{"id":29026021,"url":"https://github.com/mtg/dcase-models","last_synced_at":"2025-10-16T00:12:40.974Z","repository":{"id":39972875,"uuid":"257940878","full_name":"MTG/DCASE-models","owner":"MTG","description":"Python library for rapid prototyping of environmental sound analysis systems","archived":false,"fork":false,"pushed_at":"2022-05-20T11:31:46.000Z","size":139411,"stargazers_count":43,"open_issues_count":12,"forks_count":5,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-06-17T22:18:14.759Z","etag":null,"topics":["audio-classification","audio-tagging","deep-learning","python","sound-event-detection"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MTG.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-04-22T15:23:57.000Z","updated_at":"2025-05-31T00:16:35.000Z","dependencies_parsed_at":"2022-08-25T09:01:08.007Z","dependency_job_id":null,"html_url":"https://github.com/MTG/DCASE-models","commit_stats":null,"previous_names":["pzinemanas/dcase-models"],"tags_count":5,"template":false,"template_full_name":null,"purl":"pkg:github/MTG/DCASE-models","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MTG%2FDCASE-models","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MTG%2FDCASE-models/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MTG%2FDCASE-models/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MTG%2FDCASE-models/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MTG","download_url":"https://codeload.github.com/MTG/DCASE-models/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MTG%2FDCASE-models/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262003993,"owners_count":23243358,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["audio-classification","audio-tagging","deep-learning","python","sound-event-detection"],"created_at":"2025-06-26T05:08:11.836Z","updated_at":"2025-10-16T00:12:40.969Z","avatar_url":"https://github.com/MTG.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cpre\u003e\n  ____   ____    _    ____  _____                          _      _     \n |  _ \\ / ___|  / \\  / ___|| ____|     _ __ ___   ___   __| | ___| |___ \n | | | | |     / _ \\ \\___ \\|  _| _____| '_ ` _ \\ / _ \\ / _` |/ _ \\ / __|\n | |_| | |___ / ___ \\ ___) | |__|_____| | | | | | (_) | (_| |  __/ \\__ \\\n |____/ \\____/_/   \\_\\____/|_____|    |_| |_| |_|\\___/ \\__,_|\\___|_|___/\n                                                                       \n\u003c/pre\u003e\n\n![example workflow](https://github.com/MTG/DCASE-models/actions/workflows/main.yml/badge.svg)\n[![codecov](https://codecov.io/gh/MTG/DCASE-models/branch/master/graph/badge.svg?token=xOOVldiH0J)](https://codecov.io/gh/MTG/DCASE-models)\n[![PyPI](https://img.shields.io/pypi/v/DCASE-models)](https://pypi.org/project/DCASE-models/)\n[![GitHub license](https://img.shields.io/github/license/pzinemanas/DCASE-models)](https://github.com/pzinemanas/DCASE-models/blob/master/LICENSE)\n\n\n`DCASE-models` is an open-source Python library for rapid prototyping of environmental sound analysis systems, with an emphasis on deep–learning models. The library has a flat and light design that allows easy extension and integration with other existing tools. \n\nDocumentation\n-------------\nSee [https://dcase-models.readthedocs.io](https://dcase-models.readthedocs.io/en/latest/) for a complete reference manual and introductory tutorials.\n\n## Installation instructions\nWe recommend to install DCASE-models in a dedicated virtual environment. For instance, using [anaconda](https://www.anaconda.com/):\n```\nconda create -n dcase python=3.6\nconda activate dcase\n```\nFor GPU support:\n```\nconda install cudatoolkit cudnn\n```\nDCASE-models uses [SoX](http://sox.sourceforge.net/) for functions related to the datasets. You can install it in your conda environment by:\n```\nconda install -c conda-forge sox\n```\nWhen installing the library, you must select the tensorflow variant: version 1 (CPU-only or GPU) or version 2.\n``` \npip install DCASE-models[keras_tf] # for tensorflow 1 CPU-only version\npip install DCASE-models[keras_tf_gpu] # for tensorflow 1 GPU version\npip install DCASE-models[tf2] # for tensorflow 2\n```\n\nTo include visualization related dependencies, run the following instead:\n```\npip install DCASE-models[visualization]\n```\n\n## Usage\nThere are several ways to use this library. In this repository, we accompany the library with three types of examples.\n\n\u003e Note that the default parameters for each model, dataset and feature representation, are stored in [`parameters.json`](parameters.json) on the root directory.\n\n### Python scripts\nThe folder [`scripts`](scripts) includes python scripts for data downloading, feature extraction, model training and testing, and fine-tuning. These examples show how to use DCASE-models within a python script.\n\n### Jupyter notebooks\nThe folder [`notebooks`](notebooks) includes a list of notebooks that replicate scientific experiments using DCASE-models.\n\n### Web applications\nThe folder [`visualization`](visualization) includes a user interface to define, train and visualize the models defined in this library.\n\nGo to DCASE-models folder and run:\n```\npython -m visualization.index\n```\nThen, open your browser and navigate to:\n```\nhttp://localhost:8050/\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmtg%2Fdcase-models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmtg%2Fdcase-models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmtg%2Fdcase-models/lists"}