# uj-mastering-master A custom mastering toolkit that provides metrics to evaluate audio masterings through visual analysis. ## Current implementation ### Core features - **Audio Analysis**: Uses librosa to analyze audio files (MP3/WAV/FLAC support) - **Power Visualization**: Generates colorized power magnitude graphs over time - **Metadata Extraction**: Reads ID3 tags from MP3 files for better file identification - **Modular GUI Architecture**: Complete PyQt5 interface with drag-and-drop and file dialog support - **Font Management**: Comprehensive CJK-compatible font system with user-provided font support - **Threading & Logging**: Robust background processing with detailed logging system ### Technical stack - **Audio Processing**: librosa, numpy - **Visualization**: matplotlib with custom colormaps and embedded Qt widgets - **GUI Framework**: PyQt5 with modular widget architecture - **Metadata**: mutagen for audio tag reading - **Font Support**: Custom font loading system with CJK fallback ### Key components #### `main.py` - Complete GUI application with modular architecture - Drag-and-drop and file dialog support for audio files - Integrated font control system - Real-time analysis display and file management #### `analysis_results_manager.py` - Background threading for audio analysis - Results caching and management - Progress tracking and error handling #### `audio_visualization_widget.py` - Embedded matplotlib visualization with Qt integration - Real-time plot updates and status display #### `font_control_widget.py` & `font_manager.py` - Unified font control system with clustered interface - Auto-detection of custom fonts from `fonts/` directory - System font discovery and CJK compatibility - Auto-regeneration of plots when fonts change #### `master_core.py` - Defines the `AudioFile` class: librosa loading, rolling RMS power, BPM detection - No batch / CLI mode — all analysis is driven from `main.py` via `AnalysisResultsManager` ### Current analysis features - **RMS power analysis**: 10-second rolling window with 2-second hops - **Adaptive colour mapping**: Automatically adjusts scale based on detected headroom - High dynamic range: 0-0.6 scale for loud masters - Conservative mastering: 0-0.3 scale for quiet masters - **BPM detection**: Automatic tempo analysis - **Metadata display**: Artist and title from audio tags - **Real-time visualization**: Embedded matplotlib plots with font-aware rendering ### GUI features - **File management**: Drag-and-drop and file dialog for audio selection - **Font control**: Unified font selector with size control and plot regeneration - **Analysis display**: Real-time visualization with metadata panels - **Modular architecture**: Self-contained widgets for easy layout management ## Future development plans ### Short-term (urgent) 1. **Plot control widget cluster** - Move 'Refresh Plot' into dedicated plot/graph widget cluster - Add metric selection widget (choose which analysis to display) - Implement plot style controller (colormap, line vs bar, etc.) - Prepare foundation for mastering comparison features ### Short-term (not urgent) 1. **Enhanced metrics** - LUFS loudness measurement implementation - Dynamic range measurement (DR meter) - Peak-to-average ratio analysis - Frequency spectrum analysis 2. **Interactive plot features** - GUI-controllable plotting styles (colormap, visualization type) - Select axis ranges on the fly with automatic graph updates - Zoom/pan controls for detailed analysis - Export analysis results to CSV/JSON 3. **Advanced GUI controls** - Plot style customization interface - Real-time axis range selection (zooming in/out) - Interactive plot manipulation tools 4. **Better looking UI** - Graphical loading bar - Graphical logging text box ### Mid-to-long-term (very not urgent) 1. **Audio comparison system** - Reference vs. comparee audio file analysis - Side-by-side track comparison interface - A/B testing for mastering versions - Overlay visualization for comparative analysis 2. **Distribution & deployment** - Self-contained executable releases - Cross-platform packaging - Installer creation and distribution ### Future vision 1. **Advanced analysis tools** - Spectral centroid and bandwidth analysis - Stereo width measurements - Transient detection and analysis - Harmonic distortion detection 2. **Professional features** - EBU R128 compliance checking - Custom target curves - Professional reporting formats - Multi-format export capabilities 3. **VST plugin development** - Real-time analysis during mixing/mastering - Integration with DAWs - Live feedback during production ## Development notes ### Dependencies - librosa: Audio analysis and feature extraction - numpy: Numerical computations - matplotlib: Plotting and visualization - mutagen: Audio metadata extraction - PyQt5: GUI framework ### Architecture considerations - Current code mixes analysis and visualization - consider separation - File path handling needs improvement for cross-platform compatibility - Error handling should be enhanced for production use - Consider moving from PyQt5 to PyQt6 or PySide for better licensing ### Testing requirements - Unit tests for audio analysis functions - GUI component testing - File format compatibility testing - Performance testing with large audio files ## Usage ### Running the app ```bash uv sync # one-time, after cloning uv run ujm # launch the GUI ``` Optional flags (handled by `logger_setup.parse_log_args`): ```bash uv run ujm --log-level DEBUG # ERROR | WARN | INFO | DEBUG | TRACE uv run ujm --log-file # also write audio_analysis.log ``` The only entry point is `ujm` (defined in `pyproject.toml` as `ujm = "main:main"`). The previous `files.txt` batch mode and the `python master_core.py` workflow have been removed. ### Planned usage enhancements 1. Interactive plot manipulation and style customization 2. LUFS and advanced metric analysis 3. Audio file comparison features 4. Self-contained executable releases