MikkoLipsanen commited on
Commit
3867b35
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verified ·
1 Parent(s): a9bc342

Update app.py

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Files changed (1) hide show
  1. app.py +5 -5
app.py CHANGED
@@ -83,11 +83,11 @@ def get_text_predictions(image, segment_predictions, recognizer):
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  # Run demo code
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  with gr.Blocks(theme=gr.themes.Monochrome(), title="Multicentury HTR Demo") as demo:
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  gr.Markdown("# Multicentury HTR Demo")
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- gr.Markdown("The HTR pipeline contains three components: text region detection, textline detection and handwritten text recognition.\
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- The components run machine learning models that have been trained at the National Archives of Finland using mostly handwritten documents\
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- from 17th, 18th, 19th and 20th centuries. Best results are probably obtained when using high quality scans of documents with a regular layout.\
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- Input image can be uploaded using the *Input image* window in the *Text content* tab, and the predicted text content will appear to the window\
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- on the right side of the image. Results of text region and text line detection can be viewed in the *Text regions* and *Text lines* tabs.)
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  with gr.Tab("Text content"):
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  with gr.Row():
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  input_img = gr.Image(label="Input image", type="pil")
 
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  # Run demo code
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  with gr.Blocks(theme=gr.themes.Monochrome(), title="Multicentury HTR Demo") as demo:
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  gr.Markdown("# Multicentury HTR Demo")
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+ gr.Markdown("""The HTR pipeline contains three components: text region detection, textline detection and handwritten text recognition.
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+ The components run machine learning models that have been trained at the National Archives of Finland using mostly handwritten documents
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+ from 17th, 18th, 19th and 20th centuries. Best results are probably obtained when using high quality scans of documents with a regular layout.
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+ Input image can be uploaded using the *Input image* window in the *Text content* tab, and the predicted text content will appear to the window
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+ on the right side of the image. Results of text region and text line detection can be viewed in the *Text regions* and *Text lines* tabs.""")
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  with gr.Tab("Text content"):
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  with gr.Row():
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  input_img = gr.Image(label="Input image", type="pil")