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https://github.com/bertsky/sbb_binarization

Binarize document images

https://github.com/bertsky/sbb_binarization

Science Score: 10.0%

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    Links to: arxiv.org
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    Low similarity (7.4%) to scientific vocabulary
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Repository

Binarize document images

Basic Info
  • Host: GitHub
  • Owner: bertsky
  • License: apache-2.0
  • Default Branch: master
  • Homepage:
  • Size: 146 KB
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Fork of qurator-spk/sbb_binarization
Created over 5 years ago · Last pushed over 1 year ago

https://github.com/bertsky/sbb_binarization/blob/master/ 

# Binarization

> Binarization for document images

## Examples



## Introduction

This tool performs document image binarization (i.e. transform colour/grayscale
to black-and-white pixels) for OCR using multiple trained models. 

The method used is based on _Calvo-Zaragoza/Gallego, 2018. [A selectional auto-encoder approach for document image binarization](https://arxiv.org/abs/1706.10241)_.

## Installation

Clone the repository, enter it and run

`pip install .`

### Models

Pre-trained models can be downloaded from here:   

https://qurator-data.de/sbb_binarization/

## Usage

```sh
sbb_binarize \
  --patches \
  -m  \
   \
  
```

**Note** In virtually all cases, the `--patches` flag will improve results.

Owner

  • Name: Robert Sachunsky
  • Login: bertsky
  • Kind: user

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