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            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Multimedia :: Sound/Audio :: Analysis"
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        "description": "# mirdata\ncommon loaders for Music Information Retrieval (MIR) datasets. Find the API documentation [here](https://mirdata.readthedocs.io/).\n\n[![CircleCI](https://circleci.com/gh/mir-dataset-loaders/mirdata.svg?style=svg)](https://circleci.com/gh/mir-dataset-loaders/mirdata)\n[![codecov](https://codecov.io/gh/mir-dataset-loaders/mirdata/branch/master/graph/badge.svg)](https://codecov.io/gh/mir-dataset-loaders/mirdata)\n[![Documentation Status](https://readthedocs.org/projects/mirdata/badge/?version=latest)](https://mirdata.readthedocs.io/en/latest/?badge=latest)\n![GitHub](https://img.shields.io/github/license/mir-dataset-loaders/mirdata.svg)\n\n\nThis library provides tools for working with common MIR datasets, including tools for:\n* downloading datasets to a common location and format\n* validating that the files for a dataset are all present \n* loading annotation files to a common format, consistent with the format required by [mir_eval](https://github.com/craffel/mir_eval)\n* parsing track level metadata for detailed evaluations\n\n\n### Installation\n\nTo install, simply run:\n\n```python\npip install mirdata\n```\n\n### Quick example\n```python\nimport mirdata\n\norchset = mirdata.initialize('orchset')\norchset.download()  # download the dataset\norchset.validate()  # validate that all the expected files are there\n\nexample_track = orchset.choice_track()  # choose a random example track\nprint(example_track)  # see the available data\n```\nSee the [documentation](https://mirdata.readthedocs.io/) for more examples and the API reference.\n\n\n### Currently supported datasets\n\n\nSupported 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.\n\nFor the **complete list** of supported datasets, see the [documentation](https://mirdata.readthedocs.io/en/stable/source/quick_reference.html)\n\n\n### Citing\n\n\nThere are two ways of citing mirdata:\n\nIf you are using the library for your work, please cite the version you used as indexed at Zenodo:\n\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4355859.svg)](https://doi.org/10.5281/zenodo.4355859)\n\nIf you refer to mirdata's design principles, motivation etc., please cite the following [paper](https://zenodo.org/record/3527750#.X-Inp5NKhUI):\n\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3527750.svg)](https://doi.org/10.5281/zenodo.3527750)\n\n```\n\"mirdata: Software for Reproducible Usage of Datasets\"\nRachel M. Bittner, Magdalena Fuentes, David Rubinstein, Andreas Jansson, Keunwoo Choi, and Thor Kell\nin International Society for Music Information Retrieval (ISMIR) Conference, 2019\n```\n\n```\n@inproceedings{\n  bittner_fuentes_2019,\n  title={mirdata: Software for Reproducible Usage of Datasets},\n  author={Bittner, Rachel M and Fuentes, Magdalena and Rubinstein, David and Jansson, Andreas and Choi, Keunwoo and Kell, Thor},\n  booktitle={International Society for Music Information Retrieval (ISMIR) Conference},\n  year={2019}\n}\n```\n\nWhen 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,\nwhich can be found in the respective dataset loader using the `cite()` method. \n\n### Contributing a new dataset loader\n\nWe welcome contributions to this library, especially new datasets. Please see [contributing](https://mirdata.readthedocs.io/en/latest/source/contributing.html) for guidelines.\n\n\n",
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