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diff --git a/python-monai-weekly.spec b/python-monai-weekly.spec new file mode 100644 index 0000000..5954f85 --- /dev/null +++ b/python-monai-weekly.spec @@ -0,0 +1,385 @@ +%global _empty_manifest_terminate_build 0 +Name: python-monai-weekly +Version: 1.2.dev2318 +Release: 1 +Summary: AI Toolkit for Healthcare Imaging +License: Apache License 2.0 +URL: https://monai.io/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a0/80/76a653b7776408041f2c15d7607c8ac8c93781e6806a3a0625c8b388664e/monai-weekly-1.2.dev2318.tar.gz +BuildArch: noarch + +Requires: python3-torch +Requires: python3-numpy +Requires: python3-nibabel +Requires: python3-ninja +Requires: python3-scikit-image +Requires: python3-pillow +Requires: python3-tensorboard +Requires: python3-gdown +Requires: python3-pytorch-ignite +Requires: python3-torchvision +Requires: python3-itk +Requires: python3-tqdm +Requires: python3-lmdb +Requires: python3-psutil +Requires: python3-cucim +Requires: python3-openslide-python +Requires: python3-tifffile +Requires: python3-imagecodecs +Requires: python3-pandas +Requires: python3-einops +Requires: python3-transformers +Requires: python3-mlflow +Requires: python3-clearml +Requires: python3-matplotlib +Requires: python3-tensorboardX +Requires: python3-pyyaml +Requires: python3-fire +Requires: python3-jsonschema +Requires: python3-pynrrd +Requires: python3-pydicom +Requires: python3-h5py +Requires: python3-nni +Requires: python3-optuna +Requires: python3-onnx +Requires: python3-onnxruntime +Requires: python3-cucim +Requires: python3-einops +Requires: python3-fire +Requires: python3-gdown +Requires: python3-h5py +Requires: python3-pytorch-ignite +Requires: python3-imagecodecs +Requires: python3-itk +Requires: python3-jsonschema +Requires: python3-lmdb +Requires: python3-matplotlib +Requires: python3-mlflow +Requires: python3-nibabel +Requires: python3-ninja +Requires: python3-nni +Requires: python3-onnx +Requires: python3-onnxruntime +Requires: python3-openslide-python +Requires: python3-optuna +Requires: python3-pandas +Requires: python3-pillow +Requires: python3-psutil +Requires: python3-pydicom +Requires: python3-pynrrd +Requires: python3-pyyaml +Requires: python3-scikit-image +Requires: python3-tensorboard +Requires: python3-tensorboardX +Requires: python3-tifffile +Requires: python3-torchvision +Requires: python3-tqdm +Requires: python3-transformers + +%description +<p align="center"> + <img src="https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/docs/images/MONAI-logo-color.png" width="50%" alt='project-monai'> +</p> + +**M**edical **O**pen **N**etwork for **AI** + + +[](https://opensource.org/licenses/Apache-2.0) +[](https://badge.fury.io/py/monai) +[](https://hub.docker.com/r/projectmonai/monai) +[](https://anaconda.org/conda-forge/monai) + +[](https://github.com/Project-MONAI/MONAI/actions/workflows/pythonapp.yml) +[](https://github.com/Project-MONAI/MONAI/actions?query=branch%3Adev) +[](https://github.com/Project-MONAI/MONAI/actions/workflows/docker.yml) +[](https://docs.monai.io/en/latest/) +[](https://codecov.io/gh/Project-MONAI/MONAI) + +MONAI is a [PyTorch](https://pytorch.org/)-based, [open-source](https://github.com/Project-MONAI/MONAI/blob/dev/LICENSE) framework for deep learning in healthcare imaging, part of [PyTorch Ecosystem](https://pytorch.org/ecosystem/). +Its ambitions are: +- developing a community of academic, industrial and clinical researchers collaborating on a common foundation; +- creating state-of-the-art, end-to-end training workflows for healthcare imaging; +- providing researchers with the optimized and standardized way to create and evaluate deep learning models. + + +## Features +> _Please see [the technical highlights](https://docs.monai.io/en/latest/highlights.html) and [What's New](https://docs.monai.io/en/latest/whatsnew.html) of the