onnx, pass class_names explicitly." + ) + + # Normalize class names to lowercase for consistent matching in Aggregator + self._class_names = [str(n).lower() for n in self._class_names] + log.info("FaceMaskClassifier initialized (backend=%s, classes=%s)", self.backend, self._class_names) + + # ----------------- backends ----------------- + + def _init_torch(self): + try: + from ultralytics import YOLO + except Exception as e: + raise RuntimeError("Ultralytics not available. Install with: pip install ultralytics") from e + + if not os.path.isfile(self.model_path): + raise FileNotFoundError(f"Model not found: {self.model_path}") + + self._torch_model = YOLO(self.model_path) + try: + names = getattr(self._torch_model, "names", None) + if isinstance(names, dict) and len(names) > 0: + self._class_names = [names[i] for i in range(len(names))] + except Exception: + pass + + # Try to place on device (Ultralytics handles fallback) + try: + self._torch_model.to(self.device) + except Exception: + pass + + def _init_onnx(self): + try: + import onnxruntime as ort + except Exception as e: + raise RuntimeError("onnxruntime not available. Install with: pip install onnxruntime") from e + + if not os.path.isfile(self.model_path): + raise FileNotFoundError(f"Model not found: {self.model_path}") + + self._onnx_session = ort.InferenceSession(self.model_path, providers=["CPUExecutionProvider"]) + inp = self._onnx_session.get_inputs()[0] + self._onnx_input_name = inp.name + + # For ONNX we require class_names from kwargs (keeps strict) + if not self._class_names: + raise ValueError("ONNX backend requires 'class_names' list (e.g., ['no_mask','mask']).") + + # Detect if the exported ONNX has a static batch size of 1 + shape = inp.shape # e.g. [1, 3, 224, 224] or [None, 3, 224, 224] + self._onnx_static_batch1 = False + if isinstance(shape, (list, tuple)) and len(shape) >= 1: + bdim = shape[0] + if isinstance(bdim, int) and bdim == 1: + self._onnx_static_batch1 = True + + # ----------------- public API ----------------- + + def classify(self, frame_bgr: np.ndarray, boxes: List[Box]) -> List[MaskPrediction]: + if not boxes: + return [] + + H, W = frame_bgr.shape[:2] + crops_rgb: List[np.ndarray] = [] + kept: List[Box] = [] + + for (x1, y1, x2, y2) in boxes: + X1 = max(0, min(W - 1, int(x1))) + Y1 = max(0, min(H - 1, int(y1))) + X2 = max(0, min(W - 1, int(x2))) + Y2 = max(0, min(H - 1, int(y2))) + if X2 <= X1 or Y2 <= Y1: + continue + crop = frame_bgr[Y1:Y2, X1:X2] + rgb = _ensure_rgb(crop) + rgb = _resize_square(rgb, self.imgsz) + crops_rgb.append(rgb) + kept.append((X1, Y1, X2, Y2)) + + if not crops_rgb: + return [] + + if self.backend == "torch": + return self._infer_torch(crops_rgb, kept) + else: + return self._infer_onnx(crops_rgb, kept) + + # ----------------- inference helpers ----------------- + + def _infer_torch(self, crops_rgb: List[np.ndarray], boxes: List[Box]) -> List[MaskPrediction]: + results = self._torch_model.predict( + source=crops_rgb, + imgsz=self.imgsz, + verbose=False, + device=self.device if hasattr(self._torch_model, "overrides") else None + ) + names = self._class_names + preds: List[MaskPrediction] = [] + + for b, r in zip(boxes, results): + if getattr(r, "probs", None) is None: + # Highly unlikely for YOLO-cls; fallback to uniform + probs = np.ones((len(names),), dtype=np.float32) / max(len(names), 1) + top1 = int(np.argmax(probs)) + conf = float(probs[top1]) + else: + probs = np.asarray(r.probs.data, dtype=np.float32) # (C,) + top1 = int(getattr(r.probs, "top1", int(np.argmax(probs)))) + conf = float(getattr(r.probs, "top1conf", probs[top1])) + + label = names[top1] if 0 <= top1 < len(names) else str(top1) + preds.append(MaskPrediction(box=b, label=label.lower(), confidence=conf, raw={ + "probs": probs.tolist(), + "top1": top1 + })) + return preds + + def _infer_onnx(self, crops_rgb: List[np.ndarray], boxes: List[Box]) -> List[MaskPrediction]: + import numpy as np + import onnxruntime as ort + + def _to_nchw(arr: np.ndarray) -> np.ndarray: + # (H, W, 3) RGB -> (1, 3, H, W) float32 in [0,1] + x = (arr.astype(np.float32) / 255.0).transpose(2, 0, 1)[None, ...] + return x + + names = self._class_names + preds: List[MaskPrediction] = [] + + if getattr(self, "_onnx_static_batch1", False): + # Run one-by-one (model expects batch dimension == 1) + for rgb, b in zip(crops_rgb, boxes): + X = _to_nchw(rgb) + outputs = self._onnx_session.run(None, {self._onnx_input_name: X}) + logits = outputs[0] + if logits.ndim == 1: + logits = logits[None, ...] # (1, C) + p = _softmax(logits, axis=-1)[0] + top1 = int(np.argmax(p)) + conf = float(p[top1]) + label = names[top1] if 0 <= top1 < len(names) else str(top1) + preds.append(MaskPrediction(box=b, label=label.lower(), confidence=conf, raw={ + "probs": p.tolist(), + "top1": top1 + })) + return preds + + # Vectorized path (dynamic batch models) + X = np.stack([ + np.transpose((c.astype(np.float32) / 255.0), (2, 0, 1)) + for c in crops_rgb + ], axis=0) # (N, 3, H, W) + + outputs = self._onnx_session.run(None, {self._onnx_input_name: X}) + logits = outputs[0] + if logits.ndim == 1: + logits = logits[None, ...] + probs = _softmax(logits, axis=-1) + + for i, b in enumerate(boxes): + p = probs[i] + top1 = int(np.argmax(p)) + conf = float(p[top1]) + label = names[top1] if 0 <= top1 < len(names) else str(top1) + preds.append(MaskPrediction(box=b, label=label.lower(), confidence=conf, raw={ + "probs": p.tolist(), + "top1": top1 + })) + return preds + diff --git a/services/security/agguard/specialists/mask_service/requirements.txt b/services/security/agguard/specialists/mask_service/requirements.txt new file mode 100644 index 000000000..90663ea1d --- /dev/null +++ b/services/security/agguard/specialists/mask_service/requirements.txt @@ -0,0 +1,7 @@ +grpcio>=1.64.0 +grpcio-tools>=1.64.0 +opencv-python-headless>=4.8.0.76 +numpy>=1.24.0 +onnxruntime>=1.16.0 +prometheus_client +psutil \ No newline at end of file diff --git a/services/security/agguard/specialists/mask_service/server.py b/services/security/agguard/specialists/mask_service/server.py new file mode 100644 index 000000000..10fefeeca --- /dev/null +++ b/services/security/agguard/specialists/mask_service/server.py @@ -0,0 +1,136 @@ +# agguard/specialists/mask_service/server.py +from __future__ import annotations +import os, logging, time +from concurrent import futures +from typing import List + +import cv2 +import numpy as np +import grpc + +from agguard.proto import mask_classifier_pb2 as pb +from agguard.proto import mask_classifier_pb2_grpc as pbrpc + +from agguard.specialists.mask_service.mask_classifier import FaceMaskClassifier, MaskPrediction + +# ───────────────────────────────────────────── +# Prometheus metrics import +# ───────────────────────────────────────────── +from agguard.metrics.monitoring import ( + start_metrics_server, + INFER_REQUESTS, INFER_ERRORS, INFER_LATENCY, MODEL_LOAD_SEC +) + +log = logging.getLogger(__name__) +logging.basicConfig(level=os.environ.get("LOG_LEVEL", "INFO")) + + +def _jpeg_to_rgb(j: bytes) -> np.ndarray: + arr = np.frombuffer(j, dtype=np.uint8) + img_bgr = cv2.imdecode(arr, cv2.IMREAD_COLOR) + if img_bgr is None: + raise ValueError("Failed to decode JPEG") + return cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB) + + +def _resize_square(rgb: np.ndarray, size: int) -> np.ndarray: + return cv2.resize(rgb, (size, size), interpolation=cv2.INTER_LINEAR) + + +# ───────────────────────────────────────────── +# tolerate either service name in generated stubs +# ───────────────────────────────────────────── +ServicerBase = getattr(pbrpc, "ClassifierServiceServicer", + getattr(pbrpc, "ClassifierServicer", None)) +if ServicerBase is None: + raise ImportError("No Classifier{Service}Servicer in mask_classifier_pb2_grpc.py") + +add_servicer = getattr(pbrpc, "add_ClassifierServiceServicer_to_server", + getattr(pbrpc, "add_ClassifierServicer_to_server", None)) +if add_servicer is None: + raise ImportError("No add_Classifier{Service}Servicer_to_server in mask_classifier_pb2_grpc.py") + + +class ClassifierService(ServicerBase): + def __init__(self, model: FaceMaskClassifier): + self.model = model + + def Classify(self, request: pb.ClassifyRequest, context) -> pb.ClassifyResponse: + service_name = "mask_classifier" + INFER_REQUESTS.labels(service=service_name).inc() + t0 = time.time() + + crops_rgb: List[np.ndarray] = [] + boxes = [] + for c in request.crops: + try: + rgb = _jpeg_to_rgb(c.jpeg) + rgb = _resize_square(rgb, self.model.imgsz) + crops_rgb.append(rgb) + boxes.append((c.x1, c.y1, c.x2, c.y2)) + except Exception as e: + log.warning("Failed to decode crop: %s", e) + + preds: List[MaskPrediction] = [] + try: + if crops_rgb: + if self.model.backend == "torch": + preds = self.model._infer_torch(crops_rgb, boxes) + else: + preds = self.model._infer_onnx(crops_rgb, boxes) + except Exception as e: + INFER_ERRORS.labels(service=service_name).inc() + context.set_code(grpc.StatusCode.INTERNAL) + context.set_details(str(e)) + return pb.ClassifyResponse() + + # Record latency metric + dt = time.time() - t0 + INFER_LATENCY.labels(service=service_name).observe(dt) + log.info("[MaskClassifier] → %d predictions in %.2fs", len(preds), dt) + + out = pb.ClassifyResponse() + for p in preds: + out.preds.add( + x1=p.box[0], y1=p.box[1], x2=p.box[2], y2=p.box[3], + label=p.label.lower(), confidence=float(p.confidence) + ) + return out + + +def serve(): + backend = os.environ.get("BACKEND", "onnx").lower() + model_path = os.environ.get("MODEL_PATH", "/app/weights/mask_yolov8.onnx") + imgsz = int(os.environ.get("IMGSZ", "224")) + device = os.environ.get("DEVICE", "cpu") + classes = os.environ.get("CLASSES") + class_names = [s.strip() for s in classes.split(",")] if classes else None + + log.info("[MaskClassifier] 🔹 Loading model: %s", model_path) + t0 = time.time() + model = FaceMaskClassifier( + model_path=model_path, backend=backend, imgsz=imgsz, device=device, class_names=class_names + ) + load_time = time.time() - t0 + MODEL_LOAD_SEC.labels(service="mask_classifier").set(load_time) + log.info("[MaskClassifier] ✅ Model loaded in %.1fs", load_time) + + port = int(os.environ.get("PORT", "50061")) + metrics_port = int(os.environ.get("METRICS_PORT", "8012")) + + # Start Prometheus metrics server + start_metrics_server() + log.info("[MaskClassifier] 📊 Prometheus metrics available at :%d/metrics", metrics_port) + + # Start gRPC server + server = grpc.server(futures.ThreadPoolExecutor(max_workers=2)) + add_servicer(ClassifierService(model), server) + server.add_insecure_port(f"[::]:{port}") + log.info("[MaskClassifier] 🚀 gRPC server listening on :%d", port) + server.start() + server.wait_for_termination() + + +if __name__ == "__main__": + serve() + diff --git a/services/security/agguard/specialists/megadetector_service/Dockerfile.mega-detector b/services/security/agguard/specialists/megadetector_service/Dockerfile.mega-detector new file mode 100644 index 000000000..efda2605b --- /dev/null +++ b/services/security/agguard/specialists/megadetector_service/Dockerfile.mega-detector @@ -0,0 +1,73 @@ +############################ +# Single-stage runtime image +############################ +FROM python:3.12-slim + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + PIP_NO_CACHE_DIR=1 \ + OMP_NUM_THREADS=1 \ + OPENBLAS_NUM_THREADS=1 \ + MKL_NUM_THREADS=1 \ + OPENCV_OPENCL_RUNTIME=disabled + +# System libs (same as others) +RUN apt-get update && apt-get install -y --no-install-recommends \ + libglib2.0-0 \ + libgl1 \ + libstdc++6 \ + ca-certificates \ + git \ + && rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +# -------- Python deps -------- +COPY agguard/specialists/megadetector_service/requirements.txt . +RUN --mount=type=cache,target=/root/.cache/pip \ + python -m pip install --upgrade pip && \ + python -m pip install --no-cache-dir torch==2.4.1+cpu torchvision==0.19.1+cpu torchaudio==2.4.1+cpu \ + --index-url https://download.pytorch.org/whl/cpu && \ + python -m pip install --no-cache-dir -r requirements.txt && \ + python -m pip install --no-cache-dir megadetector + + + +# -------- App sources -------- +COPY agguard agguard + +# -------- gRPC stubs (proto -> agguard/proto) -------- +RUN mkdir -p agguard/proto && touch agguard/proto/__init__.py +RUN python -m grpc_tools.protoc \ + -I agguard/proto \ + --python_out=agguard/proto \ + --grpc_python_out=agguard/proto \ + mega_detector.proto + +# Patch generated imports to relative (so imports work inside agguard package) +RUN python - <<'PY' +from pathlib import Path; import re +p = Path("agguard/proto/mega_detector_pb2_grpc.py") +if p.exists(): + s = p.read_text(encoding="utf-8") + s2 = re.sub(r'^import (mega_detector_pb2)', r'from . import \1', s, flags=re.M) + if s2 != s: + p.write_text(s2, encoding="utf-8") + print("patched", p) +PY + +# -------- Environment defaults -------- +ENV PORT=50063 \ + MODEL_NAME=MDV5A \ + DEVICE=cpu + +ENV PORT=50063 \ + METRICS_PORT=8007 \ + MODEL_NAME=MDV5A \ + DEVICE=cpu + +EXPOSE 50063 8007 + + +# -------- Launch gRPC service -------- +CMD ["python", "-m", "agguard.specialists.megadetector_service.server"] diff --git a/services/security/agguard/specialists/megadetector_service/__init__.py b/services/security/agguard/specialists/megadetector_service/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/security/agguard/specialists/megadetector_service/requirements.txt b/services/security/agguard/specialists/megadetector_service/requirements.txt new file mode 100644 index 000000000..a587197e4 --- /dev/null +++ b/services/security/agguard/specialists/megadetector_service/requirements.txt @@ -0,0 +1,10 @@ +numpy==1.26.4 +pillow +grpcio==1.62.2 +grpcio-tools==1.62.2 +protobuf==4.25.3 +requests +PyYAML==6.0.1 +prometheus-client +psutil + diff --git a/services/security/agguard/specialists/megadetector_service/server.py b/services/security/agguard/specialists/megadetector_service/server.py new file mode 100644 index 000000000..3dd50dbf9 --- /dev/null +++ b/services/security/agguard/specialists/megadetector_service/server.py @@ -0,0 +1,160 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +MegaDetector gRPC microservice — using the official Microsoft MDv5A model. + +✅ Prometheus metrics: + - Inference requests, errors, latency, model load time + - System CPU, process CPU/memory, GPU usage (from monitoring.py) +""" + +from __future__ import annotations +import io, os, time, grpc +from concurrent import futures +import numpy as np +from PIL import Image + +# ───────────────────────────────────────────── +# MegaDetector import (official Microsoft model) +# ───────────────────────────────────────────── +from megadetector.detection import run_detector + +# ───────────────────────────────────────────── +# Proto imports +# ───────────────────────────────────────────── +from agguard.proto import mega_detector_pb2 as pb2 +from agguard.proto import mega_detector_pb2_grpc as pb2_grpc + +# ───────────────────────────────────────────── +# Prometheus metrics (using your monitoring.py) +# ───────────────────────────────────────────── +from agguard.metrics.monitoring import ( + start_metrics_server, + INFER_REQUESTS, + INFER_ERRORS, + INFER_LATENCY, + MODEL_LOAD_SEC, +) + + +# ───────────────────────────────────────────── +# MegaDetector wrapper +# ───────────────────────────────────────────── +class SimpleMegaDetector: + """Wrapper around official MegaDetector (v5A or v6A).""" + + CATEGORY_MAP = {"1": "animal", "2": "person", "3": "vehicle"} + + def __init__(self, model_name: str = "MDV5A", conf: float = 0.2): + print(f"[MegaDetector] 🔹 Loading {model_name} ...") + t0 = time.time() + + # Load model (downloads automatically if needed) + self.model = run_detector.load_detector(model_name) + self.conf = conf + + load_time = time.time() - t0 + MODEL_LOAD_SEC.labels(service="megadetector").set(load_time) + print(f"[MegaDetector] ✅ Model loaded in {load_time:.1f}s") + + def detect(self, img: Image.Image) -> list[dict]: + """Run detection on a PIL image.""" + image_np = np.array(img) + result = self.model.generate_detections_one_image(image_np) + detections = [] + + for d in result.get("detections", []): + if d.get("conf", 0) < self.conf: + continue + bbox = d["bbox"] # normalized [x, y, w, h] + detections.append({ + "category": self.CATEGORY_MAP.get(str(d["category"]), str(d["category"])), + "conf": float(d["conf"]), + "bbox": bbox + }) + return detections + + +# ───────────────────────────────────────────── +# gRPC Servicer +# ───────────────────────────────────────────── +class MegaDetectorServicer(pb2_grpc.MegaDetectorServicer): + """gRPC servicer for MegaDetector.""" + + def __init__(self): + model_name = os.getenv("MODEL_NAME", "MDV5A") + conf_thresh = float(os.getenv("CONF_THRESH", "0.2")) + self.detector = SimpleMegaDetector(model_name=model_name, conf=conf_thresh) + + def Detect(self, request, context): + INFER_REQUESTS.labels(service="megadetector").inc() + t0 = time.time() + + # Load image + try: + if request.image_bytes: + img = Image.open(io.BytesIO(request.image_bytes)).convert("RGB") + elif request.image_path: + img = Image.open(request.image_path).convert("RGB") + else: + raise ValueError("No image provided") + except Exception as e: + INFER_ERRORS.labels(service="megadetector").inc() + context.set_code(grpc.StatusCode.INVALID_ARGUMENT) + context.set_details(f"Failed to load image: {e}") + return pb2.DetectionResponse() + + # Run inference + try: + detections_raw = self.detector.detect(img) + except Exception as e: + INFER_ERRORS.labels(service="megadetector").inc() + context.set_code(grpc.StatusCode.INTERNAL) + context.set_details(f"Inference failed: {e}") + return pb2.DetectionResponse() + + dt = time.time() - t0 + INFER_LATENCY.labels(service="megadetector").observe(dt) + + # Convert normalized → absolute coordinates + w, h = img.size + detections = [] + for det in detections_raw: + x, y, bw, bh = det["bbox"] + detections.append( + pb2.Detection( + cls=det["category"], + conf=det["conf"], + x1=x * w, y1=y * h, + x2=(x + bw) * w, y2=(y + bh) * h, + ) + ) + + print(f"[MegaDetector] → {len(detections)} detections in {dt:.2f}s") + return pb2.DetectionResponse(detections=detections, inference_time=dt) + + +# ───────────────────────────────────────────── +# Entrypoint +# ───────────────────────────────────────────── +def serve(): + port = int(os.getenv("PORT", "50063")) + metrics_port = int(os.getenv("METRICS_PORT", "8000")) + + # Start Prometheus metrics server (handles system/GPU collection) + start_metrics_server() + + print(f"[MegaDetector] 📊 Metrics exposed on :{metrics_port}/metrics") + + # Start gRPC server + server = grpc.server(futures.ThreadPoolExecutor(max_workers=2)) + pb2_grpc.add_MegaDetectorServicer_to_server(MegaDetectorServicer(), server) + server.add_insecure_port(f"[::]:{port}") + print(f"[MegaDetector] 🚀 gRPC server running on port {port}") + server.start() + server.wait_for_termination() + + +if __name__ == "__main__": + serve() + diff --git a/services/security/configs/default.yaml b/services/security/configs/default.yaml new file mode 100644 index 000000000..2460eabb7 --- /dev/null +++ b/services/security/configs/default.yaml @@ -0,0 +1,91 @@ + + +# video: "D:/p9.mp4" +#"C:/Users/yehud/Downloads/cars.mp4" +fit: "1280x720" # or null to keep native +roi: "0,0;1,0;1,1;0,1" # normalized polygon; or "full" +change_thresh: 0 +min_blob_area: 200 +morph_open: 3 +show_mask: false + +# used to construct clickable HLS URLs inside alerts +media_base: "http://media-proxy:8080" # or your public host +media_auth_token: "CHANGE_ME" + + +video: + bucket: imagery + prefix: security/incidents + fps: 9 + hls_segment_time: 0.5 + hls_list_size: 4000 + hls_use_cmaf: False + draw_thickness: 3 + +logging: + level: "INFO" # DEBUG|INFO|WARNING|ERROR + file: null # e.g., "agguard.log" + +detector: + backend: "onnx" + onnx: "weights/yolov8n.onnx" # we copied it here at build-time + conf: 0.4 + imgsz: 640 + roi_pad: 16 + names: + 1: animal # <- add at least the classes you route + 2: person + 3: vehicle + + + + +tracker: + iou_thresh: 0.2 + max_miss: 20 + ema: 0.8 + min_hits: 5 + high_conf: 0.6 + appearance_alpha: 0.8 + center_blend: 0.15 + + +specialists: + - for_class: "person" + grpc: + address: "mask-classifier:50061" + kind: "mask" + timeout_sec: 5 + + - for_class: "animal" + grpc: + address: "animal-classifier:50064" + kind: "animal" + timeout_sec: 6 + + - for_class: "intruding animal" + grpc: + address: "anomalies-classifier:50062" + kind: "anomalies" + timeout_sec: 6 + + + +minio: + endpoint: "localhost:9001" + access_key: "minioadmin" + secret_key: "minioadmin123" + secure: false + default_bucket: "imagery" + +s3: + # For AWS: set only region_name; credentials come from env/role by default + endpoint_url: "http://minio-hot:9000" + region_name: "us-east-1" + aws_access_key_id: "minioadmin" + aws_secret_access_key: "minioadmin123" + default_bucket: "imagery" + connect_timeout: 3.0 + read_timeout: 10.0 + max_attempts: 3 diff --git a/services/sensorAnomalyPro/.gitignore b/services/sensorAnomalyPro/.gitignore new file mode 100644 index 000000000..3f591f5ad --- /dev/null +++ b/services/sensorAnomalyPro/.gitignore @@ -0,0 +1,64 @@ +# Logs +*.log +*.crt +sensorAnomalyPro/reports/ +__pycache__/ +*.py[cod] +*$py.class + +# Distribution / packaging +build/ +dist/ +*.egg-info/ +.eggs/ + +# Virtual environments +.venv/ +venv/ +env/ +ENV/ +.conda/ +*.conda +*.ipynb_checkpoints + +# PyInstaller / py2exe artefacts +*.manifest +*.spec + +# Unit test / coverage reports +.pytest_cache/ +.coverage +coverage.xml +htmlcov/ +.tox/ +.nox/ +.mypy_cache/ +.dmypy.json +.pyre/ +.pytype/ + +# Logs +*.log + +# IDE / editor settings +.vscode/ +.idea/ +*.swp +*.swo + +# OS generated files +.DS_Store +Thumbs.db +desktop.ini + +# Jupyter notebooks (if you create some later) +.ipynb_checkpoints/ + +# Temporary files +*.tmp +*.bak +*.orig + +reports/ +sensorAnomalyPro/reports/ +**/reports/ diff --git a/services/sensorAnomalyPro/Dockerfile.flink b/services/sensorAnomalyPro/Dockerfile.flink new file mode 100644 index 000000000..801086691 --- /dev/null +++ b/services/sensorAnomalyPro/Dockerfile.flink @@ -0,0 +1,54 @@ +FROM flink:1.19.3-scala_2.12-java11 + + +# ---------- Root setup ---------- +USER root +COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt +RUN chmod 644 /usr/local/share/ca-certificates/netfree-ca.crt && update-ca-certificates + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV PIP_DISABLE_PIP_VERSION_CHECK=1 + +# ---------- Install Python + tools ---------- +RUN apt-get update && apt-get install -y \ + python3 python3-venv python3-pip curl \ + && rm -rf /var/lib/apt/lists/* + +# ---------- Add Flink Kafka connectors ---------- +RUN curl -fSL https://repo1.maven.org/maven2/org/apache/flink/flink-connector-kafka/3.2.0-1.19/flink-connector-kafka-3.2.0-1.19.jar \ + -o /opt/flink/lib/flink-connector-kafka-3.2.0-1.19.jar && \ + curl -fSL https://repo1.maven.org/maven2/org/apache/kafka/kafka-clients/3.7.0/kafka-clients-3.7.0.jar \ + -o /opt/flink/lib/kafka-clients-3.7.0.jar + +# ---------- Python virtual environment ---------- +RUN python3 -m venv /opt/venv +ENV PATH="/opt/venv/bin:$PATH" + +# ---------- Workdir ---------- +WORKDIR /opt/app + +# ---------- Copy dependencies first (for caching) ---------- +COPY requirements.txt /opt/app/requirements.txt + +# ---------- Install dependencies ---------- +RUN pip install --upgrade pip certifi \ + && pip install --prefer-binary apache-flink protobuf grpcio \ + && pip install -r /opt/app/requirements.txt + +# ---------- Copy application code ---------- +COPY . /opt/app/ + +RUN mkdir -p /opt/app/sensorAnomalyPro/reports/models && chown -R flink:flink /opt/app/sensorAnomalyPro && chmod -R 777 /opt/app/sensorAnomalyPro + + +# ---------- Flink environment variables ---------- +ENV PYFLINK_CLIENT_EXECUTABLE=/opt/venv/bin/python +ENV PYFLINK_PYTHON=/opt/venv/bin/python +ENV PYTHONPATH="/opt/app/sensorAnomalyPro:/opt/app:$PYTHONPATH" +ENV KAFKA_BROKERS=kafka:9092 +ENV IN_TOPIC=sensor-telemetry +ENV OUT_TOPIC=sensor_anomalies + +# ---------- Default command ---------- +CMD ["job-cluster", "--job-classname", "org.apache.flink.client.python.PythonDriver", "-py", "/opt/app/sensorAnomalyPro/app.py"] diff --git a/services/sensorAnomalyPro/README.md b/services/sensorAnomalyPro/README.md new file mode 100644 index 000000000..e41cfba47 --- /dev/null +++ b/services/sensorAnomalyPro/README.md @@ -0,0 +1,204 @@ +# Sensor Anomaly Detection +Real-time anomaly detection in environmental sensor data using Flink + Kafka + Python. + +This project continuously monitors IoT sensor streams (e.g., Soil Moisture, Ambient Temperature, Humidity) and detects anomalies using statistical baselines and streaming analytics. + +## Tech Stack +Python · Apache Flink · Apache Kafka · Docker · Pandas · Statsmodels + +## Features +- Cleans and validates incoming sensor data. +- Builds statistical baselines: + - Daily (hour of day) + - Weekly (day of week + hour) + - Seasonal (day of year + hour) +- Detects anomalies: + - Band — value outside baseline ± 2×std + - Spike — sudden jump between consecutive values + - Break — sustained deviation from baseline +- Exports results to: + - reports/anomalies_report.csv + - reports/plots/ + - reports/models/ (saved baseline profiles) + +## Project Structure +sensor-anomaly-pro/ +├─ analyze_sensors.py # Batch analysis on CSV data +├─ profiles_runtime.py # Baseline export & real-time scoring +├─ app.py # Flink streaming job (Kafka → detection → Kafka) +├─ requirements.txt +├─ Dockerfile +├─ data/ +│ └─ plant_health_data.csv +└─ tests/ + +## Environment Variables +| Variable | Description | Default | +|-----------|-------------|----------| +| KAFKA_BROKERS | Kafka broker address | kafka:9092 | +| IN_TOPIC | Input topic for raw telemetry | sensor-telemetry | +| OUT_TOPIC | Output topic for anomalies | sensor_anomalies | +| PYTHONPATH | Application base path | /opt/app/sensorAnomalyPro | + +## Local (Batch Mode) +py -3.12 -m venv .venv +.\.venv\Scripts\Activate.ps1 +python -m pip install -U pip setuptools wheel +python -m pip install -r requirements.txt + +Run analysis: +set DATA_PATH=./data/plant_health_data.csv # Windows +export DATA_PATH=./data/plant_health_data.csv # Linux/macOS +python analyze_sensors.py + +Run tests: +python -m pytest -q --maxfail=1 --disable-warnings --cov=. --cov-report=term-missing + +## Docker +docker build -t sensor-anomaly-pro . +docker run --rm -e DATA_PATH="/app/data/plant_health_data.csv" -v "${PWD}/data:/app/data" -v "${PWD}/reports:/app/reports" sensor-anomaly-pro python analyze_sensors.py + +## Real-Time Flow (Kafka + Flink) +The real-time pipeline connects Kafka and Flink for continuous anomaly detection. + +| Component | Description | +|------------|-------------| +| Kafka Broker (kafka) | Handles telemetry input and anomaly output topics. | +| Flink JobManager / TaskManager | Executes app.py (the streaming anomaly detection job). | +| sensorAnomalyPro/app.py | Python Flink job that consumes, processes, and produces results. | + +### Step-by-Step + +#### 1️ Build and Start Services +```bash +docker-compose up -d --build +``` + +#### 2️ Submit the Flink Job +```bash +docker exec -it flink-jobmanager flink run -py /opt/app/sensorAnomalyPro/app.py + +``` + +#### 3️ Send Sample Sensor Data +```bash +docker exec -i kafka kafka-console-producer.sh --bootstrap-server localhost:9092 --topic dev-robot-telemetry-raw +``` +Paste this: +```json + +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +PS C:\Users\user1\Desktop\AgCloud> docker exec -i kafka kafka-console-producer.sh --bootstrap-server localhost:9092 --topic dev-robot-telemetry-raw +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +PS C:\Users\user1\Desktop\AgCloud> docker exec -i kafka kafka-console-producer.sh --bootstrap-server localhost:9092 --topic dev-robot-telemetry-raw +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +PS C:\Users\user1\Desktop\AgCloud> docker exec -i kafka kafka-console-producer.sh --bootstrap-server localhost:9092 --topic dev-robot-telemetry-raw +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +PS C:\Users\user1\Desktop\AgCloud> docker exec -i kafka kafka-console-producer.sh --bootstrap-server localhost:9092 --topic dev-robot-telemetry-raw +PS C:\Users\user1\Desktop\AgCloud> docker exec -i kafka kafka-console-producer.sh --bootstrap-server localhost:9092 --topic dev-robot-telemetry-raw +PS C:\Users\user1\Desktop\AgCloud> docker exec -i kafka kafka-console-producer.sh --bootstrap-server localhost:9092 --topic dev-robot-telemetry-raw +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-10-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2025-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":55555555555588888888,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":555555555555555,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":555555555555555,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":37.2,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":555555555555555,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Ambient_Temperature","value":555555555555555,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":555555555555555,"lat":32.055,"lon":34.845} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Ambient_Temperature","value":55,"lat":32.045,"lon":34.835} +{"ts":"2024-11-02T12:00:00Z","plant_id":1,"sensor":"Soil_Moisture","value":32.1,"lat":32.048,"lon":34.836} +{"ts":"2024-11-02T12:00:05Z","plant_id":1,"sensor":"Ambient_Temperature","value":28.5,"lat":32.048,"lon":34.836} +{"ts":"2024-11-02T12:00:08Z","plant_id":2,"sensor":"Humidity","value":71.4,"lat":32.020,"lon":34.800} +{"ts":"2024-11-02T12:00:10Z","plant_id":2,"sensor":"Soil_Moisture","value":18.2,"lat":32.020,"lon":34.800} +{"ts":"2024-11-02T12:00:15Z","plant_id":3,"sensor":"Ambient_Temperature","value":44.9,"lat":32.090,"lon":34.910} +``` + +#### 4️ View Detected Anomalies +```bash +docker exec -it kafka kafka-console-consumer.sh --bootstrap-server kafka:9092 --topic sensor_zone_stats --from-beginning +docker exec -it kafka kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic sensor_anomalies --from-beginning +``` +Example output: +```json +{ + "plant_id": 1, + "sensor": "Soil_Moisture", + "ts": "2025-09-21T12:34:56Z", + "value": 37.2, + "result": { + "ok": true, + "is_anomaly": true, + "bl_type": "seasonal", + "baseline": 23.36, + "adaptive_baseline": 23.39, + "bias": 0.05, + "lower": 7.60, + "upper": 39.18, + "band_std": 7.89, + "flags": {"band": false, "spike": false, "break": true}, + "ema_abs_res": 13.83, + "ts": "2025-09-21 12:34:56+00:00" + } +} + +``` + +--- + +## Data Flow Diagram +``` + ┌──────────────┐ ┌────────────┐ ┌────────────────────────┐ + │ Sensors / IoT│ ---> │ Kafka Topic│ ---> │ Flink (app.py) detects │ + │ telemetry │ │sensor-telemetry│ │ anomalies │ + └──────────────┘ └────────────┘ └─────────────┬──────────┘ + │ + ▼ + Kafka Topic: sensor_anomalies +``` + +--- + +## Notes +- **IN_TOPIC** = `sensor-telemetry` +- **OUT_TOPIC** = `sensor_anomalies` +- Kafka + Flink must share the same network (e.g., `agcloud_mesh`). +- Rebuild after modifying `app.py`: + ```bash + docker-compose build jobmanager taskmanager + ``` + +--- + +## Troubleshooting +- Create topics manually if missing: + ```bash + docker exec -it kafka-single kafka-topics.sh --create --topic sensor-telemetry --bootstrap-server localhost:9092 --partitions 1 --replication-factor 1 + ``` +- View logs: + ```bash + docker logs flink-jobmanager + ``` + +--- + +## License +MIT +branch shiffi-flink-sensor-connection \ No newline at end of file diff --git a/services/sensorAnomalyPro/docker-compose.yml b/services/sensorAnomalyPro/docker-compose.yml new file mode 100644 index 000000000..bf4ac0fd4 --- /dev/null +++ b/services/sensorAnomalyPro/docker-compose.yml @@ -0,0 +1,85 @@ + + + + +version: "3.9" + +services: + sensor_anomaly_pro: + build: + context: ./sensorAnomalyPro + dockerfile: Dockerfile + container_name: sensor-anomaly-pro + volumes: + - ./sensorAnomalyPro/data:/app/data + - ./sensorAnomalyPro/reports:/app/reports + environment: + - DATA_PATH=/app/data/plant_health_data.csv + command: > + python analyze_sensors.py + networks: + - ag_cloud + + jobmanager: + build: + context: . + dockerfile: Dockerfile.flink + container_name: flink-jobmanager + command: > + bash -c " + /docker-entrypoint.sh jobmanager & + echo '⏳ Waiting for Flink JobManager startup...' && + sleep 10 && + echo '🕓 Waiting for reports to be generated...' && + while [ ! -d /opt/app/sensorAnomalyPro/reports ] || [ -z \"$(ls -A /opt/app/sensorAnomalyPro/reports 2>/dev/null)\" ]; do + echo ' ↳ reports directory empty, waiting...'; + sleep 5; + done && + echo '✅ Reports ready, submitting Flink job...' && + flink run -m localhost:8081 -py /opt/app/sensorAnomalyPro/app.py && + tail -f /dev/null" + depends_on: + - sensor_anomaly_pro + ports: + - "8081:8081" + environment: + - JOB_MANAGER_RPC_ADDRESS=jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=dev-robot-telemetry-raw + - OUT_TOPIC=sensor_anomalies + - ZONE_TOPIC=sensor_zone_stats + volumes: + - ./sensorAnomalyPro/reports:/opt/app/sensorAnomalyPro/reports:rw + restart: unless-stopped + networks: + - flink-net + - ag_cloud + + taskmanager: + build: + context: . + dockerfile: Dockerfile.flink + container_name: flink-taskmanager + command: taskmanager -D taskmanager.numberOfTaskSlots=4 + depends_on: + - jobmanager + environment: + - JOB_MANAGER_RPC_ADDRESS=jobmanager + - KAFKA_BROKERS=kafka:9092 + - IN_TOPIC=dev-robot-telemetry-raw + - OUT_TOPIC=sensor_anomalies + - ZONE_TOPIC=sensor_zone_stats + - taskmanager.numberOfTaskSlots=4 + volumes: + - ./sensorAnomalyPro/reports:/opt/app/sensorAnomalyPro/reports:rw + restart: unless-stopped + networks: + - flink-net + - ag_cloud + +networks: + flink-net: + driver: bridge + ag_cloud: + external: true + name: agcloud_ag_cloud diff --git a/services/sensorAnomalyPro/requirements.txt b/services/sensorAnomalyPro/requirements.txt new file mode 100644 index 000000000..12ce1818c --- /dev/null +++ b/services/sensorAnomalyPro/requirements.txt @@ -0,0 +1,15 @@ +pandas==2.2.2 +numpy==1.26.4 +matplotlib==3.8.4 +statsmodels==0.14.2 +scipy==1.11.4 +#fastapi==0.110.0 + + + +uvicorn==0.29.0 +scikit-learn==1.3.2 +joblib==1.3.2 +protobuf>=3.20.3,<5 +grpcio>=1.54.0 +shapely diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/Dockerfile b/services/sensorAnomalyPro/sensorAnomalyPro/Dockerfile new file mode 100644 index 000000000..0600f3286 --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/Dockerfile @@ -0,0 +1,30 @@ +# Dockerfile +FROM python:3.11-slim + +WORKDIR /app + +COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt + +RUN chmod 644 /usr/local/share/ca-certificates/netfree-ca.crt && update-ca-certificates + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV PIP_DISABLE_PIP_VERSION_CHECK=1 + +COPY requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt + +# Copy source +COPY analyze_sensors.py ./ +COPY profiles_runtime.py ./ + +COPY app.py ./ +COPY data/ ./data/ +COPY zones.geojson ./ +RUN mkdir -p /app/reports/plots + + +EXPOSE 8000 + +CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"] + diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/__init__.py b/services/sensorAnomalyPro/sensorAnomalyPro/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/analyze_sensors.py b/services/sensorAnomalyPro/sensorAnomalyPro/analyze_sensors.py new file mode 100644 index 000000000..329dbd11a --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/analyze_sensors.py @@ -0,0 +1,264 @@ +# analyze_sensors.py — robust version (no stuck/gap rules, improved safety) + +from pathlib import Path +import os +import numpy as np +import pandas as pd +import matplotlib.pyplot as plt +from statsmodels.tsa.holtwinters import ExponentialSmoothing +from scipy.stats import zscore +from profiles_runtime import export_profiles + +# ---------------- Config ---------------- +# Default to the uploaded dataset location; can be overridden by env var. +DATA_PATH = Path(os.getenv("DATA_PATH", "/mnt/data/plant_health_data.csv")) +OUT_DIR = Path("reports") +PLOTS_DIR = OUT_DIR / "plots" +PLOTS_DIR.mkdir(parents=True, exist_ok=True) + +SENSORS = ["Soil_Moisture", "Ambient_Temperature", "Humidity"] +VALID_RANGES = { + "Soil_Moisture": (0, 100), + "Humidity": (0, 100), + "Ambient_Temperature": (-30, 60), +} + +EPS_STD = 1e-6 + +# -------------- Helpers ----------------- +def _as_numeric(df: pd.DataFrame, col: str) -> pd.Series: + s = pd.to_numeric(df[col], errors="coerce") + return s + + +def read_and_clean(path: Path) -> pd.DataFrame: + if not path.exists(): + raise FileNotFoundError(f"Data file not found: {path}") + df = pd.read_csv(path) + + if "Timestamp" not in df.columns: + raise ValueError("CSV must contain a 'Timestamp' column") + + df["Timestamp"] = pd.to_datetime(df["Timestamp"], errors="coerce") + df = df.dropna(subset=["Timestamp"]) + + if "Plant_ID" not in df.columns: + df["Plant_ID"] = 1 + + for c, (lo, hi) in VALID_RANGES.items(): + if c in df.columns: + df[c] = _as_numeric(df, c) + df.loc[(df[c] < lo) | (df[c] > hi), c] = np.nan + + df = df.sort_values(["Plant_ID", "Timestamp"]).reset_index(drop=True) + return df + + +def _safe_std_by(grouped: pd.core.groupby.SeriesGroupBy) -> pd.Series: + std = grouped.std() + if std.notna().any(): + m = std.mean(skipna=True) + std = std.fillna(m if pd.notna(m) else 0.0) + else: + std = std.fillna(0.0) + std = std.clip(lower=EPS_STD) + return std + +# --------- Baselines --------- +def baseline_daily(d: pd.DataFrame, col: str) -> pd.DataFrame: + x = d[["Timestamp", col]].copy() + x["hod"] = x["Timestamp"].dt.hour + prof = x.groupby("hod")[col].median().reindex(range(24)).interpolate(limit_direction="both") + std = _safe_std_by(x.groupby("hod")[col]).reindex(range(24)).fillna(method="ffill").fillna(method="bfill") + out = x.copy() + out["baseline"] = out["hod"].map(prof) + out["band_std"] = out["hod"].map(std) + out["lower"] = out["baseline"] - 2 * out["band_std"] + out["upper"] = out["baseline"] + 2 * out["band_std"] + out = out.drop(columns=["hod"]) + out["bl_type"] = "daily" + return out + +def baseline_weekly(d: pd.DataFrame, col: str) -> pd.DataFrame: + x = d[["Timestamp", col]].copy() + x["dow"] = x["Timestamp"].dt.dayofweek # 0..6 + x["hod"] = x["Timestamp"].dt.hour # 0..23 + prof = x.groupby(["dow","hod"])[col].median().unstack() + prof = prof.reindex(index=range(7), columns=range(24)) + prof = prof.interpolate(axis=0, limit_direction="both").interpolate(axis=1, limit_direction="both") + std = _safe_std_by(x.groupby(["dow","hod"])[col]).unstack() + std = std.reindex(index=range(7), columns=range(24)) + std = std.fillna(method="ffill").fillna(method="bfill").fillna(EPS_STD) + + out = x.copy() + + dow_idx = out["dow"].to_numpy(dtype=int) + hod_idx = out["hod"].to_numpy(dtype=int) + prof_np = prof.to_numpy() + std_np = std.to_numpy() + out["baseline"] = prof_np[dow_idx, hod_idx] + out["band_std"] = std_np[dow_idx, hod_idx] + out["lower"] = out["baseline"] - 2 * out["band_std"] + out["upper"] = out["baseline"] + 2 * out["band_std"] + out = out.drop(columns=["dow","hod"]) + out["bl_type"] = "weekly" + return out + +def baseline_seasonal(d: pd.DataFrame, col: str) -> pd.DataFrame: + x = d[["Timestamp", col]].copy() + x["doy"] = x["Timestamp"].dt.dayofyear # 1..366 + x["hod"] = x["Timestamp"].dt.hour # 0..23 + doy_prof = x.groupby("doy")[col].median().reindex(range(1, 367)).interpolate(limit_direction="both") + hod_prof = x.groupby("hod")[col].median().reindex(range(24)).interpolate(limit_direction="both") + std_hod = ( + _safe_std_by(x.groupby("hod")[col]) + .reindex(range(24)) + .ffill() + .bfill() + ).clip(lower=EPS_STD) + out = x.copy() + out["baseline"] = 0.5 * out["doy"].map(doy_prof) + 0.5 * out["hod"].map(hod_prof) + out["band_std"] = out["hod"].map(std_hod) + out["lower"] = out["baseline"] - 2 * out["band_std"] + out["upper"] = out["baseline"] + 2 * out["band_std"] + out = out.drop(columns=["doy","hod"]) + out["bl_type"] = "seasonal" + return out + +# ---------------- Forecasts ---------------- +def short_forecast(series: pd.Series): + s = series.dropna() + if len(s) < 48: + return None + try: + if isinstance(s.index, pd.DatetimeIndex): + s = s.asfreq("H") + else: + s.index = pd.date_range(start=pd.Timestamp.now().floor("H") - pd.Timedelta(hours=len(s)-1), + periods=len(s), freq="H") + except Exception: + pass + + sp = 168 if len(s) >= 336 else 24 + try: + model = ExponentialSmoothing( + s, trend="add", seasonal="add", seasonal_periods=sp, initialization_method="estimated" + ).fit() + return model.forecast(sp) + except Exception: + return None + + +# ---------------- Anomalies ---------------- +def detect_flags(dfb: pd.DataFrame, col: str) -> pd.DataFrame: + y = dfb.copy() + + valid = y[col].notna() + y["residual"] = np.where(valid, y[col] - y["baseline"], np.nan) + + y["flag_band"] = np.where(valid, (y[col] < y["lower"]) | (y[col] > y["upper"]), False) + + diff = y[col].diff() + z = zscore(diff.fillna(0.0).to_numpy(), nan_policy="omit") + y["diff"] = diff + y["flag_spike"] = False + if z is not None and len(z) == len(y): + y["flag_spike"] = np.abs(pd.Series(z, index=y.index).fillna(0.0)) > 3.0 + + ma = y["residual"].abs().rolling(24, min_periods=12).mean() + + band_std = y["band_std"].fillna(EPS_STD).clip(lower=EPS_STD) + y["flag_break"] = (ma > (1.5 * band_std)).fillna(False) + + y["is_anomaly"] = y[["flag_band","flag_spike","flag_break"]].any(axis=1) + return y + +# ---------------- Plotting ---------------- +def plot_one(dfp: pd.DataFrame, col: str, plant, label: str): + + if dfp[col].notna().sum() == 0: + return + + low = dfp["lower"].fillna(dfp["baseline"]) + up = dfp["upper"].fillna(dfp["baseline"]) + + plt.figure(figsize=(12, 5)) + plt.plot(dfp["Timestamp"], dfp[col], label=col) + plt.plot(dfp["Timestamp"], dfp["baseline"], label=f"baseline ({label})", linewidth=2) + plt.fill_between(dfp["Timestamp"], low, up, alpha=0.2, label="band") + anom = dfp[dfp["is_anomaly"] & dfp[col].notna()] + if not anom.empty: + plt.scatter(anom["Timestamp"], anom[col], marker="x", s=36, label="anomaly") + plt.title(f"Plant {plant} — {col} — {label}") + plt.xlabel("Time"); plt.ylabel(col) + plt.legend(); plt.tight_layout() + out = PLOTS_DIR / f"plant{plant}_{col}_{label}.png" + plt.savefig(out); plt.close() + +# ---------------- Main ---------------- +def main(): + print(f"Reading data from: {DATA_PATH}") + df = read_and_clean(DATA_PATH) + export_profiles(df) + plants = df["Plant_ID"].dropna().unique().tolist() + if not plants: + print(" No Plant_ID values found.") + return + print(f"Found {len(plants)} plants/sensors: {plants[:10]}{'...' if len(plants)>10 else ''}") + out_rows = [] + + if os.getenv("EXPORT_PROFILES", "0") == "1": + try: + + export_profiles(df) + print(" Exported runtime profiles to reports/models/") + except Exception as e: + print(f" Failed to export profiles: {e}") + + for plant in plants: + d0 = df[df["Plant_ID"] == plant].copy() + for col in SENSORS: + if col not in d0.columns: + continue + d0[col] = _as_numeric(d0, col) + d = d0[["Timestamp", col]].dropna().copy() + if d.empty: + continue + + bl_daily = baseline_daily(d, col) + bl_weekly = baseline_weekly(d, col) if len(d) >= 24*7 else None + bl_season = baseline_seasonal(d, col) if d["Timestamp"].dt.year.nunique() >= 2 or len(d) >= 24*60 else None + + _ = short_forecast(d[col]) + + for bl, name in ((bl_daily, "daily"), (bl_weekly, "weekly"), (bl_season, "seasonal")): + if bl is None: + continue + det = detect_flags(bl, col) + det["Plant_ID"] = plant + det["Sensor"] = col + det["BaselineType"] = name + out_rows.append(det) + try: + plot_one(det, col, plant, name) + except Exception as e: + print(f" plot error Plant={plant} Sensor={col} Type={name}: {e}") + + if out_rows: + out = pd.concat(out_rows, ignore_index=True) + keep = ["Timestamp","Plant_ID","Sensor","BaselineType"] + \ + [c for c in SENSORS if c in out.columns] + \ + ["baseline","lower","upper","residual","flag_band","flag_spike","flag_break","is_anomaly"] + out = out[keep].sort_values(["Plant_ID","Sensor","BaselineType","Timestamp"]) + OUT_DIR.mkdir(exist_ok=True, parents=True) + out_csv = OUT_DIR / "anomalies_report.csv" + out.to_csv(out_csv, index=False) + + n_anom = int(out["is_anomaly"].sum()) + print(f"Anomalies report: {out_csv} (total anomalies: {n_anom})") + print(f" Plots saved in: {PLOTS_DIR}") + else: + print(" No results — maybe no suitable columns/data.") + +if __name__ == "__main__": + main() diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/app.py b/services/sensorAnomalyPro/sensorAnomalyPro/app.py new file mode 100644 index 000000000..675796b1e --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/app.py @@ -0,0 +1,271 @@ +import os, json, math, logging +import pandas as pd +from statistics import mean, median, stdev +from pyflink.common import Types, Time +from pyflink.datastream import StreamExecutionEnvironment +from pyflink.datastream.connectors.kafka import KafkaSource, KafkaSink, KafkaRecordSerializationSchema +from pyflink.common.serialization import SimpleStringSchema +from pyflink.common.watermark_strategy import WatermarkStrategy +from pyflink.datastream.window import SlidingProcessingTimeWindows +from pyflink.datastream.functions import WindowFunction +from shapely.geometry import shape, Point +from pathlib import Path +from typing import Optional +from sensorAnomalyPro.profiles_runtime import load_profiles, StreamingState, score_new_point +from datetime import datetime, timezone +import json +from statistics import mean, median, stdev + + + +# --- Config --- +OUT_TOPIC = os.getenv("OUT_TOPIC", "sensor_anomalies") +ZONE_TOPIC = os.getenv("ZONE_TOPIC", "sensor-zone-stats") +ZONES_PATH = Path(__file__).resolve().parent / "zones.geojson" +AGG_INTERVAL = int(os.getenv("ZONE_AGG_INTERVAL_SEC", "300")) +SLIDE_INTERVAL = int(os.getenv("ZONE_SLIDE_INTERVAL_SEC", "60")) + +# --- Logging --- +logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s") +log = logging.getLogger("sensor-anomaly") + +# --- Zones loading --- +_zones = [] +def load_zones(): + global _zones + try: + p = Path(ZONES_PATH) + if not p.exists(): + log.warning(f"zones file not found: {ZONES_PATH}") + return + gj = json.loads(p.read_text(encoding="utf-8")) + feats = gj.get("features", []) + _zones = [(shape(f["geometry"]), f["properties"].get("name", f"zone_{i}")) for i, f in enumerate(feats)] + log.info(f"Loaded {len(_zones)} zones from {ZONES_PATH}") + except Exception as e: + log.warning(f"zones disabled: {e}") + _zones = [] + +load_zones() + + +def resolve_zone(lat, lon) -> Optional[str]: + if not _zones or lat is None or lon is None: + return None + try: + pt = Point(lon, lat) + for poly, name in _zones: + if poly.contains(pt): + return name + return None + except Exception: + return None + + +# --- Helpers --- +_profiles_cache = {} +_states = {} + +def _norm_float(x: Optional[float]) -> Optional[float]: + try: + fx = float(x) + return fx if math.isfinite(fx) else None + except Exception: + return None + +def _finite_or_none(x): + try: + fx = float(x) + return fx if math.isfinite(fx) else None + except Exception: + return None + +def _valid_latlon(lat: Optional[float], lon: Optional[float]) -> bool: + return lat is not None and lon is not None and -90.0 <= lat <= 90.0 and -180.0 <= lon <= 180.0 + +def _classify_condition(sensor: str, value: float, lower: float, upper: float) -> str: + if sensor == "Soil_Moisture": + if value < lower: return "dry" + elif value > upper: return "wet" + elif sensor == "Ambient_Temperature": + if value < lower: return "cold" + elif value > upper: return "hot" + elif sensor == "Humidity": + if value < lower: return "low_humidity" + elif value > upper: return "high_humidity" + return "normal" + + +# --- Anomaly detection --- +def detect_anomaly(evt: dict) -> dict: + plant_id, sensor = evt.get("plant_id"), evt.get("sensor_name") + key = (plant_id, sensor) + + if evt.get("value") is None: + return {"ok": False, "reason": "no_value"} + + prof = _profiles_cache.get(key) + if prof is None: + prof = load_profiles(plant_id, sensor) + if not prof: + return {"ok": False, "reason": "no_profiles"} + _profiles_cache[key] = prof + + state = _states.get(key) + if state is None: + state = StreamingState(alpha=0.08) + _states[key] = state + + try: + ts_str = evt.get("timestamp") or evt.get("ts") + ts = pd.Timestamp(ts_str) + except Exception: + return {"ok": False, "reason": "bad_ts"} + + res = score_new_point(ts=ts, value=evt.get("value"), + profiles=prof, state=state, + k_band=2.0, spike_z_like=3.0, break_mult=1.5) + if not res.get("ok", False): + return {"ok": False, "reason": res.get("reason", "unknown")} + + condition = _classify_condition(sensor, evt.get("value"), res["lower"], res["upper"]) + return { + "ok": True, + "is_anomaly": bool(res["is_anomaly"]), + "bl_type": str(res["bl_type"]), + "baseline": _finite_or_none(res["baseline"]), + "adaptive_baseline": _finite_or_none(res.get("adaptive_baseline")), + "bias": _finite_or_none(res.get("bias")), + "lower": _finite_or_none(res["lower"]), + "upper": _finite_or_none(res["upper"]), + "band_std": _finite_or_none(res["band_std"]), + "flags": {k: bool(v) for k, v in res["flags"].items()}, + "ema_abs_res": _finite_or_none(res.get("ema_abs_res")), + "ts": str(res["ts"]), + "condition": condition + } + + +# --- Map events --- +def process_event(raw: str): + try: + evt = json.loads(raw) + except json.JSONDecodeError: + return None + + lat = _norm_float(evt.get("lat")) + lon = _norm_float(evt.get("lon")) + if not _valid_latlon(lat, lon): + lat, lon = None, None + + zone_name = resolve_zone(lat, lon) + res = detect_anomaly(evt) + if not res.get("ok", True): + return None + + out = { + "idsensor": evt.get("sensor_id"), + "plant_id": evt.get("plant_id"), + "sensor": evt.get("sensor_name"), + "ts": evt.get("timestamp") or evt.get("ts"), + "value": evt.get("value"), + "lat": lat, + "lon": lon, + "zone": zone_name, + "result": res + } + return json.dumps(out) + + +# --- Zone window aggregator (new API) --- + + + +class ZoneAggregator(WindowFunction): + def apply(self, key, window, inputs): + values = [] + anomalies = 0 + + for e in inputs: + evt = json.loads(e) + if evt.get("value") is not None: + values.append(evt["value"]) + if evt["result"].get("is_anomaly"): + anomalies += 1 + + if not values: + return [] + + window_start = datetime.fromtimestamp(window.start / 1000, tz=timezone.utc).isoformat() + window_end = datetime.fromtimestamp(window.end / 1000, tz=timezone.utc).isoformat() + + result = { + "zone": key, + "window_start": window_start, + "window_end": window_end, + "count": len(values), + "mean": mean(values), + "median": median(values), + "min": min(values), + "max": max(values), + "std": stdev(values) if len(values) > 1 else 0.0, + "anomalies": anomalies + } + + log.info(f"[ZoneAggregator] zone={key}, count={len(values)}, anomalies={anomalies}") + return [json.dumps(result)] + +# --- Main --- +def main(): + brokers = os.getenv("KAFKA_BROKERS", "kafka:9092") + in_topic = os.getenv("IN_TOPIC", "sensors") + + env = StreamExecutionEnvironment.get_execution_environment() + env.set_parallelism(int(os.getenv("FLINK_PARALLELISM", "2"))) + + source = KafkaSource.builder() \ + .set_bootstrap_servers(brokers) \ + .set_topics(in_topic) \ + .set_group_id("flink-anomaly-detector") \ + .set_value_only_deserializer(SimpleStringSchema()) \ + .build() + + sink_anomalies = KafkaSink.builder() \ + .set_bootstrap_servers(brokers) \ + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(OUT_TOPIC) + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ).build() + + sink_zones = KafkaSink.builder() \ + .set_bootstrap_servers(brokers) \ + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(ZONE_TOPIC) + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ).build() + + ds = env.from_source(source, WatermarkStrategy.no_watermarks(), "kafka-in") + + processed = ds.map(process_event, output_type=Types.STRING()) \ + .filter(lambda x: x is not None) + + processed.sink_to(sink_anomalies) + + zone_summary = processed \ + .filter(lambda s: json.loads(s).get("zone") is not None) \ + .key_by(lambda s: json.loads(s)["zone"]) \ + .window(SlidingProcessingTimeWindows.of(Time.seconds(AGG_INTERVAL), + Time.seconds(SLIDE_INTERVAL))) \ + .apply(ZoneAggregator(), output_type=Types.STRING()) + + zone_summary.sink_to(sink_zones) + + env.execute("sensor-anomaly-job") + + +if __name__ == "__main__": + main() diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/data/plant_health_data.csv b/services/sensorAnomalyPro/sensorAnomalyPro/data/plant_health_data.csv new file mode 100644 index 000000000..59c68ee4e --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/data/plant_health_data.csv @@ -0,0 +1,21601 @@ +Timestamp,Plant_ID,Soil_Moisture,Ambient_Temperature,Humidity +2024-08-04 05:00:00,1,29.03792107887181,23.573387484527874 ,56.107581735896275 +2024-08-04 06:00:00,1,20.7937301586471,23.148506017008554,52.77336185849758 +2024-08-04 07:00:00,1,26.249896374270108,23.396942444999862,42.8909336156407 +2024-08-04 08:00:00,1,12.801455337953044,21.81770590700519,53.030565981651804 +2024-08-04 09:00:00,1,40.049966952512094,22.12141037783682,50.6679930979592 +2024-08-04 10:00:00,1,38.76573172875861,21.46343403894607,57.1600781852107 +2024-08-04 11:00:00,1,19.165179382414934,23.60832781399697,54.748267265455226 +2024-08-04 12:00:00,1,30.06284187961404,18.32241496973967,60.104933525057234 +2024-08-04 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21:00:00,10,25.81667197976654,19.757266553663996,69.3101567988544 +2024-11-01 22:00:00,10,37.55253951623312,23.270796468881503,52.17795553341093 +2024-11-01 23:00:00,10,30.462140046100245,21.677219847567667,52.7276276667863 +2024-11-02 00:00:00,10,39.203805670451416,27.922222715803038,52.02917893854069 +2024-11-02 01:00:00,10,22.420909598342284,26.878192710407276,54.776376063597304 +2024-11-02 02:00:00,10,22.656571164792446,26.80296309042541,75.98046460014712 +2024-11-02 03:00:00,10,21.51033397656976,33.84851210905514,29.574737878809287 +2024-11-02 04:00:00,10,30.120544664145363,25.00973090352314,48.429435091796236 diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/profiles_runtime.py b/services/sensorAnomalyPro/sensorAnomalyPro/profiles_runtime.py new file mode 100644 index 000000000..36dfcef67 --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/profiles_runtime.py @@ -0,0 +1,218 @@ +from pathlib import Path +from typing import Dict, Optional +import numpy as np +import pandas as pd +BASE_DIR = Path(__file__).resolve().parent +MODELS_DIR = BASE_DIR / "reports" / "models" +MODELS_DIR.mkdir(parents=True, exist_ok=True) + +SENSORS = ["Soil_Moisture", "Ambient_Temperature", "Humidity"] + +# ---------- Helpers ---------- +def _safe_interp(series: pd.Series, full_index): + s = series.reindex(full_index) + return s.interpolate(limit_direction="both") + +# ---------- Export (train) ---------- +def export_profiles(df: pd.DataFrame) -> None: + if "Plant_ID" not in df.columns or "Timestamp" not in df.columns: + raise ValueError("DataFrame must contain 'Plant_ID' and 'Timestamp'") + df = df.dropna(subset=["Timestamp"]).sort_values("Timestamp").copy() + + for plant in df["Plant_ID"].dropna().unique(): + d0 = df[df["Plant_ID"] == plant] + for col in SENSORS: + if col not in d0.columns: + continue + d = d0[["Timestamp", col]].dropna().copy() + if d.empty: + continue + + # ----- daily ----- + x = d.copy() + x["hod"] = x["Timestamp"].dt.hour + med_hod = _safe_interp(x.groupby("hod")[col].median(), range(24)) + std_hod = x.groupby("hod")[col].std().reindex(range(24)) + std_hod = std_hod.fillna(std_hod.mean() if not np.isnan(std_hod.mean()) else 0.0) + out = pd.DataFrame({"hod": range(24), "median": med_hod.values, "std": std_hod.values}) + (MODELS_DIR / f"daily_{plant}_{col}.csv").write_text(out.to_csv(index=False), encoding="utf-8") + + # ----- weekly ----- + if len(d) >= 24 * 7: + xw = d.copy() + xw["dow"] = xw["Timestamp"].dt.dayofweek + xw["hod"] = xw["Timestamp"].dt.hour + med_week = xw.groupby(["dow", "hod"])[col].median().unstack() + med_week = med_week.reindex(index=range(7), columns=range(24)) + med_week = med_week.apply(lambda s: s.interpolate(limit_direction="both"), axis=1)\ + .interpolate(axis=0, limit_direction="both") + + std_week = xw.groupby(["dow", "hod"])[col].std().unstack() + std_week = std_week.reindex(index=range(7), columns=range(24)) + fill_val = std_week.stack().mean() if std_week.stack().notna().any() else 0.0 + std_week = std_week.fillna(fill_val) + + med_week.reset_index(inplace=True) + std_week.reset_index(inplace=True) + med_week = med_week.melt(id_vars="dow", var_name="hod", value_name="median").sort_values(["dow", "hod"]) + std_week = std_week.melt(id_vars="dow", var_name="hod", value_name="std").sort_values(["dow", "hod"]) + ww = pd.merge(med_week, std_week, on=["dow","hod"], how="inner") + (MODELS_DIR / f"weekly_{plant}_{col}.csv").write_text(ww.to_csv(index=False), encoding="utf-8") + + # ----- seasonal ----- + if d["Timestamp"].dt.year.nunique() >= 2 or len(d) >= 24 * 60: + xs = d.copy() + xs["doy"] = xs["Timestamp"].dt.dayofyear + xs["hod"] = xs["Timestamp"].dt.hour + med_doy = _safe_interp(xs.groupby("doy")[col].median(), range(1, 367)) + med_hod2 = _safe_interp(xs.groupby("hod")[col].median(), range(24)) + std_h = xs.groupby("hod")[col].std().reindex(range(24)) + std_h = std_h.fillna(std_h.mean() if not np.isnan(std_h.mean()) else 0.0) + pd.DataFrame({"doy": range(1, 367), "median": med_doy.values})\ + .to_csv(MODELS_DIR / f"seasonal_doy_{plant}_{col}.csv", index=False) + pd.DataFrame({"hod": range(24), "median": med_hod2.values, "std": std_h.values})\ + .to_csv(MODELS_DIR / f"seasonal_hod_{plant}_{col}.csv", index=False) + +# ---------- Load ---------- +def load_profiles(plant_id, sensor) -> Dict[str, pd.DataFrame]: + out: Dict[str, pd.DataFrame] = {} + p = MODELS_DIR + daily = p / f"daily_{plant_id}_{sensor}.csv" + weekly = p / f"weekly_{plant_id}_{sensor}.csv" + sdoy = p / f"seasonal_doy_{plant_id}_{sensor}.csv" + shod = p / f"seasonal_hod_{plant_id}_{sensor}.csv" + if daily.exists(): out["daily"] = pd.read_csv(daily) + if weekly.exists(): out["weekly"] = pd.read_csv(weekly) + if sdoy.exists(): out["seasonal_doy"] = pd.read_csv(sdoy) + if shod.exists(): out["seasonal_hod"] = pd.read_csv(shod) + return out + +# ---------- Expectation (baseline/std) ---------- +def expected_from_profiles(ts: pd.Timestamp, profiles: Dict[str, pd.DataFrame]) -> Optional[Dict[str, float]]: + if not profiles: + return None + ts = pd.Timestamp(ts) + hod = int(ts.hour) + dow = int(ts.dayofweek) + doy = int(ts.dayofyear) + + # Seasonal: DOY + HOD + if "seasonal_doy" in profiles and "seasonal_hod" in profiles: + sdoy = profiles["seasonal_doy"].set_index("doy") + shod = profiles["seasonal_hod"].set_index("hod") + + med_doy = float(sdoy.loc[doy, "median"]) if doy in sdoy.index else float(sdoy["median"].iloc[-1]) + if hod in shod.index: + med_hod = float(shod.loc[hod, "median"]) + std_hod = float(shod.loc[hod, "std"]) + else: + med_hod = float(shod["median"].iloc[-1]) + std_hod = float(shod["std"].mean()) if pd.notna(shod["std"].mean()) else 0.0 + if not np.isfinite(std_hod) or std_hod <= 0.0: + std_hod = max(float(shod["std"].mean()), 1e-6) + + base = 0.5 * med_doy + 0.5 * med_hod + return {"baseline": float(base), "band_std": float(std_hod), "bl_type": "seasonal"} + + # Weekly: DOW + HOD + if "weekly" in profiles: + w = profiles["weekly"].copy() + if {"dow", "hod", "median", "std"}.issubset(set(w.columns)): + w["dow"] = w["dow"].astype(int) + w["hod"] = w["hod"].astype(int) + row = w[(w["dow"] == dow) & (w["hod"] == hod)] + if not row.empty: + base = float(row["median"].iloc[0]) + std = float(row["std"].iloc[0]) + if not np.isfinite(std) or std <= 0.0: + std = max(float(w["std"].mean()), 1e-6) + return {"baseline": base, "band_std": std, "bl_type": "weekly"} + + # Daily: HOD only + if "daily" in profiles: + d = profiles["daily"].set_index("hod") + if hod in d.index: + base = float(d.loc[hod, "median"]) + std = float(d.loc[hod, "std"]) + else: + base = float(d["median"].iloc[-1]) + std = float(d["std"].mean()) if pd.notna(d["std"].mean()) else 0.0 + if not np.isfinite(std) or std <= 0.0: + std = max(float(d["std"].mean()), 1e-6) + return {"baseline": base, "band_std": std, "bl_type": "daily"} + + return None + +# ---------- Streaming scoring ---------- +class StreamingState: + def __init__(self, alpha: float = 2/25, bias_alpha: float = 0.002): + self.prev_value: Optional[float] = None + self.ema_abs_res: Optional[float] = None + self.alpha = float(alpha) + self.bias: float = 0.0 + self.bias_alpha: float = float(bias_alpha) + + def update_ema(self, value: float): + if self.ema_abs_res is None: + self.ema_abs_res = value + else: + self.ema_abs_res = self.alpha * value + (1 - self.alpha) * self.ema_abs_res + + def update_bias(self, residual: float): + self.bias = (1 - self.bias_alpha) * self.bias + self.bias_alpha * residual + +def score_new_point( + ts: pd.Timestamp, + value: float, + profiles: Dict[str, pd.DataFrame], + state: StreamingState, + k_band: float = 2.0, + spike_z_like: float = 3.0, + break_mult: float = 1.5, +) -> Dict[str, object]: + exp = expected_from_profiles(ts, profiles) + if exp is None: + return {"ok": False, "reason": "no_profiles"} + + baseline = exp["baseline"] + band_std = exp["band_std"] + adaptive_baseline = baseline + (state.bias or 0.0) + lower = adaptive_baseline - k_band * band_std + upper = adaptive_baseline + k_band * band_std + flag_band = (value < lower) or (value > upper) + + flag_spike = False + if state.prev_value is not None: + diff = value - state.prev_value + denom = band_std if band_std > 1e-9 else 1.0 + flag_spike = abs(diff) > spike_z_like * denom + + residual = value - adaptive_baseline + state.update_ema(abs(residual)) + state.update_bias(residual) + flag_break = False + if state.ema_abs_res is not None: + flag_break = state.ema_abs_res > (break_mult * band_std) + + state.prev_value = value + + is_anomaly = flag_band or flag_spike or flag_break + return { + "ok": True, + "ts": ts, + "baseline": float(baseline), + "adaptive_baseline": float(adaptive_baseline), + "band_std": float(band_std), + "lower": float(lower), + "upper": float(upper), + "value": float(value), + "flags": { + "band": bool(flag_band), + "spike": bool(flag_spike), + "break": bool(flag_break), + }, + "is_anomaly": bool(is_anomaly), + "bl_type": exp["bl_type"], + "ema_abs_res": float(state.ema_abs_res) if state.ema_abs_res is not None else None, + "bias": float(state.bias), + } diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/requirements.txt b/services/sensorAnomalyPro/sensorAnomalyPro/requirements.txt new file mode 100644 index 000000000..12ce1818c --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/requirements.txt @@ -0,0 +1,15 @@ +pandas==2.2.2 +numpy==1.26.4 +matplotlib==3.8.4 +statsmodels==0.14.2 +scipy==1.11.4 +#fastapi==0.110.0 + + + +uvicorn==0.29.0 +scikit-learn==1.3.2 +joblib==1.3.2 +protobuf>=3.20.3,<5 +grpcio>=1.54.0 +shapely diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/tests/conftest.py b/services/sensorAnomalyPro/sensorAnomalyPro/tests/conftest.py new file mode 100644 index 000000000..a6ae30046 --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/tests/conftest.py @@ -0,0 +1,39 @@ + +import os +import sys +from pathlib import Path +import pandas as pd +import numpy as np +import pytest +from datetime import datetime, timedelta + +# Ensure project src is importable +HERE = Path(__file__).resolve().parent +SRC = HERE.parent / "sensor-anomaly-pro" / "sensor-anomaly-pro" +if SRC.exists(): + sys.path.insert(0, str(SRC)) + +@pytest.fixture(scope="session") +def mini_csv(tmp_path_factory): + # Create a tiny, valid sensors CSV for tests and set DATA_PATH to it. + tmpdir = tmp_path_factory.mktemp("data") + csv_path = tmpdir / "mini_plant_health.csv" + + # Build 3 days hourly for 2 plants + start = datetime(2024, 1, 1, 0, 0, 0) + rows = [] + for plant in ["P1", "P2"]: + for h in range(0, 24 * 3): + ts = start + timedelta(hours=h) + rows.append({ + "Plant_ID": plant, + "Timestamp": ts.isoformat(), + "Soil_Moisture": 40 + 10*np.sin(h/6.0) + (np.random.rand()-0.5), + "Ambient_Temperature": 20 + 5*np.sin(h/12.0) + (np.random.rand()-0.5), + "Humidity": 60 + 8*np.cos(h/8.0) + (np.random.rand()-0.5), + }) + df = pd.DataFrame(rows) + df.to_csv(csv_path, index=False) + + os.environ["DATA_PATH"] = str(csv_path) + return csv_path diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/tests/pytest.ini b/services/sensorAnomalyPro/sensorAnomalyPro/tests/pytest.ini new file mode 100644 index 000000000..de40b9629 --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/tests/pytest.ini @@ -0,0 +1,2 @@ +[pytest] +addopts = -q --maxfail=1 --disable-warnings diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_app_score.py b/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_app_score.py new file mode 100644 index 000000000..bb3357a7c --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_app_score.py @@ -0,0 +1,30 @@ +# tests/test_app_score.py +import os +from pathlib import Path + +import analyze_sensors as az +import sensorAnomalyPro.profiles_runtime as pr +import sensorAnomalyPro.app as appmod + +def test_score_function_end_to_end(tmp_path): + df = az.read_and_clean(Path(os.getenv("DATA_PATH", "/mnt/data/plant_health_data.csv"))) + + pr.MODELS_DIR = tmp_path / "reports" / "models" + pr.MODELS_DIR.mkdir(parents=True, exist_ok=True) + + pr.export_profiles(df) + + + row0 = df[df["Plant_ID"].notna()].iloc[0] + plant = row0["Plant_ID"] + sensor = "Soil_Moisture" if "Soil_Moisture" in df.columns else "Humidity" + + + ts = row0["Timestamp"].isoformat() + value = float(row0[sensor]) + req = appmod.ScoreRequest(plant_id=str(plant), sensor=sensor, ts=ts, value=value) + resp = appmod.score(req) + + assert resp.ok is True + for field in ["is_anomaly", "lower", "upper", "band_std", "flags", "ts", "baseline"]: + assert getattr(resp, field, None) is not None diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_detect_flags.py b/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_detect_flags.py new file mode 100644 index 000000000..a79c13d00 --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_detect_flags.py @@ -0,0 +1,35 @@ +# tests/test_detect_flags.py +import os +from pathlib import Path +import numpy as np + +import analyze_sensors as az + +def test_detect_flags_spike_is_caught(): + data_path = Path(os.getenv("DATA_PATH", "/mnt/data/plant_health_data.csv")) + df = az.read_and_clean(data_path) + + col = "Soil_Moisture" if "Soil_Moisture" in df.columns else "Humidity" + + + plant_val = df["Plant_ID"].dropna().unique()[0] + d = df[df["Plant_ID"] == plant_val].copy() + assert not d.empty, "no rows for selected plant" + + mid = len(d) // 2 + base = float(d.iloc[mid][col]) + d.iloc[mid, d.columns.get_loc(col)] = base + 50.0 + + + db = az.baseline_daily(d, col) + out = az.detect_flags(db, col) + + expected = {"flag_band", "flag_spike", "flag_break", "is_anomaly"} + assert expected.issubset(set(out.columns)), f"missing columns: {expected - set(out.columns)}" + + + flag_df = out[["flag_band", "flag_spike", "flag_break", "is_anomaly"]].fillna(False) + assert flag_df.to_numpy().any(), "expected at least one flagged point for the injected spike" + + + assert flag_df["flag_spike"].any() or flag_df["is_anomaly"].any(), "expected spike detection" diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_profiles_runtime.py b/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_profiles_runtime.py new file mode 100644 index 000000000..ea8147234 --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_profiles_runtime.py @@ -0,0 +1,17 @@ +# tests/test_profiles_runtime.py +import os +from pathlib import Path + +import analyze_sensors as az +import sensorAnomalyPro.profiles_runtime as pr + +def test_export_and_load_profiles(tmp_path): + df = az.read_and_clean(Path(os.getenv("DATA_PATH", "/mnt/data/plant_health_data.csv"))) + pr.MODELS_DIR = tmp_path / "reports" / "models" + pr.MODELS_DIR.mkdir(parents=True, exist_ok=True) + pr.export_profiles(df) + + plant = df["Plant_ID"].dropna().iloc[0] + sensor = "Soil_Moisture" if "Soil_Moisture" in df.columns else "Humidity" + prof = pr.load_profiles(plant, sensor) + assert prof is not None diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_read_clean.py b/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_read_clean.py new file mode 100644 index 000000000..d8b39c3d5 --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/tests/test_read_clean.py @@ -0,0 +1,17 @@ +import os +from pathlib import Path +import pandas as pd + +import analyze_sensors as az + +def test_read_and_clean_smoke(): + data_path = Path(os.getenv("DATA_PATH", "/mnt/data/plant_health_data.csv")) + df = az.read_and_clean(data_path) + assert not df.empty, "cleaned dataframe should not be empty" + # required columns + required = {"Plant_ID", "Timestamp"} + assert required.issubset(df.columns), f"missing columns: {required - set(df.columns)}" + # dtypes + assert pd.api.types.is_datetime64_any_dtype(df["Timestamp"]), "Timestamp must be datetime" + for col in ["Soil_Moisture", "Ambient_Temperature", "Humidity"]: + assert col in df.columns, f"missing sensor column {col}" diff --git a/services/sensorAnomalyPro/sensorAnomalyPro/zones.geojson b/services/sensorAnomalyPro/sensorAnomalyPro/zones.geojson new file mode 100644 index 000000000..423245ec0 --- /dev/null +++ b/services/sensorAnomalyPro/sensorAnomalyPro/zones.geojson @@ -0,0 +1,22 @@ + +{ + "type": "FeatureCollection", + "features": [ + { + "type": "Feature", + "properties": {"name": "Zone A"}, + "geometry": { + "type": "Polygon", + "coordinates": [[[34.75, 32.00], [34.90, 32.00], [34.90, 32.10], [34.75, 32.10], [34.75, 32.00]]] + } + }, + { + "type": "Feature", + "properties": {"name": "Zone B"}, + "geometry": { + "type": "Polygon", + "coordinates": [[[34.90, 31.95], [35.05, 31.95], [35.05, 32.05], [34.90, 32.05], [34.90, 31.95]]] + } + } + ] +} diff --git a/services/sensorGuard/Dockerfile.flink b/services/sensorGuard/Dockerfile.flink new file mode 100644 index 000000000..8d94314f5 --- /dev/null +++ b/services/sensorGuard/Dockerfile.flink @@ -0,0 +1,135 @@ +FROM flink:1.19.3-scala_2.12-java11 + +USER root + +COPY certs/*.crt /app/certs/ +RUN if [ -d ./certs ] && [ "$(ls ./certs/*.crt 2>/dev/null)" ]; then \ + echo "Configuring NetFree certificates..."; \ + cp ./certs/*.crt /usr/local/share/ca-certificates/; \ + update-ca-certificates; \ + fi +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt +ENV REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt +ENV PIP_CERT=/etc/ssl/certs/ca-certificates.crt + +RUN set -eux; \ + apt-get update; \ + apt-get install -y --no-install-recommends \ + python3 python3-venv python3-pip ca-certificates curl libgomp1; \ + rm -rf /var/lib/apt/lists/* + +RUN curl -fSL https://repo1.maven.org/maven2/org/apache/flink/flink-connector-kafka/3.2.0-1.19/flink-connector-kafka-3.2.0-1.19.jar \ + -o /opt/flink/lib/flink-connector-kafka-3.2.0-1.19.jar + +# Ensure lib directory exists +RUN mkdir -p /opt/flink/lib + +# venv + PATH +RUN python3 -m venv /opt/venv +ENV PATH="/opt/venv/bin:${PATH}" \ + PYFLINK_CLIENT_EXECUTABLE=/opt/venv/bin/python \ + PYFLINK_PYTHON=/opt/venv/bin/python \ + PYTHONUNBUFFERED=1 + +# Configure pip to use SSL certificates +RUN printf "[global]\ntrusted-host = pypi.org\n\tfiles.pythonhosted.org\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf + +COPY requirements.txt /tmp/requirements.txt +# Install Python dependencies including PyFlink +RUN pip install -r /tmp/requirements.txt && \ + pip install "apache-flink==1.19.3" + +# Compatible versions for PyFlink 1.19.3 + +# kafka-clients +RUN curl -fSL https://repo1.maven.org/maven2/org/apache/kafka/kafka-clients/3.7.0/kafka-clients-3.7.0.jar \ + -o /opt/flink/lib/kafka-clients-3.7.0.jar + +RUN curl -fSL https://repo1.maven.org/maven2/org/apache/flink/flink-connector-kafka/3.2.0-1.19/flink-connector-kafka-3.2.0-1.19.jar \ + -o /opt/flink/lib/flink-connector-kafka-3.2.0-1.19.jar + +WORKDIR /opt/app +COPY flink_app/main.py /opt/app/main.py +COPY flink_app/core /opt/app/core +COPY flink_app/io_mod /opt/app/io_mod +COPY flink_app/config /opt/app/config +COPY flink_app/api /opt/app/api + +RUN mkdir -p /opt/app/resources + +RUN chown -R flink:flink /opt/app /opt/flink && chmod -R g+rwX /opt/app +USER flink + +# Default environment variables +ENV KAFKA_BROKERS=kafka:9092 \ + IN_TOPIC=sensors \ + OUT_TOPIC=event_logs_sensors \ + KAFKA_GROUP_ID=flink-device-pipeline \ + PYTHONPATH=/opt/app \ + PYFLINK_CLIENT_EXECUTABLE=/opt/venv/bin/python \ + PYFLINK_PYTHON=/opt/venv/bin/python + +USER root + +COPY netfree-ca.crt /usr/local/share/ca-certificates/corp-ca.crt +RUN chmod 644 /usr/local/share/ca-certificates/corp-ca.crt && update-ca-certificates + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt + +RUN set -eux; \ + apt-get update; \ + apt-get install -y --no-install-recommends \ + python3 python3-venv python3-pip ca-certificates curl libgomp1; \ + rm -rf /var/lib/apt/lists/* + +RUN curl -fSL https://repo1.maven.org/maven2/org/apache/flink/flink-connector-kafka/3.2.0-1.19/flink-connector-kafka-3.2.0-1.19.jar \ + -o /opt/flink/lib/flink-connector-kafka-3.2.0-1.19.jar + +RUN mkdir -p /opt/flink/lib + +RUN python3 -m venv /opt/venv +ENV PATH="/opt/venv/bin:${PATH}" \ + PYFLINK_CLIENT_EXECUTABLE=/opt/venv/bin/python \ + PYFLINK_PYTHON=/opt/venv/bin/python \ + PYTHONUNBUFFERED=1 + +RUN printf "[global]\ntrusted-host = pypi.org\n\tfiles.pythonhosted.org\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf + +COPY requirements.txt /tmp/requirements.txt +RUN pip install -r /tmp/requirements.txt && \ + pip install "apache-flink==1.19.3" + + +RUN curl -fSL https://repo1.maven.org/maven2/org/apache/kafka/kafka-clients/3.7.0/kafka-clients-3.7.0.jar \ + -o /opt/flink/lib/kafka-clients-3.7.0.jar + +RUN curl -fSL https://repo1.maven.org/maven2/org/apache/flink/flink-connector-kafka/3.2.0-1.19/flink-connector-kafka-3.2.0-1.19.jar \ + -o /opt/flink/lib/flink-connector-kafka-3.2.0-1.19.jar + +WORKDIR /opt/app +COPY flink_app/main.py /opt/app/main.py +COPY flink_app/core /opt/app/core +COPY flink_app/io_mod /opt/app/io_mod +COPY flink_app/config /opt/app/config +COPY flink_app/api /opt/app/api + +RUN mkdir -p /opt/app/secrets && \ + chown -R flink:flink /opt/app /opt/flink /opt/app/secrets && \ + chmod -R g+rwX /opt/app && \ + chmod 775 /opt/app/secrets + +# Copy and set up entrypoint script +COPY entrypoint.sh /usr/local/bin/entrypoint.sh +RUN chmod +x /usr/local/bin/entrypoint.sh + +ENTRYPOINT ["/usr/local/bin/entrypoint.sh"] +CMD ["jobmanager"] + +ENV KAFKA_BROKERS=kafka:9092 \ + IN_TOPIC=sensors \ + OUT_TOPIC=event_logs_sensors \ + KAFKA_GROUP_ID=flink-device-pipeline \ + PYTHONPATH=/opt/app \ + PYFLINK_CLIENT_EXECUTABLE=/opt/venv/bin/python \ + PYFLINK_PYTHON=/opt/venv/bin/python diff --git a/services/sensorGuard/README.md b/services/sensorGuard/README.md new file mode 100644 index 000000000..e69de29bb diff --git a/services/sensorGuard/docker-compose.yml b/services/sensorGuard/docker-compose.yml new file mode 100644 index 000000000..bacbeb99d --- /dev/null +++ b/services/sensorGuard/docker-compose.yml @@ -0,0 +1,42 @@ +version: "3.9" + +services: + jobmanager: + build: + context: . + dockerfile: Dockerfile.flink + container_name: flink-jobmanager + command: jobmanager + ports: + - "8081:8081" + environment: + - JOB_MANAGER_RPC_ADDRESS=jobmanager + - KAFKA_BROKERS=kafka:9092 + - KAFKA_GROUP_ID=flink-device-pipeline + networks: + - ag_cloud + volumes: + - ./secrets:/opt/app/secrets + + taskmanager: + build: + context: . + dockerfile: Dockerfile.flink + container_name: flink-taskmanager + command: taskmanager -D taskmanager.numberOfTaskSlots=4 + depends_on: + - jobmanager + environment: + - JOB_MANAGER_RPC_ADDRESS=jobmanager + - KAFKA_BROKERS=kafka:9092 + - taskmanager.numberOfTaskSlots=4 + - KAFKA_GROUP_ID=flink-device-pipeline + networks: + - ag_cloud + volumes: + - ./secrets:/opt/app/secrets + +networks: + ag_cloud: + external: true + name: agcloud_ag_cloud diff --git a/services/sensorGuard/entrypoint.sh b/services/sensorGuard/entrypoint.sh new file mode 100644 index 000000000..a301d88f6 --- /dev/null +++ b/services/sensorGuard/entrypoint.sh @@ -0,0 +1,12 @@ +#!