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