Update app.py

app.py

@@ -10,12 +10,12 @@ inputs = gr.inputs.Image()
 output = gr.outputs.Image()
 
 
-def predict(image_input):
+def predict(inputs):
   img = np.array(inputs)
 
   im = tf.image.resize(img, (128, 128))
   im = tf.cast(im, tf.float32) / 255.0
-  pred_mask = self.model.predict(im[tf.newaxis, ...])
+  pred_mask = model.predict(im[tf.newaxis, ...])
   
   # take the best performing class for each pixel
   # the output of argmax looks like this [[1, 2, 0], ...]