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@@ -0,0 +1 @@ +/SAMITorch-0.2.7.tar.gz diff --git a/python-samitorch.spec b/python-samitorch.spec new file mode 100644 index 0000000..368665b --- /dev/null +++ b/python-samitorch.spec @@ -0,0 +1,567 @@ +%global _empty_manifest_terminate_build 0 +Name: python-SAMITorch +Version: 0.2.7 +Release: 1 +Summary: Deep Learning Framework For Medical Image Analysis +License: MIT +URL: https://pypi.org/project/SAMITorch/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/63/1e/ce6bfbc60593f8be90c3ed066e4ab01e21672f41b85f3fcacf09a55f09d4/SAMITorch-0.2.7.tar.gz +BuildArch: noarch + + +%description +# <img src="/icons/artificial-intelligence.png" width="60" vertical-align="bottom"> SAMITorch + +## Welcome to SAMITorch + +[](https://travis-ci.com/sami-ets/SAMITorch) + + + + + + +SAMITorch is a deep learning framework for *Shape Analysis in Medical Imaging* laboratory of [École de technologie supérieure](https://www.etsmtl.ca/) using [PyTorch](https://github.com/pytorch) library. +It implements an extensive set of loaders, transformers, models and data sets suited for deep learning in medical imaging. +Our objective is to build a tested, standard framework for quickly producing results in deep learning reasearch applied to medical imaging. + +# Table Of Contents + +- [Authors](#authors) +- [References](#references) +- [Project architecture](#project-architecture) + - [Folder structure](#folder-structure) + - [Main Components](#main-components) + - [Models](#models) + - [Transformers](#transformers) + - [Configuration](#configs) + - [Main](#main) + - [Contributing](#contributing) + - [Branch naming](#branch-naming) + - [Commits syntax](#commits-syntax) + - [Acknowledgments](#acknowledgments) + + +## Authors + +* Pierre-Luc Delisle - [pldelisle](https://github.com/pldelisle) +* Benoit Anctil-Robitaille - [banctilrobitaille](https://github.com/banctilrobitaille) + +## References + +#### Segmentation +``` +@article{RN10, + author = {Çiçek, Özgün and Abdulkadir, Ahmed and Lienkamp, Soeren S. and Brox, Thomas and Ronneberger, Olaf}, + title = {3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation}, + journal = {eprint arXiv:1606.06650}, + pages = {arXiv:1606.06650}, + url = {https://ui.adsabs.harvard.edu/\#abs/2016arXiv160606650C}, + year = {2016}, + type = {Journal Article} +} +``` + +#### Classification +``` +@inproceedings{RN12, + author = {He, K. and Zhang, X. and Ren, S. and Sun, J.}, + title = {Deep Residual Learning for Image Recognition}, + booktitle = {2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, + pages = {770-778}, + ISBN = {1063-6919}, + DOI = {10.1109/CVPR.2016.90}, + type = {Conference Proceedings} +} +``` + +#### Diffusion imaging + +#### Application + + +## Setup +> pip install -r [path/to/requirements.txt] +> python3 <main_script>.py + + +## Project architecture +### Folder structure + +``` +── samitorch +| ├── configs - This folder contains the YAML configuration files. +| │ ├── configurations.py - This file contains the definitions of different configuration classes. +| │ |── resnet3d.yaml - Standard ResNet 3D configuration file and model definition. +| │ └── unet3d.yaml - Standard UNet 3D configuration file and model definition. +| | +| ├── initializers - This folder contains custom layer/op initializers. +| | └── initializers.py +| │ +| ├── inputs - This folder contains anything relative to inputs to a network. +| | |── batch.py - Contains Batch definition object used in training. +| | |── datasets.py - Contains basic dataset definition for classification and segmentation. +| | |── images.py - Contains Enums for various methods. +| | |── patch.py - Contains Patch definition used in segmentation problems. +| | |── sample.py - Contains a Sample object. +| | |── transformers.py - Contains a series of common transformations. +| | └── utils.py - Contains various utilitary methods. +| | +| ├── models - This folder contains any standard