/bin/bash +set -e + +# Fix permissions for secrets directory if it exists (runs as root) +if [ -d "/opt/app/secrets" ]; then + echo "Fixing permissions for /opt/app/secrets..." + chown -R flink:flink /opt/app/secrets + chmod 775 /opt/app/secrets +fi + +# Call the original Flink entrypoint +exec /docker-entrypoint.sh "$@" diff --git a/services/sensorGuard/flink_app/__init__.py b/services/sensorGuard/flink_app/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/sensorGuard/flink_app/api/__init__.py b/services/sensorGuard/flink_app/api/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/sensorGuard/flink_app/api/auth.py b/services/sensorGuard/flink_app/api/auth.py new file mode 100644 index 000000000..3458232aa --- /dev/null +++ b/services/sensorGuard/flink_app/api/auth.py @@ -0,0 +1,99 @@ +import os +import pathlib +import requests +import time + +# === CONFIG === +DB_API_BASE = os.getenv("DB_API_BASE", "http://db_api_service:8001") +DB_API_TOKEN_FILE = os.getenv("DB_API_TOKEN_FILE", "/opt/app/secrets/db_api_token") +DB_API_SERVICE_NAME = os.getenv("DB_API_SERVICE_NAME", "flink_job_sensors") +ROTATE_IF_EXISTS = True # Can be set to False if token rotation is not desired on restart + +# === PATH HELPERS === +def _safe_join_url(base: str, path: str) -> str: + return f"{base.rstrip('/')}/{path.lstrip('/')}" + +def _read_token_from_file(path: str) -> str | None: + try: + p = pathlib.Path(path) + if p.exists(): + token = p.read_text(encoding="utf-8").strip() + if token and len(token) > 10: + return token + except Exception: + pass + return None + +def _write_token_to_file(path: str, token: str) -> None: + p = pathlib.Path(path) + p.parent.mkdir(parents=True, exist_ok=True) + p.write_text(token, encoding="utf-8") + print(f"[AUTH] Token saved to {path}") + +# === FETCH LOGIC === +def _fetch_token_via_bootstrap(base: str, retries: int = 3, backoff: float = 1.0) -> str | None: + url = _safe_join_url(base, "/auth/_dev_bootstrap") + payload = {"service_name": DB_API_SERVICE_NAME, "rotate_if_exists": ROTATE_IF_EXISTS} + + for attempt in range(1, retries + 1): + try: + r = requests.post(url, json=payload, timeout=10) + if r.status_code not in (200, 201): + print(f"[AUTH] Bootstrap failed ({r.status_code}): {r.text[:200]}") + time.sleep(backoff * attempt) + continue + + data = r.json() + raw = (data.get("service_account", {}) or {}).get("raw_token") \ + or (data.get("service_account", {}) or {}).get("token") + + if raw and isinstance(raw, str) and raw.strip() and "***" not in raw: + print("[AUTH] Token fetched successfully") + return raw.strip() + except Exception as e: + print(f"[AUTH] Exception: {e}") + time.sleep(backoff * attempt) + print("[AUTH] Failed to bootstrap service token") + return None + +# === PUBLIC API === +def validate_token(base: str, token: str) -> bool: + """ + Test if token is valid by making a simple API call. + Returns True if token works, False otherwise. + + NOTE: Disabled because /api/me endpoint doesn't exist. + We just assume the token is valid and let actual API calls fail if needed. + """ + # url = _safe_join_url(base, "/api/me") + # try: + # r = requests.get(url, headers={"X-Service-Token": token}, timeout=5) + # return r.status_code == 200 + # except Exception: + # return False + + # Skip validation - assume token is valid + return True if token else False + + +def get_access_token(base_url: str | None = None) -> str: + """ + Loads token from file if exists and valid, otherwise bootstraps new one via /auth/_dev_bootstrap. + Returns a valid token string. + """ + base = base_url or DB_API_BASE + token = _read_token_from_file(DB_API_TOKEN_FILE) + + # If token exists, validate it first + if token: + if validate_token(base, token): + print("[AUTH] Existing token is valid") + return token + else: + print("[AUTH] Existing token is invalid, fetching new one...") + + new_token = _fetch_token_via_bootstrap(base) + if new_token: + _write_token_to_file(DB_API_TOKEN_FILE, new_token) + return new_token + raise RuntimeError("[AUTH] Could not obtain or save service token") diff --git a/services/sensorGuard/flink_app/api/devices_client.py b/services/sensorGuard/flink_app/api/devices_client.py new file mode 100644 index 000000000..a46a4f55f --- /dev/null +++ b/services/sensorGuard/flink_app/api/devices_client.py @@ -0,0 +1,81 @@ +""" +api/devices_client.py +----------------------------------- +Fetches all active sensors (devices) from the API +and returns their IDs and models. +""" +import requests +from typing import Iterable, Tuple +from api.auth import get_access_token + + +def list_active_sensors(api_base: str, token: str, timeout: float = 10.0) -> Iterable[str]: + """ + Fetch all sensors from the devices_sensor table. + + Args: + api_base: Base URL of the API (e.g., "http://localhost:8001") + token: Access token (returned from get_access_token) + timeout: HTTP request timeout in seconds + + Yields: + Device IDs as strings. + """ + url = f"{api_base.rstrip('/')}/api/tables/devices_sensor" + headers = {"X-Service-Token": token} + + try: + response = requests.get(url, headers=headers, timeout=timeout) + if response.status_code != 200: + print(f"[DEVICES] Failed ({response.status_code}): {response.text[:120]}") + return + + items = (response.json() or {}).get("rows", []) + print(f"[DEVICES] Fetched {len(items)} sensors from API") + for dev in items: + # All sensors in table are active, just return the IDs + device_id = dev.get("id", "") + if device_id: + print(f"[DEVICES] Adding sensor: id={device_id}") + yield str(device_id) + + except requests.RequestException as e: + print(f"[DEVICES] Request error: {e}") + return + + +def get_sensors_last_seen(api_base: str = None, timeout: float = 10.0): + """ + Fetch all sensors from devices_sensor with their last_seen timestamp. + Used for silence sweep. + + Args: + api_base: Base URL of the API. If None, uses host.docker.internal (same as PATCH). + timeout: Request timeout. + + Returns: + List of dicts like: [{"id": "dev-a", "sensor_type": "temp", "last_seen": "2025-11-11T13:00:00Z"}, ...] + """ + # Use same URL pattern as update_device_last_seen (PATCH) + if api_base is None: + api_base = "http://host.docker.internal:8001" + + # Get fresh token each time (same pattern as update_device_last_seen) + token = get_access_token(api_base) + + url = f"{api_base.rstrip('/')}/api/tables/devices_sensor" + headers = {"X-Service-Token": token} + + try: + response = requests.get(url, headers=headers, timeout=timeout) + if response.status_code != 200: + print(f"[DEVICES] Failed ({response.status_code}): {response.text[:120]}") + return [] + + items = (response.json() or {}).get("rows", []) + print(f"[DEVICES] Fetched {len(items)} sensors (with last_seen) from API") + return items + + except requests.RequestException as e: + print(f"[DEVICES][ERROR] {e}") + return [] diff --git a/services/sensorGuard/flink_app/api/devices_updater.py b/services/sensorGuard/flink_app/api/devices_updater.py new file mode 100644 index 000000000..534d2893f --- /dev/null +++ b/services/sensorGuard/flink_app/api/devices_updater.py @@ -0,0 +1,30 @@ +import requests +from datetime import datetime, timezone +from api.auth import get_access_token + +def update_device_last_seen(device_id: str): + """ + Updates the 'last_seen' field for a specific device in the devices_sensor table. + Uses PATCH /api/tables/devices_sensor + """ + api_base = "http://host.docker.internal:8001" + token = get_access_token(api_base) + headers = { + "X-Service-Token": token, + "Content-Type": "application/json" + } + url = f"{api_base}/api/tables/devices_sensor" + + payload = { + "keys": {"id": device_id}, + "data": {"last_seen": datetime.now(timezone.utc).isoformat()} + } + + try: + r = requests.patch(url, json=payload, headers=headers, timeout=10) + if r.status_code == 200: + print(f"[DB-UPDATER] Updated last_seen for device {device_id}") + else: + print(f"[DB-UPDATER] Failed ({r.status_code}): {r.text}") + except Exception as e: + print(f"[DB-UPDATER] Exception: {e}") diff --git a/services/sensorGuard/flink_app/config/__init__.py b/services/sensorGuard/flink_app/config/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/sensorGuard/flink_app/config/rules.yaml b/services/sensorGuard/flink_app/config/rules.yaml new file mode 100644 index 000000000..dd718a617 --- /dev/null +++ b/services/sensorGuard/flink_app/config/rules.yaml @@ -0,0 +1,25 @@ +defaults: + expected_interval_seconds: 60 + keepalive_miss_factor: 2 + prolonged_silence_seconds: 120 + silence_sweep_interval_seconds: 120 + +ranges: + temperature: { min: 21, max: 29 } + Ambient_Temperature: { min: 21, max: 29 } + humidity: { min: 0, max: 100 } + Humidity: { min: 0, max: 100 } + soil_moist: { min: 0, max: 100 } + Soil_Moisture: { min: 0, max: 100 } + unknown_sensor: { min: 21, max: 29 } # Default range - using temperature range for testing + +stuck: + epsilon: 0.1 + min_run_length: 3 + min_duration_seconds: 600 + +features: + corrupted: true + out_of_range: true + stuck_sensor: true + silence: true \ No newline at end of file diff --git a/services/sensorGuard/flink_app/config/settings.py b/services/sensorGuard/flink_app/config/settings.py new file mode 100644 index 000000000..59853c063 --- /dev/null +++ b/services/sensorGuard/flink_app/config/settings.py @@ -0,0 +1,21 @@ +import os +from pathlib import Path + +BASE_DIR = Path(__file__).resolve().parent.parent + +class Settings: + # --- API Configuration --- + DEVICES_API_BASE = os.getenv("DEVICES_API_BASE", "http://host.docker.internal:8001") + DEVICES_API_TOKEN = os.getenv("DEVICES_API_TOKEN", None) + + # --- Kafka Configuration --- + KAFKA_BROKERS = os.getenv("KAFKA_BROKERS", "kafka:9092") + IN_TOPIC = os.getenv("IN_TOPIC", "sensors") + OUT_TOPIC = os.getenv("OUT_TOPIC", "event_logs_sensors") + KAFKA_GROUP_ID = os.getenv("KAFKA_GROUP_ID", "flink-device-pipeline") + + # --- Flink runtime paths --- + PYTHON_EXEC = os.getenv("PYFLINK_PYTHON", "/opt/venv/bin/python") + RULES_FILE = BASE_DIR / "config" / "rules.yaml" + +settings = Settings() diff --git a/services/sensorGuard/flink_app/core/__init__.py b/services/sensorGuard/flink_app/core/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/sensorGuard/flink_app/core/engine.py b/services/sensorGuard/flink_app/core/engine.py new file mode 100644 index 000000000..f4b897b93 --- /dev/null +++ b/services/sensorGuard/flink_app/core/engine.py @@ -0,0 +1,182 @@ +# core/engine.py + +from .state import StateStore +from .types import Event, Alert +from .rules import corrupted, out_of_range, stuck_sensor +from datetime import datetime, timezone +import time +import os + +from api.devices_updater import update_device_last_seen +from api.devices_client import get_sensors_last_seen +from api.auth import get_access_token + + +class Engine: + def __init__(self, cfg, writer, state: StateStore | None = None): + """ + cfg: dict read from rules.yaml (includes features/ranges/defaults/stuck) + writer: either a single object with write(alert) or a list of writers + """ + self.cfg = cfg + self.writers = writer if isinstance(writer, (list, tuple)) else [writer] + self.state = state or StateStore() + + # --- API info & persistent token --- + self.api_base = os.getenv("DB_API_BASE", "http://db_api_service:8001") + self.token = get_access_token(self.api_base) + if self.token: + print("[ENGINE] Access token acquired successfully.") + else: + print("[ENGINE][WARN] Failed to get API token at startup.") + + # --- Utilities --------------------------------------------------------- + + def _emit(self, alert: Alert): + for w in self.writers: + w.write(alert) + + def _open_once(self, dev_state, alert: Alert): + """Open an event only if it’s not already open for the same issue_type.""" + if alert.issue_type not in dev_state.open_alerts: + dev_state.open_alerts[alert.issue_type] = alert + print(f"[ENGINE] Opening new alert: {alert.issue_type} for device {alert.device_id}") + self._emit(alert) + + def _close_if_open(self, dev_state, issue_type: str, ts): + """Close an open event (if exists) and update end_ts.""" + if issue_type in dev_state.open_alerts: + a = dev_state.open_alerts.pop(issue_type) + a.end_ts = ts + print(f"[ENGINE] Closing alert: {issue_type} for device {a.device_id}") + self._emit(a) + + def _close_all_keepalive_alerts(self, dev_state, ts): + """Close missing_keepalive alert when sensor sends valid data.""" + print(f"[ENGINE] Checking open alerts before close_all_keepalive_alerts: {list(dev_state.open_alerts.keys())}") + + if "missing_keepalive" in dev_state.open_alerts: + a = dev_state.open_alerts.pop("missing_keepalive") + a.end_ts = ts + print(f"[ENGINE] Closing missing_keepalive alert (sensor back online) for {a.device_id}") + self._emit(a) + else: + print(f"[ENGINE] No missing_keepalive alert to close for this device") + + # ---------------------------------------------------------------------- + + def sweep_silence(self, now): + """ + Periodic silence check based on DB 'devices_sensor.last_seen'. + Checks for missing_keepalive (not prolonged_silence). + """ + print("[ENGINE] Starting silence sweep (via DB API)...") + + # Fetch sensors via API - uses same pattern as PATCH (host.docker.internal) + sensors = get_sensors_last_seen() + + if not sensors: + print("[ENGINE][ERROR] No sensors retrieved. Skipping silence sweep.") + return + + expected = self.cfg.get("expected_interval_seconds", 60) + miss_factor = self.cfg.get("keepalive_miss_factor", 3) + miss_thr = miss_factor * expected + print(f"[ENGINE] Checking {len(sensors)} sensors for missing keepalive > {miss_thr}s") + + for s in sensors: + sensor_id = s.get("id") + last_seen_str = s.get("last_seen") + if not sensor_id or not last_seen_str: + continue + + try: + last_seen = datetime.fromisoformat(last_seen_str.replace("Z", "+00:00")) + except Exception: + print(f"[ENGINE][WARN] Invalid timestamp for {sensor_id}: {last_seen_str}") + continue + + gap = (now - last_seen).total_seconds() + + # Check for missing_keepalive only + dev_state = self.state.get(sensor_id) + if dev_state and gap >= miss_thr and "missing_keepalive" not in dev_state.open_alerts: + alert = Alert( + issue_type="missing_keepalive", + device_id=sensor_id, + sensor_type=s.get("sensor_type", "unknown"), + site_id=None, + severity="critical", + start_ts=last_seen, + end_ts=None, + details={"gap_sec": int(gap), "expected": expected}, + ) + print(f"[ENGINE] Sensor {sensor_id} missing keepalive for {int(gap)}s — creating alert.") + dev_state.open_alerts["missing_keepalive"] = alert + self._emit(alert) + elif dev_state and gap < miss_thr and "missing_keepalive" in dev_state.open_alerts: + # Close the alert if gap is back to normal + alert = dev_state.open_alerts.pop("missing_keepalive") + alert.end_ts = now + print(f"[ENGINE] Sensor {sensor_id} keepalive restored — closing alert.") + self._emit(alert) + + # ---------------------------------------------------------------------- + + def process_event(self, ev: Event): + """Process a single event and manage open/close logic for alerts.""" + print(f"[ENGINE] Processing event: device_id={ev.device_id}, msg_type={ev.msg_type}, sensor_type={ev.sensor_type}") + + if not self.state.is_known_device(ev.device_id): + print(f"[ENGINE] Unknown device {ev.device_id} - skipping") + return + + print(f"[ENGINE] Known device {ev.device_id} - processing") + feats = (self.cfg.get("features") or {}) + dev = self.state.get(ev.device_id) + + # === Step 1: Update device state and DB === + print(f"[ENGINE] Updating device {ev.device_id} last_seen_ts from {dev.last_seen_ts} to {ev.ts}") + dev.last_seen_ts = ev.ts + dev.last_value = ev.value + + # --- Update API record --- + update_device_last_seen(ev.device_id) + + if ev.sensor_type and ev.sensor_type != "unknown_sensor": + dev.sensor_type = ev.sensor_type + + # === Step 2: Close keepalive-related alerts === + self._close_all_keepalive_alerts(dev, ev.ts) + + # === Step 3: Corrupted readings === + if feats.get("corrupted", True): + a = corrupted(ev, self.cfg) + if a: + print(f"[ENGINE] Corrupted reading detected for device {ev.device_id}") + self._open_once(dev, a) + self._close_if_open(dev, "out_of_range", ev.ts) + self._close_if_open(dev, "stuck_sensor", ev.ts) + return + print(f"[ENGINE] No corrupted reading for device {ev.device_id}") + + # === Step 4: Out-of-range checks === + if feats.get("out_of_range", True): + print(f"[ENGINE] Checking out_of_range for device {ev.device_id}, value={ev.value}") + a = out_of_range(ev, self.cfg) + if a: + print(f"[ENGINE] Out-of-range detected for device {ev.device_id}: {a}") + self._open_once(dev, a) + else: + print(f"[ENGINE] Value in range for device {ev.device_id}") + self._close_if_open(dev, "out_of_range", ev.ts) + + # === Step 5: Stuck sensor checks === + if feats.get("stuck_sensor", True): + print(f"[ENGINE] Checking stuck_sensor for device {ev.device_id}") + a = stuck_sensor(ev, dev, self.cfg) + if a: + print(f"[ENGINE] Stuck sensor detected for device {ev.device_id}") + self._open_once(dev, a) + else: + self._close_if_open(dev, "stuck_sensor", ev.ts) diff --git a/services/sensorGuard/flink_app/core/rules.py b/services/sensorGuard/flink_app/core/rules.py new file mode 100644 index 000000000..36f22d537 --- /dev/null +++ b/services/sensorGuard/flink_app/core/rules.py @@ -0,0 +1,159 @@ +from typing import Optional, Dict, Any +from datetime import timezone +from .types import Event, Alert, DeviceState + +def _utc(dt): + """Return datetime with UTC tzinfo.""" + return dt if dt.tzinfo else dt.replace(tzinfo=timezone.utc) + +def out_of_range(event: Event, cfg: Dict[str, Any]) -> Optional[Alert]: + """Check if sensor value is outside configured min/max.""" + if event.msg_type not in ["reading", "telemetry"] or event.value is None: + return None + rngs = (cfg or {}).get("ranges", {}) + lim = rngs.get(event.sensor_type, {}) + vmin, vmax = lim.get("min"), lim.get("max") + print(f"[RULES] out_of_range: sensor_type={event.sensor_type}, value={event.value}, lim={lim}, vmin={vmin}, vmax={vmax}") + if vmin is not None and event.value < vmin: + return Alert( + device_id=event.device_id, issue_type="out_of_range", + start_ts=_utc(event.ts), end_ts=None, severity="warn", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"value": event.value, "min": vmin, "max": vmax} + ) + if vmax is not None and event.value > vmax: + return Alert( + device_id=event.device_id, issue_type="out_of_range", + start_ts=_utc(event.ts), end_ts=None, severity="warn", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"value": event.value, "min": vmin, "max": vmax} + ) + return None + +def corrupted(event: Event, cfg: Dict[str, Any]) -> Optional[Alert]: + """Check if reading is invalid (null, non-numeric, bad quality).""" + if event.msg_type not in ["reading", "telemetry"]: + return None + if event.value is None: + return Alert( + device_id=event.device_id, issue_type="corrupted", + start_ts=_utc(event.ts), end_ts=None, severity="error", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"reason": "null value"} + ) + + if not isinstance(event.value, (int, float)): + return Alert( + device_id=event.device_id, issue_type="corrupted", + start_ts=_utc(event.ts), end_ts=None, severity="error", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"reason": "non-numeric"} + ) + + if event.quality and event.quality != "ok": + return Alert( + device_id=event.device_id, issue_type="corrupted", + start_ts=_utc(event.ts), end_ts=None, severity="error", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"quality": event.quality} + ) + return None + +def stuck_sensor(event: Event, state: DeviceState, cfg) -> Alert | None: + """Check if sensor value is stuck (no change over time).""" + if event.msg_type not in ["reading", "telemetry"] or event.value is None: + state.last_seen_ts = _utc(event.ts) + return None + + eps = cfg.get("stuck", {}).get("epsilon", 0.1) + min_run = cfg.get("stuck", {}).get("min_run_length", 6) + min_dur = cfg.get("stuck", {}).get("min_duration_seconds", 1800) # Default to 1800 instead of 0! + + # Debug log + if state.last_value is None: + print(f"[STUCK_SENSOR] Config for {event.device_id}: eps={eps}, min_run={min_run}, min_dur={min_dur}") + + if state.last_value is None: + state.last_value = event.value + state.run_length = 1 + state.last_seen_ts = _utc(event.ts) + state.stuck_since_ts = None + return None + + if abs(event.value - state.last_value) < eps: + state.run_length += 1 + if state.stuck_since_ts is None: + state.stuck_since_ts = _utc(event.ts) + print(f"[STUCK_SENSOR] Device {event.device_id}: run_length={state.run_length}, value={event.value}, stuck_since={state.stuck_since_ts}") + else: + print(f"[STUCK_SENSOR] Device {event.device_id}: value changed {state.last_value} -> {event.value}, resetting run_length") + state.run_length = 1 + state.stuck_since_ts = None + state.last_value = event.value + + state.last_seen_ts = _utc(event.ts) + + if state.run_length >= min_run: + if min_dur <= 0: + print(f"[STUCK_SENSOR] Device {event.device_id}: ALERT triggered (no min_dur)") + return Alert( + device_id=event.device_id, issue_type="stuck_sensor", + start_ts=state.stuck_since_ts or _utc(event.ts), end_ts=None, severity="warn", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"run_length": state.run_length, "epsilon": eps} + ) + else: + dur = (_utc(event.ts) - (state.stuck_since_ts or _utc(event.ts))).total_seconds() + print(f"[STUCK_SENSOR] Device {event.device_id}: run_length={state.run_length} >= {min_run}, dur={dur}s, min_dur={min_dur}s") + if dur >= min_dur: + print(f"[STUCK_SENSOR] Device {event.device_id}: ALERT triggered (dur >= min_dur)") + return Alert( + device_id=event.device_id, issue_type="stuck_sensor", + start_ts=state.stuck_since_ts, end_ts=None, severity="warn", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"run_length": state.run_length, "duration_sec": int(dur), "epsilon": eps} + ) + return None + +def silence_checks(event: Event, state: DeviceState, cfg) -> list[Alert]: + """Check for missing keepalive or prolonged silence alerts.""" + alerts: list[Alert] = [] + now_ts = _utc(event.ts) + + expected = cfg.get("expected_interval_seconds", 60) + miss_factor = cfg.get("keepalive_miss_factor", 3) + silence_sec = cfg.get("prolonged_silence_seconds", 1800) + + if state.last_seen_ts is None: + state.last_seen_ts = now_ts + return alerts + + gap = (now_ts - state.last_seen_ts).total_seconds() + + if gap >= silence_sec and "prolonged_silence" not in state.open_alerts: + a = Alert(device_id=event.device_id, issue_type="prolonged_silence", + start_ts=state.last_seen_ts, end_ts=None, severity="error", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"gap_sec": int(gap)}) + state.open_alerts["prolonged_silence"] = a + alerts.append(a) + elif gap < silence_sec and "prolonged_silence" in state.open_alerts: + a = state.open_alerts.pop("prolonged_silence") + a.end_ts = now_ts + alerts.append(a) + + miss_thr = miss_factor * expected + if gap >= miss_thr and gap < silence_sec and "missing_keepalive" not in state.open_alerts: + a = Alert(device_id=event.device_id, issue_type="missing_keepalive", + start_ts=state.last_seen_ts, end_ts=None, severity="critical", + sensor_type=event.sensor_type, site_id=event.site_id, + details={"gap_sec": int(gap), "expected": expected}) + state.open_alerts["missing_keepalive"] = a + alerts.append(a) + elif (gap < miss_thr or gap >= silence_sec) and "missing_keepalive" in state.open_alerts: + a = state.open_alerts.pop("missing_keepalive") + a.end_ts = now_ts + alerts.append(a) + + state.last_seen_ts = now_ts + return alerts diff --git a/services/sensorGuard/flink_app/core/state.py b/services/sensorGuard/flink_app/core/state.py new file mode 100644 index 000000000..5efa13420 --- /dev/null +++ b/services/sensorGuard/flink_app/core/state.py @@ -0,0 +1,32 @@ +from .types import DeviceState +from typing import Dict, Set + +class StateStore: + def __init__(self): + self._devices: Dict[str, DeviceState] = {} + self._known_device_ids: Set[str] = set() + + @property + def devices(self): + """Expose internal devices dictionary (read-only).""" + return self._devices + + def add_device(self, device_id: str, sensor_type: str = None) -> None: + """Initialize state for a known device.""" + device_id = str(device_id) + self._known_device_ids.add(device_id) + if device_id not in self._devices: + self._devices[device_id] = DeviceState(device_id=device_id, sensor_type=sensor_type) + + def get(self, device_id: str) -> DeviceState: + """Return state for known device, or None if unknown.""" + device_id = str(device_id) + return self._devices.get(device_id) + + def is_known_device(self, device_id: str) -> bool: + """Check if device was loaded from API.""" + return str(device_id) in self._known_device_ids + + def all_states(self): + """Iterator over all registered device states.""" + return self._devices.items() diff --git a/services/sensorGuard/flink_app/core/types.py b/services/sensorGuard/flink_app/core/types.py new file mode 100644 index 000000000..b256537fb --- /dev/null +++ b/services/sensorGuard/flink_app/core/types.py @@ -0,0 +1,35 @@ +from dataclasses import dataclass, field +from typing import Optional, Dict +from datetime import datetime + +@dataclass +class Event: + ts: datetime + device_id: str + sensor_type: str + site_id: Optional[str] + msg_type: str # "reading" | "keepalive" + value: Optional[float] + seq: Optional[int] + quality: Optional[str] # "ok"/"corrupted"/None + +@dataclass +class Alert: + device_id: str + issue_type: str + start_ts: datetime + end_ts: Optional[datetime] + severity: str + sensor_type: Optional[str] = None + site_id: Optional[str] = None + details: Dict = field(default_factory=dict) + +@dataclass +class DeviceState: + device_id: str + sensor_type: Optional[str] = None + last_seen_ts: Optional[datetime] = None + last_value: Optional[float] = None + run_length: int = 0 + stuck_since_ts: Optional[datetime] = None + open_alerts: Dict[str, "Alert"] = field(default_factory=dict) diff --git a/services/sensorGuard/flink_app/io_mod/__init__.py b/services/sensorGuard/flink_app/io_mod/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/services/sensorGuard/flink_app/io_mod/writer_console.py b/services/sensorGuard/flink_app/io_mod/writer_console.py new file mode 100644 index 000000000..2f62cb0d4 --- /dev/null +++ b/services/sensorGuard/flink_app/io_mod/writer_console.py @@ -0,0 +1,11 @@ +from core.types import Alert + +class ConsoleWriter: + def write(self, alert: Alert) -> None: + end = alert.end_ts.isoformat() if alert.end_ts else "-" + print( + f"[ALERT] type={alert.issue_type} dev={alert.device_id} " + f"sensor={alert.sensor_type} value={alert.details.get('value')} " + f"range=[{alert.details.get('min')},{alert.details.get('max')}] " + f"ts={alert.start_ts.isoformat()} sev={alert.severity}" + ) diff --git a/services/sensorGuard/flink_app/io_mod/writer_kafka.py b/services/sensorGuard/flink_app/io_mod/writer_kafka.py new file mode 100644 index 000000000..2ffb6cfd4 --- /dev/null +++ b/services/sensorGuard/flink_app/io_mod/writer_kafka.py @@ -0,0 +1,123 @@ +import os +import json +from datetime import datetime +from typing import Any, Dict, Optional + +from kafka import KafkaProducer +from core.types import Alert +from config.settings import settings + + +# Convert Alert dataclass to a stable dict for JSON serialization and downstream consumers. +def _alert_to_dict(alert: Alert) -> Dict[str, Any]: + """ + Convert Alert to an ordered, serialization-friendly dict. + Suitable for downstream consumers (DB / API / BI). + """ + details: Dict[str, Any] = getattr(alert, "details", {}) or {} + + def iso(dt: Optional[datetime]) -> Optional[str]: + return dt.isoformat() if dt else None + + d = { + "issue_type": getattr(alert, "issue_type", None), + "device_id": getattr(alert, "device_id", None), + "severity": getattr(alert, "severity", None), + "start_ts": iso(getattr(alert, "start_ts", None)), + "details": details, + } + + end_ts = getattr(alert, "end_ts", None) + if end_ts is not None: + d["end_ts"] = iso(end_ts) + + return d + + + + +# Kafka writer: send Alert objects as JSON value-only messages. +# Lazy-initialize producer to avoid early network/socket creation. +class KafkaWriter: + """ + Write Alerts to Kafka as JSON (value-only). + Defaults: + - topic from OUT_TOPIC env or 'dev-robot-telemetry-raw' + - brokers from KAFKA_BROKERS env or 'kafka:9092' + """ + def __init__( + self, + topic: str | None = None, + brokers: str | None = None, + linger_ms: int = 10, + acks: str = "all", + retries: int = 5, + ) -> None: + # Topic and bootstrap configuration. + self.topic = topic or settings.OUT_TOPIC + self.bootstrap = brokers or settings.KAFKA_BROKERS + # Producer tuning parameters. + self.linger_ms = linger_ms + self.acks = acks + self.retries = retries + # Producer instance created on first use. + self._producer: Optional[KafkaProducer] = None + + # Ensure a KafkaProducer exists; create it lazily with safe JSON serializer. + def _ensure_producer(self) -> None: + """Lazy-init KafkaProducer with JSON serializer and configured options.""" + if self._producer is None: + print(f"[KafkaWriter] Creating KafkaProducer: brokers={self.bootstrap}, topic={self.topic}") + try: + self._producer = KafkaProducer( + bootstrap_servers=self.bootstrap, + value_serializer=lambda v: json.dumps(v, ensure_ascii=False).encode("utf-8"), + linger_ms=self.linger_ms, + acks=self.acks, + retries=self.retries, + ) + print("[KafkaWriter] KafkaProducer created successfully.") + except Exception as e: + print(f"[KafkaWriter][ERROR] Failed to create KafkaProducer: {e!r}") + raise + + # Serialize and send an Alert to Kafka; log errors to stdout. + def write(self, alert: Alert) -> None: + """Send an Alert to Kafka (non-blocking send).""" + print(f"[KafkaWriter] write() called for alert: device={getattr(alert, 'device_id', None)}, issue={getattr(alert, 'issue_type', None)}") + try: + if getattr(alert, "issue_type", None) == "unknown_device": + print(f"[KafkaWriter] Skipping unknown device alert for {alert.device_id}") + return + + self._ensure_producer() + payload = _alert_to_dict(alert) + print(f"[KafkaWriter] Sending payload: {payload}") + self._producer.send(self.topic, payload) + + print( + f"[KafkaWriter] Alert sent → topic='{self.topic}', " + f"device='{alert.device_id}', issue='{alert.issue_type}', " + f"time={payload.get('start_ts')}" + ) + except Exception as e: + print(f"[KafkaWriter][ERROR] send failed: {e!r}") + + # Flush producer buffers if the producer exists. + def flush(self) -> None: + """Flush any buffered messages to Kafka.""" + try: + if self._producer: + self._producer.flush() + except Exception as e: + print(f"[KafkaWriter] flush failed: {e!r}") + + # Flush and close the underlying producer if present. + def close(self) -> None: + """Gracefully flush and close the Kafka producer.""" + try: + if self._producer: + self._producer.flush() + self._producer.close() + except Exception as e: + print(f"[KafkaWriter] close failed: {e!r}") diff --git a/services/sensorGuard/flink_app/main.py b/services/sensorGuard/flink_app/main.py new file mode 100644 index 000000000..2fe44b93b --- /dev/null +++ b/services/sensorGuard/flink_app/main.py @@ -0,0 +1,221 @@ +import os, json, yaml, threading, time +from datetime import datetime, timezone +from pathlib import Path + +from pyflink.datastream import StreamExecutionEnvironment +from pyflink.datastream.connectors.kafka import KafkaSource +from pyflink.common.serialization import SimpleStringSchema +from pyflink.common.watermark_strategy import WatermarkStrategy +from pyflink.common.typeinfo import Types +from pyflink.datastream.functions import MapFunction, ProcessFunction, RuntimeContext + +from core.engine import Engine +from core.types import Event +from io_mod.writer_console import ConsoleWriter +from io_mod.writer_kafka import KafkaWriter +from api.auth import get_access_token +from api.devices_client import list_active_sensors +from core.state import StateStore + + +DROP_INVALID = True + + +# ------------------------------------------------------------- +# Convert incoming Kafka message to Event +# ------------------------------------------------------------- +def to_event(obj: dict) -> Event | None: + if not isinstance(obj, dict): + print("[to_event] Invalid object type, expected dict.") + return None + + ts = datetime.now(timezone.utc) + device_id = obj.get("sensor_id") + sensor_type = obj.get("sensor_type") or obj.get("sensor_name", "unknown_sensor") + + if not device_id: + if DROP_INVALID: + print("[to_event] Dropping event due to missing device_id.") + return None + device_id = "unknown_device" + else: + device_id = str(device_id) + + value_str = obj.get("value") + try: + value = float(value_str) if value_str is not None else None + except ValueError: + print(f"[to_event] Invalid numeric value: {value_str}") + value = None + + print(f"[to_event] Parsed event: device_id={device_id}, sensor_type={sensor_type}") + + return Event( + ts=ts, + device_id=device_id, + sensor_type=sensor_type, + site_id=obj.get("site_id"), + msg_type=obj.get("msg_type", "reading"), + value=value, + seq=obj.get("seq"), + quality=obj.get("quality"), + ) + + +# ------------------------------------------------------------- +# Engine Mapper: applies Engine logic for each event +# ------------------------------------------------------------- +class EngineMapper(MapFunction): + def __init__(self, cfg_path: str, state: StateStore): + self.cfg_path = cfg_path + self.state = state + self.engine = None + + def open(self, runtime_context: RuntimeContext): + with open(self.cfg_path, "r", encoding="utf-8") as f: + cfg = yaml.safe_load(f) or {} + writers = [ConsoleWriter(), KafkaWriter()] + self.engine = Engine(cfg, writers, state=self.state) + + def map(self, ev: Event) -> str: + if ev is None: + return "" + print(f"[EngineMapper] Processing event for device_id={ev.device_id}") + self.engine.process_event(ev) + return ev.device_id or "" + + +# ------------------------------------------------------------- +# Silence Sweep Process (background thread) +# ------------------------------------------------------------- +class SilenceSweepProcess(ProcessFunction): + def __init__(self, cfg_path: str, interval_sec: int, state: StateStore): + self.cfg_path = cfg_path + self.interval_sec = interval_sec + self.state = state + self.engine = None + self._thread = None + self._stop = False + + def open(self, runtime_context: RuntimeContext): + print("[SilenceSweepProcess] Initializing background silence checker.") + with open(self.cfg_path, "r", encoding="utf-8") as f: + cfg = yaml.safe_load(f) or {} + + writers = [ConsoleWriter(), KafkaWriter()] + self.engine = Engine(cfg, writers, state=self.state) + + # Run silence sweep periodically in a separate thread + def loop(): + print(f"[SilenceSweep] Thread started! Interval={self.interval_sec}s") + time.sleep(self.interval_sec) + while not self._stop: + now = datetime.now(timezone.utc) + print(f"[SilenceSweep] Checking silence at {now.isoformat()}") + try: + self.engine.sweep_silence(now) + print("[SilenceSweep] Sweep completed.") + except Exception as e: + print(f"[SilenceSweep][ERROR] {e}") + time.sleep(self.interval_sec) + print("[SilenceSweep] Thread stopped.") + + self._thread = threading.Thread(target=loop, daemon=True) + self._thread.start() + + def close(self): + self._stop = True + if self._thread: + self._thread.join(timeout=2) + self._thread = None + + def process_element(self, value, ctx: 'ProcessFunction.Context'): + # No per-event logic needed + pass + + +# ------------------------------------------------------------- +# Main entry point +# ------------------------------------------------------------- +def main(): + print("=== STARTING FLINK APPLICATION ===") + base_dir = Path(__file__).resolve().parent + cfg_path = base_dir / "config" / "rules.yaml" + + # --- Load sensors from API --- + api_base = os.getenv("DB_API_BASE", "http://db_api_service:8001") + print(f"[INIT] Fetching active sensors from {api_base}...") + + token = get_access_token(api_base) + print(f"[INIT] Token received: {'YES' if token else 'NO'}") + + shared_state = StateStore() + if token: + for device_id in list_active_sensors(api_base, token): + shared_state.add_device(device_id) + print(f"[INIT] Loaded {len(shared_state.devices)} active sensors.") + else: + print("[INIT][WARN] No token, running with empty device list.") + + # --- Flink Setup --- + bootstrap = os.getenv("KAFKA_BROKERS", "kafka:9092") + topic_in = os.getenv("IN_TOPIC", "sensors") + group_id = os.getenv("KAFKA_GROUP_ID", "flink-device-pipeline") + + env = StreamExecutionEnvironment.get_execution_environment() + env.set_parallelism(1) + env.enable_checkpointing(10_000) + + # Kafka source + source = ( + KafkaSource.builder() + .set_bootstrap_servers(bootstrap) + .set_topics(topic_in) + .set_group_id(group_id) + .set_value_only_deserializer(SimpleStringSchema()) + .build() + ) + + stream = env.from_source( + source, + WatermarkStrategy.no_watermarks(), + f"kafka-source:{topic_in}" + ) + + # --- Processing pipeline --- + def parse_json(s: str): + try: + parsed = json.loads(s) + print(f"[FLINK-KAFKA] Parsed JSON: {s[:100]}...") + return parsed + except Exception as e: + print(f"[FLINK-KAFKA] Parse error: {e}") + return None + + events = ( + stream.map(parse_json) + .filter(lambda e: e is not None) + .map(to_event) + .filter(lambda e: e is not None) + ) + + # --- Apply Engine --- + mapper = EngineMapper(str(cfg_path), shared_state) + mapped = events.map(mapper, output_type=Types.STRING()).name("engine-run") + mapped.print().name("debug-print") + + # --- Silence check background thread --- + with open(cfg_path, "r", encoding="utf-8") as f: + cfg = yaml.safe_load(f) or {} + interval = cfg.get("defaults", {}).get("silence_sweep_interval_seconds", 300) + + silence_checker = SilenceSweepProcess(str(cfg_path), interval, shared_state) + events.process(silence_checker).name("silence-sweeper") + + print("[INIT] Starting Flink job...") + env.execute("DevicePipeline-With-SilenceSweep") + + +if __name__ == "__main__": + print("=== FLINK MAIN.PY EXECUTED ===") + main() diff --git a/services/sensorGuard/flink_app/resources/synthetic_stream.csv b/services/sensorGuard/flink_app/resources/synthetic_stream.csv new file mode 100644 index 000000000..71ee492ee --- /dev/null +++ b/services/sensorGuard/flink_app/resources/synthetic_stream.csv @@ -0,0 +1,523 @@ +timestamp,id,sensor_type,site_id,msg_type,value,seq,quality +2025-09-01T08:00:00Z,hum-A2,humidity,field-01,keepalive,,181,ok +2025-09-01T08:00:00Z,hum-A2,humidity,field-01,reading,54.617,1,ok +2025-09-01T08:00:00Z,soil-A3,soil_moist,field-02,keepalive,,91,ok +2025-09-01T08:00:00Z,soil-A3,soil_moist,field-02,reading,35.313,1,ok +2025-09-01T08:00:00Z,temp-A1,temperature,field-01,keepalive,,151,ok +2025-09-01T08:00:00Z,temp-A1,temperature,field-01,reading,27.338,1,ok +2025-09-01T08:01:00Z,hum-A2,humidity,field-01,reading,55.572,2,ok +2025-09-01T08:01:00Z,temp-A1,temperature,field-01,reading,26.959,2,ok +2025-09-01T08:02:00Z,hum-A2,humidity,field-01,reading,55.767,3,ok +2025-09-01T08:02:00Z,soil-A3,soil_moist,field-02,reading,35.63,2,ok +2025-09-01T08:02:00Z,temp-A1,temperature,field-01,reading,27.112,3,ok +2025-09-01T08:03:00Z,hum-A2,humidity,field-01,reading,56.764,4,ok +2025-09-01T08:03:00Z,temp-A1,temperature,field-01,reading,27.239,4,ok +2025-09-01T08:04:00Z,hum-A2,humidity,field-01,reading,56.144,5,ok +2025-09-01T08:04:00Z,soil-A3,soil_moist,field-02,reading,35.011,3,ok +2025-09-01T08:04:00Z,temp-A1,temperature,field-01,reading,27.052,5,ok +2025-09-01T08:05:00Z,hum-A2,humidity,field-01,keepalive,,182,ok +2025-09-01T08:05:00Z,hum-A2,humidity,field-01,reading,54.829,6,ok +2025-09-01T08:05:00Z,soil-A3,soil_moist,field-02,keepalive,,92,ok +2025-09-01T08:05:00Z,temp-A1,temperature,field-01,keepalive,,152,ok +2025-09-01T08:05:00Z,temp-A1,temperature,field-01,reading,27.263,6,ok +2025-09-01T08:06:00Z,hum-A2,humidity,field-01,reading,55.477,7,ok +2025-09-01T08:06:00Z,soil-A3,soil_moist,field-02,reading,35.495,4,ok +2025-09-01T08:06:00Z,temp-A1,temperature,field-01,reading,27.314,7,ok +2025-09-01T08:07:00Z,hum-A2,humidity,field-01,reading,57.417,8,ok +2025-09-01T08:07:00Z,temp-A1,temperature,field-01,reading,27.016,8,ok +2025-09-01T08:08:00Z,hum-A2,humidity,field-01,reading,56.884,9,ok +2025-09-01T08:08:00Z,soil-A3,soil_moist,field-02,reading,35.178,5,ok +2025-09-01T08:08:00Z,temp-A1,temperature,field-01,reading,27.622,9,ok +2025-09-01T08:09:00Z,hum-A2,humidity,field-01,reading,58.258,10,ok +2025-09-01T08:09:00Z,temp-A1,temperature,field-01,reading,27.59,10,ok +2025-09-01T08:10:00Z,hum-A2,humidity,field-01,keepalive,,183,ok +2025-09-01T08:10:00Z,hum-A2,humidity,field-01,reading,57.821,11,ok +2025-09-01T08:10:00Z,soil-A3,soil_moist,field-02,keepalive,,93,ok +2025-09-01T08:10:00Z,soil-A3,soil_moist,field-02,reading,35.237,6,ok +2025-09-01T08:10:00Z,temp-A1,temperature,field-01,keepalive,,153,ok +2025-09-01T08:10:00Z,temp-A1,temperature,field-01,reading,27.395,11,ok +2025-09-01T08:11:00Z,hum-A2,humidity,field-01,reading,57.256,12,ok +2025-09-01T08:11:00Z,temp-A1,temperature,field-01,reading,27.537,12,ok +2025-09-01T08:12:00Z,hum-A2,humidity,field-01,reading,58.973,13,ok +2025-09-01T08:12:00Z,soil-A3,soil_moist,field-02,reading,35.794,7,ok +2025-09-01T08:12:00Z,temp-A1,temperature,field-01,reading,27.722,13,ok +2025-09-01T08:13:00Z,hum-A2,humidity,field-01,reading,57.71,14,ok +2025-09-01T08:13:00Z,temp-A1,temperature,field-01,reading,27.619,14,ok +2025-09-01T08:14:00Z,hum-A2,humidity,field-01,reading,56.961,15,ok +2025-09-01T08:14:00Z,soil-A3,soil_moist,field-02,reading,36.138,8,ok 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+2025-09-01T10:36:00Z,temp-A1,temperature,field-01,reading,25.044,127,ok +2025-09-01T10:37:00Z,hum-A2,humidity,field-01,reading,45.478,158,ok +2025-09-01T10:37:00Z,temp-A1,temperature,field-01,reading,25.478,128,ok +2025-09-01T10:38:00Z,hum-A2,humidity,field-01,reading,46.41,159,ok +2025-09-01T10:38:00Z,soil-A3,soil_moist,field-02,reading,34.191,80,ok +2025-09-01T10:38:00Z,temp-A1,temperature,field-01,reading,25.539,129,ok +2025-09-01T10:39:00Z,hum-A2,humidity,field-01,reading,46.246,160,ok +2025-09-01T10:39:00Z,temp-A1,temperature,field-01,reading,25.467,130,ok +2025-09-01T10:40:00Z,hum-A2,humidity,field-01,keepalive,,213,ok +2025-09-01T10:40:00Z,hum-A2,humidity,field-01,reading,47.651,161,ok +2025-09-01T10:40:00Z,soil-A3,soil_moist,field-02,keepalive,,123,ok +2025-09-01T10:40:00Z,soil-A3,soil_moist,field-02,reading,34.053,81,ok +2025-09-01T10:40:00Z,temp-A1,temperature,field-01,keepalive,,177,ok +2025-09-01T10:40:00Z,temp-A1,temperature,field-01,reading,25.059,131,ok +2025-09-01T10:41:00Z,hum-A2,humidity,field-01,reading,45.25,162,ok +2025-09-01T10:41:00Z,temp-A1,temperature,field-01,reading,25.303,132,ok +2025-09-01T10:42:00Z,hum-A2,humidity,field-01,reading,44.853,163,ok +2025-09-01T10:42:00Z,soil-A3,soil_moist,field-02,reading,34.537,82,ok +2025-09-01T10:42:00Z,temp-A1,temperature,field-01,reading,25.569,133,ok +2025-09-01T10:43:00Z,hum-A2,humidity,field-01,reading,45.357,164,ok +2025-09-01T10:43:00Z,temp-A1,temperature,field-01,reading,24.875,134,ok +2025-09-01T10:44:00Z,hum-A2,humidity,field-01,reading,44.871,165,ok +2025-09-01T10:44:00Z,soil-A3,soil_moist,field-02,reading,35.114,83,ok +2025-09-01T10:44:00Z,temp-A1,temperature,field-01,reading,25.249,135,ok +2025-09-01T10:45:00Z,hum-A2,humidity,field-01,keepalive,,214,ok +2025-09-01T10:45:00Z,hum-A2,humidity,field-01,reading,45.2,166,ok +2025-09-01T10:45:00Z,soil-A3,soil_moist,field-02,keepalive,,124,ok +2025-09-01T10:45:00Z,temp-A1,temperature,field-01,keepalive,,178,ok +2025-09-01T10:45:00Z,temp-A1,temperature,field-01,reading,25.357,136,ok +2025-09-01T10:46:00Z,hum-A2,humidity,field-01,reading,45.917,167,ok +2025-09-01T10:46:00Z,soil-A3,soil_moist,field-02,reading,33.488,84,ok +2025-09-01T10:46:00Z,temp-A1,temperature,field-01,reading,24.977,137,ok +2025-09-01T10:47:00Z,hum-A2,humidity,field-01,reading,46.112,168,ok +2025-09-01T10:47:00Z,temp-A1,temperature,field-01,reading,25.216,138,ok +2025-09-01T10:48:00Z,hum-A2,humidity,field-01,reading,46.744,169,ok +2025-09-01T10:48:00Z,soil-A3,soil_moist,field-02,reading,34.053,85,ok +2025-09-01T10:48:00Z,temp-A1,temperature,field-01,reading,24.869,139,ok +2025-09-01T10:49:00Z,hum-A2,humidity,field-01,reading,44.755,170,ok +2025-09-01T10:49:00Z,temp-A1,temperature,field-01,reading,24.906,140,ok +2025-09-01T10:50:00Z,hum-A2,humidity,field-01,keepalive,,215,ok +2025-09-01T10:50:00Z,hum-A2,humidity,field-01,reading,47.39,171,ok +2025-09-01T10:50:00Z,soil-A3,soil_moist,field-02,keepalive,,125,ok +2025-09-01T10:50:00Z,soil-A3,soil_moist,field-02,reading,33.488,86,ok +2025-09-01T10:50:00Z,temp-A1,temperature,field-01,keepalive,,179,ok +2025-09-01T10:50:00Z,temp-A1,temperature,field-01,reading,24.892,141,ok +2025-09-01T10:51:00Z,hum-A2,humidity,field-01,reading,46.807,172,ok +2025-09-01T10:51:00Z,temp-A1,temperature,field-01,reading,25.083,142,ok +2025-09-01T10:52:00Z,hum-A2,humidity,field-01,reading,45.007,173,ok +2025-09-01T10:52:00Z,soil-A3,soil_moist,field-02,reading,33.951,87,ok +2025-09-01T10:52:00Z,temp-A1,temperature,field-01,reading,25.016,143,ok +2025-09-01T10:53:00Z,hum-A2,humidity,field-01,reading,43.291,174,ok +2025-09-01T10:53:00Z,temp-A1,temperature,field-01,reading,25.216,144,ok +2025-09-01T10:54:00Z,hum-A2,humidity,field-01,reading,45.02,175,ok +2025-09-01T10:54:00Z,soil-A3,soil_moist,field-02,reading,33.667,88,ok +2025-09-01T10:54:00Z,temp-A1,temperature,field-01,reading,24.829,145,ok +2025-09-01T10:55:00Z,hum-A2,humidity,field-01,keepalive,,216,ok +2025-09-01T10:55:00Z,hum-A2,humidity,field-01,reading,45.113,176,ok +2025-09-01T10:55:00Z,soil-A3,soil_moist,field-02,keepalive,,126,ok +2025-09-01T10:55:00Z,temp-A1,temperature,field-01,keepalive,,180,ok +2025-09-01T10:55:00Z,temp-A1,temperature,field-01,reading,24.985,146,ok +2025-09-01T10:56:00Z,hum-A2,humidity,field-01,reading,43.192,177,ok +2025-09-01T10:56:00Z,soil-A3,soil_moist,field-02,reading,33.871,89,ok +2025-09-01T10:56:00Z,temp-A1,temperature,field-01,reading,25.198,147,ok +2025-09-01T10:57:00Z,hum-A2,humidity,field-01,reading,45.073,178,ok +2025-09-01T10:57:00Z,temp-A1,temperature,field-01,reading,25.115,148,ok +2025-09-01T10:58:00Z,hum-A2,humidity,field-01,reading,44.843,179,ok +2025-09-01T10:58:00Z,soil-A3,soil_moist,field-02,reading,31.839,90,ok +2025-09-01T10:58:00Z,temp-A1,temperature,field-01,reading,24.736,149,ok +2025-09-01T10:59:00Z,hum-A2,humidity,field-01,reading,44.371,180,ok +2025-09-01T10:59:00Z,temp-A1,temperature,field-01,reading,25.133,150,ok diff --git a/services/sensorGuard/pytest.ini b/services/sensorGuard/pytest.ini new file mode 100644 index 000000000..678c989ca --- /dev/null +++ b/services/sensorGuard/pytest.ini @@ -0,0 +1,16 @@ +[tool:pytest] +testpaths = tests +python_files = test_*.py +python_classes = Test* +python_functions = test_* +addopts = + --verbose + --tb=short + --cov=flink_app + --cov-report=html:coverage_html + --cov-report=term-missing + --cov-fail-under=70 +markers = + unit: Unit tests + integration: Integration tests + slow: Slow tests \ No newline at end of file diff --git a/services/sensorGuard/requirements.txt b/services/sensorGuard/requirements.txt new file mode 100644 index 000000000..e70d76a76 --- /dev/null +++ b/services/sensorGuard/requirements.txt @@ -0,0 +1,7 @@ +pyyaml +kafka-python>=2.0.2 +requests +urllib3 +grpcio +avro-python3==1.10.2 +protobuf==3.20.3 \ No newline at end of file diff --git a/services/sensorGuard/test-requirements.txt b/services/sensorGuard/test-requirements.txt new file mode 100644 index 000000000..59cd202e4 --- /dev/null +++ b/services/sensorGuard/test-requirements.txt @@ -0,0 +1,3 @@ +pytest>=7.0.0 +pytest-cov>=4.0.0 +pytest-mock>=3.10.0 \ No newline at end of file diff --git a/services/sensorGuard/tests/__init__.py b/services/sensorGuard/tests/__init__.py new file mode 100644 index 000000000..1d342c1a8 --- /dev/null +++ b/services/sensorGuard/tests/__init__.py @@ -0,0 +1 @@ +# Test package init \ No newline at end of file diff --git a/services/sensorGuard/tests/test_engine.py b/services/sensorGuard/tests/test_engine.py new file mode 100644 index 000000000..ba34aaaab --- /dev/null +++ b/services/sensorGuard/tests/test_engine.py @@ -0,0 +1,195 @@ +import pytest +from unittest.mock import Mock, patch +from datetime import datetime, timezone +import sys +import os + +# Add the flink_app to path for imports +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'flink_app')) + +from core.engine import Engine +from core.types import Event, Alert +from core.state import StateStore + + +@pytest.fixture(autouse=True) +def mock_engine_dependencies(): + """Mock external dependencies for Engine class""" + with patch('core.engine.get_access_token', return_value='test_token'), \ + patch('core.engine.update_device_last_seen'): + yield + + +class TestEngine: + """Test Engine class public methods""" + + def setup_method(self): + """Arrange - Set up test fixtures""" + self.mock_writer = Mock() + self.mock_cfg = { + 'features': {'out_of_range': True, 'stuck_sensor': True}, + 'ranges': {'temperature': {'min': 0, 'max': 50}}, + 'stuck': {'min_duration_seconds': 1800} + } + self.state_store = StateStore() + self.engine = Engine(self.mock_cfg, self.mock_writer, self.state_store) + + def test_engine_initialization(self): + """Test engine initializes correctly""" + # Assert + assert self.engine.cfg == self.mock_cfg + assert len(self.engine.writers) == 1 + assert self.engine.state is self.state_store + + def test_process_event_unknown_device(self): + """Test processing event for unknown device""" + # Arrange + event = Event( + ts=datetime.now(timezone.utc), + device_id="unknown_device", + sensor_type="temperature", + site_id=None, + msg_type="reading", + value=25.0, + seq=None, + quality="ok" + ) + + # Act + self.engine.process_event(event) + + # Assert - no alerts should be emitted for unknown devices + self.mock_writer.write.assert_not_called() + + def test_process_event_known_device_normal_value(self): + """Test processing normal value for known device""" + # Arrange + self.state_store.add_device("device_1", "temperature") + event = Event( + ts=datetime.now(timezone.utc), + device_id="device_1", + sensor_type="temperature", + site_id=None, + msg_type="reading", + value=25.0, + seq=None, + quality="ok" + ) + + # Act + self.engine.process_event(event) + + # Assert - device state should be updated + device_state = self.state_store.get("device_1") + assert device_state.last_seen_ts == event.ts + assert device_state.last_value == 25.0 + + def test_emit_alert_calls_all_writers(self): + """Test _emit calls write on all writers""" + # Arrange + writer1 = Mock() + writer2 = Mock() + engine = Engine(self.mock_cfg, [writer1, writer2], self.state_store) + alert = Alert( + device_id="device_1", + issue_type="test_alert", + severity="error", + start_ts=datetime.now(timezone.utc), + end_ts=None + ) + + # Act + engine._emit(alert) + + # Assert + writer1.write.assert_called_once_with(alert) + writer2.write.assert_called_once_with(alert) + + def test_open_once_new_alert(self): + """Test opening new alert when none exists""" + # Arrange + self.state_store.add_device("device_1", "temperature") + device_state = self.state_store.get("device_1") + alert = Alert( + device_id="device_1", + issue_type="out_of_range", + severity="error", + start_ts=datetime.now(timezone.utc), + end_ts=None + ) + + # Act + self.engine._open_once(device_state, alert) + + # Assert + assert "out_of_range" in device_state.open_alerts + self.mock_writer.write.assert_called_once_with(alert) + + def test_open_once_existing_alert(self): + """Test not opening duplicate alert""" + # Arrange + self.state_store.add_device("device_1", "temperature") + device_state = self.state_store.get("device_1") + + # Pre-existing alert + existing_alert = Alert( + device_id="device_1", + issue_type="out_of_range", + severity="error", + start_ts=datetime.now(timezone.utc), + end_ts=None + ) + device_state.open_alerts["out_of_range"] = existing_alert + + new_alert = Alert( + device_id="device_1", + issue_type="out_of_range", + severity="error", + start_ts=datetime.now(timezone.utc), + end_ts=None + ) + + # Act + self.engine._open_once(device_state, new_alert) + + # Assert - should not emit new alert + self.mock_writer.write.assert_not_called() + assert device_state.open_alerts["out_of_range"] is existing_alert + + def test_close_if_open_existing_alert(self): + """Test closing existing alert""" + # Arrange + self.state_store.add_device("device_1", "temperature") + device_state = self.state_store.get("device_1") + + alert = Alert( + device_id="device_1", + issue_type="out_of_range", + severity="error", + start_ts=datetime.now(timezone.utc), + end_ts=None + ) + device_state.open_alerts["out_of_range"] = alert + close_ts = datetime.now(timezone.utc) + + # Act + self.engine._close_if_open(device_state, "out_of_range", close_ts) + + # Assert + assert "out_of_range" not in device_state.open_alerts + assert alert.end_ts == close_ts + self.mock_writer.write.assert_called_once_with(alert) + + def test_close_if_open_nonexistent_alert(self): + """Test closing non-existent alert does nothing""" + # Arrange + self.state_store.add_device("device_1", "temperature") + device_state = self.state_store.get("device_1") + close_ts = datetime.now(timezone.utc) + + # Act + self.engine._close_if_open(device_state, "out_of_range", close_ts) + + # Assert - nothing should happen + self.mock_writer.write.assert_not_called() + assert len(device_state.open_alerts) == 0 \ No newline at end of file diff --git a/services/sensorGuard/tests/test_engine_quality.py b/services/sensorGuard/tests/test_engine_quality.py new file mode 100644 index 000000000..6f6c7e9e1 --- /dev/null +++ b/services/sensorGuard/tests/test_engine_quality.py @@ -0,0 +1,683 @@ +""" +Professional, comprehensive tests for the Engine class. +These tests verify REAL business logic, not just code coverage. +""" +import pytest +import time +from unittest.mock import Mock, MagicMock, patch +from datetime import datetime, timezone, timedelta + +import sys +import os +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'flink_app')) + +from core.engine import Engine +from core.types import Event, Alert, DeviceState +from core.state import StateStore + + +@pytest.fixture(autouse=True) +def mock_engine_dependencies(): + """Mock external dependencies for Engine class""" + with patch('core.engine.get_access_token', return_value='test_token'), \ + patch('core.engine.update_device_last_seen'), \ + patch('core.engine.get_sensors_last_seen', return_value=[]): + yield + + +class TestEngineBusinessLogic: + """Tests that verify the actual sensor monitoring business rules.""" + + def setup_method(self): + """Set up test environment with realistic configuration.""" + self.mock_writer = Mock() + self.cfg = { + "features": { + "corrupted": True, + "out_of_range": True, + "stuck_sensor": True, + "silence": True + }, + "prolonged_silence_seconds": 300, # 5 minutes + "ranges": { + "temperature": {"min": -40, "max": 85}, + "humidity": {"min": 0, "max": 100} + }, + "stuck": { + "temperature": {"tolerance": 0.1, "count": 5} + } + } + self.state_store = StateStore() + self.engine = Engine(self.cfg, self.mock_writer, self.state_store) + + def create_real_sensor_message(self, device_id, sensor_type, value, msg_type="telemetry", **extra): + """Create a message in the EXACT format that comes from real sensors.""" + return { + "sid": f"sensor-{device_id}", + "id": int(device_id), + "timestamp": datetime.now(timezone.utc).isoformat(), + "msg_type": msg_type, + "value": value, + "sensor": sensor_type, + "plant_id": 123, + "temperature": value if sensor_type == "temperature" else 25.0, + "humidity": value if sensor_type == "humidity" else 65.0, + "ph": 7.0, + "n": 50.0, + "p": 30.0, + "k": 40.0, + **extra + } + + def to_event(self, sensor_message): + """Convert sensor message to Event using EXACT logic from main.py.""" + if not isinstance(sensor_message, dict): + return None + ts = datetime.now(timezone.utc) + device_id = sensor_message.get("id") + sensor_type = sensor_message.get("sensor_type") or sensor_message.get("sensor", "unknown_sensor") + if not device_id: + device_id = "unknown_device" + else: + device_id = str(device_id) + + return Event( + ts=ts, + device_id=device_id, + sensor_type=sensor_type, + site_id=sensor_message.get("site_id"), + msg_type=sensor_message.get("msg_type", "reading"), + value=sensor_message.get("value"), + seq=sensor_message.get("seq"), + quality=sensor_message.get("quality"), + ) + + def test_new_unknown_device_is_ignored_completely(self): + """CRITICAL: Unknown devices should be completely ignored - no alerts, no state changes.""" + # Arrange: Create REAL sensor message from unknown device (not in state_store) + unknown_message = self.create_real_sensor_message( + device_id="999", # Device not added to state store + sensor_type="temperature", + value=25.0 + ) + + # Act: Convert and process like real system does + event = self.to_event(unknown_message) + assert event is not None, "Valid message should convert to event" + self.engine.process_event(event) + + # Assert: No alerts should be generated for unknown devices + assert self.mock_writer.write.call_count == 0 + + # Assert: Device should not be considered known + assert not self.state_store.is_known_device("999") + + # Assert: No state should exist for this device + result = self.state_store.get("999") + assert result is None, "Unknown device should return None from state store" + + def test_sensor_comeback_closes_keepalive_alerts_immediately(self): + """CRITICAL: When sensor sends data after being silent, missing_keepalive alert must close. + NOTE: prolonged_silence alerts are NOT closed by process_event - only by sweep_silence.""" + # Arrange: Add device and simulate missing keepalive alert + device_id = "5" + self.state_store.add_device(device_id, "temperature") + device_state = self.state_store.get(device_id) + + # Manually create open missing_keepalive alert (simulating sweep_silence) + now = datetime.now(timezone.utc) + missing_alert = Alert( + device_id=device_id, + issue_type="missing_keepalive", + start_ts=now - timedelta(minutes=10), + end_ts=None, + severity="error", + sensor_type="temperature", + site_id=None, + details={"reason": "no data received"} + ) + + device_state.open_alerts["missing_keepalive"] = missing_alert + + # Act: Sensor sends REAL comeback message + comeback_message = self.create_real_sensor_message( + device_id="5", + sensor_type="temperature", + value=23.5 + ) + + comeback_event = self.to_event(comeback_message) + assert comeback_event is not None + self.engine.process_event(comeback_event) + + # Assert: missing_keepalive alert should be closed (emitted with end_ts) + assert self.mock_writer.write.call_count >= 1, "Expected at least 1 alert emission" + + # Verify the closed alert has end_ts set + calls = self.mock_writer.write.call_args_list + closed_alerts = [call[0][0] for call in calls] + + keepalive_closed = any(alert.issue_type == "missing_keepalive" and alert.end_ts is not None + for alert in closed_alerts) + + assert keepalive_closed, "missing_keepalive alert should be closed with end_ts" + + # Assert: missing_keepalive alert should no longer be open + assert "missing_keepalive" not in device_state.open_alerts + + def test_out_of_range_alert_opens_and_closes_correctly(self): + """CRITICAL: Out-of-range alerts must open when value is invalid, close when valid.""" + # Arrange: Add device + device_id = "5" + self.state_store.add_device(device_id, "temperature") + + # Act 1: Send out-of-range value using REAL message format + bad_message = self.create_real_sensor_message( + device_id="5", + sensor_type="temperature", + value=150.0 # Way above max of 85 + ) + + bad_event = self.to_event(bad_message) + assert bad_event is not None, "Valid message should convert to event" + + self.engine.process_event(bad_event) + + # Assert: Out-of-range alert should be opened + device_state = self.state_store.get(device_id) + assert "out_of_range" in device_state.open_alerts + + # Find the out-of-range alert that was emitted + calls = self.mock_writer.write.call_args_list + out_of_range_alerts = [call[0][0] for call in calls if call[0][0].issue_type == "out_of_range"] + assert len(out_of_range_alerts) == 1 + assert out_of_range_alerts[0].end_ts is None # Should be open + + # Reset mock for next assertion + self.mock_writer.reset_mock() + + # Act 2: Send valid value using REAL message format + good_message = self.create_real_sensor_message( + device_id="5", + sensor_type="temperature", + value=22.0 # Within valid range + ) + + good_event = self.to_event(good_message) + assert good_event is not None, "Valid message should convert to event" + + self.engine.process_event(good_event) + + # Assert: Out-of-range alert should be closed + assert "out_of_range" not in device_state.open_alerts + + # Verify alert was closed (emitted with end_ts) + closing_calls = self.mock_writer.write.call_args_list + if closing_calls: # Alert closure generates emission + closed_alert = closing_calls[0][0][0] + assert closed_alert.issue_type == "out_of_range" + assert closed_alert.end_ts is not None + + def test_complete_alert_lifecycle_with_multiple_bad_then_good_messages(self): + """COMPREHENSIVE: Test complete alert lifecycle - multiple bad messages, then recovery.""" + # Arrange: Add device + device_id = "10" + self.state_store.add_device(device_id, "temperature") + device_state = self.state_store.get(device_id) + + # Act 1: Send first bad message (should open alert) + bad_message_1 = self.create_real_sensor_message( + device_id="10", + sensor_type="temperature", + value=200.0 # Way out of range + ) + + self.engine.process_event(self.to_event(bad_message_1)) + + # Assert: Alert should be open + assert "out_of_range" in device_state.open_alerts + assert self.mock_writer.write.call_count == 1 # One alert opened + + # Act 2: Send second bad message (should NOT open duplicate alert) + self.mock_writer.reset_mock() + bad_message_2 = self.create_real_sensor_message( + device_id="10", + sensor_type="temperature", + value=250.0 # Still out of range + ) + + self.engine.process_event(self.to_event(bad_message_2)) + + # Assert: Still same alert, no new alert created + assert "out_of_range" in device_state.open_alerts + assert self.mock_writer.write.call_count == 0 # No new alerts + + # Act 3: Send good message (should close alert) + self.mock_writer.reset_mock() + good_message = self.create_real_sensor_message( + device_id="10", + sensor_type="temperature", + value=25.0 # Back to normal + ) + + self.engine.process_event(self.to_event(good_message)) + + # Assert: Alert should be closed completely + assert "out_of_range" not in device_state.open_alerts + assert self.mock_writer.write.call_count == 1 # Alert closure emitted + + # Verify the closed alert has proper end_ts + closed_alert = self.mock_writer.write.call_args[0][0] + assert closed_alert.issue_type == "out_of_range" + assert closed_alert.device_id == device_id + assert closed_alert.end_ts is not None + assert closed_alert.end_ts > closed_alert.start_ts # End after start + + # Act 4: Send another good message (should NOT close anything) + self.mock_writer.reset_mock() + another_good = self.create_real_sensor_message( + device_id="10", + sensor_type="temperature", + value=30.0 + ) + + self.engine.process_event(self.to_event(another_good)) + + # Assert: No alert activity (no open alerts to close) + assert len(device_state.open_alerts) == 0 + assert self.mock_writer.write.call_count == 0 + + def test_multiple_alert_types_independence(self): + """CRITICAL: Different alert types should open/close independently.""" + # Arrange + device_id = "11" + self.state_store.add_device(device_id, "temperature") + device_state = self.state_store.get(device_id) + + # Act 1: Trigger out_of_range alert + bad_temp_message = self.create_real_sensor_message( + device_id="11", + sensor_type="temperature", + value=200.0 + ) + self.engine.process_event(self.to_event(bad_temp_message)) + + # Act 2: Manually add a missing_keepalive alert (simulating silence) + keepalive_alert = Alert( + device_id=device_id, + issue_type="missing_keepalive", + start_ts=datetime.now(timezone.utc), + end_ts=None, + severity="error", + sensor_type="temperature" + ) + device_state.open_alerts["missing_keepalive"] = keepalive_alert + + # Assert: Both alerts should be open + assert "out_of_range" in device_state.open_alerts + assert "missing_keepalive" in device_state.open_alerts + assert len(device_state.open_alerts) == 2 + + # Act 3: Send good temperature (should close out_of_range but not missing_keepalive) + self.mock_writer.reset_mock() + good_temp_message = self.create_real_sensor_message( + device_id="11", + sensor_type="temperature", + value=25.0 + ) + self.engine.process_event(self.to_event(good_temp_message)) + + # Assert: out_of_range closed, missing_keepalive should be closed by _close_all_keepalive_alerts + assert "out_of_range" not in device_state.open_alerts + assert "missing_keepalive" not in device_state.open_alerts # This should be closed by comeback + + # Should have emitted 2 alerts: out_of_range closure + missing_keepalive closure + assert self.mock_writer.write.call_count == 2 + + def test_corrupted_message_overrides_out_of_range_alerts(self): + """CRITICAL: Corrupted message should close out_of_range and stuck_sensor alerts.""" + # Arrange + device_id = "12" + self.state_store.add_device(device_id, "humidity") + device_state = self.state_store.get(device_id) + + # Act 1: Create out_of_range alert first + out_of_range_message = self.create_real_sensor_message( + device_id="12", + sensor_type="humidity", + value=150.0 # Above max of 100 + ) + self.engine.process_event(self.to_event(out_of_range_message)) + + assert "out_of_range" in device_state.open_alerts + first_alert_count = self.mock_writer.write.call_count + + # Act 2: Send corrupted message (None value) + self.mock_writer.reset_mock() + corrupted_message = self.create_real_sensor_message( + device_id="12", + sensor_type="humidity", + value=None # This triggers corrupted alert + ) + self.engine.process_event(self.to_event(corrupted_message)) + + # Assert: Corrupted should open, out_of_range should be closed + assert "corrupted" in device_state.open_alerts + assert "out_of_range" not in device_state.open_alerts + + # Should emit: 1 corrupted open + 1 out_of_range close + assert self.mock_writer.write.call_count == 2 + + def test_sensor_value_oscillation_alert_behavior(self): + """COMPLEX: Test alert behavior when sensor oscillates between good/bad values.""" + # Arrange + device_id = "13" + self.state_store.add_device(device_id, "temperature") + device_state = self.state_store.get(device_id) + + # Scenario: bad -> good -> bad -> good (should open/close/open/close) + test_sequence = [ + (100.0, True), # Bad (should open alert) + (25.0, False), # Good (should close alert) + (200.0, True), # Bad again (should open new alert) + (30.0, False) # Good again (should close alert) + ] + + total_opens = 0 + total_closes = 0 + + for i, (value, should_be_bad) in enumerate(test_sequence): + self.mock_writer.reset_mock() + + message = self.create_real_sensor_message( + device_id="13", + sensor_type="temperature", + value=value + ) + self.engine.process_event(self.to_event(message)) + + if should_be_bad: + # Should have alert open + assert "out_of_range" in device_state.open_alerts + if self.mock_writer.write.call_count > 0: + total_opens += 1 + else: + # Should NOT have alert open + assert "out_of_range" not in device_state.open_alerts + if self.mock_writer.write.call_count > 0: + total_closes += 1 + + # Should have opened 2 times and closed 2 times + assert total_opens == 2, f"Expected 2 opens, got {total_opens}" + assert total_closes == 2, f"Expected 2 closes, got {total_closes}" + + def test_sweep_silence_detects_missing_devices_correctly(self): + """CRITICAL: sweep_silence must detect devices that haven't been seen for too long. + This tests the REAL business logic: sweep_silence fetches from API and compares timestamps.""" + # Arrange: Add device to state store + device_id = "never_seen_device" + self.state_store.add_device(device_id, "humidity") + device_state = self.state_store.get(device_id) + + # Mock API to return this sensor with old last_seen timestamp + old_timestamp = (datetime.now(timezone.utc) - timedelta(minutes=10)).isoformat() + mock_sensors_from_api = [ + { + "id": device_id, + "sensor_type": "humidity", + "last_seen": old_timestamp + } + ] + + # Act: Run silence sweep with mocked API response + with patch('core.engine.get_sensors_last_seen', return_value=mock_sensors_from_api): + now = datetime.now(timezone.utc) + self.engine.sweep_silence(now) + + # Assert: missing_keepalive alert should be created (gap > threshold) + assert "missing_keepalive" in device_state.open_alerts, \ + f"Expected missing_keepalive alert for device silent for 10 minutes (threshold is ~3 minutes)" + + # Verify alert was emitted + assert self.mock_writer.write.call_count >= 1, "Expected alert emission" + emitted_alert = self.mock_writer.write.call_args[0][0] + assert emitted_alert.issue_type == "missing_keepalive" + assert emitted_alert.device_id == device_id + assert emitted_alert.end_ts is None, "Alert should be open" + + def test_sweep_silence_detects_prolonged_silence_correctly(self): + """CRITICAL: sweep_silence must detect devices silent for too long and close alerts when they resume. + This tests REAL business logic: comparing API timestamps against threshold.""" + # Arrange: Add device to state store + device_id = "old_device" + self.state_store.add_device(device_id, "temperature") + device_state = self.state_store.get(device_id) + + # Mock API to return sensor with old last_seen (10 minutes ago - exceeds 3 min threshold) + old_timestamp = (datetime.now(timezone.utc) - timedelta(minutes=10)).isoformat() + mock_sensors_from_api = [ + { + "id": device_id, + "sensor_type": "temperature", + "last_seen": old_timestamp + } + ] + + # Act: Run silence sweep with mocked API - should open missing_keepalive alert + with patch('core.engine.get_sensors_last_seen', return_value=mock_sensors_from_api): + now = datetime.now(timezone.utc) + self.engine.sweep_silence(now) + + # Assert: missing_keepalive alert should be created (device silent > threshold) + assert "missing_keepalive" in device_state.open_alerts, \ + "Expected missing_keepalive alert for device silent for 10 minutes" + + # Verify alert was emitted + assert self.mock_writer.write.call_count >= 1 + first_alert = self.mock_writer.write.call_args[0][0] + assert first_alert.issue_type == "missing_keepalive" + assert first_alert.device_id == device_id + assert first_alert.end_ts is None, "Initial alert should be open" + + # Reset mock for next phase + self.mock_writer.reset_mock() + + # Act 2: Run sweep again with RECENT timestamp - should close the alert + recent_timestamp = (datetime.now(timezone.utc) - timedelta(seconds=30)).isoformat() + mock_sensors_recent = [ + { + "id": device_id, + "sensor_type": "temperature", + "last_seen": recent_timestamp + } + ] + + with patch('core.engine.get_sensors_last_seen', return_value=mock_sensors_recent): + now = datetime.now(timezone.utc) + self.engine.sweep_silence(now) + + # Assert: Alert should be closed (gap now < threshold) + assert "missing_keepalive" not in device_state.open_alerts, \ + "Alert should be closed when device is no longer silent" + + # Verify closing alert was emitted + assert self.mock_writer.write.call_count >= 1 + closing_alert = self.mock_writer.write.call_args[0][0] + assert closing_alert.issue_type == "missing_keepalive" + assert closing_alert.end_ts is not None, "Closing alert should have end_ts" + + def test_multiple_writers_receive_all_alerts(self): + """CRITICAL: When multiple writers are configured, all must receive every alert.""" + # Arrange: Setup engine with multiple writers + writer1 = Mock() + writer2 = Mock() + writer3 = Mock() + + engine = Engine(self.cfg, [writer1, writer2, writer3], self.state_store) + + device_id = "7" + self.state_store.add_device(device_id, "temperature") + + # Act: Generate an alert using REAL message format + bad_message = self.create_real_sensor_message( + device_id="7", + sensor_type="temperature", + value=-100.0 # Out of range (below min of -40) + ) + + bad_event = self.to_event(bad_message) + assert bad_event is not None + engine.process_event(bad_event) + + # Assert: All writers should receive the alert + assert writer1.write.call_count == 1 + assert writer2.write.call_count == 1 + assert writer3.write.call_count == 1 + + # Verify they all got the same alert + alert1 = writer1.write.call_args[0][0] + alert2 = writer2.write.call_args[0][0] + alert3 = writer3.write.call_args[0][0] + + assert alert1.issue_type == alert2.issue_type == alert3.issue_type == "out_of_range" + assert alert1.device_id == alert2.device_id == alert3.device_id == device_id + + def test_device_state_updates_correctly_during_processing(self): + """CRITICAL: Device state must be updated properly with each event.""" + # Arrange + device_id = "8" + self.state_store.add_device(device_id, "humidity") + + initial_state = self.state_store.get(device_id) + assert initial_state.last_seen_ts is None + assert initial_state.last_value is None + + # Act: Process first event using REAL message format + first_message = self.create_real_sensor_message( + device_id="8", + sensor_type="humidity", + value=45.2 + ) + + first_event = self.to_event(first_message) + assert first_event is not None + first_process_time = first_event.ts # Capture the actual timestamp used + + self.engine.process_event(first_event) + + # Assert: State should be updated + updated_state = self.state_store.get(device_id) + assert updated_state.last_seen_ts == first_process_time + assert updated_state.last_value == 45.2 + assert updated_state.sensor_type == "humidity" + + # Act: Process second event with different values + time.sleep(0.1) # Ensure different timestamp + second_message = self.create_real_sensor_message( + device_id="8", + sensor_type="humidity", + value=67.8 + ) + + second_event = self.to_event(second_message) + assert second_event is not None + second_process_time = second_event.ts + + self.engine.process_event(second_event) + + # Assert: State should reflect latest values + final_state = self.state_store.get(device_id) + assert final_state.last_seen_ts == second_process_time + assert final_state.last_value == 67.8 + assert final_state.sensor_type == "humidity" + + +class TestEngineEdgeCases: + """Tests for edge cases and error scenarios.""" + + def setup_method(self): + self.mock_writer = Mock() + self.cfg = { + "features": {"corrupted": True, "out_of_range": True, "stuck_sensor": True, "silence": True}, + "prolonged_silence_seconds": 300 + } + self.engine = Engine(self.cfg, self.mock_writer) + + def create_real_sensor_message(self, device_id, sensor_type, value, msg_type="telemetry", **extra): + """Create a message in the EXACT format that comes from real sensors.""" + return { + "sid": f"sensor-{device_id}", + "id": int(device_id), + "timestamp": datetime.now(timezone.utc).isoformat(), + "msg_type": msg_type, + "value": value, + "sensor": sensor_type, + "plant_id": 123, + "temperature": value if sensor_type == "temperature" else 25.0, + "humidity": value if sensor_type == "humidity" else 65.0, + "ph": 7.0, + "n": 50.0, + "p": 30.0, + "k": 40.0, + **extra + } + + def to_event(self, sensor_message): + """Convert sensor message to Event using EXACT logic from main.py.""" + if not isinstance(sensor_message, dict): + return None + ts = datetime.now(timezone.utc) + device_id = sensor_message.get("id") + sensor_type = sensor_message.get("sensor_type") or sensor_message.get("sensor", "unknown_sensor") + if not device_id: + device_id = "unknown_device" + else: + device_id = str(device_id) + + return Event( + ts=ts, + device_id=device_id, + sensor_type=sensor_type, + site_id=sensor_message.get("site_id"), + msg_type=sensor_message.get("msg_type", "reading"), + value=sensor_message.get("value"), + seq=sensor_message.get("seq"), + quality=sensor_message.get("quality"), + ) + + def test_engine_handles_none_values_gracefully(self): + """Edge case: Engine should handle None/null values without crashing.""" + # Arrange: Add device + device_id = "9" + self.engine.state.add_device(device_id, "temperature") + + # Act: Send REAL message with None value (like corrupted sensor reading) + null_message = self.create_real_sensor_message( + device_id="9", + sensor_type="temperature", + value=None # Corrupted/missing sensor reading + ) + + null_event = self.to_event(null_message) + assert null_event is not None + + # This should not raise an exception + try: + self.engine.process_event(null_event) + except Exception as e: + pytest.fail(f"Engine crashed with None value: {e}") + + def test_sweep_silence_on_empty_state_store(self): + """Edge case: sweep_silence should handle empty state store.""" + # Act: Run sweep on empty state (should not crash) + try: + self.engine.sweep_silence(datetime.now(timezone.utc)) + except Exception as e: + pytest.fail(f"sweep_silence crashed on empty state: {e}") + + # Assert: No alerts should be generated + assert self.mock_writer.write.call_count == 0 + + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) \ No newline at end of file diff --git a/services/sensorGuard/tests/test_state.py b/services/sensorGuard/tests/test_state.py new file mode 100644 index 000000000..bb2e385fa --- /dev/null +++ b/services/sensorGuard/tests/test_state.py @@ -0,0 +1,136 @@ +import pytest +from unittest.mock import Mock +import sys +import os + +# Add the flink_app to path for imports +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'flink_app')) + +from core.state import StateStore +from core.types import DeviceState + + +class TestStateStore: + """Test StateStore class public methods""" + + def setup_method(self): + """Arrange - Set up test fixtures""" + self.state_store = StateStore() + + def test_add_device_new(self): + """Test adding new device to state store""" + # Act + self.state_store.add_device("device_1", "temperature") + + # Assert + assert self.state_store.is_known_device("device_1") + device_state = self.state_store.get("device_1") + assert device_state.device_id == "device_1" + assert device_state.sensor_type == "temperature" + + def test_add_device_existing(self): + """Test adding existing device doesn't overwrite""" + # Arrange + self.state_store.add_device("device_1", "temperature") + original_state = self.state_store.get("device_1") + + # Act - Try to add same device with different sensor type + self.state_store.add_device("device_1", "humidity") + + # Assert - Original state preserved + current_state = self.state_store.get("device_1") + assert current_state is original_state + assert current_state.sensor_type == "temperature" # Not changed + + def test_is_known_device_true(self): + """Test is_known_device returns True for existing device""" + # Arrange + self.state_store.add_device("device_1", "temperature") + + # Act & Assert + assert self.state_store.is_known_device("device_1") is True + + def test_is_known_device_false(self): + """Test is_known_device returns False for non-existing device""" + # Act & Assert + assert self.state_store.is_known_device("unknown_device") is False + + def test_get_device_existing(self): + """Test getting existing device state""" + # Arrange + self.state_store.add_device("device_1", "temperature") + + # Act + device_state = self.state_store.get("device_1") + + # Assert + assert device_state is not None + assert device_state.device_id == "device_1" + assert device_state.sensor_type == "temperature" + + def test_get_device_nonexistent(self): + """Test getting non-existent device returns None""" + # Act + device_state = self.state_store.get("unknown_device") + + # Assert + assert device_state is None + + def test_all_states_empty(self): + """Test getting all devices when store is empty""" + # Act + all_devices = list(self.state_store.all_states()) + + # Assert + assert len(all_devices) == 0 + + def test_all_states_multiple(self): + """Test getting all devices with multiple devices""" + # Arrange + self.state_store.add_device("device_1", "temperature") + self.state_store.add_device("device_2", "humidity") + self.state_store.add_device("device_3", "pressure") + + # Act + all_states = list(self.state_store.all_states()) + + # Assert + assert len(all_states) == 3 + device_ids = [device_id for device_id, state in all_states] + assert "device_1" in device_ids + assert "device_2" in device_ids + assert "device_3" in device_ids + + def test_state_persistence(self): + """Test that device state persists across operations""" + # Arrange + self.state_store.add_device("device_1", "temperature") + device_state = self.state_store.get("device_1") + + # Act - Modify state + from datetime import datetime, timezone + ts = datetime.now(timezone.utc) + device_state.last_seen_ts = ts + device_state.last_value = 25.0 + + # Assert - Changes persist when retrieving again + retrieved_state = self.state_store.get("device_1") + assert retrieved_state.last_seen_ts == ts + assert retrieved_state.last_value == 25.0 + + def test_multiple_devices_independence(self): + """Test that multiple devices maintain independent state""" + # Arrange + self.state_store.add_device("device_1", "temperature") + self.state_store.add_device("device_2", "humidity") + + device_1 = self.state_store.get("device_1") + device_2 = self.state_store.get("device_2") + + # Act - Modify only device_1 + device_1.last_value = 25.0 + + # Assert - device_2 not affected + assert device_1.last_value == 25.0 + assert device_2.last_value is None + assert device_1 is not device_2 \ No newline at end of file diff --git a/services/sensorGuard/tests/test_state_fixed.py b/services/sensorGuard/tests/test_state_fixed.py new file mode 100644 index 000000000..bb2e385fa --- /dev/null +++ b/services/sensorGuard/tests/test_state_fixed.py @@ -0,0 +1,136 @@ +import pytest +from unittest.mock import Mock +import sys +import os + +# Add the flink_app to path for imports +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'flink_app')) + +from core.state import StateStore +from core.types import DeviceState + + +class TestStateStore: + """Test StateStore class public methods""" + + def setup_method(self): + """Arrange - Set up test fixtures""" + self.state_store = StateStore() + + def test_add_device_new(self): + """Test adding new device to state store""" + # Act + self.state_store.add_device("device_1", "temperature") + + # Assert + assert self.state_store.is_known_device("device_1") + device_state = self.state_store.get("device_1") + assert device_state.device_id == "device_1" + assert device_state.sensor_type == "temperature" + + def test_add_device_existing(self): + """Test adding existing device doesn't overwrite""" + # Arrange + self.state_store.add_device("device_1", "temperature") + original_state = self.state_store.get("device_1") + + # Act - Try to add same device with different sensor type + self.state_store.add_device("device_1", "humidity") + + # Assert - Original state preserved + current_state = self.state_store.get("device_1") + assert current_state is original_state + assert current_state.sensor_type == "temperature" # Not changed + + def test_is_known_device_true(self): + """Test is_known_device returns True for existing device""" + # Arrange + self.state_store.add_device("device_1", "temperature") + + # Act & Assert + assert self.state_store.is_known_device("device_1") is True + + def test_is_known_device_false(self): + """Test is_known_device returns False for non-existing device""" + # Act & Assert + assert self.state_store.is_known_device("unknown_device") is False + + def test_get_device_existing(self): + """Test getting existing device state""" + # Arrange + self.state_store.add_device("device_1", "temperature") + + # Act + device_state = self.state_store.get("device_1") + + # Assert + assert device_state is not None + assert device_state.device_id == "device_1" + assert device_state.sensor_type == "temperature" + + def test_get_device_nonexistent(self): + """Test getting non-existent device returns None""" + # Act + device_state = self.state_store.get("unknown_device") + + # Assert + assert device_state is None + + def test_all_states_empty(self): + """Test getting all devices when store is empty""" + # Act + all_devices = list(self.state_store.all_states()) + + # Assert + assert len(all_devices) == 0 + + def test_all_states_multiple(self): + """Test getting all devices with multiple devices""" + # Arrange + self.state_store.add_device("device_1", "temperature") + self.state_store.add_device("device_2", "humidity") + self.state_store.add_device("device_3", "pressure") + + # Act + all_states = list(self.state_store.all_states()) + + # Assert + assert len(all_states) == 3 + device_ids = [device_id for device_id, state in all_states] + assert "device_1" in device_ids + assert "device_2" in device_ids + assert "device_3" in device_ids + + def test_state_persistence(self): + """Test that device state persists across operations""" + # Arrange + self.state_store.add_device("device_1", "temperature") + device_state = self.state_store.get("device_1") + + # Act - Modify state + from datetime import datetime, timezone + ts = datetime.now(timezone.utc) + device_state.last_seen_ts = ts + device_state.last_value = 25.0 + + # Assert - Changes persist when retrieving again + retrieved_state = self.state_store.get("device_1") + assert retrieved_state.last_seen_ts == ts + assert retrieved_state.last_value == 25.0 + + def test_multiple_devices_independence(self): + """Test that multiple devices maintain independent state""" + # Arrange + self.state_store.add_device("device_1", "temperature") + self.state_store.add_device("device_2", "humidity") + + device_1 = self.state_store.get("device_1") + device_2 = self.state_store.get("device_2") + + # Act - Modify only device_1 + device_1.last_value = 25.0 + + # Assert - device_2 not affected + assert device_1.last_value == 25.0 + assert device_2.last_value is None + assert device_1 is not device_2 \ No newline at end of file diff --git a/services/sensorGuard/tests/test_state_quality.py b/services/sensorGuard/tests/test_state_quality.py new file mode 100644 index 000000000..a068af528 --- /dev/null +++ b/services/sensorGuard/tests/test_state_quality.py @@ -0,0 +1,319 @@ +""" +Professional, comprehensive tests for StateStore class. +These tests verify data integrity and state management correctness. +""" +import pytest +from datetime import datetime, timezone, timedelta + +import sys +import os +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'flink_app')) + +from core.state import StateStore +from core.types import DeviceState, Alert + + +class TestStateStoreDataIntegrity: + """Tests that verify data integrity and correct state management.""" + + def setup_method(self): + """Set up fresh StateStore for each test.""" + self.state_store = StateStore() + + def test_add_device_creates_proper_state_structure(self): + """CRITICAL: Adding device must create correct internal state structure.""" + # Arrange + device_id = "sensor_001" + sensor_type = "temperature" + + # Act: Add device + self.state_store.add_device(device_id, sensor_type) + + # Assert: Device should be in known devices + assert self.state_store.is_known_device(device_id) + + # Assert: Device state should be properly initialized + device_state = self.state_store.get(device_id) + assert device_state is not None + assert device_state.device_id == device_id + assert device_state.sensor_type == sensor_type + assert device_state.last_seen_ts is None # Should start as None + assert device_state.last_value is None # Should start as None + assert device_state.open_alerts == {} # Should start empty + + def test_get_unknown_device_returns_none_safely(self): + """CRITICAL: Getting unknown device must return None, not crash.""" + # Act: Try to get device that was never added + result = self.state_store.get("nonexistent_device") + + # Assert: Should return None safely + assert result is None + + # Assert: Should not be considered known + assert not self.state_store.is_known_device("nonexistent_device") + + def test_device_state_persistence_across_operations(self): + """CRITICAL: Device state changes must persist correctly.""" + # Arrange: Add device and get its state + device_id = "persistent_device" + self.state_store.add_device(device_id, "humidity") + device_state = self.state_store.get(device_id) + + # Act: Modify device state + test_time = datetime.now(timezone.utc) + test_value = 42.7 + test_alert = Alert( + issue_type="test_alert", + device_id=device_id, + sensor_type="humidity", + site_id="test_site", + severity="warning", + start_ts=test_time, + end_ts=None, + details={"test": "data"} + ) + + device_state.last_seen_ts = test_time + device_state.last_value = test_value + device_state.open_alerts["test_alert"] = test_alert + + # Assert: Changes should persist when retrieving again + retrieved_state = self.state_store.get(device_id) + assert retrieved_state.last_seen_ts == test_time + assert retrieved_state.last_value == test_value + assert "test_alert" in retrieved_state.open_alerts + assert retrieved_state.open_alerts["test_alert"].issue_type == "test_alert" + + def test_multiple_devices_maintain_separate_states(self): + """CRITICAL: Multiple devices must have completely separate states.""" + # Arrange: Add multiple devices + device1 = "temp_sensor_01" + device2 = "humid_sensor_02" + device3 = "pressure_sensor_03" + + self.state_store.add_device(device1, "temperature") + self.state_store.add_device(device2, "humidity") + self.state_store.add_device(device3, "pressure") + + # Act: Set different values for each device + time1 = datetime.now(timezone.utc) + time2 = time1 + timedelta(minutes=1) + time3 = time1 + timedelta(minutes=2) + + state1 = self.state_store.get(device1) + state2 = self.state_store.get(device2) + state3 = self.state_store.get(device3) + + state1.last_seen_ts = time1 + state1.last_value = 25.5 + + state2.last_seen_ts = time2 + state2.last_value = 65.8 + + state3.last_seen_ts = time3 + state3.last_value = 1013.2 + + # Assert: Each device maintains its own independent state + retrieved1 = self.state_store.get(device1) + retrieved2 = self.state_store.get(device2) + retrieved3 = self.state_store.get(device3) + + assert retrieved1.last_seen_ts == time1 + assert retrieved1.last_value == 25.5 + assert retrieved1.sensor_type == "temperature" + + assert retrieved2.last_seen_ts == time2 + assert retrieved2.last_value == 65.8 + assert retrieved2.sensor_type == "humidity" + + assert retrieved3.last_seen_ts == time3 + assert retrieved3.last_value == 1013.2 + assert retrieved3.sensor_type == "pressure" + + def test_all_states_returns_correct_iterator(self): + """CRITICAL: all_states() must return all devices and their current states.""" + # Arrange: Add several devices with different states + devices_data = [ + ("device_a", "temperature", 22.1), + ("device_b", "humidity", 58.3), + ("device_c", "pressure", 1015.7) + ] + + for device_id, sensor_type, value in devices_data: + self.state_store.add_device(device_id, sensor_type) + state = self.state_store.get(device_id) + state.last_value = value + + # Act: Get all states + all_states = dict(self.state_store.all_states()) + + # Assert: Should contain exactly the devices we added + assert len(all_states) == 3 + assert "device_a" in all_states + assert "device_b" in all_states + assert "device_c" in all_states + + # Assert: States should contain correct data + assert all_states["device_a"].sensor_type == "temperature" + assert all_states["device_a"].last_value == 22.1 + + assert all_states["device_b"].sensor_type == "humidity" + assert all_states["device_b"].last_value == 58.3 + + assert all_states["device_c"].sensor_type == "pressure" + assert all_states["device_c"].last_value == 1015.7 + + def test_device_id_type_conversion_consistency(self): + """CRITICAL: Device IDs must be consistently converted to strings.""" + # Act: Add devices with different ID types + self.state_store.add_device(123, "temperature") # Integer + self.state_store.add_device("456", "humidity") # String + self.state_store.add_device(789.0, "pressure") # Float + + # Assert: All should be accessible as strings + assert self.state_store.is_known_device("123") + assert self.state_store.is_known_device("456") + assert self.state_store.is_known_device("789.0") + + # Assert: States should be retrievable with string IDs + assert self.state_store.get("123") is not None + assert self.state_store.get("456") is not None + assert self.state_store.get("789.0") is not None + + # Assert: Original types should also work (converted internally) + assert self.state_store.is_known_device(123) + assert self.state_store.is_known_device(456) + assert self.state_store.is_known_device(789.0) + + def test_duplicate_device_addition_is_safe(self): + """CRITICAL: Adding same device multiple times must be safe.""" + # Arrange: Add device and modify its state + device_id = "duplicate_test_device" + self.state_store.add_device(device_id, "temperature") + + original_state = self.state_store.get(device_id) + test_time = datetime.now(timezone.utc) + original_state.last_seen_ts = test_time + original_state.last_value = 99.9 + + # Act: Add same device again (should not overwrite existing state) + self.state_store.add_device(device_id, "humidity") # Different sensor type + + # Assert: Original state should be preserved + current_state = self.state_store.get(device_id) + assert current_state.last_seen_ts == test_time + assert current_state.last_value == 99.9 + assert current_state.sensor_type == "temperature" # Should keep original + + +class TestStateStoreEdgeCases: + """Tests for edge cases and boundary conditions.""" + + def setup_method(self): + self.state_store = StateStore() + + def test_empty_state_store_operations(self): + """Edge case: Operations on empty state store should be safe.""" + # Assert: Empty state store behaves correctly + assert not self.state_store.is_known_device("any_device") + assert self.state_store.get("any_device") is None + + # all_states should return empty iterator + all_states = list(self.state_store.all_states()) + assert len(all_states) == 0 + + def test_none_and_empty_device_ids(self): + """Edge case: None/empty device IDs should be handled gracefully.""" + # Act/Assert: These should not crash + try: + result1 = self.state_store.is_known_device("") + result2 = self.state_store.get("") + # Empty string is valid, should return False/None + assert result1 is False + assert result2 is None + except Exception as e: + pytest.fail(f"Empty string device ID caused crash: {e}") + + def test_very_large_number_of_devices(self): + """Performance test: Should handle many devices efficiently.""" + # Arrange: Add many devices + num_devices = 1000 + for i in range(num_devices): + device_id = f"device_{i:04d}" + self.state_store.add_device(device_id, f"sensor_type_{i % 10}") + + # Act/Assert: Should be able to access all devices + for i in range(num_devices): + device_id = f"device_{i:04d}" + assert self.state_store.is_known_device(device_id) + state = self.state_store.get(device_id) + assert state is not None + assert state.device_id == device_id + + # Should return correct count + all_states = list(self.state_store.all_states()) + assert len(all_states) == num_devices + + +class TestStateStoreBusinessRules: + """Tests that verify business logic around state management.""" + + def setup_method(self): + self.state_store = StateStore() + + def test_alert_lifecycle_management(self): + """Business rule: Alert lifecycle should be managed correctly in device state.""" + # Arrange: Add device + device_id = "alert_lifecycle_device" + self.state_store.add_device(device_id, "temperature") + device_state = self.state_store.get(device_id) + + # Act: Simulate alert lifecycle + now = datetime.now(timezone.utc) + + # 1. Open alert + alert1 = Alert( + issue_type="out_of_range", + device_id=device_id, + sensor_type="temperature", + site_id="site1", + severity="warning", + start_ts=now, + end_ts=None, + details={"value": 150.0, "max": 85.0} + ) + device_state.open_alerts["out_of_range"] = alert1 + + # 2. Open second alert + alert2 = Alert( + issue_type="stuck_sensor", + device_id=device_id, + sensor_type="temperature", + site_id="site1", + severity="error", + start_ts=now + timedelta(minutes=1), + end_ts=None, + details={"repeated_value": 150.0} + ) + device_state.open_alerts["stuck_sensor"] = alert2 + + # Assert: Both alerts should be tracked + assert len(device_state.open_alerts) == 2 + assert "out_of_range" in device_state.open_alerts + assert "stuck_sensor" in device_state.open_alerts + + # 3. Close first alert + closed_alert = device_state.open_alerts.pop("out_of_range") + closed_alert.end_ts = now + timedelta(minutes=2) + + # Assert: Only one alert should remain open + assert len(device_state.open_alerts) == 1 + assert "out_of_range" not in device_state.open_alerts + assert "stuck_sensor" in device_state.open_alerts + + # Assert: Closed alert should have end_ts + assert closed_alert.end_ts is not None + + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) \ No newline at end of file diff --git a/services/sensorGuard/tests/test_types.py b/services/sensorGuard/tests/test_types.py new file mode 100644 index 000000000..d049f6da3 --- /dev/null +++ b/services/sensorGuard/tests/test_types.py @@ -0,0 +1,170 @@ +import pytest +from datetime import datetime, timezone +import sys +import os + +# Add the flink_app to path for imports +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'flink_app')) + +from core.types import Event, Alert, DeviceState + + +class TestEvent: + """Test Event class""" + + def test_event_creation(self): + """Test creating Event with valid data""" + # Arrange + ts = datetime.now(timezone.utc) + + # Act + event = Event( + ts=ts, + device_id="sensor_1", + sensor_type="temperature", + site_id=None, + msg_type="telemetry", + value=25.5, + seq=1, + quality="ok" + ) + + # Assert + assert event.ts == ts + assert event.device_id == "sensor_1" + assert event.sensor_type == "temperature" + assert event.value == 25.5 + assert event.msg_type == "telemetry" + assert event.seq == 1 + assert event.quality == "ok" + + def test_event_with_minimal_data(self): + """Test creating Event with minimal required data""" + # Arrange & Act + ts = datetime.now(timezone.utc) + event = Event( + ts=ts, + device_id="sensor_1", + sensor_type="temperature", + site_id=None, + msg_type="reading", + value=None, + seq=None, + quality=None + ) + + # Assert + assert event.device_id == "sensor_1" + assert event.sensor_type == "temperature" + assert event.value is None + + +class TestAlert: + """Test Alert class""" + + def test_alert_creation(self): + """Test creating Alert with valid data""" + # Arrange + start_ts = datetime.now(timezone.utc) + + # Act + alert = Alert( + device_id="sensor_1", + issue_type="out_of_range", + severity="error", + start_ts=start_ts, + end_ts=None, + sensor_type="temperature" + ) + + # Assert + assert alert.issue_type == "out_of_range" + assert alert.device_id == "sensor_1" + assert alert.severity == "error" + assert alert.start_ts == start_ts + assert alert.end_ts is None + assert alert.sensor_type == "temperature" + + def test_alert_with_end_time(self): + """Test alert with both start and end times""" + # Arrange + start_ts = datetime.now(timezone.utc) + end_ts = datetime.now(timezone.utc) + + # Act + alert = Alert( + device_id="sensor_2", + issue_type="missing_keepalive", + severity="critical", + start_ts=start_ts, + end_ts=end_ts + ) + + # Assert + assert alert.start_ts == start_ts + assert alert.end_ts == end_ts + + +class TestDeviceState: + """Test DeviceState class""" + + def test_device_state_creation(self): + """Test creating DeviceState""" + # Arrange & Act + device_state = DeviceState( + device_id="sensor_1", + sensor_type="temperature" + ) + + # Assert + assert device_state.device_id == "sensor_1" + assert device_state.sensor_type == "temperature" + assert device_state.last_seen_ts is None + assert device_state.last_value is None + assert len(device_state.open_alerts) == 0 + + def test_device_state_update(self): + """Test updating device state""" + # Arrange + device_state = DeviceState( + device_id="sensor_1", + sensor_type="temperature" + ) + ts = datetime.now(timezone.utc) + + # Act + device_state.last_seen_ts = ts + device_state.last_value = 25.0 + + # Assert + assert device_state.last_seen_ts == ts + assert device_state.last_value == 25.0 + + def test_device_state_alerts_management(self): + """Test managing alerts in device state""" + # Arrange + device_state = DeviceState( + device_id="sensor_1", + sensor_type="temperature" + ) + alert = Alert( + device_id="sensor_1", + issue_type="out_of_range", + severity="error", + start_ts=datetime.now(timezone.utc), + end_ts=None + ) + + # Act - Add alert + device_state.open_alerts["out_of_range"] = alert + + # Assert + assert "out_of_range" in device_state.open_alerts + assert device_state.open_alerts["out_of_range"] == alert + + # Act - Remove alert + removed_alert = device_state.open_alerts.pop("out_of_range") + + # Assert + assert removed_alert == alert + assert len(device_state.open_alerts) == 0 \ No newline at end of file diff --git a/services/sensorGuard/tests/test_types_fixed.py b/services/sensorGuard/tests/test_types_fixed.py new file mode 100644 index 000000000..d049f6da3 --- /dev/null +++ b/services/sensorGuard/tests/test_types_fixed.py @@ -0,0 +1,170 @@ +import pytest +from datetime import datetime, timezone +import sys +import os + +# Add the flink_app to path for imports +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'flink_app')) + +from core.types import Event, Alert, DeviceState + + +class TestEvent: + """Test Event class""" + + def test_event_creation(self): + """Test creating Event with valid data""" + # Arrange + ts = datetime.now(timezone.utc) + + # Act + event = Event( + ts=ts, + device_id="sensor_1", + sensor_type="temperature", + site_id=None, + msg_type="telemetry", + value=25.5, + seq=1, + quality="ok" + ) + + # Assert + assert event.ts == ts + assert event.device_id == "sensor_1" + assert event.sensor_type == "temperature" + assert event.value == 25.5 + assert event.msg_type == "telemetry" + assert event.seq == 1 + assert event.quality == "ok" + + def test_event_with_minimal_data(self): + """Test creating Event with minimal required data""" + # Arrange & Act + ts = datetime.now(timezone.utc) + event = Event( + ts=ts, + device_id="sensor_1", + sensor_type="temperature", + site_id=None, + msg_type="reading", + value=None, + seq=None, + quality=None + ) + + # Assert + assert event.device_id == "sensor_1" + assert event.sensor_type == "temperature" + assert event.value is None + + +class TestAlert: + """Test Alert class""" + + def test_alert_creation(self): + """Test creating Alert with valid data""" + # Arrange + start_ts = datetime.now(timezone.utc) + + # Act + alert = Alert( + device_id="sensor_1", + issue_type="out_of_range", + severity="error", + start_ts=start_ts, + end_ts=None, + sensor_type="temperature" + ) + + # Assert + assert alert.issue_type == "out_of_range" + assert alert.device_id == "sensor_1" + assert alert.severity == "error" + assert alert.start_ts == start_ts + assert alert.end_ts is None + assert alert.sensor_type == "temperature" + + def test_alert_with_end_time(self): + """Test alert with both start and end times""" + # Arrange + start_ts = datetime.now(timezone.utc) + end_ts = datetime.now(timezone.utc) + + # Act + alert = Alert( + device_id="sensor_2", + issue_type="missing_keepalive", + severity="critical", + start_ts=start_ts, + end_ts=end_ts + ) + + # Assert + assert alert.start_ts == start_ts + assert alert.end_ts == end_ts + + +class TestDeviceState: + """Test DeviceState class""" + + def test_device_state_creation(self): + """Test creating DeviceState""" + # Arrange & Act + device_state = DeviceState( + device_id="sensor_1", + sensor_type="temperature" + ) + + # Assert + assert device_state.device_id == "sensor_1" + assert device_state.sensor_type == "temperature" + assert device_state.last_seen_ts is None + assert device_state.last_value is None + assert len(device_state.open_alerts) == 0 + + def test_device_state_update(self): + """Test updating device state""" + # Arrange + device_state = DeviceState( + device_id="sensor_1", + sensor_type="temperature" + ) + ts = datetime.now(timezone.utc) + + # Act + device_state.last_seen_ts = ts + device_state.last_value = 25.0 + + # Assert + assert device_state.last_seen_ts == ts + assert device_state.last_value == 25.0 + + def test_device_state_alerts_management(self): + """Test managing alerts in device state""" + # Arrange + device_state = DeviceState( + device_id="sensor_1", + sensor_type="temperature" + ) + alert = Alert( + device_id="sensor_1", + issue_type="out_of_range", + severity="error", + start_ts=datetime.now(timezone.utc), + end_ts=None + ) + + # Act - Add alert + device_state.open_alerts["out_of_range"] = alert + + # Assert + assert "out_of_range" in device_state.open_alerts + assert device_state.open_alerts["out_of_range"] == alert + + # Act - Remove alert + removed_alert = device_state.open_alerts.pop("out_of_range") + + # Assert + assert removed_alert == alert + assert len(device_state.open_alerts) == 0 \ No newline at end of file diff --git a/services/sensorGuard/tests/test_types_quality.py b/services/sensorGuard/tests/test_types_quality.py new file mode 100644 index 000000000..d72e23ce8 --- /dev/null +++ b/services/sensorGuard/tests/test_types_quality.py @@ -0,0 +1,439 @@ +""" +Professional, comprehensive tests for Types (dataclasses). +These tests verify data validation, business rules, and type safety. +""" +import pytest +from datetime import datetime, timezone, timedelta +from copy import deepcopy + +import sys +import os +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'flink_app')) + +from core.types import Event, Alert, DeviceState + + +class TestEventDataIntegrity: + """Tests that verify Event dataclass behavior and business rules.""" + + def test_event_creation_with_all_required_fields(self): + """CRITICAL: Event must be creatable with all required fields.""" + # Arrange + test_time = datetime.now(timezone.utc) + + # Act: Create event with all fields + event = Event( + ts=test_time, + device_id="sensor_123", + sensor_type="temperature", + site_id="greenhouse_a", + msg_type="reading", + value=24.7, + seq=42, + quality="ok" + ) + + # Assert: All fields should be set correctly + assert event.ts == test_time + assert event.device_id == "sensor_123" + assert event.sensor_type == "temperature" + assert event.site_id == "greenhouse_a" + assert event.msg_type == "reading" + assert event.value == 24.7 + assert event.seq == 42 + assert event.quality == "ok" + + def test_event_with_none_optional_fields(self): + """Business rule: Event should handle None values for optional fields.""" + # Act: Create event with minimal required fields + event = Event( + ts=datetime.now(timezone.utc), + device_id="minimal_device", + sensor_type="humidity", + site_id=None, # Optional + msg_type="keepalive", + value=None, # Optional (e.g., keepalive messages) + seq=None, # Optional + quality=None # Optional + ) + + # Assert: Should handle None values gracefully + assert event.site_id is None + assert event.value is None + assert event.seq is None + assert event.quality is None + + def test_event_immutability_after_creation(self): + """Data integrity: Event fields should be modifiable after creation.""" + # Arrange: Create event + original_time = datetime.now(timezone.utc) + event = Event( + ts=original_time, + device_id="test_device", + sensor_type="temperature", + site_id="site1", + msg_type="reading", + value=25.0, + seq=1, + quality="ok" + ) + + # Act: Modify fields (should be allowed for dataclass) + new_time = original_time + timedelta(seconds=30) + event.ts = new_time + event.value = 26.5 + event.quality = "corrupted" + + # Assert: Changes should be reflected + assert event.ts == new_time + assert event.value == 26.5 + assert event.quality == "corrupted" + + def test_event_different_msg_types_validation(self): + """Business rule: Different msg_type values should be handled correctly.""" + base_params = { + "ts": datetime.now(timezone.utc), + "device_id": "msg_type_test", + "sensor_type": "temperature", + "site_id": "site1" + } + + # Test reading message + reading_event = Event( + **base_params, + msg_type="reading", + value=23.4, + seq=1, + quality="ok" + ) + assert reading_event.msg_type == "reading" + assert reading_event.value is not None + + # Test keepalive message (typically no sensor value) + keepalive_event = Event( + **base_params, + msg_type="keepalive", + value=None, # Keepalives usually don't have sensor values + seq=2, + quality=None + ) + assert keepalive_event.msg_type == "keepalive" + assert keepalive_event.value is None + + +class TestAlertDataIntegrity: + """Tests that verify Alert dataclass behavior and lifecycle management.""" + + def test_alert_creation_with_required_fields(self): + """CRITICAL: Alert must be creatable with all required fields.""" + # Arrange + start_time = datetime.now(timezone.utc) + + # Act: Create alert + alert = Alert( + device_id="alert_test_device", + issue_type="out_of_range", + start_ts=start_time, + end_ts=None, # Open alert + severity="warning", + sensor_type="temperature", + site_id="greenhouse_b", + details={"value": 150.0, "max_allowed": 85.0} + ) + + # Assert: All fields should be set correctly + assert alert.device_id == "alert_test_device" + assert alert.issue_type == "out_of_range" + assert alert.start_ts == start_time + assert alert.end_ts is None + assert alert.severity == "warning" + assert alert.sensor_type == "temperature" + assert alert.site_id == "greenhouse_b" + assert alert.details["value"] == 150.0 + assert alert.details["max_allowed"] == 85.0 + + def test_alert_lifecycle_open_to_closed(self): + """Business rule: Alert should properly transition from open to closed state.""" + # Arrange: Create open alert + start_time = datetime.now(timezone.utc) + alert = Alert( + device_id="lifecycle_test", + issue_type="stuck_sensor", + start_ts=start_time, + end_ts=None, # Initially open + severity="error" + ) + + # Verify initially open + assert alert.end_ts is None + + # Act: Close the alert + end_time = start_time + timedelta(minutes=5) + alert.end_ts = end_time + + # Assert: Should be properly closed + assert alert.end_ts == end_time + duration = alert.end_ts - alert.start_ts + assert duration.total_seconds() == 300 # 5 minutes + + def test_alert_different_severities(self): + """Business rule: Different severity levels should be supported.""" + base_params = { + "device_id": "severity_test", + "issue_type": "test_issue", + "start_ts": datetime.now(timezone.utc), + "end_ts": None + } + + # Test different severity levels + warning_alert = Alert(**base_params, severity="warning") + error_alert = Alert(**base_params, severity="error") + critical_alert = Alert(**base_params, severity="critical") + + assert warning_alert.severity == "warning" + assert error_alert.severity == "error" + assert critical_alert.severity == "critical" + + def test_alert_details_dictionary_flexibility(self): + """Business rule: Alert details should support flexible data structures.""" + # Act: Create alert with complex details + alert = Alert( + device_id="details_test", + issue_type="complex_issue", + start_ts=datetime.now(timezone.utc), + end_ts=None, + severity="warning", + details={ + "sensor_readings": [22.1, 22.1, 22.1, 22.1], + "threshold": 0.1, + "consecutive_count": 4, + "metadata": { + "location": "field_section_3", + "operator": "automated_system" + }, + "numeric_value": 42.7, + "boolean_flag": True + } + ) + + # Assert: Complex details should be preserved + assert len(alert.details["sensor_readings"]) == 4 + assert alert.details["threshold"] == 0.1 + assert alert.details["metadata"]["location"] == "field_section_3" + assert alert.details["numeric_value"] == 42.7 + assert alert.details["boolean_flag"] is True + + +class TestDeviceStateDataIntegrity: + """Tests that verify DeviceState dataclass behavior and state management.""" + + def test_device_state_creation_with_minimal_params(self): + """CRITICAL: DeviceState should initialize with sensible defaults.""" + # Act: Create device state with minimal parameters + device_state = DeviceState(device_id="minimal_device") + + # Assert: Should have proper defaults + assert device_state.device_id == "minimal_device" + assert device_state.sensor_type is None + assert device_state.last_seen_ts is None + assert device_state.last_value is None + assert device_state.run_length == 0 + assert device_state.stuck_since_ts is None + assert device_state.open_alerts == {} + + def test_device_state_alert_management(self): + """Business rule: DeviceState should properly manage multiple open alerts.""" + # Arrange: Create device state + device_state = DeviceState( + device_id="multi_alert_device", + sensor_type="temperature" + ) + + # Act: Add multiple alerts + now = datetime.now(timezone.utc) + + alert1 = Alert( + device_id="multi_alert_device", + issue_type="out_of_range", + start_ts=now, + end_ts=None, + severity="warning" + ) + + alert2 = Alert( + device_id="multi_alert_device", + issue_type="stuck_sensor", + start_ts=now + timedelta(minutes=1), + end_ts=None, + severity="error" + ) + + device_state.open_alerts["out_of_range"] = alert1 + device_state.open_alerts["stuck_sensor"] = alert2 + + # Assert: Both alerts should be tracked + assert len(device_state.open_alerts) == 2 + assert "out_of_range" in device_state.open_alerts + assert "stuck_sensor" in device_state.open_alerts + + # Assert: Alerts should maintain their properties + assert device_state.open_alerts["out_of_range"].severity == "warning" + assert device_state.open_alerts["stuck_sensor"].severity == "error" + + def test_device_state_evolution_over_time(self): + """Business rule: DeviceState should track sensor data evolution correctly.""" + # Arrange: Create device state + device_state = DeviceState( + device_id="evolution_test", + sensor_type="humidity" + ) + + # Act: Simulate sensor data evolution + time1 = datetime.now(timezone.utc) + time2 = time1 + timedelta(minutes=1) + time3 = time1 + timedelta(minutes=2) + + # First reading + device_state.last_seen_ts = time1 + device_state.last_value = 45.2 + device_state.run_length = 1 + + # Second reading (same value - potential stuck sensor) + device_state.last_seen_ts = time2 + device_state.last_value = 45.2 # Same value + device_state.run_length = 2 + device_state.stuck_since_ts = time1 # Started being stuck from first occurrence + + # Third reading (different value - unstuck) + device_state.last_seen_ts = time3 + device_state.last_value = 46.8 # Different value + device_state.run_length = 1 # Reset + device_state.stuck_since_ts = None # No longer stuck + + # Assert: State evolution should be properly tracked + assert device_state.last_seen_ts == time3 + assert device_state.last_value == 46.8 + assert device_state.run_length == 1 + assert device_state.stuck_since_ts is None + + def test_device_state_deep_copy_independence(self): + """Data integrity: DeviceState copies should be independent.""" + # Arrange: Create device state with complex data + original_time = datetime.now(timezone.utc) + original_state = DeviceState( + device_id="copy_test", + sensor_type="temperature", + last_seen_ts=original_time, + last_value=25.0, + run_length=3 + ) + + # Add an alert + alert = Alert( + device_id="copy_test", + issue_type="test_alert", + start_ts=original_time, + end_ts=None, + severity="warning" + ) + original_state.open_alerts["test_alert"] = alert + + # Act: Create deep copy + copied_state = deepcopy(original_state) + + # Modify original + new_time = original_time + timedelta(minutes=1) + original_state.last_seen_ts = new_time + original_state.last_value = 26.0 + original_state.open_alerts["test_alert"].severity = "error" + + # Assert: Copy should remain unchanged + assert copied_state.last_seen_ts == original_time + assert copied_state.last_value == 25.0 + assert copied_state.open_alerts["test_alert"].severity == "warning" + + +class TestTypesBusinessRules: + """Tests that verify business rules across all types.""" + + def test_event_to_alert_data_consistency(self): + """Business rule: Alerts generated from Events should maintain data consistency.""" + # Arrange: Create event + event_time = datetime.now(timezone.utc) + event = Event( + ts=event_time, + device_id="consistency_test", + sensor_type="pressure", + site_id="factory_floor_2", + msg_type="reading", + value=999.9, # Out of range value + seq=15, + quality="ok" + ) + + # Act: Create alert based on event (simulating engine behavior) + alert = Alert( + device_id=event.device_id, # Must match + issue_type="out_of_range", + start_ts=event.ts, # Must use event timestamp + end_ts=None, + severity="error", + sensor_type=event.sensor_type, # Must match + site_id=event.site_id, # Must match + details={ + "trigger_value": event.value, # Include event data + "trigger_seq": event.seq, + "trigger_quality": event.quality + } + ) + + # Assert: Data consistency between event and alert + assert alert.device_id == event.device_id + assert alert.start_ts == event.ts + assert alert.sensor_type == event.sensor_type + assert alert.site_id == event.site_id + assert alert.details["trigger_value"] == event.value + assert alert.details["trigger_seq"] == event.seq + assert alert.details["trigger_quality"] == event.quality + + def test_timestamp_ordering_consistency(self): + """Business rule: Timestamps should maintain logical ordering.""" + # Arrange: Create time sequence + base_time = datetime.now(timezone.utc) + event_time = base_time + alert_start = base_time + timedelta(seconds=1) + alert_end = base_time + timedelta(minutes=5) + + # Act: Create objects with time sequence + event = Event( + ts=event_time, + device_id="timing_test", + sensor_type="temperature", + site_id="test_site", + msg_type="reading", + value=25.0, + seq=1, + quality="ok" + ) + + alert = Alert( + device_id="timing_test", + issue_type="test_issue", + start_ts=alert_start, + end_ts=alert_end, + severity="warning" + ) + + device_state = DeviceState( + device_id="timing_test", + last_seen_ts=event_time + ) + + # Assert: Timestamp relationships should be logical + assert event.ts <= alert.start_ts # Event should trigger alert + assert alert.start_ts < alert.end_ts # Alert start before end + assert device_state.last_seen_ts == event.ts # State reflects event time + + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) \ No newline at end of file diff --git a/services/sound_metrics/Dockerfile b/services/sound_metrics/Dockerfile index fa1af4ac7..50c86e7ae 100644 --- a/services/sound_metrics/Dockerfile +++ b/services/sound_metrics/Dockerfile @@ -7,20 +7,40 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ WORKDIR /app +<<<<<<< HEAD + # COPY certs/ /app/certs/ -RUN if [ -d /app/certs ] && ls /app/certs/*.crt >/dev/null 2>&1; then \ - cp /app/certs/*.crt /usr/local/share/ca-certificates/ && update-ca-certificates; \ +# RUN if [ -d /app/certs ] && ls /app/certs/*.crt >/dev/null 2>&1; then \ +# cp /app/certs/*.crt /usr/local/share/ca-certificates/ && update-ca-certificates; \ +======= +>>>>>>> 4bb2e60fc0fd9a846955fa89533d661a56b1645a +# Bring in app files (including optional ./certs) +COPY . . + +# Install any *.crt in ./certs (if present), regardless of file names +RUN if [ -d /app/certs ] && [ -n "$(find /app/certs -type f -name '*.crt' -print -quit)" ]; then \ + find /app/certs -type f -name '*.crt' -exec cp {} /usr/local/share/ca-certificates/ \; && \ + update-ca-certificates; \ else \ echo "No extra CA certs found. Skipping CA update."; \ fi -# Python deps + COPY requirements.txt . -RUN pip install --no-cache-dir -r requirements.txt +# Ensure pip/requests use the system CA bundle (includes optional NetFree certs) +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + # CURL_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PIP_CERT=/etc/ssl/certs/ca-certificates.crt \ + PIP_DISABLE_PIP_VERSION_CHECK=1 -# App code -COPY src/ ./src/ +# Persist pip setting as fallback +RUN printf "[global]\ncert = /etc/ssl/certs/ca-certificates.crt\n" > /etc/pip.conf + +# Python deps (now benefit from the updated CA store if certs exist) +RUN pip install --no-cache-dir -r requirements.txt +# App code already copied above ENV PYTHONUNBUFFERED=1 \ ADDR=0.0.0.0 \ PORT=8005 \ @@ -34,9 +54,9 @@ ENV PYTHONUNBUFFERED=1 \ MINIO_BUCKET=sound \ MINIO_PREFIX=sounds/ -EXPOSE 8001 +EXPOSE 8005 HEALTHCHECK --interval=30s --timeout=5s --retries=5 \ - CMD curl -fsS http://localhost:8001/metrics >/dev/null || exit 1 + CMD curl -fsS http://localhost:8005/metrics >/dev/null || exit 1 CMD ["python", "-u", "src/metrics.py"] diff --git a/services/sound_metrics/src/metrics.py b/services/sound_metrics/src/metrics.py index 0f5e7d7d3..126ef5fe9 100644 --- a/services/sound_metrics/src/metrics.py +++ b/services/sound_metrics/src/metrics.py @@ -1,9 +1,9 @@ -# local_metrics_minio.py +# services/sound_metrics/src/metrics.py import os, re, time, math from pathlib import Path from datetime import datetime, timedelta import numpy as np, soundfile as sf -from prometheus_client import Gauge, start_http_server +from prometheus_client import Gauge, Counter, start_http_server from minio import Minio from io import BytesIO @@ -25,6 +25,9 @@ MINIO_SECRET = os.getenv("MINIO_SECRET_KEY", "minioadmin123") MINIO_BUCKET = os.getenv("MINIO_BUCKET", "sound") MINIO_PREFIX = os.getenv("MINIO_PREFIX", "sounds/") +MINIO_PREFIXES = [p.strip() for p in os.getenv("MINIO_PREFIXES", "").split(",") if p.strip()] +if not MINIO_PREFIXES: + MINIO_PREFIXES = [MINIO_PREFIX] ALLOWED_EXTS = {".wav", ".flac", ".ogg", ".aiff", ".aif", ".au", ".mp3", ".m4a", ".aac", ".opus"} FFMPEG_EXTS = {".mp3", ".m4a", ".aac"} @@ -32,31 +35,48 @@ def now_time(): return datetime.utcnow() if USE_UTC else datetime.now() -# === Prometheus metrics === +# === Prometheus metrics (REAL metrics only) === g_avg_rms = Gauge("sound_avg_volume", "5m avg RMS", ["mic_id"]) g_std_rms = Gauge("sound_std_volume", "5m std of RMS", ["mic_id"]) g_uptime = Gauge("sound_mic_uptime_ratio", "5m uptime ratio", ["mic_id"]) - -# === Filename pattern: _YYYY-MM-DD_HH-MM.ext === -FNAME_RE = re.compile( - r"^(?P[^_]+)_(?P\d{4}-\d{2}-\d{2})_(?P\d{2})-(?P\d{2})$", - re.IGNORECASE -) +g_volume_db = Gauge("sound_volume_db", "5m average volume (as dB from RMS)", ["mic_id"]) +g_mic_uptime_seconds = Gauge("mic_uptime_seconds", "Uptime seconds (in current window)", ["mic_id"]) + +# Debug / visibility counters +files_scanned_total = Counter("agcloud_files_scanned_total", "Total objects seen in MinIO", ["prefix"]) +files_parsed_total = Counter("agcloud_files_parsed_total", "Total audio files parsed", ["prefix", "mic_id"]) +files_skipped_total = Counter("agcloud_files_skipped_total", "Skipped objects", ["prefix", "reason"]) + +# Filename pattern: _.ext e.g., MIC-01_20251109T232907Z.wav +# FNAME_RE = re.compile(r"^(?P[^_]+)_(?P\d{8}T\d{6}Z)$", re.IGNORECASE) + +# Filename patterns (flexible): +# 1) _ +# 2) - +# 3) _ (no Z) +PATTERNS = [ + re.compile(r"^(?P[^_]+)_(?P\d{8}T\d{6}Z)$", re.IGNORECASE), + re.compile(r"^(?P[^-]+)-(?P\d{8}T\d{6}Z)$", re.IGNORECASE), + re.compile(r"^(?P[^_]+)_(?P\d{8}T\d{6})$", re.IGNORECASE), +] def parse_name(fname: str): - p = Path(fname) - m = FNAME_RE.match(p.stem) - if not m: - return None, None - mic = m.group("mic") - ts = datetime.strptime(f"{m.group('date')}_{m.group('h')}-{m.group('m')}", "%Y-%m-%d_%H-%M") - return mic, ts + p = Path(fname).stem + for rx in PATTERNS: + m = rx.match(p) + if m: + mic = m.group("mic") + ts_str = m.group("ts") + # allow both with/without 'Z' + fmt = "%Y%m%dT%H%M%SZ" if ts_str.endswith("Z") else "%Y%m%dT%H%M%S" + ts = datetime.strptime(ts_str, fmt) + return mic, ts + return None, None def window_start_for(ts: datetime) -> datetime: bucket_min = (ts.minute // WINDOW_MIN) * WINDOW_MIN return ts.replace(minute=bucket_min, second=0, microsecond=0) -# === Audio processing === def load_audio_bytes(data: bytes, ext: str): if ext in FFMPEG_EXTS: if not HAVE_PYDUB: @@ -94,6 +114,13 @@ def process_audio_bytes(data: bytes, ext: str): total += 1 return rms_all, std_all, active, total +def apply_delta(slot, delta, sign): + slot["sum"] += sign * delta["sum"] + slot["sum_sq"] += sign * delta["sum_sq"] + slot["n"] += sign * delta["n"] + slot["active_frames"] += sign * delta["active_frames"] + slot["total_frames"] += sign * delta["total_frames"] + def flush_finished_windows(now: datetime, agg): finished = [] for (mic, wstart), s in list(agg.items()): @@ -101,123 +128,125 @@ def flush_finished_windows(now: datetime, agg): n = s["n"] if n: mean = s["sum"] / n - var = (s["sum_sq"] / n) - mean**2 - std = math.sqrt(max(var, 0)) - uptime = s["active_frames"] / s["total_frames"] if s["total_frames"] else 0.0 + var = (s["sum_sq"] / n) - mean**2 + std = math.sqrt(max(var, 0.0)) + uptime_ratio = s["active_frames"] / s["total_frames"] if s["total_frames"] else 0.0 + + # Set REAL metrics g_avg_rms.labels(mic).set(mean) g_std_rms.labels(mic).set(std) - g_uptime.labels(mic).set(uptime) - print(f"[FLUSH] mic={mic} window={wstart:%Y-%m-%d %H:%M} RMS={mean:.5f} STD={std:.5f} uptime={uptime:.3f}") + g_uptime.labels(mic).set(uptime_ratio) + + # Derived REAL metrics for dashboard + db = 20.0 * math.log10(max(mean, 1e-12)) + g_volume_db.labels(mic).set(db) + uptime_seconds = s["active_frames"] * FRAME_SEC + g_mic_uptime_seconds.labels(mic).set(uptime_seconds) + + print(f"[FLUSH] mic={mic} window={wstart:%Y-%m-%d %H:%M} " + f"RMS={mean:.5f} STD={std:.5f} uptime_ratio={uptime_ratio:.3f} " + f"db={db:.2f} uptime_sec={uptime_seconds:.2f}") + finished.append((mic, wstart)) for key in finished: del agg[key] -def apply_delta(slot, delta, sign): - """Apply (sign=+1 add, sign=-1 subtract) a contribution delta to an agg slot.""" - slot["sum"] += sign * delta["sum"] - slot["sum_sq"] += sign * delta["sum_sq"] - slot["n"] += sign * delta["n"] - slot["active_frames"] += sign * delta["active_frames"] - slot["total_frames"] += sign * delta["total_frames"] - def main(): start_http_server(PORT, addr=ADDR) - print(f"✅ MinIO Metrics available at: http://{ADDR}:{PORT}/metrics") - - # MinIO client + print(f"✔ MinIO sound metrics at: http://{ADDR}:{PORT}/metrics") client = Minio(MINIO_ENDPOINT, MINIO_ACCESS, MINIO_SECRET, secure=False) - # seen: fname -> etag (to detect updates/overwrites) - seen = {} - # agg: (mic, wstart) -> accumulators - agg = {} - # contrib: fname -> {"wstart": datetime, "delta": {...}} - # keeps last contribution of each file, so we can subtract it before re-adding - contrib = {} + seen = {} # fname -> etag + agg = {} # (mic, wstart) -> accumulators + contrib = {} # fname -> {"wstart": dt, "delta": {...}} while True: now = now_time() - try: - objects = client.list_objects(MINIO_BUCKET, prefix=MINIO_PREFIX, recursive=True) - except Exception as e: - print(f"[WARN] Failed to list objects from MinIO: {e}") - time.sleep(10) - continue - - for obj in objects: - fname_full = obj.object_name # includes prefix/path - fname = Path(fname_full).name - ext = Path(fname).suffix.lower() - if ext not in ALLOWED_EXTS: - continue - - etag = getattr(obj, "etag", None) - - # If we already processed this exact version (same etag), skip - if fname in seen and seen[fname] == etag: - continue - - mic, ts = parse_name(fname) - if not mic: - # skip files that don't match naming scheme - continue - + # try: + # objects = client.list_objects(MINIO_BUCKET, prefix=MINIO_PREFIX, recursive=True) + # except Exception as e: + # print(f"[WARN] list_objects failed: {e}") + # time.sleep(10) + # continue + + # Iterate all configured prefixes + for prefix in MINIO_PREFIXES: try: - resp = client.get_object(MINIO_BUCKET, fname_full) - data = resp.read() + objects = client.list_objects(MINIO_BUCKET, prefix=prefix, recursive=True) except Exception as e: - print(f"[ERROR] get_object {fname}: {e}") - # ensure the connection is closed even on error - try: - resp.close(); resp.release_conn() - except Exception: - pass + print(f"[WARN] list_objects failed for prefix={prefix}: {e}") + time.sleep(5) continue - finally: - try: - resp.close(); resp.release_conn() - except Exception: - pass - try: - rms, _std, active, total = process_audio_bytes(data, ext) - except Exception as e: - print(f"[ERROR] process_audio {fname}: {e}") - continue + for obj in objects: + fname_full = obj.object_name + fname = Path(fname_full).name + ext = Path(fname).suffix.lower() + files_scanned_total.labels(prefix=prefix).inc() + if ext not in ALLOWED_EXTS: + files_skipped_total.labels(prefix=prefix, reason="ext").inc() + continue + + etag = getattr(obj, "etag", None) + if fname in seen and seen[fname] == etag: + continue + + mic, ts = parse_name(fname) + if not mic: + files_skipped_total.labels(prefix=prefix, reason="name").inc() + # Helpful log once in a while + print(f"[SKIP:name] {fname_full} (pattern mismatch)") + continue + + resp = None + try: + resp = client.get_object(MINIO_BUCKET, fname_full) + data = resp.read() + except Exception as e: + print(f"[ERROR] get_object {fname}: {e}") + if resp: + try: resp.close(); resp.release_conn() + except Exception: pass + continue + finally: + if resp: + try: resp.close(); resp.release_conn() + except Exception: pass - # Prepare new contribution for this file - new_wstart = window_start_for(ts) - new_delta = { - "sum": float(rms), - "sum_sq": float(rms * rms), - "n": 1, - "active_frames": int(active), - "total_frames": int(total), - } - - # If this file contributed before, remove its previous contribution first - if fname in contrib: - prev = contrib[fname] - prev_wstart = prev["wstart"] - prev_delta = prev["delta"] - prev_key = (mic, prev_wstart) - # Only subtract if the previous window slot still exists - if prev_key in agg: - apply_delta(agg[prev_key], prev_delta, sign=-1) - - # Now add the new contribution to the appropriate window slot - key = (mic, new_wstart) - slot = agg.setdefault(key, {"sum": 0.0, "sum_sq": 0.0, "n": 0, "active_frames": 0, "total_frames": 0}) - apply_delta(slot, new_delta, sign=+1) - - # Remember the last seen etag and contribution - seen[fname] = etag - contrib[fname] = {"wstart": new_wstart, "delta": new_delta} - - print(f"[OK] {fname} → mic={mic} RMS={rms:.4f} active={active}/{total} window={new_wstart:%Y-%m-%d %H:%M}") + try: + rms, _std, active, total = process_audio_bytes(data, ext) + except Exception as e: + print(f"[ERROR] process_audio {fname}: {e}") + continue + + new_wstart = window_start_for(ts) + new_delta = { + "sum": float(rms), + "sum_sq": float(rms * rms), + "n": 1, + "active_frames": int(active), + "total_frames": int(total), + } + files_parsed_total.labels(prefix=prefix, mic_id=mic).inc() + + if fname in contrib: + prev = contrib[fname] + prev_key = (mic, prev["wstart"]) + if prev_key in agg: + apply_delta(agg[prev_key], prev["delta"], sign=-1) + + key = (mic, new_wstart) + slot = agg.setdefault(key, {"sum": 0.0, "sum_sq": 0.0, "n": 0, + "active_frames": 0, "total_frames": 0}) + apply_delta(slot, new_delta, sign=+1) + + seen[fname] = etag + contrib[fname] = {"wstart": new_wstart, "delta": new_delta} + print(f"[OK] {fname} → mic={mic} RMS={rms:.4f} active={active}/{total} " + f"window={new_wstart:%Y-%m-%d %H:%M}") flush_finished_windows(now, agg) - time.sleep(15) # reduce load on MinIO + time.sleep(15) if __name__ == "__main__": main() diff --git a/services/sounds_classifier/Dockerfile.classifier-svc b/services/sounds_classifier/Dockerfile.classifier-svc index 54efca366..14fc3ff43 100644 --- a/services/sounds_classifier/Dockerfile.classifier-svc +++ b/services/sounds_classifier/Dockerfile.classifier-svc @@ -1,58 +1,58 @@ -FROM python:3.12-slim - -# System deps + codecs + CA + Kafka/DB native libs (librdkafka, libpq) -RUN apt-get update && apt-get install -y --no-install-recommends \ - build-essential \ - libsndfile1 \ - ffmpeg \ - ca-certificates \ - wget curl \ - librdkafka1 \ - libpq5 \ - && rm -rf /var/lib/apt/lists/* - -WORKDIR /app - -# ---- Corporate CAs ---- -# Place your CA files under classify/certs/*.crt before build -COPY certs/*.crt /usr/local/share/ca-certificates/ -RUN update-ca-certificates - -ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ - REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ - PYTHONUNBUFFERED=1 - - -COPY requirements.txt /app/requirements.txt -RUN python -m pip install --upgrade pip \ - && pip install --no-cache-dir -r /app/requirements.txt - -# Install PyTorch CPU wheels from official index (kept separate for clearer errors/caching) -RUN pip install --no-cache-dir --index-url https://download.pytorch.org/whl/cpu torch==2.5.1+cpu - -# ---- Checkpoint bootstrap (download once at build if missing) ---- -# Configure via build-args or ENV: -ARG CHECKPOINT_URL="https://example.com/path/to/Cnn14_mAP=0.431.pth" -ARG CHECKPOINT_PATH="/app/classification/models/panns_data/Cnn14_mAP=0.431.pth" -ENV CHECKPOINT_URL=${CHECKPOINT_URL} \ - CHECKPOINT=${CHECKPOINT_PATH} - -# Create target folder and download checkpoint WITHOUT importing project code -RUN set -eux; \ - p="${CHECKPOINT}"; \ - url="${CHECKPOINT_URL}"; \ - mkdir -p "$(dirname "$p")"; \ - if [ ! -f "$p" ]; then \ - [ -n "$url" ]; curl -L -o "$p" "$url"; \ - fi; \ - echo "Checkpoint ready at: $p" - -RUN mkdir -p /root/panns_data && \ - curl -L -o /root/panns_data/class_labels_indices.csv \ - https://storage.googleapis.com/us_audioset/youtube_corpus/v1/csv/class_labels_indices.csv - -COPY src/classification /app/classification -RUN touch /app/classification/__init__.py - -EXPOSE 8088 +FROM python:3.12-slim + +# System deps + codecs + CA + Kafka/DB native libs (librdkafka, libpq) +RUN apt-get update && apt-get install -y --no-install-recommends \ + build-essential \ + libsndfile1 \ + ffmpeg \ + ca-certificates \ + wget curl \ + librdkafka1 \ + libpq5 \ + && rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +# ---- Corporate CAs ---- +# Place your CA files under classify/certs/*.crt before build +COPY certs/*.crt /usr/local/share/ca-certificates/ +RUN update-ca-certificates + +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PYTHONUNBUFFERED=1 + + +COPY requirements.txt /app/requirements.txt +RUN python -m pip install --upgrade pip \ + && pip install --no-cache-dir -r /app/requirements.txt + +# Install PyTorch CPU wheels from official index (kept separate for clearer errors/caching) +RUN pip install --no-cache-dir --index-url https://download.pytorch.org/whl/cpu torch==2.5.1+cpu + +# ---- Checkpoint bootstrap (download once at build if missing) ---- +# Configure via build-args or ENV: +ARG CHECKPOINT_URL="https://example.com/path/to/Cnn14_mAP=0.431.pth" +ARG CHECKPOINT_PATH="/app/classification/models/panns_data/Cnn14_mAP=0.431.pth" +ENV CHECKPOINT_URL=${CHECKPOINT_URL} \ + CHECKPOINT=${CHECKPOINT_PATH} + +# Create target folder and download checkpoint WITHOUT importing project code +RUN set -eux; \ + p="${CHECKPOINT}"; \ + url="${CHECKPOINT_URL}"; \ + mkdir -p "$(dirname "$p")"; \ + if [ ! -f "$p" ]; then \ + [ -n "$url" ]; curl -L -o "$p" "$url"; \ + fi; \ + echo "Checkpoint ready at: $p" + +RUN mkdir -p /root/panns_data && \ + curl -L -o /root/panns_data/class_labels_indices.csv \ + https://storage.googleapis.com/us_audioset/youtube_corpus/v1/csv/class_labels_indices.csv + +COPY src/classification /app/classification +RUN touch /app/classification/__init__.py + +EXPOSE 8088 CMD ["uvicorn", "classification.app:app", "--host", "0.0.0.0", "--port", "8088", "--log-level", "info"] \ No newline at end of file diff --git a/services/sounds_classifier/README.md b/services/sounds_classifier/README.md index d95b238dd..aa7dda159 100644 --- a/services/sounds_classifier/README.md +++ b/services/sounds_classifier/README.md @@ -1,59 +1,59 @@ -# 🎧 Sound Classifier Service (CNN14-based) - -Service that classifies audio files using CNN14 model. It: -1. Receives S3 object location (bucket+key) -2. Classifies the sound -3. Stores result in PostgreSQL (optional) -4. Sends alert to Kafka topic if specific sounds detected (optional) -Built with **FastAPI**, **PANNs (CNN14)**, **PostgreSQL**, and optional **Kafka alerts** for real-time monitoring. - -## Quick Start -```bash -docker compose up -d sounds_classifier -``` -Service runs on **http://localhost:8088** (see `docker-compose.yml`, port 8088). - -## API Usage -```json -POST /classify -{ - "s3_bucket": "your-bucket", - "s3_key": "path/to/audio.wav" -} -``` - -### Example Response -```json -{ - "label": "vehicle", - "probs": { - "vehicle": 0.93, - "animal": 0.05, - "shotgun": 0.02 - } -} -``` - -## Supported Audio Formats -- WAV, MP3, FLAC, OGG -- M4A, AAC, WMA, OPUS - - -## Health & Docs -- `GET /health` → basic readiness and model load status -- Swagger UI: [http://localhost:8088/docs](http://localhost:8088/docs) - -## 🧪 Testing -Run all tests (unit + integration): -```bash -pytest -v --cov=src --cov-report=term-missing -``` - -## System Requirements -- Docker and Docker Compose -- MinIO instance with access credentials - -## Notes - • First startup may take ~30s to load the CNN14 model into memory. - • Kafka alerts are optional; see `KAFKA_BROKERS` and `ALERTS_TOPIC`. +# 🎧 Sound Classifier Service (CNN14-based) + +Service that classifies audio files using CNN14 model. It: +1. Receives S3 object location (bucket+key) +2. Classifies the sound +3. Stores result in PostgreSQL (optional) +4. Sends alert to Kafka topic if specific sounds detected (optional) +Built with **FastAPI**, **PANNs (CNN14)**, **PostgreSQL**, and optional **Kafka alerts** for real-time monitoring. + +## Quick Start +```bash +docker compose up -d sounds_classifier +``` +Service runs on **http://localhost:8088** (see `docker-compose.yml`, port 8088). + +## API Usage +```json +POST /classify +{ + "s3_bucket": "your-bucket", + "s3_key": "path/to/audio.wav" +} +``` + +### Example Response +```json +{ + "label": "vehicle", + "probs": { + "vehicle": 0.93, + "animal": 0.05, + "shotgun": 0.02 + } +} +``` + +## Supported Audio Formats +- WAV, MP3, FLAC, OGG +- M4A, AAC, WMA, OPUS + + +## Health & Docs +- `GET /health` → basic readiness and model load status +- Swagger UI: [http://localhost:8088/docs](http://localhost:8088/docs) + +## 🧪 Testing +Run all tests (unit + integration): +```bash +pytest -v --cov=src --cov-report=term-missing +``` + +## System Requirements +- Docker and Docker Compose +- MinIO instance with access credentials + +## Notes + • First startup may take ~30s to load the CNN14 model into memory. + • Kafka alerts are optional; see `KAFKA_BROKERS` and `ALERTS_TOPIC`. • Database writes are handled through `classification.core.db_io_pg`. \ No newline at end of file diff --git a/services/sounds_classifier/requirements.txt b/services/sounds_classifier/requirements.txt index f13de3deb..cb7054ecc 100644 --- a/services/sounds_classifier/requirements.txt +++ b/services/sounds_classifier/requirements.txt @@ -1,20 +1,20 @@ -# Web API -fastapi==0.115.5 -uvicorn[standard]==0.30.6 -pydantic==2.9.2 - -# Core scientific / audio -numpy==1.26.4 -scipy==1.11.4 -librosa==0.10.2.post1 -soundfile==0.12.1 -joblib==1.4.2 -scikit-learn==1.5.2 - -# Storage / messaging / DB -minio==7.2.7 -confluent-kafka==2.6.0 -psycopg2-binary==2.9.9 - -# PANNs helper (optional but referenced by imports) -panns-inference==0.1.1 +# Web API +fastapi==0.115.5 +uvicorn[standard]==0.30.6 +pydantic==2.9.2 + +# Core scientific / audio +numpy==1.26.4 +scipy==1.11.4 +librosa==0.10.2.post1 +soundfile==0.12.1 +joblib==1.4.2 +scikit-learn==1.5.2 + +# Storage / messaging / DB +minio==7.2.7 +confluent-kafka==2.6.0 +psycopg2-binary==2.9.9 + +# PANNs helper (optional but referenced by imports) +panns-inference==0.1.1 diff --git a/services/sounds_classifier/src/classification/__init__.py b/services/sounds_classifier/src/classification/__init__.py index 5ac24be70..d163ffe0c 100644 --- a/services/sounds_classifier/src/classification/__init__.py +++ b/services/sounds_classifier/src/classification/__init__.py @@ -1,7 +1,7 @@ -""" -Top-level package for the project. -Avoid importing heavy submodules at package import time to keep imports safe for tests. -""" - -__all__ = ["__version__"] +""" +Top-level package for the project. +Avoid importing heavy submodules at package import time to keep imports safe for tests. +""" + +__all__ = ["__version__"] __version__ = "0.0.0" \ No newline at end of file diff --git a/services/sounds_classifier/src/classification/app.py b/services/sounds_classifier/src/classification/app.py index 1fc5e252c..a2b526747 100644 --- a/services/sounds_classifier/src/classification/app.py +++ b/services/sounds_classifier/src/classification/app.py @@ -1,209 +1,209 @@ -import logging -import time -from fastapi import FastAPI, HTTPException -from pydantic import BaseModel -from typing import Dict, Optional -import os -import numpy as np -import joblib -from psycopg2 import extensions - -from panns_inference import AudioTagging -from classification.core.model_io import SAMPLE_RATE -from classification.scripts import classify as cls_script -from classification.core.db_utils import ensure_run, open_db, resolve_file_id -from classification.core.db_io_pg import finish_run, upsert_file_aggregate - -app = FastAPI(title="Audio Classifier API", version="2.0.0") - -# --- Globals (singletons) --- -PANN_MODEL: Optional[AudioTagging] = None -SK_PIPELINE = None -DB_CONN = None -DB_RUN_ID = os.getenv("DB_RUN_ID", "api-default") -DB_SCHEMA = os.getenv("DB_SCHEMA", "agcloud_audio") - -CHECKPOINT_PATH = os.getenv( - "CHECKPOINT", - "/app/classification/models/panns_data/Cnn14_mAP=0.431.pth" -) -HEAD_PATH = os.getenv( - "HEAD", - "/app/classification/models/head/head_cnn14_rf.joblib" # adapt if different -) - -class ClassifyIn(BaseModel): - s3_bucket: str - s3_key: str - return_probs: bool = True - -class ClassifyOut(BaseModel): - label: str - probs: Dict[str, float] - sent_alert: bool = True - alert_topic: Optional[str] = None - alert_skip_reason: Optional[str] = None - -def _ensure_conn_clean(conn): - """Rollback any non-idle transaction so the connection is usable.""" - try: - if conn is not None and conn.get_transaction_status() != extensions.TRANSACTION_STATUS_IDLE: - conn.rollback() - except Exception: - # swallow – if rollback itself fails, next ops will raise and be handled - pass - -@app.on_event("startup") -def load_models_on_startup() -> None: - """ - Load heavy models once and perform a short warm-up to avoid cold-start. - Also open DB connection and ensure run row exists. """ - global PANN_MODEL, SK_PIPELINE, DB_CONN - logger = logging.getLogger("uvicorn.error") - - logger.info("Loading models into memory...") - PANN_MODEL = AudioTagging(checkpoint_path=CHECKPOINT_PATH) - SK_PIPELINE = None - try: - if os.path.exists(HEAD_PATH): - SK_PIPELINE = joblib.load(HEAD_PATH) - logger.info("✅ SK pipeline loaded from HEAD.") - else: - logger.warning(f"HEAD pipeline not found at {HEAD_PATH}; using built-in head.") - except Exception as e: - logger.warning(f"HEAD pipeline load failed ({e}); using built-in head.") - - # 3) Warm-up forward pass with 1 second of silence - dummy = np.zeros((1, SAMPLE_RATE * 10), dtype=np.float32) # add batch dim - try: - _ = PANN_MODEL.inference(dummy) - logger.info("✅ PANN model warm-up complete.") - except Exception as e: - logger.warning(f"PANN warm-up skipped ({e})") - - # DB connect + ensure run - try: - DB_CONN = open_db() - ensure_run(DB_CONN, DB_RUN_ID) - logger.info(f"✅ DB connected; run '{DB_RUN_ID}' ensured in schema '{DB_SCHEMA}'.") - except Exception as e: - logger.error(f"DB init failed: {e}") - raise - - logger.info("✅ All models loaded and ready.") - -@app.on_event("shutdown") -def close_db_on_shutdown() -> None: - """ - Cleanly close the global DB connection on shutdown. - """ - global DB_CONN - try: - if DB_CONN is not None: - try: - finish_run(DB_CONN, DB_RUN_ID) - except Exception: - pass - DB_CONN.close() - except Exception: - pass - finally: - DB_CONN = None - -# dedicated API perf logger -api_logger = logging.getLogger("audio_cls.api") -api_logger.setLevel(logging.INFO) -if not api_logger.handlers: - h = logging.StreamHandler() - h.setFormatter(logging.Formatter("[%(asctime)s] [API] %(message)s", "%Y-%m-%d %H:%M:%S")) - api_logger.addHandler(h) - -@app.post("/classify", response_model=ClassifyOut) -def classify(body: ClassifyIn): - """ - Run the full classification pipeline: - - Download from MinIO (s3_bucket + s3_key) - - Model inference with open-set threshold - - DB upsert into agcloud_audio.file_aggregates - """ - start = time.perf_counter() - status_code = 200 - _ensure_conn_clean(DB_CONN) - try: - # 1) Require the file to already exist in public.sound_new_sounds_connections → else 404 - try: - file_id = resolve_file_id(DB_CONN, bucket=body.s3_bucket, object_key=body.s3_key) - except ValueError as e: - DB_CONN.rollback() - # file not found in public.sound_new_sounds_connections → return 404 (do NOT create) - raise HTTPException(status_code=404, detail=str(e)) - - # 2) Run classification - result = cls_script.run_classification_job( - s3_bucket=body.s3_bucket, - s3_key=body.s3_key, - pann_model=PANN_MODEL, - sk_pipeline=SK_PIPELINE - ) - - # 3) Upsert aggregate to DB (JSONB) - upsert_file_aggregate(DB_CONN, { - "run_id": DB_RUN_ID, - "file_id": file_id, - "head_probs_json": result.get("probs", {}), - "head_pred_label": result.get("label"), - "head_pred_prob": result.get("pred_prob"), - "head_unknown_threshold": result.get("unknown_threshold"), - "head_is_another": result.get("is_another"), - "num_windows": result.get("num_windows"), - "agg_mode": result.get("agg_mode"), - "processing_ms": result.get("processing_ms"), - }) - - # 4) Build API response (include alert status if exists) - out = {"label": result.get("label", ""), - "probs": result.get("probs", {}), - "sent_alert": bool(result.get("sent_alert", False)), - "alert_topic": result.get("alert_topic"), - "alert_skip_reason": result.get("alert_skip_reason"), - } - if not body.return_probs: - out["probs"] = {} - return ClassifyOut(**out) - - except HTTPException as e: - status_code = e.status_code - raise - except Exception as e: - try: - DB_CONN.rollback() - except Exception: - pass - status_code = 500 - raise HTTPException(status_code=500, detail=str(e)) - finally: - elapsed_ms = (time.perf_counter() - start) * 1000.0 - api_logger.info( - f"path=/classify bucket={body.s3_bucket} key={body.s3_key} " - f"latency_ms={elapsed_ms:.2f} status={status_code}" - ) - -@app.get("/health") -def health(): - return { - "ok": True, - "pann_loaded": PANN_MODEL is not None, - "sk_pipeline_loaded": SK_PIPELINE is not None - } - -@app.middleware("http") -async def timing_middleware(request, call_next): - t0 = time.perf_counter() - response = await call_next(request) - elapsed_ms = (time.perf_counter() - t0) * 1000.0 - - # log only interesting routes (keep or adjust as you like) - if request.url.path in ("/classify", "/health"): - api_logger.info(f"path={request.url.path} status={response.status_code} latency_ms={elapsed_ms:.2f}") - - return response +import logging +import time +from fastapi import FastAPI, HTTPException +from pydantic import BaseModel +from typing import Dict, Optional +import os +import numpy as np +import joblib +from psycopg2 import extensions + +from panns_inference import AudioTagging +from classification.core.model_io import SAMPLE_RATE +from classification.scripts import classify as cls_script +from classification.core.db_utils import ensure_run, open_db, resolve_file_id +from classification.core.db_io_pg import finish_run, upsert_file_aggregate + +app = FastAPI(title="Audio Classifier API", version="2.0.0") + +# --- Globals (singletons) --- +PANN_MODEL: Optional[AudioTagging] = None +SK_PIPELINE = None +DB_CONN = None +DB_RUN_ID = os.getenv("DB_RUN_ID", "api-default") +DB_SCHEMA = os.getenv("DB_SCHEMA", "agcloud_audio") + +CHECKPOINT_PATH = os.getenv( + "CHECKPOINT", + "/app/classification/models/panns_data/Cnn14_mAP=0.431.pth" +) +HEAD_PATH = os.getenv( + "HEAD", + "/app/classification/models/head/head_cnn14_rf.joblib" # adapt if different +) + +class ClassifyIn(BaseModel): + s3_bucket: str + s3_key: str + return_probs: bool = True + +class ClassifyOut(BaseModel): + label: str + probs: Dict[str, float] + sent_alert: bool = True + alert_topic: Optional[str] = None + alert_skip_reason: Optional[str] = None + +def _ensure_conn_clean(conn): + """Rollback any non-idle transaction so the connection is usable.""" + try: + if conn is not None and conn.get_transaction_status() != extensions.TRANSACTION_STATUS_IDLE: + conn.rollback() + except Exception: + # swallow – if rollback itself fails, next ops will raise and be handled + pass + +@app.on_event("startup") +def load_models_on_startup() -> None: + """ + Load heavy models once and perform a short warm-up to avoid cold-start. + Also open DB connection and ensure run row exists. """ + global PANN_MODEL, SK_PIPELINE, DB_CONN + logger = logging.getLogger("uvicorn.error") + + logger.info("Loading models into memory...") + PANN_MODEL = AudioTagging(checkpoint_path=CHECKPOINT_PATH) + SK_PIPELINE = None + try: + if os.path.exists(HEAD_PATH): + SK_PIPELINE = joblib.load(HEAD_PATH) + logger.info("✅ SK pipeline loaded from HEAD.") + else: + logger.warning(f"HEAD pipeline not found at {HEAD_PATH}; using built-in head.") + except Exception as e: + logger.warning(f"HEAD pipeline load failed ({e}); using built-in head.") + + # 3) Warm-up forward pass with 1 second of silence + dummy = np.zeros((1, SAMPLE_RATE * 10), dtype=np.float32) # add batch dim + try: + _ = PANN_MODEL.inference(dummy) + logger.info("✅ PANN model warm-up complete.") + except Exception as e: + logger.warning(f"PANN warm-up skipped ({e})") + + # DB connect + ensure run + try: + DB_CONN = open_db() + ensure_run(DB_CONN, DB_RUN_ID) + logger.info(f"✅ DB connected; run '{DB_RUN_ID}' ensured in schema '{DB_SCHEMA}'.") + except Exception as e: + logger.error(f"DB init failed: {e}") + raise + + logger.info("✅ All models loaded and ready.") + +@app.on_event("shutdown") +def close_db_on_shutdown() -> None: + """ + Cleanly close the global DB connection on shutdown. + """ + global DB_CONN + try: + if DB_CONN is not None: + try: + finish_run(DB_CONN, DB_RUN_ID) + except Exception: + pass + DB_CONN.close() + except Exception: + pass + finally: + DB_CONN = None + +# dedicated API perf logger +api_logger = logging.getLogger("audio_cls.api") +api_logger.setLevel(logging.INFO) +if not api_logger.handlers: + h = logging.StreamHandler() + h.setFormatter(logging.Formatter("[%(asctime)s] [API] %(message)s", "%Y-%m-%d %H:%M:%S")) + api_logger.addHandler(h) + +@app.post("/classify", response_model=ClassifyOut) +def classify(body: ClassifyIn): + """ + Run the full classification pipeline: + - Download from MinIO (s3_bucket + s3_key) + - Model inference with open-set threshold + - DB upsert into agcloud_audio.file_aggregates + """ + start = time.perf_counter() + status_code = 200 + _ensure_conn_clean(DB_CONN) + try: + # 1) Require the file to already exist in public.sound_new_sounds_connections → else 404 + try: + file_id = resolve_file_id(DB_CONN, bucket=body.s3_bucket, object_key=body.s3_key) + except ValueError as e: + DB_CONN.rollback() + # file not found in public.sound_new_sounds_connections → return 404 (do NOT create) + raise HTTPException(status_code=404, detail=str(e)) + + # 2) Run classification + result = cls_script.run_classification_job( + s3_bucket=body.s3_bucket, + s3_key=body.s3_key, + pann_model=PANN_MODEL, + sk_pipeline=SK_PIPELINE + ) + + # 3) Upsert aggregate to DB (JSONB) + upsert_file_aggregate(DB_CONN, { + "run_id": DB_RUN_ID, + "file_id": file_id, + "head_probs_json": result.get("probs", {}), + "head_pred_label": result.get("label"), + "head_pred_prob": result.get("pred_prob"), + "head_unknown_threshold": result.get("unknown_threshold"), + "head_is_another": result.get("is_another"), + "num_windows": result.get("num_windows"), + "agg_mode": result.get("agg_mode"), + "processing_ms": result.get("processing_ms"), + }) + + # 4) Build API response (include alert status if exists) + out = {"label": result.get("label", ""), + "probs": result.get("probs", {}), + "sent_alert": bool(result.get("sent_alert", False)), + "alert_topic": result.get("alert_topic"), + "alert_skip_reason": result.get("alert_skip_reason"), + } + if not body.return_probs: + out["probs"] = {} + return ClassifyOut(**out) + + except HTTPException as e: + status_code = e.status_code + raise + except Exception as e: + try: + DB_CONN.rollback() + except Exception: + pass + status_code = 500 + raise HTTPException(status_code=500, detail=str(e)) + finally: + elapsed_ms = (time.perf_counter() - start) * 1000.0 + api_logger.info( + f"path=/classify bucket={body.s3_bucket} key={body.s3_key} " + f"latency_ms={elapsed_ms:.2f} status={status_code}" + ) + +@app.get("/health") +def health(): + return { + "ok": True, + "pann_loaded": PANN_MODEL is not None, + "sk_pipeline_loaded": SK_PIPELINE is not None + } + +@app.middleware("http") +async def timing_middleware(request, call_next): + t0 = time.perf_counter() + response = await call_next(request) + elapsed_ms = (time.perf_counter() - t0) * 1000.0 + + # log only interesting routes (keep or adjust as you like) + if request.url.path in ("/classify", "/health"): + api_logger.info(f"path={request.url.path} status={response.status_code} latency_ms={elapsed_ms:.2f}") + + return response diff --git a/services/sounds_classifier/src/classification/backbones/cnn14.py b/services/sounds_classifier/src/classification/backbones/cnn14.py index af4420017..afc7e327e 100644 --- a/services/sounds_classifier/src/classification/backbones/cnn14.py +++ b/services/sounds_classifier/src/classification/backbones/cnn14.py @@ -1,80 +1,80 @@ -from __future__ import annotations -from typing import Tuple, List, Optional -import numpy as np -from panns_inference import AudioTagging -from classification.core.model_io import _to_numpy, ensure_checkpoint - -def load_cnn14_model( - checkpoint_path: Optional[str] = None, - checkpoint_url: Optional[str] = None, - device: str = "cpu" -) -> AudioTagging: - """ - Load a CNN14 AudioTagging model. - Either checkpoint_path or checkpoint_url must be provided. - Always resolves to a local path via ensure_checkpoint. - """ - if not (checkpoint_path or checkpoint_url): - raise FileNotFoundError("Either checkpoint_path or checkpoint_url must be provided.") - - ckpt = ensure_checkpoint(checkpoint_path, checkpoint_url) # returns a local path - return AudioTagging(checkpoint_path=ckpt, device=device) - - -def run_embedding(at: AudioTagging, wav: np.ndarray) -> np.ndarray: - try: - res = at.inference(wav) - except Exception: - res = at.inference(wav[None, :]) - - emb = None - if isinstance(res, dict): - emb = res.get("embedding", None) - elif isinstance(res, tuple) and len(res) >= 2: - emb = res[1] - if emb is None: - raise RuntimeError("No embedding returned by panns_inference.") - return _to_numpy(emb).reshape(-1) - - -def run_cnn14_embedding(model: AudioTagging, wav: np.ndarray) -> np.ndarray: - """ - Run embedding extraction; validate input waveform. - Raises ValueError if wav is empty. - """ - wav = np.asarray(wav) - if wav.size == 0: - raise ValueError("waveform must not be empty") - if wav.dtype != np.float32: - wav = wav.astype(np.float32, copy=False) - return run_embedding(model, wav) - - -def run_cnn14_embeddings_batch(model: AudioTagging, windows: np.ndarray, batch_size: int = 32) -> np.ndarray: - """ - Compute embeddings for a batch of windows in shape (N, samples). - Returns array (N, emb_dim) float32. - """ - if windows.ndim != 2: - raise ValueError("windows must be 2D (N, samples)") - n = windows.shape[0] - embs = [] - i = 0 - while i < n: - j = min(i + batch_size, n) - chunk = np.array(windows[i:j], dtype=np.float32, copy=True, order="C") - # panns_inference supports batched input (N, samples) - res = model.inference(chunk) - if isinstance(res, dict): - emb = res.get("embedding") - elif isinstance(res, tuple) and len(res) >= 2: - emb = res[1] - else: - raise RuntimeError("Unexpected inference output") - e = _to_numpy(emb).astype(np.float32, copy=False) - if e.ndim == 1: - e = e[None, :] - embs.append(e) - i = j - E = np.concatenate(embs, axis=0).astype(np.float32, copy=False) - return E +from __future__ import annotations +from typing import Tuple, List, Optional +import numpy as np +from panns_inference import AudioTagging +from classification.core.model_io import _to_numpy, ensure_checkpoint + +def load_cnn14_model( + checkpoint_path: Optional[str] = None, + checkpoint_url: Optional[str] = None, + device: str = "cpu" +) -> AudioTagging: + """ + Load a CNN14 AudioTagging model. + Either checkpoint_path or checkpoint_url must be provided. + Always resolves to a local path via ensure_checkpoint. + """ + if not (checkpoint_path or checkpoint_url): + raise FileNotFoundError("Either checkpoint_path or checkpoint_url must be provided.") + + ckpt = ensure_checkpoint(checkpoint_path, checkpoint_url) # returns a local path + return AudioTagging(checkpoint_path=ckpt, device=device) + + +def run_embedding(at: AudioTagging, wav: np.ndarray) -> np.ndarray: + try: + res = at.inference(wav) + except Exception: + res = at.inference(wav[None, :]) + + emb = None + if isinstance(res, dict): + emb = res.get("embedding", None) + elif isinstance(res, tuple) and len(res) >= 2: + emb = res[1] + if emb is None: + raise RuntimeError("No embedding returned by panns_inference.") + return _to_numpy(emb).reshape(-1) + + +def run_cnn14_embedding(model: AudioTagging, wav: np.ndarray) -> np.ndarray: + """ + Run embedding extraction; validate input waveform. + Raises ValueError if wav is empty. + """ + wav = np.asarray(wav) + if wav.size == 0: + raise ValueError("waveform must not be empty") + if wav.dtype != np.float32: + wav = wav.astype(np.float32, copy=False) + return run_embedding(model, wav) + + +def run_cnn14_embeddings_batch(model: AudioTagging, windows: np.ndarray, batch_size: int = 32) -> np.ndarray: + """ + Compute embeddings for a batch of windows in shape (N, samples). + Returns array (N, emb_dim) float32. + """ + if windows.ndim != 2: + raise ValueError("windows must be 2D (N, samples)") + n = windows.shape[0] + embs = [] + i = 0 + while i < n: + j = min(i + batch_size, n) + chunk = np.array(windows[i:j], dtype=np.float32, copy=True, order="C") + # panns_inference supports batched input (N, samples) + res = model.inference(chunk) + if isinstance(res, dict): + emb = res.get("embedding") + elif isinstance(res, tuple) and len(res) >= 2: + emb = res[1] + else: + raise RuntimeError("Unexpected inference output") + e = _to_numpy(emb).astype(np.float32, copy=False) + if e.ndim == 1: + e = e[None, :] + embs.append(e) + i = j + E = np.concatenate(embs, axis=0).astype(np.float32, copy=False) + return E diff --git a/services/sounds_classifier/src/classification/core/db_gis_helpers.py b/services/sounds_classifier/src/classification/core/db_gis_helpers.py new file mode 100644 index 000000000..5788698a6 --- /dev/null +++ b/services/sounds_classifier/src/classification/core/db_gis_helpers.py @@ -0,0 +1,87 @@ +# db_gis_helpers.py +from __future__ import annotations +from typing import Optional, Tuple +from datetime import datetime, timezone + +def _to_dt_utc(value): + """Accepts datetime or ISO string (possibly ending with 'Z') and returns aware datetime in UTC.""" + if isinstance(value, datetime): + return value.astimezone(timezone.utc) if value.tzinfo else value.replace(tzinfo=timezone.utc) + s = str(value) + if s.endswith("Z"): + s = s[:-1] # drop Z for strptime + dt = datetime.fromisoformat(s) if "T" in s else datetime.strptime(s, "%Y-%m-%dT%H:%M:%S") + return dt.replace(tzinfo=timezone.utc) + try: + # try full ISO first + dt = datetime.fromisoformat(s) + return dt.astimezone(timezone.utc) if dt.tzinfo else dt.replace(tzinfo=timezone.utc) + except Exception: + # last resort: YYYY-MM-DDTHH:MM:SS + dt = datetime.strptime(s.replace(" ", "T"), "%Y-%m-%dT%H:%M:%S") + return dt.replace(tzinfo=timezone.utc) + +def fetch_gis_by_device_and_time(conn, device_id: str, started_at) -> Tuple[Optional[float], Optional[float], Optional[str]]: + started_dt = _to_dt_utc(started_at) + try: + with conn.cursor() as cur: + cur.execute( + """ + SELECT + (gis_origin->>'latitude')::double precision AS lat, + (gis_origin->>'longitude')::double precision AS lon, + (gis_origin->>'area') AS area + FROM public.sounds_metadata + WHERE device_id = %s + AND capture_time = %s + LIMIT 1 + """, + (device_id, started_dt), + ) + row = cur.fetchone() + if row: + return row[0], row[1], row[2] + + cur.execute( + """ + SELECT + (gis_origin->>'latitude')::double precision AS lat, + (gis_origin->>'longitude')::double precision AS lon, + (gis_origin->>'area') AS area + FROM public.sounds_metadata + WHERE device_id = %s + AND capture_time BETWEEN %s - interval '30 seconds' AND %s + interval '30 seconds' + ORDER BY ABS(EXTRACT(EPOCH FROM (capture_time - %s))) ASC + LIMIT 1 + """, + (device_id, started_dt, started_dt, started_dt), + ) + row = cur.fetchone() + if row: + return row[0], row[1], row[2] + except Exception: + pass + return None, None, None + +def fetch_gis_by_filename(conn, file_name: str) -> Tuple[Optional[float], Optional[float], Optional[str]]: + try: + with conn.cursor() as cur: + cur.execute( + """ + SELECT + (gis_origin->>'latitude')::double precision AS lat, + (gis_origin->>'longitude')::double precision AS lon, + (gis_origin->>'area') AS area + FROM public.sounds_metadata + WHERE file_name = %s + ORDER BY created_at DESC + LIMIT 1 + """, + (file_name,), + ) + row = cur.fetchone() + if row: + return row[0], row[1], row[2] + except Exception: + pass + return None, None, None diff --git a/services/sounds_classifier/src/classification/core/db_io_pg.py b/services/sounds_classifier/src/classification/core/db_io_pg.py index 877ffebb1..5a1789e4c 100644 --- a/services/sounds_classifier/src/classification/core/db_io_pg.py +++ b/services/sounds_classifier/src/classification/core/db_io_pg.py @@ -1,112 +1,112 @@ -from __future__ import annotations - -import json -import re -from typing import Any, Dict, Optional - -import psycopg2 -import psycopg2.extras -from psycopg2.extensions import connection as PGConnection -from psycopg2 import sql -import logging - -LOGGER = logging.getLogger(__name__) -_SCHEMA_RE = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$") - -def open_db(db_url: str, schema: str = "audio_cls") -> PGConnection: - if not db_url: - raise ValueError("db_url is required (e.g., postgresql://user:pass@host:port/db)") - if not _SCHEMA_RE.match(schema): - raise ValueError(f"invalid schema name: {schema}") - - conn = psycopg2.connect(db_url) - conn.autocommit = False - try: - with conn.cursor() as cur: - cur.execute(sql.SQL("CREATE SCHEMA IF NOT EXISTS {}").format(sql.Identifier(schema))) - cur.execute(sql.SQL("SET search_path TO {}, public").format(sql.Identifier(schema))) - conn.commit() - LOGGER.info("DB connected; schema=%s", schema) - except Exception: - conn.rollback() - LOGGER.exception("failed to init schema/search_path") - raise - return conn - -def upsert_run(conn: PGConnection, meta: Dict[str, Any]) -> None: - try: - with conn.cursor() as cur: - cur.execute( - """ - INSERT INTO runs - (run_id, model_name, checkpoint, head_path, labels_csv, - window_sec, hop_sec, pad_last, agg, topk, device, code_version, notes) - VALUES - (%(run_id)s, %(model_name)s, %(checkpoint)s, %(head_path)s, %(labels_csv)s, - %(window_sec)s, %(hop_sec)s, %(pad_last)s, %(agg)s, %(topk)s, %(device)s, %(code_version)s, %(notes)s) - ON CONFLICT (run_id) DO NOTHING - """, - meta, - ) - conn.commit() - LOGGER.debug("upsert_run: %s", meta.get("run_id")) - except Exception: - conn.rollback() - LOGGER.exception("upsert_run failed") - raise - -def finish_run(conn: PGConnection, run_id: str) -> None: - try: - with conn.cursor() as cur: - cur.execute("UPDATE runs SET finished_at = now() WHERE run_id = %s", (run_id,)) - conn.commit() - LOGGER.info("finish_run: %s", run_id) - except Exception: - conn.rollback() - LOGGER.exception("finish_run failed: %s", run_id) - raise - -def _jsonify(v: Any) -> psycopg2.extras.Json: - if isinstance(v, str): - try: - v = json.loads(v) - except Exception: - v = {"raw": v} - return psycopg2.extras.Json(v) - -def upsert_file_aggregate(conn: PGConnection, row: Dict[str, Any]) -> None: - data = dict(row) - if "head_probs_json" in data and data["head_probs_json"] is not None: - data["head_probs_json"] = _jsonify(data.get("head_probs_json")) - - try: - with conn.cursor() as cur: - cur.execute( - """ - INSERT INTO file_aggregates - (run_id, file_id, - head_probs_json, head_pred_label, head_pred_prob, head_unknown_threshold, head_is_another, - num_windows, agg_mode, processing_ms) - VALUES - (%(run_id)s, %(file_id)s, - %(head_probs_json)s, %(head_pred_label)s, %(head_pred_prob)s, %(head_unknown_threshold)s, %(head_is_another)s, - %(num_windows)s, %(agg_mode)s, %(processing_ms)s) - ON CONFLICT (run_id, file_id) DO UPDATE SET - head_probs_json = EXCLUDED.head_probs_json, - head_pred_label = EXCLUDED.head_pred_label, - head_pred_prob = EXCLUDED.head_pred_prob, - head_unknown_threshold = EXCLUDED.head_unknown_threshold, - head_is_another = EXCLUDED.head_is_another, - num_windows = EXCLUDED.num_windows, - agg_mode = EXCLUDED.agg_mode, - processing_ms = EXCLUDED.processing_ms - """, - data, - ) - conn.commit() - LOGGER.debug("upsert_file_aggregate: run=%s file=%s", data.get("run_id"), data.get("file_id")) - except Exception: - conn.rollback() - LOGGER.exception("upsert_file_aggregate failed") - raise - +from __future__ import annotations + +import json +import re +from typing import Any, Dict, Optional + +import psycopg2 +import psycopg2.extras +from psycopg2.extensions import connection as PGConnection +from psycopg2 import sql +import logging + +LOGGER = logging.getLogger(__name__) +_SCHEMA_RE = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$") + +def open_db(db_url: str, schema: str = "audio_cls") -> PGConnection: + if not db_url: + raise ValueError("db_url is required (e.g., postgresql://user:pass@host:port/db)") + if not _SCHEMA_RE.match(schema): + raise ValueError(f"invalid schema name: {schema}") + + conn = psycopg2.connect(db_url) + conn.autocommit = False + try: + with conn.cursor() as cur: + cur.execute(sql.SQL("CREATE SCHEMA IF NOT EXISTS {}").format(sql.Identifier(schema))) + cur.execute(sql.SQL("SET search_path TO {}, public").format(sql.Identifier(schema))) + conn.commit() + LOGGER.info("DB connected; schema=%s", schema) + except Exception: + conn.rollback() + LOGGER.exception("failed to init schema/search_path") + raise + return conn + +def upsert_run(conn: PGConnection, meta: Dict[str, Any]) -> None: + try: + with conn.cursor() as cur: + cur.execute( + """ + INSERT INTO runs + (run_id, model_name, checkpoint, head_path, labels_csv, + window_sec, hop_sec, pad_last, agg, topk, device, code_version, notes) + VALUES + (%(run_id)s, %(model_name)s, %(checkpoint)s, %(head_path)s, %(labels_csv)s, + %(window_sec)s, %(hop_sec)s, %(pad_last)s, %(agg)s, %(topk)s, %(device)s, %(code_version)s, %(notes)s) + ON CONFLICT (run_id) DO NOTHING + """, + meta, + ) + conn.commit() + LOGGER.debug("upsert_run: %s", meta.get("run_id")) + except Exception: + conn.rollback() + LOGGER.exception("upsert_run failed") + raise + +def finish_run(conn: PGConnection, run_id: str) -> None: + try: + with conn.cursor() as cur: + cur.execute("UPDATE runs SET finished_at = now() WHERE run_id = %s", (run_id,)) + conn.commit() + LOGGER.info("finish_run: %s", run_id) + except Exception: + conn.rollback() + LOGGER.exception("finish_run failed: %s", run_id) + raise + +def _jsonify(v: Any) -> psycopg2.extras.Json: + if isinstance(v, str): + try: + v = json.loads(v) + except Exception: + v = {"raw": v} + return psycopg2.extras.Json(v) + +def upsert_file_aggregate(conn: PGConnection, row: Dict[str, Any]) -> None: + data = dict(row) + if "head_probs_json" in data and data["head_probs_json"] is not None: + data["head_probs_json"] = _jsonify(data.get("head_probs_json")) + + try: + with conn.cursor() as cur: + cur.execute( + """ + INSERT INTO file_aggregates + (run_id, file_id, + head_probs_json, head_pred_label, head_pred_prob, head_unknown_threshold, head_is_another, + num_windows, agg_mode, processing_ms) + VALUES + (%(run_id)s, %(file_id)s, + %(head_probs_json)s, %(head_pred_label)s, %(head_pred_prob)s, %(head_unknown_threshold)s, %(head_is_another)s, + %(num_windows)s, %(agg_mode)s, %(processing_ms)s) + ON CONFLICT (run_id, file_id) DO UPDATE SET + head_probs_json = EXCLUDED.head_probs_json, + head_pred_label = EXCLUDED.head_pred_label, + head_pred_prob = EXCLUDED.head_pred_prob, + head_unknown_threshold = EXCLUDED.head_unknown_threshold, + head_is_another = EXCLUDED.head_is_another, + num_windows = EXCLUDED.num_windows, + agg_mode = EXCLUDED.agg_mode, + processing_ms = EXCLUDED.processing_ms + """, + data, + ) + conn.commit() + LOGGER.debug("upsert_file_aggregate: run=%s file=%s", data.get("run_id"), data.get("file_id")) + except Exception: + conn.rollback() + LOGGER.exception("upsert_file_aggregate failed") + raise + diff --git a/services/sounds_classifier/src/classification/core/db_utils.py b/services/sounds_classifier/src/classification/core/db_utils.py index 4e00c56ff..f2b7f139e 100644 --- a/services/sounds_classifier/src/classification/core/db_utils.py +++ b/services/sounds_classifier/src/classification/core/db_utils.py @@ -1,126 +1,126 @@ -import os -import psycopg2 -from psycopg2 import sql -from typing import Optional - -FILES_SCHEMA = os.getenv("FILES_SCHEMA", "public") -FILES_TABLE = os.getenv("FILES_TABLE", "sound_new_sounds_connections") - -def _files_table_ql() -> sql.SQL: - return sql.SQL("{}.{}").format(sql.Identifier(FILES_SCHEMA), sql.Identifier(FILES_TABLE)) - -_KEY_COL = sql.Identifier("key") - -def open_db(): - host = os.getenv("DB_HOST", "postgres") - port = int(os.getenv("DB_PORT", "5432")) - db = os.getenv("DB_NAME", "missions_db") - user = os.getenv("DB_USER", "missions_user") - pwd = os.getenv("DB_PASSWORD", "pg123") - schema = os.getenv("DB_SCHEMA", "agcloud_audio") - - conn = psycopg2.connect(host=host, port=port, dbname=db, user=user, password=pwd) - conn.autocommit = False - with conn.cursor() as cur: - cur.execute(sql.SQL("SET search_path TO {}, public;").format(sql.Identifier(schema))) - return conn - -def ensure_file(conn, *, bucket: str, object_key: str, - size_bytes: Optional[int] = None, - sample_rate: Optional[int] = None, - duration_s: Optional[float] = None) -> int: - """Idempotent ensure in public.sound_new_sounds_connections by (bucket, object_key).""" - combined_key = f"{bucket}/{object_key}".lstrip("/") - try: - with conn.cursor() as cur: - cur.execute( - sql.SQL("SELECT id FROM {} WHERE {} = %s") - .format(_files_table_ql(),_KEY_COL), - (combined_key,), - ) - row = cur.fetchone() - if row: - return int(row[0]) - - cur.execute( - sql.SQL(""" - INSERT INTO {} ({}, size_bytes, sample_rate, duration_s) - VALUES (%s, %s, %s, %s) - RETURNING id - """).format(_files_table_ql(), _KEY_COL), - (combined_key, size_bytes, sample_rate, duration_s), - ) - new_id = cur.fetchone()[0] - - conn.commit() - return int(new_id) - except Exception: - conn.rollback() - raise - -def ensure_run(conn, run_id: str): - """ - Ensure there is a row in agcloud_audio.runs for FK constraints. - This will INSERT ... ON CONFLICT DO NOTHING with reasonable defaults. - """ - import os - window_sec = float(os.getenv("WINDOW_SEC", "2.0")) - hop_sec = float(os.getenv("HOP_SEC", "0.5")) - pad_last = os.getenv("PAD_LAST", "true").lower() in ("1", "true", "yes", "on") - - with conn.cursor() as cur: - cur.execute(""" - INSERT INTO runs ( - run_id, model_name, checkpoint, head_path, labels_csv, - window_sec, hop_sec, pad_last, agg, topk, device, code_version, notes - ) - VALUES ( - %(run_id)s, %(model_name)s, %(checkpoint)s, %(head_path)s, %(labels_csv)s, - %(window_sec)s, %(hop_sec)s, %(pad_last)s, %(agg)s, %(topk)s, %(device)s, - %(code_version)s, %(notes)s - ) - ON CONFLICT (run_id) DO NOTHING - """, { - "run_id": run_id, - "model_name": os.getenv("MODEL_NAME", "panns_cnn14"), - "checkpoint": os.getenv("CHECKPOINT", "panns_cnn14.pth"), - "head_path": os.getenv("HEAD", ""), - "labels_csv": os.getenv("LABELS_CSV", ""), - "window_sec": float(os.getenv("WINDOW_SEC", "10")), - "hop_sec": float(os.getenv("HOP_SEC", "10")), - "pad_last": os.getenv("PAD_LAST", "false").lower() == "true", - "agg": os.getenv("AGG", "mean"), - "topk": int(os.getenv("TOPK", "3")), - "device": os.getenv("DEVICE", "cpu"), - "code_version": os.getenv("CODE_VERSION", ""), - "notes": os.getenv("RUN_NOTES", "created by API ensure_run") - }) - conn.commit() - -def resolve_file_id(conn, *, file_id: Optional[int] = None, - bucket: Optional[str] = None, object_key: Optional[str] = None) -> int: - """Select-only (NO insert). Raises ValueError if not found.""" - with conn.cursor() as cur: - if file_id is not None: - cur.execute( - sql.SQL("SELECT id FROM {} WHERE id = %s").format(_files_table_ql()), - (file_id,), - ) - row = cur.fetchone() - if row: - return int(row[0]) - raise ValueError(f"id {file_id} not found in {FILES_SCHEMA}.{FILES_TABLE}") - - if bucket is not None and object_key is not None: - combined_key = f"{bucket}/{object_key}".lstrip("/") - cur.execute( - sql.SQL("SELECT id FROM {} WHERE {} = %s") - .format(_files_table_ql(), _KEY_COL), - (combined_key,), - ) - row = cur.fetchone() - if row: - return int(row[0]) - raise ValueError(f"File s3://{bucket}/{object_key} not found in {FILES_SCHEMA}.{FILES_TABLE}") - - raise ValueError("Must provide file_id or (bucket, object_key)") +import os +import psycopg2 +from psycopg2 import sql +from typing import Optional + +FILES_SCHEMA = os.getenv("FILES_SCHEMA", "public") +FILES_TABLE = os.getenv("FILES_TABLE", "sound_new_sounds_connections") + +def _files_table_ql() -> sql.SQL: + return sql.SQL("{}.{}").format(sql.Identifier(FILES_SCHEMA), sql.Identifier(FILES_TABLE)) + +_KEY_COL = sql.Identifier("key") + +def open_db(): + host = os.getenv("DB_HOST", "postgres") + port = int(os.getenv("DB_PORT", "5432")) + db = os.getenv("DB_NAME", "missions_db") + user = os.getenv("DB_USER", "missions_user") + pwd = os.getenv("DB_PASSWORD", "pg123") + schema = os.getenv("DB_SCHEMA", "agcloud_audio") + + conn = psycopg2.connect(host=host, port=port, dbname=db, user=user, password=pwd) + conn.autocommit = False + with conn.cursor() as cur: + cur.execute(sql.SQL("SET search_path TO {}, public;").format(sql.Identifier(schema))) + return conn + +def ensure_file(conn, *, bucket: str, object_key: str, + size_bytes: Optional[int] = None, + sample_rate: Optional[int] = None, + duration_s: Optional[float] = None) -> int: + """Idempotent ensure in public.sound_new_sounds_connections by (bucket, object_key).""" + combined_key = f"{bucket}/{object_key}".lstrip("/") + try: + with conn.cursor() as cur: + cur.execute( + sql.SQL("SELECT id FROM {} WHERE {} = %s") + .format(_files_table_ql(),_KEY_COL), + (combined_key,), + ) + row = cur.fetchone() + if row: + return int(row[0]) + + cur.execute( + sql.SQL(""" + INSERT INTO {} ({}, size_bytes, sample_rate, duration_s) + VALUES (%s, %s, %s, %s) + RETURNING id + """).format(_files_table_ql(), _KEY_COL), + (combined_key, size_bytes, sample_rate, duration_s), + ) + new_id = cur.fetchone()[0] + + conn.commit() + return int(new_id) + except Exception: + conn.rollback() + raise + +def ensure_run(conn, run_id: str): + """ + Ensure there is a row in agcloud_audio.runs for FK constraints. + This will INSERT ... ON CONFLICT DO NOTHING with reasonable defaults. + """ + import os + window_sec = float(os.getenv("WINDOW_SEC", "2.0")) + hop_sec = float(os.getenv("HOP_SEC", "0.5")) + pad_last = os.getenv("PAD_LAST", "true").lower() in ("1", "true", "yes", "on") + + with conn.cursor() as cur: + cur.execute(""" + INSERT INTO runs ( + run_id, model_name, checkpoint, head_path, labels_csv, + window_sec, hop_sec, pad_last, agg, topk, device, code_version, notes + ) + VALUES ( + %(run_id)s, %(model_name)s, %(checkpoint)s, %(head_path)s, %(labels_csv)s, + %(window_sec)s, %(hop_sec)s, %(pad_last)s, %(agg)s, %(topk)s, %(device)s, + %(code_version)s, %(notes)s + ) + ON CONFLICT (run_id) DO NOTHING + """, { + "run_id": run_id, + "model_name": os.getenv("MODEL_NAME", "panns_cnn14"), + "checkpoint": os.getenv("CHECKPOINT", "panns_cnn14.pth"), + "head_path": os.getenv("HEAD", ""), + "labels_csv": os.getenv("LABELS_CSV", ""), + "window_sec": float(os.getenv("WINDOW_SEC", "10")), + "hop_sec": float(os.getenv("HOP_SEC", "10")), + "pad_last": os.getenv("PAD_LAST", "false").lower() == "true", + "agg": os.getenv("AGG", "mean"), + "topk": int(os.getenv("TOPK", "3")), + "device": os.getenv("DEVICE", "cpu"), + "code_version": os.getenv("CODE_VERSION", ""), + "notes": os.getenv("RUN_NOTES", "created by API ensure_run") + }) + conn.commit() + +def resolve_file_id(conn, *, file_id: Optional[int] = None, + bucket: Optional[str] = None, object_key: Optional[str] = None) -> int: + """Select-only (NO insert). Raises ValueError if not found.""" + with conn.cursor() as cur: + if file_id is not None: + cur.execute( + sql.SQL("SELECT id FROM {} WHERE id = %s").format(_files_table_ql()), + (file_id,), + ) + row = cur.fetchone() + if row: + return int(row[0]) + raise ValueError(f"id {file_id} not found in {FILES_SCHEMA}.{FILES_TABLE}") + + if bucket is not None and object_key is not None: + combined_key = f"{bucket}/{object_key}".lstrip("/") + cur.execute( + sql.SQL("SELECT id FROM {} WHERE {} = %s") + .format(_files_table_ql(), _KEY_COL), + (combined_key,), + ) + row = cur.fetchone() + if row: + return int(row[0]) + raise ValueError(f"File s3://{bucket}/{object_key} not found in {FILES_SCHEMA}.{FILES_TABLE}") + + raise ValueError("Must provide file_id or (bucket, object_key)") diff --git a/services/sounds_classifier/src/classification/core/model_io.py b/services/sounds_classifier/src/classification/core/model_io.py index 2465b6bca..fcfa3a0f6 100644 --- a/services/sounds_classifier/src/classification/core/model_io.py +++ b/services/sounds_classifier/src/classification/core/model_io.py @@ -1,248 +1,248 @@ -from __future__ import annotations - -import pathlib -import shutil -import subprocess -from typing import Any, List, Optional, Tuple, Literal - -import numpy as np -import soundfile as sf -import librosa -import logging -import os -from numpy.lib.stride_tricks import sliding_window_view - -try: - import torch -except Exception: - torch = None - -LOGGER = logging.getLogger(__name__) - -SAMPLE_RATE = 32000 -MIN_SAMPLES = 16000 -HARD_EXTS = {".mp3", ".opus", ".m4a", ".aac", ".wma"} -SUPPORTED_EXTS = {".wav", ".mp3", ".flac", ".ogg", ".m4a", ".aac", ".wma", ".opus"} - -def ensure_numpy_1d(x): - """ - Force input to be numpy float32 vector (1-D). - Accepts numpy, torch.Tensor, TF tensors, and torch-like wrappers (duck-typed). - """ - # Torch-like (duck typing): has detach/cpu/numpy - if not isinstance(x, np.ndarray): - has_detach = hasattr(x, "detach") - has_cpu = hasattr(x, "cpu") - has_numpy = hasattr(x, "numpy") - if has_detach and has_cpu and has_numpy: - try: - x = x.detach().cpu().numpy() - except Exception: - pass - # Generic tensors (e.g., TF), expose .numpy() without detach/cpu - elif has_numpy and callable(getattr(x, "numpy", None)): - try: - x = x.numpy() - except Exception: - pass - - # Final conversion to numpy float32 - x = np.asarray(x, dtype=np.float32) - - # Flatten to 1-D - if x.ndim > 1: - x = x.reshape(-1) - return x - - -def has_ffmpeg() -> bool: - return shutil.which("ffmpeg") is not None - - -def decode_with_ffmpeg_to_float32_mono(path: str, target_sr: int = SAMPLE_RATE) -> np.ndarray: - cmd = ["ffmpeg", "-v", "error", "-i", path, "-vn", "-ac", "1", "-ar", str(target_sr), "-f", "f32le", "pipe:1"] - proc = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True) - y = np.frombuffer(proc.stdout, dtype=np.float32) - if y.size < MIN_SAMPLES: - y = np.concatenate([y, np.zeros(MIN_SAMPLES - y.size, dtype=np.float32)], axis=0) - return y - - -def ensure_checkpoint(checkpoint_path: str, checkpoint_url: Optional[str]) -> str: - import urllib.request - p = pathlib.Path(checkpoint_path) - p.parent.mkdir(parents=True, exist_ok=True) - if p.exists(): - return str(p) - if not checkpoint_url: - raise FileNotFoundError(f"No checkpoint at {p}. Provide --checkpoint or --checkpoint-url.") - urllib.request.urlretrieve(checkpoint_url, p) - LOGGER.info("downloaded checkpoint to %s", p) - return str(p) - - -def load_audio(path: str, target_sr: int = SAMPLE_RATE) -> np.ndarray: - ext = pathlib.Path(path).suffix.lower() - - def _pad(y: np.ndarray) -> np.ndarray: - if y.size < MIN_SAMPLES: - y = np.concatenate([y, np.zeros(MIN_SAMPLES - y.size, dtype=np.float32)]) - return y - - # Compressed/streaming formats first (e.g., mp3, m4a, etc.) - if ext in HARD_EXTS: - try: - y, _ = librosa.load(path, sr=target_sr, mono=True) - y = ensure_numpy_1d(y) - return _pad(y) - except Exception: - if has_ffmpeg(): - LOGGER.warning("librosa failed; using ffmpeg fallback for %s", path) - y = decode_with_ffmpeg_to_float32_mono(path, target_sr) - y = ensure_numpy_1d(y) - return _pad(y) - LOGGER.exception("failed to load compressed audio: %s", path) - raise - - # Uncompressed / common wavs - try: - y, sr = sf.read(path, always_2d=False) - if hasattr(y, "ndim") and y.ndim > 1: - y = np.mean(y, axis=1) - - y = ensure_numpy_1d(y) - if int(sr) != int(target_sr): - y = librosa.resample(y, orig_sr=int(sr), target_sr=int(target_sr)) - y = ensure_numpy_1d(y) - - return _pad(y) - - except Exception: - try: - y, _ = librosa.load(path, sr=target_sr, mono=True) - y = ensure_numpy_1d(y) - return _pad(y) - except Exception: - if has_ffmpeg(): - LOGGER.warning("soundfile/librosa failed; using ffmpeg fallback for %s", path) - y = decode_with_ffmpeg_to_float32_mono(path, target_sr) - y = ensure_numpy_1d(y) - return _pad(y) - LOGGER.exception("failed to load audio: %s", path) - raise - - -def _to_numpy(x: Any) -> np.ndarray: - if (torch is not None) and hasattr(torch, "Tensor") and isinstance(x, torch.Tensor): # type: ignore - x = x.detach().cpu().numpy() - arr = np.asarray(x, dtype=np.float32) - if arr.ndim == 2: - if arr.shape[0] == 1: - arr = arr[0] - elif arr.shape[1] == 1: - arr = arr[:, 0] - else: - arr = arr.reshape(-1) - elif arr.ndim != 1: - arr = arr.reshape(-1) - return arr - - -def segment_waveform( - wav: np.ndarray, - sr: int = SAMPLE_RATE, - window_sec: float = 2.0, - hop_sec: float = 0.5, - pad_last: bool = True, -) -> List[np.ndarray]: - """ - Splits waveform into overlapping fixed-size windows. - Returns list of 1D numpy arrays (segments), each of length window_sec * sr. - """ - wav = np.asarray(wav, dtype=np.float32).reshape(-1) - win = max(1, int(round(window_sec * sr))) - hop = max(1, int(round(hop_sec * sr))) - n = wav.size - - segments: List[np.ndarray] = [] - if n == 0: - return segments - - i = 0 - while i + win <= n: - seg = wav[i: i + win].astype(np.float32) - segments.append(seg) - i += hop - - if pad_last and (i < n): - tail = wav[i:] - pad = np.zeros(win - tail.size, dtype=np.float32) - seg = np.concatenate([tail, pad], axis=0) - segments.append(seg) - elif not segments and pad_last: - pad = np.zeros(win - n, dtype=np.float32) - seg = np.concatenate([wav, pad], axis=0) - segments.append(seg) - - # ensure all are 1D np.float32 arrays - return [np.asarray(seg, dtype=np.float32).flatten() for seg in segments] - - -def segment_waveform_2d_view( - wav: np.ndarray, - sr: int = SAMPLE_RATE, - window_sec: float = 2.0, - hop_sec: float = 0.5, - pad_last: bool = True, -) -> np.ndarray: - """ - Return a 2D view of windows with shape (N, win) float32, minimizing copies. - The last window is padded if pad_last=True and needed (that one will copy). - """ - wav = np.asarray(wav, dtype=np.float32).reshape(-1) - win = max(1, int(round(window_sec * sr))) - hop = max(1, int(round(hop_sec * sr))) - n = wav.size - if n == 0: - return np.zeros((0, win), dtype=np.float32) - - if n >= win: - # sliding view for all full windows (no copy) - sw = sliding_window_view(wav, win)[::hop] # shape (N_full, win), view - if pad_last and ((n - win) % hop != 0): - tail_start = (sw.shape[0] * hop) - tail = wav[tail_start:] - pad = np.zeros(win - tail.size, dtype=np.float32) - last = np.concatenate([tail, pad], axis=0)[None, :] - return np.vstack([sw.astype(np.float32, copy=False), last.astype(np.float32, copy=False)]) - return sw.astype(np.float32, copy=False) - - # n < win - if pad_last: - pad = np.zeros(win - n, dtype=np.float32) - return np.concatenate([wav, pad], axis=0)[None, :] - return np.zeros((0, win), dtype=np.float32) - - -def aggregate_matrix(mat: np.ndarray, mode: Literal["mean", "max"] = "mean") -> np.ndarray: - if not isinstance(mat, np.ndarray): - raise TypeError("mat must be a numpy.ndarray") - if mat.ndim != 2: - raise ValueError("expected shape (num_windows, num_classes)") - if mat.shape[0] == 0: - raise ValueError("cannot aggregate an empty window matrix (num_windows == 0)") - if mat.shape[1] == 0: - raise ValueError("expected num_classes > 0") - if mode == "mean": - # Ignore NaNs when computing per-class means - v = np.nanmean(mat.astype(np.float32, copy=False), axis=0) - elif mode == "max": - # Ignore NaNs when computing per-class max - v = np.nanmax(mat.astype(np.float32, copy=False), axis=0) - else: - raise ValueError(f"Unsupported aggregation mode: {mode}") - - # Ensure finite float32 output; all-NaN columns become 0.0 - v = np.nan_to_num(v, nan=0.0, posinf=np.finfo(np.float32).max, neginf=np.finfo(np.float32).min) - return v.astype(np.float32, copy=False) - +from __future__ import annotations + +import pathlib +import shutil +import subprocess +from typing import Any, List, Optional, Tuple, Literal + +import numpy as np +import soundfile as sf +import librosa +import logging +import os +from numpy.lib.stride_tricks import sliding_window_view + +try: + import torch +except Exception: + torch = None + +LOGGER = logging.getLogger(__name__) + +SAMPLE_RATE = 32000 +MIN_SAMPLES = 16000 +HARD_EXTS = {".mp3", ".opus", ".m4a", ".aac", ".wma"} +SUPPORTED_EXTS = {".wav", ".mp3", ".flac", ".ogg", ".m4a", ".aac", ".wma", ".opus"} + +def ensure_numpy_1d(x): + """ + Force input to be numpy float32 vector (1-D). + Accepts numpy, torch.Tensor, TF tensors, and torch-like wrappers (duck-typed). + """ + # Torch-like (duck typing): has detach/cpu/numpy + if not isinstance(x, np.ndarray): + has_detach = hasattr(x, "detach") + has_cpu = hasattr(x, "cpu") + has_numpy = hasattr(x, "numpy") + if has_detach and has_cpu and has_numpy: + try: + x = x.detach().cpu().numpy() + except Exception: + pass + # Generic tensors (e.g., TF), expose .numpy() without detach/cpu + elif has_numpy and callable(getattr(x, "numpy", None)): + try: + x = x.numpy() + except Exception: + pass + + # Final conversion to numpy float32 + x = np.asarray(x, dtype=np.float32) + + # Flatten to 1-D + if x.ndim > 1: + x = x.reshape(-1) + return x + + +def has_ffmpeg() -> bool: + return shutil.which("ffmpeg") is not None + + +def decode_with_ffmpeg_to_float32_mono(path: str, target_sr: int = SAMPLE_RATE) -> np.ndarray: + cmd = ["ffmpeg", "-v", "error", "-i", path, "-vn", "-ac", "1", "-ar", str(target_sr), "-f", "f32le", "pipe:1"] + proc = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True) + y = np.frombuffer(proc.stdout, dtype=np.float32) + if y.size < MIN_SAMPLES: + y = np.concatenate([y, np.zeros(MIN_SAMPLES - y.size, dtype=np.float32)], axis=0) + return y + + +def ensure_checkpoint(checkpoint_path: str, checkpoint_url: Optional[str]) -> str: + import urllib.request + p = pathlib.Path(checkpoint_path) + p.parent.mkdir(parents=True, exist_ok=True) + if p.exists(): + return str(p) + if not checkpoint_url: + raise FileNotFoundError(f"No checkpoint at {p}. Provide --checkpoint or --checkpoint-url.") + urllib.request.urlretrieve(checkpoint_url, p) + LOGGER.info("downloaded checkpoint to %s", p) + return str(p) + + +def load_audio(path: str, target_sr: int = SAMPLE_RATE) -> np.ndarray: + ext = pathlib.Path(path).suffix.lower() + + def _pad(y: np.ndarray) -> np.ndarray: + if y.size < MIN_SAMPLES: + y = np.concatenate([y, np.zeros(MIN_SAMPLES - y.size, dtype=np.float32)]) + return y + + # Compressed/streaming formats first (e.g., mp3, m4a, etc.) + if ext in HARD_EXTS: + try: + y, _ = librosa.load(path, sr=target_sr, mono=True) + y = ensure_numpy_1d(y) + return _pad(y) + except Exception: + if has_ffmpeg(): + LOGGER.warning("librosa failed; using ffmpeg fallback for %s", path) + y = decode_with_ffmpeg_to_float32_mono(path, target_sr) + y = ensure_numpy_1d(y) + return _pad(y) + LOGGER.exception("failed to load compressed audio: %s", path) + raise + + # Uncompressed / common wavs + try: + y, sr = sf.read(path, always_2d=False) + if hasattr(y, "ndim") and y.ndim > 1: + y = np.mean(y, axis=1) + + y = ensure_numpy_1d(y) + if int(sr) != int(target_sr): + y = librosa.resample(y, orig_sr=int(sr), target_sr=int(target_sr)) + y = ensure_numpy_1d(y) + + return _pad(y) + + except Exception: + try: + y, _ = librosa.load(path, sr=target_sr, mono=True) + y = ensure_numpy_1d(y) + return _pad(y) + except Exception: + if has_ffmpeg(): + LOGGER.warning("soundfile/librosa failed; using ffmpeg fallback for %s", path) + y = decode_with_ffmpeg_to_float32_mono(path, target_sr) + y = ensure_numpy_1d(y) + return _pad(y) + LOGGER.exception("failed to load audio: %s", path) + raise + + +def _to_numpy(x: Any) -> np.ndarray: + if (torch is not None) and hasattr(torch, "Tensor") and isinstance(x, torch.Tensor): # type: ignore + x = x.detach().cpu().numpy() + arr = np.asarray(x, dtype=np.float32) + if arr.ndim == 2: + if arr.shape[0] == 1: + arr = arr[0] + elif arr.shape[1] == 1: + arr = arr[:, 0] + else: + arr = arr.reshape(-1) + elif arr.ndim != 1: + arr = arr.reshape(-1) + return arr + + +def segment_waveform( + wav: np.ndarray, + sr: int = SAMPLE_RATE, + window_sec: float = 2.0, + hop_sec: float = 0.5, + pad_last: bool = True, +) -> List[np.ndarray]: + """ + Splits waveform into overlapping fixed-size windows. + Returns list of 1D numpy arrays (segments), each of length window_sec * sr. + """ + wav = np.asarray(wav, dtype=np.float32).reshape(-1) + win = max(1, int(round(window_sec * sr))) + hop = max(1, int(round(hop_sec * sr))) + n = wav.size + + segments: List[np.ndarray] = [] + if n == 0: + return segments + + i = 0 + while i + win <= n: + seg = wav[i: i + win].astype(np.float32) + segments.append(seg) + i += hop + + if pad_last and (i < n): + tail = wav[i:] + pad = np.zeros(win - tail.size, dtype=np.float32) + seg = np.concatenate([tail, pad], axis=0) + segments.append(seg) + elif not segments and pad_last: + pad = np.zeros(win - n, dtype=np.float32) + seg = np.concatenate([wav, pad], axis=0) + segments.append(seg) + + # ensure all are 1D np.float32 arrays + return [np.asarray(seg, dtype=np.float32).flatten() for seg in segments] + + +def segment_waveform_2d_view( + wav: np.ndarray, + sr: int = SAMPLE_RATE, + window_sec: float = 2.0, + hop_sec: float = 0.5, + pad_last: bool = True, +) -> np.ndarray: + """ + Return a 2D view of windows with shape (N, win) float32, minimizing copies. + The last window is padded if pad_last=True and needed (that one will copy). + """ + wav = np.asarray(wav, dtype=np.float32).reshape(-1) + win = max(1, int(round(window_sec * sr))) + hop = max(1, int(round(hop_sec * sr))) + n = wav.size + if n == 0: + return np.zeros((0, win), dtype=np.float32) + + if n >= win: + # sliding view for all full windows (no copy) + sw = sliding_window_view(wav, win)[::hop] # shape (N_full, win), view + if pad_last and ((n - win) % hop != 0): + tail_start = (sw.shape[0] * hop) + tail = wav[tail_start:] + pad = np.zeros(win - tail.size, dtype=np.float32) + last = np.concatenate([tail, pad], axis=0)[None, :] + return np.vstack([sw.astype(np.float32, copy=False), last.astype(np.float32, copy=False)]) + return sw.astype(np.float32, copy=False) + + # n < win + if pad_last: + pad = np.zeros(win - n, dtype=np.float32) + return np.concatenate([wav, pad], axis=0)[None, :] + return np.zeros((0, win), dtype=np.float32) + + +def aggregate_matrix(mat: np.ndarray, mode: Literal["mean", "max"] = "mean") -> np.ndarray: + if not isinstance(mat, np.ndarray): + raise TypeError("mat must be a numpy.ndarray") + if mat.ndim != 2: + raise ValueError("expected shape (num_windows, num_classes)") + if mat.shape[0] == 0: + raise ValueError("cannot aggregate an empty window matrix (num_windows == 0)") + if mat.shape[1] == 0: + raise ValueError("expected num_classes > 0") + if mode == "mean": + # Ignore NaNs when computing per-class means + v = np.nanmean(mat.astype(np.float32, copy=False), axis=0) + elif mode == "max": + # Ignore NaNs when computing per-class max + v = np.nanmax(mat.astype(np.float32, copy=False), axis=0) + else: + raise ValueError(f"Unsupported aggregation mode: {mode}") + + # Ensure finite float32 output; all-NaN columns become 0.0 + v = np.nan_to_num(v, nan=0.0, posinf=np.finfo(np.float32).max, neginf=np.finfo(np.float32).min) + return v.astype(np.float32, copy=False) + diff --git a/services/sounds_classifier/src/classification/models/custom_labels.csv b/services/sounds_classifier/src/classification/models/custom_labels.csv index 7cb2d9a9f..028674305 100644 --- a/services/sounds_classifier/src/classification/models/custom_labels.csv +++ b/services/sounds_classifier/src/classification/models/custom_labels.csv @@ -1,12 +1,12 @@ -index,display_name -0,predatory_animals -1,non_predatory_animals -2,birds -3,fire -4,footsteps -5,insects -6,screaming -7,shotgun -8,stormy_weather -9,streaming_water -10,vehicle +index,display_name +0,predatory_animals +1,non_predatory_animals +2,birds +3,fire +4,footsteps +5,insects +6,screaming +7,shotgun +8,stormy_weather +9,streaming_water +10,vehicle diff --git a/services/sounds_classifier/src/classification/models/head/head_cnn14_rf.joblib.meta.json b/services/sounds_classifier/src/classification/models/head/head_cnn14_rf.joblib.meta.json index b4ba52c84..fc380654f 100644 --- a/services/sounds_classifier/src/classification/models/head/head_cnn14_rf.joblib.meta.json +++ b/services/sounds_classifier/src/classification/models/head/head_cnn14_rf.joblib.meta.json @@ -1,23 +1,23 @@ -{ - "class_order": [ - "predatory_animals", - "non_predatory_animals", - "birds", - "fire", - "footsteps", - "insects", - "screaming", - "shotgun", - "stormy_weather", - "streaming_water", - "vehicle" - ], - "seed": 42, - "test_size": 0.2, - "train_dir": "C:\\Users\\user1\\Desktop\\programming\\kamatech\\AgCloud\\AgCloud\\classification\\data\\train", - "checkpoint": "C:\\Users\\user1\\panns_data\\Cnn14_mAP=0.431.pth", - "device": "cpu", - "backbone": "cnn14", - "embedding_dim": 2048, - "head_type": "rf" +{ + "class_order": [ + "predatory_animals", + "non_predatory_animals", + "birds", + "fire", + "footsteps", + "insects", + "screaming", + "shotgun", + "stormy_weather", + "streaming_water", + "vehicle" + ], + "seed": 42, + "test_size": 0.2, + "train_dir": "C:\\Users\\user1\\Desktop\\programming\\kamatech\\AgCloud\\AgCloud\\classification\\data\\train", + "checkpoint": "C:\\Users\\user1\\panns_data\\Cnn14_mAP=0.431.pth", + "device": "cpu", + "backbone": "cnn14", + "embedding_dim": 2048, + "head_type": "rf" } \ No newline at end of file diff --git a/services/sounds_classifier/src/classification/scripts/alerts.py b/services/sounds_classifier/src/classification/scripts/alerts.py index 5b47861cd..bccf69048 100644 --- a/services/sounds_classifier/src/classification/scripts/alerts.py +++ b/services/sounds_classifier/src/classification/scripts/alerts.py @@ -1,183 +1,183 @@ -import json -import time -import logging -from typing import Optional, Dict, Any -from confluent_kafka import Producer, KafkaException -import uuid -from datetime import datetime, timezone - -LOGGER = logging.getLogger("audio_cls.alerts") -if not LOGGER.handlers: - # Minimal console handler if none configured by the app - h = logging.StreamHandler() - fmt = logging.Formatter("[%(levelname)s] %(name)s: %(message)s") - h.setFormatter(fmt) - LOGGER.addHandler(h) -LOGGER.setLevel(logging.INFO) - -# Cache one Producer per brokers string -_producer_cache: dict[str, Producer] = {} - -def _get_producer(brokers: str) -> Producer: - """ - Lazily create and cache a Kafka Producer for the given brokers string. - Do NOT load env here; configuration is passed by the caller (service). - """ - p = _producer_cache.get(brokers) - if p is not None: - return p - - conf = { - "bootstrap.servers": brokers, - "queue.buffering.max.ms": 5, # small batching for low latency - "message.timeout.ms": 5000, # fail fast - "socket.keepalive.enable": True, - "api.version.request": True, - } - try: - p = Producer(conf) - except KafkaException as e: - LOGGER.error("Failed to initialize Kafka producer (brokers=%s): %s", brokers, e) - raise - _producer_cache[brokers] = p - return p - -def _delivery_report(err, msg): - if err is not None: - LOGGER.warning("Kafka delivery failed: %s", err) - else: - LOGGER.info( - "Kafka delivered: topic=%s partition=%s offset=%s", - msg.topic(), msg.partition(), msg.offset() - ) - -def _iso_utc(dt: datetime) -> str: - return dt.astimezone(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ") - -def send_alert( - *, - brokers: str, - topic: str, - label: str, - probs: Dict[str, float], - meta: Optional[Dict[str, Any]] = None, -) -> bool: - """ - Send a JSON alert to Kafka. Returns True if enqueued+delivered (within flush timeout), - False on immediate failure. Delivery problems are logged via _delivery_report. - """ - payload = { - "label": label, - "probs": probs, - "meta": meta or {}, - "ts": int(time.time() * 1000), - } - try: - p = _get_producer(brokers) - p.produce(topic=topic, value=json.dumps(payload).encode("utf-8"), callback=_delivery_report) - # Serve delivery callbacks; flush returns number of undelivered messages (0 == success) - p.poll(0) - # undelivered = p.flush(5) - # if undelivered != 0: - # LOGGER.warning("Kafka flush returned %s undelivered message(s)", undelivered) - # return False - return True - except KafkaException as e: - LOGGER.error("Kafka exception while producing: %s", e) - return False - except BufferError as e: - LOGGER.error("Kafka local queue full: %s", e) - return False - except Exception as e: - LOGGER.error("Kafka produce error: %s", e) - return False - -# ---- Backwards compatibility shim ---- -def send_kafka_alert(file_path: str, label: str, prob: float) -> bool: - """ - Legacy helper kept for backward compatibility. Reads brokers/topic from env - ONLY if caller insists on using this function. Prefer send_alert(...). - """ - import os # local import to avoid env dependency on module load - brokers = os.getenv("KAFKA_BROKERS") or os.getenv("KAFKA_BROKER", "localhost:9092") - topic = os.getenv("ALERTS_TOPIC") or os.getenv("KAFKA_ALERTS_TOPIC", "alerts") - - payload_probs = {label: float(prob)} - meta = {"file_path": file_path, "source": "legacy_send_kafka_alert"} - - return send_alert( - brokers=brokers, - topic=topic, - label=label, - probs=payload_probs, - meta=meta, - ) - -# ---- Structured alert with strict required fields ---- -REQUIRED_FIELDS = ("alert_id", "alert_type", "device_id", "started_at") - -def send_structured_alert( - *, - brokers: str, - topic: str = "alerts", - alert_type: str, - device_id: str, - started_at: str, - ended_at: Optional[str] = None, - confidence: Optional[float] = None, - severity: Optional[int] = None, - area: Optional[str] = None, - lat: Optional[float] = None, - lon: Optional[float] = None, - image_url: Optional[str] = None, - vod: Optional[str] = None, - hls: Optional[str] = None, - meta: Optional[Dict[str, Any]] = None, - alert_id: Optional[str] = None, - message_key: Optional[str] = None, -) -> bool: - """ - Send alert JSON to Kafka in the required schema. - Required: alert_id, alert_type, device_id, started_at (ISO-8601 Z). - Optional fields are included ONLY if explicitly provided (no defaults/guesses). - """ - payload: Dict[str, Any] = { - "alert_id": alert_id or str(uuid.uuid4()), - "alert_type": alert_type, - "device_id": device_id, - "started_at": started_at, - } - - # Append optional fields IFF provided (no guessing) - if ended_at: payload["ended_at"] = ended_at - if confidence is not None: payload["confidence"] = float(confidence) - if severity is not None: payload["severity"] = int(severity) - if area: payload["area"] = area - if lat is not None: payload["lat"] = float(lat) - if lon is not None: payload["lon"] = float(lon) - if image_url: payload["image_url"] = image_url - if vod: payload["vod"] = vod - if hls: payload["hls"] = hls - if meta is not None: payload["meta"] = meta - - missing = [f for f in REQUIRED_FIELDS if f not in payload or payload[f] in (None, "")] - if missing: - LOGGER.error("Structured alert missing required fields: %s", missing) - return False - - try: - p = _get_producer(brokers) - p.produce( - topic=topic, - value=json.dumps(payload).encode("utf-8"), - key=(message_key.encode("utf-8") if isinstance(message_key, str) else None), - callback=_delivery_report - ) - p.poll(0) - return True - except KafkaException as e: - LOGGER.error("Kafka exception while producing structured alert: %s", e) - return False - except Exception as e: - LOGGER.error("Kafka produce error (structured alert): %s", e) +import json +import time +import logging +from typing import Optional, Dict, Any +from confluent_kafka import Producer, KafkaException +import uuid +from datetime import datetime, timezone + +LOGGER = logging.getLogger("audio_cls.alerts") +if not LOGGER.handlers: + # Minimal console handler if none configured by the app + h = logging.StreamHandler() + fmt = logging.Formatter("[%(levelname)s] %(name)s: %(message)s") + h.setFormatter(fmt) + LOGGER.addHandler(h) +LOGGER.setLevel(logging.INFO) + +# Cache one Producer per brokers string +_producer_cache: dict[str, Producer] = {} + +def _get_producer(brokers: str) -> Producer: + """ + Lazily create and cache a Kafka Producer for the given brokers string. + Do NOT load env here; configuration is passed by the caller (service). + """ + p = _producer_cache.get(brokers) + if p is not None: + return p + + conf = { + "bootstrap.servers": brokers, + "queue.buffering.max.ms": 5, # small batching for low latency + "message.timeout.ms": 5000, # fail fast + "socket.keepalive.enable": True, + "api.version.request": True, + } + try: + p = Producer(conf) + except KafkaException as e: + LOGGER.error("Failed to initialize Kafka producer (brokers=%s): %s", brokers, e) + raise + _producer_cache[brokers] = p + return p + +def _delivery_report(err, msg): + if err is not None: + LOGGER.warning("Kafka delivery failed: %s", err) + else: + LOGGER.info( + "Kafka delivered: topic=%s partition=%s offset=%s", + msg.topic(), msg.partition(), msg.offset() + ) + +def _iso_utc(dt: datetime) -> str: + return dt.astimezone(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ") + +def send_alert( + *, + brokers: str, + topic: str, + label: str, + probs: Dict[str, float], + meta: Optional[Dict[str, Any]] = None, +) -> bool: + """ + Send a JSON alert to Kafka. Returns True if enqueued+delivered (within flush timeout), + False on immediate failure. Delivery problems are logged via _delivery_report. + """ + payload = { + "label": label, + "probs": probs, + "meta": meta or {}, + "ts": int(time.time() * 1000), + } + try: + p = _get_producer(brokers) + p.produce(topic=topic, value=json.dumps(payload).encode("utf-8"), callback=_delivery_report) + # Serve delivery callbacks; flush returns number of undelivered messages (0 == success) + p.poll(0) + # undelivered = p.flush(5) + # if undelivered != 0: + # LOGGER.warning("Kafka flush returned %s undelivered message(s)", undelivered) + # return False + return True + except KafkaException as e: + LOGGER.error("Kafka exception while producing: %s", e) + return False + except BufferError as e: + LOGGER.error("Kafka local queue full: %s", e) + return False + except Exception as e: + LOGGER.error("Kafka produce error: %s", e) + return False + +# ---- Backwards compatibility shim ---- +def send_kafka_alert(file_path: str, label: str, prob: float) -> bool: + """ + Legacy helper kept for backward compatibility. Reads brokers/topic from env + ONLY if caller insists on using this function. Prefer send_alert(...). + """ + import os # local import to avoid env dependency on module load + brokers = os.getenv("KAFKA_BROKERS") or os.getenv("KAFKA_BROKER", "localhost:9092") + topic = os.getenv("ALERTS_TOPIC") or os.getenv("KAFKA_ALERTS_TOPIC", "alerts") + + payload_probs = {label: float(prob)} + meta = {"file_path": file_path, "source": "legacy_send_kafka_alert"} + + return send_alert( + brokers=brokers, + topic=topic, + label=label, + probs=payload_probs, + meta=meta, + ) + +# ---- Structured alert with strict required fields ---- +REQUIRED_FIELDS = ("alert_id", "alert_type", "device_id", "started_at") + +def send_structured_alert( + *, + brokers: str, + topic: str = "alerts", + alert_type: str, + device_id: str, + started_at: str, + ended_at: Optional[str] = None, + confidence: Optional[float] = None, + severity: Optional[int] = None, + area: Optional[str] = None, + lat: Optional[float] = None, + lon: Optional[float] = None, + image_url: Optional[str] = None, + vod: Optional[str] = None, + hls: Optional[str] = None, + meta: Optional[Dict[str, Any]] = None, + alert_id: Optional[str] = None, + message_key: Optional[str] = None, +) -> bool: + """ + Send alert JSON to Kafka in the required schema. + Required: alert_id, alert_type, device_id, started_at (ISO-8601 Z). + Optional fields are included ONLY if explicitly provided (no defaults/guesses). + """ + payload: Dict[str, Any] = { + "alert_id": alert_id or str(uuid.uuid4()), + "alert_type": alert_type, + "device_id": device_id, + "started_at": started_at, + } + + # Append optional fields IFF provided (no guessing) + if ended_at: payload["ended_at"] = ended_at + if confidence is not None: payload["confidence"] = float(confidence) + if severity is not None: payload["severity"] = int(severity) + if area: payload["area"] = area + if lat is not None: payload["lat"] = float(lat) + if lon is not None: payload["lon"] = float(lon) + if image_url: payload["image_url"] = image_url + if vod: payload["vod"] = vod + if hls: payload["hls"] = hls + if meta is not None: payload["meta"] = meta + + missing = [f for f in REQUIRED_FIELDS if f not in payload or payload[f] in (None, "")] + if missing: + LOGGER.error("Structured alert missing required fields: %s", missing) + return False + + try: + p = _get_producer(brokers) + p.produce( + topic=topic, + value=json.dumps(payload).encode("utf-8"), + key=(message_key.encode("utf-8") if isinstance(message_key, str) else None), + callback=_delivery_report + ) + p.poll(0) + return True + except KafkaException as e: + LOGGER.error("Kafka exception while producing structured alert: %s", e) + return False + except Exception as e: + LOGGER.error("Kafka produce error (structured alert): %s", e) return False \ No newline at end of file diff --git a/services/sounds_classifier/src/classification/scripts/classify.py b/services/sounds_classifier/src/classification/scripts/classify.py index 9746badbb..81a829837 100644 --- a/services/sounds_classifier/src/classification/scripts/classify.py +++ b/services/sounds_classifier/src/classification/scripts/classify.py @@ -1,419 +1,456 @@ -from __future__ import annotations - -import logging -import os -import tempfile -from pathlib import Path -import time -from typing import Dict, List, Optional, Tuple, Any -from panns_inference import AudioTagging -import numpy as np -import joblib - -from minio import Minio -from minio.error import S3Error -import re -from datetime import datetime, timezone -import uuid - -from classification.core.model_io import ( - SAMPLE_RATE, - _to_numpy, - load_audio, # returns 1-D float32 mono @ SAMPLE_RATE - segment_waveform_2d_view, - aggregate_matrix, -) -from classification.backbones.cnn14 import load_cnn14_model, run_cnn14_embeddings_batch -from classification.scripts import alerts - -# ----------------------------- -# Environment configuration -# ----------------------------- -DEVICE = os.getenv("DEVICE", "cpu").strip().lower() -BACKBONE = os.getenv("BACKBONE", "cnn14").strip().lower() - -CHECKPOINT = os.getenv("CHECKPOINT") or "" -CHECKPOINT_URL = os.getenv("CHECKPOINT_URL") or "" - -HEAD_PATH = os.getenv("HEAD") or "" # joblib path -LABELS_CSV = os.getenv("LABELS_CSV") or "" # optional (if head has classes_, not needed) - -WINDOW_SEC = float(os.getenv("WINDOW_SEC", "2.0")) -HOP_SEC = float(os.getenv("HOP_SEC", "0.5")) -PAD_LAST = os.getenv("PAD_LAST", "true").strip().lower() in ("1", "true", "yes", "on") -AGG = os.getenv("AGG", "mean").strip().lower() # "mean" | "max" - -UNKNOWN_THRESHOLD = float(os.getenv("UNKNOWN_THRESHOLD", "0.55")) - -MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "minio:9000") -MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "minio") -MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "minio123") -MINIO_SECURE = os.getenv("MINIO_SECURE", "false").strip().lower() in ("1", "true", "yes", "on") - -ALLOWED_BUCKETS: List[str] = [b.strip() for b in os.getenv("ALLOWED_BUCKETS", "sound").split(",") if b.strip()] -ALLOWED_CONTENT_TYPES: List[str] = [t.strip() for t in os.getenv( - "ALLOWED_CONTENT_TYPES", - "audio/wav,audio/x-wav,audio/mpeg,audio/flac,audio/ogg,audio/mp4" -).split(",") if t.strip()] -MAX_BYTES = int(os.getenv("MAX_BYTES", str(50 * 1024 * 1024))) - -KAFKA_BROKERS = os.getenv("KAFKA_BROKERS", "kafka:9092") -ALERTS_TOPIC = os.getenv("ALERTS_TOPIC", "alerts") - -# ----------------------------- -# Lazy runtime (model/head/labels) -# ----------------------------- -class _Runtime: - model = None # CNN14 backbone - head = None # sklearn pipeline with predict_proba - classes: List[str] = [] # class names aligned to head output - -R = _Runtime() - -_MINIO_CLIENT = None - -def _get_minio(): - global _MINIO_CLIENT - if _MINIO_CLIENT is None: - _MINIO_CLIENT = Minio( - MINIO_ENDPOINT, access_key=MINIO_ACCESS_KEY, secret_key=MINIO_SECRET_KEY, secure=MINIO_SECURE - ) - return _MINIO_CLIENT - -_TS_PATTERNS = ( - # ISO-like with Z or without Z, with or without 'T' - r"(?P\d{4}-?\d{2}-?\d{2}[T ]?\d{2}:?\d{2}:?\d{2}Z?)", - # Compact: YYYYMMDDTHHMMSSZ or YYYYMMDDHHMMSS - r"(?P\d{8}T?\d{6}Z?)", - # Epoch seconds or millis - r"(?P\d{10}|\d{13})", -) - -def _parse_started_at_from_token(token: str) -> Optional[str]: - """Return ISO8601 UTC Z string if token looks like a timestamp; else None.""" - t = token.strip() - # epoch - if re.fullmatch(r"\d{13}", t): - dt = datetime.fromtimestamp(int(t)/1000.0, tz=timezone.utc) - return dt.strftime("%Y-%m-%dT%H:%M:%SZ") - if re.fullmatch(r"\d{10}", t): - dt = datetime.fromtimestamp(int(t), tz=timezone.utc) - return dt.strftime("%Y-%m-%dT%H:%M:%SZ") - # compact YYYYMMDD[ T]?HHMMSS[Z]? - m = re.fullmatch(r"(\d{8})T?(\d{6})Z?", t) - if m: - d, h = m.groups() - dt = datetime.strptime(d + h, "%Y%m%d%H%M%S").replace(tzinfo=timezone.utc) - return dt.strftime("%Y-%m-%dT%H:%M:%SZ") - # ISO-ish (allow missing separators) - # normalize: keep only digits and Z, then rebuild - if re.fullmatch(r"\d{4}-?\d{2}-?\d{2}[T ]?\d{2}:?\d{2}:?\d{2}Z?", t): - # try a few formats - for fmt in ("%Y-%m-%dT%H:%M:%SZ", "%Y-%m-%d %H:%M:%SZ", - "%Y-%m-%dT%H:%M:%S", "%Y%m%dT%H%M%SZ", "%Y%m%d%H%M%S"): - try: - if t.endswith("Z") and fmt.endswith("Z"): - dt = datetime.strptime(t.replace(" ", "T"), fmt).replace(tzinfo=timezone.utc) - return dt.strftime("%Y-%m-%dT%H:%M:%SZ") - if not t.endswith("Z") and not fmt.endswith("Z"): - dt = datetime.strptime(t.replace(" ", "T").replace("-", "").replace(":", ""), "%Y%m%dT%H%M%S").replace(tzinfo=timezone.utc) - return dt.strftime("%Y-%m-%dT%H:%M:%SZ") - except Exception: - pass - return None - -def _extract_device_and_started_at_from_key(s3_key: str) -> Tuple[Optional[str], Optional[str]]: - """ - Expect filenames like 'sensorId_timestamp.*' (timestamp token can be in a few formats). - Return (device_id, started_at_isoZ) or (None, None) if not confident. - """ - name = Path(s3_key).name - m = re.match(r"(?P[^_/]+)_(?P[^_.]+)", name) - if not m: - return None, None - device_id = m.group("dev").strip() - ts_token = m.group("ts").strip() - started_at = _parse_started_at_from_token(ts_token) - if not device_id or not started_at: - return None, None - return device_id, started_at - -def _load_backbone_once() -> None: - if R.model is not None: - return - if BACKBONE != "cnn14": - raise RuntimeError(f"Only BACKBONE=cnn14 is supported in this service, got {BACKBONE}") - # load_cnn14_model internally handles checkpoint/url (your impl) - R.model = load_cnn14_model(CHECKPOINT or None, device=DEVICE) - -def _load_head_once() -> None: - if R.head is not None: - return - if not HEAD_PATH: - raise RuntimeError("HEAD env var is required (path to joblib head)") - R.head = joblib.load(HEAD_PATH) - if not hasattr(R.head, "predict_proba"): - raise RuntimeError("HEAD must expose predict_proba(X) and classes_)") - - # 1) try labels from CSV if provided (most robust for production) - labels_csv = os.getenv("LABELS_CSV") or "" - if labels_csv: - from classification.core.model_io import load_labels_from_csv - labels = load_labels_from_csv(labels_csv) - if not labels: - raise RuntimeError(f"Labels CSV is empty or unreadable: {labels_csv}") - R.classes = labels - return - - # 2) else, try meta.json next to HEAD (HEAD_META env or HEAD+'.meta.json') - head_meta = os.getenv("HEAD_META") or (HEAD_PATH + ".meta.json") - labels_from_meta = [] - try: - if os.path.exists(head_meta): - import json - with open(head_meta, "r", encoding="utf-8") as f: - meta = json.load(f) - if isinstance(meta.get("class_order"), list) and len(meta["class_order"]) > 0: - labels_from_meta = [str(x) for x in meta["class_order"]] - except Exception as e: - print(f"⚠️ Warning: failed to parse HEAD meta: {e}") - - # 3) reconcile with head.classes_ - head_classes = list(getattr(R.head, "classes_", [])) - if labels_from_meta: - # if head.classes_ are [0..N-1], we map by index - if all(isinstance(c, (int, np.integer)) for c in head_classes): - if len(head_classes) != len(labels_from_meta): - raise RuntimeError( - f"Meta class_order length ({len(labels_from_meta)}) != head.classes_ length ({len(head_classes)})" - ) - R.classes = labels_from_meta - return - # else: if head.classes_ already hold real names, prefer them - R.classes = [str(c) for c in head_classes] if head_classes else labels_from_meta - return - - # 4) fallback to head.classes_ as strings - if head_classes: - R.classes = [str(c) for c in head_classes] - return - - # 5) no labels source found - raise RuntimeError( - "No labels source found. Provide LABELS_CSV, or HEAD_META with class_order, " - "or ensure the head exposes string class names via classes_." - ) - -# ----------------------------- -# Embedding/inference helpers -# ----------------------------- - -def _aggregate_probs(per_window_probs: np.ndarray) -> np.ndarray: - """ - Aggregate per-window class probabilities to a single clip-level vector. - Supports mean|max; returns 1-D float32. - """ - if per_window_probs.ndim != 2: - raise ValueError("expected shape (num_windows, num_classes)") - if per_window_probs.shape[0] == 0: - return np.zeros((per_window_probs.shape[1],), dtype=np.float32) - v = aggregate_matrix(per_window_probs, mode=AGG) - # When AGG=max, v might be logits-like — but we trained on probs, so it is already probabilities. - # If needed: apply softmax here. For a calibrated head (sklearn) it's already in [0,1]. - return v.astype(np.float32, copy=False) - -# ----------------------------- -# Public API for service -# ----------------------------- - -# Create a dedicated logger for performance metrics -perf_logger = logging.getLogger("audio_cls.perf") -perf_logger.setLevel(logging.INFO) -if not perf_logger.handlers: - h = logging.StreamHandler() - fmt = logging.Formatter("[%(asctime)s] [PERF] %(message)s", "%Y-%m-%d %H:%M:%S") - h.setFormatter(fmt) - perf_logger.addHandler(h) - -def classify_file( - path: str, - pann_model: Optional[AudioTagging] = None, - sk_pipeline: Optional[Any] = None -) -> Dict[str, object]: - t0 = time.perf_counter() - if sk_pipeline is None: - _load_head_once() - if pann_model is None: - _load_backbone_once() - - wav = np.array(load_audio(path, SAMPLE_RATE), dtype=np.float32, copy=True, order="C") - windows_2d = segment_waveform_2d_view( - wav, SAMPLE_RATE, window_sec=WINDOW_SEC, hop_sec=HOP_SEC, pad_last=PAD_LAST - ) - - num_windows = int(windows_2d.shape[0]) - if num_windows == 0: - result = { - "label": "another", - "probs": {c: 0.0 for c in R.classes}, - "pred_prob": 0.0, - "unknown_threshold": UNKNOWN_THRESHOLD, - "is_another": True, - "num_windows": 0, - "agg_mode": AGG, - "processing_ms": int((time.perf_counter() - t0) * 1000.0), - } - return result - - # Batch embeddings - if pann_model is not None: - win = np.array(windows_2d, dtype=np.float32, copy=True, order="C") - seg = pann_model.inference(win) - if isinstance(seg, dict): - seg = seg.get("embedding") - elif isinstance(seg, tuple) and len(seg) >= 2: - seg = seg[1] - seg = np.asarray(seg, dtype=np.float32) - if seg.ndim == 1: - seg = seg[None, :] - else: - win = np.array(windows_2d, dtype=np.float32, copy=True, order="C") - seg = run_cnn14_embeddings_batch(R.model, win, batch_size=32) - - # Head predict_proba - clf = sk_pipeline if sk_pipeline is not None else R.head - per_window_probs = np.asarray(clf.predict_proba(seg), dtype=np.float32) - - # Aggregate and finalize - agg_vec = _aggregate_probs(per_window_probs) - k = int(np.argmax(agg_vec)) - top_prob = float(agg_vec[k]) - top_label = R.classes[k] - final_label = top_label if top_prob >= UNKNOWN_THRESHOLD else "another" - probs = {cls: float(p) for cls, p in zip(R.classes, agg_vec)} - - processing_ms = int((time.perf_counter() - t0) * 1000.0) - - return { - "label": final_label, - "probs": probs, - "pred_prob": top_prob, - "unknown_threshold": UNKNOWN_THRESHOLD, - "is_another": (final_label == "another"), - "num_windows": num_windows, - "agg_mode": AGG, - "processing_ms": processing_ms, - } - -def run_classification_job( - *, - s3_bucket: str, - s3_key: str, - pann_model: Optional[AudioTagging] = None, - sk_pipeline: Optional[Any] = None -) -> Dict[str, object]: - """ - Download from MinIO → classify_file → (optional) Kafka alert. - Returns a dict with 'label', 'probs, and alert send status. - """ - _load_head_once() - if ALLOWED_BUCKETS and s3_bucket not in ALLOWED_BUCKETS: - raise RuntimeError(f"Bucket '{s3_bucket}' is not allowed") - - client = _get_minio() - - # stat & validate - try: - stat = client.stat_object(s3_bucket, s3_key) - except S3Error as e: - raise RuntimeError(f"S3 stat failed: {e}") from e - size = getattr(stat, "size", None) - ctype = getattr(stat, "content_type", "") or "" - if size and size > MAX_BYTES: - raise RuntimeError(f"Object too large: {size} > {MAX_BYTES}") - if ctype and ALLOWED_CONTENT_TYPES and ctype not in ALLOWED_CONTENT_TYPES: - raise RuntimeError(f"Unsupported content-type: {ctype}") - - # download to temp - suffix = Path(s3_key).suffix or ".wav" - fd, tmp_path = tempfile.mkstemp(prefix="audio_", suffix=suffix) - os.close(fd) - try: - client.fget_object(s3_bucket, s3_key, tmp_path) - result = classify_file(tmp_path, pann_model=pann_model, sk_pipeline=sk_pipeline) - # default alert flags - result.setdefault("sent_alert", False) - result.setdefault("alert_topic", None) - result.setdefault("alert_skip_reason", None) - if result.get("processing_ms") is not None: - try: - result["processing_ms"] = int(result["processing_ms"]) - except Exception: - pass - if result["label"] != "another" and KAFKA_BROKERS and ALERTS_TOPIC: - device_id, started_at = _extract_device_and_started_at_from_key(s3_key) - if device_id and started_at: - try: - label = str(result["label"]) - alert_type = f"suspicious_sound-{label}" - - severity = None - sev_map_env = os.getenv("ALERT_SEVERITY_MAP", "").strip() - if sev_map_env: - try: - _sev_map = __import__("json").loads(sev_map_env) - if isinstance(_sev_map, dict) and label in _sev_map: - _s = _sev_map[label] - if isinstance(_s, (int, np.integer)): - severity = int(_s) - except Exception: - pass - - confidence = float(result.get("pred_prob") or 0.0) - - meta = { - "bucket": s3_bucket, - "key": s3_key, - "processing_ms": result.get("processing_ms"), - } - if meta["processing_ms"] is None: - meta.pop("processing_ms") - message_key = f"{device_id}|{started_at}" - - ok = alerts.send_structured_alert( - brokers=KAFKA_BROKERS, - topic=ALERTS_TOPIC, - alert_type=alert_type, - device_id=device_id, - started_at=started_at, - confidence=confidence, - severity=severity, - meta=meta, - message_key=message_key, - ) - perf_logger.info("About to send alert: topic=%s key=%s type=%s", - ALERTS_TOPIC, message_key, alert_type) - if ok: - result["sent_alert"] = True - result["alert_topic"] = ALERTS_TOPIC - else: - perf_logger.warning("Alert send returned False (topic=%s key=%s)", ALERTS_TOPIC, s3_key) - result["alert_skip_reason"] = "kafka_produce_returned_false" - except Exception as e: - perf_logger.warning("Alert send failed: %s (key=%s)", e, s3_key) - result["alert_skip_reason"] = "kafka_exception" - else: - perf_logger.warning( - "Skip alert (missing device_id/started_at) for key=%s", s3_key - ) - result["alert_skip_reason"] = "missing_device_or_started_at" - elif result["label"] == "another": - result["alert_skip_reason"] = "label_is_another" - elif not KAFKA_BROKERS or not ALERTS_TOPIC: - result["alert_skip_reason"] = "missing_env_brokers_or_topic" - return result - finally: - try: - os.remove(tmp_path) - except Exception: - pass +from __future__ import annotations + +import logging +import os +import tempfile +from pathlib import Path +import time +from typing import Dict, List, Optional, Tuple, Any +from panns_inference import AudioTagging +import numpy as np +import joblib + +from minio import Minio +from minio.error import S3Error +import re +from datetime import datetime, timezone +import uuid + +from classification.core.model_io import ( + SAMPLE_RATE, + _to_numpy, + load_audio, # returns 1-D float32 mono @ SAMPLE_RATE + segment_waveform_2d_view, + aggregate_matrix, +) +from classification.backbones.cnn14 import load_cnn14_model, run_cnn14_embeddings_batch +from classification.scripts import alerts +from classification.core.db_utils import open_db +from classification.core.db_gis_helpers import ( + fetch_gis_by_device_and_time, + fetch_gis_by_filename, +) + +# ----------------------------- +# Environment configuration +# ----------------------------- +DEVICE = os.getenv("DEVICE", "cpu").strip().lower() +BACKBONE = os.getenv("BACKBONE", "cnn14").strip().lower() + +CHECKPOINT = os.getenv("CHECKPOINT") or "" +CHECKPOINT_URL = os.getenv("CHECKPOINT_URL") or "" + +HEAD_PATH = os.getenv("HEAD") or "" # joblib path +LABELS_CSV = os.getenv("LABELS_CSV") or "" # optional (if head has classes_, not needed) + +WINDOW_SEC = float(os.getenv("WINDOW_SEC", "2.0")) +HOP_SEC = float(os.getenv("HOP_SEC", "0.5")) +PAD_LAST = os.getenv("PAD_LAST", "true").strip().lower() in ("1", "true", "yes", "on") +AGG = os.getenv("AGG", "mean").strip().lower() # "mean" | "max" + +UNKNOWN_THRESHOLD = float(os.getenv("UNKNOWN_THRESHOLD", "0.55")) + +MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "minio:9000") +MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "minio") +MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "minio123") +MINIO_SECURE = os.getenv("MINIO_SECURE", "false").strip().lower() in ("1", "true", "yes", "on") + +ALLOWED_BUCKETS: List[str] = [b.strip() for b in os.getenv("ALLOWED_BUCKETS", "sound").split(",") if b.strip()] +ALLOWED_CONTENT_TYPES: List[str] = [t.strip() for t in os.getenv( + "ALLOWED_CONTENT_TYPES", + "audio/wav,audio/x-wav,audio/mpeg,audio/flac,audio/ogg,audio/mp4" +).split(",") if t.strip()] +MAX_BYTES = int(os.getenv("MAX_BYTES", str(50 * 1024 * 1024))) + +KAFKA_BROKERS = os.getenv("KAFKA_BROKERS", "kafka:9092") +ALERTS_TOPIC = os.getenv("ALERTS_TOPIC", "alerts") + +# ----------------------------- +# Lazy runtime (model/head/labels) +# ----------------------------- +class _Runtime: + model = None # CNN14 backbone + head = None # sklearn pipeline with predict_proba + classes: List[str] = [] # class names aligned to head output + +R = _Runtime() + +_MINIO_CLIENT = None +_DB_CONN = None + +def _get_minio(): + global _MINIO_CLIENT + if _MINIO_CLIENT is None: + _MINIO_CLIENT = Minio( + MINIO_ENDPOINT, access_key=MINIO_ACCESS_KEY, secret_key=MINIO_SECRET_KEY, secure=MINIO_SECURE + ) + return _MINIO_CLIENT + +def _get_db_conn(): + """ + Lazy-open and cache a DB connection using open_db(). + """ + global _DB_CONN + if _DB_CONN is None: + _DB_CONN = open_db() + return _DB_CONN + +_TS_PATTERNS = ( + # ISO-like with Z or without Z, with or without 'T' + r"(?P\d{4}-?\d{2}-?\d{2}[T ]?\d{2}:?\d{2}:?\d{2}Z?)", + # Compact: YYYYMMDDTHHMMSSZ or YYYYMMDDHHMMSS + r"(?P\d{8}T?\d{6}Z?)", + # Epoch seconds or millis + r"(?P\d{10}|\d{13})", +) + +def _parse_started_at_from_token(token: str) -> Optional[str]: + """Return ISO8601 UTC Z string if token looks like a timestamp; else None.""" + t = token.strip() + # epoch + if re.fullmatch(r"\d{13}", t): + dt = datetime.fromtimestamp(int(t)/1000.0, tz=timezone.utc) + return dt.strftime("%Y-%m-%dT%H:%M:%SZ") + if re.fullmatch(r"\d{10}", t): + dt = datetime.fromtimestamp(int(t), tz=timezone.utc) + return dt.strftime("%Y-%m-%dT%H:%M:%SZ") + # compact YYYYMMDD[ T]?HHMMSS[Z]? + m = re.fullmatch(r"(\d{8})T?(\d{6})Z?", t) + if m: + d, h = m.groups() + dt = datetime.strptime(d + h, "%Y%m%d%H%M%S").replace(tzinfo=timezone.utc) + return dt.strftime("%Y-%m-%dT%H:%M:%SZ") + # ISO-ish (allow missing separators) + # normalize: keep only digits and Z, then rebuild + if re.fullmatch(r"\d{4}-?\d{2}-?\d{2}[T ]?\d{2}:?\d{2}:?\d{2}Z?", t): + # try a few formats + for fmt in ("%Y-%m-%dT%H:%M:%SZ", "%Y-%m-%d %H:%M:%SZ", + "%Y-%m-%dT%H:%M:%S", "%Y%m%dT%H%M%SZ", "%Y%m%d%H%M%S"): + try: + if t.endswith("Z") and fmt.endswith("Z"): + dt = datetime.strptime(t.replace(" ", "T"), fmt).replace(tzinfo=timezone.utc) + return dt.strftime("%Y-%m-%dT%H:%M:%SZ") + if not t.endswith("Z") and not fmt.endswith("Z"): + dt = datetime.strptime(t.replace(" ", "T").replace("-", "").replace(":", ""), "%Y%m%dT%H%M%S").replace(tzinfo=timezone.utc) + return dt.strftime("%Y-%m-%dT%H:%M:%SZ") + except Exception: + pass + return None + +def _extract_device_and_started_at_from_key(s3_key: str) -> Tuple[Optional[str], Optional[str]]: + """ + Expect filenames like 'sensorId_timestamp.*' (timestamp token can be in a few formats). + Return (device_id, started_at_isoZ) or (None, None) if not confident. + """ + name = Path(s3_key).name + m = re.match(r"(?P[^_/]+)_(?P[^_.]