You cannot select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
sbb_binarization/README.md

1.2 KiB

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.

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

sbb_binarize \
  --patches \
  -m <directory with models> \
  <input image> \
  <output image>

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