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|
%global _empty_manifest_terminate_build 0
Name: python-calamari-ocr
Version: 2.2.2
Release: 1
Summary: please add a summary manually as the author left a blank one
License: Apache License 2.0
URL: https://github.com/Calamari-OCR/calamari
Source0: https://mirrors.aliyun.com/pypi/web/packages/29/96/71b03c7c955b0fd718154303c8c6f4b8cba5f4413e3fa3efddedbf765898/calamari_ocr-2.2.2.tar.gz
BuildArch: noarch
Requires: python3-edit-distance
Requires: python3-h5py
Requires: python3-lxml
Requires: python3-bidi
Requires: python3-tensorflow
Requires: python3-tfaip
Requires: python3-xlsxwriter
%description
[](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},
}
```
%package -n python3-calamari-ocr
Summary: please add a summary manually as the author left a blank one
Provides: python-calamari-ocr
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-calamari-ocr
[](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},
}
```
%package help
Summary: Development documents and examples for calamari-ocr
Provides: python3-calamari-ocr-doc
%description help
[](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},
}
```
%prep
%autosetup -n calamari_ocr-2.2.2
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-calamari-ocr -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 2.2.2-1
- Package Spec generated
|
