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b7221a3
1 Parent(s): df954f0

Update app.py

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  1. app.py +11 -5
app.py CHANGED
@@ -58,7 +58,7 @@ def process_document(image):
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  sequence = sequence.replace(processor.tokenizer.eos_token, "").replace(processor.tokenizer.pad_token, "")
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  sequence = re.sub(r"<.*?>", "", sequence, count=1).strip() # remove first task start token
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- return processor.token2json(sequence)
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  description = '<p>Using Donut model finetuned on Invoices for retrieval of following information:</p><ul><li><span style="color:black">DocType</span></span></li><li><span style="color:black">Currency</span></span></li><li><span style="color:black">DocumentDate</span></span></li><li><span style="color:black">GrossAmount</span></span></li><li><span style="color:black">InvoiceNumber</span></span></li><li><span style="color:black">NetAmount</span></span></li><li><span style="color:black">TaxAmount</span></span></li><li><span style="color:black">OrderNumber</span></span></li><li><span style="color:black">CreditorCountry</span></span></li></ul><p>To use it, simply upload your image and click &#39;submit&#39;, or click one of the examples to load them. Read more at the links below.</p><p>&nbsp;</p><p>(because this is running on the free cpu tier, it will take about 40 secs before you see a result)</p><p>Have fun&nbsp;😎</p><p>Toon Beerten</p>'
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  article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2111.15664' target='_blank'>Donut: OCR-free Document Understanding Transformer</a> | <a href='https://github.com/clovaai/donut' target='_blank'>Github Repo</a></p>"
@@ -79,14 +79,20 @@ with gr.Blocks(css=css) as demo:
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  gr.Markdown(title)
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  gr.Markdown(description)
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- inp = gr.Image(label='Upload invoice here:',elem_id="inp") #.style(height=400)
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  with gr.Row().style():
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  with gr.Column(scale=1):
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- gr.Examples([["example.jpg"], ["example_2.jpg"], ["example_3.jpg"]], inputs=[inp])
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  with gr.Column():
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- out = gr.JSON(label='Extracted information:')
 
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  btn = gr.Button("Extract")
 
 
 
 
 
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- btn.click(fn=process_document, inputs=inp, outputs=out)
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  demo.launch()
 
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  sequence = sequence.replace(processor.tokenizer.eos_token, "").replace(processor.tokenizer.pad_token, "")
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  sequence = re.sub(r"<.*?>", "", sequence, count=1).strip() # remove first task start token
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+ return processor.token2json(sequence), image
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  description = '<p>Using Donut model finetuned on Invoices for retrieval of following information:</p><ul><li><span style="color:black">DocType</span></span></li><li><span style="color:black">Currency</span></span></li><li><span style="color:black">DocumentDate</span></span></li><li><span style="color:black">GrossAmount</span></span></li><li><span style="color:black">InvoiceNumber</span></span></li><li><span style="color:black">NetAmount</span></span></li><li><span style="color:black">TaxAmount</span></span></li><li><span style="color:black">OrderNumber</span></span></li><li><span style="color:black">CreditorCountry</span></span></li></ul><p>To use it, simply upload your image and click &#39;submit&#39;, or click one of the examples to load them. Read more at the links below.</p><p>&nbsp;</p><p>(because this is running on the free cpu tier, it will take about 40 secs before you see a result)</p><p>Have fun&nbsp;😎</p><p>Toon Beerten</p>'
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  article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2111.15664' target='_blank'>Donut: OCR-free Document Understanding Transformer</a> | <a href='https://github.com/clovaai/donut' target='_blank'>Github Repo</a></p>"
 
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  gr.Markdown(title)
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  gr.Markdown(description)
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+
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  with gr.Row().style():
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  with gr.Column(scale=1):
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+ inp = gr.Image(label='Upload invoice here:') #.style(height=400)
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  with gr.Column():
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+ gr.Examples([["example.jpg"], ["example_2.jpg"], ["example_3.jpg"]], inputs=[inp])
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+ with gr.Row().style():
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  btn = gr.Button("Extract")
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+ with gr.Row().style():
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+ with gr.Column(scale=1):
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+ imgout = gr.Image(label='Uploaded document:',elem_id="inp")
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+ with gr.Column(scale=1):
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+ jsonout = gr.JSON(label='Extracted information:')
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+ btn.click(fn=process_document, inputs=inp, outputs=[jsonout,imgout])
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  demo.launch()