uj-mastering-master

Custom mastering toolkit providing comprehensive metrics to evaluate audio masterings through visual analysis.
Developed with Claude Code assistance.

Features

✅ Current Implementation

• Complete GUI Application: Modular PyQt5 interface with drag-and-drop and file dialog support
• Real-time Analysis: Background threading with embedded matplotlib visualization
• Font Management: CJK-compatible font system with custom font support from fonts/ directory
• Audio Support: MP3, WAV, and FLAC file analysis
• RMS Power Analysis: Rolling window analysis with adaptive color mapping
• Metadata Display: Automatic extraction and display of audio tags and BPM

🚧 In Development

• Plot Control Widgets: Dedicated cluster for plot manipulation and style controls
• LUFS Metrics: Professional loudness measurement implementation
• Interactive Plotting: Real-time axis control and style customization

🔮 Planned Features

• Audio Comparison: Reference vs. comparee analysis for mastering evaluation
• Advanced Metrics: Dynamic range, spectral analysis, and professional standards compliance
• Standalone Releases: Self-contained executable distribution

Dependencies

• Core: librosa, numpy, matplotlib, mutagen
• GUI: PyQt5
• Audio Processing: Advanced librosa-based analysis pipeline

Usage

GUI Application (Recommended)

python main.py

• Load Files: Use "Open Audio File..." button or drag-and-drop
• Font Control: Adjust interface fonts and regenerate plots automatically
• Analysis Display: View real-time RMS power analysis with metadata
• File Management: Switch between analyzed files using the file list

Command Line Analysis (Legacy)

# 1. Edit files.txt with your audio file paths
# 2. Run batch analysis
python master_core.py

Architecture

Modular Design

• Self-contained Widgets: Easy layout management and customization
• Background Processing: Non-blocking analysis with progress feedback
• Signal-based Communication: Clean separation between GUI and analysis logic

Key Components

• main.py: Complete GUI application with modular architecture
• font_control_widget.py: Unified font management with plot regeneration
• analysis_results_manager.py: Threaded analysis with caching
• audio_visualization_widget.py: Embedded matplotlib with Qt integration

Development Roadmap

🎯 Next Priority: Plot Control System

Moving from font-focused interface to comprehensive plot manipulation:

• Cluster plot controls (refresh, style, metric selection)
• Interactive axis range selection
• Real-time plot style customization
• Foundation for comparison features

🎵 Short-term Goals

• LUFS Implementation: Professional loudness standards
• Plot Interactivity: GUI-controlled visualization styles
• Metric Selection: Choose which analysis to display

🎼 Long-term Vision

• Mastering Comparison: Side-by-side analysis tools
• Professional Standards: EBU R128 compliance checking
• Standalone Distribution: Self-contained executable releases