Adds scene

README.md

@@ -3,17 +3,41 @@
 [![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](https://python.deepstack.cc/). Provides class for making requests to the object detection endpoint, and functions for processing the result. See the Jupyter notebooks for usage.
-Run deepstack (CPU, noAVX mode):
+Unofficial python API for [DeepStack](https://python.deepstack.cc/). Provides classes for making requests to the object detection & face detection/recognition endpoints. Also includes some helper functions for processing the results. See the Jupyter notebooks for usage.
+
+Run deepstack with all three endpoints active (CPU, noAVX mode):
+```
+docker run \
+      -e VISION-SCENE=True \
+      -e VISION-DETECTION=True \
+      -e VISION-FACE=True \
+      -v localstorage:/datastore \
+      -p 5000:5000 \
+      -e API-KEY="" \
+      --name deepstack deepquestai/deepstack:noavx
+```
+Check deepstack is running using curl (from root of this repo):
+```
+curl -X POST -F image=@tests/images/test-image3.jpg 'http://localhost:5000/v1/vision/detection'
 ```
-docker run -e VISION-DETECTION=True -e VISION-FACE=True -e MODE=High -d \
-      -v localstorage:/datastore -p 5000:5000 \
-      -e API-KEY="Mysecretkey" \
-       --name deepstack deepquestai/deepstack:noavx
+If all goes well you should see the following returned:
+```
+{"success":true,"predictions":[{"confidence":0.9998661,"label":"person","y_min":0,"x_min":258,"y_max":676,"x_max":485},{"confidence":0.9996547,"label":"person","y_min":0,"x_min":405,"y_max":652,"x_max":639},{"confidence":0.99745613,"label":"dog","y_min":311,"x_min":624,"y_max":591,"x_max":825}]}
 ```
 
 ## Development
-* Use `venv` -> `source venv/bin/activate`
-* `pip install -r requirements-dev.txt`
+* Create venv -> `python3.7 -m venv venv`
+* Use venv -> `source venv/bin/activate`
+* `pip3 install -r requirements.txt` and `pip3 install -r requirements-dev.txt`
 * Run tests with `venv/bin/pytest tests/*`
 * Black format with `venv/bin/black deepstack/core.py` and `venv/bin/black tests/test_deepstack.py`
+
+## Jupyter
+* Docs are created using Jupyter notebooks
+* Install in venv with -> `pip3 install jupyterlab`
+* Run -> `venv/bin/jupyter lab`
+
+## Deployment to pypi
+* Generate requirements with -> `pip3 freeze > requirements.txt`
+* Create a distribution with -> `python3 setup.py sdist` (creates dist)
+* Upload packages with twine with -> `twine upload dist/*`

deepstack/core.py

@@ -14,6 +14,7 @@
 URL_FACE_DETECTION = "http://{}:{}/v1/vision/face"
 URL_FACE_REGISTRATION = "http://{}:{}/v1/vision/face/register"
 URL_FACE_RECOGNITION = "http://{}:{}/v1/vision/face/recognize"
+URL_SCENE_DETECTION = "http://{}:{}/v1/vision/scene"
 
 
 def format_confidence(confidence: Union[str, float]) -> float:
@@ -113,26 +114,27 @@ def __init__(
         self._url_detection = url_detection
         self._api_key = api_key
         self._timeout = timeout
-        self._predictions = []
+        self._response = None
 
     def detect(self, image_bytes: bytes):
         """Process image_bytes, performing detection."""
-        self._predictions = []
+        self._response = None
         url = self._url_detection.format(self._ip_address, self._port)
 
         response = post_image(url, image_bytes, self._api_key, self._timeout)
 
-        if response.status_code == HTTP_OK:
-            if response.json()["success"]:
-                self._predictions = response.json()["predictions"]
-            else:
-                error = response.json()["error"]
-                raise DeepstackException(f"Error from Deepstack: {error}")
+        if not response.status_code == HTTP_OK:
+            raise DeepstackException(f"Error from request: {response.status_code}")
+            return
+
+        self._response = response.json()
+        if not self._response["success"]:
+            raise DeepstackException(f"Error from Deepstack: {error}")
 
     @property
     def predictions(self):
-        """Return the classifier attributes."""
-        return self._predictions
+        """Return the predictions."""
+        raise NotImplementedError
 
 
 class DeepstackObject(Deepstack):
@@ -149,6 +151,31 @@ def __init__(
             ip_address, port, api_key, timeout, url_detection=URL_OBJECT_DETECTION
         )
 
+    @property
+    def predictions(self):
+        """Return the predictions."""
+        return self._response["predictions"]
+
+
+class DeepstackScene(Deepstack):
+    """Work with scenes"""
+
+    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_SCENE_DETECTION
+        )
+
+    @property
+    def predictions(self):
+        """Return the predictions."""
+        return self._response
+
 
 class DeepstackFace(Deepstack):
     """Work with objects"""
@@ -164,6 +191,11 @@ def __init__(
             ip_address, port, api_key, timeout, url_detection=URL_FACE_DETECTION
         )
 
+    @property
+    def predictions(self):
+        """Return the classifier attributes."""
+        return self._response["predictions"]
+
     def register_face(self, name: str, image_bytes: bytes):
         """
         Register a face name to a file.
@@ -185,14 +217,14 @@ def register_face(self, name: str, image_bytes: bytes):
 
     def recognise(self, image_bytes: bytes):
         """Process image_bytes, performing recognition."""
-        self._predictions = []
         url = URL_FACE_RECOGNITION.format(self._ip_address, self._port)
 
         response = post_image(url, image_bytes, self._api_key, self._timeout)
 
-        if response.status_code == HTTP_OK:
-            if response.json()["success"]:
-                self._predictions = response.json()["predictions"]
-            else:
-                error = response.json()["error"]
-                raise DeepstackException(f"Error from Deepstack: {error}")
+        if not response.status_code == HTTP_OK:
+            raise DeepstackException(f"Error from request: {response.status_code}")
+            return
+
+        self._response = response.json()
+        if not self._response["success"]:
+            raise DeepstackException(f"Error from Deepstack: {error}")

requirements-dev.txt

@@ -1,3 +1,4 @@
 pytest
 black
-requests_mock
+requests_mock
+matplotlib