Update main.py

main.py

@@ -28,12 +28,11 @@ model1.add(keras.layers.Conv2D(3, (9, 9), activation='tanh', padding='same'))
 model1.load_weights('modelV13_500trained_1.h5')
 
 def predict(mask):
-  X = numpy.round((mask/255.0))[numpy.newaxis, :, :, numpy.newaxis]
-  v = model1.predict(X)*255
-  output = (v - v.min()) / (v.max() - v.min())
-  print(output.shape)
-  return output[0, :, :, 0], output[0, :, :, 1], output[0, :, :, 2]
+    X = numpy.round((mask/255.0))[numpy.newaxis, :, :, numpy.newaxis]
+    v = model1.predict(X)*255
+    output = (v - v.min()) / (v.max() - v.min())
+    print(output.shape)
+    return output[0, :, :, 0], output[0, :, :, 1], output[0, :, :, 2]
 
 demo = gradio.Interface(fn=predict, inputs=gradio.Image(image_mode="L", source="canvas", tool="sketch", values=numpy.zeros(636, 101), outputs=[gradio.Image(image_mode="L"), gradio.Image(image_mode="L"), gradio.Image(image_mode="L")])
-
 demo.run()