Upload handler.py

handler.py

@@ -0,0 +1,57 @@
+import supervision as sv
+import urllib.request
+import numpy as np
+import cv2
+import base64
+from inference_sdk import InferenceHTTPClient
+
+class Image_detect:
+    def __init__(self, key): #pass api key to model
+        self.CLIENT = InferenceHTTPClient(
+            api_url="https://detect.roboflow.com",
+            api_key=key
+        )
+        
+    def __call__(self, path , isurl):    
+###########################  Load Image  #################################       
+        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.imread(path)
+###########################################################################       
+            
+        
+###########################  Model Detection  #################################
+        # change model_id to use a different model 
+        # can try: 
+        # clothing-segmentation-dataset/1
+        # t-shirts-detector/1
+        # mainmodel/2
+        result = self.CLIENT.infer(path, model_id="mainmodel/2")
+        detections = sv.Detections.from_inference(result)
+        # print(detections)
+###########################################################################
+
+
+###########################  Data proccessing  #################################
+        # only pass the first detection
+        # change 1 -> to len(detections.xyxy) to pass all photos
+        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)     
+        # create base 64 object
+        jpg_as_text = base64.b64encode(buffer)
+###########################################################################
+        return jpg_as_text
+###########################################################################    
+    
+    
+    
+#  test run  
+# Model = Image_detect("api key")
+# print(Model("test_images/test5.jpg", 0))