{
    "info": {
        "author": "Albin Correya, Furkan Yesiler, Chris Traile, Philip Tovstogan, and Diego Silva",
        "author_email": "albin.correya@upf.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU Affero General Public License v3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Multimedia :: Sound/Audio :: Analysis"
        ],
        "description": "# acoss: Audio Cover Song Suite\n[![Build Status](https://travis-ci.org/furkanyesiler/acoss.svg?branch=master)](https://travis-ci.org/furkanyesiler/acoss)\n[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)\n[![License: AGPL v3](https://img.shields.io/badge/License-AGPL%20v3-blue.svg)](https://www.gnu.org/licenses/agpl-3.0)\n\n[acoss: Audio Cover Song Suite]() is a feature extraction and benchmarking frameworks for the \ncover song identification tasks. This tool has been developed along with the DA-TACOS dataset. \n\n## Setup & Installation\n\nWe recommend you to install the python package from source. \n\n#### Install from source (recommended)\n\n- Clone or download the repo.\n- Install `acoss` package by using the following command inside the directory.\n```bash\npython3 setup.py install\n```\n\n#### Install using pip\n\n```bash\npip3 install acoss\n```\n\n> NOTE: While using pip install, you might need to have a local installation of [librosa](https://librosa.github.io/) \npython library.\n\n## How to cite\n\nPlease site our paper if you use this tool in your resarch.\n\n> Furkan Yesiler, Chris Tralie, Albin Correya, Diego F. Silva, Philip Tovstogan, Emilia G\u00f3mez, and Xavier Serra. Da-TACOS: A Dataset for Cover Song Identification and Understanding. In 20th International Society for Music Information Retrieval Conference (ISMIR 2019), Delft, The Netherlands, 2019.\n\n\n## How to contribute?\n\n* Fork the repo!\n* Create your feature branch: git checkout -b my-new-feature\n* Please read the [documentation]() for adding your new audio feature or cover identification algorithm to acoss.\n* Commit your changes: git commit -am 'Add some feature'\n* Push to the branch: git push origin my-new-feature\n* Submit a pull request\n\n\n## Acknowledgements\n\nMIP-Frontiers, TROMPA\n\n\n\n",
        "description_content_type": "text/markdown",
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/furkanyesiler/acoss",
        "keywords": "audio music dsp musicinformationretireval coversongidentification",
        "license": "AGPL3.0",
        "maintainer": "",
        "maintainer_email": "",
        "name": "acoss",
        "package_url": "https://pypi.org/project/acoss/",
        "platform": "",
        "project_url": "https://pypi.org/project/acoss/",
        "project_urls": {
            "Homepage": "https://github.com/furkanyesiler/acoss",
            "Source": "https://github.com/furkanyesiler/acoss",
            "Tracker": "https://github.com/furkanyesiler/acoss/issues"
        },
        "release_url": "https://pypi.org/project/acoss/0.0.1/",
        "requires_dist": [
            "madmom",
            "numpy (>=1.16.5)",
            "pandas",
            "scipy (==1.2.1)",
            "scikit-learn (==0.19.2)",
            "deepdish",
            "essentia"
        ],
        "requires_python": "",
        "summary": "Audio Cover Song Suite (acoss): A benchmarking suite for cover song identification tasks",
        "version": "0.0.1"
    },
    "last_serial": 5976389,
    "releases": {
        "0.0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "275f3ef0e5988f724e218e762a7e0f5f",
                    "sha256": "1149d7453d2b94f6dd9e3f137998f4d2b2d3de1bd757994941a6b1e708664f6b"
                },
                "downloads": -1,
                "filename": "acoss-0.0.1-cp36-cp36m-manylinux1_i686.whl",
                "has_sig": false,
                "md5_digest": "275f3ef0e5988f724e218e762a7e0f5f",
                "packagetype": "bdist_wheel",
                "python_version": "cp36",
                "requires_python": null,
                "size": 106580,
                "upload_time": "2019-10-15T11:33:28",
                "url": "https://files.pythonhosted.org/packages/e9/42/e1f21ac83140e3eceb322543c936629183810ddd6432e90074c242bf47c1/acoss-0.0.1-cp36-cp36m-manylinux1_i686.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "8418084af3e4bc8922bc266e13d54d69",
                    "sha256": "bb3863fb6b1134216abe2a432dc81ca65615cfc299dc78e562f5bbeb18bb276f"
                },
                "downloads": -1,
                "filename": "acoss-0.0.1-cp36-cp36m-manylinux1_x86_64.whl",
                "has_sig": false,
                "md5_digest": "8418084af3e4bc8922bc266e13d54d69",
                "packagetype": "bdist_wheel",
                "python_version": "cp36",
                "requires_python": null,
                "size": 111715,
                "upload_time": "2019-10-15T11:33:32",
                "url": "https://files.pythonhosted.org/packages/80/ce/6f1bd996e25c450d319b25fa6ec021b8e5d350ef1b2c36c0be1bb5af8a76/acoss-0.0.1-cp36-cp36m-manylinux1_x86_64.whl"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "275f3ef0e5988f724e218e762a7e0f5f",
                "sha256": "1149d7453d2b94f6dd9e3f137998f4d2b2d3de1bd757994941a6b1e708664f6b"
            },
            "downloads": -1,
            "filename": "acoss-0.0.1-cp36-cp36m-manylinux1_i686.whl",
            "has_sig": false,
            "md5_digest": "275f3ef0e5988f724e218e762a7e0f5f",
            "packagetype": "bdist_wheel",
            "python_version": "cp36",
            "requires_python": null,
            "size": 106580,
            "upload_time": "2019-10-15T11:33:28",
            "url": "https://files.pythonhosted.org/packages/e9/42/e1f21ac83140e3eceb322543c936629183810ddd6432e90074c242bf47c1/acoss-0.0.1-cp36-cp36m-manylinux1_i686.whl"
        },
        {
            "comment_text": "",
            "digests": {
                "md5": "8418084af3e4bc8922bc266e13d54d69",
                "sha256": "bb3863fb6b1134216abe2a432dc81ca65615cfc299dc78e562f5bbeb18bb276f"
            },
            "downloads": -1,
            "filename": "acoss-0.0.1-cp36-cp36m-manylinux1_x86_64.whl",
            "has_sig": false,
            "md5_digest": "8418084af3e4bc8922bc266e13d54d69",
            "packagetype": "bdist_wheel",
            "python_version": "cp36",
            "requires_python": null,
            "size": 111715,
            "upload_time": "2019-10-15T11:33:32",
            "url": "https://files.pythonhosted.org/packages/80/ce/6f1bd996e25c450d319b25fa6ec021b8e5d350ef1b2c36c0be1bb5af8a76/acoss-0.0.1-cp36-cp36m-manylinux1_x86_64.whl"
        }
    ]
}