main.py

import cv2
import numpy as np
import csv
import os
from datetime import datetime
import time

# === Configuration ===
VIDEO_SOURCE = 0  # Replace with 0 for webcam or path to CCTV footage
CASCADE_PATH = "haarcascade_car.xml"  # Pre-trained car detector

# === Initialize video ===
cap = cv2.VideoCapture(VIDEO_SOURCE)
car_cascade = cv2.CascadeClassifier(CASCADE_PATH)

if not cap.isOpened():
    print("❌ Error: Cannot open video source!")
    exit()

# === Setup counters and parameters ===
line_y = 400
counter = 0
object_id = 0
objects = {}
counted = set()
paused = False

# === Setup log folder ===
if not os.path.exists("logs"):
    os.makedirs("logs")

csv_path = "logs/car_log.csv"

if not os.path.exists(csv_path):
    with open(csv_path, "w", newline="") as f:
        csv.writer(f).writerow(["Car_ID", "Timestamp", "Count", "X", "Y"])

def distance(p1, p2):
    return np.sqrt((p1[0]-p2[0])**2 + (p1[1]-p2[1])**2)

# === FPS calculation ===
prev_time = time.time()
fps = 0

print("🚗 Car Detection & Counting Started...")
print("Press 'q' to quit, 'p' to pause/resume, 'r' to reset counter.")

while True:
    if not paused:
        ret, frame = cap.read()
        if not ret:
            print("End of video or camera disconnected.")
            break

        # Convert to grayscale (for Haar cascade)
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        cars = car_cascade.detectMultiScale(gray, 1.1, 4)

        current_objects = {}
        cv2.line(frame, (0, line_y), (frame.shape[1], line_y), (0, 0, 255), 2)

        for (x, y, w, h) in cars:
            cx, cy = x + w // 2, y + h // 2

            matched = False
            for oid, (ox, oy) in objects.items():
                if distance((cx, cy), (ox, oy)) < 50:
                    current_objects[oid] = (cx, cy)
                    matched = True

                    # Count when crossing the red line
                    if oid not in counted and line_y - 10 <= cy <= line_y + 10:
                        counter += 1
                        counted.add(oid)

                        with open(csv_path, "a", newline="") as f:
                            csv.writer(f).writerow([
                                oid, datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
                                counter, cx, cy
                            ])

                        cv2.imwrite(f"logs/car_{oid}_{counter}.jpg", frame[y:y+h, x:x+w])
                    break

            if not matched:
                object_id += 1
                current_objects[object_id] = (cx, cy)

            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
            cv2.putText(frame, f'Car {object_id}', (x, y - 10),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 255), 2)

        objects = current_objects.copy()

        # === FPS Calculation ===
        curr_time = time.time()
        fps = 1 / (curr_time - prev_time)
        prev_time = curr_time

        cv2.putText(frame, f'Cars Counted: {counter}', (30, 50),
                    cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 2)
        cv2.putText(frame, f'FPS: {int(fps)}', (30, 90),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 2)

    cv2.imshow("🚘 Real-Time Car Tracker (CCTV)", frame)

    key = cv2.waitKey(1) & 0xFF
    if key == ord('q'):
        break
    elif key == ord('p'):
        paused = not paused
    elif key == ord('r'):
        counter = 0
        counted.clear()
        print("Counter reset!")

cap.release()
cv2.destroyAllWindows()

print("\n🟢 Tracking Ended")
print(f"🔹 Total Cars Counted: {counter}")
print(f"🔹 Logs saved at: {csv_path}")