Update app.py

app.py

@@ -248,21 +248,23 @@ def predict(image):
     image = cv2.resize(image, (input_shape[2], input_shape[3]))
     image = image.reshape(3, 640, 640)
 
+    # Normalize the image
+    mean = [0.485, 0.456, 0.406]
+    std = [0.229, 0.224, 0.225]
+    image = (image / 255.0 - mean)/std
+
+    print("normalized image:" image.shape)
+    
     # Convert the image to a numpy array and add a batch dimension
     if len(input_shape) == 4 and input_shape[0] == 1:
         image = np.expand_dims(image, axis=0)
     
     image = image.astype(np.float32) # after expands/astype (1, 640, 640, 3)
-
-    # Normalize the image
-    mean = [0.485, 0.456, 0.406]
-    std = [0.229, 0.224, 0.225]
-    image = (image / 255.0 - mean)/std
     
     # Perform inference
     output = model.run(None, {input_name: image})
     # print(type(output))
-    # print(output)
+    print("model.run worked")
 
     return output