diff options
Diffstat (limited to 'python-chia.spec')
| -rw-r--r-- | python-chia.spec | 273 |
1 files changed, 273 insertions, 0 deletions
diff --git a/python-chia.spec b/python-chia.spec new file mode 100644 index 0000000..22c34c1 --- /dev/null +++ b/python-chia.spec @@ -0,0 +1,273 @@ +%global _empty_manifest_terminate_build 0 +Name: python-chia +Version: 2.5.0 +Release: 1 +Summary: Concept Hierarchies for Incremental and Active Learning +License: BSD License +URL: https://github.com/cabrust/chia +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/6b/3c/5d34b6146b2a6e437795093e1c5b16b3fa86cf661ae4fba5d9da5ad6c1f3/chia-2.5.0.tar.gz +BuildArch: noarch + +Requires: python3-configuration +Requires: python3-nltk +Requires: python3-imageio +Requires: python3-pillow +Requires: python3-gputil +Requires: python3-networkx +Requires: python3-numpy +Requires: python3-tensorflow-addons +Requires: python3-tensorflow + +%description +# CHIA: Concept Hierarchies for Incremental and Active Learning + + + + + + +CHIA implements methods centered around hierarchical classification in a lifelong learning environment. +It forms the basis for some of the experiments and tools developed at [Computer Vision Group Jena](http://www.inf-cv.uni-jena.de/). +Development is continued at the [DLR Institute of Data Science](https://www.dlr.de/dw/en/desktopdefault.aspx/tabid-12192/21400_read-49437/) + +**Methods**\ +CHIA implements: + * **One-Hot Softmax Classifier** as a baseline. + * **Probabilistic Hierarchical Classifier** Brust, C. A., & Denzler, J. (2019). *Integrating domain knowledge: using hierarchies to improve deep classifiers*. In Asian Conference on Pattern Recognition (ACPR) + * **CHILLAX** Brust, C. A., Barz, B., & Denzler, J. (2021). *Making Every Label Count: Handling Semantic Imprecision by Integrating Domain Knowledge*. In International Conference on Pattern Recognition (ICPR). + * **Self-Supervised CHILLAX** Brust, C. A., Barz, B., & Denzler, J. (2022). *Self-Supervised Learning from Semantically Imprecise Data*. In Computer Vision Theory and Applications (VISAPP) + * **Semantic Label Sharing** Fergus, R., Bernal, H., Weiss, Y., & Torralba, A. (2010). *Semantic label sharing for learning with many categories*. In European Conference on Computer Vision (ECCV). + +**Datasets**\ +CHIA has integrated support including hierarchies for a number of popular datasets. See [here](docs/architecture.md#dataset) for a complete list. + + +## Installation and Getting Started +CHIA is available on PyPI. To install, simply run: +```bash +pip install chia +``` +or clone this repository, and run: +```bash +pip install -e . +``` + +To run the [example experiment](examples/experiment.py) which makes sure that everything works, use the following command: +```bash +python examples/experiment.py examples/configuration.json +``` +After a few minutes, the last lines of output should look like this: +```text +[SHUTDOWN] [Experiment] Successful: True +``` + +## Documentation +The following articles explain more about CHIA: + * [Architecture](docs/architecture.md) explains the overall construction. It also includes reference descriptions of most classes. + * [Configuration](docs/configuration.md) describes how experiments and CHIA itself are configured. + * [Using your own dataset](docs/dataset.md) explains our JSON format for adding your own data. + +## Citation +If you use CHIA for your research, kindly cite: +> Brust, C. A., & Denzler, J. (2019). Integrating domain knowledge: using hierarchies to improve deep classifiers. In Asian Conference on Pattern Recognition. Springer, Cham. + +You can refer to the following BibTeX: +```bibtex +@inproceedings{Brust2019IDK, +author = {Clemens-Alexander Brust and Joachim Denzler}, +booktitle = {Asian Conference on Pattern Recognition (ACPR)}, +title = {Integrating Domain Knowledge: Using Hierarchies to Improve Deep Classifiers}, +year = {2019}, +doi = {10.1007/978-3-030-41404-7_1} +} +``` + + + + +%package -n python3-chia +Summary: Concept Hierarchies for Incremental and Active Learning +Provides: python-chia +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-chia +# CHIA: Concept Hierarchies for Incremental and Active Learning + + + + + + +CHIA implements methods centered around hierarchical classification in a lifelong learning environment. +It forms the basis for some of the experiments and tools developed at [Computer Vision Group Jena](http://www.inf-cv.uni-jena.de/). +Development is continued at the [DLR Institute of Data Science](https://www.dlr.de/dw/en/desktopdefault.aspx/tabid-12192/21400_read-49437/) + +**Methods**\ +CHIA implements: + * **One-Hot Softmax Classifier** as a baseline. + * **Probabilistic Hierarchical Classifier** Brust, C. A., & Denzler, J. (2019). *Integrating domain knowledge: using hierarchies to improve deep classifiers*. In Asian Conference on Pattern Recognition (ACPR) + * **CHILLAX** Brust, C. A., Barz, B., & Denzler, J. (2021). *Making Every Label Count: Handling Semantic Imprecision by Integrating Domain Knowledge*. In International Conference on Pattern Recognition (ICPR). + * **Self-Supervised CHILLAX** Brust, C. A., Barz, B., & Denzler, J. (2022). *Self-Supervised Learning from Semantically Imprecise Data*. In Computer