Upload handler.py

handler.py

@@ -6,58 +6,68 @@ import cv2
 import base64
 from inference_sdk import InferenceHTTPClient
 
-class EndpointHandler():
-    def __init__(self, key): #pass api key to model
+
+class EndpointHandler:
+    def __init__(self):  # pass api key to model
         pass
-        
+
     def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
         inputs = data.get("inputs")
         isurl = inputs.get("isurl")
         path = inputs.get("path")
         key = inputs.get("key")
-###########################  Load Image  #################################       
-        CLIENT = InferenceHTTPClient(
-            api_url="https://detect.roboflow.com",
-            api_key=key
-        )
-        if(isurl): # for url set isurl = 1
+        ###########################  Load Image  #################################
+        CLIENT = InferenceHTTPClient(api_url="https://detect.roboflow.com", api_key=key)
+        if isurl:  # for url set isurl = 1
             req = urllib.request.urlopen(path)
             arr = np.asarray(bytearray(req.read()), dtype=np.uint8)
-            img = cv2.imdecode(arr, -1) # 'Load it as it is'
-        else: # for image file
+            img = cv2.imdecode(arr, -1)  # 'Load it as it is'
+        else:  # for image file
             img = cv2.imread(path)
-###########################################################################       
-            
-        
-###########################  Model Detection  #################################
-        # change model_id to use a different model 
-        # can try: 
+        ###########################################################################
+
+        ###########################  Model Detection  #################################
+        # change model_id to use a different model
+        # can try:
         # clothing-segmentation-dataset/1
         # t-shirts-detector/1
         # mainmodel/2
         result = CLIENT.infer(path, model_id="mainmodel/2")
         detections = sv.Detections.from_inference(result)
         # print(detections)
-###########################################################################
-
+        ###########################################################################
 
-###########################  Data proccessing  #################################
+        ###########################  Data proccessing  #################################
         # only pass the first detection
         # change 1 -> to len(detections.xyxy) to pass all photos
-        if(detections.confidence.size == 0): 
+        if detections.confidence.size == 0:
             return "Not Found"
         else:
-            x1, y1, x2, y2 = int(detections.xyxy[0][0]), int(detections.xyxy[0][1]), int(detections.xyxy[0][2]), int(detections.xyxy[0][3])
-            clothes = img[y1: y2, x1: x2]
-            retval , buffer = cv2.imencode('.jpg', clothes)     
+            x1, y1, x2, y2 = (
+                int(detections.xyxy[0][0]),
+                int(detections.xyxy[0][1]),
+                int(detections.xyxy[0][2]),
+                int(detections.xyxy[0][3]),
+            )
+            clothes = img[y1:y2, x1:x2]
+            retval, buffer = cv2.imencode(".jpg", clothes)
         # create base 64 object
-        jpg_as_text = base64.b64encode(buffer)
-###########################################################################
+        jpg_as_text = base64.b64encode(buffer) # Decode bytes to string
+        ###########################################################################
         return jpg_as_text
-###########################################################################    
-    
-    
-    
-#  test run  
-# Model = Image_detect("api key")
-# print(Model("test_images/test5.jpg", 0))
+
+
+###########################################################################
+
+
+# data = {
+#     "inputs": {
+#         "isurl": True,
+#         "path": "http://192.168.10.20/cam-hi.jpg",
+#         "key": "iJuYzEzNEFSaQq4e0hfE",
+#     }
+# }
+
+# #  test run
+# Model = EndpointHandler()
+# print(Model(data))