rajistics commited on
Commit
f0ccd65
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1 Parent(s): 06faa9e

Removed lower

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Files changed (1) hide show
  1. app.py +3 -3
app.py CHANGED
@@ -74,7 +74,7 @@ def process_image(image):
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  draw = ImageDraw.Draw(image)
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  font = ImageFont.load_default()
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  for prediction, box in zip(true_predictions, true_boxes):
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- predicted_label = iob_to_label(prediction).lower()
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  print (predicted_label)
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  print (label2color[predicted_label])
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  #draw.rectangle(box, outline=label2color[predicted_label])
@@ -84,9 +84,9 @@ def process_image(image):
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  title = "Interactive demo: LayoutLMv3"
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- description = "Demo for Microsoft's LayoutLMv3, a Transformer for state-of-the-art document image understanding tasks. This particular model is fine-tuned on FUNSD, a dataset of manually annotated forms. It annotates the words appearing in the image as QUESTION/ANSWER/HEADER/OTHER. To use it, simply upload an image or use the example image below and click 'Submit'. Results will show up in a few seconds. If you want to make the output bigger, right-click on it and select 'Open image in new tab'."
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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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  css = ".output-image, .input-image {height: 40rem !important; width: 100% !important;}"
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  #css = "@media screen and (max-width: 600px) { .output_image, .input_image {height:20rem !important; width: 100% !important;} }"
 
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  draw = ImageDraw.Draw(image)
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  font = ImageFont.load_default()
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  for prediction, box in zip(true_predictions, true_boxes):
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+ predicted_label = iob_to_label(prediction) #.lower()
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  print (predicted_label)
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  print (label2color[predicted_label])
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  #draw.rectangle(box, outline=label2color[predicted_label])
 
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  title = "Interactive demo: LayoutLMv3"
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+ description = "Demo for Microsoft's LayoutLMv3, a Transformer for state-of-the-art document image understanding tasks. This particular model is fine-tuned on CORD, a dataset of ***. It annotates the words appearing in the image as ***. To use it, simply upload an image or use the example image below and click 'Submit'. Results will show up in a few seconds. If you want to make the output bigger, right-click on it and select 'Open image in new tab'."
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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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  css = ".output-image, .input-image {height: 40rem !important; width: 100% !important;}"
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  #css = "@media screen and (max-width: 600px) { .output_image, .input_image {height:20rem !important; width: 100% !important;} }"