Update app.py

app.py

@@ -20,13 +20,13 @@ def predict(image):
 # determined by the first position in the shape tuple, in this case 1.
     data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)
 # Replace this with the path to your image
-    image = gr.inputs.Image()
+    
 #resize the image to a 224x224 with the same strategy as in TM2:
 #resizing the image to be at least 224x224 and then cropping from the center
     size = (224, 224)
-    
+    image = gr.inputs.Image()
     image = ImageOps.fit(image, size, Image.Resampling.LANCZOS)
-
+    
 #turn the image into a numpy array
     image_array = np.asarray(image)
 # Normalize the image