and tested deep learning models. +| │ |── layers.py - Contains layer definitions. +| | |── resnet3d.py - Contains a standard ResNet 3D model. +| | └── unet3d.py - Contains a standard UNet 3D model. +| | +| |── parsers - This folder contains parsers definition used in SAMITorch. +| | +| ├── preprocessing - This folder contains anything relative to input preprocessing, and scripts that must be executed prior training. +| | +| └── utils - This folder contains any utils you may need. +| |── files.py - Contains file related utils methods. +| |── slice_builder.py - Contains an object to build slices out of a data sets (for image segmentation). +| └── tensors.py - Contains tensor related utils methods. +── tests - Folder containing unit tests of the standard framework api and functions. + +``` + +### Main components +(To be documented shortly...) +#### Models + +#### Transformers + +#### Configs + +#### Main + +## Contributing +If you find a bug or have an idea for an improvement, please first have a look at our [contribution guideline](https://github.com/sami-ets/SAMITorch/blob/master/CONTRIBUTING.md). Then, +- [X] Create a branch by feature and/or bug fix +- [X] Get the code +- [X] Commit and push +- [X] Create a pull request + +## Branch naming + +| Instance | Branch | Description, Instructions, Notes | +|-----------------|-----------------------------------------------------|----------------------------------------------------| +| Stable | stable | Accepts merges from Development and Hotfixes | +| Development | dev/ [Short description] [Issue number] | Accepts merges from Features / Issues and Hotfixes | +| Features/Issues | feature/ [Short feature description] [Issue number] | Always branch off HEAD or dev/ | +| Hotfix | fix/ [Short feature description] [Issue number] | Always branch off Stable | + +## Commits syntax + +##### Adding code: +> \+ Added [Short Description] [Issue Number] + +##### Deleting code: +> \- Deleted [Short Description] [Issue Number] + +##### Modifying code: +> \* Changed [Short Description] [Issue Number] + +##### Merging branches: +> Y Merged [Short Description] + +## To build documentation + +SAMITorch uses Sphinx Documentation. To build doc, simply execute the following: + +> cd docs +> sphinx-build -b html source build + + +## Acknowledgment +Thanks to [École de technologie supérieure](https://www.etsmtl.ca/), [Hervé Lombaert](https://profs.etsmtl.ca/hlombaert/) and [Christian Desrosiers](https://www.etsmtl.ca/Professeurs/cdesrosiers/Accueil) for providing us a lab and helping us in our research activities. + +Icons made by <a href="http://www.flaticon.com/authors/freepik" title="Freepik">Freepik</a> from <a href="http://www.flaticon.com" title="Flaticon">www.flaticon.com</a> is licensed by <a href="http://creativecommons.org/licenses/by/3.0/" title="Creative Commons BY 3.0" target="_blank">CC 3.0 BY</a> + +%package -n python3-SAMITorch +Summary: Deep Learning Framework For Medical Image Analysis +Provides: python-SAMITorch +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-SAMITorch +# <img src="/icons/artificial-intelligence.png" width="60" vertical-align="bottom"> SAMITorch + +## Welcome to SAMITorch + +[](https://travis-ci.com/sami-ets/SAMITorch) + + + + + + +SAMITorch is a deep learning framework for *Shape Analysis in Medical Imaging* laboratory of [École de technologie supérieure](https://www.etsmtl.ca/) using [PyTorch](https://github.com/pytorch) library. +It implements an extensive set of loaders, transformers, models and data sets suited for deep learning in medical imaging. +Our objective is to build a tested, standard framework for quickly producing results in deep learning reasearch applied to medical imaging. + +# Table Of Contents + +- [Authors](#authors) +- [References](#references) +- [Project architecture](#project-architecture) + - [Folder structure](#folder-structure) + - [Main