[](https://github.com/Calamari-OCR/calamari/actions/workflows/python-test.yml)
[](https://github.com/Calamari-OCR/calamari/actions/workflows/python-publish.yml)
[](https://github.com/Calamari-OCR/calamari/actions/workflows/black.yml)
OCR Engine based on OCRopy and Kraken using python3.
It is designed to both be easy to use from the command line but also be modular to be integrated and customized from other python scripts.
## Documentation
The documentation of Calamari is hosted [here](https://calamari-ocr.readthedocs.io).
## Pretrained model repository
Pretrained models are available at (https://github.com/Calamari-OCR/calamari_models).
The current release can be accessed [here](https://github.com/Calamari-OCR/calamari_models/archive/2.0.zip) (255 MB).
## Installing
Calamari is available on [pypi](https://pypi.org/project/calamari-ocr):
```shell
pip install calamari-ocr
```
Read the [docs](https://calamari-ocr.readthedocs.io) for further instructions.
## Command-Line Interface
See the [docs](https://calamari-ocr.readthedocs.io) to learn how to use Calamari from the command line.
## Calamari API
See the [docs](https://calamari-ocr.readthedocs.io) to learn how to adapt Calamari for your needs.
## Citing Calamari
If you use Calamari in your Research-Project, please cite:
> Wick, C., Reul, C., Puppe, F.: *Calamari - A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition.* Digital Humanities Quarterly **14**(1) (2020)
```
@article{wick_calamari_2020,
title = {Calamari - {A} {High}-{Performance} {Tensorflow}-based {Deep} {Learning} {Package} for {Optical} {Character} {Recognition}},
volume = {14},
number = {1},
journal = {Digital Humanities Quarterly},
author = {Wick, Christoph and Reul, Christian and Puppe, Frank},
year = {2020},
}
```
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