Adds super class

Author: robmarkcole

README.md

@@ -3,9 +3,15 @@
 [![build status](http://img.shields.io/travis/robmarkcole/deepstack-python/master.svg?style=flat)](https://travis-ci.org/robmarkcole/deepstack-python)
 
 # deepstack-python
-Unofficial python API for DeepStack. Provides class for making requests to the object detection endpoint, and functions for processing the result. See the `usage.ipynb` notebook for usage.
+Unofficial python API for [DeepStack](https://python.deepstack.cc/). Provides class for making requests to the object detection endpoint, and functions for processing the result. See the `usage.ipynb` notebook for usage.
+
+## Services
+Face and object detection endpoints return bounding boxes of faces and objects respectively. 
+
+TODO: add face registration and recognition.
 
 ## Development
-* Use `venv`
+* Use `venv` -> `source venv/bin/activate`
 * `pip install -r requirements-dev.txt`
 * Run tests with `venv/bin/pytest tests/*`
+* Black format with `venv/bin/black deepstack/core.py`

deepstack/core.py

@@ -9,6 +9,10 @@
 HTTP_OK = 200
 DEFAULT_TIMEOUT = 10  # seconds
 
+## API urls
+URL_OBJECT_DETECTION = "http://{}:{}/v1/vision/detection"
+URL_FACE_DETECTION = "http://{}:{}/v1/vision/face"
+
 
 def format_confidence(confidence: Union[str, float]) -> float:
     """Takes a confidence from the API like 
@@ -70,21 +74,21 @@ class DeepstackException(Exception):
     pass
 
 
-class DeepstackObject:
-    """The object detection API locates and classifies 80 
-    different kinds of objects in a single image.."""
+class Deepstack(object):
+    """Base class for deepstack."""
 
     def __init__(
         self,
         ip_address: str,
         port: str,
         api_key: str = "",
         timeout: int = DEFAULT_TIMEOUT,
+        url_detection: str = "",
     ):
 
-        self._url_object_detection = "http://{}:{}/v1/vision/detection".format(
-            ip_address, port
-        )
+        self._ip_address = ip_address
+        self._port = port
+        self._url_detection = url_detection
         self._api_key = api_key
         self._timeout = timeout
         self._predictions = []
@@ -97,10 +101,9 @@ def process_file(self, file_path: str):
     def process_image_bytes(self, image_bytes: bytes):
         """Process an image."""
         self._predictions = []
+        url = self._url_detection.format(self._ip_address, self._port)
 
-        response = post_image(
-            self._url_object_detection, image_bytes, self._api_key, self._timeout
-        )
+        response = post_image(url, image_bytes, self._api_key, self._timeout)
 
         if response.status_code == HTTP_OK:
             if response.json()["success"]:
@@ -113,3 +116,18 @@ def process_image_bytes(self, image_bytes: bytes):
     def predictions(self):
         """Return the classifier attributes."""
         return self._predictions
+
+
+class DeepstackObject(Deepstack):
+    """Work with objects"""
+
+    def __init__(
+        self,
+        ip_address: str,
+        port: str,
+        api_key: str = "",
+        timeout: int = DEFAULT_TIMEOUT,
+    ):
+        super().__init__(
+            ip_address, port, api_key, timeout, url_detection=URL_OBJECT_DETECTION
+        )

usage.ipynb

@@ -88,7 +88,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -117,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -143,7 +143,7 @@
        "  'x_max': 825}]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -162,7 +162,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -178,16 +178,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['person', 'dog']"
+       "['dog', 'person']"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -205,16 +205,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'person': 2, 'dog': 1}"
+       "{'dog': 1, 'person': 2}"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -226,16 +226,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['person', 'dog']"
+       "['dog', 'person']"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -253,7 +253,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -262,7 +262,7 @@
        "[0.9998661, 0.9996547]"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -281,9 +281,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1\n"
+     ]
+    }
+   ],
    "source": [
     "CONFIDENCE_THRESHOLD = 0.9997\n",
     "print(len(ds.get_confidences_above_threshold(confidences, CONFIDENCE_THRESHOLD)))"