Transform your music into visual experiences with dreamer. This Python tool analyzes audio files using advanced signal processing to generate synchronized video visualizations, creating dynamic animations that respond to your music's rhythm, frequency content, and energy.
Key Features: - Mel spectrogram analysis for frequency visualization - RMS energy tracking for dynamic animations - Real-time audio processing with librosa - Customizable visual effects and animations - Easy-to-use command line interface
- Audio Analysis
- Mel spectrogram generation for frequency visualization
- RMS energy tracking for amplitude analysis
- Real-time audio processing with librosa
- Visualization
- Dynamic video generation synchronized to music
- Customizable visual effects and animations
- High-quality MP4 output
- Easy Integration
- Simple command-line interface
- Python API for programmatic usage
- Flexible input format support
You can install dreamer using pip:
pip install harmonic-resonance-dreamerAfter installation, you can use the dreamer command to create a new project:
dreamerThe basic command to generate a visualization is:
dreamer <audio_file>Where <audio_file> is the path to your audio file (supports WAV format).
dreamer depends on the following Python packages:
- textual: Terminal user interface framework
- rich: Terminal formatting and styling
- jinja2: Template engine
- librosa: Audio processing library
- matplotlib: Plotting and visualization
- numpy: Numerical computing
Contributions are welcome! Please see our [GitHub issues](https://github.com/harmonic-resonance/dreamer/issues) for ways to contribute.
dreamer is licensed under the MIT License. See the LICENSE file for more details.