Components](#main-components) + - [Models](#models) + - [Transformers](#transformers) + - [Configuration](#configs) + - [Main](#main) + - [Contributing](#contributing) + - [Branch naming](#branch-naming) + - [Commits syntax](#commits-syntax) + - [Acknowledgments](#acknowledgments) + + +## Authors + +* Pierre-Luc Delisle - [pldelisle](https://github.com/pldelisle) +* Benoit Anctil-Robitaille - [banctilrobitaille](https://github.com/banctilrobitaille) + +## References + +#### Segmentation +``` +@article{RN10, + author = {Çiçek, Özgün and Abdulkadir, Ahmed and Lienkamp, Soeren S. and Brox, Thomas and Ronneberger, Olaf}, + title = {3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation}, + journal = {eprint arXiv:1606.06650}, + pages = {arXiv:1606.06650}, + url = {https://ui.adsabs.harvard.edu/\#abs/2016arXiv160606650C}, + year = {2016}, + type = {Journal Article} +} +``` + +#### Classification +``` +@inproceedings{RN12, + author = {He, K. and Zhang, X. and Ren, S. and Sun, J.}, + title = {Deep Residual Learning for Image Recognition}, + booktitle = {2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, + pages = {770-778}, + ISBN = {1063-6919}, + DOI = {10.1109/CVPR.2016.90}, + type = {Conference Proceedings} +} +``` + +#### Diffusion imaging + +#### Application + + +## Setup +> pip install -r [path/to/requirements.txt] +> python3 <main_script>.py + + +## Project architecture +### Folder structure + +``` +── samitorch +| ├── configs - This folder contains the YAML configuration files. +| │ ├── configurations.py - This file contains the definitions of different configuration classes. +| │ |── resnet3d.yaml - Standard ResNet 3D configuration file and model definition. +| │ └── unet3d.yaml - Standard UNet 3D configuration file and model definition. +| | +| ├── initializers - This folder contains custom layer/op initializers. +| | └── initializers.py +| │ +| ├── inputs - This folder contains anything relative to inputs to a network. +| | |── batch.py - Contains Batch definition object used in training. +| | |── datasets.py - Contains basic dataset definition for classification and segmentation. +| | |── images.py - Contains Enums for various methods. +| | |── patch.py - Contains Patch definition used in segmentation problems. +| | |── sample.py - Contains a Sample object. +| | |── transformers.py - Contains a series of common transformations. +| | └── utils.py - Contains various utilitary methods. +| | +| ├── models - This folder contains any standard and tested deep learning models. +| │ |── layers.py - Contains layer definitions. +| | |── resnet3d.py - Contains a standard ResNet 3D model. +| | └── unet3d.py - Contains a standard UNet 3D model. +| | +| |── parsers - This folder contains parsers definition used in SAMITorch. +| | +| ├── preprocessing - This folder contains anything relative to input preprocessing, and scripts that must be executed prior training. +| | +| └── utils - This folder contains any utils you may need. +| |── files.py - Contains file related utils methods. +| |── slice_builder.py - Contains an object to build slices out of a data sets (for image segmentation). +| └── tensors.py - Contains tensor related utils methods. +── tests - Folder containing unit tests of the standard framework api and functions. + +``` + +### Main components +(To be documented shortly...) +#### Models + +#### Transformers + +#### Configs + +#### Main + +## Contributing +If you find a bug or have an idea for an improvement, please first have a look at our [contribution guideline](https://github.com/sami-ets/SAMITorch/blob/master/CONTRIBUTING.md). Then, +- [X] Create a branch by feature and/or bug fix +- [X] Get the code +- [X] Commit and push +- [X] Create a pull request + +## Branch naming + +| Instance | Branch | Description, Instructions, Notes | +|-----------------|-----------------------------------------------------|----------------------------------------------------| +| Stable | stable | Accepts merges from Development and Hotfixes | +| Development | dev/ [Short