debug print

app.py

@@ -18,12 +18,14 @@ output_layer = compiled_model.output(0)
 ##### 
 def predict(img: np.ndarray) -> str:
     # input: numpy array of image in RGB (see defaults for https://www.gradio.app/docs/#image)
-    
+    print(f'initial image shape: {img.shape}')
     # The MobileNet model expects images in RGB format.
     # Resize to MobileNet image shape.
     input_image = cv2.resize(src=img, dsize=(224, 224))
+    print(f'resized: {img.shape}')
     # Reshape to model input shape.
     input_image = np.expand_dims(input_image, 0)
+    print(f'final shape: {img.shape}')
     
     # Get inference result
     result_infer = compiled_model([input_image])[output_layer]