Revise description

app.py

@@ -71,8 +71,8 @@ input3 = gr.Image(shape=(28, 28), type='numpy', image_mode='L', label='Third ima
 output = [gr.Label(), gr.Plot()]
 # output = [gr.Plot()]
 # it's good practice to pass examples, description and a title to guide users
-title = 'Image classification'
-description = 'Upload an image'
+title = 'Bag of Image Classification'
+description = 'This is the demo for Keras Implementation of Classification using Attention-based Deep Multiple Instance Learning (MIL). The model will try to predict whether number 8 is within the set of input images. As it was trained on MNIST dataset, please use MNIST image for precise result.'
 
 gr_interface = gr.Interface(
     infer, inputs=[input1, input2, input3], outputs=output, allow_flagging='never',
@@ -83,6 +83,3 @@ gr_interface = gr.Interface(
                 ['samples/5.png', 'samples/6.png', 'samples/3.png'], ['samples/7.png', 'samples/8.png', 'samples/9.png']]
 )
 gr_interface.launch(enable_queue=True, debug=True, inbrowser=True)
-
-# gr_interface = gr.Interface(infer, input, output, examples=examples, allow_flagging=False, analytics_enabled=False, title=title, description=description).launch(enable_queue=True, debug=False)
-# gr_interface.launch()