Catch exceptions

Author: robmarkcole

deepstack/core.py

@@ -9,7 +9,7 @@
 HTTP_OK = 200
 HTTP_BAD_REQUEST = 400
 HTTP_UNAUTHORIZED = 401
-TIMEOUT = 20  # seconds
+DEFAULT_TIMEOUT = 10  # seconds
 
 
 def format_confidence(confidence: Union[str, float]) -> float:
@@ -55,21 +55,40 @@ def get_objects_summary(predictions: List[Dict]):
     }
 
 
-def post_image(url: str, image: bytes):
+def post_image(url: str, image: bytes, api_key: str, timeout: int):
     """Post an image to Deepstack."""
-    response = requests.post(url, files={"image": image}, timeout=TIMEOUT)
-    return response
+    try:
+        response = requests.post(
+            url, files={"image": image}, data={"api_key": api_key}, timeout=timeout
+        )
+        return response
+    except requests.exceptions.Timeout:
+        raise DeepstackException(
+            f"Timeout connecting to Deepstack, current timeout is {timeout} seconds"
+        )
+
+
+class DeepstackException(Exception):
+    pass
 
 
 class DeepstackObject:
     """The object detection API locates and classifies 80 
     different kinds of objects in a single image.."""
 
-    def __init__(self, ip_address: str, port: str):
+    def __init__(
+        self,
+        ip_address: str,
+        port: str,
+        api_key: str = "",
+        timeout: int = DEFAULT_TIMEOUT,
+    ):
 
         self._url_object_detection = "http://{}:{}/v1/vision/detection".format(
             ip_address, port
         )
+        self._api_key = api_key
+        self._timeout = timeout
         self._predictions = []
 
     def process_file(self, file_path: str):
@@ -81,10 +100,16 @@ def process_image_bytes(self, image_bytes: bytes):
         """Process an image."""
         self._predictions = []
 
-        response = post_image(self._url_object_detection, image_bytes)
-        if response:
-            if response.status_code == HTTP_OK:
+        response = post_image(
+            self._url_object_detection, 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}")
 
     @property
     def predictions(self):

usage.ipynb

@@ -15,32 +15,36 @@
    "source": [
     "import deepstack.core as ds\n",
     "from PIL import Image\n",
+    "import pprint\n",
     "import matplotlib.pyplot as plt\n",
     "%matplotlib inline"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
     "IP_ADDRESS = 'localhost'\n",
-    "PORT = '5000'"
+    "PORT = '5000'\n",
+    "API_KEY = \"Mysecretkey\"\n",
+    "# API_KEY = \"BadKey\"\n",
+    "TIMEOUT = 8"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
-    "dsobject = ds.DeepstackObject(IP_ADDRESS, PORT)"
+    "dsobject = ds.DeepstackObject(IP_ADDRESS, PORT, API_KEY, TIMEOUT)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -71,21 +75,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 7.72 ms, sys: 6.6 ms, total: 14.3 ms\n",
-      "Wall time: 7.63 s\n"
+      "[{'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}]\n"
      ]
     }
    ],
    "source": [
-    "%%time\n",
-    "dsobject.process_file(image_path)"
+    "#%%time\n",
+    "try:\n",
+    "    dsobject.process_file(image_path)\n",
+    "    print(dsobject.predictions)\n",
+    "except ds.DeepstackException as exc:\n",
+    "    print(exc)"
    ]
   },
   {
@@ -97,7 +104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -123,7 +130,7 @@
        "  'x_max': 825}]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -142,7 +149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -158,7 +165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -167,7 +174,7 @@
        "{'dog', 'person'}"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -185,16 +192,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'dog': 1, 'person': 2}"
+       "{'person': 2, 'dog': 1}"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -212,7 +219,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -221,7 +228,7 @@
        "[0.9998661, 0.9996547]"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -240,23 +247,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "[0.9998661]"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1\n"
+     ]
     }
    ],
    "source": [
     "CONFIDENCE_THRESHOLD = 0.9997\n",
-    "ds.get_confidences_above_threshold(confidences, CONFIDENCE_THRESHOLD)"
+    "print(len(ds.get_confidences_above_threshold(confidences, CONFIDENCE_THRESHOLD)))"
    ]
   },
   {