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.
0877199c68 | 3 years ago | |
---|---|---|
.circleci | 4 years ago | |
repo | 4 years ago | |
sbb_binarize | 3 years ago | |
.gitignore | 4 years ago | |
.gitkeep | 5 years ago | |
.gitmodules | 4 years ago | |
CHANGELOG.md | 3 years ago | |
LICENSE | 5 years ago | |
Makefile | 4 years ago | |
README.md | 3 years ago | |
make.sh | 5 years ago | |
ocrd-tool.json | 4 years ago | |
requirements.txt | 3 years ago | |
setup.py | 4 years ago |
README.md
Binarization
Binarization for document images
Examples
Introduction
This tool performs document image binarization using trained models. The method is based on Calvo-Zaragoza and Gallego, 2018.
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 <path to directory containing model files> \
<input image> \
<output image>
Note In virtually all cases, applying the --patches
flag will improve the quality of results.
Example
sbb_binarize --patches -m /path/to/models/ myimage.tif myimage-bin.tif
To use the OCR-D interface:
ocrd-sbb-binarize --overwrite -I INPUT_FILE_GRP -O OCR-D-IMG-BIN -P model "/var/lib/sbb_binarization"