Fast Music Remover: Lightweight Music and Noise Removal for Media

Fast Music Remover: Lightweight Music and Noise Removal for Media

Summary

Fast Music Remover is a C++ based, lightweight tool designed for efficient music and noise removal from YouTube and other internet media. It leverages DeepFilterNet for advanced audio enhancement, empowering users to take control of their media consumption. The project offers a modular, cross-platform solution with both a web UI and containerized deployment options.

Repository Info

Updated on February 24, 2026
View on GitHub

Tags

audio-processingmusic-removernoise-removaldeepfilternetC++media-toolsaudio-enhancementmachine-learning

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Introduction

Fast Music Remover is an innovative open-source project that provides a powerful, C++ based solution for removing background music and noise from various media sources, including YouTube videos. Utilizing the advanced capabilities of DeepFilterNet, it delivers high-quality audio enhancement, allowing users to focus on core content without distractions. The project aims to be efficient, modular, and cross-platform, offering a minimalistic web UI and containerized deployment for ease of use.

Installation

Getting started with Fast Music Remover is straightforward, with options for quick deployment via Docker or a more controlled manual setup.

Option 1: Quick Start with Docker

This is the recommended method for quickly testing Fast Music Remover.

  1. Pull the pre-built image:

    docker pull ghcr.io/omeryusufyagci/fast-music-remover:latest

  2. Run the container:

    docker run -p 8080:8080 ghcr.io/omeryusufyagci/fast-music-remover:latest

Alternatively, you can build the image locally using Docker Compose:

docker-compose up --build

Once the container is running, access the application at http://localhost:8080 in your web browser.

Option 2: Manual Installation

For those who prefer a manual setup or wish to contribute, follow these steps:

  1. Prerequisites: Ensure you have Python 3.9+, FFmpeg, CMake, nlohmann-json, and libsndfile installed on your system. Refer to the official GitHub repository for detailed installation commands for Ubuntu/Debian and macOS.

  2. Install Python Dependencies: Navigate to the project root and install required Python packages:

    pip install -r requirements.txt

  3. Compile the Media Processor:

    cd MediaProcessor
mkdir build
cd build
cmake ..
make

  4. Start the Backend Server: Navigate back to the project root and run the Flask backend:

    python3 app.py

    The server will be accessible at http://127.0.0.1:8080.

Examples

Fast Music Remover features a minimalistic UI to streamline access to its core features. You can see a screenshot of the user interface and a demo video showcasing its capabilities directly on the project's GitHub page.

Why Use It

Fast Music Remover offers several compelling reasons for its use:

  • High-Quality Audio Enhancement: Utilizes DeepFilterNet for superior music and noise removal, delivering cleaner audio.
  • Efficiency: Built with C++, ensuring fast and lightweight processing.
  • Cross-Platform Compatibility: Designed to run seamlessly across Linux, macOS, and Windows.
  • User Control: Empowers users to customize their media consumption by removing unwanted audio elements.
  • Easy Deployment: Offers convenient Docker images for quick setup and a user-friendly web interface.

Links