milestone releases._ + +- flexible pre-processing for multi-dimensional medical imaging data; +- compositional & portable APIs for ease of integration in existing workflows; +- domain-specific implementations for networks, losses, evaluation metrics and more; +- customizable design for varying user expertise; +- multi-GPU data parallelism support. + + +## Installation + +To install [the current release](https://pypi.org/project/monai/), you can simply run: + +```bash +pip install monai +``` + +Please refer to [the installation guide](https://docs.monai.io/en/latest/installation.html) for other installation options. + +## Getting Started + +[MedNIST demo](https://colab.research.google.com/drive/1wy8XUSnNWlhDNazFdvGBHLfdkGvOHBKe) and [MONAI for PyTorch Users](https://colab.research.google.com/drive/1boqy7ENpKrqaJoxFlbHIBnIODAs1Ih1T) are available on Colab. + +Examples and notebook tutorials are located at [Project-MONAI/tutorials](https://github.com/Project-MONAI/tutorials). + +Technical documentation is available at [docs.monai.io](https://docs.monai.io). + +## Citation + +If you have used MONAI in your research, please cite us! The citation can be exported from: https://arxiv.org/abs/2211.02701. + +## Model Zoo +[The MONAI Model Zoo](https://github.com/Project-MONAI/model-zoo) is a place for researchers and data scientists to share the latest and great models from the community. +Utilizing [the MONAI Bundle format](https://docs.monai.io/en/latest/bundle_intro.html) makes it easy to [get started](https://github.com/Project-MONAI/tutorials/tree/main/model_zoo) building workflows with MONAI. + +## Contributing +For guidance on making a contribution to MONAI, see the [contributing guidelines](https://github.com/Project-MONAI/MONAI/blob/dev/CONTRIBUTING.md). + +## Community +Join the conversation on Twitter [@ProjectMONAI](https://twitter.com/ProjectMONAI) or join our [Slack channel](https://forms.gle/QTxJq3hFictp31UM9). + +Ask and answer questions over on [MONAI's GitHub Discussions tab](https://github.com/Project-MONAI/MONAI/discussions). + +## Links +- Website: https://monai.io/ +- API documentation (milestone): https://docs.monai.io/ +- API documentation (latest dev): https://docs.monai.io/en/latest/ +- Code: https://github.com/Project-MONAI/MONAI +- Project tracker: https://github.com/Project-MONAI/MONAI/projects +- Issue tracker: https://github.com/Project-MONAI/MONAI/issues +- Wiki: https://github.com/Project-MONAI/MONAI/wiki +- Test status: https://github.com/Project-MONAI/MONAI/actions +- PyPI package: https://pypi.org/project/monai/ +- conda-forge: https://anaconda.org/conda-forge/monai +- Weekly previews: https://pypi.org/project/monai-weekly/ +- Docker Hub: https://hub.docker.com/r/projectmonai/monai + + +%package -n python3-monai-weekly +Summary: AI Toolkit for Healthcare Imaging +Provides: python-monai-weekly +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-monai-weekly +<p align="center"> + <img src="https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/docs/images/MONAI-logo-color.png" width="50%" alt='project-monai'> +</p> + +**M**edical **O**pen **N**etwork for **AI** + + +[](https://opensource.org/licenses/Apache-2.0) +[](https://badge.fury.io/py/monai) +[](https://hub.docker.com/r/projectmonai/monai) +[](https://anaconda.org/conda-forge/monai) + +[](https://github.com/Project-MONAI/MONAI/actions/workflows/pythonapp.yml) +[](https://github.com/Project-MONAI/MONAI/actions?query=branch%3Adev) +[](https://github.com/Project-MONAI/MONAI/actions/workflows/docker.yml) +[](https://docs.monai.io/en/latest/) +[](https://codecov.io/gh/Project-MONAI/MONAI) + +MONAI is a [PyTorch](https://pytorch.org/)-based, [open-source](https://github.com/Project-MONAI/MONAI/blob/dev/LICENSE) framework for deep learning in healthcare imaging, part of [PyTorch Ecosystem](https://pytorch.org/ecosystem/). +Its ambitions are: +- developing a community of academic, industrial and clinical researchers collaborating on a common foundation; +- creating state-of-the-art, end-to-end training workflows for healthcare imaging; +- providing researchers with the optimized and standardized way to create and evaluate deep learning models. + + +## Features +> _Please see [the technical highlights](https://docs.monai.io/en/latest/highlights.html) and [What's New](https://docs.monai.io/en/latest/whatsnew.html) of the milestone releases._ + +- flexible pre-processing for multi-dimensional medical imaging data; +- compositional & portable APIs for ease of integration in existing workflows; +- domain-specific implementations for networks, losses, evaluation metrics and more; +- customizable design for varying user expertise; +- multi-GPU data parallelism support. + + +## Installation + +To install [the current release](https://pypi.org/project/monai/), you can simply run: + +```bash +pip install monai +``` + +Please refer to [the installation guide](https://docs.monai.io/en/latest/installation.html) for other installation options. + +## Getting Started + +[MedNIST demo](https://colab.research.google.com/drive/1wy8XUSnNWlhDNazFdvGBHLfdkGvOHBKe) and [MONAI for PyTorch Users](https://colab.research.google.com/drive/1boqy7ENpKrqaJoxFlbHIBnIODAs1Ih1T) are available on Colab. + +Examples and notebook tutorials are located at [Project-MONAI/tutorials](https://github.com/Project-MONAI/tutorials). + +Technical documentation is available at [docs.monai.io](https://docs.monai.io). + +## Citation + +If you have used MONAI in your research, please cite us! The citation can be exported from: https://arxiv.org/abs/2211.02701. + +## Model Zoo +[The MONAI Model Zoo](https://github.com/Project-MONAI/model-zoo) is a place for researchers and data scientists to share the latest and great models from the community. +Utilizing [the MONAI Bundle format](https://docs.monai.io/en/latest/bundle_intro.html) makes it easy to [get started](https://github.com/Project-MONAI/tutorials/tree/main/model_zoo) building workflows with MONAI. + +## Contributing +For guidance on making a contribution to MONAI, see the [contributing guidelines](https://github.com/Project-MONAI/MONAI/blob/dev/CONTRIBUTING.md). + +## Community +Join the conversation on Twitter [@ProjectMONAI](https://twitter.com/ProjectMONAI) or join our [Slack channel](https://forms.gle/QTxJq3hFictp31UM9). + +Ask and answer questions over on [MONAI's GitHub Discussions tab](https://github.com/Project-MONAI/MONAI/discussions). + +## Links +- Website: https://monai.io/ +- API documentation (milestone): https://docs.monai.io/ +- API documentation (latest dev): https://docs.monai.io/en/latest/ +- Code: https://github.com/Project-MONAI/MONAI +- Project tracker: https://github.com/Project-MONAI/MONAI/projects +- Issue tracker: https://github.com/Project-MONAI/MONAI/issues +- Wiki: https://github.com/Project-MONAI/MONAI/wiki +- Test status: https://github.com/Project-MONAI/MONAI/actions +- PyPI package: https://pypi.org/project/monai/ +- conda-forge: https://anaconda.org/conda-forge/monai +- Weekly previews: https://pypi.org/project/monai-weekly/ +- Docker Hub: https://hub.docker.com/r/projectmonai/monai + + +%package help +Summary: Development documents and examples for monai-weekly +Provides: python3-monai-weekly-doc +%description help +<p align="center"> + <img src="https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/docs/images/MONAI-logo-color.png" width="50%" alt='project-monai'> +</p> + +**M**edical **O**pen **N**etwork for **AI** + + +[](https://opensource.org/licenses/Apache-2.0) +[](https://badge.fury.io/py/monai) +[](https://hub.docker.com/r/projectmonai/monai) +[](https://anaconda.org/conda-forge/monai) + +[](https://github.com/Project-MONAI/MONAI/actions/workflows/pythonapp.yml) +[](https://github.com/Project-MONAI/MONAI/actions?query=branch%3Adev) +[](https://github.com/Project-MONAI/MONAI/actions/workflows/docker.yml) +[](https://docs.monai.io/en/latest/) +[](https://codecov.io/gh/Project-MONAI/MONAI) + +MONAI