+)", name) + if not m: + return None, None + device_id = m.group("dev").strip() + ts_token = m.group("ts").strip() + started_at = _parse_started_at_from_token(ts_token) + if not device_id or not started_at: + return None, None + return device_id, started_at + +def _load_backbone_once() -> None: + if R.model is not None: + return + if BACKBONE != "cnn14": + raise RuntimeError(f"Only BACKBONE=cnn14 is supported in this service, got {BACKBONE}") + # load_cnn14_model internally handles checkpoint/url (your impl) + R.model = load_cnn14_model(CHECKPOINT or None, device=DEVICE) + +def _load_head_once() -> None: + if R.head is not None: + return + if not HEAD_PATH: + raise RuntimeError("HEAD env var is required (path to joblib head)") + R.head = joblib.load(HEAD_PATH) + if not hasattr(R.head, "predict_proba"): + raise RuntimeError("HEAD must expose predict_proba(X) and classes_)") + + # 1) try labels from CSV if provided (most robust for production) + labels_csv = os.getenv("LABELS_CSV") or "" + if labels_csv: + from classification.core.model_io import load_labels_from_csv + labels = load_labels_from_csv(labels_csv) + if not labels: + raise RuntimeError(f"Labels CSV is empty or unreadable: {labels_csv}") + R.classes = labels + return + + # 2) else, try meta.json next to HEAD (HEAD_META env or HEAD+'.meta.json') + head_meta = os.getenv("HEAD_META") or (HEAD_PATH + ".meta.json") + labels_from_meta = [] + try: + if os.path.exists(head_meta): + import json + with open(head_meta, "r", encoding="utf-8") as f: + meta = json.load(f) + if isinstance(meta.get("class_order"), list) and len(meta["class_order"]) > 0: + labels_from_meta = [str(x) for x in meta["class_order"]] + except Exception as e: + print(f"⚠️ Warning: failed to parse HEAD meta: {e}") + + # 3) reconcile with head.classes_ + head_classes = list(getattr(R.head, "classes_", [])) + if labels_from_meta: + # if head.classes_ are [0..N-1], we map by index + if all(isinstance(c, (int, np.integer)) for c in head_classes): + if len(head_classes) != len(labels_from_meta): + raise RuntimeError( + f"Meta class_order length ({len(labels_from_meta)}) != head.classes_ length ({len(head_classes)})" + ) + R.classes = labels_from_meta + return + # else: if head.classes_ already hold real names, prefer them + R.classes = [str(c) for c in head_classes] if head_classes else labels_from_meta + return + + # 4) fallback to head.classes_ as strings + if head_classes: + R.classes = [str(c) for c in head_classes] + return + + # 5) no labels source found + raise RuntimeError( + "No labels source found. Provide LABELS_CSV, or HEAD_META with class_order, " + "or ensure the head exposes string class names via classes_." + ) + +# ----------------------------- +# Embedding/inference helpers +# ----------------------------- + +def _aggregate_probs(per_window_probs: np.ndarray) -> np.ndarray: + """ + Aggregate per-window class probabilities to a single clip-level vector. + Supports mean|max; returns 1-D float32. + """ + if per_window_probs.ndim != 2: + raise ValueError("expected shape (num_windows, num_classes)") + if per_window_probs.shape[0] == 0: + return np.zeros((per_window_probs.shape[1],), dtype=np.float32) + v = aggregate_matrix(per_window_probs, mode=AGG) + # When AGG=max, v might be logits-like — but we trained on probs, so it is already probabilities. + # If needed: apply softmax here. For a calibrated head (sklearn) it's already in [0,1]. + return v.astype(np.float32, copy=False) + +# ----------------------------- +# Public API for service +# ----------------------------- + +# Create a dedicated logger for performance metrics +perf_logger = logging.getLogger("audio_cls.perf") +perf_logger.setLevel(logging.INFO) +if not perf_logger.handlers: + h = logging.StreamHandler() + fmt = logging.Formatter("[%(asctime)s] [PERF] %(message)s", "%Y-%m-%d %H:%M:%S") + h.setFormatter(fmt) + perf_logger.addHandler(h) + +def classify_file( + path: str, + pann_model: Optional[AudioTagging] = None, + sk_pipeline: Optional[Any] = None +) -> Dict[str, object]: + t0 = time.perf_counter() + if sk_pipeline is None: + _load_head_once() + if pann_model is None: + _load_backbone_once() + + wav = np.array(load_audio(path, SAMPLE_RATE), dtype=np.float32, copy=True, order="C") + windows_2d = segment_waveform_2d_view( + wav, SAMPLE_RATE, window_sec=WINDOW_SEC, hop_sec=HOP_SEC, pad_last=PAD_LAST + ) + + num_windows = int(windows_2d.shape[0]) + if num_windows == 0: + result = { + "label": "another", + "probs": {c: 0.0 for c in R.classes}, + "pred_prob": 0.0, + "unknown_threshold": UNKNOWN_THRESHOLD, + "is_another": True, + "num_windows": 0, + "agg_mode": AGG, + "processing_ms": int((time.perf_counter() - t0) * 1000.0), + } + return result + + # Batch embeddings + if pann_model is not None: + win = np.array(windows_2d, dtype=np.float32, copy=True, order="C") + seg = pann_model.inference(win) + if isinstance(seg, dict): + seg = seg.get("embedding") + elif isinstance(seg, tuple) and len(seg) >= 2: + seg = seg[1] + seg = np.asarray(seg, dtype=np.float32) + if seg.ndim == 1: + seg = seg[None, :] + else: + win = np.array(windows_2d, dtype=np.float32, copy=True, order="C") + seg = run_cnn14_embeddings_batch(R.model, win, batch_size=32) + + # Head predict_proba + clf = sk_pipeline if sk_pipeline is not None else R.head + per_window_probs = np.asarray(clf.predict_proba(seg), dtype=np.float32) + + # Aggregate and finalize + agg_vec = _aggregate_probs(per_window_probs) + k = int(np.argmax(agg_vec)) + top_prob = float(agg_vec[k]) + top_label = R.classes[k] + final_label = top_label if top_prob >= UNKNOWN_THRESHOLD else "another" + probs = {cls: float(p) for cls, p in zip(R.classes, agg_vec)} + + processing_ms = int((time.perf_counter() - t0) * 1000.0) + + return { + "label": final_label, + "probs": probs, + "pred_prob": top_prob, + "unknown_threshold": UNKNOWN_THRESHOLD, + "is_another": (final_label == "another"), + "num_windows": num_windows, + "agg_mode": AGG, + "processing_ms": processing_ms, + } + +def run_classification_job( + *, + s3_bucket: str, + s3_key: str, + pann_model: Optional[AudioTagging] = None, + sk_pipeline: Optional[Any] = None +) -> Dict[str, object]: + """ + Download from MinIO → classify_file → (optional) Kafka alert. + Returns a dict with 'label', 'probs, and alert send status. + """ + _load_head_once() + if ALLOWED_BUCKETS and s3_bucket not in ALLOWED_BUCKETS: + raise RuntimeError(f"Bucket '{s3_bucket}' is not allowed") + + client = _get_minio() + + # stat & validate + try: + stat = client.stat_object(s3_bucket, s3_key) + except S3Error as e: + raise RuntimeError(f"S3 stat failed: {e}") from e + size = getattr(stat, "size", None) + ctype = getattr(stat, "content_type", "") or "" + if size and size > MAX_BYTES: + raise RuntimeError(f"Object too large: {size} > {MAX_BYTES}") + if ctype and ALLOWED_CONTENT_TYPES and ctype not in ALLOWED_CONTENT_TYPES: + raise RuntimeError(f"Unsupported content-type: {ctype}") + + # download to temp + suffix = Path(s3_key).suffix or ".wav" + fd, tmp_path = tempfile.mkstemp(prefix="audio_", suffix=suffix) + os.close(fd) + try: + client.fget_object(s3_bucket, s3_key, tmp_path) + result = classify_file(tmp_path, pann_model=pann_model, sk_pipeline=sk_pipeline) + # default alert flags + result.setdefault("sent_alert", False) + result.setdefault("alert_topic", None) + result.setdefault("alert_skip_reason", None) + if result.get("processing_ms") is not None: + try: + result["processing_ms"] = int(result["processing_ms"]) + except Exception: + pass + + if result["label"] != "another" and KAFKA_BROKERS and ALERTS_TOPIC: + device_id, started_at = _extract_device_and_started_at_from_key(s3_key) + if device_id and started_at: + lat = lon = area = None + try: + conn = _get_db_conn() + lat, lon, area = fetch_gis_by_device_and_time(conn, device_id, started_at) + if lat is None or lon is None: + file_name = Path(s3_key).name + fl, fn, fa = fetch_gis_by_filename(conn, file_name) + lat = lat if lat is not None else fl + lon = lon if lon is not None else fn + area = area or fa + except Exception: + pass + + try: + label = str(result["label"]) + alert_type = f"suspicious_sound-{label}" + + severity = None + sev_map_env = os.getenv("ALERT_SEVERITY_MAP", "").strip() + if sev_map_env: + try: + _sev_map = __import__("json").loads(sev_map_env) + if isinstance(_sev_map, dict) and label in _sev_map: + _s = _sev_map[label] + if isinstance(_s, (int, np.integer)): + severity = int(_s) + except Exception: + pass + + confidence = float(result.get("pred_prob") or 0.0) + + meta = { + "bucket": s3_bucket, + "key": s3_key, + "processing_ms": result.get("processing_ms"), + } + if meta["processing_ms"] is None: + meta.pop("processing_ms") + message_key = f"{device_id}|{started_at}" + alert_id = str(uuid.uuid4()) + + perf_logger.info( + "About to send structured alert: topic=%s key=%s type=%s lat=%s lon=%s area=%s", + ALERTS_TOPIC, message_key, alert_type, lat, lon, area + ) + + ok = alerts.send_structured_alert( + brokers=KAFKA_BROKERS, + topic=ALERTS_TOPIC, + alert_type=alert_type, + device_id=device_id, + started_at=started_at, + confidence=confidence, + severity=severity, + area=area, + lat=lat, + lon=lon, + meta=meta, + alert_id=alert_id, + message_key=message_key, + ) + if ok: + result["sent_alert"] = True + result["alert_topic"] = ALERTS_TOPIC + else: + perf_logger.warning("Alert send returned False (topic=%s key=%s)", ALERTS_TOPIC, s3_key) + result["alert_skip_reason"] = "kafka_produce_returned_false" + except Exception as e: + perf_logger.warning("Alert send failed: %s (key=%s)", e, s3_key) + result["alert_skip_reason"] = "kafka_exception" + else: + perf_logger.warning( + "Skip alert (missing device_id/started_at) for key=%s", s3_key + ) + result["alert_skip_reason"] = "missing_device_or_started_at" + elif result["label"] == "another": + result["alert_skip_reason"] = "label_is_another" + elif not KAFKA_BROKERS or not ALERTS_TOPIC: + result["alert_skip_reason"] = "missing_env_brokers_or_topic" + return result + finally: + try: + os.remove(tmp_path) + except Exception: + pass diff --git a/services/sounds_classifier/tests/conftest.py b/services/sounds_classifier/tests/conftest.py index 10920f2c3..afb6a527e 100644 --- a/services/sounds_classifier/tests/conftest.py +++ b/services/sounds_classifier/tests/conftest.py @@ -1,56 +1,56 @@ -import sys -import pathlib -import os -import pytest - -# 1) Ensure "src" is on sys.path so `import classification...` works -# This walks up from tests/ to repo root and prepends /src -HERE = pathlib.Path(__file__).resolve() -ROOT = HERE -for _ in range(6): # walk up a few levels just in case - if (ROOT / "src").exists(): - sys.path.insert(0, str(ROOT / "src")) - break - ROOT = ROOT.parent - -# 2) Provide minimal, isolated env defaults for tests -@pytest.fixture(autouse=True) -def _isolate_env(monkeypatch: pytest.MonkeyPatch, tmp_path: pathlib.Path): - # Core runtime defaults - monkeypatch.setenv("DEVICE", "cpu") - monkeypatch.setenv("BACKBONE", "cnn14") - - # Windowing / aggregation - monkeypatch.setenv("WINDOW_SEC", "2.0") - monkeypatch.setenv("HOP_SEC", "0.5") - monkeypatch.setenv("PAD_LAST", "true") - monkeypatch.setenv("AGG", "mean") - monkeypatch.setenv("UNKNOWN_THRESHOLD", "0.55") - - # Disable optional integrations by default - monkeypatch.setenv("KAFKA_BROKERS", "") - monkeypatch.delenv("WRITE_DB", raising=False) - monkeypatch.delenv("DB_URL", raising=False) - - # HEAD path (tests can override with real/mocked head if needed) - head_dir = tmp_path / "head" - head_dir.mkdir(parents=True, exist_ok=True) - monkeypatch.setenv("HEAD", str(head_dir / "dummy.joblib")) - # Let tests decide labels source; default to none - monkeypatch.setenv("LABELS_CSV", "") - monkeypatch.delenv("HEAD_META", raising=False) - - # MinIO defaults (won't be used unless explicitly mocked) - monkeypatch.setenv("MINIO_ENDPOINT", "minio:9000") - monkeypatch.setenv("MINIO_ACCESS_KEY", "minio") - monkeypatch.setenv("MINIO_SECRET_KEY", "minio123") - monkeypatch.setenv("MINIO_SECURE", "false") - - # Kafka alerts defaults - monkeypatch.setenv("ALERTS_TOPIC", "dev-robot-alerts") - - # Checkpoint defaults (tests typically mock loading; real file not needed) - monkeypatch.setenv("CHECKPOINT", str(tmp_path / "models" / "panns_data" / "Cnn14_mAP=0.431.pth")) - monkeypatch.delenv("CHECKPOINT_URL", raising=False) - - yield +import sys +import pathlib +import os +import pytest + +# 1) Ensure "src" is on sys.path so `import classification...` works +# This walks up from tests/ to repo root and prepends /src +HERE = pathlib.Path(__file__).resolve() +ROOT = HERE +for _ in range(6): # walk up a few levels just in case + if (ROOT / "src").exists(): + sys.path.insert(0, str(ROOT / "src")) + break + ROOT = ROOT.parent + +# 2) Provide minimal, isolated env defaults for tests +@pytest.fixture(autouse=True) +def _isolate_env(monkeypatch: pytest.MonkeyPatch, tmp_path: pathlib.Path): + # Core runtime defaults + monkeypatch.setenv("DEVICE", "cpu") + monkeypatch.setenv("BACKBONE", "cnn14") + + # Windowing / aggregation + monkeypatch.setenv("WINDOW_SEC", "2.0") + monkeypatch.setenv("HOP_SEC", "0.5") + monkeypatch.setenv("PAD_LAST", "true") + monkeypatch.setenv("AGG", "mean") + monkeypatch.setenv("UNKNOWN_THRESHOLD", "0.55") + + # Disable optional integrations by default + monkeypatch.setenv("KAFKA_BROKERS", "") + monkeypatch.delenv("WRITE_DB", raising=False) + monkeypatch.delenv("DB_URL", raising=False) + + # HEAD path (tests can override with real/mocked head if needed) + head_dir = tmp_path / "head" + head_dir.mkdir(parents=True, exist_ok=True) + monkeypatch.setenv("HEAD", str(head_dir / "dummy.joblib")) + # Let tests decide labels source; default to none + monkeypatch.setenv("LABELS_CSV", "") + monkeypatch.delenv("HEAD_META", raising=False) + + # MinIO defaults (won't be used unless explicitly mocked) + monkeypatch.setenv("MINIO_ENDPOINT", "minio:9000") + monkeypatch.setenv("MINIO_ACCESS_KEY", "minio") + monkeypatch.setenv("MINIO_SECRET_KEY", "minio123") + monkeypatch.setenv("MINIO_SECURE", "false") + + # Kafka alerts defaults + monkeypatch.setenv("ALERTS_TOPIC", "dev-robot-alerts") + + # Checkpoint defaults (tests typically mock loading; real file not needed) + monkeypatch.setenv("CHECKPOINT", str(tmp_path / "models" / "panns_data" / "Cnn14_mAP=0.431.pth")) + monkeypatch.delenv("CHECKPOINT_URL", raising=False) + + yield diff --git a/services/sounds_classifier/tests/test_alerts.py b/services/sounds_classifier/tests/test_alerts.py index 97989ff34..f2dd89850 100644 --- a/services/sounds_classifier/tests/test_alerts.py +++ b/services/sounds_classifier/tests/test_alerts.py @@ -1,161 +1,161 @@ -import json -import types -import os -import pytest - -import classification.scripts.alerts as alerts - - -# ---------- test helpers ---------- -class DummyMsg: - def __init__(self, topic, partition, offset): - self._t = topic - self._p = partition - self._o = offset - def topic(self): return self._t - def partition(self): return self._p - def offset(self): return self._o - - -class DummyProducer: - def __init__(self, *a, **kw): - self._queue = [] - self._flushed = 0 - def produce(self, *, topic, value, callback=None): - self._queue.append((topic, value)) - if callback: - callback(None, DummyMsg(topic, 0, len(self._queue) - 1)) - def poll(self, _): # api compatibility - pass - def flush(self, timeout): - self._flushed += 1 - return 0 # 0 undelivered → success - - -@pytest.fixture(autouse=True) -def _clear_cache(): - alerts._producer_cache.clear() - yield - alerts._producer_cache.clear() - - -# ---------- tests ---------- -def test_send_alert_success_and_payload(monkeypatch): - dp = DummyProducer() - monkeypatch.setattr(alerts, "Producer", lambda *_a, **_k: dp, raising=True) - - ok = alerts.send_alert( - brokers="kafka:9092", - topic="dev-robot-alerts", - label="car", - probs={"car": 0.9, "dog": 0.1}, - meta={"bucket": "b", "key": "k.wav"}, - ) - assert ok is True - # Verify one message with proper JSON payload - assert len(dp._queue) == 1 - topic, raw = dp._queue[0] - assert topic == "dev-robot-alerts" - payload = json.loads(raw.decode("utf-8")) - assert payload["label"] == "car" - assert payload["probs"]["car"] == pytest.approx(0.9) - assert isinstance(payload["ts"], int) - - -def test_producer_cache_reuse(monkeypatch): - calls = {"made": 0} - def mk(*_a, **_k): - calls["made"] += 1 - return DummyProducer() - monkeypatch.setattr(alerts, "Producer", mk, raising=True) - - # First call creates a producer - assert alerts.send_alert(brokers="kafka:9092", topic="t", label="x", probs={"x": 1.0}) - # Second call should reuse cache → no extra Producer() - assert alerts.send_alert(brokers="kafka:9092", topic="t", label="y", probs={"y": 1.0}) - assert calls["made"] == 1 - assert len(alerts._producer_cache) == 1 - - -def test_send_alert_is_non_blocking_and_returns_true(monkeypatch, caplog): - class ProducerNoFlush(DummyProducer): - def flush(self, timeout): - return 1 # would indicate undelivered if we used it, but we don't block now - - monkeypatch.setattr(alerts, "Producer", lambda *_a, **_k: ProducerNoFlush(), raising=True) - - ok = alerts.send_alert(brokers="b:9092", topic="t", label="x", probs={"x": 1.0}) - assert ok is True - assert any("Kafka delivered" in rec.message or "Kafka" in rec.message for rec in caplog.records) - - -def test_send_alert_kafka_exception_on_init(monkeypatch, caplog): - class DummyKafkaEx(alerts.KafkaException): # use the module's class - pass - def boom(*_a, **_k): - raise DummyKafkaEx("init failed") - monkeypatch.setattr(alerts, "Producer", boom, raising=True) - - ok = alerts.send_alert(brokers="bad:9092", topic="t", label="x", probs={"x": 1.0}) - assert ok is False - assert any("exception while producing" in rec.message or "Failed to initialize Kafka" in rec.message - for rec in caplog.records) - - -def test_send_alert_buffer_error(monkeypatch, caplog): - class BufErrProducer(DummyProducer): - def produce(self, *a, **k): - raise BufferError("local queue full") - monkeypatch.setattr(alerts, "Producer", lambda *_a, **_k: BufErrProducer(), raising=True) - - ok = alerts.send_alert(brokers="b:9092", topic="t", label="x", probs={"x": 1.0}) - assert ok is False - assert any("local queue full" in rec.message for rec in caplog.records) - - -def test_send_alert_runtime_error(monkeypatch, caplog): - class BoomProducer(DummyProducer): - def produce(self, *a, **k): - raise RuntimeError("produce exploded") - monkeypatch.setattr(alerts, "Producer", lambda *_a, **_k: BoomProducer(), raising=True) - - ok = alerts.send_alert(brokers="b:9092", topic="t", label="x", probs={"x": 1.0}) - assert ok is False - assert any("produce error" in rec.message for rec in caplog.records) - - -def test_legacy_send_kafka_alert_reads_env(monkeypatch): - # Check that env is read and forwarded into send_alert - captured = {} - def fake_send_alert(*, brokers, topic, label, probs, meta): - captured["brokers"] = brokers - captured["topic"] = topic - captured["label"] = label - captured["probs"] = probs - captured["meta"] = meta - return True - - monkeypatch.setenv("KAFKA_BROKERS", "env-b:9092") - monkeypatch.setenv("ALERTS_TOPIC", "env-topic") - monkeypatch.setattr(alerts, "send_alert", fake_send_alert, raising=True) - - ok = alerts.send_kafka_alert(file_path="/tmp/a.wav", label="car", prob=0.7) - assert ok is True - assert captured["brokers"] == "env-b:9092" - assert captured["topic"] == "env-topic" - assert captured["label"] == "car" - assert captured["probs"] == {"car": 0.7} - assert captured["meta"]["file_path"] == "/tmp/a.wav" - - -def test__delivery_report_logs_ok_and_err(caplog): - # OK case - alerts._delivery_report(None, DummyMsg("t", 0, 1)) - # Error case - class Err: - def __str__(self): return "boom" - alerts._delivery_report(Err(), DummyMsg("t", 0, 2)) - - # We don't assert exact wording, just that both paths logged - assert any("Kafka delivered" in r.message for r in caplog.records) - assert any("Kafka delivery failed" in r.message for r in caplog.records) +import json +import types +import os +import pytest + +import classification.scripts.alerts as alerts + + +# ---------- test helpers ---------- +class DummyMsg: + def __init__(self, topic, partition, offset): + self._t = topic + self._p = partition + self._o = offset + def topic(self): return self._t + def partition(self): return self._p + def offset(self): return self._o + + +class DummyProducer: + def __init__(self, *a, **kw): + self._queue = [] + self._flushed = 0 + def produce(self, *, topic, value, callback=None): + self._queue.append((topic, value)) + if callback: + callback(None, DummyMsg(topic, 0, len(self._queue) - 1)) + def poll(self, _): # api compatibility + pass + def flush(self, timeout): + self._flushed += 1 + return 0 # 0 undelivered → success + + +@pytest.fixture(autouse=True) +def _clear_cache(): + alerts._producer_cache.clear() + yield + alerts._producer_cache.clear() + + +# ---------- tests ---------- +def test_send_alert_success_and_payload(monkeypatch): + dp = DummyProducer() + monkeypatch.setattr(alerts, "Producer", lambda *_a, **_k: dp, raising=True) + + ok = alerts.send_alert( + brokers="kafka:9092", + topic="dev-robot-alerts", + label="car", + probs={"car": 0.9, "dog": 0.1}, + meta={"bucket": "b", "key": "k.wav"}, + ) + assert ok is True + # Verify one message with proper JSON payload + assert len(dp._queue) == 1 + topic, raw = dp._queue[0] + assert topic == "dev-robot-alerts" + payload = json.loads(raw.decode("utf-8")) + assert payload["label"] == "car" + assert payload["probs"]["car"] == pytest.approx(0.9) + assert isinstance(payload["ts"], int) + + +def test_producer_cache_reuse(monkeypatch): + calls = {"made": 0} + def mk(*_a, **_k): + calls["made"] += 1 + return DummyProducer() + monkeypatch.setattr(alerts, "Producer", mk, raising=True) + + # First call creates a producer + assert alerts.send_alert(brokers="kafka:9092", topic="t", label="x", probs={"x": 1.0}) + # Second call should reuse cache → no extra Producer() + assert alerts.send_alert(brokers="kafka:9092", topic="t", label="y", probs={"y": 1.0}) + assert calls["made"] == 1 + assert len(alerts._producer_cache) == 1 + + +def test_send_alert_is_non_blocking_and_returns_true(monkeypatch, caplog): + class ProducerNoFlush(DummyProducer): + def flush(self, timeout): + return 1 # would indicate undelivered if we used it, but we don't block now + + monkeypatch.setattr(alerts, "Producer", lambda *_a, **_k: ProducerNoFlush(), raising=True) + + ok = alerts.send_alert(brokers="b:9092", topic="t", label="x", probs={"x": 1.0}) + assert ok is True + assert any("Kafka delivered" in rec.message or "Kafka" in rec.message for rec in caplog.records) + + +def test_send_alert_kafka_exception_on_init(monkeypatch, caplog): + class DummyKafkaEx(alerts.KafkaException): # use the module's class + pass + def boom(*_a, **_k): + raise DummyKafkaEx("init failed") + monkeypatch.setattr(alerts, "Producer", boom, raising=True) + + ok = alerts.send_alert(brokers="bad:9092", topic="t", label="x", probs={"x": 1.0}) + assert ok is False + assert any("exception while producing" in rec.message or "Failed to initialize Kafka" in rec.message + for rec in caplog.records) + + +def test_send_alert_buffer_error(monkeypatch, caplog): + class BufErrProducer(DummyProducer): + def produce(self, *a, **k): + raise BufferError("local queue full") + monkeypatch.setattr(alerts, "Producer", lambda *_a, **_k: BufErrProducer(), raising=True) + + ok = alerts.send_alert(brokers="b:9092", topic="t", label="x", probs={"x": 1.0}) + assert ok is False + assert any("local queue full" in rec.message for rec in caplog.records) + + +def test_send_alert_runtime_error(monkeypatch, caplog): + class BoomProducer(DummyProducer): + def produce(self, *a, **k): + raise RuntimeError("produce exploded") + monkeypatch.setattr(alerts, "Producer", lambda *_a, **_k: BoomProducer(), raising=True) + + ok = alerts.send_alert(brokers="b:9092", topic="t", label="x", probs={"x": 1.0}) + assert ok is False + assert any("produce error" in rec.message for rec in caplog.records) + + +def test_legacy_send_kafka_alert_reads_env(monkeypatch): + # Check that env is read and forwarded into send_alert + captured = {} + def fake_send_alert(*, brokers, topic, label, probs, meta): + captured["brokers"] = brokers + captured["topic"] = topic + captured["label"] = label + captured["probs"] = probs + captured["meta"] = meta + return True + + monkeypatch.setenv("KAFKA_BROKERS", "env-b:9092") + monkeypatch.setenv("ALERTS_TOPIC", "env-topic") + monkeypatch.setattr(alerts, "send_alert", fake_send_alert, raising=True) + + ok = alerts.send_kafka_alert(file_path="/tmp/a.wav", label="car", prob=0.7) + assert ok is True + assert captured["brokers"] == "env-b:9092" + assert captured["topic"] == "env-topic" + assert captured["label"] == "car" + assert captured["probs"] == {"car": 0.7} + assert captured["meta"]["file_path"] == "/tmp/a.wav" + + +def test__delivery_report_logs_ok_and_err(caplog): + # OK case + alerts._delivery_report(None, DummyMsg("t", 0, 1)) + # Error case + class Err: + def __str__(self): return "boom" + alerts._delivery_report(Err(), DummyMsg("t", 0, 2)) + + # We don't assert exact wording, just that both paths logged + assert any("Kafka delivered" in r.message for r in caplog.records) + assert any("Kafka delivery failed" in r.message for r in caplog.records) diff --git a/services/sounds_classifier/tests/test_app.py b/services/sounds_classifier/tests/test_app.py index 154264c1e..6056cf4ef 100644 --- a/services/sounds_classifier/tests/test_app.py +++ b/services/sounds_classifier/tests/test_app.py @@ -1,215 +1,215 @@ -from fastapi.testclient import TestClient -import classification.app as app_mod - -# ----------------------------- -# Helpers / Fakes -# ----------------------------- -class DummyAT: - """Lightweight fake for AudioTagging to let startup warm-up pass.""" - def __init__(self, *a, **k): - pass - def inference(self, x): - # Return something with "embedding" to match warm-up expectations - return {"embedding": [0.0, 0.0]} - -class DummyConn: - """Fake psycopg2 connection used by open_db().""" - def __init__(self): - self.closed = False - self._executed = [] - def cursor(self): - class C: - def __init__(self, outer): - self.outer = outer - def __enter__(self): - return self - def __exit__(self, *a): - return False - def execute(self, *a, **k): - self.outer._executed.append(("EXEC", a, k)) - return C(self) - def commit(self): - self._executed.append(("COMMIT", None, None)) - def rollback(self): - self._executed.append(("ROLLBACK", None, None)) - def close(self): - self.closed = True - -def _patch_startup_and_db(monkeypatch, *, capture): - """ - Patch all heavy/IO dependencies used by app startup and endpoints. - 'capture' is a dict used to collect calls for assertions. - """ - # Avoid heavy model loading - monkeypatch.setattr(app_mod, "AudioTagging", DummyAT, raising=True) - # Pretend pipeline file does not exist -> skip joblib.load - monkeypatch.setattr(app_mod.os.path, "exists", lambda p: False, raising=True) - - # open_db returns DummyConn and we keep the instance in capture - def _open_db(): - conn = DummyConn() - capture["conn"] = conn - return conn - monkeypatch.setattr(app_mod, "open_db", _open_db, raising=True) - - # No-op ensure_run - monkeypatch.setattr(app_mod, "ensure_run", lambda conn, run_id: None, raising=True) - - # Safe defaults for resolve/upsert; specific tests will override if needed - monkeypatch.setattr(app_mod, "resolve_file_id", lambda *a, **k: 123, raising=True) - - def _upsert(conn, payload): - capture.setdefault("upserts", []).append({"conn": conn, "payload": payload}) - monkeypatch.setattr(app_mod, "upsert_file_aggregate", _upsert, raising=True) - - -# ----------------------------- -# Tests -# ----------------------------- -def test_health_ok(monkeypatch): - cap = {} - _patch_startup_and_db(monkeypatch, capture=cap) - # Use context manager so startup/shutdown definitely run - with TestClient(app_mod.app) as client: - r = client.get("/health") - assert r.status_code == 200 - data = r.json() - assert isinstance(data, dict) - assert data.get("ok") is True - # Assert values that reflect startup side effects - assert data.get("pann_loaded") is True - assert data.get("sk_pipeline_loaded") in (True, False) - # DB connection was created - assert cap.get("conn") is not None - -def test_startup_and_shutdown_close_db(monkeypatch): - cap = {} - _patch_startup_and_db(monkeypatch, capture=cap) - # Run inside context to trigger startup+shutdown - with TestClient(app_mod.app) as client: - r = client.get("/health") - assert r.status_code == 200 - # During runtime, connection object is set - assert cap.get("conn") is not None - assert cap["conn"].closed is False - # After shutdown hook ran, global DB_CONN should be None and fake conn closed - assert app_mod.DB_CONN is None - assert cap["conn"].closed is True - -def test_classify_200_success(monkeypatch): - cap = {} - _patch_startup_and_db(monkeypatch, capture=cap) - - # resolve_file_id -> a fixed file_id - monkeypatch.setattr(app_mod, "resolve_file_id", lambda *a, **k: 42, raising=True) - - # classification core returns a rich dict (with extra fields) - import classification.scripts.classify as cls - monkeypatch.setattr( - cls, - "run_classification_job", - lambda **k: { - "label": "car", - "probs": {"car": 0.9, "dog": 0.1}, - "pred_prob": 0.9, - "unknown_threshold": 0.55, - "is_another": False, - "num_windows": 5, - "agg_mode": "mean", - "processing_ms": 123.0, - }, - raising=True - ) - - with TestClient(app_mod.app) as client: - r = client.post("/classify", json={"s3_bucket": "ok", "s3_key": "file.wav", "return_porbs": True}) - assert r.status_code == 200 - body = r.json() - assert body["label"] == "car" - # default return_probs is False -> probs stripped - assert body["probs"] == {"car": 0.9, "dog": 0.1} - - # Verify upsert called with our collected payload - assert len(cap.get("upserts", [])) == 1 - payload = cap["upserts"][0]["payload"] - assert payload["file_id"] == 42 - assert payload["head_pred_label"] == "car" - assert payload["num_windows"] == 5 - assert payload["agg_mode"] == "mean" - assert payload["processing_ms"] == 123.0 - -def test_classify_200_with_return_probs_true(monkeypatch): - cap = {} - _patch_startup_and_db(monkeypatch, capture=cap) - monkeypatch.setattr(app_mod, "resolve_file_id", lambda *a, **k: 88, raising=True) - - import classification.scripts.classify as cls - monkeypatch.setattr( - cls, - "run_classification_job", - lambda **k: {"label": "dog", "probs": {"car": 0.2, "dog": 0.8}}, - raising=True - ) - - with TestClient(app_mod.app) as client: - r = client.post("/classify", json={"s3_bucket": "b", "s3_key": "key.wav", "return_probs": True}) - assert r.status_code == 200 - body = r.json() - assert body["label"] == "dog" - assert body["probs"] == {"car": 0.2, "dog": 0.8} - # ensure upsert invoked - assert len(cap.get("upserts", [])) == 1 - assert cap["upserts"][0]["payload"]["file_id"] == 88 - -def test_classify_404_when_file_missing(monkeypatch): - cap = {} - _patch_startup_and_db(monkeypatch, capture=cap) - # Simulate resolve_file_id failure (file not in public.files) - def _resolve(*a, **k): - raise ValueError("not found") - monkeypatch.setattr(app_mod, "resolve_file_id", _resolve, raising=True) - - with TestClient(app_mod.app) as client: - r = client.post("/classify", json={"s3_bucket": "b", "s3_key": "missing.wav"}) - assert r.status_code == 404 - # No upsert on failure - assert cap.get("upserts", []) == [] - -def test_classify_500_when_core_raises(monkeypatch): - cap = {} - _patch_startup_and_db(monkeypatch, capture=cap) - monkeypatch.setattr(app_mod, "resolve_file_id", lambda *a, **k: 55, raising=True) - - import classification.scripts.classify as cls - def _raiser(**k): - raise RuntimeError("boom") - monkeypatch.setattr(cls, "run_classification_job", _raiser, raising=True) - - with TestClient(app_mod.app) as client: - r = client.post("/classify", json={"s3_bucket": "b", "s3_key": "crash.wav"}) - assert r.status_code == 500 - # No upsert on failure - assert cap.get("upserts", []) == [] - -def test_middleware_executes(monkeypatch): - """ - Hitting endpoints implicitly passes through the timing middleware. - This test mainly ensures middleware path executes without errors - (coverage); assertions are on status only. - """ - cap = {} - _patch_startup_and_db(monkeypatch, capture=cap) - # First pass: just exercise /health - with TestClient(app_mod.app) as client: - r1 = client.get("/health") - assert r1.status_code == 200 - - # Second pass: exercise /classify with a minimal classifier mock - cap = {} - _patch_startup_and_db(monkeypatch, capture=cap) - import classification.scripts.classify as cls - monkeypatch.setattr(cls, "run_classification_job", - lambda **k: {"label": "ok", "probs": {}}, raising=True) - with TestClient(app_mod.app) as client: - r = client.post("/classify", json={"s3_bucket": "b", "s3_key": "k.wav"}) - assert r.status_code == 200 +from fastapi.testclient import TestClient +import classification.app as app_mod + +# ----------------------------- +# Helpers / Fakes +# ----------------------------- +class DummyAT: + """Lightweight fake for AudioTagging to let startup warm-up pass.""" + def __init__(self, *a, **k): + pass + def inference(self, x): + # Return something with "embedding" to match warm-up expectations + return {"embedding": [0.0, 0.0]} + +class DummyConn: + """Fake psycopg2 connection used by open_db().""" + def __init__(self): + self.closed = False + self._executed = [] + def cursor(self): + class C: + def __init__(self, outer): + self.outer = outer + def __enter__(self): + return self + def __exit__(self, *a): + return False + def execute(self, *a, **k): + self.outer._executed.append(("EXEC", a, k)) + return C(self) + def commit(self): + self._executed.append(("COMMIT", None, None)) + def rollback(self): + self._executed.append(("ROLLBACK", None, None)) + def close(self): + self.closed = True + +def _patch_startup_and_db(monkeypatch, *, capture): + """ + Patch all heavy/IO dependencies used by app startup and endpoints. + 'capture' is a dict used to collect calls for assertions. + """ + # Avoid heavy model loading + monkeypatch.setattr(app_mod, "AudioTagging", DummyAT, raising=True) + # Pretend pipeline file does not exist -> skip joblib.load + monkeypatch.setattr(app_mod.os.path, "exists", lambda p: False, raising=True) + + # open_db returns DummyConn and we keep the instance in capture + def _open_db(): + conn = DummyConn() + capture["conn"] = conn + return conn + monkeypatch.setattr(app_mod, "open_db", _open_db, raising=True) + + # No-op ensure_run + monkeypatch.setattr(app_mod, "ensure_run", lambda conn, run_id: None, raising=True) + + # Safe defaults for resolve/upsert; specific tests will override if needed + monkeypatch.setattr(app_mod, "resolve_file_id", lambda *a, **k: 123, raising=True) + + def _upsert(conn, payload): + capture.setdefault("upserts", []).append({"conn": conn, "payload": payload}) + monkeypatch.setattr(app_mod, "upsert_file_aggregate", _upsert, raising=True) + + +# ----------------------------- +# Tests +# ----------------------------- +def test_health_ok(monkeypatch): + cap = {} + _patch_startup_and_db(monkeypatch, capture=cap) + # Use context manager so startup/shutdown definitely run + with TestClient(app_mod.app) as client: + r = client.get("/health") + assert r.status_code == 200 + data = r.json() + assert isinstance(data, dict) + assert data.get("ok") is True + # Assert values that reflect startup side effects + assert data.get("pann_loaded") is True + assert data.get("sk_pipeline_loaded") in (True, False) + # DB connection was created + assert cap.get("conn") is not None + +def test_startup_and_shutdown_close_db(monkeypatch): + cap = {} + _patch_startup_and_db(monkeypatch, capture=cap) + # Run inside context to trigger startup+shutdown + with TestClient(app_mod.app) as client: + r = client.get("/health") + assert r.status_code == 200 + # During runtime, connection object is set + assert cap.get("conn") is not None + assert cap["conn"].closed is False + # After shutdown hook ran, global DB_CONN should be None and fake conn closed + assert app_mod.DB_CONN is None + assert cap["conn"].closed is True + +def test_classify_200_success(monkeypatch): + cap = {} + _patch_startup_and_db(monkeypatch, capture=cap) + + # resolve_file_id -> a fixed file_id + monkeypatch.setattr(app_mod, "resolve_file_id", lambda *a, **k: 42, raising=True) + + # classification core returns a rich dict (with extra fields) + import classification.scripts.classify as cls + monkeypatch.setattr( + cls, + "run_classification_job", + lambda **k: { + "label": "car", + "probs": {"car": 0.9, "dog": 0.1}, + "pred_prob": 0.9, + "unknown_threshold": 0.55, + "is_another": False, + "num_windows": 5, + "agg_mode": "mean", + "processing_ms": 123.0, + }, + raising=True + ) + + with TestClient(app_mod.app) as client: + r = client.post("/classify", json={"s3_bucket": "ok", "s3_key": "file.wav", "return_porbs": True}) + assert r.status_code == 200 + body = r.json() + assert body["label"] == "car" + # default return_probs is False -> probs stripped + assert body["probs"] == {"car": 0.9, "dog": 0.1} + + # Verify upsert called with our collected payload + assert len(cap.get("upserts", [])) == 1 + payload = cap["upserts"][0]["payload"] + assert payload["file_id"] == 42 + assert payload["head_pred_label"] == "car" + assert payload["num_windows"] == 5 + assert payload["agg_mode"] == "mean" + assert payload["processing_ms"] == 123.0 + +def test_classify_200_with_return_probs_true(monkeypatch): + cap = {} + _patch_startup_and_db(monkeypatch, capture=cap) + monkeypatch.setattr(app_mod, "resolve_file_id", lambda *a, **k: 88, raising=True) + + import classification.scripts.classify as cls + monkeypatch.setattr( + cls, + "run_classification_job", + lambda **k: {"label": "dog", "probs": {"car": 0.2, "dog": 0.8}}, + raising=True + ) + + with TestClient(app_mod.app) as client: + r = client.post("/classify", json={"s3_bucket": "b", "s3_key": "key.wav", "return_probs": True}) + assert r.status_code == 200 + body = r.json() + assert body["label"] == "dog" + assert body["probs"] == {"car": 0.2, "dog": 0.8} + # ensure upsert invoked + assert len(cap.get("upserts", [])) == 1 + assert cap["upserts"][0]["payload"]["file_id"] == 88 + +def test_classify_404_when_file_missing(monkeypatch): + cap = {} + _patch_startup_and_db(monkeypatch, capture=cap) + # Simulate resolve_file_id failure (file not in public.files) + def _resolve(*a, **k): + raise ValueError("not found") + monkeypatch.setattr(app_mod, "resolve_file_id", _resolve, raising=True) + + with TestClient(app_mod.app) as client: + r = client.post("/classify", json={"s3_bucket": "b", "s3_key": "missing.wav"}) + assert r.status_code == 404 + # No upsert on failure + assert cap.get("upserts", []) == [] + +def test_classify_500_when_core_raises(monkeypatch): + cap = {} + _patch_startup_and_db(monkeypatch, capture=cap) + monkeypatch.setattr(app_mod, "resolve_file_id", lambda *a, **k: 55, raising=True) + + import classification.scripts.classify as cls + def _raiser(**k): + raise RuntimeError("boom") + monkeypatch.setattr(cls, "run_classification_job", _raiser, raising=True) + + with TestClient(app_mod.app) as client: + r = client.post("/classify", json={"s3_bucket": "b", "s3_key": "crash.wav"}) + assert r.status_code == 500 + # No upsert on failure + assert cap.get("upserts", []) == [] + +def test_middleware_executes(monkeypatch): + """ + Hitting endpoints implicitly passes through the timing middleware. + This test mainly ensures middleware path executes without errors + (coverage); assertions are on status only. + """ + cap = {} + _patch_startup_and_db(monkeypatch, capture=cap) + # First pass: just exercise /health + with TestClient(app_mod.app) as client: + r1 = client.get("/health") + assert r1.status_code == 200 + + # Second pass: exercise /classify with a minimal classifier mock + cap = {} + _patch_startup_and_db(monkeypatch, capture=cap) + import classification.scripts.classify as cls + monkeypatch.setattr(cls, "run_classification_job", + lambda **k: {"label": "ok", "probs": {}}, raising=True) + with TestClient(app_mod.app) as client: + r = client.post("/classify", json={"s3_bucket": "b", "s3_key": "k.wav"}) + assert r.status_code == 200 diff --git a/services/sounds_classifier/tests/test_classify_core.py b/services/sounds_classifier/tests/test_classify_core.py index 3ccace665..8c9423af3 100644 --- a/services/sounds_classifier/tests/test_classify_core.py +++ b/services/sounds_classifier/tests/test_classify_core.py @@ -1,262 +1,262 @@ -import numpy as np -from pathlib import Path -import classification.scripts.classify as c - - -# ---- Helpers ---- -class DummyHead: - def __init__(self, classes): - self.classes_ = classes - self._probas = None - def set_out(self, arr): - self._probas = arr - def predict_proba(self, X): - n = X.shape[0] - return np.tile(self._probas, (n, 1)) - -def _reset_runtime(): - c.R = c._Runtime() - -def _to_dict_result(res): - """Normalize classifier outputs to a dict {label, probs} for tests.""" - if isinstance(res, tuple): - label, probs = res - return {"label": label, "probs": probs} - return res - - -# ---- Core classification flow & validations ---- -def test_classify_file_unknown_threshold(monkeypatch): - _reset_runtime() - c.R.model = object() - head = DummyHead(classes=["car", "dog"]) - head.set_out(np.array([0.51, 0.49], dtype=np.float32)) - c.R.head = head - c.R.classes = head.classes_ - - monkeypatch.setattr(c, "load_audio", lambda p, sr: np.ones(16000, dtype=np.float32), raising=True) - # one window: shape (1, 16000) - monkeypatch.setattr(c, "segment_waveform_2d_view", - lambda *a, **k: np.ones((1, 16000), dtype=np.float32), - raising=True) - monkeypatch.setattr( - c, - "run_cnn14_embeddings_batch", - lambda _model, windows, batch_size=32: np.tile(np.array([[1, 2, 3, 4]], dtype=np.float32), (windows.shape[0], 1)), - raising=True, - ) - result = _to_dict_result(c.classify_file("dummy.wav")) - assert result["label"] in ("car", "another") - assert set(result["probs"].keys()) == {"car", "dog"} - - -def test__aggregate_probs_rejects_bad_ndim(): - x = np.array([0.1, 0.9], dtype=np.float32) # 1-D - try: - c._aggregate_probs(x) - assert False, "Expected ValueError for 1-D array" - except ValueError as e: - assert "expected shape" in str(e) - - -def test__aggregate_probs_empty_windows_returns_zeros(): - x = np.zeros((0, 3), dtype=np.float32) - out = c._aggregate_probs(x) - assert out.shape == (3,) - assert np.allclose(out, 0.0) - - -def test_classify_file_returns_another_when_no_segments(monkeypatch): - _reset_runtime() - c.R.model = object() - - class Head: - def __init__(self): self.classes_ = ["car", "dog"] - def predict_proba(self, X): return np.zeros((X.shape[0], 2), dtype=np.float32) - - c.R.head = Head() - c.R.classes = ["car", "dog"] - - monkeypatch.setattr(c, "load_audio", lambda p, sr: np.ones(16000, dtype=np.float32), raising=True) - # zero windows: shape (0, 16000) - monkeypatch.setattr(c, "segment_waveform_2d_view", - lambda *a, **k: np.zeros((0, 16000), dtype=np.float32), - raising=True) - - result = _to_dict_result(c.classify_file("dummy.wav")) - assert result["label"] == "another" - assert set(result["probs"].keys()) == {"car", "dog"} - - -def test_classify_file_with_agg_max(monkeypatch): - _reset_runtime() - old_agg = c.AGG - c.AGG = "max" - try: - c.R.model = object() - - class Head: - def __init__(self): self.classes_ = ["a", "b"] - def predict_proba(self, X): - # pretend we got two windows → choose element-wise max - return np.array([[0.2, 0.8], [0.6, 0.4]], dtype=np.float32) - - c.R.head = Head() - c.R.classes = ["a", "b"] - - monkeypatch.setattr(c, "load_audio", lambda p, sr: np.ones(2 * 16000, dtype=np.float32), raising=True) - # two windows: shape (2, 16000) - monkeypatch.setattr(c, "segment_waveform_2d_view", - lambda *a, **k: np.ones((2, 16000), dtype=np.float32), - raising=True) - monkeypatch.setattr( - c, - "run_cnn14_embeddings_batch", - lambda _model, windows, batch_size=32: np.tile(np.array([[1, 2, 3, 4]], dtype=np.float32), (windows.shape[0], 1)), - raising=True, - ) - result = _to_dict_result(c.classify_file("x.wav")) - assert set(result["probs"].keys()) == {"a", "b"} - assert np.isclose(result["probs"]["a"], 0.6) or np.isclose(result["probs"]["b"], 0.8) - finally: - c.AGG = old_agg - - -def test_run_classification_job_happy_path(monkeypatch, tmp_path): - _reset_runtime() - - class Stat: size = 10; content_type = "audio/wav" - class Client: - def stat_object(self, b, k): return Stat() - def fget_object(self, b, k, dst): Path(dst).write_bytes(b"RIFF") - - monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) - - c.KAFKA_BROKERS, c.ALERTS_TOPIC = "", "dev-robot-alerts" - monkeypatch.setattr(c.alerts, "send_alert", lambda **kw: None, raising=True) - - c.R.model = object() - head = DummyHead(classes=["car", "dog"]); head.set_out(np.array([0.6, 0.4], dtype=np.float32)) - c.R.head = head; c.R.classes = head.classes_ - - monkeypatch.setattr(c, "load_audio", lambda p, sr: np.ones(16000, dtype=np.float32), raising=True) - monkeypatch.setattr(c, "segment_waveform_2d_view", - lambda *a, **k: np.ones((1, 16000), dtype=np.float32), - raising=True) - monkeypatch.setattr( - c, - "run_cnn14_embeddings_batch", - lambda _model, windows, batch_size=32: np.tile(np.array([[1, 2, 3, 4]], dtype=np.float32), (windows.shape[0], 1)), - raising=True, - ) - - out = _to_dict_result(c.run_classification_job(s3_bucket="b", s3_key="k.wav")) - assert out["label"] in ("car", "another") - assert "probs" in out and isinstance(out["probs"], dict) - - -def test_run_classification_job_bucket_not_allowed(): - _reset_runtime() - c.R.head = object() - old = c.ALLOWED_BUCKETS - c.ALLOWED_BUCKETS = ["only-this-bucket"] - try: - try: - _ = c.run_classification_job(s3_bucket="not-allowed", s3_key="a.wav") - assert False, "Expected RuntimeError for disallowed bucket" - except RuntimeError as e: - assert "not allowed" in str(e) - finally: - c.ALLOWED_BUCKETS = old - - -def test_run_classification_job_rejects_content_type(monkeypatch): - _reset_runtime() - c.R.head = object() - c.ALLOWED_BUCKETS = [] - old_types = c.ALLOWED_CONTENT_TYPES - c.ALLOWED_CONTENT_TYPES = ["audio/wav"] - - class Stat: size = 1024; content_type = "text/plain" - class Client: - def stat_object(self, b, k): return Stat() - def fget_object(self, b, k, dst): Path(dst).write_bytes(b"RIFF") - - monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) - - try: - _ = c.run_classification_job(s3_bucket="ok", s3_key="a.wav") - assert False, "Expected RuntimeError for unsupported content-type" - except RuntimeError as e: - assert "Unsupported content-type" in str(e) - finally: - c.ALLOWED_CONTENT_TYPES = old_types - - -def test_run_classification_job_rejects_size(monkeypatch): - _reset_runtime() - c.R.head = object() - c.ALLOWED_BUCKETS = [] - old_max = c.MAX_BYTES; c.MAX_BYTES = 10 - - class Stat: size = 11; content_type = "audio/wav" - class Client: - def stat_object(self, b, k): return Stat() - def fget_object(self, b, k, dst): Path(dst).write_bytes(b"RIFF") - - monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) - - try: - _ = c.run_classification_job(s3_bucket="ok", s3_key="a.wav") - assert False, "Expected RuntimeError for object too large" - except RuntimeError as e: - assert "Object too large" in str(e) - finally: - c.MAX_BYTES = old_max - - -def test_run_classification_job_s3error_fails_fast(monkeypatch): - _reset_runtime() - c.R.head = object() - c.ALLOWED_BUCKETS = [] - - class S3Err(Exception): pass - monkeypatch.setattr(c, "S3Error", S3Err, raising=True) - - class Client: - def stat_object(self, b, k): raise S3Err("boom") - def fget_object(self, b, k, dst): raise AssertionError("should not be called") - - monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) - - try: - _ = c.run_classification_job(s3_bucket="ok", s3_key="a.wav") - assert False, "Expected RuntimeError wrapping S3 failure" - except RuntimeError as e: - assert "S3 stat failed" in str(e) - - -def test_run_classification_job_adds_wav_suffix_when_missing(monkeypatch): - _reset_runtime() - c.R.head = object() - c.R.classes = ["car", "dog"] - c.ALLOWED_BUCKETS = [] - - class Stat: size = 100; content_type = "audio/wav" - observed = {"ext": None} - - class Client: - def stat_object(self, b, k): return Stat() - def fget_object(self, b, k, dst): - observed["ext"] = Path(dst).suffix - Path(dst).write_bytes(b"RIFF") - - monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) - monkeypatch.setattr(c, "classify_file", - lambda p, **_: {"label": "another", "probs": {"car": 0.0, "dog": 0.0}}, - raising=True) - monkeypatch.setattr(c.os, "remove", lambda p: None, raising=True) - - out = _to_dict_result(c.run_classification_job(s3_bucket="ok", s3_key="noext")) - assert out["label"] in ("another", "car", "dog") - assert observed["ext"] == ".wav" +import numpy as np +from pathlib import Path +import classification.scripts.classify as c + + +# ---- Helpers ---- +class DummyHead: + def __init__(self, classes): + self.classes_ = classes + self._probas = None + def set_out(self, arr): + self._probas = arr + def predict_proba(self, X): + n = X.shape[0] + return np.tile(self._probas, (n, 1)) + +def _reset_runtime(): + c.R = c._Runtime() + +def _to_dict_result(res): + """Normalize classifier outputs to a dict {label, probs} for tests.""" + if isinstance(res, tuple): + label, probs = res + return {"label": label, "probs": probs} + return res + + +# ---- Core classification flow & validations ---- +def test_classify_file_unknown_threshold(monkeypatch): + _reset_runtime() + c.R.model = object() + head = DummyHead(classes=["car", "dog"]) + head.set_out(np.array([0.51, 0.49], dtype=np.float32)) + c.R.head = head + c.R.classes = head.classes_ + + monkeypatch.setattr(c, "load_audio", lambda p, sr: np.ones(16000, dtype=np.float32), raising=True) + # one window: shape (1, 16000) + monkeypatch.setattr(c, "segment_waveform_2d_view", + lambda *a, **k: np.ones((1, 16000), dtype=np.float32), + raising=True) + monkeypatch.setattr( + c, + "run_cnn14_embeddings_batch", + lambda _model, windows, batch_size=32: np.tile(np.array([[1, 2, 3, 4]], dtype=np.float32), (windows.shape[0], 1)), + raising=True, + ) + result = _to_dict_result(c.classify_file("dummy.wav")) + assert result["label"] in ("car", "another") + assert set(result["probs"].keys()) == {"car", "dog"} + + +def test__aggregate_probs_rejects_bad_ndim(): + x = np.array([0.1, 0.9], dtype=np.float32) # 1-D + try: + c._aggregate_probs(x) + assert False, "Expected ValueError for 1-D array" + except ValueError as e: + assert "expected shape" in str(e) + + +def test__aggregate_probs_empty_windows_returns_zeros(): + x = np.zeros((0, 3), dtype=np.float32) + out = c._aggregate_probs(x) + assert out.shape == (3,) + assert np.allclose(out, 0.0) + + +def test_classify_file_returns_another_when_no_segments(monkeypatch): + _reset_runtime() + c.R.model = object() + + class Head: + def __init__(self): self.classes_ = ["car", "dog"] + def predict_proba(self, X): return np.zeros((X.shape[0], 2), dtype=np.float32) + + c.R.head = Head() + c.R.classes = ["car", "dog"] + + monkeypatch.setattr(c, "load_audio", lambda p, sr: np.ones(16000, dtype=np.float32), raising=True) + # zero windows: shape (0, 16000) + monkeypatch.setattr(c, "segment_waveform_2d_view", + lambda *a, **k: np.zeros((0, 16000), dtype=np.float32), + raising=True) + + result = _to_dict_result(c.classify_file("dummy.wav")) + assert result["label"] == "another" + assert set(result["probs"].keys()) == {"car", "dog"} + + +def test_classify_file_with_agg_max(monkeypatch): + _reset_runtime() + old_agg = c.AGG + c.AGG = "max" + try: + c.R.model = object() + + class Head: + def __init__(self): self.classes_ = ["a", "b"] + def predict_proba(self, X): + # pretend we got two windows → choose element-wise max + return np.array([[0.2, 0.8], [0.6, 0.4]], dtype=np.float32) + + c.R.head = Head() + c.R.classes = ["a", "b"] + + monkeypatch.setattr(c, "load_audio", lambda p, sr: np.ones(2 * 16000, dtype=np.float32), raising=True) + # two windows: shape (2, 16000) + monkeypatch.setattr(c, "segment_waveform_2d_view", + lambda *a, **k: np.ones((2, 16000), dtype=np.float32), + raising=True) + monkeypatch.setattr( + c, + "run_cnn14_embeddings_batch", + lambda _model, windows, batch_size=32: np.tile(np.array([[1, 2, 3, 4]], dtype=np.float32), (windows.shape[0], 1)), + raising=True, + ) + result = _to_dict_result(c.classify_file("x.wav")) + assert set(result["probs"].keys()) == {"a", "b"} + assert np.isclose(result["probs"]["a"], 0.6) or np.isclose(result["probs"]["b"], 0.8) + finally: + c.AGG = old_agg + + +def test_run_classification_job_happy_path(monkeypatch, tmp_path): + _reset_runtime() + + class Stat: size = 10; content_type = "audio/wav" + class Client: + def stat_object(self, b, k): return Stat() + def fget_object(self, b, k, dst): Path(dst).write_bytes(b"RIFF") + + monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) + + c.KAFKA_BROKERS, c.ALERTS_TOPIC = "", "dev-robot-alerts" + monkeypatch.setattr(c.alerts, "send_alert", lambda **kw: None, raising=True) + + c.R.model = object() + head = DummyHead(classes=["car", "dog"]); head.set_out(np.array([0.6, 0.4], dtype=np.float32)) + c.R.head = head; c.R.classes = head.classes_ + + monkeypatch.setattr(c, "load_audio", lambda p, sr: np.ones(16000, dtype=np.float32), raising=True) + monkeypatch.setattr(c, "segment_waveform_2d_view", + lambda *a, **k: np.ones((1, 16000), dtype=np.float32), + raising=True) + monkeypatch.setattr( + c, + "run_cnn14_embeddings_batch", + lambda _model, windows, batch_size=32: np.tile(np.array([[1, 2, 3, 4]], dtype=np.float32), (windows.shape[0], 1)), + raising=True, + ) + + out = _to_dict_result(c.run_classification_job(s3_bucket="b", s3_key="k.wav")) + assert out["label"] in ("car", "another") + assert "probs" in out and isinstance(out["probs"], dict) + + +def test_run_classification_job_bucket_not_allowed(): + _reset_runtime() + c.R.head = object() + old = c.ALLOWED_BUCKETS + c.ALLOWED_BUCKETS = ["only-this-bucket"] + try: + try: + _ = c.run_classification_job(s3_bucket="not-allowed", s3_key="a.wav") + assert False, "Expected RuntimeError for disallowed bucket" + except RuntimeError as e: + assert "not allowed" in str(e) + finally: + c.ALLOWED_BUCKETS = old + + +def test_run_classification_job_rejects_content_type(monkeypatch): + _reset_runtime() + c.R.head = object() + c.ALLOWED_BUCKETS = [] + old_types = c.ALLOWED_CONTENT_TYPES + c.ALLOWED_CONTENT_TYPES = ["audio/wav"] + + class Stat: size = 1024; content_type = "text/plain" + class Client: + def stat_object(self, b, k): return Stat() + def fget_object(self, b, k, dst): Path(dst).write_bytes(b"RIFF") + + monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) + + try: + _ = c.run_classification_job(s3_bucket="ok", s3_key="a.wav") + assert False, "Expected RuntimeError for unsupported content-type" + except RuntimeError as e: + assert "Unsupported content-type" in str(e) + finally: + c.ALLOWED_CONTENT_TYPES = old_types + + +def test_run_classification_job_rejects_size(monkeypatch): + _reset_runtime() + c.R.head = object() + c.ALLOWED_BUCKETS = [] + old_max = c.MAX_BYTES; c.MAX_BYTES = 10 + + class Stat: size = 11; content_type = "audio/wav" + class Client: + def stat_object(self, b, k): return Stat() + def fget_object(self, b, k, dst): Path(dst).write_bytes(b"RIFF") + + monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) + + try: + _ = c.run_classification_job(s3_bucket="ok", s3_key="a.wav") + assert False, "Expected RuntimeError for object too large" + except RuntimeError as e: + assert "Object too large" in str(e) + finally: + c.MAX_BYTES = old_max + + +def test_run_classification_job_s3error_fails_fast(monkeypatch): + _reset_runtime() + c.R.head = object() + c.ALLOWED_BUCKETS = [] + + class S3Err(Exception): pass + monkeypatch.setattr(c, "S3Error", S3Err, raising=True) + + class Client: + def stat_object(self, b, k): raise S3Err("boom") + def fget_object(self, b, k, dst): raise AssertionError("should not be called") + + monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) + + try: + _ = c.run_classification_job(s3_bucket="ok", s3_key="a.wav") + assert False, "Expected RuntimeError wrapping S3 failure" + except RuntimeError as e: + assert "S3 stat failed" in str(e) + + +def test_run_classification_job_adds_wav_suffix_when_missing(monkeypatch): + _reset_runtime() + c.R.head = object() + c.R.classes = ["car", "dog"] + c.ALLOWED_BUCKETS = [] + + class Stat: size = 100; content_type = "audio/wav" + observed = {"ext": None} + + class Client: + def stat_object(self, b, k): return Stat() + def fget_object(self, b, k, dst): + observed["ext"] = Path(dst).suffix + Path(dst).write_bytes(b"RIFF") + + monkeypatch.setattr(c, "_get_minio", lambda: Client(), raising=True) + monkeypatch.setattr(c, "classify_file", + lambda p, **_: {"label": "another", "probs": {"car": 0.0, "dog": 0.0}}, + raising=True) + monkeypatch.setattr(c.os, "remove", lambda p: None, raising=True) + + out = _to_dict_result(c.run_classification_job(s3_bucket="ok", s3_key="noext")) + assert out["label"] in ("another", "car", "dog") + assert observed["ext"] == ".wav" diff --git a/services/sounds_classifier/tests/test_classify_head_loading.py b/services/sounds_classifier/tests/test_classify_head_loading.py index 2769dd620..60064879c 100644 --- a/services/sounds_classifier/tests/test_classify_head_loading.py +++ b/services/sounds_classifier/tests/test_classify_head_loading.py @@ -1,142 +1,142 @@ -import json -import numpy as np -import classification.scripts.classify as c - - -def _reset_runtime(): - c.R = c._Runtime() - - -def test__load_backbone_once_calls_loader(monkeypatch): - _reset_runtime() - old = c.BACKBONE - try: - c.BACKBONE = "cnn14" - called = {"ok": False} - def fake_loader(checkpoint_path=None, device="cpu", checkpoint_url=None): - called["ok"] = True - return object() - monkeypatch.setattr(c, "load_cnn14_model", fake_loader, raising=True) - c._load_backbone_once() - assert called["ok"] is True and c.R.model is not None - # Second call should be a no-op - called["ok"] = False - c._load_backbone_once() - assert called["ok"] is False - finally: - c.BACKBONE = old - - -def test__load_backbone_once_rejects_non_cnn14(): - _reset_runtime() - old = c.BACKBONE - try: - c.BACKBONE = "something-else" - try: - c._load_backbone_once() - assert False, "Expected RuntimeError for unsupported backbone" - except RuntimeError as e: - assert "Only BACKBONE=cnn14" in str(e) - finally: - c.BACKBONE = old - - -def test__load_head_once_requires_head(): - _reset_runtime() - old = c.HEAD_PATH - try: - c.HEAD_PATH = "" - try: - c._load_head_once() - assert False, "Expected RuntimeError when HEAD env/path is missing" - except RuntimeError as e: - assert "HEAD env var is required" in str(e) - finally: - c.HEAD_PATH = old - - -def test__load_head_once_uses_labels_csv(monkeypatch): - _reset_runtime() - - class DummyHead: - def __init__(self): - self.classes_ = ["x", "y"] - def predict_proba(self, X): - return np.zeros((X.shape[0], 2), dtype=np.float32) - - c.HEAD_PATH = "dummy.joblib" - monkeypatch.setattr(c.joblib, "load", lambda _: DummyHead(), raising=True) - - monkeypatch.setenv("LABELS_CSV", "labels.csv") - import classification.core.model_io as mio - # Important: raising=False because the attribute doesn't exist in the real module - monkeypatch.setattr(mio, "load_labels_from_csv", lambda _: ["car", "dog"], raising=False) - - c._load_head_once() - assert c.R.head is not None - assert c.R.classes == ["car", "dog"] - monkeypatch.delenv("LABELS_CSV", raising=False) - - -def test__load_head_once_fallback_to_head_classes(monkeypatch): - _reset_runtime() - - class DummyHead: - def __init__(self): - self.classes_ = ["cat", "plane"] - def predict_proba(self, X): - return np.zeros((X.shape[0], 2), dtype=np.float32) - - c.HEAD_PATH = "dummy.joblib" - monkeypatch.setattr(c.joblib, "load", lambda _: DummyHead(), raising=True) - monkeypatch.delenv("LABELS_CSV", raising=False) - monkeypatch.setenv("HEAD_META", "does_not_exist.json") - - c._load_head_once() - assert c.R.head is not None - assert c.R.classes == ["cat", "plane"] - - -def test__load_head_once_uses_meta_with_indexed_classes(monkeypatch, tmp_path): - _reset_runtime() - - class DummyHeadInt: - def __init__(self): - self.classes_ = [0, 1] - def predict_proba(self, X): - return np.zeros((X.shape[0], 2), dtype=np.float32) - - c.HEAD_PATH = "dummy.joblib" - monkeypatch.setattr(c.joblib, "load", lambda _: DummyHeadInt(), raising=True) - - meta_path = tmp_path / "head_meta.json" - meta_path.write_text(json.dumps({"class_order": ["engine", "bird"]}), encoding="utf-8") - monkeypatch.setenv("HEAD_META", str(meta_path)) - monkeypatch.delenv("LABELS_CSV", raising=False) - - c._load_head_once() - assert c.R.classes == ["engine", "bird"] - - -def test__load_head_once_meta_length_mismatch_raises(monkeypatch, tmp_path): - _reset_runtime() - - class DummyHeadInt: - def __init__(self): - self.classes_ = [0, 1] - def predict_proba(self, X): - return np.zeros((X.shape[0], 2), dtype=np.float32) - - c.HEAD_PATH = "dummy.joblib" - monkeypatch.setattr(c.joblib, "load", lambda _: DummyHeadInt(), raising=True) - - meta_path = tmp_path / "bad_meta.json" - meta_path.write_text(json.dumps({"class_order": ["only-one"]}), encoding="utf-8") - monkeypatch.setenv("HEAD_META", str(meta_path)) - monkeypatch.delenv("LABELS_CSV", raising=False) - - try: - c._load_head_once() - assert False, "Expected RuntimeError for meta length mismatch" - except RuntimeError as e: - assert "class_order length" in str(e) +import json +import numpy as np +import classification.scripts.classify as c + + +def _reset_runtime(): + c.R = c._Runtime() + + +def test__load_backbone_once_calls_loader(monkeypatch): + _reset_runtime() + old = c.BACKBONE + try: + c.BACKBONE = "cnn14" + called = {"ok": False} + def fake_loader(checkpoint_path=None, device="cpu", checkpoint_url=None): + called["ok"] = True + return object() + monkeypatch.setattr(c, "load_cnn14_model", fake_loader, raising=True) + c._load_backbone_once() + assert called["ok"] is True and c.R.model is not None + # Second call should be a no-op + called["ok"] = False + c._load_backbone_once() + assert called["ok"] is False + finally: + c.BACKBONE = old + + +def test__load_backbone_once_rejects_non_cnn14(): + _reset_runtime() + old = c.BACKBONE + try: + c.BACKBONE = "something-else" + try: + c._load_backbone_once() + assert False, "Expected RuntimeError for unsupported backbone" + except RuntimeError as e: + assert "Only BACKBONE=cnn14" in str(e) + finally: + c.BACKBONE = old + + +def test__load_head_once_requires_head(): + _reset_runtime() + old = c.HEAD_PATH + try: + c.HEAD_PATH = "" + try: + c._load_head_once() + assert False, "Expected RuntimeError when HEAD env/path is missing" + except RuntimeError as e: + assert "HEAD env var is required" in str(e) + finally: + c.HEAD_PATH = old + + +def test__load_head_once_uses_labels_csv(monkeypatch): + _reset_runtime() + + class DummyHead: + def __init__(self): + self.classes_ = ["x", "y"] + def predict_proba(self, X): + return np.zeros((X.shape[0], 2), dtype=np.float32) + + c.HEAD_PATH = "dummy.joblib" + monkeypatch.setattr(c.joblib, "load", lambda _: DummyHead(), raising=True) + + monkeypatch.setenv("LABELS_CSV", "labels.csv") + import classification.core.model_io as mio + # Important: raising=False because the attribute doesn't exist in the real module + monkeypatch.setattr(mio, "load_labels_from_csv", lambda _: ["car", "dog"], raising=False) + + c._load_head_once() + assert c.R.head is not None + assert c.R.classes == ["car", "dog"] + monkeypatch.delenv("LABELS_CSV", raising=False) + + +def test__load_head_once_fallback_to_head_classes(monkeypatch): + _reset_runtime() + + class DummyHead: + def __init__(self): + self.classes_ = ["cat", "plane"] + def predict_proba(self, X): + return np.zeros((X.shape[0], 2), dtype=np.float32) + + c.HEAD_PATH = "dummy.joblib" + monkeypatch.setattr(c.joblib, "load", lambda _: DummyHead(), raising=True) + monkeypatch.delenv("LABELS_CSV", raising=False) + monkeypatch.setenv("HEAD_META", "does_not_exist.json") + + c._load_head_once() + assert c.R.head is not None + assert c.R.classes == ["cat", "plane"] + + +def test__load_head_once_uses_meta_with_indexed_classes(monkeypatch, tmp_path): + _reset_runtime() + + class DummyHeadInt: + def __init__(self): + self.classes_ = [0, 1] + def predict_proba(self, X): + return np.zeros((X.shape[0], 2), dtype=np.float32) + + c.HEAD_PATH = "dummy.joblib" + monkeypatch.setattr(c.joblib, "load", lambda _: DummyHeadInt(), raising=True) + + meta_path = tmp_path / "head_meta.json" + meta_path.write_text(json.dumps({"class_order": ["engine", "bird"]}), encoding="utf-8") + monkeypatch.setenv("HEAD_META", str(meta_path)) + monkeypatch.delenv("LABELS_CSV", raising=False) + + c._load_head_once() + assert c.R.classes == ["engine", "bird"] + + +def test__load_head_once_meta_length_mismatch_raises(monkeypatch, tmp_path): + _reset_runtime() + + class DummyHeadInt: + def __init__(self): + self.classes_ = [0, 1] + def predict_proba(self, X): + return np.zeros((X.shape[0], 2), dtype=np.float32) + + c.HEAD_PATH = "dummy.joblib" + monkeypatch.setattr(c.joblib, "load", lambda _: DummyHeadInt(), raising=True) + + meta_path = tmp_path / "bad_meta.json" + meta_path.write_text(json.dumps({"class_order": ["only-one"]}), encoding="utf-8") + monkeypatch.setenv("HEAD_META", str(meta_path)) + monkeypatch.delenv("LABELS_CSV", raising=False) + + try: + c._load_head_once() + assert False, "Expected RuntimeError for meta length mismatch" + except RuntimeError as e: + assert "class_order length" in str(e) diff --git a/services/sounds_classifier/tests/test_cnn14.py b/services/sounds_classifier/tests/test_cnn14.py index 742810377..44330e533 100644 --- a/services/sounds_classifier/tests/test_cnn14.py +++ b/services/sounds_classifier/tests/test_cnn14.py @@ -1,111 +1,111 @@ -import numpy as np -import types -import builtins -import pytest -import classification.backbones.cnn14 as cnn14 -from classification.backbones.cnn14 import run_cnn14_embeddings_batch -from classification.core.model_io import segment_waveform_2d_view, SAMPLE_RATE - -class DummyAT: - def __init__(self, checkpoint_path: str, device: str = "cpu"): - self.checkpoint_path = checkpoint_path - self.device = device - def inference(self, wav): - # Return (dummy_probs, dummy_embedding) - emb = np.ones((1, 2048), dtype=np.float32) - return (None, emb) - -class DummyATTuple: - def inference(self, x): - # x: (N, samples) - N = x.shape[0] - emb_dim = 8 - scores = np.zeros((N, 10), dtype=np.float32) # unused - embs = np.arange(N * emb_dim, dtype=np.float32).reshape(N, emb_dim) - return (scores, embs) - -class DummyATDict: - def inference(self, x): - N = x.shape[0] - emb_dim = 16 - return {"embedding": np.ones((N, emb_dim), dtype=np.float32)} - -def test_load_cnn14_model_uses_ensure_checkpoint(monkeypatch, tmp_path): - ckpt = tmp_path / "m.pth" - def fake_ensure(path, url): - ckpt.write_bytes(b"dummy") - return str(ckpt) - monkeypatch.setattr(cnn14, "ensure_checkpoint", fake_ensure) - # Mock panns_inference.AudioTagging - monkeypatch.setattr(cnn14, "AudioTagging", DummyAT, raising=True) - - m = cnn14.load_cnn14_model(checkpoint_path=str(ckpt), device="cpu") - assert isinstance(m, DummyAT) - assert m.checkpoint_path == str(ckpt) - -def test_run_cnn14_embedding_happy_path(monkeypatch): - dummy = DummyAT("x") - x = np.random.randn(32000).astype(np.float32) - e = cnn14.run_cnn14_embedding(dummy, x) - assert e.shape == (2048,) - -def test_run_cnn14_embedding_empty_raises(monkeypatch): - dummy = DummyAT("x") - with pytest.raises(ValueError): - cnn14.run_cnn14_embedding(dummy, np.array([], dtype=np.float32)) - - -def test_run_cnn14_embeddings_batch_tuple_output(monkeypatch): - model = DummyATTuple() - # Prevent flattening of (N, D) to (N*D,) - monkeypatch.setattr(cnn14, "_to_numpy", - lambda x: np.asarray(x, dtype=np.float32), - raising=True) - - windows = np.ones((5, 32000), dtype=np.float32) - E = run_cnn14_embeddings_batch(model, windows, batch_size=2) - assert E.shape == (5, 8) - assert np.allclose(E[1], np.arange(8, 16, dtype=np.float32)) - -def test_run_cnn14_embeddings_batch_dict_output(monkeypatch): - model = DummyATDict() - # Prevent flattening of (N, D) to (N*D,) - monkeypatch.setattr(cnn14, "_to_numpy", - lambda x: np.asarray(x, dtype=np.float32), - raising=True) - windows = np.ones((3, 16000), dtype=np.float32) - E = run_cnn14_embeddings_batch(model, windows, batch_size=32) - assert E.shape == (3, 16) - assert np.allclose(E, 1.0) - -def test_segment_waveform_2d_basic_exact_fit(): - sr = SAMPLE_RATE - win_s = 1.0 - hop_s = 0.75 - wav = np.ones(int(sr * 1.6), dtype=np.float32) - segs = segment_waveform_2d_view(wav, sr=sr, window_sec=win_s, hop_sec=hop_s, pad_last=False) - # Expect exactly one full window: [0..1.0] - assert segs.shape[0] == 1 - assert segs.shape[1] == int(sr * win_s) - # No padding is expected when pad_last=False - -def test_segment_waveform_2d_pad_last(): - sr = SAMPLE_RATE - win_s = 1.0 - hop_s = 0.75 - wav = np.ones(int(sr * 1.6), dtype=np.float32) - segs = segment_waveform_2d_view(wav, sr=sr, window_sec=win_s, hop_sec=hop_s, pad_last=True) - # Expect one full window + one padded tail window → total 2 - assert segs.shape[0] == 2 - assert segs.shape[1] == int(sr * win_s) - assert np.any(segs[-1] == 0.0) - -def test_segment_waveform_2d_empty_input_returns_empty_or_padded(): - sr = SAMPLE_RATE - segs_no_pad = segment_waveform_2d_view(np.zeros(0, dtype=np.float32), sr=sr, - window_sec=1.0, hop_sec=0.5, pad_last=False) - assert segs_no_pad.shape == (0, int(sr * 1.0)) - segs_pad = segment_waveform_2d_view(np.zeros(0, dtype=np.float32), sr=sr, - window_sec=1.0, hop_sec=0.5, pad_last=True) - # Current impl returns 0 windows even with pad_last for empty input - assert segs_pad.shape == (0, int(sr * 1.0)) +import numpy as np +import types +import builtins +import pytest +import classification.backbones.cnn14 as cnn14 +from classification.backbones.cnn14 import run_cnn14_embeddings_batch +from classification.core.model_io import segment_waveform_2d_view, SAMPLE_RATE + +class DummyAT: + def __init__(self, checkpoint_path: str, device: str = "cpu"): + self.checkpoint_path = checkpoint_path + self.device = device + def inference(self, wav): + # Return (dummy_probs, dummy_embedding) + emb = np.ones((1, 2048), dtype=np.float32) + return (None, emb) + +class DummyATTuple: + def inference(self, x): + # x: (N, samples) + N = x.shape[0] + emb_dim = 8 + scores = np.zeros((N, 10), dtype=np.float32) # unused + embs = np.arange(N * emb_dim, dtype=np.float32).reshape(N, emb_dim) + return (scores, embs) + +class DummyATDict: + def inference(self, x): + N = x.shape[0] + emb_dim = 16 + return {"embedding": np.ones((N, emb_dim), dtype=np.float32)} + +def test_load_cnn14_model_uses_ensure_checkpoint(monkeypatch, tmp_path): + ckpt = tmp_path / "m.pth" + def fake_ensure(path, url): + ckpt.write_bytes(b"dummy") + return str(ckpt) + monkeypatch.setattr(cnn14, "ensure_checkpoint", fake_ensure) + # Mock panns_inference.AudioTagging + monkeypatch.setattr(cnn14, "AudioTagging", DummyAT, raising=True) + + m = cnn14.load_cnn14_model(checkpoint_path=str(ckpt), device="cpu") + assert isinstance(m, DummyAT) + assert m.checkpoint_path == str(ckpt) + +def test_run_cnn14_embedding_happy_path(monkeypatch): + dummy = DummyAT("x") + x = np.random.randn(32000).astype(np.float32) + e = cnn14.run_cnn14_embedding(dummy, x) + assert e.shape == (2048,) + +def test_run_cnn14_embedding_empty_raises(monkeypatch): + dummy = DummyAT("x") + with pytest.raises(ValueError): + cnn14.run_cnn14_embedding(dummy, np.array([], dtype=np.float32)) + + +def test_run_cnn14_embeddings_batch_tuple_output(monkeypatch): + model = DummyATTuple() + # Prevent flattening of (N, D) to (N*D,) + monkeypatch.setattr(cnn14, "_to_numpy", + lambda x: np.asarray(x, dtype=np.float32), + raising=True) + + windows = np.ones((5, 32000), dtype=np.float32) + E = run_cnn14_embeddings_batch(model, windows, batch_size=2) + assert E.shape == (5, 8) + assert np.allclose(E[1], np.arange(8, 16, dtype=np.float32)) + +def test_run_cnn14_embeddings_batch_dict_output(monkeypatch): + model = DummyATDict() + # Prevent flattening of (N, D) to (N*D,) + monkeypatch.setattr(cnn14, "_to_numpy", + lambda x: np.asarray(x, dtype=np.float32), + raising=True) + windows = np.ones((3, 16000), dtype=np.float32) + E = run_cnn14_embeddings_batch(model, windows, batch_size=32) + assert E.shape == (3, 16) + assert np.allclose(E, 1.0) + +def test_segment_waveform_2d_basic_exact_fit(): + sr = SAMPLE_RATE + win_s = 1.0 + hop_s = 0.75 + wav = np.ones(int(sr * 1.6), dtype=np.float32) + segs = segment_waveform_2d_view(wav, sr=sr, window_sec=win_s, hop_sec=hop_s, pad_last=False) + # Expect exactly one full window: [0..1.0] + assert segs.shape[0] == 1 + assert segs.shape[1] == int(sr * win_s) + # No padding is expected when pad_last=False + +def test_segment_waveform_2d_pad_last(): + sr = SAMPLE_RATE + win_s = 1.0 + hop_s = 0.75 + wav = np.ones(int(sr * 1.6), dtype=np.float32) + segs = segment_waveform_2d_view(wav, sr=sr, window_sec=win_s, hop_sec=hop_s, pad_last=True) + # Expect one full window + one padded tail window → total 2 + assert segs.shape[0] == 2 + assert segs.shape[1] == int(sr * win_s) + assert np.any(segs[-1] == 0.0) + +def test_segment_waveform_2d_empty_input_returns_empty_or_padded(): + sr = SAMPLE_RATE + segs_no_pad = segment_waveform_2d_view(np.zeros(0, dtype=np.float32), sr=sr, + window_sec=1.0, hop_sec=0.5, pad_last=False) + assert segs_no_pad.shape == (0, int(sr * 1.0)) + segs_pad = segment_waveform_2d_view(np.zeros(0, dtype=np.float32), sr=sr, + window_sec=1.0, hop_sec=0.5, pad_last=True) + # Current impl returns 0 windows even with pad_last for empty input + assert segs_pad.shape == (0, int(sr * 1.0)) diff --git a/services/sounds_classifier/tests/test_db_io_pg.py b/services/sounds_classifier/tests/test_db_io_pg.py index 528d86c32..235f5a5e5 100644 --- a/services/sounds_classifier/tests/test_db_io_pg.py +++ b/services/sounds_classifier/tests/test_db_io_pg.py @@ -1,167 +1,167 @@ -import json -import types -import pytest -import classification.core.db_io_pg as dbpg - - -# ------------------------- -# Dummy connection helpers -# ------------------------- - -class DummyCursor: - def __init__(self, rec=None, raise_on_execute=False): - self.queries = [] - self._rec = rec - self._raise = raise_on_execute - def execute(self, q, p=None): - if self._raise: - raise RuntimeError("boom-exec") - self.queries.append((q, p)) - def fetchone(self): - return (123,) - def __enter__(self): - return self - def __exit__(self, *a): - return False - -class DummyConn: - def __init__(self, raise_on_execute=False): - self.cursors = [] - self.autocommit = False - self._commits = 0 - self._rollbacks = 0 - self._raise = raise_on_execute - def cursor(self): - c = DummyCursor(raise_on_execute=self._raise) - self.cursors.append(c) - return c - def commit(self): - self._commits += 1 - def rollback(self): - self._rollbacks += 1 - - -# ------------------------- -# open_db -# ------------------------- - -def test_open_db_validates_and_initializes_schema(monkeypatch): - # make psycopg2.connect return our dummy connection - monkeypatch.setattr(dbpg.psycopg2, "connect", lambda url: DummyConn()) - conn = dbpg.open_db("postgresql://u:p@h:5432/db", schema="audio_cls") - assert isinstance(conn, DummyConn) - # schema init should have committed once - assert conn._commits >= 1 - -def test_open_db_rejects_bad_schema(): - with pytest.raises(ValueError): - dbpg.open_db("postgresql://u:p@h:5432/db", schema="bad-dash") - -def test_open_db_rollback_on_failure(monkeypatch): - # first cursor.execute will raise - monkeypatch.setattr(dbpg.psycopg2, "connect", lambda url: DummyConn(raise_on_execute=True)) - with pytest.raises(RuntimeError): - dbpg.open_db("postgresql://u:p@h:5432/db", schema="audio_cls") - - -# ------------------------- -# upsert_run -# ------------------------- - -def test_upsert_run_success(monkeypatch): - conn = DummyConn() - dbpg.upsert_run(conn, { - "run_id": "r1", "model_name": "CNN14", "checkpoint": "ckpt", - "head_path": "h", "labels_csv": "l", "window_sec": 2.0, "hop_sec": 0.5, - "pad_last": True, "agg": "mean", "topk": 10, "device": "cpu", - "code_version": "v", "notes": "n" - }) - assert conn._commits == 1 - assert conn._rollbacks == 0 - # Ensure at least one execute has been issued - assert conn.cursors and conn.cursors[0].queries - -def test_upsert_run_rollback_on_exception(monkeypatch): - conn = DummyConn(raise_on_execute=True) - with pytest.raises(RuntimeError): - dbpg.upsert_run(conn, { - "run_id":"r1","model_name":"CNN14","checkpoint":"ckpt","head_path":"h","labels_csv":"l", - "window_sec":2.0,"hop_sec":0.5,"pad_last":True,"agg":"mean","topk":10,"device":"cpu", - "code_version":"v","notes":"n" - }) - assert conn._rollbacks == 1 - assert conn._commits == 0 - - -# ------------------------- -# finish_run -# ------------------------- - -def test_finish_run_success(): - conn = DummyConn() - dbpg.finish_run(conn, "r1") - assert conn._commits == 1 - assert conn._rollbacks == 0 - assert conn.cursors[0].queries # UPDATE executed - -def test_finish_run_rollback_on_exception(): - conn = DummyConn(raise_on_execute=True) - with pytest.raises(RuntimeError): - dbpg.finish_run(conn, "r1") - assert conn._rollbacks == 1 - assert conn._commits == 0 - -def test__jsonify_variants(monkeypatch): - # Wrap psycopg2.extras.Json to observe value passed in - captured = {"value": None} - def fake_json(v): - captured["value"] = v - return ("JsonWrapped", v) - - monkeypatch.setattr(dbpg.psycopg2.extras, "Json", fake_json, raising=True) - - # string with valid JSON → parsed dict - j = dbpg._jsonify('{"a":1}') - assert j == ("JsonWrapped", {"a": 1}) - assert captured["value"] == {"a": 1} - - # plain string → {"raw": "..."} - j2 = dbpg._jsonify("hello") - assert j2 == ("JsonWrapped", {"raw": "hello"}) - assert captured["value"] == {"raw": "hello"} - - # dict passes through - j3 = dbpg._jsonify({"k": 3}) - assert j3 == ("JsonWrapped", {"k": 3}) - assert captured["value"] == {"k": 3} - -def test_upsert_file_aggregate_success(monkeypatch): - # Make Json a pass-through so psycopg2.extras.Json(v) -> v - monkeypatch.setattr(dbpg.psycopg2.extras, "Json", lambda x: x, raising=True) - - conn = DummyConn() - dbpg.upsert_file_aggregate(conn, { - "run_id":"r1","file_id":123, - "head_probs_json":{"car":0.9},"head_pred_label":"car","head_pred_prob":0.9, - "head_unknown_threshold":0.55,"head_is_another":False, - "num_windows":3,"agg_mode":"mean","processing_ms":123 - }) - assert conn._commits == 1 - assert conn._rollbacks == 0 - -def test_upsert_file_aggregate_accepts_string_json_and_rollback_on_exception(monkeypatch): - # Json wrapper - monkeypatch.setattr(dbpg.psycopg2.extras, "Json", lambda x: x, raising=True) - - # connection that will fail during execute - conn = DummyConn(raise_on_execute=True) - with pytest.raises(RuntimeError): - dbpg.upsert_file_aggregate(conn, { - "run_id":"r1","file_id":123, - "head_probs_json":'{"car":0.9}', # string json - "head_pred_label":"car","head_pred_prob":0.9, - "head_unknown_threshold":0.55,"head_is_another":False, - "num_windows":3,"agg_mode":"mean","processing_ms":123 - }) - assert conn._rollbacks == 1 - assert conn._commits == 0 +import json +import types +import pytest +import classification.core.db_io_pg as dbpg + + +# ------------------------- +# Dummy connection helpers +# ------------------------- + +class DummyCursor: + def __init__(self, rec=None, raise_on_execute=False): + self.queries = [] + self._rec = rec + self._raise = raise_on_execute + def execute(self, q, p=None): + if self._raise: + raise RuntimeError("boom-exec") + self.queries.append((q, p)) + def fetchone(self): + return (123,) + def __enter__(self): + return self + def __exit__(self, *a): + return False + +class DummyConn: + def __init__(self, raise_on_execute=False): + self.cursors = [] + self.autocommit = False + self._commits = 0 + self._rollbacks = 0 + self._raise = raise_on_execute + def cursor(self): + c = DummyCursor(raise_on_execute=self._raise) + self.cursors.append(c) + return c + def commit(self): + self._commits += 1 + def rollback(self): + self._rollbacks += 1 + + +# ------------------------- +# open_db +# ------------------------- + +def test_open_db_validates_and_initializes_schema(monkeypatch): + # make psycopg2.connect return our dummy connection + monkeypatch.setattr(dbpg.psycopg2, "connect", lambda url: DummyConn()) + conn = dbpg.open_db("postgresql://u:p@h:5432/db", schema="audio_cls") + assert isinstance(conn, DummyConn) + # schema init should have committed once + assert conn._commits >= 1 + +def test_open_db_rejects_bad_schema(): + with pytest.raises(ValueError): + dbpg.open_db("postgresql://u:p@h:5432/db", schema="bad-dash") + +def test_open_db_rollback_on_failure(monkeypatch): + # first cursor.execute will raise + monkeypatch.setattr(dbpg.psycopg2, "connect", lambda url: DummyConn(raise_on_execute=True)) + with pytest.raises(RuntimeError): + dbpg.open_db("postgresql://u:p@h:5432/db", schema="audio_cls") + + +# ------------------------- +# upsert_run +# ------------------------- + +def test_upsert_run_success(monkeypatch): + conn = DummyConn() + dbpg.upsert_run(conn, { + "run_id": "r1", "model_name": "CNN14", "checkpoint": "ckpt", + "head_path": "h", "labels_csv": "l", "window_sec": 2.0, "hop_sec": 0.5, + "pad_last": True, "agg": "mean", "topk": 10, "device": "cpu", + "code_version": "v", "notes": "n" + }) + assert conn._commits == 1 + assert conn._rollbacks == 0 + # Ensure at least one execute has been issued + assert conn.cursors and conn.cursors[0].queries + +def test_upsert_run_rollback_on_exception(monkeypatch): + conn = DummyConn(raise_on_execute=True) + with pytest.raises(RuntimeError): + dbpg.upsert_run(conn, { + "run_id":"r1","model_name":"CNN14","checkpoint":"ckpt","head_path":"h","labels_csv":"l", + "window_sec":2.0,"hop_sec":0.5,"pad_last":True,"agg":"mean","topk":10,"device":"cpu", + "code_version":"v","notes":"n" + }) + assert conn._rollbacks == 1 + assert conn._commits == 0 + + +# ------------------------- +# finish_run +# ------------------------- + +def test_finish_run_success(): + conn = DummyConn() + dbpg.finish_run(conn, "r1") + assert conn._commits == 1 + assert conn._rollbacks == 0 + assert conn.cursors[0].queries # UPDATE executed + +def test_finish_run_rollback_on_exception(): + conn = DummyConn(raise_on_execute=True) + with pytest.raises(RuntimeError): + dbpg.finish_run(conn, "r1") + assert conn._rollbacks == 1 + assert conn._commits == 0 + +def test__jsonify_variants(monkeypatch): + # Wrap psycopg2.extras.Json to observe value passed in + captured = {"value": None} + def fake_json(v): + captured["value"] = v + return ("JsonWrapped", v) + + monkeypatch.setattr(dbpg.psycopg2.extras, "Json", fake_json, raising=True) + + # string with valid JSON → parsed dict + j = dbpg._jsonify('{"a":1}') + assert j == ("JsonWrapped", {"a": 1}) + assert captured["value"] == {"a": 1} + + # plain string → {"raw": "..."