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--- |
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tags: |
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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 CNN model for document image binarization. It can be |
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used to convert all pixels in a color or grayscale document image |
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to only black or white pixels. The main aim 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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# 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, winning 2 tasks. |
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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, winning 1 task. |
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For details, see [sbb_binarization](https://github.com/qurator-spk/sbb_binarization) on GitHub. |
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# Weights |
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We provide a `saved model` for Tensorflow2. |
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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) |
