Update app.py

app.py

@@ -24,9 +24,6 @@ with gr.Blocks() as demo:
 
     class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',
            'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']
-
-    # Normalize the pixel values
-    img = np.array(img) / 255.0
     
     # clothing dataset
     mnist = tf.keras.datasets.mnist
@@ -72,7 +69,10 @@ with gr.Blocks() as demo:
         
     def classifyImage(img):
         #global probability_model
-        #global class_names
+        #global class_names      
+        
+        # Normalize the pixel values
+        img = np.array(img) / 255.0
         
         input_array = np.expand_dims(img, axis=0) # add an extra dimension to represent the batch size