Update handler.py

handler.py

@@ -4,27 +4,33 @@ import requests
 from io import BytesIO
 from PIL import Image
 import time
+import os
 
 
 class EndpointHandler():
     def __init__(self, path=""):
         # load the model
-        print('Loading the yolo model')
-        model_path = "yolov8m_detect_usdl.pt"
-        self.model = YOLO(model_path)
-        print('Yolo model loaded successfully')
+        print(f'value of path is : {path}')
+        current_directory = os.getcwd()
+        print(f'current dir: {current_directory}')
+        print(f'all files: {os.listdir(current_directory)}')
+        # model_path = "yolov8m_detect_usdl.pt"
+        # self.model = YOLO(model_path)
+        # print('Yolo model loaded successfully')
 
 
     def __call__(self, data: Dict) -> Dict:
 
-        image_url = data.get('image_url')
-        print(f'Image url is : {image_url}')
-        response = requests.get(image_url)
-        pil_image = Image.open(BytesIO(response.content))
+        print(f'Value of data is : {data}')
+
+        # image_url = data.get('image_url')
+        # print(f'Image url is : {image_url}')
+        # response = requests.get(image_url)
+        # pil_image = Image.open(BytesIO(response.content))
         
-        print('Model inference started....')
-        t1 = time.time()
-        results = self.model(pil_image)
-        print(f'TIME Model inference: {time.time() - t1}')
-        # postprocess the prediction
-        return {"bbox": results[0].boxes.data.tolist()}
+        # print('Model inference started....')
+        # t1 = time.time()
+        # results = self.model(pil_image)
+        # print(f'TIME Model inference: {time.time() - t1}')
+        # postprocess the prediction -> results[0].boxes.data.tolist()
+        return {"bbox": 'data'}