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README.md
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 HDF5 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
With OCR-D, you can use the [Resource Manager](Tensorflow SavedModel) to deploy models, e.g.
ocrd resmgr download ocrd-sbb-binarize "*"
Usage
sbb_binarize \
-m <path to directory containing model files \
<input image> \
<output image>
Images containing a lot of border noise (black pixels) should be cropped beforehand to improve the quality of results.
Example
sbb_binarize -m /path/to/model/ myimage.tif myimage-bin.tif
To use the OCR-D interface:
ocrd-sbb-binarize -I INPUT_FILE_GRP -O OCR-D-IMG-BIN -P model default
Testing
For simple smoke tests, the following will
-
download models
-
download test data
-
run the OCR-D wrapper (on page and region level):
make model make test