} + j2 = dbpg._jsonify("hello") + assert j2 == ("JsonWrapped", {"raw": "hello"}) + assert captured["value"] == {"raw": "hello"} + + # dict passes through + j3 = dbpg._jsonify({"k": 3}) + assert j3 == ("JsonWrapped", {"k": 3}) + assert captured["value"] == {"k": 3} + +def test_upsert_file_aggregate_success(monkeypatch): + # Make Json a pass-through so psycopg2.extras.Json(v) -> v + monkeypatch.setattr(dbpg.psycopg2.extras, "Json", lambda x: x, raising=True) + + conn = DummyConn() + dbpg.upsert_file_aggregate(conn, { + "run_id":"r1","file_id":123, + "head_probs_json":{"car":0.9},"head_pred_label":"car","head_pred_prob":0.9, + "head_unknown_threshold":0.55,"head_is_another":False, + "num_windows":3,"agg_mode":"mean","processing_ms":123 + }) + assert conn._commits == 1 + assert conn._rollbacks == 0 + +def test_upsert_file_aggregate_accepts_string_json_and_rollback_on_exception(monkeypatch): + # Json wrapper + monkeypatch.setattr(dbpg.psycopg2.extras, "Json", lambda x: x, raising=True) + + # connection that will fail during execute + conn = DummyConn(raise_on_execute=True) + with pytest.raises(RuntimeError): + dbpg.upsert_file_aggregate(conn, { + "run_id":"r1","file_id":123, + "head_probs_json":'{"car":0.9}', # string json + "head_pred_label":"car","head_pred_prob":0.9, + "head_unknown_threshold":0.55,"head_is_another":False, + "num_windows":3,"agg_mode":"mean","processing_ms":123 + }) + assert conn._rollbacks == 1 + assert conn._commits == 0 diff --git a/services/sounds_classifier/tests/test_db_utils.py b/services/sounds_classifier/tests/test_db_utils.py index 02b7f0e06..bbe6e8f43 100644 --- a/services/sounds_classifier/tests/test_db_utils.py +++ b/services/sounds_classifier/tests/test_db_utils.py @@ -1,165 +1,165 @@ -import os -import re -import pytest - -import classification.core.db_utils as dbu - -# ----------------------------- -# Fake psycopg2 connection/cursor -# ----------------------------- -class FakeCursor: - def __init__(self, script_recorder): - self.script_recorder = script_recorder - self._fetchone = None # single value returned by fetchone() - - def __enter__(self): - return self - - def __exit__(self, exc_type, exc, tb): - return False - - def execute(self, query, params=None): - # Record statements and params for later assertions - self.script_recorder.append(("EXEC", str(query), params)) - - def fetchone(self): - return self._fetchone - - # helper for tests to set what fetchone should return - def set_fetchone(self, value): - self._fetchone = value - - -class FakeConn: - def __init__(self): - self.autocommit = False - self.closed = False - self._script = [] - self._cursor = FakeCursor(self._script) - - def cursor(self): - return self._cursor - - def commit(self): - self._script.append(("COMMIT", None, None)) - - def rollback(self): - self._script.append(("ROLLBACK", None, None)) - - def close(self): - self.closed = True - - # test helper - def script(self): - return list(self._script) - - -# ----------------------------- -# Fixture -# ----------------------------- -@pytest.fixture -def fake_conn(monkeypatch): - """ - Patch psycopg2.connect to return our FakeConn. - Also ensure env vars exist with harmless defaults. - """ - fc = FakeConn() - - def fake_connect(**kwargs): - return fc - - # Patch psycopg2.connect inside db_utils module - monkeypatch.setattr(dbu.psycopg2, "connect", fake_connect) - - # Minimal env for db_utils.open_db() - monkeypatch.setenv("DB_HOST", "postgres") - monkeypatch.setenv("DB_PORT", "5432") - monkeypatch.setenv("DB_NAME", "missions_db") - monkeypatch.setenv("DB_USER", "missions_user") - monkeypatch.setenv("DB_PASSWORD", "pg123") - monkeypatch.setenv("DB_SCHEMA", "agcloud_audio") - - return fc - - -# ----------------------------- -# Tests for open_db() -# ----------------------------- -def test_open_db_sets_search_path(fake_conn): - conn = dbu.open_db() - assert conn is fake_conn - # We expect one SET search_path statement with our schema - script = conn.script() - execs = [s for s in script if s[0] == "EXEC"] - assert any( - ("SET search_path TO" in q) and ("agcloud_audio" in q) - for _, q, _ in execs - ), f"Expected SET search_path to agcloud_audio, got: {execs}" - # autocommit should remain False - assert conn.autocommit is False - - -# ----------------------------- -# Tests for ensure_run() -# ----------------------------- -def test_ensure_run_inserts_and_commits(fake_conn, monkeypatch): - # Provide env to fill NOT NULL columns - monkeypatch.setenv("MODEL_NAME", "panns_cnn14") - monkeypatch.setenv("CHECKPOINT", "ckpt.pth") - monkeypatch.setenv("HEAD", "/tmp/head.joblib") - monkeypatch.setenv("LABELS_CSV", "") - monkeypatch.setenv("WINDOW_SEC", "10") - monkeypatch.setenv("HOP_SEC", "10") - monkeypatch.setenv("PAD_LAST", "true") - monkeypatch.setenv("AGG", "mean") - monkeypatch.setenv("TOPK", "3") - monkeypatch.setenv("DEVICE", "cpu") - monkeypatch.setenv("CODE_VERSION", "test") - monkeypatch.setenv("RUN_NOTES", "unit-test") - - dbu.ensure_run(fake_conn, run_id="run-123") - # We expect one INSERT and one COMMIT - script = fake_conn.script() - insert_calls = [s for s in script if s[0] == "EXEC" and "INSERT INTO runs" in s[1]] - assert len(insert_calls) == 1, f"expected single INSERT, got: {insert_calls}" - assert ("COMMIT", None, None) in script - - -# ----------------------------- -# Tests for resolve_file_id() -# ----------------------------- -def test_resolve_file_id_by_file_id_ok(fake_conn): - # Simulate existing file_id - fake_conn._cursor.set_fetchone((42,)) - file_id = dbu.resolve_file_id(fake_conn, file_id=42) - assert file_id == 42 - # Verify the WHERE clause by id appeared - execs = [s for s in fake_conn.script() if s[0] == "EXEC"] - assert any("WHERE file_id = %s" in q for _, q, _ in execs) - -def test_resolve_file_id_by_file_id_not_found(fake_conn): - fake_conn._cursor.set_fetchone(None) - with pytest.raises(ValueError) as ex: - dbu.resolve_file_id(fake_conn, file_id=999) - assert "file_id 999 not found" in str(ex.value) - -def test_resolve_file_id_by_bucket_key_ok(fake_conn): - # Simulate a row found by (bucket, object_key) - fake_conn._cursor.set_fetchone((321,)) - out = dbu.resolve_file_id(fake_conn, bucket="b", object_key="k") - assert out == 321 - execs = [s for s in fake_conn.script() if s[0] == "EXEC"] - assert any("WHERE bucket = %s AND object_key = %s" in q for _, q, _ in execs) - -def test_resolve_file_id_by_bucket_key_not_found(fake_conn): - fake_conn._cursor.set_fetchone(None) - with pytest.raises(ValueError) as ex: - dbu.resolve_file_id(fake_conn, bucket="b", object_key="k") - msg = str(ex.value) - # Be flexible about formatting: just assert key parts of the message exist - assert "not found in public.files" in msg - assert "s3://b/k" in msg or ("bucket" in msg and "object_key" in msg and "b" in msg and "k" in msg) - -def test_resolve_file_id_requires_params(fake_conn): - with pytest.raises(ValueError): - dbu.resolve_file_id(fake_conn) # neither file_id nor (bucket,key) +import os +import re +import pytest + +import classification.core.db_utils as dbu + +# ----------------------------- +# Fake psycopg2 connection/cursor +# ----------------------------- +class FakeCursor: + def __init__(self, script_recorder): + self.script_recorder = script_recorder + self._fetchone = None # single value returned by fetchone() + + def __enter__(self): + return self + + def __exit__(self, exc_type, exc, tb): + return False + + def execute(self, query, params=None): + # Record statements and params for later assertions + self.script_recorder.append(("EXEC", str(query), params)) + + def fetchone(self): + return self._fetchone + + # helper for tests to set what fetchone should return + def set_fetchone(self, value): + self._fetchone = value + + +class FakeConn: + def __init__(self): + self.autocommit = False + self.closed = False + self._script = [] + self._cursor = FakeCursor(self._script) + + def cursor(self): + return self._cursor + + def commit(self): + self._script.append(("COMMIT", None, None)) + + def rollback(self): + self._script.append(("ROLLBACK", None, None)) + + def close(self): + self.closed = True + + # test helper + def script(self): + return list(self._script) + + +# ----------------------------- +# Fixture +# ----------------------------- +@pytest.fixture +def fake_conn(monkeypatch): + """ + Patch psycopg2.connect to return our FakeConn. + Also ensure env vars exist with harmless defaults. + """ + fc = FakeConn() + + def fake_connect(**kwargs): + return fc + + # Patch psycopg2.connect inside db_utils module + monkeypatch.setattr(dbu.psycopg2, "connect", fake_connect) + + # Minimal env for db_utils.open_db() + monkeypatch.setenv("DB_HOST", "postgres") + monkeypatch.setenv("DB_PORT", "5432") + monkeypatch.setenv("DB_NAME", "missions_db") + monkeypatch.setenv("DB_USER", "missions_user") + monkeypatch.setenv("DB_PASSWORD", "pg123") + monkeypatch.setenv("DB_SCHEMA", "agcloud_audio") + + return fc + + +# ----------------------------- +# Tests for open_db() +# ----------------------------- +def test_open_db_sets_search_path(fake_conn): + conn = dbu.open_db() + assert conn is fake_conn + # We expect one SET search_path statement with our schema + script = conn.script() + execs = [s for s in script if s[0] == "EXEC"] + assert any( + ("SET search_path TO" in q) and ("agcloud_audio" in q) + for _, q, _ in execs + ), f"Expected SET search_path to agcloud_audio, got: {execs}" + # autocommit should remain False + assert conn.autocommit is False + + +# ----------------------------- +# Tests for ensure_run() +# ----------------------------- +def test_ensure_run_inserts_and_commits(fake_conn, monkeypatch): + # Provide env to fill NOT NULL columns + monkeypatch.setenv("MODEL_NAME", "panns_cnn14") + monkeypatch.setenv("CHECKPOINT", "ckpt.pth") + monkeypatch.setenv("HEAD", "/tmp/head.joblib") + monkeypatch.setenv("LABELS_CSV", "") + monkeypatch.setenv("WINDOW_SEC", "10") + monkeypatch.setenv("HOP_SEC", "10") + monkeypatch.setenv("PAD_LAST", "true") + monkeypatch.setenv("AGG", "mean") + monkeypatch.setenv("TOPK", "3") + monkeypatch.setenv("DEVICE", "cpu") + monkeypatch.setenv("CODE_VERSION", "test") + monkeypatch.setenv("RUN_NOTES", "unit-test") + + dbu.ensure_run(fake_conn, run_id="run-123") + # We expect one INSERT and one COMMIT + script = fake_conn.script() + insert_calls = [s for s in script if s[0] == "EXEC" and "INSERT INTO runs" in s[1]] + assert len(insert_calls) == 1, f"expected single INSERT, got: {insert_calls}" + assert ("COMMIT", None, None) in script + + +# ----------------------------- +# Tests for resolve_file_id() +# ----------------------------- +def test_resolve_file_id_by_file_id_ok(fake_conn): + # Simulate existing file_id + fake_conn._cursor.set_fetchone((42,)) + file_id = dbu.resolve_file_id(fake_conn, file_id=42) + assert file_id == 42 + # Verify the WHERE clause by id appeared + execs = [s for s in fake_conn.script() if s[0] == "EXEC"] + assert any("WHERE file_id = %s" in q for _, q, _ in execs) + +def test_resolve_file_id_by_file_id_not_found(fake_conn): + fake_conn._cursor.set_fetchone(None) + with pytest.raises(ValueError) as ex: + dbu.resolve_file_id(fake_conn, file_id=999) + assert "file_id 999 not found" in str(ex.value) + +def test_resolve_file_id_by_bucket_key_ok(fake_conn): + # Simulate a row found by (bucket, object_key) + fake_conn._cursor.set_fetchone((321,)) + out = dbu.resolve_file_id(fake_conn, bucket="b", object_key="k") + assert out == 321 + execs = [s for s in fake_conn.script() if s[0] == "EXEC"] + assert any("WHERE bucket = %s AND object_key = %s" in q for _, q, _ in execs) + +def test_resolve_file_id_by_bucket_key_not_found(fake_conn): + fake_conn._cursor.set_fetchone(None) + with pytest.raises(ValueError) as ex: + dbu.resolve_file_id(fake_conn, bucket="b", object_key="k") + msg = str(ex.value) + # Be flexible about formatting: just assert key parts of the message exist + assert "not found in public.files" in msg + assert "s3://b/k" in msg or ("bucket" in msg and "object_key" in msg and "b" in msg and "k" in msg) + +def test_resolve_file_id_requires_params(fake_conn): + with pytest.raises(ValueError): + dbu.resolve_file_id(fake_conn) # neither file_id nor (bucket,key) diff --git a/services/sounds_classifier/tests/test_model_io.py b/services/sounds_classifier/tests/test_model_io.py index c635ffd19..4634a9804 100644 --- a/services/sounds_classifier/tests/test_model_io.py +++ b/services/sounds_classifier/tests/test_model_io.py @@ -1,258 +1,258 @@ -import numpy as np -from pathlib import Path -import types -import pytest -import soundfile as sf - -import classification.core.model_io as mio -from classification.core.model_io import ( - aggregate_matrix, - segment_waveform, - load_audio, - SAMPLE_RATE, - ensure_checkpoint, - ensure_numpy_1d, - _to_numpy, -) - -# ---------- aggregate_matrix: happy paths and error branches ---------- - -def test_aggregate_matrix_mean_and_max_non_empty(): - X = np.array([[0.1, 0.9], [0.7, 0.3], [0.2, 0.8]], dtype=np.float32) - m = aggregate_matrix(X, mode="mean") - M = aggregate_matrix(X, mode="max") - assert np.allclose(m, X.mean(0)) - assert np.allclose(M, X.max(0)) - -def test_aggregate_matrix_empty_raises(): - X = np.zeros((0, 2), dtype=np.float32) - with pytest.raises(ValueError) as e: - aggregate_matrix(X, mode="mean") - assert "empty window matrix" in str(e.value) - -def test_aggregate_matrix_zero_classes_raises(): - X = np.zeros((3, 0), dtype=np.float32) - with pytest.raises(ValueError) as e: - aggregate_matrix(X, mode="mean") - assert "num_classes > 0" in str(e.value) - -def test_aggregate_matrix_wrong_type_and_ndim(): - with pytest.raises(TypeError): - aggregate_matrix([[1, 2], [3, 4]], mode="mean") # not np.ndarray - with pytest.raises(ValueError): - aggregate_matrix(np.array([1, 2, 3], dtype=np.float32), mode="mean") # 1D - with pytest.raises(ValueError): - aggregate_matrix(np.zeros((2, 2, 2), dtype=np.float32), mode="mean") # 3D - -def test_aggregate_matrix_unsupported_mode(): - X = np.ones((2, 2), dtype=np.float32) - with pytest.raises(ValueError): - aggregate_matrix(X, mode="median") - -def test_aggregate_matrix_nan_and_infs_are_handled(): - X = np.array([[np.nan, 1.0, np.inf, -np.inf], - [2.0, np.nan, 3.0, -5.0 ]], dtype=np.float32) - out_mean = aggregate_matrix(X, mode="mean") - out_max = aggregate_matrix(X, mode="max") - assert out_mean.dtype == np.float32 - assert out_max.dtype == np.float32 - # NaNs should be treated as missing, and inf/-inf should be clamped via nan_to_num. - assert np.isfinite(out_mean).all() - assert np.isfinite(out_max).all() - -# ---------- ensure_numpy_1d & _to_numpy ---------- - -def test_ensure_numpy_1d_duck_typed_torch_like(): - class DuckTensor: - def __init__(self, arr): self._arr = np.asarray(arr, dtype=np.float32) - def detach(self): return self - def cpu(self): return self - def numpy(self): return self._arr - x = DuckTensor([[1.0], [2.0], [3.0]]) - y = ensure_numpy_1d(x) - assert isinstance(y, np.ndarray) - assert y.shape == (3,) - assert y.dtype == np.float32 - -def test_ensure_numpy_1d_object_with_numpy_method_only(): - class OnlyNumpy: - def __init__(self, arr): self._arr = np.asarray(arr, dtype=np.float32) - def numpy(self): return self._arr - x = OnlyNumpy([[1.0, 2.0, 3.0]]) - y = ensure_numpy_1d(x) - assert y.shape == (3,) - assert y.dtype == np.float32 - -def test__to_numpy_handles_2d_shapes_and_casts_to_float32(): - x = np.array([[1.0], [2.0], [3.0]], dtype=np.float64) - y = _to_numpy(x) - assert y.dtype == np.float32 - assert y.shape == (3,) - -@pytest.mark.skipif(mio.torch is None, reason="torch is not available") -def test__to_numpy_with_real_torch_tensor_when_available(): - import torch - x = torch.tensor([[1.0, 2.0, 3.0]], dtype=torch.float32) - try: - y = _to_numpy(x) - except RuntimeError as e: - # Some builds of torch raise when calling .numpy() if NumPy is mismatched/not present. - assert "Numpy is not available" in str(e) - else: - assert isinstance(y, np.ndarray) - assert y.dtype == np.float32 - assert y.shape == (3,) - -# ---------- segment_waveform edge cases ---------- - -def test_segment_waveform_empty_and_padding_logic(): - # empty wav returns [] - assert segment_waveform(np.array([], dtype=np.float32), sr=SAMPLE_RATE) == [] - - # shorter than one window, pad_last=True adds one padded segment - short = np.ones(100, dtype=np.float32) - segs = segment_waveform(short, sr=SAMPLE_RATE, window_sec=0.01, hop_sec=0.005, pad_last=True) - assert len(segs) >= 1 - for s in segs: - assert s.ndim == 1 and s.dtype == np.float32 - - # shorter than one window, pad_last=False should not add segment - segs2 = segment_waveform(short, sr=SAMPLE_RATE, window_sec=0.01, hop_sec=0.005, pad_last=False) - # Depending on rounding, there may be 0 or >0 windows; enforce that no tail padding is added: - # if the first while loop didn't fit any full window, with pad_last=False we expect 0 segments. - assert len(segs2) in (0,) - -def test_segment_waveform_overlap_and_types(): - wav = np.arange(1000, dtype=np.int16) # non-float input should be casted - segs = segment_waveform(wav, sr=1000, window_sec=0.1, hop_sec=0.05, pad_last=True) - assert len(segs) >= 1 - assert all(s.dtype == np.float32 for s in segs) - -# ---------- load_audio: WAV roundtrip & padding ---------- - -def _sine(sr: int, seconds: float) -> np.ndarray: - t = np.linspace(0, seconds, int(sr * seconds), endpoint=False, dtype=np.float32) - return np.sin(2 * np.pi * 440.0 * t).astype(np.float32) - -def test_load_audio_roundtrip_and_padding(tmp_path: Path): - wav = _sine(SAMPLE_RATE, 0.25) # shorter than MIN_SAMPLES (16000) - p = tmp_path / "a.wav" - sf.write(p, wav, samplerate=SAMPLE_RATE, subtype="PCM_16") - out = load_audio(str(p), SAMPLE_RATE) - assert out.dtype == np.float32 - assert out.ndim == 1 - assert out.size >= mio.MIN_SAMPLES # padded - -def test_load_audio_resample_path(monkeypatch, tmp_path: Path): - # Write at sr=16000; target is 32000. Force librosa.resample path. - wav16 = _sine(16000, 0.2).astype(np.float32) - p = tmp_path / "b.wav" - sf.write(p, wav16, samplerate=16000, subtype="PCM_16") - - called = {"resample": False} - def fake_resample(y, orig_sr, target_sr): - called["resample"] = True - # return float64 to test cast back to float32 - return np.asarray(np.repeat(y, 2), dtype=np.float64) - - monkeypatch.setattr(mio.librosa, "resample", fake_resample, raising=True) - out = load_audio(str(p), SAMPLE_RATE) - assert called["resample"] is True - assert out.dtype == np.float32 - assert out.ndim == 1 - -# ---------- load_audio: HARD_EXTS (mp3/m4a/...) branch + ffmpeg fallback ---------- - -def test_load_audio_hard_ext_uses_librosa_success(monkeypatch, tmp_path: Path): - # Fake an mp3 file; we'll mock librosa.load to return data, so the bytes don't matter. - p = tmp_path / "x.mp3" - p.write_bytes(b"ID3") - - def fake_librosa_load(path, sr, mono): - assert str(path) == str(p) - return np.ones(100, dtype=np.float32), sr - - monkeypatch.setattr(mio.librosa, "load", fake_librosa_load, raising=True) - out = load_audio(str(p), SAMPLE_RATE) - assert out.dtype == np.float32 - assert out.ndim == 1 - assert out.size >= mio.MIN_SAMPLES - -def test_load_audio_hard_ext_librosa_fail_ffmpeg_fallback(monkeypatch, tmp_path: Path): - p = tmp_path / "y.m4a" - p.write_bytes(b"\x00\x00\x00\x20ftypM4A ") # header-ish; not used - - def fake_librosa_fail(*a, **k): raise RuntimeError("boom") - monkeypatch.setattr(mio.librosa, "load", fake_librosa_fail, raising=True) - monkeypatch.setattr(mio, "has_ffmpeg", lambda: True, raising=True) - # make ffmpeg path return short buffer to test padding - monkeypatch.setattr(mio, "decode_with_ffmpeg_to_float32_mono", - lambda path, target_sr: np.ones(10, dtype=np.float32), raising=True) - out = load_audio(str(p), SAMPLE_RATE) - assert out.size >= mio.MIN_SAMPLES - assert out.dtype == np.float32 - -def test_load_audio_all_fail_then_ffmpeg(monkeypatch, tmp_path: Path): - # For non-HARD ext: raise in soundfile.read, then raise in librosa.load, then use ffmpeg - p = tmp_path / "z.ogg" - p.write_bytes(b"OggS...") - - def fake_sf_read(*a, **k): raise RuntimeError("sf fail") - def fake_librosa_load(*a, **k): raise RuntimeError("librosa fail") - - monkeypatch.setattr(sf, "read", fake_sf_read, raising=True) - monkeypatch.setattr(mio.librosa, "load", fake_librosa_load, raising=True) - monkeypatch.setattr(mio, "has_ffmpeg", lambda: True, raising=True) - monkeypatch.setattr(mio, "decode_with_ffmpeg_to_float32_mono", - lambda path, target_sr: np.ones(33, dtype=np.float32), raising=True) - out = load_audio(str(p), SAMPLE_RATE) - assert out.ndim == 1 and out.dtype == np.float32 - -# ---------- ffmpeg helpers ---------- - -def test_has_ffmpeg_uses_shutil_which(monkeypatch): - # Ensure function depends on shutil.which - monkeypatch.setattr(mio.shutil, "which", lambda _: "/usr/bin/ffmpeg") - assert mio.has_ffmpeg() is True - monkeypatch.setattr(mio.shutil, "which", lambda _: None) - assert mio.has_ffmpeg() is False - -def test_decode_with_ffmpeg_to_float32_mono_monkeypatched(monkeypatch, tmp_path: Path): - # We won't call real ffmpeg; we mock subprocess.run to return a small f32 buffer. - p = tmp_path / "q.ogg" - p.write_bytes(b"OggS...") - - class DummyProc: - def __init__(self, data): self.stdout = data; self.stderr = b"" - # 4 float32 numbers -> 16 bytes; MIN_SAMPLES will trigger padding. - raw = (np.array([0.1, 0.2, 0.3, 0.4], dtype=np.float32)).tobytes() - - monkeypatch.setattr( - mio.subprocess, "run", - lambda cmd, stdout, stderr, check: DummyProc(raw), - raising=True - ) - - out = mio.decode_with_ffmpeg_to_float32_mono(str(p), mio.SAMPLE_RATE) - assert out.dtype == np.float32 - assert out.ndim == 1 - assert out.size >= mio.MIN_SAMPLES - -# ---------- ensure_checkpoint (patch urllib at global module level) ---------- - -def test_ensure_checkpoint_downloads_when_missing(monkeypatch, tmp_path): - target = tmp_path / "models" / "panns_data" / "m.pth" - called = {"ok": False} - def fake_urlretrieve(url, dst): - called["ok"] = True - Path(dst).write_bytes(b"ok") - monkeypatch.setattr("urllib.request.urlretrieve", fake_urlretrieve, raising=True) - path = ensure_checkpoint(str(target), "http://example.com/m.pth") - assert called["ok"] is True - assert Path(path).exists() - -def test_ensure_numpy_and_to_numpy_helpers(): - x = np.array([[1.0], [2.0], [3.0]], dtype=np.float32) - assert ensure_numpy_1d(x).shape == (3,) - y = _to_numpy(x.reshape(1, -1)) - assert y.ndim == 1 +import numpy as np +from pathlib import Path +import types +import pytest +import soundfile as sf + +import classification.core.model_io as mio +from classification.core.model_io import ( + aggregate_matrix, + segment_waveform, + load_audio, + SAMPLE_RATE, + ensure_checkpoint, + ensure_numpy_1d, + _to_numpy, +) + +# ---------- aggregate_matrix: happy paths and error branches ---------- + +def test_aggregate_matrix_mean_and_max_non_empty(): + X = np.array([[0.1, 0.9], [0.7, 0.3], [0.2, 0.8]], dtype=np.float32) + m = aggregate_matrix(X, mode="mean") + M = aggregate_matrix(X, mode="max") + assert np.allclose(m, X.mean(0)) + assert np.allclose(M, X.max(0)) + +def test_aggregate_matrix_empty_raises(): + X = np.zeros((0, 2), dtype=np.float32) + with pytest.raises(ValueError) as e: + aggregate_matrix(X, mode="mean") + assert "empty window matrix" in str(e.value) + +def test_aggregate_matrix_zero_classes_raises(): + X = np.zeros((3, 0), dtype=np.float32) + with pytest.raises(ValueError) as e: + aggregate_matrix(X, mode="mean") + assert "num_classes > 0" in str(e.value) + +def test_aggregate_matrix_wrong_type_and_ndim(): + with pytest.raises(TypeError): + aggregate_matrix([[1, 2], [3, 4]], mode="mean") # not np.ndarray + with pytest.raises(ValueError): + aggregate_matrix(np.array([1, 2, 3], dtype=np.float32), mode="mean") # 1D + with pytest.raises(ValueError): + aggregate_matrix(np.zeros((2, 2, 2), dtype=np.float32), mode="mean") # 3D + +def test_aggregate_matrix_unsupported_mode(): + X = np.ones((2, 2), dtype=np.float32) + with pytest.raises(ValueError): + aggregate_matrix(X, mode="median") + +def test_aggregate_matrix_nan_and_infs_are_handled(): + X = np.array([[np.nan, 1.0, np.inf, -np.inf], + [2.0, np.nan, 3.0, -5.0 ]], dtype=np.float32) + out_mean = aggregate_matrix(X, mode="mean") + out_max = aggregate_matrix(X, mode="max") + assert out_mean.dtype == np.float32 + assert out_max.dtype == np.float32 + # NaNs should be treated as missing, and inf/-inf should be clamped via nan_to_num. + assert np.isfinite(out_mean).all() + assert np.isfinite(out_max).all() + +# ---------- ensure_numpy_1d & _to_numpy ---------- + +def test_ensure_numpy_1d_duck_typed_torch_like(): + class DuckTensor: + def __init__(self, arr): self._arr = np.asarray(arr, dtype=np.float32) + def detach(self): return self + def cpu(self): return self + def numpy(self): return self._arr + x = DuckTensor([[1.0], [2.0], [3.0]]) + y = ensure_numpy_1d(x) + assert isinstance(y, np.ndarray) + assert y.shape == (3,) + assert y.dtype == np.float32 + +def test_ensure_numpy_1d_object_with_numpy_method_only(): + class OnlyNumpy: + def __init__(self, arr): self._arr = np.asarray(arr, dtype=np.float32) + def numpy(self): return self._arr + x = OnlyNumpy([[1.0, 2.0, 3.0]]) + y = ensure_numpy_1d(x) + assert y.shape == (3,) + assert y.dtype == np.float32 + +def test__to_numpy_handles_2d_shapes_and_casts_to_float32(): + x = np.array([[1.0], [2.0], [3.0]], dtype=np.float64) + y = _to_numpy(x) + assert y.dtype == np.float32 + assert y.shape == (3,) + +@pytest.mark.skipif(mio.torch is None, reason="torch is not available") +def test__to_numpy_with_real_torch_tensor_when_available(): + import torch + x = torch.tensor([[1.0, 2.0, 3.0]], dtype=torch.float32) + try: + y = _to_numpy(x) + except RuntimeError as e: + # Some builds of torch raise when calling .numpy() if NumPy is mismatched/not present. + assert "Numpy is not available" in str(e) + else: + assert isinstance(y, np.ndarray) + assert y.dtype == np.float32 + assert y.shape == (3,) + +# ---------- segment_waveform edge cases ---------- + +def test_segment_waveform_empty_and_padding_logic(): + # empty wav returns [] + assert segment_waveform(np.array([], dtype=np.float32), sr=SAMPLE_RATE) == [] + + # shorter than one window, pad_last=True adds one padded segment + short = np.ones(100, dtype=np.float32) + segs = segment_waveform(short, sr=SAMPLE_RATE, window_sec=0.01, hop_sec=0.005, pad_last=True) + assert len(segs) >= 1 + for s in segs: + assert s.ndim == 1 and s.dtype == np.float32 + + # shorter than one window, pad_last=False should not add segment + segs2 = segment_waveform(short, sr=SAMPLE_RATE, window_sec=0.01, hop_sec=0.005, pad_last=False) + # Depending on rounding, there may be 0 or >0 windows; enforce that no tail padding is added: + # if the first while loop didn't fit any full window, with pad_last=False we expect 0 segments. + assert len(segs2) in (0,) + +def test_segment_waveform_overlap_and_types(): + wav = np.arange(1000, dtype=np.int16) # non-float input should be casted + segs = segment_waveform(wav, sr=1000, window_sec=0.1, hop_sec=0.05, pad_last=True) + assert len(segs) >= 1 + assert all(s.dtype == np.float32 for s in segs) + +# ---------- load_audio: WAV roundtrip & padding ---------- + +def _sine(sr: int, seconds: float) -> np.ndarray: + t = np.linspace(0, seconds, int(sr * seconds), endpoint=False, dtype=np.float32) + return np.sin(2 * np.pi * 440.0 * t).astype(np.float32) + +def test_load_audio_roundtrip_and_padding(tmp_path: Path): + wav = _sine(SAMPLE_RATE, 0.25) # shorter than MIN_SAMPLES (16000) + p = tmp_path / "a.wav" + sf.write(p, wav, samplerate=SAMPLE_RATE, subtype="PCM_16") + out = load_audio(str(p), SAMPLE_RATE) + assert out.dtype == np.float32 + assert out.ndim == 1 + assert out.size >= mio.MIN_SAMPLES # padded + +def test_load_audio_resample_path(monkeypatch, tmp_path: Path): + # Write at sr=16000; target is 32000. Force librosa.resample path. + wav16 = _sine(16000, 0.2).astype(np.float32) + p = tmp_path / "b.wav" + sf.write(p, wav16, samplerate=16000, subtype="PCM_16") + + called = {"resample": False} + def fake_resample(y, orig_sr, target_sr): + called["resample"] = True + # return float64 to test cast back to float32 + return np.asarray(np.repeat(y, 2), dtype=np.float64) + + monkeypatch.setattr(mio.librosa, "resample", fake_resample, raising=True) + out = load_audio(str(p), SAMPLE_RATE) + assert called["resample"] is True + assert out.dtype == np.float32 + assert out.ndim == 1 + +# ---------- load_audio: HARD_EXTS (mp3/m4a/...) branch + ffmpeg fallback ---------- + +def test_load_audio_hard_ext_uses_librosa_success(monkeypatch, tmp_path: Path): + # Fake an mp3 file; we'll mock librosa.load to return data, so the bytes don't matter. + p = tmp_path / "x.mp3" + p.write_bytes(b"ID3") + + def fake_librosa_load(path, sr, mono): + assert str(path) == str(p) + return np.ones(100, dtype=np.float32), sr + + monkeypatch.setattr(mio.librosa, "load", fake_librosa_load, raising=True) + out = load_audio(str(p), SAMPLE_RATE) + assert out.dtype == np.float32 + assert out.ndim == 1 + assert out.size >= mio.MIN_SAMPLES + +def test_load_audio_hard_ext_librosa_fail_ffmpeg_fallback(monkeypatch, tmp_path: Path): + p = tmp_path / "y.m4a" + p.write_bytes(b"\x00\x00\x00\x20ftypM4A ") # header-ish; not used + + def fake_librosa_fail(*a, **k): raise RuntimeError("boom") + monkeypatch.setattr(mio.librosa, "load", fake_librosa_fail, raising=True) + monkeypatch.setattr(mio, "has_ffmpeg", lambda: True, raising=True) + # make ffmpeg path return short buffer to test padding + monkeypatch.setattr(mio, "decode_with_ffmpeg_to_float32_mono", + lambda path, target_sr: np.ones(10, dtype=np.float32), raising=True) + out = load_audio(str(p), SAMPLE_RATE) + assert out.size >= mio.MIN_SAMPLES + assert out.dtype == np.float32 + +def test_load_audio_all_fail_then_ffmpeg(monkeypatch, tmp_path: Path): + # For non-HARD ext: raise in soundfile.read, then raise in librosa.load, then use ffmpeg + p = tmp_path / "z.ogg" + p.write_bytes(b"OggS...") + + def fake_sf_read(*a, **k): raise RuntimeError("sf fail") + def fake_librosa_load(*a, **k): raise RuntimeError("librosa fail") + + monkeypatch.setattr(sf, "read", fake_sf_read, raising=True) + monkeypatch.setattr(mio.librosa, "load", fake_librosa_load, raising=True) + monkeypatch.setattr(mio, "has_ffmpeg", lambda: True, raising=True) + monkeypatch.setattr(mio, "decode_with_ffmpeg_to_float32_mono", + lambda path, target_sr: np.ones(33, dtype=np.float32), raising=True) + out = load_audio(str(p), SAMPLE_RATE) + assert out.ndim == 1 and out.dtype == np.float32 + +# ---------- ffmpeg helpers ---------- + +def test_has_ffmpeg_uses_shutil_which(monkeypatch): + # Ensure function depends on shutil.which + monkeypatch.setattr(mio.shutil, "which", lambda _: "/usr/bin/ffmpeg") + assert mio.has_ffmpeg() is True + monkeypatch.setattr(mio.shutil, "which", lambda _: None) + assert mio.has_ffmpeg() is False + +def test_decode_with_ffmpeg_to_float32_mono_monkeypatched(monkeypatch, tmp_path: Path): + # We won't call real ffmpeg; we mock subprocess.run to return a small f32 buffer. + p = tmp_path / "q.ogg" + p.write_bytes(b"OggS...") + + class DummyProc: + def __init__(self, data): self.stdout = data; self.stderr = b"" + # 4 float32 numbers -> 16 bytes; MIN_SAMPLES will trigger padding. + raw = (np.array([0.1, 0.2, 0.3, 0.4], dtype=np.float32)).tobytes() + + monkeypatch.setattr( + mio.subprocess, "run", + lambda cmd, stdout, stderr, check: DummyProc(raw), + raising=True + ) + + out = mio.decode_with_ffmpeg_to_float32_mono(str(p), mio.SAMPLE_RATE) + assert out.dtype == np.float32 + assert out.ndim == 1 + assert out.size >= mio.MIN_SAMPLES + +# ---------- ensure_checkpoint (patch urllib at global module level) ---------- + +def test_ensure_checkpoint_downloads_when_missing(monkeypatch, tmp_path): + target = tmp_path / "models" / "panns_data" / "m.pth" + called = {"ok": False} + def fake_urlretrieve(url, dst): + called["ok"] = True + Path(dst).write_bytes(b"ok") + monkeypatch.setattr("urllib.request.urlretrieve", fake_urlretrieve, raising=True) + path = ensure_checkpoint(str(target), "http://example.com/m.pth") + assert called["ok"] is True + assert Path(path).exists() + +def test_ensure_numpy_and_to_numpy_helpers(): + x = np.array([[1.0], [2.0], [3.0]], dtype=np.float32) + assert ensure_numpy_1d(x).shape == (3,) + y = _to_numpy(x.reshape(1, -1)) + assert y.ndim == 1 diff --git a/services/sounds_flink/config.py b/services/sounds_flink/config.py index 0d30cdf02..989f8677e 100644 --- a/services/sounds_flink/config.py +++ b/services/sounds_flink/config.py @@ -1,23 +1,23 @@ -import os - -# Kafka / topics -KAFKA_BROKERS = os.getenv("KAFKA_BROKERS", "kafka:9092") -SOURCE_TOPIC = os.getenv("SOURCE_TOPIC", "sound_new_sounds_connections") -SINK_TOPIC = os.getenv("SINK_TOPIC", "") # empty = print to stdout only -GROUP_ID = os.getenv("GROUP_ID", "flink-classifier-sounds") -KAFKA_START = os.getenv("KAFKA_START", "earliest") # earliest|latest - -# HTTP classifier -CLASSIFIER_HTTP_URL = os.getenv("CLASSIFIER_HTTP_URL", "http://sounds_classifier:8088/classify") -REQUEST_TIMEOUT = float(os.getenv("REQUEST_TIMEOUT", "5.0")) -RETRIES_TOTAL = int(os.getenv("RETRIES_TOTAL", "3")) -BACKOFF_FACTOR = float(os.getenv("BACKOFF_FACTOR", "0.5")) - -# Flink -DEFAULT_PARALLELISM = int(os.getenv("DEFAULT_PARALLELISM", "1")) -CHECKPOINT_MS = int(os.getenv("CHECKPOINT_MS", "10000")) # 10s -DELIVERY_GUARANTEE = os.getenv("DELIVERY_GUARANTEE", "AT_LEAST_ONCE") # AT_LEAST_ONCE|NONE -TRANSACTION_TIMEOUT_MS = os.getenv("TRANSACTION_TIMEOUT_MS", "600000") # 10 min - -# Optional default bucket to use when input only carries an object key +import os + +# Kafka / topics +KAFKA_BROKERS = os.getenv("KAFKA_BROKERS", "kafka:9092") +SOURCE_TOPIC = os.getenv("SOURCE_TOPIC", "sound_new_sounds_connections") +SINK_TOPIC = os.getenv("SINK_TOPIC", "") # empty = print to stdout only +GROUP_ID = os.getenv("GROUP_ID", "flink-classifier-sounds") +KAFKA_START = os.getenv("KAFKA_START", "earliest") # earliest|latest + +# HTTP classifier +CLASSIFIER_HTTP_URL = os.getenv("CLASSIFIER_HTTP_URL", "http://sounds_classifier:8088/classify") +REQUEST_TIMEOUT = float(os.getenv("REQUEST_TIMEOUT", "5.0")) +RETRIES_TOTAL = int(os.getenv("RETRIES_TOTAL", "3")) +BACKOFF_FACTOR = float(os.getenv("BACKOFF_FACTOR", "0.5")) + +# Flink +DEFAULT_PARALLELISM = int(os.getenv("DEFAULT_PARALLELISM", "1")) +CHECKPOINT_MS = int(os.getenv("CHECKPOINT_MS", "10000")) # 10s +DELIVERY_GUARANTEE = os.getenv("DELIVERY_GUARANTEE", "AT_LEAST_ONCE") # AT_LEAST_ONCE|NONE +TRANSACTION_TIMEOUT_MS = os.getenv("TRANSACTION_TIMEOUT_MS", "600000") # 10 min + +# Optional default bucket to use when input only carries an object key DEFAULT_BUCKET = os.getenv("DEFAULT_BUCKET", "sound") \ No newline at end of file diff --git a/services/sounds_flink/flink_job.py b/services/sounds_flink/flink_job.py index 7b42b0799..de2429cc9 100644 --- a/services/sounds_flink/flink_job.py +++ b/services/sounds_flink/flink_job.py @@ -1,83 +1,83 @@ -""" -Flink Python DataStream job: -- Kafka source (JSON notifications) -- Per-record HTTP classification via pooled Session (processor.process_json_line) -- Optional Kafka sink; if SINK_TOPIC is empty -> print to stdout -""" - -from pyflink.datastream import StreamExecutionEnvironment -from pyflink.datastream.connectors.kafka import ( - KafkaSource, KafkaSink, KafkaRecordSerializationSchema, DeliveryGuarantee -) -from pyflink.common.serialization import SimpleStringSchema -from pyflink.common.watermark_strategy import WatermarkStrategy -from pyflink.datastream.checkpointing_mode import CheckpointingMode -from pyflink.common import Types -from processor import process_json_line - -from config import ( - KAFKA_BROKERS, - SOURCE_TOPIC, - SINK_TOPIC, - GROUP_ID, - KAFKA_START, - DEFAULT_PARALLELISM, - CHECKPOINT_MS, - DELIVERY_GUARANTEE, - TRANSACTION_TIMEOUT_MS, -) - -def main(): - env = StreamExecutionEnvironment.get_execution_environment() - env.set_parallelism(DEFAULT_PARALLELISM) - env.enable_checkpointing(CHECKPOINT_MS, CheckpointingMode.EXACTLY_ONCE) - - source = ( - KafkaSource.builder() - .set_bootstrap_servers(KAFKA_BROKERS) - .set_topics(SOURCE_TOPIC) - .set_group_id(GROUP_ID) - .set_property("auto.offset.reset", KAFKA_START) - .set_value_only_deserializer(SimpleStringSchema()) - .build() - ) - - stream = env.from_source( - source, - WatermarkStrategy.no_watermarks(), - f"source-{SOURCE_TOPIC}", - ) - - mapped = stream.map(process_json_line, output_type=Types.STRING()) - filtered = mapped.filter(lambda s: bool(s and s.strip())) - - # Always print for quick debugging - filtered.name("stdout-preview").print() - - # Optional Kafka sink - if SINK_TOPIC: - guarantee = ( - DeliveryGuarantee.AT_LEAST_ONCE - if DELIVERY_GUARANTEE.upper() == "AT_LEAST_ONCE" - else DeliveryGuarantee.NONE - ) - sink = ( - KafkaSink.builder() - .set_bootstrap_servers(KAFKA_BROKERS) - .set_record_serializer( - KafkaRecordSerializationSchema.builder() - .set_topic(SINK_TOPIC) - .set_value_serialization_schema(SimpleStringSchema()) - .build() - ) - .set_delivery_guarantee(guarantee) - .set_property("transaction.timeout.ms", TRANSACTION_TIMEOUT_MS) - .build() - ) - filtered.sink_to(sink).name(f"sink-{SINK_TOPIC}") - - env.execute("flink-http-classifier") - - -if __name__ == "__main__": - main() +""" +Flink Python DataStream job: +- Kafka source (JSON notifications) +- Per-record HTTP classification via pooled Session (processor.process_json_line) +- Optional Kafka sink; if SINK_TOPIC is empty -> print to stdout +""" + +from pyflink.datastream import StreamExecutionEnvironment +from pyflink.datastream.connectors.kafka import ( + KafkaSource, KafkaSink, KafkaRecordSerializationSchema, DeliveryGuarantee +) +from pyflink.common.serialization import SimpleStringSchema +from pyflink.common.watermark_strategy import WatermarkStrategy +from pyflink.datastream.checkpointing_mode import CheckpointingMode +from pyflink.common import Types +from processor import process_json_line + +from config import ( + KAFKA_BROKERS, + SOURCE_TOPIC, + SINK_TOPIC, + GROUP_ID, + KAFKA_START, + DEFAULT_PARALLELISM, + CHECKPOINT_MS, + DELIVERY_GUARANTEE, + TRANSACTION_TIMEOUT_MS, +) + +def main(): + env = StreamExecutionEnvironment.get_execution_environment() + env.set_parallelism(DEFAULT_PARALLELISM) + env.enable_checkpointing(CHECKPOINT_MS, CheckpointingMode.EXACTLY_ONCE) + + source = ( + KafkaSource.builder() + .set_bootstrap_servers(KAFKA_BROKERS) + .set_topics(SOURCE_TOPIC) + .set_group_id(GROUP_ID) + .set_property("auto.offset.reset", KAFKA_START) + .set_value_only_deserializer(SimpleStringSchema()) + .build() + ) + + stream = env.from_source( + source, + WatermarkStrategy.no_watermarks(), + f"source-{SOURCE_TOPIC}", + ) + + mapped = stream.map(process_json_line, output_type=Types.STRING()) + filtered = mapped.filter(lambda s: bool(s and s.strip())) + + # Always print for quick debugging + filtered.name("stdout-preview").print() + + # Optional Kafka sink + if SINK_TOPIC: + guarantee = ( + DeliveryGuarantee.AT_LEAST_ONCE + if DELIVERY_GUARANTEE.upper() == "AT_LEAST_ONCE" + else DeliveryGuarantee.NONE + ) + sink = ( + KafkaSink.builder() + .set_bootstrap_servers(KAFKA_BROKERS) + .set_record_serializer( + KafkaRecordSerializationSchema.builder() + .set_topic(SINK_TOPIC) + .set_value_serialization_schema(SimpleStringSchema()) + .build() + ) + .set_delivery_guarantee(guarantee) + .set_property("transaction.timeout.ms", TRANSACTION_TIMEOUT_MS) + .build() + ) + filtered.sink_to(sink).name(f"sink-{SINK_TOPIC}") + + env.execute("flink-http-classifier") + + +if __name__ == "__main__": + main() diff --git a/services/sounds_flink/processor.py b/services/sounds_flink/processor.py index b65784e9d..1b4c77814 100644 --- a/services/sounds_flink/processor.py +++ b/services/sounds_flink/processor.py @@ -1,136 +1,136 @@ -import json -import logging -from datetime import datetime -from typing import Tuple, Optional, Dict -from urllib.parse import unquote, unquote_plus - -import requests -from requests.adapters import HTTPAdapter -from urllib3.util.retry import Retry - -from config import ( - CLASSIFIER_HTTP_URL, - REQUEST_TIMEOUT, - RETRIES_TOTAL, - BACKOFF_FACTOR, - DEFAULT_BUCKET, -) - -# Reusable HTTP session with retries/backoff -_session = requests.Session() -_retries = Retry( - total=RETRIES_TOTAL, - backoff_factor=BACKOFF_FACTOR, - status_forcelist=(429, 500, 502, 503, 504), - allowed_methods=["GET", "POST"], - respect_retry_after_header=True, -) -_session.mount("http://", HTTPAdapter(max_retries=_retries)) -_session.mount("https://", HTTPAdapter(max_retries=_retries)) - - -def _try_json(raw: str) -> Optional[Dict]: - try: - return json.loads(raw) - except Exception: - return None - - -def _extract_bucket_key(event: Dict) -> Tuple[Optional[str], Optional[str]]: - """ - Extract (bucket, key) from multiple possible MinIO/S3 event shapes. - Supports: - - short link format: {"file_name": "...", "key": "/", "linked_time": "..."} - - flat: {"Bucket": "...", "Key": "..."} - - Records[0].s3.bucket.name / Records[0].s3.object.key - """ - bucket: Optional[str] = None - key: Optional[str] = None - - # 1) Short link format (from *_connections topics): key="/" - if isinstance(event.get("key"), str): - k = event["key"].strip() - k = unquote_plus(unquote(k)) - if "/" in k: - bucket, key = k.split("/", 1) - else: - key = k # no bucket provided here - - # 2) Flat shape - if (bucket is None or key is None) and event.get("Bucket") and event.get("Key"): - bucket = bucket or event.get("Bucket") - key = key or event.get("Key") - - # 3) Records[...] S3-style - if bucket is None or key is None: - records = event.get("Records") or [] - if records: - r0 = records[0] - s3 = r0.get("s3", {}) - b = s3.get("bucket", {}) - o = s3.get("object", {}) - bucket = bucket or b.get("name") - key = key or o.get("key") - - # Normalize/URL-decode - if isinstance(key, str) and key: - key = unquote_plus(unquote(key)) - - return bucket, key - - -def _classify(bucket: Optional[str], key: Optional[str]) -> Optional[Dict]: - """ - Call the classifier service with the resolved (bucket, key). - The classifier expects: - { "s3_bucket": "...", "s3_key": "..." } - """ - if not key: - return None - - # Prefer provided bucket, otherwise fallback to DEFAULT_BUCKET if configured - eff_bucket = bucket or (DEFAULT_BUCKET if DEFAULT_BUCKET else None) - if not eff_bucket: - # Without a bucket we cannot call the classifier - return None - - payload = { - "s3_bucket": eff_bucket, - "s3_key": key, - } - - try: - resp = _session.post(CLASSIFIER_HTTP_URL, json=payload, timeout=REQUEST_TIMEOUT) - if resp.status_code >= 400: - logging.warning("Classifier returned %s for key=%s", resp.status_code, key) - return None - return resp.json() - except Exception as e: - logging.warning("Classifier request failed for key=%s: %s", key, e) - return None - - -def process_json_line(raw: str) -> str: - """ - Map function: input raw JSON string -> output JSON string or "" to skip. - 1) Parse JSON - 2) Extract (bucket, key) - 3) Call classifier (payload: s3_bucket/s3_key) - 4) Return compact JSON result or "" to drop - """ - event = _try_json(raw) - if not event: - return "" - - bucket, key = _extract_bucket_key(event) - result = _classify(bucket, key) - if not result: - return "" - - out = { - "s3_bucket": bucket or DEFAULT_BUCKET or "", - "s3_key": key, - "result": result, - "received_at": datetime.utcnow().isoformat(timespec="seconds") + "Z", - } - return json.dumps(out, separators=(",", ":")) +import json +import logging +from datetime import datetime +from typing import Tuple, Optional, Dict +from urllib.parse import unquote, unquote_plus + +import requests +from requests.adapters import HTTPAdapter +from urllib3.util.retry import Retry + +from config import ( + CLASSIFIER_HTTP_URL, + REQUEST_TIMEOUT, + RETRIES_TOTAL, + BACKOFF_FACTOR, + DEFAULT_BUCKET, +) + +# Reusable HTTP session with retries/backoff +_session = requests.Session() +_retries = Retry( + total=RETRIES_TOTAL, + backoff_factor=BACKOFF_FACTOR, + status_forcelist=(429, 500, 502, 503, 504), + allowed_methods=["GET", "POST"], + respect_retry_after_header=True, +) +_session.mount("http://", HTTPAdapter(max_retries=_retries)) +_session.mount("https://", HTTPAdapter(max_retries=_retries)) + + +def _try_json(raw: str) -> Optional[Dict]: + try: + return json.loads(raw) + except Exception: + return None + + +def _extract_bucket_key(event: Dict) -> Tuple[Optional[str], Optional[str]]: + """ + Extract (bucket, key) from multiple possible MinIO/S3 event shapes. + Supports: + - short link format: {"file_name": "...", "key": "/", "linked_time": "..."} + - flat: {"Bucket": "...", "Key": "..."} + - Records[0].s3.bucket.name / Records[0].s3.object.key + """ + bucket: Optional[str] = None + key: Optional[str] = None + + # 1) Short link format (from *_connections topics): key="/" + if isinstance(event.get("key"), str): + k = event["key"].strip() + k = unquote_plus(unquote(k)) + if "/" in k: + bucket, key = k.split("/", 1) + else: + key = k # no bucket provided here + + # 2) Flat shape + if (bucket is None or key is None) and event.get("Bucket") and event.get("Key"): + bucket = bucket or event.get("Bucket") + key = key or event.get("Key") + + # 3) Records[...] S3-style + if bucket is None or key is None: + records = event.get("Records") or [] + if records: + r0 = records[0] + s3 = r0.get("s3", {}) + b = s3.get("bucket", {}) + o = s3.get("object", {}) + bucket = bucket or b.get("name") + key = key or o.get("key") + + # Normalize/URL-decode + if isinstance(key, str) and key: + key = unquote_plus(unquote(key)) + + return bucket, key + + +def _classify(bucket: Optional[str], key: Optional[str]) -> Optional[Dict]: + """ + Call the classifier service with the resolved (bucket, key). + The classifier expects: + { "s3_bucket": "...", "s3_key": "..." } + """ + if not key: + return None + + # Prefer provided bucket, otherwise fallback to DEFAULT_BUCKET if configured + eff_bucket = bucket or (DEFAULT_BUCKET if DEFAULT_BUCKET else None) + if not eff_bucket: + # Without a bucket we cannot call the classifier + return None + + payload = { + "s3_bucket": eff_bucket, + "s3_key": key, + } + + try: + resp = _session.post(CLASSIFIER_HTTP_URL, json=payload, timeout=REQUEST_TIMEOUT) + if resp.status_code >= 400: + logging.warning("Classifier returned %s for key=%s", resp.status_code, key) + return None + return resp.json() + except Exception as e: + logging.warning("Classifier request failed for key=%s: %s", key, e) + return None + + +def process_json_line(raw: str) -> str: + """ + Map function: input raw JSON string -> output JSON string or "" to skip. + 1) Parse JSON + 2) Extract (bucket, key) + 3) Call classifier (payload: s3_bucket/s3_key) + 4) Return compact JSON result or "" to drop + """ + event = _try_json(raw) + if not event: + return "" + + bucket, key = _extract_bucket_key(event) + result = _classify(bucket, key) + if not result: + return "" + + out = { + "s3_bucket": bucket or DEFAULT_BUCKET or "", + "s3_key": key, + "result": result, + "received_at": datetime.utcnow().isoformat(timespec="seconds") + "Z", + } + return json.dumps(out, separators=(",", ":")) diff --git a/services/sounds_flink/requirements.txt b/services/sounds_flink/requirements.txt index bb811ad65..f5de43b68 100644 --- a/services/sounds_flink/requirements.txt +++ b/services/sounds_flink/requirements.txt @@ -1,6 +1,6 @@ -apache-flink==1.19.3 -requests==2.32.3 -urllib3==2.2.3 -protobuf==4.25.3 -googleapis-common-protos==1.63.0 -grpcio==1.60.0 +apache-flink==1.19.3 +requests==2.32.3 +urllib3==2.2.3 +protobuf==4.25.3 +googleapis-common-protos==1.63.0 +grpcio==1.60.0 diff --git a/services/tests/test_db_upsert.py b/services/tests/test_db_upsert.py new file mode 100644 index 000000000..15d5ec27f --- /dev/null +++ b/services/tests/test_db_upsert.py @@ -0,0 +1,25 @@ +# services/rover_ingest/tests/test_db_upsert.py +import os +import pytest +from services.rover_ingest.db import upsert +from services.rover_ingest.schema import ImageMeta +from services.rover_ingest import storage_minio + +requires_db = pytest.mark.skipif( + not os.getenv("PG_DSN"), reason="PG_DSN not set" +) + +@requires_db +def test_upsert_idempotent(monkeypatch): + monkeypatch.setattr(storage_minio, "object_exists", lambda key: True) + meta = ImageMeta.model_validate({ + "schema_ver": 1, + "device_id": "rover-07", + "image_id": "20250910T101500Z-abc123", + "captured_at": "2025-09-10T10:15:00Z", + "gps": {"lat": 31.7, "lon": 35.2}, + "s3_key": "rover-07/2025/09/10/20250910T101500Z-abc123.jpg", + "meta_src": "manifest", + }) + upsert(meta) + upsert(meta) \ No newline at end of file diff --git a/services/tests/test_metrics.py b/services/tests/test_metrics.py new file mode 100644 index 000000000..864522304 --- /dev/null +++ b/services/tests/test_metrics.py @@ -0,0 +1,26 @@ +# services/rover_ingest/tests/test_metrics.py +from services.rover_ingest.app import handle_message, INGEST_OK, INGEST_FAIL +from services.rover_ingest import storage_minio +from services.rover_ingest.db import upsert + +def test_handle_message_increments_success(monkeypatch): + payload = { + "schema_ver": 1, + "device_id": "rover-07", + "image_id": "20250910T101500Z-abc123", + "captured_at": "2025-09-10T10:15:00Z", + "gps": {"lat": 31.7, "lon": 35.2}, + "s3_key": "rover-07/2025/09/10/20250910T101500Z-abc123.jpg", + "meta_src": "manifest", + } + monkeypatch.setattr(storage_minio, "object_exists", lambda key: True) + called = {"n": 0} + monkeypatch.setattr("services.rover_ingest.db.upsert", lambda meta: None) + + before_ok = INGEST_OK._value.get() + before_fail = INGEST_FAIL._value.get() + + handle_message(payload) + + assert INGEST_OK._value.get() == before_ok + 1 + assert INGEST_FAIL._value.get() == before_fail diff --git a/services/tests/test_schema.py b/services/tests/test_schema.py new file mode 100644 index 000000000..a1ae80750 --- /dev/null +++ b/services/tests/test_schema.py @@ -0,0 +1,48 @@ +# from services.rover_ingest.schema import ImageMeta + +# def test_parse_valid_minimal(): +# payload = { +# "schema_ver": 1, +# "device_id": "r1", +# "image_id": "img-1", +# "captured_at": "2025-01-01T10:00:00Z", +# "gps": {"lat": 31.0, "lon": 35.0}, +# "heading_deg": 370.0, +# "alt_m": 1.2, +# "s3_key": "rover-images/r1/2025/01/01/img-1.jpg", +# "meta_src": "manifest" +# } +# meta = ImageMeta.parse_obj(payload) +# assert 0.0 <= meta.heading_deg < 360.0 + +# def test_missing_required_raises(): +# bad = {"device_id": "r1"} +# try: +# ImageMeta.parse_obj(bad) +# assert False, "expected validation error" +# except Exception: +# assert True + +# services/rover_ingest/tests/test_schema.py +import datetime as dt +import pytest +from pydantic import BaseModel, field_validator +from services.rover_ingest.schema import ImageMeta + +def test_valid_payload_parses(): + payload = { + "schema_ver": 1, + "device_id": "rover-07", + "image_id": "20250910T101500Z-abc123", + "captured_at": "2025-09-10T10:15:00Z", + "gps": {"lat": 31.7767, "lon": 35.2345}, + "s3_key": "rover-07/2025/09/10/20250910T101500Z-abc123.jpg", + "meta_src": "manifest", + } + m = ImageMeta.model_validate(payload) + assert m.device_id == "rover-07" + assert m.captured_at.tzinfo is not None + +def test_missing_required_field_fails(): + with pytest.raises(Exception): + ImageMeta.model_validate({"schema_ver": 1}) diff --git a/services/tests/test_validators.py b/services/tests/test_validators.py new file mode 100644 index 000000000..96c82d119 --- /dev/null +++ b/services/tests/test_validators.py @@ -0,0 +1,31 @@ +import pytest +from types import SimpleNamespace +from services.rover_ingest.validators import validate_semantics + +def test_validate_semantics_passes_when_object_exists(monkeypatch): + meta = SimpleNamespace( + device_id="rover-07", + s3_key="rover-07/2025/09/10/20250910T101500Z-abc123.jpg", + gps=SimpleNamespace(lat=31.7, lon=35.2), + captured_at=None + ) + monkeypatch.setenv("MINIO_BUCKET", "rover-images") + monkeypatch.setenv("MINIO_ENDPOINT", "dummy:9000") + + from services.rover_ingest import storage_minio + monkeypatch.setattr(storage_minio, "object_exists", lambda key: True) + + validate_semantics(meta) + +def test_validate_semantics_raises_when_missing_object(monkeypatch): + meta = SimpleNamespace( + device_id="rover-07", + s3_key="missing.jpg", + gps=SimpleNamespace(lat=31.7, lon=35.2), + captured_at=None + ) + from services.rover_ingest import storage_minio + monkeypatch.setattr(storage_minio, "object_exists", lambda key: False) + + with pytest.raises(FileNotFoundError): + validate_semantics(meta) diff --git a/services/vector_service/Dockerfile b/services/vector_service/Dockerfile new file mode 100644 index 000000000..1ee96b19d --- /dev/null +++ b/services/vector_service/Dockerfile @@ -0,0 +1,11 @@ +FROM python:3.11-slim + +WORKDIR /app +COPY . /app + +RUN pip install fastapi uvicorn asyncpg numpy + +EXPOSE 8000 + +CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"] + diff --git a/services/vector_service/README b/services/vector_service/README new file mode 100644 index 000000000..0ed58aca6 --- /dev/null +++ b/services/vector_service/README @@ -0,0 +1,184 @@ +========================================= +README – Sensor Embeddings Search System +========================================= + +📘 Overview +----------- +This project implements an AI-powered similarity search system +based on **sensor embeddings** stored in PostgreSQL with the `pgvector` extension. + +It allows: +- Creating embeddings for sensors from the `sensors` table. +- Storing embeddings in the `embeddings` table. +- Searching for similar sensors based on vector similarity. +- Running advanced, filtered similarity queries (by date, type, status). + +------------------------------------------ +📦 Database Schema +------------------------------------------ + +CREATE TABLE sensors ( + id SERIAL PRIMARY KEY, + sensor TEXT UNIQUE NOT NULL, + sensor_type TEXT NOT NULL, + owner_name TEXT, + lat DOUBLE PRECISION, + lon DOUBLE PRECISION, + install_date TIMESTAMP DEFAULT NOW(), + status TEXT DEFAULT 'active', + description TEXT, + last_maintenance TIMESTAMP +); + +CREATE TABLE embeddings ( + id BIGSERIAL PRIMARY KEY, + sensor_id INT REFERENCES sensors(id) ON DELETE CASCADE, + vec vector(5) +); + +------------------------------------------ +🚀 How to Run +------------------------------------------ + +1️⃣ Start Docker containers: + docker compose up postgres vector_service + +2️⃣ Check that the API is live: + http://localhost:8005/docs + +3️⃣ Generate embeddings from sensors: + Invoke-RestMethod -Method Post -Uri "http://localhost:8005/generate_embeddings_from_sensors" + +4️⃣ Verify data: + docker exec -it postgres psql -U missions_user -d missions_db + SELECT COUNT(*) FROM embeddings; + +------------------------------------------ +🔍 Main API Endpoints with Examples +------------------------------------------ + +------------------------------------------ +1️⃣ Generate Embeddings +------------------------------------------ +Creates embeddings for all sensors in the database. + +PowerShell: +Invoke-RestMethod -Method Post -Uri "http://localhost:8005/generate_embeddings_from_sensors" + +------------------------------------------ +2️⃣ Search by Vector +------------------------------------------ +Finds embeddings most similar to the provided vector. + +PowerShell: +Invoke-RestMethod -Method Post -Uri "http://localhost:8005/search" ` + -Headers @{ "Content-Type" = "application/json" } ` + -Body '[31.7,34.8,9,5,1]' | ConvertTo-Json -Depth 5 + +------------------------------------------ +3️⃣ Find Similar Sensors by Sensor ID +------------------------------------------ +Returns sensors most similar to a specific sensor. + +PowerShell: +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors/2" | ConvertTo-Json -Depth 5 + +------------------------------------------ +4️⃣ Advanced Similarity Search +------------------------------------------ +Flexible endpoint supporting multiple filters. + +🔹 Base query (no filters) +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28" ` + | ConvertTo-Json -Depth 5 + +🔹 Same day only +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&same_day=true" ` + | ConvertTo-Json -Depth 5 + +🔹 Same day + same type +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&same_day=true&same_type=true" ` + | ConvertTo-Json -Depth 5 + +🔹 Same day + same type + same status +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&same_day=true&same_type=true&same_status=true" ` + | ConvertTo-Json -Depth 5 + +🔹sensors installed on Wednesday +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&date_filter=wednesday" ` + | ConvertTo-Json -Depth 5 + +🔹sensors installed on last Wednesday +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&date_filter=last_wednesday&same_type=true" ` + | ConvertTo-Json -Depth 5 +------------------------------------------ +📊 SQL Examples +------------------------------------------ + +-- Show all sensors: +SELECT id, sensor_name, install_date FROM sensors; + +-- Insert two sensors with the same installation day: +INSERT INTO sensors (sensor_name, sensor_type, owner_name, lat, lon, install_date, status) +VALUES +('TestSensor_A', 'temperature', 'Dana', 31.771, 34.790, '2025-10-26 09:00:00', 'active'), +('TestSensor_B', 'temperature', 'Dana', 31.772, 34.792, '2025-10-26 11:00:00', 'active'); + +-- Generate embeddings for the new sensors: +Invoke-RestMethod -Method Post -Uri "http://localhost:8005/generate_embeddings_from_sensors" + +-- Verify embeddings: +SELECT e.sensor_id, s.sensor_name, s.sensor_type, e.vec::text +FROM embeddings e +JOIN sensors s ON e.sensor_id = s.id; + +------------------------------------------ +🧠 Example JSON Output +------------------------------------------ + +{ + "base_sensor": { + "sensor_id": 28, + "sensor_name": "SoilTemp02", + "sensor_type": "temperature", + "install_date": "2025-10-25T09:00:00Z", + "status": "active" + }, + "criteria": { + "same_day": true, + "same_type": true, + "same_status": true + }, + "similar_sensors": [ + { + "sensor_id": 31, + "distance": 1.83, + "sensor_name": "SoilTemp05", + "sensor_type": "temperature", + "install_date": "2025-10-25T11:00:00Z", + "status": "active" + }, + { + "sensor_id": 33, + "distance": 3.44, + "sensor_name": "SoilTemp07", + "sensor_type": "temperature", + "install_date": "2025-10-25T08:00:00Z", + "status": "active" + } + ] +} + +------------------------------------------ +📌 Summary +------------------------------------------ +✔ End-to-end embedding pipeline for sensors +✔ PostgreSQL vector search using `pgvector` +✔ Smart similarity filtering by: + • Same day + • Same type + • Same status +✔ All queries available through one generic endpoint: + `/similar_sensors_advanced` + +========================================= diff --git a/services/vector_service/main.py b/services/vector_service/main.py new file mode 100644 index 000000000..1b33713b8 --- /dev/null +++ b/services/vector_service/main.py @@ -0,0 +1,324 @@ +from fastapi import FastAPI, HTTPException +import asyncpg +import numpy as np +import os +from datetime import datetime, timedelta + +app = FastAPI() + +DB_HOST = os.getenv("DB_HOST", "postgres") +DB_PORT = int(os.getenv("DB_PORT", 5432)) +DB_USER = os.getenv("DB_USER", "missions_user") +DB_PASS = os.getenv("DB_PASS", "pg123") +DB_NAME = os.getenv("DB_NAME", "missions_db") + + +# ========================================================= +# STARTUP – CREATE CONNECTION POOL (SAFE) +# ========================================================= +@app.on_event("startup") +async def startup(): + print("⏳ Creating Postgres pool...") + try: + app.state.pool = await asyncpg.create_pool( + user=DB_USER, + password=DB_PASS, + host=DB_HOST, + port=DB_PORT, + database=DB_NAME, + min_size=1, + max_size=10, + ) + # ensure pgvector exists + async with app.state.pool.acquire() as conn: + await conn.execute("CREATE EXTENSION IF NOT EXISTS vector;") + + print("✅ Postgres connection pool ready.") + except Exception as e: + print(f"❌ Failed to connect to Postgres: {e}") + raise + + +@app.on_event("shutdown") +async def shutdown(): + await app.state.pool.close() + print("🛑 Connection pool closed") + + +# ========================================================= +# Helper: Validate Embedding Vector +# ========================================================= +def validate_vector(vec): + if not isinstance(vec, list): + raise HTTPException(400, "Vector must be a list of floats.") + if len(vec) != 5: + raise HTTPException(400, "Embedding vector must be length 5.") + try: + return [float(x) for x in vec] + except: + raise HTTPException(400, "Vector contains non-numeric values.") + + + +# ========================================================= +# INSERT VECTOR (sensor_embeddings) +# ========================================================= +@app.post("/add_embedding") +async def add_embedding(sensor_id: int, vector: list[float]): + vec = validate_vector(vector) + vec_str = "[" + ",".join(str(x) for x in vec) + "]" + + async with app.state.pool.acquire() as conn: + await conn.execute( + """ + INSERT INTO sensor_embeddings (sensor_id, vec) + VALUES ($1, $2::vector) + """, + sensor_id, vec_str + ) + + return {"status": "ok"} + + + +# ========================================================= +# VECTOR SEARCH +# ========================================================= +@app.post("/search") +async def search(vector: list[float], limit: int = 5): + vec = validate_vector(vector) + vec_str = "[" + ",".join(str(x) for x in vec) + "]" + + async with app.state.pool.acquire() as conn: + rows = await conn.fetch( + """ + SELECT id, vec <-> $1::vector AS distance + FROM sensor_embeddings + ORDER BY distance + LIMIT $2; + """, + vec_str, limit + ) + + return {"results": [{"id": r["id"], "distance": r["distance"]} for r in rows]} + + + +# ========================================================= +# GENERATE EMBEDDINGS FROM SENSORS +# ========================================================= +@app.post("/generate_embeddings_from_sensors") +async def generate_embeddings_from_sensors(): + + async with app.state.pool.acquire() as conn: + rows = await conn.fetch( + """ + SELECT sensor_id, sensor_name, sensor_type, lat, lon, status + FROM sensors; + """ + ) + + if not rows: + return {"message": "No sensors found."} + + inserted = 0 + + for r in rows: + sensor_id = r["sensor_id"] + name_len = len(r["sensor_name"] or "") + type_len = len(r["sensor_type"] or "") + lat = r["lat"] or 0.0 + lon = r["lon"] or 0.0 + status_score = 1.0 if (r["status"] or "").lower() == "active" else 0.0 + + # vector(5) is still your default + vector = np.array([lat, lon, name_len, type_len, status_score], dtype=float) + vec_str = "[" + ",".join(str(x) for x in vector) + "]" + + await conn.execute( + """ + INSERT INTO sensor_embeddings (sensor_id, vec) + VALUES ($1, $2::vector) + """, + sensor_id, vec_str + ) + inserted += 1 + + print(f"✅ {inserted} embeddings created.") + return {"message": f"{inserted} embeddings generated."} + + + +# ========================================================= +# FIND SIMILAR SENSORS BY SENSOR ID +# ========================================================= +@app.get("/similar_sensors/{sensor_id}") +async def similar_sensors(sensor_id: int, limit: int = 5): + + async with app.state.pool.acquire() as conn: + + row = await conn.fetchrow( + "SELECT vec FROM sensor_embeddings WHERE sensor_id=$1;", + sensor_id + ) + if not row: + return {"message": f"No embedding found for sensor_id {sensor_id}"} + + vec = row["vec"] + + results = await conn.fetch( + """ + SELECT e.sensor_id, e.vec <-> $1 AS distance, + s.sensor_name, s.sensor_type, s.lat, s.lon, s.status + FROM sensor_embeddings e + JOIN sensors s ON e.sensor_id = s.sensor_id + WHERE e.sensor_id <> $2 + ORDER BY distance + LIMIT $3; + """, + vec, sensor_id, limit + ) + + return { + "similar_sensors": [ + { + "sensor_id": r["sensor_id"], + "distance": r["distance"], + "sensor_name": r["sensor_name"], + "sensor_type": r["sensor_type"], + "lat": r["lat"], + "lon": r["lon"], + "status": r["status"] + } + for r in results + ] + } + + + +# ========================================================= +# ADVANCED SIMILARITY SEARCH +# ========================================================= +@app.get("/similar_sensors_advanced") +async def similar_sensors_advanced( + sensor_id: int, + same_day: bool = False, + same_type: bool = False, + same_status: bool = False, + date_filter: str = None, + limit: int = 5 +): + + async with app.state.pool.acquire() as conn: + + sensor = await conn.fetchrow("SELECT * FROM sensors WHERE sensor_id=$1;", sensor_id) + if not sensor: + return {"message": f"Sensor {sensor_id} not found."} + + base_date = sensor["install_date"].date() + sensor_type = sensor["sensor_type"] + status = sensor["status"] + + row = await conn.fetchrow( + "SELECT vec FROM sensor_embeddings WHERE sensor_id=$1;", + sensor_id + ) + if not row: + return {"message": f"No embedding found for sensor {sensor_id}."} + + vec = row["vec"] + + # --- date logic --- + today = datetime.utcnow().date() + weekdays = { + "monday": 0, "tuesday": 1, "wednesday": 2, + "thursday": 3, "friday": 4, "saturday": 5, "sunday": 6 + } + + start_date = end_date = None + + if date_filter: + df = date_filter.lower() + + if df == "today": + start_date = end_date = today + + elif df == "yesterday": + start_date = end_date = today - timedelta(days=1) + + elif df.startswith("last_"): + day = df.replace("last_", "") + if day in weekdays: + today_wd = today.weekday() + days_back = (today_wd - weekdays[day] + 7) % 7 + 7 + target = today - timedelta(days=days_back) + start_date = end_date = target + + elif df in weekdays: + today_wd = today.weekday() + days_back = (today_wd - weekdays[df] + 7) % 7 + target = today - timedelta(days=days_back) + start_date = end_date = target + + # Base query + query = """ + SELECT e.sensor_id, e.vec <-> $1 AS distance, + s.sensor_name, s.sensor_type, s.install_date, s.status + FROM sensor_embeddings e + JOIN sensors s ON e.sensor_id = s.sensor_id + WHERE e.sensor_id <> $2 + """ + params = [vec, sensor_id] + idx = 3 + + if same_day: + query += f" AND DATE(s.install_date) = ${idx}" + params.append(base_date) + idx += 1 + + if same_type: + query += f" AND s.sensor_type = ${idx}" + params.append(sensor_type) + idx += 1 + + if same_status: + query += f" AND s.status = ${idx}" + params.append(status) + idx += 1 + + if start_date and end_date: + query += f" AND DATE(s.install_date) BETWEEN ${idx} AND ${idx+1}" + params.extend([start_date, end_date]) + idx += 2 + + query += f" ORDER BY distance LIMIT ${idx}" + params.append(limit) + + results = await conn.fetch(query, *params) + + return { + "base_sensor": { + "sensor_id": sensor_id, + "sensor_name": sensor["sensor_name"], + "sensor_type": sensor_type, + "install_date": str(sensor["install_date"]), + "status": status + }, + "filters": { + "same_day": same_day, + "same_type": same_type, + "same_status": same_status, + "date_filter": date_filter + }, + "similar_sensors": [ + { + "sensor_id": r["sensor_id"], + "distance": r["distance"], + "sensor_name": r["sensor_name"], + "sensor_type": r["sensor_type"], + "install_date": str(r["install_date"]), + "status": r["status"] + } + for r in results + ] + } diff --git a/services/vector_service/vector_service/Dockerfile b/services/vector_service/vector_service/Dockerfile new file mode 100644 index 000000000..1ee96b19d --- /dev/null +++ b/services/vector_service/vector_service/Dockerfile @@ -0,0 +1,11 @@ +FROM python:3.11-slim + +WORKDIR /app +COPY . /app + +RUN pip install fastapi uvicorn asyncpg numpy + +EXPOSE 8000 + +CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"] + diff --git a/services/vector_service/vector_service/README b/services/vector_service/vector_service/README new file mode 100644 index 000000000..0ed58aca6 --- /dev/null +++ b/services/vector_service/vector_service/README @@ -0,0 +1,184 @@ +========================================= +README – Sensor Embeddings Search System +========================================= + +📘 Overview +----------- +This project implements an AI-powered similarity search system +based on **sensor embeddings** stored in PostgreSQL with the `pgvector` extension. + +It allows: +- Creating embeddings for sensors from the `sensors` table. +- Storing embeddings in the `embeddings` table. +- Searching for similar sensors based on vector similarity. +- Running advanced, filtered similarity queries (by date, type, status). + +------------------------------------------ +📦 Database Schema +------------------------------------------ + +CREATE TABLE sensors ( + id SERIAL PRIMARY KEY, + sensor TEXT UNIQUE NOT NULL, + sensor_type TEXT NOT NULL, + owner_name TEXT, + lat DOUBLE PRECISION, + lon DOUBLE PRECISION, + install_date TIMESTAMP DEFAULT NOW(), + status TEXT DEFAULT 'active', + description TEXT, + last_maintenance TIMESTAMP +); + +CREATE TABLE embeddings ( + id BIGSERIAL PRIMARY KEY, + sensor_id INT REFERENCES sensors(id) ON DELETE CASCADE, + vec vector(5) +); + +------------------------------------------ +🚀 How to Run +------------------------------------------ + +1️⃣ Start Docker containers: + docker compose up postgres vector_service + +2️⃣ Check that the API is live: + http://localhost:8005/docs + +3️⃣ Generate embeddings from sensors: + Invoke-RestMethod -Method Post -Uri "http://localhost:8005/generate_embeddings_from_sensors" + +4️⃣ Verify data: + docker exec -it postgres psql -U missions_user -d missions_db + SELECT COUNT(*) FROM embeddings; + +------------------------------------------ +🔍 Main API Endpoints with Examples +------------------------------------------ + +------------------------------------------ +1️⃣ Generate Embeddings +------------------------------------------ +Creates embeddings for all sensors in the database. + +PowerShell: +Invoke-RestMethod -Method Post -Uri "http://localhost:8005/generate_embeddings_from_sensors" + +------------------------------------------ +2️⃣ Search by Vector +------------------------------------------ +Finds embeddings most similar to the provided vector. + +PowerShell: +Invoke-RestMethod -Method Post -Uri "http://localhost:8005/search" ` + -Headers @{ "Content-Type" = "application/json" } ` + -Body '[31.7,34.8,9,5,1]' | ConvertTo-Json -Depth 5 + +------------------------------------------ +3️⃣ Find Similar Sensors by Sensor ID +------------------------------------------ +Returns sensors most similar to a specific sensor. + +PowerShell: +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors/2" | ConvertTo-Json -Depth 5 + +------------------------------------------ +4️⃣ Advanced Similarity Search +------------------------------------------ +Flexible endpoint supporting multiple filters. + +🔹 Base query (no filters) +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28" ` + | ConvertTo-Json -Depth 5 + +🔹 Same day only +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&same_day=true" ` + | ConvertTo-Json -Depth 5 + +🔹 Same day + same type +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&same_day=true&same_type=true" ` + | ConvertTo-Json -Depth 5 + +🔹 Same day + same type + same status +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&same_day=true&same_type=true&same_status=true" ` + | ConvertTo-Json -Depth 5 + +🔹sensors installed on Wednesday +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&date_filter=wednesday" ` + | ConvertTo-Json -Depth 5 + +🔹sensors installed on last Wednesday +Invoke-RestMethod -Uri "http://localhost:8005/similar_sensors_advanced?sensor_id=28&date_filter=last_wednesday&same_type=true" ` + | ConvertTo-Json -Depth 5 +------------------------------------------ +📊 SQL Examples +------------------------------------------ + +-- Show all sensors: +SELECT id, sensor_name, install_date FROM sensors; + +-- Insert two sensors with the same installation day: +INSERT INTO sensors (sensor_name, sensor_type, owner_name, lat, lon, install_date, status) +VALUES +('TestSensor_A', 'temperature', 'Dana', 31.771, 34.790, '2025-10-26 09:00:00', 'active'), +('TestSensor_B', 'temperature', 'Dana', 31.772, 34.792, '2025-10-26 11:00:00', 'active'); + +-- Generate embeddings for the new sensors: +Invoke-RestMethod -Method Post -Uri "http://localhost:8005/generate_embeddings_from_sensors" + +-- Verify embeddings: +SELECT e.sensor_id, s.sensor_name, s.sensor_type, e.vec::text +FROM embeddings e +JOIN sensors s ON e.sensor_id = s.id; + +------------------------------------------ +🧠 Example JSON Output +------------------------------------------ + +{ + "base_sensor": { + "sensor_id": 28, + "sensor_name": "SoilTemp02", + "sensor_type": "temperature", + "install_date": "2025-10-25T09:00:00Z", + "status": "active" + }, + "criteria": { + "same_day": true, + "same_type": true, + "same_status": true + }, + "similar_sensors": [ + { + "sensor_id": 31, + "distance": 1.83, + "sensor_name": "SoilTemp05", + "sensor_type": "temperature", + "install_date": "2025-10-25T11:00:00Z", + "status": "active" + }, + { + "sensor_id": 33, + "distance": 3.44, + "sensor_name": "SoilTemp07", + "sensor_type": "temperature", + "install_date": "2025-10-25T08:00:00Z", + "status": "active" + } + ] +} + +------------------------------------------ +📌 Summary +------------------------------------------ +✔ End-to-end embedding pipeline for sensors +✔ PostgreSQL vector search using `pgvector` +✔ Smart similarity filtering by: + • Same day + • Same type + • Same status +✔ All queries available through one generic endpoint: + `/similar_sensors_advanced` + +========================================= diff --git a/services/vector_service/vector_service/main.py b/services/vector_service/vector_service/main.py new file mode 100644 index 000000000..1b33713b8 --- /dev/null +++ b/services/vector_service/vector_service/main.py @@ -0,0 +1,324 @@ +from fastapi import FastAPI, HTTPException +import asyncpg +import numpy as np +import os +from datetime import datetime, timedelta + +app = FastAPI() + +DB_HOST = os.getenv("DB_HOST", "postgres") +DB_PORT = int(os.getenv("DB_PORT", 5432)) +DB_USER = os.getenv("DB_USER", "missions_user") +DB_PASS = os.getenv("DB_PASS", "pg123") +DB_NAME = os.getenv("DB_NAME", "missions_db") + + +# ========================================================= +# STARTUP – CREATE CONNECTION POOL (SAFE) +# ========================================================= +@app.on_event("startup") +async def startup(): + print("⏳ Creating Postgres pool...") + try: + app.state.pool = await asyncpg.create_pool( + user=DB_USER, + password=DB_PASS, + host=DB_HOST, + port=DB_PORT, + database=DB_NAME, + min_size=1, + max_size=10, + ) + # ensure pgvector exists + async with app.state.pool.acquire() as conn: + await conn.execute("CREATE EXTENSION IF NOT EXISTS vector;") + + print("✅ Postgres connection pool ready.") + except Exception as e: + print(f"❌ Failed to connect to Postgres: {e}") + raise + + +@app.on_event("shutdown") +async def shutdown(): + await app.state.pool.close() + print("🛑 Connection pool closed") + + +# ========================================================= +# Helper: Validate Embedding Vector +# ========================================================= +def validate_vector(vec): + if not isinstance(vec, list): + raise HTTPException(400, "Vector must be a list of floats.") + if len(vec) != 5: + raise HTTPException(400, "Embedding vector must be length 5.") + try: + return [float(x) for x in vec] + except: + raise HTTPException(400, "Vector contains non-numeric values.") + + + +# ========================================================= +# INSERT VECTOR (sensor_embeddings) +# ========================================================= +@app.post("/add_embedding") +async def add_embedding(sensor_id: int, vector: list[float]): + vec = validate_vector(vector) + vec_str = "[" + ",".join(str(x) for x in vec) + "]" + + async with app.state.pool.acquire() as conn: + await conn.execute( + """ + INSERT INTO sensor_embeddings (sensor_id, vec) + VALUES ($1, $2::vector) + """, + sensor_id, vec_str + ) + + return {"status": "ok"} + + + +# ========================================================= +# VECTOR SEARCH +# ========================================================= +@app.post("/search") +async def search(vector: list[float], limit: int = 5): + vec = validate_vector(vector) + vec_str = "[" + ",".join(str(x) for x in vec) + "]" + + async with app.state.pool.acquire() as conn: + rows = await conn.fetch( + """ + SELECT id, vec <-> $1::vector AS distance + FROM sensor_embeddings + ORDER BY distance + LIMIT $2; + """, + vec_str, limit + ) + + return {"results": [{"id": r["id"], "distance": r["distance"]} for r in rows]} + + + +# ========================================================= +# GENERATE EMBEDDINGS FROM SENSORS +# ========================================================= +@app.post("/generate_embeddings_from_sensors") +async def generate_embeddings_from_sensors(): + + async with app.state.pool.acquire() as conn: + rows = await conn.fetch( + """ + SELECT sensor_id, sensor_name, sensor_type, lat, lon, status + FROM sensors; + """ + ) + + if not rows: + return {"message": "No sensors found."