%global _empty_manifest_terminate_build 0 Name: python-elasticdeform Version: 0.5.0 Release: 1 Summary: Elastic deformations for N-D images. License: BSD URL: https://github.com/gvtulder/elasticdeform Source0: https://mirrors.nju.edu.cn/pypi/web/packages/b6/ee/562d0bc43151411ffcfbac1cb1419748df9fbffb2a2685c9735f3e7e6352/elasticdeform-0.5.0.tar.gz Requires: python3-numpy Requires: python3-scipy %description [![Documentation Status](https://readthedocs.org/projects/elasticdeform/badge/?version=latest)](https://elasticdeform.readthedocs.io/en/latest/?badge=latest) [![Test](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml) [![Build](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml) [![DOI](https://zenodo.org/badge/145003699.svg)](https://zenodo.org/badge/latestdoi/145003699) This library implements elastic grid-based deformations for N-dimensional images. The elastic deformation approach is described in * Ronneberger, Fischer, and Brox, "U-Net: Convolutional Networks for Biomedical Image Segmentation" () * Çiçek et al., "3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation" () The procedure generates a coarse displacement grid with a random displacement for each grid point. This grid is then interpolated to compute a displacement for each pixel in the input image. The input image is then deformed using the displacement vectors and a spline interpolation. In addition to the normal, forward deformation, this package also provides a function that can backpropagate the gradient through the deformation. This makes it possible to use the deformation as a layer in a convolutional neural network. For convenience, TensorFlow and PyTorch wrappers are provided in `elasticdeform.tf` and `elasticdeform.torch`. %package -n python3-elasticdeform Summary: Elastic deformations for N-D images. Provides: python-elasticdeform BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip BuildRequires: python3-cffi BuildRequires: gcc BuildRequires: gdb %description -n python3-elasticdeform [![Documentation Status](https://readthedocs.org/projects/elasticdeform/badge/?version=latest)](https://elasticdeform.readthedocs.io/en/latest/?badge=latest) [![Test](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml) [![Build](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml) [![DOI](https://zenodo.org/badge/145003699.svg)](https://zenodo.org/badge/latestdoi/145003699) This library implements elastic grid-based deformations for N-dimensional images. The elastic deformation approach is described in * Ronneberger, Fischer, and Brox, "U-Net: Convolutional Networks for Biomedical Image Segmentation" () * Çiçek et al., "3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation" () The procedure generates a coarse displacement grid with a random displacement for each grid point. This grid is then interpolated to compute a displacement for each pixel in the input image. The input image is then deformed using the displacement vectors and a spline interpolation. In addition to the normal, forward deformation, this package also provides a function that can backpropagate the gradient through the deformation. This makes it possible to use the deformation as a layer in a convolutional neural network. For convenience, TensorFlow and PyTorch wrappers are provided in `elasticdeform.tf` and `elasticdeform.torch`. %package help Summary: Development documents and examples for elasticdeform Provides: python3-elasticdeform-doc %description help [![Documentation Status](https://readthedocs.org/projects/elasticdeform/badge/?version=latest)](https://elasticdeform.readthedocs.io/en/latest/?badge=latest) [![Test](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml) [![Build](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml) [![DOI](https://zenodo.org/badge/145003699.svg)](https://zenodo.org/badge/latestdoi/145003699) This library implements elastic grid-based deformations for N-dimensional images. The elastic deformation approach is described in * Ronneberger, Fischer, and Brox, "U-Net: Convolutional Networks for Biomedical Image Segmentation" () * Çiçek et al., "3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation" () The procedure generates a coarse displacement grid with a random displacement for each grid point. This grid is then interpolated to compute a displacement for each pixel in the input image. The input image is then deformed using the displacement vectors and a spline interpolation. In addition to the normal, forward deformation, this package also provides a function that can backpropagate the gradient through the deformation. This makes it possible to use the deformation as a layer in a convolutional neural network. For convenience, TensorFlow and PyTorch wrappers are provided in `elasticdeform.tf` and `elasticdeform.torch`. %prep %autosetup -n elasticdeform-0.5.0 %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-elasticdeform -f filelist.lst %dir %{python3_sitearch}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue May 30 2023 Python_Bot - 0.5.0-1 - Package Spec generated