Vision Theory and Applications (VISAPP) + * **Semantic Label Sharing** Fergus, R., Bernal, H., Weiss, Y., & Torralba, A. (2010). *Semantic label sharing for learning with many categories*. In European Conference on Computer Vision (ECCV). + +**Datasets**\ +CHIA has integrated support including hierarchies for a number of popular datasets. See [here](docs/architecture.md#dataset) for a complete list. + + +## Installation and Getting Started +CHIA is available on PyPI. To install, simply run: +```bash +pip install chia +``` +or clone this repository, and run: +```bash +pip install -e . +``` + +To run the [example experiment](examples/experiment.py) which makes sure that everything works, use the following command: +```bash +python examples/experiment.py examples/configuration.json +``` +After a few minutes, the last lines of output should look like this: +```text +[SHUTDOWN] [Experiment] Successful: True +``` + +## Documentation +The following articles explain more about CHIA: + * [Architecture](docs/architecture.md) explains the overall construction. It also includes reference descriptions of most classes. + * [Configuration](docs/configuration.md) describes how experiments and CHIA itself are configured. + * [Using your own dataset](docs/dataset.md) explains our JSON format for adding your own data. + +## Citation +If you use CHIA for your research, kindly cite: +> Brust, C. A., & Denzler, J. (2019). Integrating domain knowledge: using hierarchies to improve deep classifiers. In Asian Conference on Pattern Recognition. Springer, Cham. + +You can refer to the following BibTeX: +```bibtex +@inproceedings{Brust2019IDK, +author = {Clemens-Alexander Brust and Joachim Denzler}, +booktitle = {Asian Conference on Pattern Recognition (ACPR)}, +title = {Integrating Domain Knowledge: Using Hierarchies to Improve Deep Classifiers}, +year = {2019}, +doi = {10.1007/978-3-030-41404-7_1} +} +``` + + + + +%package help +Summary: Development documents and examples for chia +Provides: python3-chia-doc +%description help +# CHIA: Concept Hierarchies for Incremental and Active Learning + + + + + + +CHIA implements methods centered around hierarchical classification in a lifelong learning environment. +It forms the basis for some of the experiments and tools developed at [Computer Vision Group Jena](http://www.inf-cv.uni-jena.de/). +Development is continued at the [DLR Institute of Data Science](https://www.dlr.de/dw/en/desktopdefault.aspx/tabid-12192/21400_read-49437/) + +**Methods**\ +CHIA implements: + * **One-Hot Softmax Classifier** as a baseline. + * **Probabilistic Hierarchical Classifier** Brust, C. A., & Denzler, J. (2019). *Integrating domain knowledge: using hierarchies to improve deep classifiers*. In Asian Conference on Pattern Recognition (ACPR) + * **CHILLAX** Brust, C. A., Barz, B., & Denzler, J. (2021). *Making Every Label Count: Handling Semantic Imprecision by Integrating Domain Knowledge*. In International Conference on Pattern Recognition (ICPR). + * **Self-Supervised CHILLAX** Brust, C. A., Barz, B., & Denzler, J. (2022). *Self-Supervised Learning from Semantically Imprecise Data*. In Computer Vision Theory and Applications (VISAPP) + * **Semantic Label Sharing** Fergus, R., Bernal, H., Weiss, Y., & Torralba, A. (2010). *Semantic label sharing for learning with many categories*. In European Conference on Computer Vision (ECCV). + +**Datasets**\ +CHIA has integrated support including hierarchies for a number of popular datasets. See [here](docs/architecture.md#dataset) for a complete list. + + +## Installation and Getting Started +CHIA is available on PyPI. To install, simply run: +```bash +pip install chia +``` +or clone this repository, and run: +```bash +pip install -e . +``` + +To run the [example experiment](examples/experiment.py) which makes sure that everything works, use the following command: +```bash +python examples/experiment.py examples/configuration.json +``` +After a few minutes, the last lines of output should look like this: +```text +[SHUTDOWN] [Experiment] Successful: True +``` + +## Documentation +The following articles explain more about CHIA: + * [Architecture](docs/architecture.md) explains the overall construction. It also includes reference descriptions of most classes. + * [Configuration](docs/configuration.md) describes how experiments and CHIA itself are configured. + * [Using your own dataset](docs/dataset.md) explains our JSON format for adding your own data. + +## Citation +If you use CHIA for your research, kindly cite: +> Brust, C. A., & Denzler, J. (2019). Integrating domain knowledge: using hierarchies to improve deep classifiers. In Asian Conference on Pattern Recognition. Springer, Cham. + +You can refer to the following BibTeX: +```bibtex +@inproceedings{Brust2019IDK, +author = {Clemens-Alexander Brust and Joachim Denzler}, +booktitle = {Asian Conference on Pattern Recognition (ACPR)}, +title = {Integrating Domain Knowledge: Using Hierarchies to Improve Deep Classifiers}, +year = {2019}, +doi = {10.1007/978-3-030-41404-7_1} +} +``` + + + + +%prep +%autosetup -n chia-2.5.0 + +%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-chia -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 2.5.0-1 +- Package Spec generated |