From 1711408bc3b4aa291ccf7697ac6599c22b5fa7c0 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Wed, 10 May 2023 06:52:49 +0000 Subject: automatic import of python-torchjpeg --- .gitignore | 1 + python-torchjpeg.spec | 207 ++++++++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 209 insertions(+) create mode 100644 python-torchjpeg.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..2ac49ed 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/torchjpeg-0.9.29.tar.gz diff --git a/python-torchjpeg.spec b/python-torchjpeg.spec new file mode 100644 index 0000000..651ccc1 --- /dev/null +++ b/python-torchjpeg.spec @@ -0,0 +1,207 @@ +%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 - 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 -- cgit v1.2.3