huchukato/stemify-desktop

🎵 Stemify Desktop - The Audio Splitter

📝 Description

Stemify Desktop is a professional desktop application for AI-powered audio stem separation. Built with Facebook Research's Demucs model, it allows users to separate audio tracks into individual components (vocals, drums, bass, other) with high accuracy.

✨ Features

• 🖥️ Desktop Application - Native app for Windows, macOS, and Linux
• 🤖 AI-Powered Separation - Uses state-of-the-art Demucs AI model
• ⚡ Real-time Processing - Fast audio separation with progress tracking
• 🎵 Multiple Formats - Support for MP3 files up to 20MB
• 🎨 Professional UI - Modern interface with custom branding
• 📱 Offline Capability - Works without internet connection
• 🔄 Drag & Drop - Intuitive file upload interface

🚀 Downloads

Windows

• Stemify-1.0.0-win-universal.zip (93.1 MB) - Universal installer (x64 + x86 + ARM64)

macOS

• Stemify-1.0.0-macos-intel.dmg (119 MB) - Intel Mac (x64)
• Stemify-1.0.0-macos-arm64.dmg (114 MB) - Apple Silicon (ARM64)

Linux

• Stemify-1.0.0.AppImage (120 MB) - Intel/AMD (x64)
• Stemify-1.0.0-arm64.AppImage (121 MB) - ARM64

🎯 How to Use

1. Download the appropriate file for your operating system
2. Install the application following your OS instructions
3. Launch Stemify Desktop
4. Upload your audio file (drag & drop or click)
5. Wait for AI processing
6. Download your separated tracks

🛠️ Technical Details

Architecture

• Frontend: React + TypeScript + Vite
• Backend: Flask + Python
• Desktop: Electron wrapper
• AI Model: Facebook Research Demucs
• Audio Processing: Real-time stem separation

Supported Formats

• Input: MP3 files up to 20MB
• Output: 4 stems (Vocals, Drums, Bass, Other)
• Quality: High-fidelity separation

System Requirements

• Windows: Windows 10+ (ARM64)
• macOS: macOS 10.12+ (Apple Silicon)
• Linux: Modern Linux distribution (ARM64)
• Memory: 4GB RAM minimum
• Storage: 500MB free space

🧠 Model Information

Stemify uses the Demucs v4 model from Facebook Research, specifically trained for high-quality music source separation. The model has been trained on large datasets and can separate:

• 🎤 Vocals - Lead and backing vocals
• 🥁 Drums - Complete drum kit
• 🎸 Bass - Bass guitar and low-frequency elements
• 🎹 Other - Remaining instruments (guitar, piano, synths, etc.)

📊 Performance

• Processing Time: 2-5 minutes for typical 3-5 minute tracks
• Quality: Professional-grade separation
• Memory Usage: ~2GB during processing
• CPU Usage: Optimized for ARM64 processors

🔧 Build from Source

git clone https://github.com/huchukato/stemify-audio-splitter.git
cd stemify-audio-splitter/demucs-gui
npm install
npm run electron-build -- --mac --win --linux

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Facebook Research for the Demucs model
• Electron Team for the desktop framework
• React Community for the frontend library
• Python Audio Community for audio processing tools

� Author

• huchukato
  • 🐙 GitHub
  • 🐦 X (Twitter)
  • 🎨 Civitai - Check out my AI art models!

�📞 Support

• GitHub Issues: Report bugs
• Discussions: Community forum
• Email: Contact through GitHub profile

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Made with ❤️ by huchukato

Transform your music with AI-powered stem separation!