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1.5 KiB
1.5 KiB
Binarization
Binarization for document images
Examples
Introduction
This tool performs document image binarization using a trained ResNet50-UNet model.
Installation
Clone the repository, enter it and run
pip install .
Models
Pre-trained models in h5 format can be downloaded from here:
https://qurator-data.de/sbb_binarization/
We also provide a Tensorflow saved_model via Huggingface:
https://huggingface.co/SBB/sbb_binarization
Usage
sbb_binarize \
--patches \
-m <path to directory containing model files> \
<input image> \
<output image>
In virtually all cases, applying the --patches flag will improve the quality of results.
Images containing a lot of border noise (black pixels) should be cropped beforehand to 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"