description] [Issue number] | Accepts merges from Features / Issues and Hotfixes | +| Features/Issues | feature/ [Short feature description] [Issue number] | Always branch off HEAD or dev/ | +| Hotfix | fix/ [Short feature description] [Issue number] | Always branch off Stable | + +## Commits syntax + +##### Adding code: +> \+ Added [Short Description] [Issue Number] + +##### Deleting code: +> \- Deleted [Short Description] [Issue Number] + +##### Modifying code: +> \* Changed [Short Description] [Issue Number] + +##### Merging branches: +> Y Merged [Short Description] + +## To build documentation + +SAMITorch uses Sphinx Documentation. To build doc, simply execute the following: + +> cd docs +> sphinx-build -b html source build + + +## Acknowledgment +Thanks to [École de technologie supérieure](https://www.etsmtl.ca/), [Hervé Lombaert](https://profs.etsmtl.ca/hlombaert/) and [Christian Desrosiers](https://www.etsmtl.ca/Professeurs/cdesrosiers/Accueil) for providing us a lab and helping us in our research activities. + +Icons made by <a href="http://www.flaticon.com/authors/freepik" title="Freepik">Freepik</a> from <a href="http://www.flaticon.com" title="Flaticon">www.flaticon.com</a> is licensed by <a href="http://creativecommons.org/licenses/by/3.0/" title="Creative Commons BY 3.0" target="_blank">CC 3.0 BY</a> + +%package help +Summary: Development documents and examples for SAMITorch +Provides: python3-SAMITorch-doc +%description help +# <img src="/icons/artificial-intelligence.png" width="60" vertical-align="bottom"> SAMITorch + +## Welcome to SAMITorch + +[](https://travis-ci.com/sami-ets/SAMITorch) + + + + + + +SAMITorch is a deep learning framework for *Shape Analysis in Medical Imaging* laboratory of [École de technologie supérieure](https://www.etsmtl.ca/) using [PyTorch](https://github.com/pytorch) library. +It implements an extensive set of loaders, transformers, models and data sets suited for deep learning in medical imaging. +Our objective is to build a tested, standard framework for quickly producing results in deep learning reasearch applied to medical imaging. + +# Table Of Contents + +- [Authors](#authors) +- [References](#references) +- [Project architecture](#project-architecture) + - [Folder structure](#folder-structure) + - [Main Components](#main-components) + - [Models](#models) + - [Transformers](#transformers) + - [Configuration](#configs) + - [Main](#main) + - [Contributing](#contributing) + - [Branch naming](#branch-naming) + - [Commits syntax](#commits-syntax) + - [Acknowledgments](#acknowledgments) + + +## Authors + +* Pierre-Luc Delisle - [pldelisle](https://github.com/pldelisle) +* Benoit Anctil-Robitaille - [banctilrobitaille](https://github.com/banctilrobitaille) + +## References + +#### Segmentation +``` +@article{RN10, + author = {Çiçek, Özgün and Abdulkadir, Ahmed and Lienkamp, Soeren S. and Brox, Thomas and Ronneberger, Olaf}, + title = {3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation}, + journal = {eprint arXiv:1606.06650}, + pages = {arXiv:1606.06650}, + url = {https://ui.adsabs.harvard.edu/\#abs/2016arXiv160606650C}, + year = {2016}, + type = {Journal Article} +} +``` + +#### Classification +``` +@inproceedings{RN12, + author = {He, K. and Zhang, X. and Ren, S. and Sun, J.}, + title = {Deep Residual Learning for Image Recognition}, + booktitle = {2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, + pages = {770-778}, + ISBN = {1063-6919}, + DOI = {10.1109/CVPR.2016.90}, + type = {Conference Proceedings} +} +``` + +#### Diffusion imaging + +#### Application + + +## Setup +> pip install -r [path/to/requirements.txt] +> python3 <main_script>.py + + +## Project architecture +### Folder structure + +``` +── samitorch +| ├── configs - This folder contains the YAML configuration files. +| │ ├── configurations.py - This file contains the definitions of different configuration classes. +| │ |── resnet3d.yaml - Standard ResNet 3D configuration