is a [PyTorch](https://pytorch.org/)-based, [open-source](https://github.com/Project-MONAI/MONAI/blob/dev/LICENSE) framework for deep learning in healthcare imaging, part of [PyTorch Ecosystem](https://pytorch.org/ecosystem/). +Its ambitions are: +- developing a community of academic, industrial and clinical researchers collaborating on a common foundation; +- creating state-of-the-art, end-to-end training workflows for healthcare imaging; +- providing researchers with the optimized and standardized way to create and evaluate deep learning models. + + +## Features +> _Please see [the technical highlights](https://docs.monai.io/en/latest/highlights.html) and [What's New](https://docs.monai.io/en/latest/whatsnew.html) of the milestone releases._ + +- flexible pre-processing for multi-dimensional medical imaging data; +- compositional & portable APIs for ease of integration in existing workflows; +- domain-specific implementations for networks, losses, evaluation metrics and more; +- customizable design for varying user expertise; +- multi-GPU data parallelism support. + + +## Installation + +To install [the current release](https://pypi.org/project/monai/), you can simply run: + +```bash +pip install monai +``` + +Please refer to [the installation guide](https://docs.monai.io/en/latest/installation.html) for other installation options. + +## Getting Started + +[MedNIST demo](https://colab.research.google.com/drive/1wy8XUSnNWlhDNazFdvGBHLfdkGvOHBKe) and [MONAI for PyTorch Users](https://colab.research.google.com/drive/1boqy7ENpKrqaJoxFlbHIBnIODAs1Ih1T) are available on Colab. + +Examples and notebook tutorials are located at [Project-MONAI/tutorials](https://github.com/Project-MONAI/tutorials). + +Technical documentation is available at [docs.monai.io](https://docs.monai.io). + +## Citation + +If you have used MONAI in your research, please cite us! The citation can be exported from: https://arxiv.org/abs/2211.02701. + +## Model Zoo +[The MONAI Model Zoo](https://github.com/Project-MONAI/model-zoo) is a place for researchers and data scientists to share the latest and great models from the community. +Utilizing [the MONAI Bundle format](https://docs.monai.io/en/latest/bundle_intro.html) makes it easy to [get started](https://github.com/Project-MONAI/tutorials/tree/main/model_zoo) building workflows with MONAI. + +## Contributing +For guidance on making a contribution to MONAI, see the [contributing guidelines](https://github.com/Project-MONAI/MONAI/blob/dev/CONTRIBUTING.md). + +## Community +Join the conversation on Twitter [@ProjectMONAI](https://twitter.com/ProjectMONAI) or join our [Slack channel](https://forms.gle/QTxJq3hFictp31UM9). + +Ask and answer questions over on [MONAI's GitHub Discussions tab](https://github.com/Project-MONAI/MONAI/discussions). + +## Links +- Website: https://monai.io/ +- API documentation (milestone): https://docs.monai.io/ +- API documentation (latest dev): https://docs.monai.io/en/latest/ +- Code: https://github.com/Project-MONAI/MONAI +- Project tracker: https://github.com/Project-MONAI/MONAI/projects +- Issue tracker: https://github.com/Project-MONAI/MONAI/issues +- Wiki: https://github.com/Project-MONAI/MONAI/wiki +- Test status: https://github.com/Project-MONAI/MONAI/actions +- PyPI package: https://pypi.org/project/monai/ +- conda-forge: https://anaconda.org/conda-forge/monai +- Weekly previews: https://pypi.org/project/monai-weekly/ +- Docker Hub: https://hub.docker.com/r/projectmonai/monai + + +%prep +%autosetup -n monai-weekly-1.2.dev2318 + +%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-monai-weekly -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.2.dev2318-1 +- Package Spec generated |