automatic import of python-torchjpeg

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+/torchjpeg-0.9.29.tar.gz
diff --git a/python-torchjpeg.spec b/python-torchjpeg.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-torchjpeg
+Version:	0.9.29
+Release:	1
+Summary:	Utilities for JPEG data access and manipulation in pytorch
+License:	MIT
+URL:		https://queuecumber.gitlab.io/torchjpeg
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/f6/d3/9155bef69a398ddf63902321fb236d0195491ceb23f075b353008c87971d/torchjpeg-0.9.29.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-torch
+Requires:	python3-torchvision
+Requires:	python3-Pillow
+
+%description
+# TorchJPEG
+
+[![pipeline status](https://gitlab.com/Queuecumber/torchjpeg/badges/master/pipeline.svg)](https://gitlab.com/Queuecumber/torchjpeg/-/pipelines/latest)
+[![coverage report](https://gitlab.com/Queuecumber/torchjpeg/badges/master/coverage.svg)](https://gitlab.com/Queuecumber/torchjpeg/-/pipelines/latest)
+[![PyPI](https://img.shields.io/pypi/v/torchjpeg)](https://pypi.org/project/torchjpeg/)
+[![License](https://img.shields.io/badge/license-MIT-blue)](https://gitlab.com/Queuecumber/torchjpeg/-/blob/master/LICENSE)
+
+This package contains a C++ extension for pytorch that interfaces with libjpeg to allow for manipulation of low-level JPEG data.
+By using libjpeg, quantization results are guaranteed to be consistent with other applications, like image viewers or MATLAB,
+which use libjpeg to compress and decompress images. This is useful because JPEG images can be effected by round-off
+errors or slight differences in the decompression procedure. Besides this, this library can be used to read and write
+DCT coefficients, functionality which is not available from other python interfaces.
+
+Besides this, the library includes many utilities related to JPEG compression, many of which are written using native pytorch code meaning
+they can be differentiated or GPU accelerated. The library currently includes packages related to the DCT, quantization, metrics, and dataset
+transformations.
+
+## LIBJPEG
+
+Currently builds against: `libjpeg-9d`. libjpeg is statically linked during the build process. See [http://www.ijg.org/files/](http://www.ijg.org/files/) for libjpeg source. 
+The full libjpeg source is included with the torchjpeg source code and will be built during the install process (for a source or sdist install).
+
+## Install
+
+Packages are hosted on [pypi](https://pypi.org/project/torchjpeg/). Install using pip, note that only Linux builds are supported at the moment. 
+
+```
+pip install torchjpeg
+```
+
+If there is demand for builds on other platforms it may happen in the future. Also note that the wheel is intended to be compatible with manylinux2014
+which means it should work on modern Linux systems, however, because of they way pytorch works, we can't actually build it using all of the manylinux2014
+tools. So compliance is not guaranteed and YMMV.
+
+```{warning}
+torchjpeg is currently in pre-beta development and consists mostly of converted research code. The public facing API, including any and all names of
+parameters and functions, is subject to change at any time. We follow semver for versioning and will adhere to that before making and breaking
+changes.
+```
+
+## Citation
+
+If you use our code in a publication, we ask that you cite the following paper ([bibtex](http://maxehr.umiacs.io/bibtex/ehrlich2020quantization.txt)):
+
+> Max Ehrlich, Larry Davis, Ser-Nam Lim, and Abhinav Shrivastava. "Quantization Guided JPEG Artifact Correction." In Proceedings of the European Conference on Computer Vision, 2020
+
+%package -n python3-torchjpeg
+Summary:	Utilities for JPEG data access and manipulation in pytorch
+Provides:	python-torchjpeg
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-torchjpeg
+# TorchJPEG
+
+[![pipeline status](https://gitlab.com/Queuecumber/torchjpeg/badges/master/pipeline.svg)](https://gitlab.com/Queuecumber/torchjpeg/-/pipelines/latest)
+[![coverage report](https://gitlab.com/Queuecumber/torchjpeg/badges/master/coverage.svg)](https://gitlab.com/Queuecumber/torchjpeg/-/pipelines/latest)
+[![PyPI](https://img.shields.io/pypi/v/torchjpeg)](https://pypi.org/project/torchjpeg/)
+[![License](https://img.shields.io/badge/license-MIT-blue)](https://gitlab.com/Queuecumber/torchjpeg/-/blob/master/LICENSE)
+
+This package contains a C++ extension for pytorch that interfaces with libjpeg to allow for manipulation of low-level JPEG data.
+By using libjpeg, quantization results are guaranteed to be consistent with other applications, like image viewers or MATLAB,
+which use libjpeg to compress and decompress images. This is useful because JPEG images can be effected by round-off
+errors or slight differences in the decompression procedure. Besides this, this library can be used to read and write
+DCT coefficients, functionality which is not available from other python interfaces.
