Rend

A simple Windows GUI for AI Music Stem Separation (Demucs) built with CustomTkinter.

Features

• Offline CPU Execution: Uses demucs (htdemucs) for processing without requiring a GPU or internet connection for inference (after model download).
• Model Selection: Choose between htdemucs (Default) and mdx (Extra) models.
• High Quality Mode: Enable shifts=2 for better separation quality (processed slightly slower).
• Karaoke Mode: Automatic 2-stem output merging stems into 'Vocals' vs 'Backing'.
• WAV Export: Saves separated stems directly as WAV files using soundfile.
• Dark Mode GUI: Clean and modern interface powered by customtkinter.
• Threaded Processing: Keeps the UI responsive during separation.

Installation

Prerequisites

• Python 3.10+
• FFmpeg: ffmpeg.exe and ffprobe.exe must be present in the root directory.

Setup

1. Clone the repository:

   git clone https://github.com/DQ-Labs/Rend.git
   cd Rend

2. Create and activate a virtual environment:

   python -m venv venv
   .\venv\Scripts\activate

3. Install dependencies using the automated setup script:

   .\setup_dev.ps1

   This script patches the local Demucs copy for Windows compatibility and installs all requirements.

Usage

Run the application:

python app.py

• Select an input audio file.
• The stems will be saved in the output directory (default: separated/ or similar relative path).

Architecture

• Local Demucs Source: The project relies on a local copy of the demucs library located in the demucs_source folder. This requires an editable install (pip install -e .) to function correctly with custom modifications.
• Dependency Management: Critical dependencies like torch and soundfile must be compatible with the system Python version (Python 3.11/3.12 recommended).

Building from Source

To create a standalone EXE file using PyInstaller:

1. Requirements:

   • Ensure ffmpeg.exe and ffprobe.exe are in the root directory.
   • Activate your virtual environment.

2. Build Command: Run the following command to build the executable using the pre-configured spec file:

   pyinstaller Rend.spec --clean --noconfirm

   Make sure to run this via your virtual environment's Python (e.g., .\venv\Scripts\python.exe -m PyInstaller ...) if you have multiple Python versions installed.

   The Rend.spec file is configured to:

   • Include demucs_source in the path and data bundle.
   • Bundle ffmpeg.exe and ffprobe.exe binaries.
   • Handle hidden imports for demucs and soundfile.
   • Create a single-file executable (dist/Rend.exe).

Known Behavior

• Launch Time: The final .exe takes approximately 30 seconds to launch. This is normal behavior for a PyInstaller "one-file" build as it unpacks temporary files to a runtime directory.
• First Run: On the very first separation, the application will automatically download the necessary AI models. This requires an internet connection and may take some time depending on your speed. Subsequent runs will be offline.
• Troubleshooting: If you previously encountered NumPy errors during packaging, these have been addressed in the latest build spec (v1.1+).