{"id":24699007,"url":"https://github.com/harmonicode/tunespy","last_synced_at":"2025-10-09T07:32:34.239Z","repository":{"id":269932812,"uuid":"908893417","full_name":"HarmoniCode/TuneSpy","owner":"HarmoniCode","description":"TuneSpy is a Python application that allows users to load audio files, generate spectrograms, extract MFCC features, and compare the loaded audio with a preprocessed database of songs to find the most similar match.","archived":false,"fork":false,"pushed_at":"2025-01-26T02:16:28.000Z","size":45425,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-01-26T03:21:57.815Z","etag":null,"topics":["audio-feature-extraction","audio-mixing","fingerprint","music-identification","python","qt5"],"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/HarmoniCode.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-12-27T08:20:13.000Z","updated_at":"2025-01-26T02:16:31.000Z","dependencies_parsed_at":null,"dependency_job_id":"02d42b89-91da-43c4-a1f5-5642a74723d7","html_url":"https://github.com/HarmoniCode/TuneSpy","commit_stats":null,"previous_names":["harmonicode/tunespy"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HarmoniCode%2FTuneSpy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HarmoniCode%2FTuneSpy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HarmoniCode%2FTuneSpy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HarmoniCode%2FTuneSpy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/HarmoniCode","download_url":"https://codeload.github.com/HarmoniCode/TuneSpy/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":235801794,"owners_count":19047126,"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-feature-extraction","audio-mixing","fingerprint","music-identification","python","qt5"],"created_at":"2025-01-27T04:35:06.932Z","updated_at":"2025-10-09T07:32:24.228Z","avatar_url":"https://github.com/HarmoniCode.png","language":"Python","readme":"\n# TuneSpy\n![Python](https://img.shields.io/badge/python-3.x-blue.svg)\n![License](https://img.shields.io/badge/license-MIT-green.svg)\n![Platform](https://img.shields.io/badge/platform-Windows%20%7C%20macOS%20%7C%20Linux-lightgrey.svg)\n\n![alt text](./Styles/image.png)\n\nTuneSpy shares similarities with the popular **Shazam** app, as both are designed to identify and match audio clips with songs from a database. While Shazam primarily focuses on real-time audio recognition using advanced fingerprinting algorithms optimized for mobile environments, TuneSpy is a desktop application aimed at exploring the core concepts of audio processing and music matching.\n\nTuneSpy is a Python application that allows users to load audio files, generate spectrograms, extract MFCC features, and compare the loaded audio with a preprocessed database of songs to find the most similar match.\n\n\n\n\n## Features\n\n- Load audio files in various formats (MP3, WAV, FLAC)\n- Generate spectrograms and save them as PNG images\n- Extract MFCC features and save them as JSON files\n- Hash spectrogram images using perceptual hashing\n- Compare loaded audio with a preprocessed database of songs\n- Display the most similar songs with similarity percentages\n- Mix two audio files with adjustable weights\n- Play and stop audio playback\n\n## Requirements\n\n- Python 3.x\n- Required Python packages (install using `pip`):\n  - `librosa`\n  - `numpy`\n  - `matplotlib`\n  - `imagehash`\n  - `Pillow`\n  - `PyQt5`\n  - `soundfile`\n  - `sounddevice`\n  - `scipy`\n  - `mutagen`\n\n## Installation\n\n1. Clone the repository:\n   ```sh\n   git clone https://github.com/HarmoniCode/TuneSpy.git\n   cd TuneSpy\n   ```\n\n2. Install the required Python packages:\n   ```sh\n   pip install -r requirements.txt\n   ```\n\n## Running the Application\n\n```sh\npython main.py\n```\n\n## License\n\nThis project is licensed under the MIT License. See the LICENSE file for details.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharmonicode%2Ftunespy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fharmonicode%2Ftunespy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharmonicode%2Ftunespy/lists"}