%global _empty_manifest_terminate_build 0 Name: python-mirdata Version: 0.3.7 Release: 1 Summary: Common loaders for MIR datasets. License: BSD-3-Clause URL: https://github.com/mir-dataset-loaders/mirdata Source0: https://mirrors.aliyun.com/pypi/web/packages/bd/57/00c6ce24c1a5f8db1ae0fe9256d05a2c77978b1b05585beb4db36b15389d/mirdata-0.3.7.tar.gz BuildArch: noarch Requires: python3-tqdm Requires: python3-librosa Requires: python3-numpy Requires: python3-jams Requires: python3-requests Requires: python3-pretty-midi Requires: python3-chardet Requires: python3-pyyaml Requires: python3-scipy Requires: python3-h5py Requires: python3-smart-open Requires: python3-Deprecated Requires: python3-pandas Requires: python3-openpyxl Requires: python3-openpyxl Requires: python3-dali-dataset Requires: python3-numpydoc Requires: python3-recommonmark Requires: python3-sphinx Requires: python3-sphinxcontrib-napoleon Requires: python3-sphinx-rtd-theme Requires: python3-smart-open[gcs] Requires: python3-music21 Requires: python3-smart-open[http] Requires: python3-smart-open[s3] Requires: python3-pytest Requires: python3-pytest-cov Requires: python3-pytest-pep8 Requires: python3-pytest-mock Requires: python3-pytest-localserver Requires: python3-testcontainers Requires: python3-future Requires: python3-coveralls Requires: python3-types-PyYAML Requires: python3-types-chardet Requires: python3-smart-open[all] %description # mirdata common loaders for Music Information Retrieval (MIR) datasets. Find the API documentation [here](https://mirdata.readthedocs.io/). [![CircleCI](https://circleci.com/gh/mir-dataset-loaders/mirdata.svg?style=svg)](https://circleci.com/gh/mir-dataset-loaders/mirdata) [![codecov](https://codecov.io/gh/mir-dataset-loaders/mirdata/branch/master/graph/badge.svg)](https://codecov.io/gh/mir-dataset-loaders/mirdata) [![Documentation Status](https://readthedocs.org/projects/mirdata/badge/?version=latest)](https://mirdata.readthedocs.io/en/latest/?badge=latest) ![GitHub](https://img.shields.io/github/license/mir-dataset-loaders/mirdata.svg) This library provides tools for working with common MIR datasets, including tools for: * downloading datasets to a common location and format * validating that the files for a dataset are all present * loading annotation files to a common format, consistent with the format required by [mir_eval](https://github.com/craffel/mir_eval) * parsing track level metadata for detailed evaluations ### Installation To install, simply run: ```python pip install mirdata ``` ### Quick example ```python import mirdata orchset = mirdata.initialize('orchset') orchset.download() # download the dataset orchset.validate() # validate that all the expected files are there example_track = orchset.choice_track() # choose a random example track print(example_track) # see the available data ``` See the [documentation](https://mirdata.readthedocs.io/) for more examples and the API reference. ### Currently supported datasets Supported datasets include [AcousticBrainz](https://zenodo.org/record/2553414#.X8jTgulKhhE), [DALI](https://github.com/gabolsgabs/DALI), [Guitarset](http://github.com/marl/guitarset/), [MAESTRO](https://magenta.tensorflow.org/datasets/maestro), [TinySOL](https://www.orch-idea.org/), among many others. For the **complete list** of supported datasets, see the [documentation](https://mirdata.readthedocs.io/en/stable/source/quick_reference.html) ### Citing There are two ways of citing mirdata: If you are using the library for your work, please cite the version you used as indexed at Zenodo: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4355859.svg)](https://doi.org/10.5281/zenodo.4355859) If you refer to mirdata's design principles, motivation etc., please cite the following [paper](https://zenodo.org/record/3527750#.X-Inp5NKhUI): [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3527750.svg)](https://doi.org/10.5281/zenodo.3527750) ``` "mirdata: Software for Reproducible Usage of Datasets" Rachel M. Bittner, Magdalena Fuentes, David Rubinstein, Andreas Jansson, Keunwoo Choi, and Thor Kell in International Society for Music Information Retrieval (ISMIR) Conference, 2019 ``` ``` @inproceedings{ bittner_fuentes_2019, title={mirdata: Software for Reproducible Usage of Datasets}, author={Bittner, Rachel M and Fuentes, Magdalena and Rubinstein, David and Jansson, Andreas and Choi, Keunwoo and Kell, Thor}, booktitle={International Society for Music Information Retrieval (ISMIR) Conference}, year={2019} } ``` When working with datasets, please cite the version of `mirdata` that you are using (given by the `DOI` above) **AND** include the reference of the dataset, which can be found in the respective dataset loader using the `cite()` method. ### Contributing a new dataset loader We welcome contributions to this library, especially new datasets. Please see [contributing](https://mirdata.readthedocs.io/en/latest/source/contributing.html) for guidelines. %package -n python3-mirdata Summary: Common loaders for MIR datasets. Provides: python-mirdata BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-mirdata # mirdata common loaders for Music Information Retrieval (MIR) datasets. Find the API documentation [here](https://mirdata.readthedocs.io/). [![CircleCI](https://circleci.com/gh/mir-dataset-loaders/mirdata.svg?style=svg)](https://circleci.com/gh/mir-dataset-loaders/mirdata) [![codecov](https://codecov.io/gh/mir-dataset-loaders/mirdata/branch/master/graph/badge.svg)](https://codecov.io/gh/mir-dataset-loaders/mirdata) [![Documentation Status](https://readthedocs.org/projects/mirdata/badge/?version=latest)](https://mirdata.readthedocs.io/en/latest/?badge=latest) ![GitHub](https://img.shields.io/github/license/mir-dataset-loaders/mirdata.svg) This library provides tools for working with common MIR datasets, including tools for: * downloading datasets to a common location and format * validating that the files for a dataset are all present * loading annotation files to a common format, consistent with the format required by [mir_eval](https://github.com/craffel/mir_eval) * parsing track level metadata for detailed evaluations ### Installation To install, simply run: ```python pip install mirdata ``` ### Quick example ```python import mirdata orchset = mirdata.initialize('orchset') orchset.download() # download the dataset orchset.validate() # validate that all the expected files are there example_track = orchset.choice_track() # choose a random example track print(example_track) # see the available data ``` See the [documentation](https://mirdata.readthedocs.io/) for more examples and the API reference. ### Currently supported datasets Supported datasets include [AcousticBrainz](https://zenodo.org/record/2553414#.X8jTgulKhhE), [DALI](https://github.com/gabolsgabs/DALI), [Guitarset](http://github.com/marl/guitarset/), [MAESTRO](https://magenta.tensorflow.org/datasets/maestro), [TinySOL](https://www.orch-idea.org/), among many others. For the **complete list** of supported datasets, see the [documentation](https://mirdata.readthedocs.io/en/stable/source/quick_reference.html) ### Citing There are two ways of citing mirdata: If you are using the library for your work, please cite the version you used as indexed at Zenodo: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4355859.svg)](https://doi.org/10.5281/zenodo.4355859) If you refer to mirdata's design principles, motivation etc., please cite the following [paper](https://zenodo.org/record/3527750#.X-Inp5NKhUI): [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3527750.svg)](https://doi.org/10.5281/zenodo.3527750) ``` "mirdata: Software for Reproducible Usage of Datasets" Rachel M. Bittner, Magdalena Fuentes, David Rubinstein, Andreas Jansson, Keunwoo Choi, and Thor Kell in International Society for Music Information Retrieval (ISMIR) Conference, 2019 ``` ``` @inproceedings{ bittner_fuentes_2019, title={mirdata: Software for Reproducible Usage of Datasets}, author={Bittner, Rachel M and Fuentes, Magdalena and Rubinstein, David and Jansson, Andreas and Choi, Keunwoo and Kell, Thor}, booktitle={International Society for Music Information Retrieval (ISMIR) Conference}, year={2019} } ``` When working with datasets, please cite the version of `mirdata` that you are using (given by the `DOI` above) **AND** include the reference of