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__author__ = 'Taneem Jan, taneemishere.github.io' |
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import gradio as gr |
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import main_program |
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def model_interface(image): |
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return main_model(image) |
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def main_model(input_image): |
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result = main_program.main_method(input_image) |
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return result |
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interface_title = "<br> <p style='margin: 0% 8% 0% 8%'>HTML Code Generation from Images with Deep Neural Networks</p>" |
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interface_description = """<p style='margin: 0% 8% 2% 8%; text-align: justify;text-justify: inter-word;'> Writing |
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code in a programming language for a designed mockup or a graphical user interface created by designers and UI |
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engineers, is done mostly by developers to build and develop custom websites and software. The development work is |
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not approachable by those unfamiliar with programming, to drive these personas capable of designing and developing |
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the code bases and website structures we come up with an automated system. In this work, we showed and proposed that |
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methods of deep learning and computer vision can be grasped to train a model that will automatically generate HTML |
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code from a single input mockup image and try to build an end-to-end automated system with around 88% of accuracy for |
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developing the structures of web pages.</p> """ |
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interface_article = """<div style='text-align: center;'> <br><br><a href='https://twitter.com/taneemishere' |
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target='_blank'>Developed by Taneem Jan</a> </div> |
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<div style='text-align: center;'> <a href='https://taneemishere.github.io/projects/project-one.html' |
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target='_blank'>Paper</a>     <a href='https://github.com/taneemishere/html-code-generation-from-images-with-deep-neural-networks' |
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target='_blank'>Code</a> </div> |
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""" |
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interface = gr.Interface( |
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model_interface, |
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inputs='image', |
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outputs='text', |
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allow_flagging="manual", |
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title=interface_title, |
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description=interface_description, |
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article=interface_article |
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) |
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interface.launch(share=False) |
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