+
+Besides this, the library includes many utilities related to JPEG compression, many of which are written using native pytorch code meaning
+they can be differentiated or GPU accelerated. The library currently includes packages related to the DCT, quantization, metrics, and dataset
+transformations.
+
+## LIBJPEG
+
+Currently builds against: `libjpeg-9d`. libjpeg is statically linked during the build process. See [http://www.ijg.org/files/](http://www.ijg.org/files/) for libjpeg source. 
+The full libjpeg source is included with the torchjpeg source code and will be built during the install process (for a source or sdist install).
+
+## Install
+
+Packages are hosted on [pypi](https://pypi.org/project/torchjpeg/). Install using pip, note that only Linux builds are supported at the moment. 
+
+```
+pip install torchjpeg
+```
+
+If there is demand for builds on other platforms it may happen in the future. Also note that the wheel is intended to be compatible with manylinux2014
+which means it should work on modern Linux systems, however, because of they way pytorch works, we can't actually build it using all of the manylinux2014
+tools. So compliance is not guaranteed and YMMV.
+
+```{warning}
+torchjpeg is currently in pre-beta development and consists mostly of converted research code. The public facing API, including any and all names of
+parameters and functions, is subject to change at any time. We follow semver for versioning and will adhere to that before making and breaking
+changes.
+```
+
+## Citation
+
+If you use our code in a publication, we ask that you cite the following paper ([bibtex](http://maxehr.umiacs.io/bibtex/ehrlich2020quantization.txt)):
+
+> Max Ehrlich, Larry Davis, Ser-Nam Lim, and Abhinav Shrivastava. "Quantization Guided JPEG Artifact Correction." In Proceedings of the European Conference on Computer Vision, 2020
+
+%package help
+Summary:	Development documents and examples for torchjpeg
+Provides:	python3-torchjpeg-doc
+%description help
+# TorchJPEG
+
+[![pipeline status](https://gitlab.com/Queuecumber/torchjpeg/badges/master/pipeline.svg)](https://gitlab.com/Queuecumber/torchjpeg/-/pipelines/latest)
+[![coverage report](https://gitlab.com/Queuecumber/torchjpeg/badges/master/coverage.svg)](https://gitlab.com/Queuecumber/torchjpeg/-/pipelines/latest)
+[![PyPI](https://img.shields.io/pypi/v/torchjpeg)](https://pypi.org/project/torchjpeg/)
+[![License](https://img.shields.io/badge/license-MIT-blue)](https://gitlab.com/Queuecumber/torchjpeg/-/blob/master/LICENSE)
+
+This package contains a C++ extension for pytorch that interfaces with libjpeg to allow for manipulation of low-level JPEG data.
+By using libjpeg, quantization results are guaranteed to be consistent with other applications, like image viewers or MATLAB,
+which use libjpeg to compress and decompress images. This is useful because JPEG images can be effected by round-off
+errors or slight differences in the decompression procedure. Besides this, this library can be used to read and write
+DCT coefficients, functionality which is not available from other python interfaces.
+
+Besides this, the library includes many utilities related to JPEG compression, many of which are written using native pytorch code meaning
+they can be differentiated or GPU accelerated. The library currently includes packages related to the DCT, quantization, metrics, and dataset
+transformations.
+
+## LIBJPEG
+
+Currently builds against: `libjpeg-9d`. libjpeg is statically linked during the build process. See [http://www.ijg.org/files/](http://www.ijg.org/files/) for libjpeg source. 
+The full libjpeg source is included with the torchjpeg source code and will be built during the install process (for a source or sdist install).
+
+## Install
+
+Packages are hosted on [pypi](https://pypi.org/project/torchjpeg/). Install using pip, note that only Linux builds are supported at the moment. 
+
+```
+pip install torchjpeg
+```
+
+If there is demand for builds on other platforms it may happen in the future. Also note that the wheel is intended to be compatible with manylinux2014
+which means it should work on modern Linux systems, however, because of they way pytorch works, we can't actually build it using all of the manylinux2014
+tools. So compliance is not guaranteed and YMMV.
+
+```{warning}
+torchjpeg is currently in pre-beta development and consists mostly of converted research code. The public facing API, including any and all names of
+parameters and functions, is subject to change at any time. We follow semver for versioning and will adhere to that before making and breaking
+changes.
+```
+
+## Citation
+
+If you use our code in a publication, we ask that you cite the following paper ([bibtex](http://maxehr.umiacs.io/bibtex/ehrlich2020quantization.txt)):
+
+> Max Ehrlich, Larry Davis, Ser-Nam Lim, and Abhinav Shrivastava. "Quantization Guided JPEG Artifact Correction." In Proceedings of the European Conference on Computer Vision, 2020
+
+%prep
+%autosetup -n torchjpeg-0.9.29
+
+%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-torchjpeg -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.9.29-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..25157eb
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+57470f6a9a7d392bf67d11e04371beac  torchjpeg-0.9.29.tar.gz