TuneSpy 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.
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.
- Load audio files in various formats (MP3, WAV, FLAC)
- Generate spectrograms and save them as PNG images
- Extract MFCC features and save them as JSON files
- Hash spectrogram images using perceptual hashing
- Compare loaded audio with a preprocessed database of songs
- Display the most similar songs with similarity percentages
- Mix two audio files with adjustable weights
- Play and stop audio playback
https://drive.google.com/file/d/1ryWmfJg-txpcvSwQyOTFaXqKX9mjTL75/view?usp=sharing
- Python 3.x
- Required Python packages (install using
pip):librosanumpymatplotlibimagehashPillowPyQt5soundfilesounddevicescipymutagen
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Clone the repository:
git clone https://github.com/HarmoniCode/TuneSpy.git cd TuneSpy -
Install the required Python packages:
pip install -r requirements.txt
python main.pyThis project is licensed under the MIT License. See the LICENSE file for details.