A music playlist generator that analyzes audio files to create mood and energy-based playlists using PyTorch machine learning.
This repository was re-created after being mistakenly pushed to the wrong GitHub account.
As a result, the full commit history from the original repository is not reflected here.
- Audio Analysis: Extract tempo, loudness, spectral centroid, and other audio features
- Mood Classification: Use PyTorch models to classify songs by mood and energy
- Pattern Recognition: Identify patterns across songs to form cohesive playlists
- Automatic Playlist Generation: Create playlists based on detected patterns and similarities
pip install -r requirements.txt├── src/
│ ├── audio_analysis/ # Core audio analysis functions
│ ├── feature_extraction/ # Feature extraction pipeline
│ ├── models/ # PyTorch models for classification
│ ├── playlist_gen/ # Playlist generation algorithms
│ └── data/ # Data management and metadata handling
├── tests/ # Unit tests
├── examples/ # Example usage scripts
└── requirements.txt # Python dependencies
from src.playlist_gen import PlaylistGenerator
# Initialize the generator
generator = PlaylistGenerator()
# Add songs to analyze
generator.add_songs("path/to/music/folder")
# Generate playlists
playlists = generator.generate_playlists()🚧 Under Development - Core audio analysis and ML model implementation in progress.