rajistics commited on
Commit
82e65b0
Β·
1 Parent(s): 33e48a5

Markdown edits

Browse files
Files changed (1) hide show
  1. app.py +1 -3
app.py CHANGED
@@ -80,9 +80,7 @@ def process_image(image):
80
 
81
 
82
  title = "Extracting Receipts: LayoutLMv3"
83
- description = "Demo for Microsoft's LayoutLMv3, a Transformer for state-of-the-art document image understanding tasks. \
84
- This particular model is fine-tuned from [LayoutLMv3](https://huggingface.co/microsoft/layoutlmv3-base) on Consolidated Receipt Dataset ([CORD] (https://github.com/clovaai/cord), 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 [notebook by Niels](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LayoutLMv3). \
85
- 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. "
86
 
87
  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>"
88
  examples =[['test0.jpeg'],['test1.jpeg'],['test2.jpeg']]
 
80
 
81
 
82
  title = "Extracting Receipts: LayoutLMv3"
83
+ description = "Demo for Microsoft's LayoutLMv3, a Transformer for state-of-the-art document image understanding tasks. This particular model is fine-tuned from [LayoutLMv3](https://huggingface.co/microsoft/layoutlmv3-base) on Consolidated Receipt Dataset ([CORD] (https://github.com/clovaai/cord), 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 [notebook by Niels](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LayoutLMv3). 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. "
 
 
84
 
85
  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>"
86
  examples =[['test0.jpeg'],['test1.jpeg'],['test2.jpeg']]