https://github.com/brokenbyteofcode/rhythmengine
I'll try make a Rhythm engine for games obviously.
https://github.com/brokenbyteofcode/rhythmengine
Last synced: 12 months ago
JSON representation
I'll try make a Rhythm engine for games obviously.
- Host: GitHub
- URL: https://github.com/brokenbyteofcode/rhythmengine
- Owner: BrokenByteOfCode
- License: mit
- Created: 2025-01-25T11:47:53.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-25T11:55:39.000Z (over 1 year ago)
- Last Synced: 2025-06-29T18:51:08.516Z (about 1 year ago)
- Language: Python
- Size: 13.7 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# RhythmEngine 🎵
A Python library for audio rhythm analysis and click track generation. Detect beats in audio files and generate synchronized click tracks with dynamic volume levels.
## Features
- **Beat Detection**: Multi-processed analysis for accurate beat tracking
- **Click Track Generation**: Create dynamic click sounds that sync with detected beats
- **Audio Export**: Save processed audio with click tracks in standard formats
- **Customizable Parameters**: Adjust click sounds and analysis parameters
## Installation
### Requirements
- Python 3.8+
- FFmpeg (for audio file support)
### Dependencies
```bash
pip install librosa numpy pydub
```
### Recommended Installation
```bash
# Clone repository
git clone https://github.com/andriy8800555355/RhythmEngine.git
cd RhythmEngine
# Install requirements
pip install -r requirements.txt
```
## Usage
### Basic Example
```python
from RhythmEngine import RhythmEngine
# Initialize with audio file
engine = RhythmEngine("input_song.mp3")
# Generate click track
mixed_audio = engine.generate_click_track()
# Save output
engine.save_mixed_audio("output_with_clicks.wav")
# Get detected beats
beat_times = engine.get_beat_times()
print(f"Detected beats at: {beat_times}")
```
### Advanced Usage
```python
# Custom click sound parameters
engine.generate_click_track(
click_duration=0.1, # Click duration in seconds
freq1=1000, # Primary frequency (Hz)
freq2=1500 # Secondary frequency (Hz)
)
# Access raw audio data
original_audio = engine.y # Raw audio waveform
sample_rate = engine.sr # Sampling rate
mixed_audio = engine.mixed_audio # Processed audio with clicks
```
## API Documentation
### `RhythmEngine(audio_path: str)`
Main class for rhythm processing
**Parameters**:
- `audio_path`: Path to audio file (supports most common formats)
### Methods
#### `generate_click_track(click_duration=0.07, freq1=880, freq2=1320)`
Generate click track synchronized with detected beats
**Parameters**:
- `click_duration`: Duration of click sound in seconds (default: 0.07)
- `freq1`: Primary frequency component in Hz (default: 880)
- `freq2`: Secondary frequency component in Hz (default: 1320)
**Returns**:
- `np.ndarray`: Mixed audio waveform with click track
#### `save_mixed_audio(output_path: str)`
Save processed audio to file
**Parameters**:
- `output_path`: Output file path (format determined by extension)
#### `get_beat_times()`
Get detected beat times
**Returns**:
- `List[float]`: List of beat times in seconds
## Implementation Details
- **Multi-processing**: Uses parallel processing for faster beat detection
- **Dynamic Volume**: Click volume adapts to onset strength of original audio
- **Normalization**: Automatic peak normalization prevents clipping
- **Tempo Estimation**: Combines global tempo estimation with local beat tracking
## Supported Formats
Input: MP3, WAV, FLAC, OGG, AAC (any format supported by FFmpeg)
Output: WAV (other formats supported via Pydub)
## Acknowledgments
- Uses [librosa](https://librosa.org/) for audio analysis
- Audio processing with [pydub](https://github.com/jiaaro/pydub)
- Built with NumPy for efficient array operations
---
**Contributions welcome!** Please open an issue or PR for suggestions/bug reports.