Update app.py

app.py

@@ -244,18 +244,23 @@ def predict(image):
     input_name = model.get_inputs()[0].name
     input_shape = model.get_inputs()[0].shape
 
-    print("start", image.shape)
+    print("start", image.shape) #start (720, 1280, 3)
+
 
     # Resize the image to the model's input shape
     image = cv2.resize(image, (input_shape[2], input_shape[3]))
     
-    print("after resize", image.shape)
+    print("after resize", image.shape) # after resize (640, 640, 3)
+
+    image = image.reshape(3, 640, 640)
+
+    print("after reshape", image.shape) # after reshape
 
     # 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)
+    image = image.astype(np.float32) # after expands/astype (1, 640, 640, 3)
 
     print("after expands/astype", image.shape)