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Gerber, Mike
93de16d81e
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5 years ago | |
|---|---|---|
| .circleci | 5 years ago | |
| ocrd_calamari | 5 years ago | |
| test | 5 years ago | |
| .coveragerc | 5 years ago | |
| .gitignore | 5 years ago | |
| Dockerfile | 5 years ago | |
| LICENSE | 7 years ago | |
| Makefile | 5 years ago | |
| README-DEV.md | 5 years ago | |
| README.md | 5 years ago | |
| ocrd-tool.json | 7 years ago | |
| requirements-test.txt | 5 years ago | |
| requirements.txt | 5 years ago | |
| setup.py | 5 years ago | |
README.md
ocrd_calamari
Recognize text using Calamari OCR.
Introduction
This offers a OCR-D compliant workspace processor for some of the functionality of Calamari OCR.
This processor only operates on the text line level and so needs a line segmentation (and by extension a binarized image) as its input.
Installation
From PyPI
pip install ocrd_calamari
From Repo
pip install .
Install models
Download standard models:
wget https://github.com/Calamari-OCR/calamari_models/archive/master.zip
unzip master.zip
Download models trained on GT4HistOCR data:
wget https://file.spk-berlin.de:8443/calamari-models/GT4HistOCR/model.tar.xz
mkdir gt4hist-calamari
cd gt4hist-calamari
tar xf ../model.tar.xz
Example Usage
ocrd-calamari-recognize -p test-parameters.json -m mets.xml -I OCR-D-SEG-LINE -O OCR-D-OCR-CALAMARI
With test-parameters.json:
{
"checkpoint": "/path/to/some/trained/models/*.ckpt.json"
}
TODO
- Support Calamari's "extended prediction data" output
- Currently, the processor only supports a prediction using confidence voting of multiple models. While this is superior, it makes sense to support single model prediction, too.