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import gradio as gr |
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import subprocess |
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def nougat_ocr(file_name): |
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print('******* inside nougat_ocr *******') |
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cli_command = [ |
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'nougat', |
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'--out', 'output', |
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'pdf', f'{file_name}', |
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'--checkpoint', 'nougat' |
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] |
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subprocess.run(cli_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True) |
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return |
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def predict(pdf_file): |
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print('******* inside predict *******') |
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print(f"temporary file - {pdf_file.name}") |
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pdf_name = pdf_file.name.split('/')[-1].split('.')[0] |
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print(f"pdf file name - {pdf_name}") |
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nougat_ocr(pdf_file.name) |
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print("BAACCKKK") |
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with open(f'output/{pdf_name}.mmd', 'r') as file: |
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content = file.read() |
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return content |
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with gr.Blocks() as demo: |
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gr.HTML("<h1><center>Nougat: Neural Optical Understanding for Academic Documents<center><h1>") |
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gr.HTML("<h3><center>Lukas Blecher et al. <a href='https://arxiv.org/pdf/2308.13418.pdf' target='_blank'>Paper</a>, <a href='https://facebookresearch.github.io/nougat/'>Project</a><center></h3>") |
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with gr.Row(): |
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pdf_file = gr.File(label='Upload a PDF', scale=1) |
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mkd = gr.Markdown('<h2><center><i>OR</i></center></h2>',scale=1) |
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pdf_link = gr.Textbox(placeholder='Enter an arxiv link here', label='Provide a link', scale=1) |
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btn = gr.Button() |
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parsed_output = gr.Markdown() |
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btn.click(predict, pdf_file, parsed_output ) |
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demo.queue() |
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demo.launch(debug=True) |
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