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.

Go to file

vahid 5c37d18cb0 enable flowing from directory		3 years ago
.circleci	use resmgr for model download	4 years ago
repo	add assets subrepo	4 years ago
sbb_binarize	enable flowing from directory	3 years ago
.gitignore	📦 v0.0.2	4 years ago
.gitkeep	Add new directory, you can find corresponding models in qurator-data	5 years ago
.gitmodules	add assets subrepo	4 years ago
CHANGELOG.md	Update CHANGELOG.md	3 years ago
LICENSE	Add LICENSE	5 years ago
Makefile	fix test	4 years ago
README.md	improve usage instructions	3 years ago
make.sh	Add new file	5 years ago
ocrd-tool.json	add ocrd-tool.json	4 years ago
requirements.txt	don't require Keras explicitely	3 years ago
setup.py	minimal CI setup	4 years ago

Binarization

Binarization for document images

Examples

This tool performs document image binarization using trained models. The method is based on Calvo-Zaragoza and Gallego, 2018.

Clone the repository, enter it and run

pip install .

Pre-trained models can be downloaded from here:

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"