SBB
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Image-to-Image
TF-Keras
pixelwise-segmentation
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  - image-to-image
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  license: apache-2.0
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  ---
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- This is a model for document image binarization.
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- For details, see [https://github.com/qurator-spk/sbb_binarization](sbb_binarization).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - image-to-image
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  license: apache-2.0
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  ---
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+ # About `sbb_binarization`
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+ This is a model for document image binarization. It can be used
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+ to convert all pixels in a color or grayscale document image to
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+ only black or white pixels. The main purpose is to improve the
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+ contrast between foreground (text) and background (paper) for
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+ purposes of OCR. The model is based on a `ResNet50-Unet` model.
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+
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+ # Results
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+ In the *DocEng’2021 Time-quality binarization competition*
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+ ([paper](https://dib.cin.ufpe.br/docs/DocEng21_bin_competition_report.pdf)),
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+ the model ranked 12 times under the top 8 of 63 methods in the
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+ OCR-related quality scores, and won 2 tasks.
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+
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+ In the *ICDAR 2021 Competition on Time-Quality Document Image
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+ Binarization* ([paper](https://dib.cin.ufpe.br/docs/papers/ICDAR2021-TQDIB_final_published.pdf)),
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+ the model ranked 2 times under the top 20 of 61 methods,
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+ and won 1 task.
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+
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+ For details, see [sbb_binarization](https://github.com/qurator-spk/sbb_binarization) on GitHub.
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+
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+ # Weights
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+ We provide a `saved model` for Tensorflow2.
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+
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+ | Model | Downloads
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+ | -------------| ------------------------
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+ | `2021_03_09` | [`saved_model`](https://huggingface.co/SBB/sbb_binarization/tree/main/saved_model)