file and model definition. +| │ └── unet3d.yaml - Standard UNet 3D configuration file and model definition. +| | +| ├── initializers - This folder contains custom layer/op initializers. +| | └── initializers.py +| │ +| ├── inputs - This folder contains anything relative to inputs to a network. +| | |── batch.py - Contains Batch definition object used in training. +| | |── datasets.py - Contains basic dataset definition for classification and segmentation. +| | |── images.py - Contains Enums for various methods. +| | |── patch.py - Contains Patch definition used in segmentation problems. +| | |── sample.py - Contains a Sample object. +| | |── transformers.py - Contains a series of common transformations. +| | └── utils.py - Contains various utilitary methods. +| | +| ├── models - This folder contains any standard and tested deep learning models. +| │ |── layers.py - Contains layer definitions. +| | |── resnet3d.py - Contains a standard ResNet 3D model. +| | └── unet3d.py - Contains a standard UNet 3D model. +| | +| |── parsers - This folder contains parsers definition used in SAMITorch. +| | +| ├── preprocessing - This folder contains anything relative to input preprocessing, and scripts that must be executed prior training. +| | +| └── utils - This folder contains any utils you may need. +| |── files.py - Contains file related utils methods. +| |── slice_builder.py - Contains an object to build slices out of a data sets (for image segmentation). +| └── tensors.py - Contains tensor related utils methods. +── tests - Folder containing unit tests of the standard framework api and functions. + +``` + +### Main components +(To be documented shortly...) +#### Models + +#### Transformers + +#### Configs + +#### Main + +## Contributing +If you find a bug or have an idea for an improvement, please first have a look at our [contribution guideline](https://github.com/sami-ets/SAMITorch/blob/master/CONTRIBUTING.md). Then, +- [X] Create a branch by feature and/or bug fix +- [X] Get the code +- [X] Commit and push +- [X] Create a pull request + +## Branch naming + +| Instance | Branch | Description, Instructions, Notes | +|-----------------|-----------------------------------------------------|----------------------------------------------------| +| Stable | stable | Accepts merges from Development and Hotfixes | +| Development | dev/ [Short description] [Issue number] | Accepts merges from Features / Issues and Hotfixes | +| Features/Issues | feature/ [Short feature description] [Issue number] | Always branch off HEAD or dev/ | +| Hotfix | fix/ [Short feature description] [Issue number] | Always branch off Stable | + +## Commits syntax + +##### Adding code: +> \+ Added [Short Description] [Issue Number] + +##### Deleting code: +> \- Deleted [Short Description] [Issue Number] + +##### Modifying code: +> \* Changed [Short Description] [Issue Number] + +##### Merging branches: +> Y Merged [Short Description] + +## To build documentation + +SAMITorch uses Sphinx Documentation. To build doc, simply execute the following: + +> cd docs +> sphinx-build -b html source build + + +## Acknowledgment +Thanks to [École de technologie supérieure](https://www.etsmtl.ca/), [Hervé Lombaert](https://profs.etsmtl.ca/hlombaert/) and [Christian Desrosiers](https://www.etsmtl.ca/Professeurs/cdesrosiers/Accueil) for providing us a lab and helping us in our research activities. + +Icons made by <a href="http://www.flaticon.com/authors/freepik" title="Freepik">Freepik</a> from <a href="http://www.flaticon.com" title="Flaticon">www.flaticon.com</a> is licensed by <a href="http://creativecommons.org/licenses/by/3.0/" title="Creative Commons BY 3.0" target="_blank">CC 3.0 BY</a> + +%prep +%autosetup -n SAMITorch-0.2.7 + +%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-SAMITorch -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.7-1 +- Package Spec generated @@ -0,0 +1 @@ +4ef6dba35cb74eb7925a9fcf2c590a59 SAMITorch-0.2.7.tar.gz |