} + + inserted = 0 + + for r in rows: + sensor_id = r["sensor_id"] + name_len = len(r["sensor_name"] or "") + type_len = len(r["sensor_type"] or "") + lat = r["lat"] or 0.0 + lon = r["lon"] or 0.0 + status_score = 1.0 if (r["status"] or "").lower() == "active" else 0.0 + + # vector(5) is still your default + vector = np.array([lat, lon, name_len, type_len, status_score], dtype=float) + vec_str = "[" + ",".join(str(x) for x in vector) + "]" + + await conn.execute( + """ + INSERT INTO sensor_embeddings (sensor_id, vec) + VALUES ($1, $2::vector) + """, + sensor_id, vec_str + ) + inserted += 1 + + print(f"✅ {inserted} embeddings created.") + return {"message": f"{inserted} embeddings generated."} + + + +# ========================================================= +# FIND SIMILAR SENSORS BY SENSOR ID +# ========================================================= +@app.get("/similar_sensors/{sensor_id}") +async def similar_sensors(sensor_id: int, limit: int = 5): + + async with app.state.pool.acquire() as conn: + + row = await conn.fetchrow( + "SELECT vec FROM sensor_embeddings WHERE sensor_id=$1;", + sensor_id + ) + if not row: + return {"message": f"No embedding found for sensor_id {sensor_id}"} + + vec = row["vec"] + + results = await conn.fetch( + """ + SELECT e.sensor_id, e.vec <-> $1 AS distance, + s.sensor_name, s.sensor_type, s.lat, s.lon, s.status + FROM sensor_embeddings e + JOIN sensors s ON e.sensor_id = s.sensor_id + WHERE e.sensor_id <> $2 + ORDER BY distance + LIMIT $3; + """, + vec, sensor_id, limit + ) + + return { + "similar_sensors": [ + { + "sensor_id": r["sensor_id"], + "distance": r["distance"], + "sensor_name": r["sensor_name"], + "sensor_type": r["sensor_type"], + "lat": r["lat"], + "lon": r["lon"], + "status": r["status"] + } + for r in results + ] + } + + + +# ========================================================= +# ADVANCED SIMILARITY SEARCH +# ========================================================= +@app.get("/similar_sensors_advanced") +async def similar_sensors_advanced( + sensor_id: int, + same_day: bool = False, + same_type: bool = False, + same_status: bool = False, + date_filter: str = None, + limit: int = 5 +): + + async with app.state.pool.acquire() as conn: + + sensor = await conn.fetchrow("SELECT * FROM sensors WHERE sensor_id=$1;", sensor_id) + if not sensor: + return {"message": f"Sensor {sensor_id} not found."} + + base_date = sensor["install_date"].date() + sensor_type = sensor["sensor_type"] + status = sensor["status"] + + row = await conn.fetchrow( + "SELECT vec FROM sensor_embeddings WHERE sensor_id=$1;", + sensor_id + ) + if not row: + return {"message": f"No embedding found for sensor {sensor_id}."} + + vec = row["vec"] + + # --- date logic --- + today = datetime.utcnow().date() + weekdays = { + "monday": 0, "tuesday": 1, "wednesday": 2, + "thursday": 3, "friday": 4, "saturday": 5, "sunday": 6 + } + + start_date = end_date = None + + if date_filter: + df = date_filter.lower() + + if df == "today": + start_date = end_date = today + + elif df == "yesterday": + start_date = end_date = today - timedelta(days=1) + + elif df.startswith("last_"): + day = df.replace("last_", "") + if day in weekdays: + today_wd = today.weekday() + days_back = (today_wd - weekdays[day] + 7) % 7 + 7 + target = today - timedelta(days=days_back) + start_date = end_date = target + + elif df in weekdays: + today_wd = today.weekday() + days_back = (today_wd - weekdays[df] + 7) % 7 + target = today - timedelta(days=days_back) + start_date = end_date = target + + # Base query + query = """ + SELECT e.sensor_id, e.vec <-> $1 AS distance, + s.sensor_name, s.sensor_type, s.install_date, s.status + FROM sensor_embeddings e + JOIN sensors s ON e.sensor_id = s.sensor_id + WHERE e.sensor_id <> $2 + """ + params = [vec, sensor_id] + idx = 3 + + if same_day: + query += f" AND DATE(s.install_date) = ${idx}" + params.append(base_date) + idx += 1 + + if same_type: + query += f" AND s.sensor_type = ${idx}" + params.append(sensor_type) + idx += 1 + + if same_status: + query += f" AND s.status = ${idx}" + params.append(status) + idx += 1 + + if start_date and end_date: + query += f" AND DATE(s.install_date) BETWEEN ${idx} AND ${idx+1}" + params.extend([start_date, end_date]) + idx += 2 + + query += f" ORDER BY distance LIMIT ${idx}" + params.append(limit) + + results = await conn.fetch(query, *params) + + return { + "base_sensor": { + "sensor_id": sensor_id, + "sensor_name": sensor["sensor_name"], + "sensor_type": sensor_type, + "install_date": str(sensor["install_date"]), + "status": status + }, + "filters": { + "same_day": same_day, + "same_type": same_type, + "same_status": same_status, + "date_filter": date_filter + }, + "similar_sensors": [ + { + "sensor_id": r["sensor_id"], + "distance": r["distance"], + "sensor_name": r["sensor_name"], + "sensor_type": r["sensor_type"], + "install_date": str(r["install_date"]), + "status": r["status"] + } + for r in results + ] + } diff --git a/services/weed_detection/models/train.py b/services/weed_detection/models/train.py index e9cd358a5..55d927e93 100644 --- a/services/weed_detection/models/train.py +++ b/services/weed_detection/models/train.py @@ -180,11 +180,7 @@ def dice_loss_from_logits(logits: torch.Tensor, target01: torch.Tensor, eps: flo @torch.no_grad() def pixel_accuracy_from_logits(logits, target01, threshold=0.5): - """ - logits: [B,1,H,W] - פלט המודל לפני sigmoid - target01: [B,1,H,W] - מסכה עם 0/1 - threshold: סף בינארי (לרוב 0.5) - """ + probs = torch.sigmoid(logits) preds = (probs > threshold).float() correct = (preds == target01).float().sum() diff --git a/services/weed_detection/services/minio_sync.py b/services/weed_detection/services/minio_sync.py index 2f64195a5..5812fecac 100644 --- a/services/weed_detection/services/minio_sync.py +++ b/services/weed_detection/services/minio_sync.py @@ -36,12 +36,11 @@ def download_prefix_to_dir(cfg: MinioConfig, prefix: str, local_dir: Path) -> li for obj in client.list_objects(cfg.bucket, prefix=prefix, recursive=True): name = obj.object_name if not name or name.endswith("/"): - continue # “תיקיות” מדומות + continue listed += 1 suf = Path(name).suffix.lower() if suf not in ALLOWED_EXTS: - # אפשר להשתיק אם לא רוצים לוגים על סיומות # print(f"[skip-ext] {name}") continue diff --git a/services/weed_detection/src/pipeline/db.py b/services/weed_detection/src/pipeline/db.py index 5fb271655..1734b5f1c 100644 --- a/services/weed_detection/src/pipeline/db.py +++ b/services/weed_detection/src/pipeline/db.py @@ -7,11 +7,9 @@ def get_engine(): db_url = os.getenv("DB_URL") if not db_url: raise RuntimeError("DB_URL is not set in environment") - # echo=False לשקט; אפשר True לדיבוג return create_engine(db_url, future=True) -# משפטי INSERT בהתאם לשדות שה-Runner מזין -# הערה: מיועד ל-PostgreSQL + PostGIS. אם SQLite – צריך להתאים (לשמור WKT כ-TEXT). + INSERT_DET = text(""" INSERT INTO anomalies (mission_id, device_id, ts, anomaly_type_id, severity, details, geom) VALUES (:mission_id, :device_id, :ts, :anomaly_type_id, :severity, CAST(:details AS JSONB), diff --git a/services/weed_detection/src/pipeline/utils.py b/services/weed_detection/src/pipeline/utils.py index 9dfdc8bb6..426ba28af 100644 --- a/services/weed_detection/src/pipeline/utils.py +++ b/services/weed_detection/src/pipeline/utils.py @@ -12,7 +12,7 @@ def load_image(path: str | Path): raise FileNotFoundError(f"Failed to load image: {p}") img = np.ascontiguousarray(img) h, w = img.shape[:2] - return img, w, h # זה הפורמט שה-Runner שלך מצפה לו + return img, w, h def image_id_from_path(p: str | Path) -> str: return Path(p).stem diff --git a/simulators/data/fruit/images/-RLW8KRN_jpg.rf.0043ffb17d38c36fbef82f22630f9768.jpg b/simulators/data/fruit/images/-RLW8KRN_jpg.rf.0043ffb17d38c36fbef82f22630f9768.jpg new file mode 100644 index 000000000..9c303ab5e Binary files /dev/null and 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000000000..812fe0191 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0032.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043133609, + "file_name": "frame_0032.jpg", + "frame_idx": 23 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0033.json b/simulators/data/security/cam-central-01/metadata/frame_0033.json new file mode 100644 index 000000000..34e519801 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0033.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043134609, + "file_name": "frame_0033.jpg", + "frame_idx": 24 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0034.json b/simulators/data/security/cam-central-01/metadata/frame_0034.json new file mode 100644 index 000000000..02fd91ac4 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0034.json @@ 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a/simulators/data/security/cam-central-01/metadata/frame_0039.json b/simulators/data/security/cam-central-01/metadata/frame_0039.json new file mode 100644 index 000000000..a87485024 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0039.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043140609, + "file_name": "frame_0039.jpg", + "frame_idx": 30 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0040.json b/simulators/data/security/cam-central-01/metadata/frame_0040.json new file mode 100644 index 000000000..5892fdb20 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0040.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043141609, + "file_name": "frame_0040.jpg", + "frame_idx": 31 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0041.json 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a/simulators/data/security/cam-central-01/metadata/frame_0050.json b/simulators/data/security/cam-central-01/metadata/frame_0050.json new file mode 100644 index 000000000..ab236b234 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0050.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043151609, + "file_name": "frame_0050.jpg", + "frame_idx": 41 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0051.json b/simulators/data/security/cam-central-01/metadata/frame_0051.json new file mode 100644 index 000000000..ce6ebc7c5 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0051.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043152609, + "file_name": "frame_0051.jpg", + "frame_idx": 42 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0052.json 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000000000..f562fc83f --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0054.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043155609, + "file_name": "frame_0054.jpg", + "frame_idx": 45 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0055.json b/simulators/data/security/cam-central-01/metadata/frame_0055.json new file mode 100644 index 000000000..38314ffc0 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0055.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043156609, + "file_name": "frame_0055.jpg", + "frame_idx": 46 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0056.json b/simulators/data/security/cam-central-01/metadata/frame_0056.json new file mode 100644 index 000000000..69afa7a9a --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0056.json @@ 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a/simulators/data/security/cam-central-01/metadata/frame_0061.json b/simulators/data/security/cam-central-01/metadata/frame_0061.json new file mode 100644 index 000000000..5ce85eaec --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0061.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043162609, + "file_name": "frame_0061.jpg", + "frame_idx": 52 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0062.json b/simulators/data/security/cam-central-01/metadata/frame_0062.json new file mode 100644 index 000000000..fae025967 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0062.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043163609, + "file_name": "frame_0062.jpg", + "frame_idx": 53 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0063.json b/simulators/data/security/cam-central-01/metadata/frame_0063.json new file mode 100644 index 000000000..4bdc25309 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0063.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043164609, + "file_name": "frame_0063.jpg", + "frame_idx": 54 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0064.json b/simulators/data/security/cam-central-01/metadata/frame_0064.json new file mode 100644 index 000000000..7f0bb6406 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0064.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043165609, + "file_name": "frame_0064.jpg", + "frame_idx": 55 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0065.json b/simulators/data/security/cam-central-01/metadata/frame_0065.json new file mode 100644 index 000000000..e06dc5b26 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0065.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043166609, + "file_name": "frame_0065.jpg", + "frame_idx": 56 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0066.json b/simulators/data/security/cam-central-01/metadata/frame_0066.json new file mode 100644 index 000000000..49491b582 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0066.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043167609, + "file_name": "frame_0066.jpg", + "frame_idx": 57 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0067.json b/simulators/data/security/cam-central-01/metadata/frame_0067.json new file mode 100644 index 000000000..30a960940 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0067.json @@ 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a/simulators/data/security/cam-central-01/metadata/frame_0072.json b/simulators/data/security/cam-central-01/metadata/frame_0072.json new file mode 100644 index 000000000..2912d430e --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0072.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043173609, + "file_name": "frame_0072.jpg", + "frame_idx": 63 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0073.json b/simulators/data/security/cam-central-01/metadata/frame_0073.json new file mode 100644 index 000000000..3d0110364 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0073.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043174609, + "file_name": "frame_0073.jpg", + "frame_idx": 64 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0074.json b/simulators/data/security/cam-central-01/metadata/frame_0074.json new file mode 100644 index 000000000..047561bfd --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0074.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043175609, + "file_name": "frame_0074.jpg", + "frame_idx": 65 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0075.json b/simulators/data/security/cam-central-01/metadata/frame_0075.json new file mode 100644 index 000000000..19ac9391c --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0075.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043176609, + "file_name": "frame_0075.jpg", + "frame_idx": 66 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0076.json b/simulators/data/security/cam-central-01/metadata/frame_0076.json new file mode 100644 index 000000000..782f061c2 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0076.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043177609, + "file_name": "frame_0076.jpg", + "frame_idx": 67 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0077.json b/simulators/data/security/cam-central-01/metadata/frame_0077.json new file mode 100644 index 000000000..9d387f2da --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0077.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043178609, + "file_name": "frame_0077.jpg", + "frame_idx": 68 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0078.json b/simulators/data/security/cam-central-01/metadata/frame_0078.json new file mode 100644 index 000000000..a683ac215 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0078.json @@ 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a/simulators/data/security/cam-central-01/metadata/frame_0083.json b/simulators/data/security/cam-central-01/metadata/frame_0083.json new file mode 100644 index 000000000..fc340f907 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0083.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043184609, + "file_name": "frame_0083.jpg", + "frame_idx": 74 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0084.json b/simulators/data/security/cam-central-01/metadata/frame_0084.json new file mode 100644 index 000000000..2dcc417d3 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0084.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043185609, + "file_name": "frame_0084.jpg", + "frame_idx": 75 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0085.json 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000000000..09b1fcfc3 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0087.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043188609, + "file_name": "frame_0087.jpg", + "frame_idx": 78 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0088.json b/simulators/data/security/cam-central-01/metadata/frame_0088.json new file mode 100644 index 000000000..4cfdc0ae1 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0088.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043189609, + "file_name": "frame_0088.jpg", + "frame_idx": 79 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0089.json b/simulators/data/security/cam-central-01/metadata/frame_0089.json new file mode 100644 index 000000000..5fb2d5003 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0089.json @@ 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a/simulators/data/security/cam-central-01/metadata/frame_0094.json b/simulators/data/security/cam-central-01/metadata/frame_0094.json new file mode 100644 index 000000000..ab0c4d715 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0094.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043195609, + "file_name": "frame_0094.jpg", + "frame_idx": 85 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0095.json b/simulators/data/security/cam-central-01/metadata/frame_0095.json new file mode 100644 index 000000000..ec25f6455 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0095.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043196609, + "file_name": "frame_0095.jpg", + "frame_idx": 86 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0096.json 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000000000..182f4ca0a --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0098.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043199609, + "file_name": "frame_0098.jpg", + "frame_idx": 89 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0099.json b/simulators/data/security/cam-central-01/metadata/frame_0099.json new file mode 100644 index 000000000..c74bd3a50 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0099.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043200609, + "file_name": "frame_0099.jpg", + "frame_idx": 90 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0100.json b/simulators/data/security/cam-central-01/metadata/frame_0100.json new file mode 100644 index 000000000..45cf5025c --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0100.json @@ 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a/simulators/data/security/cam-central-01/metadata/frame_0105.json b/simulators/data/security/cam-central-01/metadata/frame_0105.json new file mode 100644 index 000000000..c49d99e44 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0105.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043206609, + "file_name": "frame_0105.jpg", + "frame_idx": 96 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0106.json b/simulators/data/security/cam-central-01/metadata/frame_0106.json new file mode 100644 index 000000000..9793be294 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0106.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043207609, + "file_name": "frame_0106.jpg", + "frame_idx": 97 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0107.json b/simulators/data/security/cam-central-01/metadata/frame_0107.json new file mode 100644 index 000000000..da1ce5ec2 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0107.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043208609, + "file_name": "frame_0107.jpg", + "frame_idx": 98 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0108.json b/simulators/data/security/cam-central-01/metadata/frame_0108.json new file mode 100644 index 000000000..c668353f6 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0108.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043209609, + "file_name": "frame_0108.jpg", + "frame_idx": 99 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0109.json b/simulators/data/security/cam-central-01/metadata/frame_0109.json new file mode 100644 index 000000000..c6cc83b89 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0109.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043210609, + "file_name": "frame_0109.jpg", + "frame_idx": 100 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0110.json b/simulators/data/security/cam-central-01/metadata/frame_0110.json new file mode 100644 index 000000000..94406bbd6 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0110.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043211609, + "file_name": "frame_0110.jpg", + "frame_idx": 101 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0111.json b/simulators/data/security/cam-central-01/metadata/frame_0111.json new file mode 100644 index 000000000..a5ea7e5ee --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0111.json @@ 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a/simulators/data/security/cam-central-01/metadata/frame_0116.json b/simulators/data/security/cam-central-01/metadata/frame_0116.json new file mode 100644 index 000000000..dd014917b --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0116.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043217609, + "file_name": "frame_0116.jpg", + "frame_idx": 107 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0117.json b/simulators/data/security/cam-central-01/metadata/frame_0117.json new file mode 100644 index 000000000..84036eb03 --- /dev/null +++ b/simulators/data/security/cam-central-01/metadata/frame_0117.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-central-01", + "capture_time": 1763043218609, + "file_name": "frame_0117.jpg", + "frame_idx": 108 +} \ No newline at end of file diff --git a/simulators/data/security/cam-central-01/metadata/frame_0118.json 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b/simulators/data/security/cam-south-02/metadata/frame_0030.json new file mode 100644 index 000000000..29526794a --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0030.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971741269, + "file_name": "frame_0030.jpg", + "frame_idx": 30 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0031.json b/simulators/data/security/cam-south-02/metadata/frame_0031.json new file mode 100644 index 000000000..a5ea7a320 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0031.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971742269, + "file_name": "frame_0031.jpg", + "frame_idx": 31 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0032.json b/simulators/data/security/cam-south-02/metadata/frame_0032.json new file mode 100644 index 000000000..69bfd4165 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0032.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971743269, + "file_name": "frame_0032.jpg", + "frame_idx": 32 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0033.json b/simulators/data/security/cam-south-02/metadata/frame_0033.json new file mode 100644 index 000000000..8a88d92b5 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0033.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971744269, + "file_name": "frame_0033.jpg", + "frame_idx": 33 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0034.json b/simulators/data/security/cam-south-02/metadata/frame_0034.json new file mode 100644 index 000000000..e6493f426 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0034.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971745269, + "file_name": "frame_0034.jpg", + "frame_idx": 34 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0035.json b/simulators/data/security/cam-south-02/metadata/frame_0035.json new file mode 100644 index 000000000..bdbf52ad7 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0035.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971746269, + "file_name": "frame_0035.jpg", + "frame_idx": 35 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0036.json b/simulators/data/security/cam-south-02/metadata/frame_0036.json new file mode 100644 index 000000000..495e6eba0 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0036.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971747269, + "file_name": "frame_0036.jpg", + "frame_idx": 36 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0037.json b/simulators/data/security/cam-south-02/metadata/frame_0037.json new file mode 100644 index 000000000..d1e8c9dea --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0037.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971748269, + "file_name": "frame_0037.jpg", + "frame_idx": 37 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0038.json b/simulators/data/security/cam-south-02/metadata/frame_0038.json new file mode 100644 index 000000000..04c33e1c2 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0038.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971749269, + "file_name": "frame_0038.jpg", + "frame_idx": 38 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0039.json b/simulators/data/security/cam-south-02/metadata/frame_0039.json new file mode 100644 index 000000000..7f2b2c4f4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0039.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971750269, + "file_name": "frame_0039.jpg", + "frame_idx": 39 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0040.json b/simulators/data/security/cam-south-02/metadata/frame_0040.json new file mode 100644 index 000000000..c86cc938c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0040.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971751269, + "file_name": "frame_0040.jpg", + "frame_idx": 40 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0041.json b/simulators/data/security/cam-south-02/metadata/frame_0041.json new file mode 100644 index 000000000..9550779e8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0041.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971752269, + "file_name": "frame_0041.jpg", + "frame_idx": 41 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0042.json b/simulators/data/security/cam-south-02/metadata/frame_0042.json new file mode 100644 index 000000000..0ffb2a9cd --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0042.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971753269, + "file_name": "frame_0042.jpg", + "frame_idx": 42 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0043.json b/simulators/data/security/cam-south-02/metadata/frame_0043.json new file mode 100644 index 000000000..1deab4ee4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0043.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971754269, + "file_name": "frame_0043.jpg", + "frame_idx": 43 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0044.json b/simulators/data/security/cam-south-02/metadata/frame_0044.json new file mode 100644 index 000000000..6fe99174f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0044.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971755269, + "file_name": "frame_0044.jpg", + "frame_idx": 44 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0045.json b/simulators/data/security/cam-south-02/metadata/frame_0045.json new file mode 100644 index 000000000..309ea5cca --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0045.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971756269, + "file_name": "frame_0045.jpg", + "frame_idx": 45 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0046.json b/simulators/data/security/cam-south-02/metadata/frame_0046.json new file mode 100644 index 000000000..70761c01c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0046.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971757269, + "file_name": "frame_0046.jpg", + "frame_idx": 46 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0047.json b/simulators/data/security/cam-south-02/metadata/frame_0047.json new file mode 100644 index 000000000..bfcb511c2 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0047.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971758269, + "file_name": "frame_0047.jpg", + "frame_idx": 47 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0048.json b/simulators/data/security/cam-south-02/metadata/frame_0048.json new file mode 100644 index 000000000..fff599152 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0048.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971759269, + "file_name": "frame_0048.jpg", + "frame_idx": 48 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0049.json b/simulators/data/security/cam-south-02/metadata/frame_0049.json new file mode 100644 index 000000000..ebbe06fa3 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0049.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971760269, + "file_name": "frame_0049.jpg", + "frame_idx": 49 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0050.json b/simulators/data/security/cam-south-02/metadata/frame_0050.json new file mode 100644 index 000000000..3749da627 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0050.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971761269, + "file_name": "frame_0050.jpg", + "frame_idx": 50 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0051.json b/simulators/data/security/cam-south-02/metadata/frame_0051.json new file mode 100644 index 000000000..a290a28b0 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0051.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971762269, + "file_name": "frame_0051.jpg", + "frame_idx": 51 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0052.json b/simulators/data/security/cam-south-02/metadata/frame_0052.json new file mode 100644 index 000000000..8c315f6bb --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0052.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971763269, + "file_name": "frame_0052.jpg", + "frame_idx": 52 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0053.json b/simulators/data/security/cam-south-02/metadata/frame_0053.json new file mode 100644 index 000000000..f68a04f13 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0053.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971764269, + "file_name": "frame_0053.jpg", + "frame_idx": 53 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0054.json b/simulators/data/security/cam-south-02/metadata/frame_0054.json new file mode 100644 index 000000000..e221430ab --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0054.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971765269, + "file_name": "frame_0054.jpg", + "frame_idx": 54 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0055.json b/simulators/data/security/cam-south-02/metadata/frame_0055.json new file mode 100644 index 000000000..66f88f68c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0055.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971766269, + "file_name": "frame_0055.jpg", + "frame_idx": 55 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0056.json b/simulators/data/security/cam-south-02/metadata/frame_0056.json new file mode 100644 index 000000000..2636faeee --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0056.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971767269, + "file_name": "frame_0056.jpg", + "frame_idx": 56 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0057.json b/simulators/data/security/cam-south-02/metadata/frame_0057.json new file mode 100644 index 000000000..ae0b0af7f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0057.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971768269, + "file_name": "frame_0057.jpg", + "frame_idx": 57 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0058.json b/simulators/data/security/cam-south-02/metadata/frame_0058.json new file mode 100644 index 000000000..a8923f0e7 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0058.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971769269, + "file_name": "frame_0058.jpg", + "frame_idx": 58 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0059.json b/simulators/data/security/cam-south-02/metadata/frame_0059.json new file mode 100644 index 000000000..f41d6b07c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0059.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971770269, + "file_name": "frame_0059.jpg", + "frame_idx": 59 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0060.json b/simulators/data/security/cam-south-02/metadata/frame_0060.json new file mode 100644 index 000000000..67f04c2bd --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0060.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971771269, + "file_name": "frame_0060.jpg", + "frame_idx": 60 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0061.json b/simulators/data/security/cam-south-02/metadata/frame_0061.json new file mode 100644 index 000000000..e8758f1a4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0061.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971772269, + "file_name": "frame_0061.jpg", + "frame_idx": 61 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0062.json b/simulators/data/security/cam-south-02/metadata/frame_0062.json new file mode 100644 index 000000000..3925884b0 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0062.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971773269, + "file_name": "frame_0062.jpg", + "frame_idx": 62 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0063.json b/simulators/data/security/cam-south-02/metadata/frame_0063.json new file mode 100644 index 000000000..224c483f4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0063.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971774269, + "file_name": "frame_0063.jpg", + "frame_idx": 63 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0064.json b/simulators/data/security/cam-south-02/metadata/frame_0064.json new file mode 100644 index 000000000..7ee135906 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0064.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971775269, + "file_name": "frame_0064.jpg", + "frame_idx": 64 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0065.json b/simulators/data/security/cam-south-02/metadata/frame_0065.json new file mode 100644 index 000000000..6e0a3fb17 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0065.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971776269, + "file_name": "frame_0065.jpg", + "frame_idx": 65 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0066.json b/simulators/data/security/cam-south-02/metadata/frame_0066.json new file mode 100644 index 000000000..5449969b0 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0066.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971777269, + "file_name": "frame_0066.jpg", + "frame_idx": 66 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0067.json b/simulators/data/security/cam-south-02/metadata/frame_0067.json new file mode 100644 index 000000000..9b5b4ebf2 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0067.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971778269, + "file_name": "frame_0067.jpg", + "frame_idx": 67 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0068.json b/simulators/data/security/cam-south-02/metadata/frame_0068.json new file mode 100644 index 000000000..8dd466154 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0068.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971779269, + "file_name": "frame_0068.jpg", + "frame_idx": 68 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0069.json b/simulators/data/security/cam-south-02/metadata/frame_0069.json new file mode 100644 index 000000000..e0340be3a --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0069.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971780269, + "file_name": "frame_0069.jpg", + "frame_idx": 69 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0070.json b/simulators/data/security/cam-south-02/metadata/frame_0070.json new file mode 100644 index 000000000..7e52d296f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0070.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971781269, + "file_name": "frame_0070.jpg", + "frame_idx": 70 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0071.json b/simulators/data/security/cam-south-02/metadata/frame_0071.json new file mode 100644 index 000000000..3488f1eb4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0071.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971782269, + "file_name": "frame_0071.jpg", + "frame_idx": 71 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0072.json b/simulators/data/security/cam-south-02/metadata/frame_0072.json new file mode 100644 index 000000000..a67526f91 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0072.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971783269, + "file_name": "frame_0072.jpg", + "frame_idx": 72 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0073.json b/simulators/data/security/cam-south-02/metadata/frame_0073.json new file mode 100644 index 000000000..855da20af --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0073.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971784269, + "file_name": "frame_0073.jpg", + "frame_idx": 73 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0074.json b/simulators/data/security/cam-south-02/metadata/frame_0074.json new file mode 100644 index 000000000..c71cf8dc3 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0074.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971785269, + "file_name": "frame_0074.jpg", + "frame_idx": 74 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0075.json b/simulators/data/security/cam-south-02/metadata/frame_0075.json new file mode 100644 index 000000000..eef1310e8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0075.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971786269, + "file_name": "frame_0075.jpg", + "frame_idx": 75 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0076.json b/simulators/data/security/cam-south-02/metadata/frame_0076.json new file mode 100644 index 000000000..bedc2ce81 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0076.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971787269, + "file_name": "frame_0076.jpg", + "frame_idx": 76 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0077.json b/simulators/data/security/cam-south-02/metadata/frame_0077.json new file mode 100644 index 000000000..315a4ae26 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0077.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971788269, + "file_name": "frame_0077.jpg", + "frame_idx": 77 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0078.json b/simulators/data/security/cam-south-02/metadata/frame_0078.json new file mode 100644 index 000000000..f08f87fb6 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0078.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971789269, + "file_name": "frame_0078.jpg", + "frame_idx": 78 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0079.json b/simulators/data/security/cam-south-02/metadata/frame_0079.json new file mode 100644 index 000000000..431fb9e0a --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0079.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971790269, + "file_name": "frame_0079.jpg", + "frame_idx": 79 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0080.json b/simulators/data/security/cam-south-02/metadata/frame_0080.json new file mode 100644 index 000000000..9b12f7b0d --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0080.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971791269, + "file_name": "frame_0080.jpg", + "frame_idx": 80 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0081.json b/simulators/data/security/cam-south-02/metadata/frame_0081.json new file mode 100644 index 000000000..f358ee556 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0081.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971792269, + "file_name": "frame_0081.jpg", + "frame_idx": 81 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0082.json b/simulators/data/security/cam-south-02/metadata/frame_0082.json new file mode 100644 index 000000000..466472144 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0082.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971793269, + "file_name": "frame_0082.jpg", + "frame_idx": 82 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0083.json b/simulators/data/security/cam-south-02/metadata/frame_0083.json new file mode 100644 index 000000000..3299e5a4e --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0083.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971794269, + "file_name": "frame_0083.jpg", + "frame_idx": 83 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0084.json b/simulators/data/security/cam-south-02/metadata/frame_0084.json new file mode 100644 index 000000000..df40f83d8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0084.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971795269, + "file_name": "frame_0084.jpg", + "frame_idx": 84 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0085.json b/simulators/data/security/cam-south-02/metadata/frame_0085.json new file mode 100644 index 000000000..b75189fae --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0085.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971796269, + "file_name": "frame_0085.jpg", + "frame_idx": 85 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0086.json b/simulators/data/security/cam-south-02/metadata/frame_0086.json new file mode 100644 index 000000000..3dee4d138 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0086.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971797269, + "file_name": "frame_0086.jpg", + "frame_idx": 86 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0087.json b/simulators/data/security/cam-south-02/metadata/frame_0087.json new file mode 100644 index 000000000..bff2238b4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0087.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971798269, + "file_name": "frame_0087.jpg", + "frame_idx": 87 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0088.json b/simulators/data/security/cam-south-02/metadata/frame_0088.json new file mode 100644 index 000000000..374a425e3 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0088.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971799269, + "file_name": "frame_0088.jpg", + "frame_idx": 88 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0089.json b/simulators/data/security/cam-south-02/metadata/frame_0089.json new file mode 100644 index 000000000..dd1d298bb --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0089.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971800269, + "file_name": "frame_0089.jpg", + "frame_idx": 89 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0090.json b/simulators/data/security/cam-south-02/metadata/frame_0090.json new file mode 100644 index 000000000..1f0257f3d --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0090.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971801269, + "file_name": "frame_0090.jpg", + "frame_idx": 90 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0091.json b/simulators/data/security/cam-south-02/metadata/frame_0091.json new file mode 100644 index 000000000..ffae682c2 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0091.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971802269, + "file_name": "frame_0091.jpg", + "frame_idx": 91 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0092.json b/simulators/data/security/cam-south-02/metadata/frame_0092.json new file mode 100644 index 000000000..1f063820a --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0092.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971803269, + "file_name": "frame_0092.jpg", + "frame_idx": 92 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0093.json b/simulators/data/security/cam-south-02/metadata/frame_0093.json new file mode 100644 index 000000000..184654182 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0093.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971804269, + "file_name": "frame_0093.jpg", + "frame_idx": 93 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0094.json b/simulators/data/security/cam-south-02/metadata/frame_0094.json new file mode 100644 index 000000000..8cd61c5a8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0094.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971805269, + "file_name": "frame_0094.jpg", + "frame_idx": 94 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0095.json b/simulators/data/security/cam-south-02/metadata/frame_0095.json new file mode 100644 index 000000000..14200c4f5 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0095.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971806269, + "file_name": "frame_0095.jpg", + "frame_idx": 95 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0096.json b/simulators/data/security/cam-south-02/metadata/frame_0096.json new file mode 100644 index 000000000..97c6bbf94 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0096.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971807269, + "file_name": "frame_0096.jpg", + "frame_idx": 96 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0097.json b/simulators/data/security/cam-south-02/metadata/frame_0097.json new file mode 100644 index 000000000..40dc5901b --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0097.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971808269, + "file_name": "frame_0097.jpg", + "frame_idx": 97 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0098.json b/simulators/data/security/cam-south-02/metadata/frame_0098.json new file mode 100644 index 000000000..fab3f7d18 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0098.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971809269, + "file_name": "frame_0098.jpg", + "frame_idx": 98 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0099.json b/simulators/data/security/cam-south-02/metadata/frame_0099.json new file mode 100644 index 000000000..fbf0a5fff --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0099.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971810269, + "file_name": "frame_0099.jpg", + "frame_idx": 99 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0100.json b/simulators/data/security/cam-south-02/metadata/frame_0100.json new file mode 100644 index 000000000..23f2a586f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0100.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971811269, + "file_name": "frame_0100.jpg", + "frame_idx": 100 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0101.json b/simulators/data/security/cam-south-02/metadata/frame_0101.json new file mode 100644 index 000000000..4d4689bbc --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0101.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971812269, + "file_name": "frame_0101.jpg", + "frame_idx": 101 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0102.json b/simulators/data/security/cam-south-02/metadata/frame_0102.json new file mode 100644 index 000000000..10331f857 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0102.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971813269, + "file_name": "frame_0102.jpg", + "frame_idx": 102 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0103.json b/simulators/data/security/cam-south-02/metadata/frame_0103.json new file mode 100644 index 000000000..feedb88b8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0103.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971814269, + "file_name": "frame_0103.jpg", + "frame_idx": 103 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0104.json b/simulators/data/security/cam-south-02/metadata/frame_0104.json new file mode 100644 index 000000000..fe47c6011 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0104.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971815269, + "file_name": "frame_0104.jpg", + "frame_idx": 104 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0105.json b/simulators/data/security/cam-south-02/metadata/frame_0105.json new file mode 100644 index 000000000..df89930a2 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0105.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971816269, + "file_name": "frame_0105.jpg", + "frame_idx": 105 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0106.json b/simulators/data/security/cam-south-02/metadata/frame_0106.json new file mode 100644 index 000000000..a0dc90894 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0106.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971817269, + "file_name": "frame_0106.jpg", + "frame_idx": 106 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0107.json b/simulators/data/security/cam-south-02/metadata/frame_0107.json new file mode 100644 index 000000000..e296fe4cd --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0107.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971818269, + "file_name": "frame_0107.jpg", + "frame_idx": 107 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0108.json b/simulators/data/security/cam-south-02/metadata/frame_0108.json new file mode 100644 index 000000000..d26f3880d --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0108.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971819269, + "file_name": "frame_0108.jpg", + "frame_idx": 108 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0109.json b/simulators/data/security/cam-south-02/metadata/frame_0109.json new file mode 100644 index 000000000..f0f259df0 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0109.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971820269, + "file_name": "frame_0109.jpg", + "frame_idx": 109 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0110.json b/simulators/data/security/cam-south-02/metadata/frame_0110.json new file mode 100644 index 000000000..1dd2404a7 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0110.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971821269, + "file_name": "frame_0110.jpg", + "frame_idx": 110 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0111.json b/simulators/data/security/cam-south-02/metadata/frame_0111.json new file mode 100644 index 000000000..7e0ec5c41 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0111.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971822269, + "file_name": "frame_0111.jpg", + "frame_idx": 111 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0112.json b/simulators/data/security/cam-south-02/metadata/frame_0112.json new file mode 100644 index 000000000..32564d8a8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0112.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971823269, + "file_name": "frame_0112.jpg", + "frame_idx": 112 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0113.json b/simulators/data/security/cam-south-02/metadata/frame_0113.json new file mode 100644 index 000000000..4417b0315 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0113.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971824269, + "file_name": "frame_0113.jpg", + "frame_idx": 113 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0114.json b/simulators/data/security/cam-south-02/metadata/frame_0114.json new file mode 100644 index 000000000..352c7ce06 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0114.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971825269, + "file_name": "frame_0114.jpg", + "frame_idx": 114 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0115.json b/simulators/data/security/cam-south-02/metadata/frame_0115.json new file mode 100644 index 000000000..1f2df5555 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0115.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971826269, + "file_name": "frame_0115.jpg", + "frame_idx": 115 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0116.json b/simulators/data/security/cam-south-02/metadata/frame_0116.json new file mode 100644 index 000000000..e9f54e60a --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0116.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971827269, + "file_name": "frame_0116.jpg", + "frame_idx": 116 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0117.json b/simulators/data/security/cam-south-02/metadata/frame_0117.json new file mode 100644 index 000000000..e902e1d8d --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0117.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971828269, + "file_name": "frame_0117.jpg", + "frame_idx": 117 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0118.json b/simulators/data/security/cam-south-02/metadata/frame_0118.json new file mode 100644 index 000000000..69a190520 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0118.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971829269, + "file_name": "frame_0118.jpg", + "frame_idx": 118 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0119.json b/simulators/data/security/cam-south-02/metadata/frame_0119.json new file mode 100644 index 000000000..50ecf6ded --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0119.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971830269, + "file_name": "frame_0119.jpg", + "frame_idx": 119 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0120.json b/simulators/data/security/cam-south-02/metadata/frame_0120.json new file mode 100644 index 000000000..7f8f22d75 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0120.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971831269, + "file_name": "frame_0120.jpg", + "frame_idx": 120 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0121.json b/simulators/data/security/cam-south-02/metadata/frame_0121.json new file mode 100644 index 000000000..1f2f74a9e --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0121.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971832269, + "file_name": "frame_0121.jpg", + "frame_idx": 121 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0122.json b/simulators/data/security/cam-south-02/metadata/frame_0122.json new file mode 100644 index 000000000..4a7ed3239 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0122.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971833269, + "file_name": "frame_0122.jpg", + "frame_idx": 122 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0123.json b/simulators/data/security/cam-south-02/metadata/frame_0123.json new file mode 100644 index 000000000..f398496e8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0123.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971834269, + "file_name": "frame_0123.jpg", + "frame_idx": 123 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0124.json b/simulators/data/security/cam-south-02/metadata/frame_0124.json new file mode 100644 index 000000000..e07c9a888 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0124.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971835269, + "file_name": "frame_0124.jpg", + "frame_idx": 124 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0125.json b/simulators/data/security/cam-south-02/metadata/frame_0125.json new file mode 100644 index 000000000..89b7bb798 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0125.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971836269, + "file_name": "frame_0125.jpg", + "frame_idx": 125 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0126.json b/simulators/data/security/cam-south-02/metadata/frame_0126.json new file mode 100644 index 000000000..c1bcb291e --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0126.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971837269, + "file_name": "frame_0126.jpg", + "frame_idx": 126 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0127.json b/simulators/data/security/cam-south-02/metadata/frame_0127.json new file mode 100644 index 000000000..afc7f883c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0127.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971838269, + "file_name": "frame_0127.jpg", + "frame_idx": 127 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0128.json b/simulators/data/security/cam-south-02/metadata/frame_0128.json new file mode 100644 index 000000000..f207041c4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0128.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971839269, + "file_name": "frame_0128.jpg", + "frame_idx": 128 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0129.json b/simulators/data/security/cam-south-02/metadata/frame_0129.json new file mode 100644 index 000000000..dfe377054 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0129.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971840269, + "file_name": "frame_0129.jpg", + "frame_idx": 129 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0130.json b/simulators/data/security/cam-south-02/metadata/frame_0130.json new file mode 100644 index 000000000..f86254a47 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0130.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971841269, + "file_name": "frame_0130.jpg", + "frame_idx": 130 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0131.json b/simulators/data/security/cam-south-02/metadata/frame_0131.json new file mode 100644 index 000000000..07a614ff9 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0131.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971842269, + "file_name": "frame_0131.jpg", + "frame_idx": 131 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0132.json b/simulators/data/security/cam-south-02/metadata/frame_0132.json new file mode 100644 index 000000000..28d25f095 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0132.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971843269, + "file_name": "frame_0132.jpg", + "frame_idx": 132 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0133.json b/simulators/data/security/cam-south-02/metadata/frame_0133.json new file mode 100644 index 000000000..621e5755a --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0133.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971844269, + "file_name": "frame_0133.jpg", + "frame_idx": 133 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0134.json b/simulators/data/security/cam-south-02/metadata/frame_0134.json new file mode 100644 index 000000000..deb5c58fb --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0134.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971845269, + "file_name": "frame_0134.jpg", + "frame_idx": 134 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0135.json b/simulators/data/security/cam-south-02/metadata/frame_0135.json new file mode 100644 index 000000000..db0d78a91 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0135.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971846269, + "file_name": "frame_0135.jpg", + "frame_idx": 135 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0136.json b/simulators/data/security/cam-south-02/metadata/frame_0136.json new file mode 100644 index 000000000..9286ca1de --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0136.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971847269, + "file_name": "frame_0136.jpg", + "frame_idx": 136 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0137.json b/simulators/data/security/cam-south-02/metadata/frame_0137.json new file mode 100644 index 000000000..d47d406c8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0137.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971848269, + "file_name": "frame_0137.jpg", + "frame_idx": 137 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0138.json b/simulators/data/security/cam-south-02/metadata/frame_0138.json new file mode 100644 index 000000000..2806f20df --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0138.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971849269, + "file_name": "frame_0138.jpg", + "frame_idx": 138 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0139.json b/simulators/data/security/cam-south-02/metadata/frame_0139.json new file mode 100644 index 000000000..581321b1f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0139.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971850269, + "file_name": "frame_0139.jpg", + "frame_idx": 139 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0140.json b/simulators/data/security/cam-south-02/metadata/frame_0140.json new file mode 100644 index 000000000..2bc3cc718 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0140.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971851269, + "file_name": "frame_0140.jpg", + "frame_idx": 140 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0141.json b/simulators/data/security/cam-south-02/metadata/frame_0141.json new file mode 100644 index 000000000..1366475a0 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0141.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971852269, + "file_name": "frame_0141.jpg", + "frame_idx": 141 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0142.json b/simulators/data/security/cam-south-02/metadata/frame_0142.json new file mode 100644 index 000000000..30644131a --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0142.json @@ -0,0 +1,6 @@ +{ + "camera_id": 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of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0145.json b/simulators/data/security/cam-south-02/metadata/frame_0145.json new file mode 100644 index 000000000..a054e2e7f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0145.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971856269, + "file_name": "frame_0145.jpg", + "frame_idx": 145 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0146.json b/simulators/data/security/cam-south-02/metadata/frame_0146.json new file mode 100644 index 000000000..6e66c4451 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0146.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971857269, + "file_name": "frame_0146.jpg", + "frame_idx": 146 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0147.json b/simulators/data/security/cam-south-02/metadata/frame_0147.json new file mode 100644 index 000000000..5fdf1f0ca --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0147.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971858269, + "file_name": "frame_0147.jpg", + "frame_idx": 147 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0148.json b/simulators/data/security/cam-south-02/metadata/frame_0148.json new file mode 100644 index 000000000..53f801443 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0148.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971859269, + "file_name": "frame_0148.jpg", + "frame_idx": 148 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0149.json b/simulators/data/security/cam-south-02/metadata/frame_0149.json new file mode 100644 index 000000000..c3958b44c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0149.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971860269, + "file_name": "frame_0149.jpg", + "frame_idx": 149 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0150.json b/simulators/data/security/cam-south-02/metadata/frame_0150.json new file mode 100644 index 000000000..a8fc0b172 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0150.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971861269, + "file_name": "frame_0150.jpg", + "frame_idx": 150 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0151.json b/simulators/data/security/cam-south-02/metadata/frame_0151.json new file mode 100644 index 000000000..c77a8c838 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0151.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971862269, + "file_name": "frame_0151.jpg", + "frame_idx": 151 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0152.json b/simulators/data/security/cam-south-02/metadata/frame_0152.json new file mode 100644 index 000000000..0583d973f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0152.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971863269, + "file_name": "frame_0152.jpg", + "frame_idx": 152 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0153.json b/simulators/data/security/cam-south-02/metadata/frame_0153.json new file mode 100644 index 000000000..9c2afb304 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0153.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971864269, + "file_name": "frame_0153.jpg", + "frame_idx": 153 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0154.json b/simulators/data/security/cam-south-02/metadata/frame_0154.json new file mode 100644 index 000000000..c1717226a --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0154.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971865269, + "file_name": "frame_0154.jpg", + "frame_idx": 154 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0155.json b/simulators/data/security/cam-south-02/metadata/frame_0155.json new file mode 100644 index 000000000..03f535d2c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0155.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971866269, + "file_name": "frame_0155.jpg", + "frame_idx": 155 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0156.json b/simulators/data/security/cam-south-02/metadata/frame_0156.json new file mode 100644 index 000000000..98af9078d --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0156.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971867269, + "file_name": "frame_0156.jpg", + "frame_idx": 156 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0157.json b/simulators/data/security/cam-south-02/metadata/frame_0157.json new file mode 100644 index 000000000..bb900af7f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0157.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971868269, + "file_name": "frame_0157.jpg", + "frame_idx": 157 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0158.json b/simulators/data/security/cam-south-02/metadata/frame_0158.json new file mode 100644 index 000000000..d3b9370e4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0158.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971869269, + "file_name": "frame_0158.jpg", + "frame_idx": 158 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0159.json b/simulators/data/security/cam-south-02/metadata/frame_0159.json new file mode 100644 index 000000000..a8627a442 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0159.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971870269, + "file_name": "frame_0159.jpg", + "frame_idx": 159 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0160.json b/simulators/data/security/cam-south-02/metadata/frame_0160.json new file mode 100644 index 000000000..f5380292e --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0160.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971871269, + "file_name": "frame_0160.jpg", + "frame_idx": 160 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0161.json b/simulators/data/security/cam-south-02/metadata/frame_0161.json new file mode 100644 index 000000000..690b15b31 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0161.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971872269, + "file_name": "frame_0161.jpg", + "frame_idx": 161 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0162.json b/simulators/data/security/cam-south-02/metadata/frame_0162.json new file mode 100644 index 000000000..72e9fb486 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0162.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971873269, + "file_name": "frame_0162.jpg", + "frame_idx": 162 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0163.json b/simulators/data/security/cam-south-02/metadata/frame_0163.json new file mode 100644 index 000000000..8a8a8f3cd --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0163.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971874269, + "file_name": "frame_0163.jpg", + "frame_idx": 163 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0164.json b/simulators/data/security/cam-south-02/metadata/frame_0164.json new file mode 100644 index 000000000..cb5bc4036 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0164.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971875269, + "file_name": "frame_0164.jpg", + "frame_idx": 164 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0165.json b/simulators/data/security/cam-south-02/metadata/frame_0165.json new file mode 100644 index 000000000..a34beac1f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0165.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971876269, + "file_name": "frame_0165.jpg", + "frame_idx": 165 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0166.json b/simulators/data/security/cam-south-02/metadata/frame_0166.json new file mode 100644 index 000000000..129775639 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0166.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971877269, + "file_name": "frame_0166.jpg", + "frame_idx": 166 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0167.json b/simulators/data/security/cam-south-02/metadata/frame_0167.json new file mode 100644 index 000000000..17c0412a6 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0167.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971878269, + "file_name": "frame_0167.jpg", + "frame_idx": 167 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0168.json b/simulators/data/security/cam-south-02/metadata/frame_0168.json new file mode 100644 index 000000000..15ae1c6ee --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0168.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971879269, + "file_name": "frame_0168.jpg", + "frame_idx": 168 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0169.json b/simulators/data/security/cam-south-02/metadata/frame_0169.json new file mode 100644 index 000000000..8071da9c1 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0169.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971880269, + "file_name": "frame_0169.jpg", + "frame_idx": 169 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0170.json b/simulators/data/security/cam-south-02/metadata/frame_0170.json new file mode 100644 index 000000000..710ae1ea6 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0170.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971881269, + "file_name": "frame_0170.jpg", + "frame_idx": 170 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0171.json b/simulators/data/security/cam-south-02/metadata/frame_0171.json new file mode 100644 index 000000000..787bdae24 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0171.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971882269, + "file_name": "frame_0171.jpg", + "frame_idx": 171 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0172.json b/simulators/data/security/cam-south-02/metadata/frame_0172.json new file mode 100644 index 000000000..cd66fe579 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0172.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971883269, + "file_name": "frame_0172.jpg", + "frame_idx": 172 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0173.json b/simulators/data/security/cam-south-02/metadata/frame_0173.json new file mode 100644 index 000000000..ca3034ce4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0173.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971884269, + "file_name": "frame_0173.jpg", + "frame_idx": 173 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0174.json b/simulators/data/security/cam-south-02/metadata/frame_0174.json new file mode 100644 index 000000000..5b0935bc3 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0174.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971885269, + "file_name": "frame_0174.jpg", + "frame_idx": 174 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0175.json b/simulators/data/security/cam-south-02/metadata/frame_0175.json new file mode 100644 index 000000000..6a336b94c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0175.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971886269, + "file_name": "frame_0175.jpg", + "frame_idx": 175 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0176.json b/simulators/data/security/cam-south-02/metadata/frame_0176.json new file mode 100644 index 000000000..4447c1cd0 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0176.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971887269, + "file_name": "frame_0176.jpg", + "frame_idx": 176 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0177.json b/simulators/data/security/cam-south-02/metadata/frame_0177.json new file mode 100644 index 000000000..9165e029e --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0177.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971888269, + "file_name": "frame_0177.jpg", + "frame_idx": 177 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0178.json b/simulators/data/security/cam-south-02/metadata/frame_0178.json new file mode 100644 index 000000000..33fd9479f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0178.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971889269, + "file_name": "frame_0178.jpg", + "frame_idx": 178 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0179.json b/simulators/data/security/cam-south-02/metadata/frame_0179.json new file mode 100644 index 000000000..ce52cfc26 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0179.