%global _empty_manifest_terminate_build 0 Name: python-satflow Version: 0.3.36 Release: 1 Summary: Satellite Optical Flow License: MIT License URL: https://github.com/openclimatefix/satflow Source0: https://mirrors.nju.edu.cn/pypi/web/packages/ee/e0/cc6d95438ff7c0fcfc71a722913a9bd38f60b0d0fe863f393a08777d01f6/satflow-0.3.36.tar.gz BuildArch: noarch Requires: python3-albumentations Requires: python3-antialiased-cnns Requires: python3-hydra-core Requires: python3-hydra-optuna-sweeper Requires: python3-hydra-colorlog Requires: python3-lightning-bolts Requires: python3-neptune-client Requires: python3-neptune-pytorch-lightning Requires: python3-pytest Requires: python3-dotenv Requires: python3-pytorch-msssim Requires: python3-rich Requires: python3-torchvision Requires: python3-affine Requires: python3-torch-optimizer Requires: python3-huggingface-hub Requires: python3-einops Requires: python3-metnet Requires: python3-skillful-nowcasting Requires: python3-perceiver-model Requires: python3-nowcasting-dataset Requires: python3-nowcasting-utils Requires: python3-transformers Requires: python3-torch %description # SatFlow ***Sat***ellite Optical ***Flow*** with machine learning models. The goal of this repo is to improve upon optical flow models for predicting future satellite images from current and past ones, focused primarily on EUMETSAT data. ## Installation Clone the repository, then run ```shell conda env create -f environment.yml conda activate satflow pip install -e . ```` Alternatively, you can also install a usually older version through ```pip install satflow``` ## Data The data used here is a combination of the UK Met Office's rainfall radar data, EUMETSAT MSG satellite data (12 channels), derived data from the MSG satellites (cloud masks, etc.), and numerical weather prediction data. Currently, some example transformed EUMETSAT data can be downloaded from the tagged release, as well as included under ```datasets/```. %package -n python3-satflow Summary: Satellite Optical Flow Provides: python-satflow BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-satflow # SatFlow ***Sat***ellite Optical ***Flow*** with machine learning models. The goal of this repo is to improve upon optical flow models for predicting future satellite images from current and past ones, focused primarily on EUMETSAT data. ## Installation Clone the repository, then run ```shell conda env create -f environment.yml conda activate satflow pip install -e . ```` Alternatively, you can also install a usually older version through ```pip install satflow``` ## Data The data used here is a combination of the UK Met Office's rainfall radar data, EUMETSAT MSG satellite data (12 channels), derived data from the MSG satellites (cloud masks, etc.), and numerical weather prediction data. Currently, some example transformed EUMETSAT data can be downloaded from the tagged release, as well as included under ```datasets/```. %package help Summary: Development documents and examples for satflow Provides: python3-satflow-doc %description help # SatFlow ***Sat***ellite Optical ***Flow*** with machine learning models. The goal of this repo is to improve upon optical flow models for predicting future satellite images from current and past ones, focused primarily on EUMETSAT data. ## Installation Clone the repository, then run ```shell conda env create -f environment.yml conda activate satflow pip install -e . ```` Alternatively, you can also install a usually older version through ```pip install satflow``` ## Data The data used here is a combination of the UK Met Office's rainfall radar data, EUMETSAT MSG satellite data (12 channels), derived data from the MSG satellites (cloud masks, etc.), and numerical weather prediction data. Currently, some example transformed EUMETSAT data can be downloaded from the tagged release, as well as included under ```datasets/```. %prep %autosetup -n satflow-0.3.36 %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-satflow -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue May 30 2023 Python_Bot - 0.3.36-1 - Package Spec generated