Professional-grade AI stem separation. Local. Unlimited. One-time payment.

StemLab is a powerful, local Windows application for separating audio tracks into individual stems (Vocals, Drums, Bass, Other). It leverages state-of-the-art AI models (Demucs and MDX-Net) to deliver studio-quality results without monthly subscriptions or cloud upload limits.

• 100% Offline & Local: No data leaves your machine. Privacy guaranteed.
• Unlimited Usage: No credits, no timers, no subscriptions.
• Advanced AI Models:
  • Hybrid Ensemble: Combines Demucs (for instrument separation) and MDX-Net (for ultra-clean vocals).
  • De-Reverb & De-Echo: Experimental post-processing to remove room ambiance.
• Multiple Stem Modes:
  • 2-Stem: Vocals / Instrumental
  • 4-Stem: Vocals, Drums, Bass, Other
  • 6-Stem: Vocals, Drums, Bass, Guitar, Piano, Other
  • Vocals Only (Ultra Clean): Specialized pipeline for the cleanest possible acapellas.
  • Instrumental / Karaoke: High-quality backing tracks.
• Professional Workflow:
  • Batch Processing: Drag & drop multiple files.
  • Format Support: Export as WAV (Lossless) or MP3 (320kbps).
  • GPU Acceleration: Auto-detects NVIDIA GPUs for faster processing. (Testing)
  • Smart Queue: Manage your jobs with progress bars and cancellation.

• OS: Windows 10 or 11 (64-bit)
• RAM: 8GB minimum (16GB recommended)
• GPU (Optional): NVIDIA GPU with 4GB+ VRAM for accelerated processing. (Runs on CPU if no GPU is found).
• Python: Python 3.10 (for building from source).

Purchase the ready-to-run StemLab.exe from Gumroad. (Instant download, no setup required).

If you want to modify the code or build it yourself, follow these steps:

1. Clone the Repository:

   git clone https://github.com/sunsetsacoustic/StemLab.git
   cd StemLab

2. Install Python 3.10: Ensure you have Python 3.10 installed and added to your PATH.

3. Run the Build Script: We provide a robust build script that handles virtual environment creation and dependency installation automatically.

   Double-click rebuild_cpu_robust.bat.

   This script will:

   • Create a local virtual environment (venv_cpu).
   • Install all required libraries (PyQt6, torch, demucs, audio-separator, etc.).
   • Package the application into a single .exe file using PyInstaller.

4. Run the App:

   • From Source: Double-click run_cpu.bat.
   • Compiled EXE: Check the dist folder for StemLab.exe.

• Demucs by Meta Research
• Audio Separator (MDX-Net implementation)
• PyQt6 for the User Interface

Built with ❤️ by Sunsets Acoustic