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971890269, + "file_name": "frame_0179.jpg", + "frame_idx": 179 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0180.json b/simulators/data/security/cam-south-02/metadata/frame_0180.json new file mode 100644 index 000000000..93ae04272 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0180.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971891269, + "file_name": "frame_0180.jpg", + "frame_idx": 180 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0181.json b/simulators/data/security/cam-south-02/metadata/frame_0181.json new file mode 100644 index 000000000..1c2458c00 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0181.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971892269, + "file_name": "frame_0181.jpg", + "frame_idx": 181 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0182.json b/simulators/data/security/cam-south-02/metadata/frame_0182.json new file mode 100644 index 000000000..4a8fc2718 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0182.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971893269, + "file_name": "frame_0182.jpg", + "frame_idx": 182 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0183.json b/simulators/data/security/cam-south-02/metadata/frame_0183.json new file mode 100644 index 000000000..f496488f8 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0183.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971894269, + "file_name": "frame_0183.jpg", + "frame_idx": 183 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0184.json b/simulators/data/security/cam-south-02/metadata/frame_0184.json new file mode 100644 index 000000000..d18d516d4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0184.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971895269, + "file_name": "frame_0184.jpg", + "frame_idx": 184 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0185.json b/simulators/data/security/cam-south-02/metadata/frame_0185.json new file mode 100644 index 000000000..7215963e4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0185.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971896269, + "file_name": "frame_0185.jpg", + "frame_idx": 185 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0186.json b/simulators/data/security/cam-south-02/metadata/frame_0186.json new file mode 100644 index 000000000..887d6d68e --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0186.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971897269, + "file_name": "frame_0186.jpg", + "frame_idx": 186 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0187.json b/simulators/data/security/cam-south-02/metadata/frame_0187.json new file mode 100644 index 000000000..8e01dd24c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0187.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971898269, + "file_name": "frame_0187.jpg", + "frame_idx": 187 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0188.json b/simulators/data/security/cam-south-02/metadata/frame_0188.json new file mode 100644 index 000000000..692b84f59 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0188.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971899269, + "file_name": "frame_0188.jpg", + "frame_idx": 188 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0189.json b/simulators/data/security/cam-south-02/metadata/frame_0189.json new file mode 100644 index 000000000..ee8159fa4 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0189.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971900269, + "file_name": "frame_0189.jpg", + "frame_idx": 189 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0190.json b/simulators/data/security/cam-south-02/metadata/frame_0190.json new file mode 100644 index 000000000..d998455df --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0190.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971901269, + "file_name": "frame_0190.jpg", + "frame_idx": 190 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0191.json b/simulators/data/security/cam-south-02/metadata/frame_0191.json new file mode 100644 index 000000000..c25bc11b6 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0191.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971902269, + "file_name": "frame_0191.jpg", + "frame_idx": 191 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0192.json b/simulators/data/security/cam-south-02/metadata/frame_0192.json new file mode 100644 index 000000000..d58ddeb94 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0192.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971903269, + "file_name": "frame_0192.jpg", + "frame_idx": 192 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0193.json b/simulators/data/security/cam-south-02/metadata/frame_0193.json new file mode 100644 index 000000000..bd7d0001f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0193.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971904269, + "file_name": "frame_0193.jpg", + "frame_idx": 193 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0194.json b/simulators/data/security/cam-south-02/metadata/frame_0194.json new file mode 100644 index 000000000..f5683bb6d --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0194.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971905269, + "file_name": "frame_0194.jpg", + "frame_idx": 194 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0195.json b/simulators/data/security/cam-south-02/metadata/frame_0195.json new file mode 100644 index 000000000..440ee19d2 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0195.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971906269, + "file_name": "frame_0195.jpg", + "frame_idx": 195 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0196.json b/simulators/data/security/cam-south-02/metadata/frame_0196.json new file mode 100644 index 000000000..67ea61d2e --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0196.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971907269, + "file_name": "frame_0196.jpg", + "frame_idx": 196 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0197.json b/simulators/data/security/cam-south-02/metadata/frame_0197.json new file mode 100644 index 000000000..b52957e7f --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0197.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971908269, + "file_name": "frame_0197.jpg", + "frame_idx": 197 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0198.json b/simulators/data/security/cam-south-02/metadata/frame_0198.json new file mode 100644 index 000000000..9bd12b009 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0198.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971909269, + "file_name": "frame_0198.jpg", + "frame_idx": 198 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0199.json b/simulators/data/security/cam-south-02/metadata/frame_0199.json new file mode 100644 index 000000000..30769f758 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0199.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971910269, + "file_name": "frame_0199.jpg", + "frame_idx": 199 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0200.json b/simulators/data/security/cam-south-02/metadata/frame_0200.json new file mode 100644 index 000000000..f8bbd5bee --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0200.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971911269, + "file_name": "frame_0200.jpg", + "frame_idx": 200 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0201.json b/simulators/data/security/cam-south-02/metadata/frame_0201.json new file mode 100644 index 000000000..1704053c9 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0201.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971912269, + "file_name": "frame_0201.jpg", + "frame_idx": 201 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0202.json b/simulators/data/security/cam-south-02/metadata/frame_0202.json new file mode 100644 index 000000000..9eefe7744 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0202.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971913269, + "file_name": "frame_0202.jpg", + "frame_idx": 202 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0203.json b/simulators/data/security/cam-south-02/metadata/frame_0203.json new file mode 100644 index 000000000..44339fcbb --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0203.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971914269, + "file_name": "frame_0203.jpg", + "frame_idx": 203 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0204.json b/simulators/data/security/cam-south-02/metadata/frame_0204.json new file mode 100644 index 000000000..7d0b0b145 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0204.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971915269, + "file_name": "frame_0204.jpg", + "frame_idx": 204 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0205.json b/simulators/data/security/cam-south-02/metadata/frame_0205.json new file mode 100644 index 000000000..6cdec35bc --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0205.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971916269, + "file_name": "frame_0205.jpg", + "frame_idx": 205 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0206.json b/simulators/data/security/cam-south-02/metadata/frame_0206.json new file mode 100644 index 000000000..98cacd1b2 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0206.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971917269, + "file_name": "frame_0206.jpg", + "frame_idx": 206 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0207.json b/simulators/data/security/cam-south-02/metadata/frame_0207.json new file mode 100644 index 000000000..85b28c144 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0207.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971918269, + "file_name": "frame_0207.jpg", + "frame_idx": 207 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0208.json b/simulators/data/security/cam-south-02/metadata/frame_0208.json new file mode 100644 index 000000000..3ab50d99c --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0208.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971919269, + "file_name": "frame_0208.jpg", + "frame_idx": 208 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0209.json b/simulators/data/security/cam-south-02/metadata/frame_0209.json new file mode 100644 index 000000000..76b4a79aa --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0209.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971920269, + "file_name": "frame_0209.jpg", + "frame_idx": 209 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0210.json b/simulators/data/security/cam-south-02/metadata/frame_0210.json new file mode 100644 index 000000000..0d14a5533 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0210.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971921269, + "file_name": "frame_0210.jpg", + "frame_idx": 210 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0211.json b/simulators/data/security/cam-south-02/metadata/frame_0211.json new file mode 100644 index 000000000..01ab0f223 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0211.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971922269, + "file_name": "frame_0211.jpg", + "frame_idx": 211 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0212.json b/simulators/data/security/cam-south-02/metadata/frame_0212.json new file mode 100644 index 000000000..e7dbfade7 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0212.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971923269, + "file_name": "frame_0212.jpg", + "frame_idx": 212 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0213.json b/simulators/data/security/cam-south-02/metadata/frame_0213.json new file mode 100644 index 000000000..b5b3cacdf --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0213.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971924269, + "file_name": "frame_0213.jpg", + "frame_idx": 213 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0214.json b/simulators/data/security/cam-south-02/metadata/frame_0214.json new file mode 100644 index 000000000..6f549ae47 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0214.json @@ -0,0 +1,6 @@ +{ + "camera_id": 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of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0217.json b/simulators/data/security/cam-south-02/metadata/frame_0217.json new file mode 100644 index 000000000..0c979ac9b --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0217.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971928269, + "file_name": "frame_0217.jpg", + "frame_idx": 217 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0218.json b/simulators/data/security/cam-south-02/metadata/frame_0218.json new file mode 100644 index 000000000..fa89bdd32 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0218.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971929269, + "file_name": "frame_0218.jpg", + "frame_idx": 218 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0219.json 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/dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0221.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971932269, + "file_name": "frame_0221.jpg", + "frame_idx": 221 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0222.json b/simulators/data/security/cam-south-02/metadata/frame_0222.json new file mode 100644 index 000000000..7567b04e3 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0222.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971933269, + "file_name": "frame_0222.jpg", + "frame_idx": 222 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0223.json b/simulators/data/security/cam-south-02/metadata/frame_0223.json new file mode 100644 index 000000000..da8b077c6 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0223.json @@ -0,0 +1,6 @@ +{ + "camera_id": 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of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0226.json b/simulators/data/security/cam-south-02/metadata/frame_0226.json new file mode 100644 index 000000000..c379cd693 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0226.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971937269, + "file_name": "frame_0226.jpg", + "frame_idx": 226 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0227.json b/simulators/data/security/cam-south-02/metadata/frame_0227.json new file mode 100644 index 000000000..c3ac5c8f6 --- /dev/null +++ b/simulators/data/security/cam-south-02/metadata/frame_0227.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-south-02", + "capture_time": 1762971938269, + "file_name": "frame_0227.jpg", + "frame_idx": 227 +} \ No newline at end of file diff --git a/simulators/data/security/cam-south-02/metadata/frame_0228.json 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1762970550189, + "file_name": "frame_0027.jpg", + "frame_idx": 27 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0028.json b/simulators/data/security/cam-west-02/metadata/frame_0028.json new file mode 100644 index 000000000..f03c8ceda --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0028.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970551189, + "file_name": "frame_0028.jpg", + "frame_idx": 28 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0029.json b/simulators/data/security/cam-west-02/metadata/frame_0029.json new file mode 100644 index 000000000..8272a4153 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0029.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970552189, + "file_name": "frame_0029.jpg", + "frame_idx": 29 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0030.json b/simulators/data/security/cam-west-02/metadata/frame_0030.json new file mode 100644 index 000000000..a8a256e00 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0030.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970553189, + "file_name": "frame_0030.jpg", + "frame_idx": 30 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0031.json b/simulators/data/security/cam-west-02/metadata/frame_0031.json new file mode 100644 index 000000000..c7e2d6478 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0031.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970554189, + "file_name": "frame_0031.jpg", + "frame_idx": 31 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0032.json b/simulators/data/security/cam-west-02/metadata/frame_0032.json new file mode 100644 index 000000000..31817be0d --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0032.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970555189, + "file_name": "frame_0032.jpg", + "frame_idx": 32 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0033.json b/simulators/data/security/cam-west-02/metadata/frame_0033.json new file mode 100644 index 000000000..aca2e1e2b --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0033.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970556189, + "file_name": "frame_0033.jpg", + "frame_idx": 33 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0034.json b/simulators/data/security/cam-west-02/metadata/frame_0034.json new file mode 100644 index 000000000..b2da56088 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0034.json @@ -0,0 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newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0037.json b/simulators/data/security/cam-west-02/metadata/frame_0037.json new file mode 100644 index 000000000..12d669494 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0037.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970560189, + "file_name": "frame_0037.jpg", + "frame_idx": 37 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0038.json b/simulators/data/security/cam-west-02/metadata/frame_0038.json new file mode 100644 index 000000000..3d75c41f9 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0038.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970561189, + "file_name": "frame_0038.jpg", + "frame_idx": 38 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0039.json b/simulators/data/security/cam-west-02/metadata/frame_0039.json new file mode 100644 index 000000000..5ee6249e0 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0039.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970562189, + "file_name": "frame_0039.jpg", + "frame_idx": 39 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0040.json b/simulators/data/security/cam-west-02/metadata/frame_0040.json new file mode 100644 index 000000000..15f45aedd --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0040.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970563189, + "file_name": "frame_0040.jpg", + "frame_idx": 40 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0041.json b/simulators/data/security/cam-west-02/metadata/frame_0041.json new file mode 100644 index 000000000..dd0b3422c --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0041.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970564189, + "file_name": "frame_0041.jpg", + "frame_idx": 41 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0042.json b/simulators/data/security/cam-west-02/metadata/frame_0042.json new file mode 100644 index 000000000..8ba017e80 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0042.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970565189, + "file_name": "frame_0042.jpg", + "frame_idx": 42 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0043.json b/simulators/data/security/cam-west-02/metadata/frame_0043.json new file mode 100644 index 000000000..06a69ee39 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0043.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970566189, + "file_name": "frame_0043.jpg", + "frame_idx": 43 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0044.json b/simulators/data/security/cam-west-02/metadata/frame_0044.json new file mode 100644 index 000000000..b85d70ebd --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0044.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970567189, + "file_name": "frame_0044.jpg", + "frame_idx": 44 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0045.json b/simulators/data/security/cam-west-02/metadata/frame_0045.json new file mode 100644 index 000000000..0a05269fc --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0045.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970568189, + "file_name": "frame_0045.jpg", + "frame_idx": 45 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0046.json b/simulators/data/security/cam-west-02/metadata/frame_0046.json new file mode 100644 index 000000000..44d8761bd --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0046.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970569189, + "file_name": "frame_0046.jpg", + "frame_idx": 46 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0047.json b/simulators/data/security/cam-west-02/metadata/frame_0047.json new file mode 100644 index 000000000..006d55bcf --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0047.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970570189, + "file_name": "frame_0047.jpg", + "frame_idx": 47 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0048.json b/simulators/data/security/cam-west-02/metadata/frame_0048.json new file mode 100644 index 000000000..0b173fa9f --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0048.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970571189, + "file_name": "frame_0048.jpg", + "frame_idx": 48 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0049.json b/simulators/data/security/cam-west-02/metadata/frame_0049.json new file mode 100644 index 000000000..5116a4a0b --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0049.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970572189, + "file_name": "frame_0049.jpg", + "frame_idx": 49 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0050.json b/simulators/data/security/cam-west-02/metadata/frame_0050.json new file mode 100644 index 000000000..a67bcaa5d --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0050.json @@ -0,0 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newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0053.json b/simulators/data/security/cam-west-02/metadata/frame_0053.json new file mode 100644 index 000000000..6fb1bf9bd --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0053.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970576189, + "file_name": "frame_0053.jpg", + "frame_idx": 53 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0054.json b/simulators/data/security/cam-west-02/metadata/frame_0054.json new file mode 100644 index 000000000..a4d0f5e34 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0054.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970577189, + "file_name": "frame_0054.jpg", + "frame_idx": 54 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0055.json b/simulators/data/security/cam-west-02/metadata/frame_0055.json new file mode 100644 index 000000000..127b10ce6 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0055.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970578189, + "file_name": "frame_0055.jpg", + "frame_idx": 55 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0056.json b/simulators/data/security/cam-west-02/metadata/frame_0056.json new file mode 100644 index 000000000..36fb64a49 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0056.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970579189, + "file_name": "frame_0056.jpg", + "frame_idx": 56 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0057.json b/simulators/data/security/cam-west-02/metadata/frame_0057.json new file mode 100644 index 000000000..d9d229668 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0057.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970580189, + "file_name": "frame_0057.jpg", + "frame_idx": 57 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0058.json b/simulators/data/security/cam-west-02/metadata/frame_0058.json new file mode 100644 index 000000000..edcba21c8 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0058.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970581189, + "file_name": "frame_0058.jpg", + "frame_idx": 58 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0059.json b/simulators/data/security/cam-west-02/metadata/frame_0059.json new file mode 100644 index 000000000..ce7724b39 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0059.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970582189, + "file_name": "frame_0059.jpg", + "frame_idx": 59 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0060.json b/simulators/data/security/cam-west-02/metadata/frame_0060.json new file mode 100644 index 000000000..8359bf670 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0060.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970583189, + "file_name": "frame_0060.jpg", + "frame_idx": 60 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0061.json b/simulators/data/security/cam-west-02/metadata/frame_0061.json new file mode 100644 index 000000000..8adcc1c15 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0061.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970584189, + "file_name": "frame_0061.jpg", + "frame_idx": 61 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0062.json b/simulators/data/security/cam-west-02/metadata/frame_0062.json new file mode 100644 index 000000000..28e16bd95 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0062.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970585189, + "file_name": "frame_0062.jpg", + "frame_idx": 62 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0063.json b/simulators/data/security/cam-west-02/metadata/frame_0063.json new file mode 100644 index 000000000..364dd77f3 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0063.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970586189, + "file_name": "frame_0063.jpg", + "frame_idx": 63 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0064.json b/simulators/data/security/cam-west-02/metadata/frame_0064.json new file mode 100644 index 000000000..1073f9e04 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0064.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970587189, + "file_name": "frame_0064.jpg", + "frame_idx": 64 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0065.json b/simulators/data/security/cam-west-02/metadata/frame_0065.json new file mode 100644 index 000000000..65d9d087b --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0065.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970588189, + "file_name": "frame_0065.jpg", + "frame_idx": 65 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0066.json b/simulators/data/security/cam-west-02/metadata/frame_0066.json new file mode 100644 index 000000000..70f293d0e --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0066.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970589189, + "file_name": "frame_0066.jpg", + "frame_idx": 66 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0067.json b/simulators/data/security/cam-west-02/metadata/frame_0067.json new file mode 100644 index 000000000..f67cc2bcd --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0067.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970590189, + "file_name": "frame_0067.jpg", + "frame_idx": 67 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0068.json b/simulators/data/security/cam-west-02/metadata/frame_0068.json new file mode 100644 index 000000000..82ece425d --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0068.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970591189, + "file_name": "frame_0068.jpg", + "frame_idx": 68 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0069.json b/simulators/data/security/cam-west-02/metadata/frame_0069.json new file mode 100644 index 000000000..1888911db --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0069.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970592189, + "file_name": "frame_0069.jpg", + "frame_idx": 69 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0070.json b/simulators/data/security/cam-west-02/metadata/frame_0070.json new file mode 100644 index 000000000..3152e0fad --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0070.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970593189, + "file_name": "frame_0070.jpg", + "frame_idx": 70 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0071.json b/simulators/data/security/cam-west-02/metadata/frame_0071.json new file mode 100644 index 000000000..6cd2c2f97 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0071.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970594189, + "file_name": "frame_0071.jpg", + "frame_idx": 71 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0072.json b/simulators/data/security/cam-west-02/metadata/frame_0072.json new file mode 100644 index 000000000..b06d07951 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0072.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970595189, + "file_name": "frame_0072.jpg", + "frame_idx": 72 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0073.json b/simulators/data/security/cam-west-02/metadata/frame_0073.json new file mode 100644 index 000000000..ac82e2861 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0073.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970596189, + "file_name": "frame_0073.jpg", + "frame_idx": 73 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0074.json b/simulators/data/security/cam-west-02/metadata/frame_0074.json new file mode 100644 index 000000000..4f21638b2 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0074.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970597189, + "file_name": "frame_0074.jpg", + "frame_idx": 74 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0075.json b/simulators/data/security/cam-west-02/metadata/frame_0075.json new file mode 100644 index 000000000..189680382 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0075.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970598189, + "file_name": "frame_0075.jpg", + "frame_idx": 75 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0076.json b/simulators/data/security/cam-west-02/metadata/frame_0076.json new file mode 100644 index 000000000..02ae4d36f --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0076.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970599189, + "file_name": "frame_0076.jpg", + "frame_idx": 76 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0077.json b/simulators/data/security/cam-west-02/metadata/frame_0077.json new file mode 100644 index 000000000..00c02904f --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0077.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970600189, + "file_name": "frame_0077.jpg", + "frame_idx": 77 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0078.json b/simulators/data/security/cam-west-02/metadata/frame_0078.json new file mode 100644 index 000000000..1dd65f10f --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0078.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970601189, + "file_name": "frame_0078.jpg", + "frame_idx": 78 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0079.json b/simulators/data/security/cam-west-02/metadata/frame_0079.json new file mode 100644 index 000000000..4064925bf --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0079.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970602189, + "file_name": "frame_0079.jpg", + "frame_idx": 79 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0080.json b/simulators/data/security/cam-west-02/metadata/frame_0080.json new file mode 100644 index 000000000..1dd0f7775 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0080.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970603189, + "file_name": "frame_0080.jpg", + "frame_idx": 80 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0081.json b/simulators/data/security/cam-west-02/metadata/frame_0081.json new file mode 100644 index 000000000..7854729a6 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0081.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970604189, + "file_name": "frame_0081.jpg", + "frame_idx": 81 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0082.json b/simulators/data/security/cam-west-02/metadata/frame_0082.json new file mode 100644 index 000000000..8def46369 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0082.json @@ -0,0 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newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0085.json b/simulators/data/security/cam-west-02/metadata/frame_0085.json new file mode 100644 index 000000000..f14cdc6c9 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0085.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970608189, + "file_name": "frame_0085.jpg", + "frame_idx": 85 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0086.json b/simulators/data/security/cam-west-02/metadata/frame_0086.json new file mode 100644 index 000000000..221ab5f35 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0086.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970609189, + "file_name": "frame_0086.jpg", + "frame_idx": 86 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0087.json b/simulators/data/security/cam-west-02/metadata/frame_0087.json new file mode 100644 index 000000000..f07dd87d6 --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0087.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970610189, + "file_name": "frame_0087.jpg", + "frame_idx": 87 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0088.json b/simulators/data/security/cam-west-02/metadata/frame_0088.json new file mode 100644 index 000000000..d1d27de0a --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0088.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970611189, + "file_name": "frame_0088.jpg", + "frame_idx": 88 +} \ No newline at end of file diff --git a/simulators/data/security/cam-west-02/metadata/frame_0089.json b/simulators/data/security/cam-west-02/metadata/frame_0089.json new file mode 100644 index 000000000..c814c502d --- /dev/null +++ b/simulators/data/security/cam-west-02/metadata/frame_0089.json @@ -0,0 +1,6 @@ +{ + "camera_id": "cam-west-02", + "capture_time": 1762970612189, + "file_name": "frame_0089.jpg", + "frame_idx": 89 +} \ No newline at end of file diff --git a/simulators/data/sound/metadata/mic-1_20250916T191623Z.json b/simulators/data/sound/metadata/mic-1_20250916T191623Z.json index aeae61742..113596ed9 100644 --- a/simulators/data/sound/metadata/mic-1_20250916T191623Z.json +++ b/simulators/data/sound/metadata/mic-1_20250916T191623Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-1_20250916T191623Z.wav", - "device_id": "mic-1", - "capture_time": "2025-09-16T19:16:23Z", - "duration_sec": 5.0, - "done": false, - "sample_rate_hz": 16000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 31.89561, - "longitude": 34.9681 - } +{ + "file_name": "mic-1_20250916T191623Z.wav", + "device_id": "mic-1", + "capture_time": "2025-09-16T19:16:23Z", + "duration_sec": 5.0, + "done": false, + "sample_rate_hz": 16000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 31.89561, + "longitude": 34.8459 + } } \ No newline at end of file diff --git a/simulators/data/sound/metadata/mic-1_20250917T162528Z.json b/simulators/data/sound/metadata/mic-1_20250917T162528Z.json index a3f00a370..607d82e3e 100644 --- a/simulators/data/sound/metadata/mic-1_20250917T162528Z.json +++ b/simulators/data/sound/metadata/mic-1_20250917T162528Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-1_20250917T162528Z.wav", - "device_id": "mic-1", - "capture_time": "2025-09-17T16:25:28Z", - "duration_sec": 5.0, - "done": false, - "sample_rate_hz": 44100, - "channels": 2, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 31.89561, - "longitude": 34.9681 - } +{ + "file_name": "mic-1_20250917T162528Z.wav", + "device_id": "mic-1", + "capture_time": "2025-09-17T16:25:28Z", + "duration_sec": 5.0, + "done": false, + "sample_rate_hz": 44100, + "channels": 2, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 31.89561, + "longitude": 34.8459 + } } \ No newline at end of file diff --git a/simulators/data/sound/metadata/mic-2_20250917T182119Z.json b/simulators/data/sound/metadata/mic-2_20250917T182119Z.json index cbfe50df5..b3f104c42 100644 --- a/simulators/data/sound/metadata/mic-2_20250917T182119Z.json +++ b/simulators/data/sound/metadata/mic-2_20250917T182119Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-2_20250917T182119Z.wav", - "device_id": "mic-2", - "capture_time": "2025-09-17T18:21:19Z", - "duration_sec": 5.0, - "done": false, - "sample_rate_hz": 16000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 31.89561, - "longitude": 34.9681 - } +{ + "file_name": "mic-2_20250917T182119Z.wav", + "device_id": "mic-2", + "capture_time": "2025-09-17T18:21:19Z", + "duration_sec": 5.0, + "done": false, + "sample_rate_hz": 16000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 31.89561, + "longitude": 34.8459 + } } \ No newline at end of file diff --git a/simulators/data/sound/metadata/mic-33_20250917T162407Z.json b/simulators/data/sound/metadata/mic-33_20250917T162407Z.json index 8d25c7de7..8dde5f02d 100644 --- a/simulators/data/sound/metadata/mic-33_20250917T162407Z.json +++ b/simulators/data/sound/metadata/mic-33_20250917T162407Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-33_20250917T162407Z.wav", - "device_id": "mic-33", - "capture_time": "2025-09-17T16:24:07Z", - "duration_sec": 50.0, - "done": false, - "sample_rate_hz": 44100, - "channels": 2, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 31.89561, - "longitude": 34.9681 - } +{ + "file_name": "mic-33_20250917T162407Z.wav", + "device_id": "mic-33", + "capture_time": "2025-09-17T16:24:07Z", + "duration_sec": 50.0, + "done": false, + "sample_rate_hz": 44100, + "channels": 2, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 31.89561, + "longitude": 34.8459 + } } \ No newline at end of file diff --git a/simulators/data/ultra-sound/metadata/mic-u-2_20251003T120500Z.json b/simulators/data/ultra-sound/metadata/mic-u-2_20251003T120500Z.json index 904c0e9d7..43ce7d2a8 100644 --- a/simulators/data/ultra-sound/metadata/mic-u-2_20251003T120500Z.json +++ b/simulators/data/ultra-sound/metadata/mic-u-2_20251003T120500Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-u-2_20251003T120500Z.wav", - "device_id": "mic-u-2", - "capture_time": "2025-10-03T12:05:00Z", - "duration_sec": 0.002, - "done": false, - "sample_rate_hz": 500000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 32.89561, - "longitude": 30.9681 - } +{ + "file_name": "mic-u-2_20251003T120500Z.wav", + "device_id": "mic-u-2", + "capture_time": "2025-10-03T12:05:00Z", + "duration_sec": 0.002, + "done": false, + "sample_rate_hz": 500000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 32.89561, + "longitude": 30.9681 + } } \ No newline at end of file diff --git a/simulators/data/ultra-sound/metadata/mic-u-2_20251101T120500Z.json b/simulators/data/ultra-sound/metadata/mic-u-2_20251101T120500Z.json index ea64becee..d6ca0d3fc 100644 --- a/simulators/data/ultra-sound/metadata/mic-u-2_20251101T120500Z.json +++ b/simulators/data/ultra-sound/metadata/mic-u-2_20251101T120500Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-u-2_20251101T120500Z.wav", - "device_id": "mic-u-2", - "capture_time": "2025-11-01T12:05:00Z", - "duration_sec": 0.002, - "done": false, - "sample_rate_hz": 500000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 32.89561, - "longitude": 30.9681 - } +{ + "file_name": "mic-u-2_20251101T120500Z.wav", + "device_id": "mic-u-2", + "capture_time": "2025-11-01T12:05:00Z", + "duration_sec": 0.002, + "done": false, + "sample_rate_hz": 500000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 32.89561, + "longitude": 30.9681 + } } \ No newline at end of file diff --git a/simulators/data/ultra-sound/metadata/mic-u-2_20251102T120500Z.json b/simulators/data/ultra-sound/metadata/mic-u-2_20251102T120500Z.json index aa691f67c..d5a7b2360 100644 --- a/simulators/data/ultra-sound/metadata/mic-u-2_20251102T120500Z.json +++ b/simulators/data/ultra-sound/metadata/mic-u-2_20251102T120500Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-u-2_20251102T120500Z.wav", - "device_id": "mic-u-2", - "capture_time": "2025-11-02T12:05:00Z", - "duration_sec": 0.002, - "done": false, - "sample_rate_hz": 500000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 32.89561, - "longitude": 30.9681 - } +{ + "file_name": "mic-u-2_20251102T120500Z.wav", + "device_id": "mic-u-2", + "capture_time": "2025-11-02T12:05:00Z", + "duration_sec": 0.002, + "done": false, + "sample_rate_hz": 500000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 32.89561, + "longitude": 30.9681 + } } \ No newline at end of file diff --git a/simulators/data/ultra-sound/metadata/mic-u-2_20251102T140500Z.json b/simulators/data/ultra-sound/metadata/mic-u-2_20251102T140500Z.json index b2175772f..fdae67d8b 100644 --- a/simulators/data/ultra-sound/metadata/mic-u-2_20251102T140500Z.json +++ b/simulators/data/ultra-sound/metadata/mic-u-2_20251102T140500Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-u-2_20251102T140500Z.wav", - "device_id": "mic-u-2", - "capture_time": "2025-11-02T14:05:00Z", - "duration_sec": 0.002, - "done": false, - "sample_rate_hz": 500000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 32.89561, - "longitude": 30.9681 - } +{ + "file_name": "mic-u-2_20251102T140500Z.wav", + "device_id": "mic-u-2", + "capture_time": "2025-11-02T14:05:00Z", + "duration_sec": 0.002, + "done": false, + "sample_rate_hz": 500000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 32.89561, + "longitude": 30.9681 + } } \ No newline at end of file diff --git a/simulators/data/ultra-sound/metadata/mic-u-2_20251103T120500Z.json b/simulators/data/ultra-sound/metadata/mic-u-2_20251103T120500Z.json index 4c9194165..51251b6f5 100644 --- a/simulators/data/ultra-sound/metadata/mic-u-2_20251103T120500Z.json +++ b/simulators/data/ultra-sound/metadata/mic-u-2_20251103T120500Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-u-2_20251103T120500Z.wav", - "device_id": "mic-u-2", - "capture_time": "2025-11-03T12:05:00Z", - "duration_sec": 0.002, - "done": false, - "sample_rate_hz": 500000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 32.89561, - "longitude": 30.9681 - } +{ + "file_name": "mic-u-2_20251103T120500Z.wav", + "device_id": "mic-u-2", + "capture_time": "2025-11-03T12:05:00Z", + "duration_sec": 0.002, + "done": false, + "sample_rate_hz": 500000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 32.89561, + "longitude": 30.9681 + } } \ No newline at end of file diff --git a/simulators/data/ultra-sound/metadata/mic-u-2_20251104T120500Z.json b/simulators/data/ultra-sound/metadata/mic-u-2_20251104T120500Z.json index ec582d87f..268fa727e 100644 --- a/simulators/data/ultra-sound/metadata/mic-u-2_20251104T120500Z.json +++ b/simulators/data/ultra-sound/metadata/mic-u-2_20251104T120500Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-u-2_20251104T120500Z.wav", - "device_id": "mic-u-2", - "capture_time": "2025-11-04T12:05:00Z", - "duration_sec": 0.002, - "done": false, - "sample_rate_hz": 500000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 32.89561, - "longitude": 30.9681 - } +{ + "file_name": "mic-u-2_20251104T120500Z.wav", + "device_id": "mic-u-2", + "capture_time": "2025-11-04T12:05:00Z", + "duration_sec": 0.002, + "done": false, + "sample_rate_hz": 500000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 32.89561, + "longitude": 30.9681 + } } \ No newline at end of file diff --git a/simulators/data/ultra-sound/metadata/mic-u-2_20251105T120500Z.json b/simulators/data/ultra-sound/metadata/mic-u-2_20251105T120500Z.json index 47e76c56f..41fc118b5 100644 --- a/simulators/data/ultra-sound/metadata/mic-u-2_20251105T120500Z.json +++ b/simulators/data/ultra-sound/metadata/mic-u-2_20251105T120500Z.json @@ -1,14 +1,14 @@ -{ - "file_name": "mic-u-2_20251105T120500Z.wav", - "device_id": "mic-u-2", - "capture_time": "2025-11-05T12:05:00Z", - "duration_sec": 0.002, - "done": false, - "sample_rate_hz": 500000, - "channels": 1, - "content_type": "audio/wav", - "gis_origin": { - "latitude": 32.89561, - "longitude": 30.9681 - } +{ + "file_name": "mic-u-2_20251105T120500Z.wav", + "device_id": "mic-u-2", + "capture_time": "2025-11-05T12:05:00Z", + "duration_sec": 0.002, + "done": false, + "sample_rate_hz": 500000, + "channels": 1, + "content_type": "audio/wav", + "gis_origin": { + "latitude": 32.89561, + "longitude": 30.9681 + } } \ No newline at end of file diff --git a/simulators/docker-compose.yml b/simulators/docker-compose.yml index 36098b6b1..0dee1f194 100644 --- a/simulators/docker-compose.yml +++ b/simulators/docker-compose.yml @@ -1,31 +1,39 @@ services: data-publisher: - build: . - container_name: data-publisher - env_file: .env - volumes: - - ./data/air/images:/data/images:ro - - ./data/air/metadata:/data/metadata:ro - command: ["python", "-u", "/app/data_publisher.py"] + build: . + container_name: data-publisher + env_file: .env + volumes: + - ./data/air/images:/data/images:ro + - ./data/air/metadata:/data/metadata:ro + command: ["python", "-u", "/app/data_publisher.py"] sound-publisher: - build: . - container_name: sound-publisher - env_file: .env.sound - volumes: - - ./data/sound/sounds:/data/sound/sounds:ro - - ./data/sound/metadata:/data/sound/metadata:ro - command: ["python", "-u", "/app/data_publisher.py"] + build: . + container_name: sound-publisher + env_file: .env.sound + volumes: + - ./data/sound/sounds:/data/sound/sounds:ro + - ./data/sound/metadata:/data/sound/metadata:ro + command: ["python", "-u", "/app/data_publisher.py"] ultra-sound-publisher: - build: . - container_name: ultra-sound-publisher - env_file: .env.ultra - volumes: - - ./data/ultra/sounds:/data/ultra/sounds:ro - - ./data/ultra/metadata:/data/metadata:ro - command: ["python", "-u", "/app/data_publisher.py"] + build: . + container_name: ultra-sound-publisher + env_file: .env.ultra + volumes: + - ./data/ultra-sound/sounds:/data/ultra-sound/sounds:ro + - ./data/ultra-sound/metadata:/data/ultra-sound/metadata:ro + command: ["python", "-u", "/app/data_publisher.py"] + fruit-publisher: + build: . + container_name: fruit-publisher + env_file: .env.fruit + volumes: + - ./data/fruit/images:/data/fruit/images:ro + - ./data/fruit/metadata:/data/metadata:ro + command: ["python", "-u", "/app/data_publisher.py"] networks: default: external: true diff --git a/simulators/security/Dockerfile b/simulators/security/Dockerfile new file mode 100644 index 000000000..1118fa4a4 --- /dev/null +++ b/simulators/security/Dockerfile @@ -0,0 +1,27 @@ +# Use official Python slim image +FROM python:3.12-slim + +# Copy the NetFree certificate into the container + +# COPY netfree-ca.crt /usr/local/share/ca-certificates/netfree-ca.crt + +# COPY certs/*.crt /usr/local/share/ca-certificates/ + + +# Install system dependencies, add the certificate, and clean cache +RUN apt-get update && \ + apt-get install -y --no-install-recommends ca-certificates && \ + update-ca-certificates && \ + rm -rf /var/lib/apt/lists/* + +# Install Python dependencies +RUN pip install --no-cache-dir paho-mqtt + +# Set working directory +WORKDIR /app + +# Copy project files +COPY data_publisher.py . + +# Run the Python script +CMD ["python", "-u", "/app/data_publisher.py"] diff --git a/simulators/security/data_publisher.py b/simulators/security/data_publisher.py new file mode 100644 index 000000000..30eb929de --- /dev/null +++ b/simulators/security/data_publisher.py @@ -0,0 +1,177 @@ + +#!/usr/bin/env python3 +import os +import json +import time +import uuid +import hashlib +import mimetypes +import threading +from datetime import datetime, timezone +import paho.mqtt.client as mqtt + +# ───────────────────────────────────────────── +# Configuration +# ───────────────────────────────────────────── +SECURITY_DIR = os.getenv("SECURITY_DIR", "/security") + +MQTT_HOST_DATA = os.getenv("MQTT_HOST_DATA", "large-mosquitto") +MQTT_PORT_DATA = int(os.getenv("MQTT_PORT_DATA", "1885")) +MQTT_TOPIC_DATA = os.getenv("MQTT_TOPIC_DATA", "MQTT/imagery/security") + +MQTT_HOST_META = os.getenv("MQTT_HOST_META", "mosquitto") +MQTT_PORT_META = int(os.getenv("MQTT_PORT_META", "1883")) +MQTT_TOPIC_META = os.getenv("MQTT_TOPIC_META", "dev-security-images-keys") + +INTERVAL_PUBLISH = 0.8 +QOS = int(os.getenv("MQTT_QOS", "1")) + + +# ───────────────────────────────────────────── +# Helpers +# ───────────────────────────────────────────── +def sha256_hex(path: str): + with open(path, "rb") as f: + return hashlib.sha256(f.read()).hexdigest() + + +def iso_utc(): + return datetime.utcnow().replace(tzinfo=timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ") + + +def generate_new_name(ext=".jpg", camera_id="UNKNOWN"): + timestamp = datetime.utcnow().strftime("%Y%m%dT%H%M%SZ") + return f"{camera_id}_{timestamp}{ext}" + + +def load_metadata_for(img_path, metadata_dir): + base = os.path.splitext(os.path.basename(img_path))[0] + meta_path = os.path.join(metadata_dir, f"{base}.json") + if os.path.exists(meta_path): + with open(meta_path, "r", encoding="utf-8") as f: + return json.load(f) + return {} + + +def get_all_images(images_dir): + exts = {".jpg", ".jpeg", ".png", ".tif"} + return [ + os.path.join(images_dir, f) + for f in sorted(os.listdir(images_dir)) + if os.path.splitext(f)[1].lower() in exts + ] + + +# ───────────────────────────────────────────── +# Publishing logic +# ───────────────────────────────────────────── +def publish_image(image_path, metadata_dir, camera_id, client_images, client_meta): + ext = os.path.splitext(image_path)[1].lower() + meta_data = load_metadata_for(image_path, metadata_dir) + meta_data["camera_id"] = camera_id + new_file_name = generate_new_name(ext, camera_id) + meta_data["file_name"] = new_file_name + meta_data["capture_time"] = iso_utc() + + with open(image_path, "rb") as f: + data = f.read() + + timestamp_ms = int(time.time() * 1000) + + guessed_type, _ = mimetypes.guess_type(image_path) + if guessed_type: + content_type = guessed_type.replace("/", "_") + else: + content_type = "application_octet-stream" + + topic = f"{MQTT_TOPIC_DATA}/{timestamp_ms}/{content_type}/{new_file_name}" + client_images.publish(topic, payload=data, qos=QOS) + + payload = json.dumps(meta_data, ensure_ascii=False) + client_meta.publish(MQTT_TOPIC_META, payload, qos=QOS) + + print(f"[{camera_id}] Published image: {new_file_name} | topic: {topic} | type: {guessed_type}") + + +# ───────────────────────────────────────────── +# Per-camera worker (single run) +# ───────────────────────────────────────────── +def camera_worker(camera_path): + camera_id = os.path.basename(camera_path) + images_dir = os.path.join(camera_path, "images") + metadata_dir = os.path.join(camera_path, "metadata") + + if not os.path.isdir(images_dir): + print(f"[{camera_id}] Skipping: no /images folder found") + return + if not os.path.isdir(metadata_dir): + print(f"[{camera_id}] Warning: no /metadata folder found") + + # Create separate MQTT clients per camera + client_images = mqtt.Client(client_id=f"{camera_id}-img-{uuid.uuid4().hex[:6]}") + client_images.connect(MQTT_HOST_DATA, MQTT_PORT_DATA, keepalive=60) + client_images.loop_start() + + client_meta = mqtt.Client(client_id=f"{camera_id}-meta-{uuid.uuid4().hex[:6]}") + client_meta.connect(MQTT_HOST_META, MQTT_PORT_META, keepalive=60) + client_meta.loop_start() + + print(f"[{camera_id}] Started publishing thread") + + try: + all_imgs = get_all_images(images_dir) + if not all_imgs: + print(f"[{camera_id}] No images found, skipping.") + else: + for img in all_imgs: + publish_image(img, metadata_dir, camera_id, client_images, client_meta) + time.sleep(INTERVAL_PUBLISH) + + print(f"[{camera_id}] Finished publishing {len(all_imgs)} images.") + except Exception as e: + print(f"[{camera_id}] Error: {e}") + finally: + client_images.loop_stop() + client_images.disconnect() + client_meta.loop_stop() + client_meta.disconnect() + + +# ───────────────────────────────────────────── +# Main entry point +# ───────────────────────────────────────────── +def main(): + print("Camera simulator (single-run mode, multi-camera parallel)") + print(f"Root directory: {SECURITY_DIR}") + + if not os.path.isdir(SECURITY_DIR): + print(f"❌ SECURITY_DIR does not exist: {SECURITY_DIR}") + return + + camera_dirs = [ + os.path.join(SECURITY_DIR, d) + for d in os.listdir(SECURITY_DIR) + if os.path.isdir(os.path.join(SECURITY_DIR, d)) + ] + + if not camera_dirs: + print("❌ No camera directories found.") + return + + threads = [] + for cam_dir in camera_dirs: + t = threading.Thread(target=camera_worker, args=(cam_dir,)) + t.start() + threads.append(t) + + # Wait for all camera threads to finish + for t in threads: + t.join() + + print("✅ All cameras finished publishing. Exiting.") + + +if __name__ == "__main__": + main() + + diff --git a/simulators/security/docker-compose.yml b/simulators/security/docker-compose.yml new file mode 100644 index 000000000..a9b525fdb --- /dev/null +++ b/simulators/security/docker-compose.yml @@ -0,0 +1,24 @@ +services: + + data-publisher: + build: . + container_name: security-publisher + # env_file: .env + volumes: + - ../data/security:/security:ro + command: ["python", "-u", "/app/data_publisher.py"] + + # sound-publisher: + # build: . + # # image: data-publisher:latest # or 'build: .' again if you prefer + # container_name: sound-publisher + # env_file: .env.sound # separate env file for sound topics/ids + # volumes: + # - ./data/sound/sounds:/data/sound/sounds:ro + # - ./data/sound/metadata:/data/sound/metadata:ro + # command: ["python", "-u", "/app/data_publisher.py"] + +networks: + default: + external: true + name: agcloud_ag_cloud diff --git a/storage_with_mqtt/.gitignore b/storage_with_mqtt/.gitignore index 6a7c12c02..cf956e5a1 100644 --- a/storage_with_mqtt/.gitignore +++ b/storage_with_mqtt/.gitignore @@ -5,6 +5,7 @@ __pycache__/ *.pyd # Virtualenv +.venv/ venv/ .env .env.* diff --git a/storage_with_mqtt/data/config/config.json b/storage_with_mqtt/data/config/config.json new file mode 100644 index 000000000..1697d34c4 --- /dev/null +++ b/storage_with_mqtt/data/config/config.json @@ -0,0 +1,40 @@ +{ + "version": "10", + "aliases": { + "gcs": { + "url": "https://storage.googleapis.com", + "accessKey": "YOUR-ACCESS-KEY-HERE", + "secretKey": "YOUR-SECRET-KEY-HERE", + "api": "S3v2", + "path": "dns" + }, + "hot": { + "url": "http://minio-hot:9000", + "accessKey": "minioadmin", + "secretKey": "minioadmin123", + "api": "s3v4", + "path": "auto" + }, + "local": { + "url": "http://localhost:9000", + "accessKey": "", + "secretKey": "", + "api": "S3v4", + "path": "auto" + }, + "play": { + "url": "https://play.min.io", + "accessKey": "Q3AM3UQ867SPQQA43P2F", + "secretKey": "zuf+tfteSlswRu7BJ86wekitnifILbZam1KYY3TG", + "api": "S3v4", + "path": "auto" + }, + "s3": { + "url": "https://s3.amazonaws.com", + "accessKey": "YOUR-ACCESS-KEY-HERE", + "secretKey": "YOUR-SECRET-KEY-HERE", + "api": "S3v4", + "path": "dns" + } + } +} \ No newline at end of file diff --git a/storage_with_mqtt/data/config/config.json.old b/storage_with_mqtt/data/config/config.json.old new file mode 100644 index 000000000..9dff1de73 --- /dev/null +++ b/storage_with_mqtt/data/config/config.json.old @@ -0,0 +1,33 @@ +{ + "version": "10", + "aliases": { + "gcs": { + "url": "https://storage.googleapis.com", + "accessKey": "YOUR-ACCESS-KEY-HERE", + "secretKey": "YOUR-SECRET-KEY-HERE", + "api": "S3v2", + "path": "dns" + }, + "local": { + "url": "http://localhost:9000", + "accessKey": "", + "secretKey": "", + "api": "S3v4", + "path": "auto" + }, + "play": { + "url": "https://play.min.io", + "accessKey": "Q3AM3UQ867SPQQA43P2F", + "secretKey": "zuf+tfteSlswRu7BJ86wekitnifILbZam1KYY3TG", + "api": "S3v4", + "path": "auto" + }, + "s3": { + "url": "https://s3.amazonaws.com", + "accessKey": "YOUR-ACCESS-KEY-HERE", + "secretKey": "YOUR-SECRET-KEY-HERE", + "api": "S3v4", + "path": "dns" + } + } +} \ No newline at end of file diff --git a/storage_with_mqtt/data/config/share/downloads.json b/storage_with_mqtt/data/config/share/downloads.json new file mode 100644 index 000000000..75362d1d0 --- /dev/null +++ b/storage_with_mqtt/data/config/share/downloads.json @@ -0,0 +1,4 @@ +{ + "version": "1", + "shares": {} +} \ No newline at end of file diff --git a/storage_with_mqtt/data/config/share/uploads.json b/storage_with_mqtt/data/config/share/uploads.json new file mode 100644 index 000000000..75362d1d0 --- /dev/null +++ b/storage_with_mqtt/data/config/share/uploads.json @@ -0,0 +1,4 @@ +{ + "version": "1", + "shares": {} +} \ No newline at end of file diff --git a/storage_with_mqtt/docker-compose.yml b/storage_with_mqtt/docker-compose.yml index 453282381..31bb24ae7 100644 --- a/storage_with_mqtt/docker-compose.yml +++ b/storage_with_mqtt/docker-compose.yml @@ -152,6 +152,9 @@ services: volumes: - ./storage/monitoring/provisioning:/etc/grafana/provisioning:ro - ./storage/monitoring/grafana-dashboard.json:/var/lib/grafana/dashboards/minio-dashboard.json:ro + # --NetFree-- + - ./certs/company-ca.crt:/usr/local/share/ca-certificates/company-ca.crt:ro + command: ["/bin/sh","-c","update-ca-certificates && /run.sh"] networks: minionet: diff --git a/storage_with_mqtt/mqtt_images/mqtt_ingest/Dockerfile b/storage_with_mqtt/mqtt_images/mqtt_ingest/Dockerfile index bcdb44863..a27d23994 100644 --- a/storage_with_mqtt/mqtt_images/mqtt_ingest/Dockerfile +++ b/storage_with_mqtt/mqtt_images/mqtt_ingest/Dockerfile @@ -1,5 +1,4 @@ -# syntax=docker/dockerfile:1 -FROM python:3.12-slim +FROM python:3.11-slim # Build argument ARG USE_NETFREE=true diff --git a/storage_with_mqtt/mqtt_images/mqtt_ingest/app.py b/storage_with_mqtt/mqtt_images/mqtt_ingest/app.py index 8fc9344d4..7fd26d5bd 100644 --- a/storage_with_mqtt/mqtt_images/mqtt_ingest/app.py +++ b/storage_with_mqtt/mqtt_images/mqtt_ingest/app.py @@ -142,21 +142,41 @@ def parse_topic(topic: str) -> dict: ns, idx = "sounds", parts_lower.index("sounds") if ns == "imagery": - # format: MQTT/imagery//// - if len(parts) > idx + 1 and parts[idx + 1]: - result["camera"] = parts[idx + 1] - if len(parts) > idx + 2 and parts[idx + 2]: - try: - ts = int(parts[idx + 2]) - if ts > 0: - result["publish_ts_ms"] = ts - except ValueError: - pass - if len(parts) > idx + 3 and parts[idx + 3]: - result["content_type"] = parts[idx + 3].replace("_", "/") - if len(parts) > idx + 4 and parts[idx + 4]: - result["filename"] = parts[idx + 4] + tail = parts[-3:] if len(parts) >= 3 else parts + head = parts[idx + 1 : len(parts) - 3] if len(parts) > idx + 4 else parts[idx + 1 : idx + 2] + if head: + if FORCE_DEVICE_ID: + result["camera"] = FORCE_DEVICE_ID + prefix = "/".join(head) + else: + result["camera"] = head[-1] + prefix = "/".join(head[:-1]) + else: + prefix = "" + print(f"[DEBUG] result['camera']={result['camera']}, prefix={prefix}, FORCE_DEVICE_ID={FORCE_DEVICE_ID}", flush=True) + try: + result["publish_ts_ms"] = int(tail[0]) + except Exception: + pass + if len(tail) >= 2: + result["content_type"] = tail[1].replace("_", "/") + if len(tail) >= 3: + result["filename"] = tail[2] + + # --- DEBUG + try to detect device from filename --- + filename_base = os.path.splitext(result["filename"])[0] + if "_" in filename_base: + possible_device = filename_base.split("_")[0] + print(f"[DEBUG] filename_base={filename_base}, possible_device={possible_device}", flush=True) + if possible_device.lower().startswith("fruit") or possible_device.lower().startswith("camera"): + result["camera"] = possible_device + print(f"[DEBUG] DETECTED device from filename -> {result['camera']}", flush=True) + else: + print(f"[DEBUG] filename does not match expected pattern", flush=True) + else: + print(f"[DEBUG] filename_base has no '-': {filename_base}", flush=True) + result["extra_prefix"] = prefix elif ns in ("sounds", "sounds_ultra"): if len(parts) > idx + 1 and parts[idx + 1]: try: @@ -190,6 +210,8 @@ def parse_topic(topic: str) -> dict: date_part = datetime.fromtimestamp(result["publish_ts_ms"] / 1000, tz=timezone.utc).strftime("%Y-%m-%d") device_id = result["camera"] + if FORCE_DEVICE_ID: + device_id = FORCE_DEVICE_ID if result["media_type"] == "sounds": if device_id.startswith(f"{CAMERA_PREFIX}-"): @@ -206,11 +228,16 @@ def parse_topic(topic: str) -> dict: else: device_name = f"{CAMERA_PREFIX}-{device_id}" - # key = f"{result['media_type']}/{device_name}/{date_part}/{result['publish_ts_ms']}/{result['filename']}" is_ultra = ns == "sounds_ultra" - topdir = ULTRA_DIR_PREFIX if is_ultra else result["media_type"] - key = f"{topdir}/{device_name}/{date_part}/{result['publish_ts_ms']}/{result['filename']}" - + topdir = ULTRA_DIR_PREFIX if is_ultra else result["media_type"] + if ns == "imagery": + subpath = "/".join(parts[idx + 1 : -3]) + if subpath: + key = f"{subpath}/{device_name}/{date_part}/{result['publish_ts_ms']}/{result['filename']}" + else: + key = f"{topdir}/{device_name}/{date_part}/{result['publish_ts_ms']}/{result['filename']}" + else: + key = f"{topdir}/{device_name}/{date_part}/{result['publish_ts_ms']}/{result['filename']}" result["key"] = key result["device_id"] = device_name result["image_id"] = stem(result["filename"]) or uuid.uuid4().hex @@ -473,4 +500,4 @@ def _stop(*_): print("INGEST stopped.", flush=True) if __name__ == "__main__": - main() + main() \ No newline at end of file diff --git a/storage_with_mqtt/mqtt_images/mqtt_publisher/app.py b/storage_with_mqtt/mqtt_images/mqtt_publisher/app.py index a3897a753..86d653f35 100644 --- a/storage_with_mqtt/mqtt_images/mqtt_publisher/app.py +++ b/storage_with_mqtt/mqtt_images/mqtt_publisher/app.py @@ -2,6 +2,8 @@ import os, time, glob, random, pathlib import paho.mqtt.client as mqtt from paho.mqtt.client import CallbackAPIVersion +import json +import random HOST = os.getenv("MQTT_HOST", "large-mosquitto") PORT = int(os.getenv("MQTT_PORT", "1885")) @@ -65,6 +67,28 @@ def on_connect(client, userdata, flags, reason_code, properties): r = client.publish(topic, payload=data, qos=QOS) r.wait_for_publish() sent += 1 + # --- Telemetry publish (same ts_ms & sensor) --- + # Configurable base position via env (optional): + BASE_LAT = float(os.getenv("BASE_LAT", "32.061")) + BASE_LON = float(os.getenv("BASE_LON", "34.772")) + BASE_HDG = float(os.getenv("BASE_HDG", "180")) + BASE_SPD = float(os.getenv("BASE_SPD", "2.0")) + + def _jitter(base: float, j: float = 0.0005) -> float: + # ~50m random jitter around the base point + import random + return base + random.uniform(-j, j) + + telemetry = { + "lat": round(_jitter(BASE_LAT), 6), + "lon": round(_jitter(BASE_LON), 6), + "heading": round(BASE_HDG + __import__("random").uniform(-10, 10), 1), + "speed_mps": round(max(0.0, __import__("random").gauss(BASE_SPD, 0.5)), 2), + } + telemetry_topic = f"{TOPIC_BASE.replace('imagery', 'telemetry')}/{CAMERA_ID}/{ts_ms}" + client.publish(telemetry_topic, payload=json.dumps(telemetry).encode("utf-8"), qos=QOS) + # --- end telemetry publish --- + if DELAY_MS > 0: time.sleep(DELAY_MS / 1000.0) except Exception as e: diff --git a/storage_with_mqtt/storage/Lifecycle_rules/minio-bootstrap/Dockerfile b/storage_with_mqtt/storage/Lifecycle_rules/minio-bootstrap/Dockerfile index d5b4d94f9..362870915 100644 --- a/storage_with_mqtt/storage/Lifecycle_rules/minio-bootstrap/Dockerfile +++ b/storage_with_mqtt/storage/Lifecycle_rules/minio-bootstrap/Dockerfile @@ -1,27 +1,38 @@ # ============================ -# Stage 1: copy mc binary +# Stage 1: get mc binary # ============================ FROM minio/mc:latest AS mc-source + # ============================ # Stage 2: main image # ============================ FROM alpine:3.19 -# ===== Install dependencies ===== -# include dos2unix so line endings are normalized automatically -RUN apk add --no-cache bash curl ca-certificates netcat-openbsd dos2unix && \ + +# Install base tools +RUN apk add --no-cache \ + bash \ + curl \ + ca-certificates \ + netcat-openbsd \ + dos2unix && \ update-ca-certificates + # ===== Add NetFree CA ===== -COPY certs/*.crt /usr/local/share/ca-certificates/ -RUN update-ca-certificates -# ===== Copy mc from the official image ===== +RUN mkdir -p /usr/local/share/ca-certificates +COPY certs/ /usr/local/share/ca-certificates/ +RUN update-ca-certificates || true + +# ---------------------------- +# Install mc (MinIO client) +# ---------------------------- COPY --from=mc-source /usr/bin/mc /usr/local/bin/mc RUN chmod +x /usr/local/bin/mc -# ===== Create directories ===== + +# ---------------------------- +# Entrypoint script +# ---------------------------- RUN mkdir -p /entrypoint /config -# ===== Copy init script ===== COPY entrypoint/init.sh /entrypoint/init.sh -# ===== Normalize and ensure execution permissions ===== -# (this guarantees LF endings + execute permission for everyone) RUN dos2unix /entrypoint/init.sh && chmod 755 /entrypoint/init.sh -# ===== Entry point ===== + CMD ["/entrypoint/init.sh"] diff --git a/storage_with_mqtt/storage/Lifecycle_rules/minio-bootstrap/entrypoint/init.sh b/storage_with_mqtt/storage/Lifecycle_rules/minio-bootstrap/entrypoint/init.sh index 16b388157..9b988eeb3 100644 --- a/storage_with_mqtt/storage/Lifecycle_rules/minio-bootstrap/entrypoint/init.sh +++ b/storage_with_mqtt/storage/Lifecycle_rules/minio-bootstrap/entrypoint/init.sh @@ -21,6 +21,11 @@ echo "[bootstrap] Waiting for COLD (${COLD_ENDPOINT})..." until mc ls "${MC_ALIAS_COLD}" >/dev/null 2>&1; do sleep 2; done echo "[bootstrap] Creating buckets..." + +# Allow anonymous download on all HOT buckets +mc anonymous set download "${MC_ALIAS_HOT}/sound" || true +mc anonymous set download "${MC_ALIAS_HOT}/imagery" || true + mc mb "${MC_ALIAS_HOT}/imagery" || true mc mb "${MC_ALIAS_HOT}/sound" || true mc mb "${MC_ALIAS_COLD}/imagery" || true @@ -171,7 +176,7 @@ mc event add "${MC_ALIAS_HOT}/imagery" \ mc event add "${MC_ALIAS_HOT}/imagery" \ arn:minio:sqs::fruits:kafka \ --event put \ - --prefix "fruits/" + --prefix "fruit/tree" mc event add "${MC_ALIAS_HOT}/imagery" \ arn:minio:sqs::leaves:kafka \ diff --git a/streaming/flink/Dockerfile.flink-py b/streaming/flink/Dockerfile.flink-py index 60664e730..f0ae765ce 100644 --- a/streaming/flink/Dockerfile.flink-py +++ b/streaming/flink/Dockerfile.flink-py @@ -5,7 +5,30 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ python3 python3-pip python3-venv curl && \ rm -rf /var/lib/apt/lists/* +# Optional extra CA certs (e.g. NetFree) from ./certs +COPY certs/ /tmp/certs + +RUN set -eux; \ + if [ -d /tmp/certs ] && ls /tmp/certs/*.crt >/dev/null 2>&1; then \ + echo "Adding extra CA certs from /tmp/certs ..."; \ + cp /tmp/certs/*.crt /usr/local/share/ca-certificates/; \ + chmod 644 /usr/local/share/ca-certificates/*.crt; \ + update-ca-certificates; \ + else \ + echo "No extra CA certs found, skipping."; \ + fi + +# System-wide SSL env (works with or without extra CAs) +ENV SSL_CERT_FILE=/etc/ssl/certs/ca-certificates.crt \ + REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt \ + PIP_CERT=/etc/ssl/certs/ca-certificates.crt + + +# Python deps (with trusted-host for NetFree) RUN python3 -m pip install --no-cache-dir \ + --trusted-host pypi.org \ + --trusted-host pypi.python.org \ + --trusted-host files.pythonhosted.org \ "apache-flink==1.18.1" \ aiohttp==3.9.5 \ minio==7.2.7 \ diff --git a/streaming/flink/jobs/http_dispatcher.py b/streaming/flink/jobs/http_dispatcher.py index 5fcdfb553..671b1db60 100644 --- a/streaming/flink/jobs/http_dispatcher.py +++ b/streaming/flink/jobs/http_dispatcher.py @@ -85,7 +85,11 @@ async def _make_session(self, timeout: aiohttp.ClientTimeout) -> aiohttp.ClientS async def _post_once(self, url: str, payload: Dict[str, Any], headers: Dict[str, str]): async with self.session.post(url, json=payload, headers=headers) as resp: - return resp.status, await resp.text() + try: + data = await resp.json() + except Exception: + data = await resp.text() + return resp.status, data async def _post_with_retry(self, url: str, payload: Dict[str, Any], headers: Dict[str, str]): attempt = 0 @@ -111,33 +115,57 @@ def map(self, s: str) -> str: # 1) Parse JSON try: event = json.loads(s) + # Handle double-encoded JSON strings (common in Kafka/MinIO) + if isinstance(event, str): + event = json.loads(event) except Exception as e: return json.dumps( {"ok": False, "status": 422, "body": f"bad json: {e}", "raw": s, "stage": "parse"}, ensure_ascii=False ) - # 2) Generate idempotency key event_id = event.get("event_id") or str(uuid.uuid4()) + + # 3) Extract bucket/key – support both native and MinIO S3-event formats + import sys, urllib.parse - # 3) Validate fields: must have bucket+key; image_uri not allowed - if "image_uri" in event: - return json.dumps( - {"ok": False, "status": 422, - "body": "image_uri not supported; use {bucket,key} only", - "event": event, "stage": "validate"}, - ensure_ascii=False - ) + def dbg(msg: str): + sys.stdout.write(f"[DEBUG] {msg}\n") + sys.stdout.flush() bucket = event.get("bucket") key = event.get("key") - if not bucket or not key: - return json.dumps( - {"ok": False, "status": 422, - "body": "missing required fields: bucket and key", - "event": event, "stage": "validate"}, - ensure_ascii=False - ) + + # Try to detect MinIO S3 event format + if (not bucket or not key): + # Case A: nested Records structure + records = event.get("Records") + if isinstance(records, list) and len(records) > 0: + try: + rec = records[0] + s3_block = rec.get("s3", {}) + bucket = s3_block.get("bucket", {}).get("name") + raw_key = s3_block.get("object", {}).get("key") + if raw_key: + key = urllib.parse.unquote(raw_key) + if key.startswith("imagery/"): + key = key[len("imagery/"):] + dbg(f"Parsed from S3 event: bucket={bucket}, key={key}") + except Exception as e: + dbg(f"Error parsing S3 event: {e}") + # Case B: flat event with Key field + elif "Key" in event and isinstance(event["Key"], str): + key = event["Key"] + if key.startswith("imagery/"): + key = key[len("imagery/"):] + bucket = "imagery" + dbg(f"Parsed flat event: bucket={bucket}, key={key}") + # Case C: nested body from previous inference + if (not bucket or not key) and isinstance(event.get("body"), dict): + body = event["body"] + bucket = body.get("bucket") or body.get("bucket_out") + key = body.get("key") + dbg(f"Parsed nested body: bucket={bucket}, key={key}") # 4) Prepare headers and payload: send only bucket/key to the inference service headers = { @@ -239,4 +267,4 @@ def _is_ok(s: str) -> bool: if __name__ == "__main__": - main() + main() \ No newline at end of file diff --git a/templates/templates.yml b/templates/templates.yml index aae4b76db..228971b89 100644 --- a/templates/templates.yml +++ b/templates/templates.yml @@ -4,17 +4,90 @@ templates: summary: "🚨 Smoke detected by ${device_id} near ${area} (confidence ${confidence})" recommendation: "Inspect the ${area} immediately. If fire is confirmed, contact emergency services." - masked_person: - category: security - summary: "Person wearing a mask detected by ${device_id} at ${timestamp}" - recommendation: "Verify the person’s authorization using the live feed." - fruit_ripeness_high: category: agriculture summary: "🍓 High fruit ripeness detected by ${device_id} (${confidence} ≥ ${threshold})" recommendation: "Harvest or inspect the plantation area. Ripe/overripe fruits ratio: ${description}" + + fence_hole: + category: security + summary: "🚧 Fence hole detected by ${device_id} in ${area} (conf ${confidence})" + recommendation: "Dispatch a patrol to ${area} and review recent footage." + plant_drought_detected: category: agriculture - summary: "🌿 Plant drought detected by ${device_id} in ${area} (severity ${severity}, confidence ${confidence})" + summary: "🌿 Plant drought detected by ${device_id} (severity ${severity}, confidence ${confidence})" recommendation: "Check irrigation in ${area}. Status: ${watering_status}. Audio file: ${file}" + + suspicious_sound-predatory_animals: + category: security + summary: "⚠️ Predatory animal sound detected by ${device_id} (confidence ${confidence})" + recommendation: "Stay alert and avoid the area until confirmed safe." + + suspicious_sound-non_predatory_animals: + category: environment + summary: "🐾 Animal sounds detected by ${device_id}" + recommendation: "No immediate action required. Monitor if sounds persist." + + suspicious_sound-birds: + category: environment + summary: "🐦 Bird activity detected by ${device_id}" + recommendation: "Normal environmental sounds. No action needed." + + suspicious_sound-fire: + category: emergency + summary: "🔥 Possible fire sounds detected by ${device_id} (confidence ${confidence})" + recommendation: "Inspect the area for signs of fire and alert authorities if confirmed." + + suspicious_sound-footsteps: + category: security + summary: "👣 Footsteps detected by ${device_id} at ${timestamp}" + recommendation: "Check surveillance feed or nearby activity." + + suspicious_sound-insects: + category: environment + summary: "🐝 Insect sounds detected by ${device_id}" + recommendation: "Low concern. Suitable for ecological monitoring." + + suspicious_sound-screaming: + category: emergency + summary: "🚨 Screaming detected by ${device_id}" + recommendation: "Verify immediately. Contact security or emergency services if needed." + + suspicious_sound-shotgun: + category: security + summary: "🔫 Possible gunshot detected by ${device_id}" + recommendation: "Treat as high-priority event. Notify authorities immediately." + + suspicious_sound-stormy_weather: + category: environmental + summary: "🌩️ Storm sounds detected by ${device_id}" + recommendation: "Monitor weather alerts and secure outdoor equipment." + + suspicious_sound-streaming_water: + category: environmental + summary: "💧 Flowing water detected by ${device_id}" + recommendation: "Check for flooding or irrigation system leaks." + + suspicious_sound-vehicle: + category: movement + summary: "🚗 Vehicle detected by ${device_id} at ${timestamp}" + recommendation: "Verify authorized vehicle access in ${area}." + + + masked_person: + category: security + summary: "Person wearing a mask detected by ${device_id}" + recommendation: "Verify the person’s authorization using the live feed." + + "intruding animal": + category: security + summary: "🐾 Intruding ${subject} detected by ${device_id}" + recommendation: "Assess whether the ${subject} poses a threat or damage risk. Consider activating deterrent systems or notifying farm personnel." + + climbing_fence: + category: perimeter + summary: "🧗 Fence-climbing activity of ${subject} detected by ${device_id}" + recommendation: "Inspect the fence section immediately. Possible intruder or wildlife breach attempt." + diff --git a/tools/send_alert_kafka.py b/tools/send_alert_kafka.py new file mode 100644 index 000000000..02ecf9b8f --- /dev/null +++ b/tools/send_alert_kafka.py @@ -0,0 +1,54 @@ +import json, uuid, argparse, datetime +from kafka import KafkaProducer + +# --------- CLI --------- +p = argparse.ArgumentParser(description="Send alert to Kafka") +p.add_argument("--bootstrap", default="localhost:9092") +p.add_argument("--topic", default="alerts") +p.add_argument("--alert-type", required=True) +p.add_argument("--device-id", required=True) +p.add_argument("--started-at", default=None, help="ISO8601; default=now UTC") +p.add_argument("--lat", type=float, default=None) +p.add_argument("--lon", type=float, default=None) +p.add_argument("--image-url", default=None) +p.add_argument("--severity", type=int, default=3) +p.add_argument("--area", default="north_field") +args = p.parse_args() + +# --------- Build payload --------- +# NOTE: Comments are NOT sent; kept here for clarity +payload = { + # --- Required fields --- + "alert_id": str(uuid.uuid4()), + "alert_type": args.alert_type, # e.g. "fence_hole" or "smoke_detected" + "device_id": args.device_id, # e.g. "camera-01" + "started_at": ( + args.started_at + if args.started_at + else datetime.datetime.now(datetime.timezone.utc).isoformat() + ), + # --- Optional fields --- + "confidence": None, # fill by your detector if available + "severity": args.severity, + "area": args.area, + "lat": args.lat, + "lon": args.lon, + "image_url": args.image_url, + "meta": {}, # you can enrich with bucket/key, etc. +} + +# Remove None fields to keep payload clean +payload = {k: v for k, v in payload.items() if v is not None} + +# --------- Send --------- +producer = KafkaProducer( + bootstrap_servers=args.bootstrap, + value_serializer=lambda v: json.dumps(v, ensure_ascii=False).encode("utf-8"), + linger_ms=50, + retries=5, +) +fut = producer.send(args.topic, payload) +rec = fut.get(timeout=10) +producer.flush() +print(f"OK: topic={args.topic} partition={rec.partition} offset={rec.offset}") +print(json.dumps(payload, ensure_ascii=False))