Metadata-Version: 2.1
Name: sbb-binarization
Version: 0.0.2
Summary: Pixelwise binarization with selectional auto-encoders in Keras
Home-page: https://github.com/qurator-spk/sbb_binarization
Author: Vahid Rezanezhad
License: Apache License 2.0
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: numpy (<1.19.0,>=1.17.0)
Requires-Dist: setuptools (>=41)
Requires-Dist: opencv-python-headless
Requires-Dist: ocrd (>=2.18.0)
Requires-Dist: keras (<2.4,>=2.3.1)
Requires-Dist: tensorflow (<1.16,>=1.15)

# Binarization

> Binarization for document images

## Introduction

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

## 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 \
  -m <directory with models> \
  -i <image file> \
  -p <set to true to let the model see the image divided into patches> \
  -s <directory where the results will be saved>`
```