the dataset, which can be found in the respective dataset loader using the `cite()` method. ### Contributing a new dataset loader We welcome contributions to this library, especially new datasets. Please see [contributing](https://mirdata.readthedocs.io/en/latest/source/contributing.html) for guidelines. %package help Summary: Development documents and examples for mirdata Provides: python3-mirdata-doc %description help # mirdata common loaders for Music Information Retrieval (MIR) datasets. Find the API documentation [here](https://mirdata.readthedocs.io/). [![CircleCI](https://circleci.com/gh/mir-dataset-loaders/mirdata.svg?style=svg)](https://circleci.com/gh/mir-dataset-loaders/mirdata) [![codecov](https://codecov.io/gh/mir-dataset-loaders/mirdata/branch/master/graph/badge.svg)](https://codecov.io/gh/mir-dataset-loaders/mirdata) [![Documentation Status](https://readthedocs.org/projects/mirdata/badge/?version=latest)](https://mirdata.readthedocs.io/en/latest/?badge=latest) ![GitHub](https://img.shields.io/github/license/mir-dataset-loaders/mirdata.svg) This library provides tools for working with common MIR datasets, including tools for: * downloading datasets to a common location and format * validating that the files for a dataset are all present * loading annotation files to a common format, consistent with the format required by [mir_eval](https://github.com/craffel/mir_eval) * parsing track level metadata for detailed evaluations ### Installation To install, simply run: ```python pip install mirdata ``` ### Quick example ```python import mirdata orchset = mirdata.initialize('orchset') orchset.download() # download the dataset orchset.validate() # validate that all the expected files are there example_track = orchset.choice_track() # choose a random example track print(example_track) # see the available data ``` See the [documentation](https://mirdata.readthedocs.io/) for more examples and the API reference. ### Currently supported datasets Supported datasets include [AcousticBrainz](https://zenodo.org/record/2553414#.X8jTgulKhhE), [DALI](https://github.com/gabolsgabs/DALI), [Guitarset](http://github.com/marl/guitarset/), [MAESTRO](https://magenta.tensorflow.org/datasets/maestro), [TinySOL](https://www.orch-idea.org/), among many others. For the **complete list** of supported datasets, see the [documentation](https://mirdata.readthedocs.io/en/stable/source/quick_reference.html) ### Citing There are two ways of citing mirdata: If you are using the library for your work, please cite the version you used as indexed at Zenodo: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4355859.svg)](https://doi.org/10.5281/zenodo.4355859) If you refer to mirdata's design principles, motivation etc., please cite the following [paper](https://zenodo.org/record/3527750#.X-Inp5NKhUI): [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3527750.svg)](https://doi.org/10.5281/zenodo.3527750) ``` "mirdata: Software for Reproducible Usage of Datasets" Rachel M. Bittner, Magdalena Fuentes, David Rubinstein, Andreas Jansson, Keunwoo Choi, and Thor Kell in International Society for Music Information Retrieval (ISMIR) Conference, 2019 ``` ``` @inproceedings{ bittner_fuentes_2019, title={mirdata: Software for Reproducible Usage of Datasets}, author={Bittner, Rachel M and Fuentes, Magdalena and Rubinstein, David and Jansson, Andreas and Choi, Keunwoo and Kell, Thor}, booktitle={International Society for Music Information Retrieval (ISMIR) Conference}, year={2019} } ``` When working with datasets, please cite the version of `mirdata` that you are using (given by the `DOI` above) **AND** include the reference of the dataset, which can be found in the respective dataset loader using the `cite()` method. ### Contributing a new dataset loader We welcome contributions to this library, especially new datasets. Please see [contributing](https://mirdata.readthedocs.io/en/latest/source/contributing.html) for guidelines. %prep %autosetup -n mirdata-0.3.7 %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-mirdata -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Thu Jun 08 2023 Python_Bot - 0.3.7-1 - Package Spec generated