{"id":13586708,"url":"https://github.com/GianlucaPaolocci/Sound-classification-on-Raspberry-Pi-with-Tensorflow","last_synced_at":"2025-04-07T18:34:33.649Z","repository":{"id":22385404,"uuid":"94887182","full_name":"GianlucaPaolocci/Sound-classification-on-Raspberry-Pi-with-Tensorflow","owner":"GianlucaPaolocci","description":"In this project is presented a simple method to train an MLP neural network for audio signals. The trained model can be exported on a Raspberry Pi (2 or superior suggested) to classify audio signal registered with USB microphone  ","archived":false,"fork":false,"pushed_at":"2022-11-16T09:49:26.000Z","size":394,"stargazers_count":94,"open_issues_count":8,"forks_count":30,"subscribers_count":9,"default_branch":"master","last_synced_at":"2024-10-29T23:34:28.031Z","etag":null,"topics":["audio-analysis","audio-signals","dataset","librosa","machine-learning","multilayer-perceptron-network","raspberry","raspberry-pi","sound-classification","tensorflow","tensorflow-models"],"latest_commit_sha":null,"homepage":"","language":"Python","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/GianlucaPaolocci.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":"2017-06-20T12:08:31.000Z","updated_at":"2024-06-02T02:39:53.000Z","dependencies_parsed_at":"2022-09-16T12:10:12.578Z","dependency_job_id":null,"html_url":"https://github.com/GianlucaPaolocci/Sound-classification-on-Raspberry-Pi-with-Tensorflow","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GianlucaPaolocci%2FSound-classification-on-Raspberry-Pi-with-Tensorflow","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GianlucaPaolocci%2FSound-classification-on-Raspberry-Pi-with-Tensorflow/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GianlucaPaolocci%2FSound-classification-on-Raspberry-Pi-with-Tensorflow/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GianlucaPaolocci%2FSound-classification-on-Raspberry-Pi-with-Tensorflow/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/GianlucaPaolocci","download_url":"https://codeload.github.com/GianlucaPaolocci/Sound-classification-on-Raspberry-Pi-with-Tensorflow/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247578544,"owners_count":20961270,"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-analysis","audio-signals","dataset","librosa","machine-learning","multilayer-perceptron-network","raspberry","raspberry-pi","sound-classification","tensorflow","tensorflow-models"],"created_at":"2024-08-01T15:05:45.445Z","updated_at":"2025-04-07T18:34:33.301Z","avatar_url":"https://github.com/GianlucaPaolocci.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"# SOUND CLASSIFICATION WITH TENSORFLOW ON RASPBERRY PI\n\n![alt text](https://raw.githubusercontent.com/GianlucaPaolocci/Sound-classification-on-Raspberry-Pi-with-Tensorflow/master/img/Immagine.png)\n\n#  BUILD THE PROJECT\n\n  The project is developed and tested with Python 2.7.\n\n  Install following Python libraries on your PC/Workstation and Raspberry Pi:\n  \n    Tensorflow, Scikit-learn, Librosa\n  \n  Install following library on your Raspberry only:\n  \n    Sounddevice\n  \n\n1. **DOWNLOAD UrbanSound8K DATASET**\n\n  https://serv.cusp.nyu.edu/projects/urbansounddataset/urbansound8k.html\n\n2. **TRAIN THE MODEL**\n\n  Set the right path where you downloaded the dataset in your code.\n\n  Set the right path where you want to save the trained model.\n\n  Run \"trainModel.py\" on your PC/Workstation.\n\n3. **RUN THE MODEL**\n\n  Export the trained model on you Raspberry Pi ('model.meta', 'model.index', 'checkpoint', 'model.data-00000-of-00001').\n  \n  Export 'fit_params.npy' on your Raspberry Pi.\n\n  Run \"classiPi.py\" on your Raspberry and enjoy!\n\n# REMEMBER TO\n\n  Remember to reference this project in your works.\n\n# AUTHORS\n \n  Gianluca Paolocci, University of Naples Parthenope, Science and Techonlogies Departement, Ms.c Applied Computer Science\n  https://www.linkedin.com/in/gianluca-paolocci-a19678b6/\n  \n  Luigi Russo, University of Naples Parthenope, Science and Techonlogies Departement, Ms.c Applied Computer Science\n  \n# CONTACTS\n\n  if you have problems, questions, ideas or suggestions, please contact me to:\n  - **gianluca.paolocci@studenti.uniparthenope.it**\n  \n \u003ca href=\"http://www.reliablecounter.com\" target=\"_blank\"\u003e\u003cimg src=\"http://www.reliablecounter.com/count.php?page=https://github.com/GianlucaPaolocci/Sound-classification-on-Raspberry-Pi-with-Tensorflow\u0026digit=style/plain/29/\u0026reloads=1\" alt=\"\" title=\"\" border=\"0\"\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"http://\" target=\"_blank\" style=\"font-family: Geneva, Arial; font-size: 9px; color: #330010; text-decoration: none;\"\u003e\u003c/a\u003e\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FGianlucaPaolocci%2FSound-classification-on-Raspberry-Pi-with-Tensorflow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FGianlucaPaolocci%2FSound-classification-on-Raspberry-Pi-with-Tensorflow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FGianlucaPaolocci%2FSound-classification-on-Raspberry-Pi-with-Tensorflow/lists"}