rajistics commited on
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f87e896
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1 Parent(s): af1ca19

Got it, I think

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  1. app.py +2 -2
app.py CHANGED
@@ -80,9 +80,9 @@ def process_image(image):
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  title = "Extracting Receipts: LayoutLMv3"
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- description = """<p Demo for Microsoft's LayoutLMv3, a Transformer for state-of-the-art document image understanding tasks. </p> <p This particular model is fine-tuned from
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  <a href="https://github.com/clovaai/cord">CORD</a> on the Consolidated Receipt Dataset, a dataset of receipts. If you search the πŸ€— Hugging Face hub you will see other related models fine-tuned for other documents. This model is trained using fine-tuning to look for entities around menu items, subtotal, and total prices. To perform your own fine-tuning, take a look at the
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- <a href="https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LayoutLMv3">notebook by Niels</a>. </p> <p To try it out, simply upload an image or use the example image below and click 'Submit'. Results will show up in a few seconds. To see the output bigger, right-click on it, select 'Open image in new tab', and use your browser's zoom feature. </p>"""
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  article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2204.08387' target='_blank'>LayoutLMv3: Multi-modal Pre-training for Visually-Rich Document Understanding</a> | <a href='https://github.com/microsoft/unilm' target='_blank'>Github Repo</a></p>"
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  examples =[['test0.jpeg'],['test1.jpeg'],['test2.jpeg']]
 
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  title = "Extracting Receipts: LayoutLMv3"
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+ description = """<p> Demo for Microsoft's LayoutLMv3, a Transformer for state-of-the-art document image understanding tasks. </p> <p> This particular model is fine-tuned from
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  <a href="https://github.com/clovaai/cord">CORD</a> on the Consolidated Receipt Dataset, a dataset of receipts. If you search the πŸ€— Hugging Face hub you will see other related models fine-tuned for other documents. This model is trained using fine-tuning to look for entities around menu items, subtotal, and total prices. To perform your own fine-tuning, take a look at the
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+ <a href="https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LayoutLMv3">notebook by Niels</a>. </p> <p> To try it out, simply upload an image or use the example image below and click 'Submit'. Results will show up in a few seconds. To see the output bigger, right-click on it, select 'Open image in new tab', and use your browser's zoom feature. </p>"""
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  article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2204.08387' target='_blank'>LayoutLMv3: Multi-modal Pre-training for Visually-Rich Document Understanding</a> | <a href='https://github.com/microsoft/unilm' target='_blank'>Github Repo</a></p>"
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  examples =[['test0.jpeg'],['test1.jpeg'],['test2.jpeg']]