Add comprehensive documentation and usage instructions
- Added CLAUDE.md with detailed project documentation and roadmap - Enhanced README.md with usage section for command line and GUI modes - Updated with Claude Code credit - Improved master_core.py with better song name handling and BPM display 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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# uj-mastering-master
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A custom mastering toolkit that provides metrics to evaluate audio masterings through visual analysis.
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## Current Implementation
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### Core Features
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- **Audio Analysis**: Uses librosa to analyze audio files (MP3/WAV support)
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- **Power Visualization**: Generates colorized power magnitude graphs over time
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- **Metadata Extraction**: Reads ID3 tags from MP3 files for better file identification
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- **GUI Foundation**: Basic PyQt5 drag-and-drop interface (work in progress)
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### Technical Stack
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- **Audio Processing**: librosa, numpy
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- **Visualization**: matplotlib with custom colormaps
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- **GUI Framework**: PyQt5 (drag-and-drop functionality)
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- **Metadata**: mutagen for MP3 tag reading
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### Key Components
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#### `master_core.py`
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- `AudioFile` class: Main audio processing class
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- Loads audio files and extracts basic metrics (max/avg amplitude, BPM)
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- `get_energy_levels_over_time()`: Calculates RMS power over rolling windows
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- `plot_energy_levels_over_time()`: Creates colorized power graphs with automatic headroom detection
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- `analyze_track_librosa()`: Legacy analysis function (dBFS calculations)
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- File processing from `files.txt` configuration
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#### `main.py`
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- PyQt5 drag-and-drop interface
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- Currently displays file paths but doesn't integrate with analysis functions
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- Placeholder for GUI integration
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#### `files.txt`
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- Configuration file listing audio files to analyze
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- Supports comments (`;` and `#` prefixed lines)
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- Currently contains various music file paths
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### Current Analysis Features
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- **RMS Power Analysis**: 10-second rolling window with 2-second hops
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- **Adaptive Color Mapping**: Automatically adjusts scale based on detected headroom
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- High dynamic range: 0-0.6 scale for loud masters
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- Conservative mastering: 0-0.3 scale for quiet masters
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- **BPM Detection**: Automatic tempo analysis
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- **Metadata Display**: Artist and title from ID3 tags
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### Known Issues
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- GUI integration incomplete (drag-drop doesn't trigger analysis)
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- MP3 tag reading temporarily disabled in some parts
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- No interactive features yet implemented
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## Future Development Plans
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### Short-term Goals
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1. **Complete GUI Integration**
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- Connect drag-drop functionality to analysis pipeline
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- Real-time graph display in GUI window
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- File browser for batch processing
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2. **Enhanced Metrics**
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- Dynamic range measurement (DR meter)
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- Peak-to-average ratio analysis
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- Frequency spectrum analysis
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- Loudness standards compliance (LUFS)
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3. **Interactive Features**
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- Zoom/pan on power graphs
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- Playback controls with visual cursor
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- Export analysis results to CSV/JSON
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### Medium-term Goals
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1. **Advanced Analysis Tools**
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- Spectral centroid and bandwidth analysis
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- Stereo width measurements
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- Transient detection and analysis
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- Harmonic distortion detection
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2. **Comparison Features**
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- Side-by-side track comparison
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- Reference track overlay
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- Mastering version A/B testing
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3. **Batch Processing**
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- Folder-based analysis
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- Automated report generation
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- Progress tracking for large collections
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### Long-term Vision
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1. **VST Plugin Development**
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- Real-time analysis during mixing/mastering
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- Integration with DAWs
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- Live feedback during production
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2. **Professional Features**
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- EBU R128 compliance checking
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- Custom target curves
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- Professional reporting formats
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- Multi-format export capabilities
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## Development Notes
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### Dependencies
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- librosa: Audio analysis and feature extraction
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- numpy: Numerical computations
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- matplotlib: Plotting and visualization
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- mutagen: Audio metadata extraction
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- PyQt5: GUI framework
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### Architecture Considerations
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- Current code mixes analysis and visualization - consider separation
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- File path handling needs improvement for cross-platform compatibility
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- Error handling should be enhanced for production use
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- Consider moving from PyQt5 to PyQt6 or PySide for better licensing
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### Testing Requirements
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- Unit tests for audio analysis functions
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- GUI component testing
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- File format compatibility testing
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- Performance testing with large audio files
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## Usage
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### Current Usage
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1. Add audio file paths to `files.txt`
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2. Run `python master_core.py` for batch analysis
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3. Run `python main.py` for GUI (incomplete)
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### Planned Usage
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1. Drag and drop audio files into GUI
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2. Real-time analysis with interactive graphs
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3. Export reports and comparisons
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4. VST plugin for DAW integration
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