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StemSplitter: Audio Separation Server

StemSplitter is a powerful and efficient server designed for separating audio tracks into their individual components, such as vocals, drums, and instruments. Leveraging the capabilities of the Demucs deep learning model within a Flask-based framework, this server provides an API endpoint for processing audio files.

Features

  • Advanced Audio Separation: Utilizes the state-of-the-art Demucs model for accurate and efficient audio track separation.
  • Secure API: The server offers a secure API endpoint for uploading audio files and receiving the processed output.
  • Docker Integration: Containerized with Docker for easy setup, deployment, and scalability.
  • Customizable: Easy to modify and extend based on individual project requirements.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

What you need to install the software:

  • Docker
  • Python 3.8+
  • pip (Python package manager)

Installation

  1. Clone the Repository

    git clone https://github.com/jinoAlgon/StemSplitter-Audio-Separation-Server.git
cd StemSplitter

  2. Build and Run the Docker Container

    docker build -t audio-server .
docker run -p 5000:5000 audio-server

The server will start running on localhost at port 5000.

Usage

To separate an audio file into stems:

  1. Send a POST request to http://localhost:5000/separate with the audio file.
  2. Receive the processed file as a zip containing the separated tracks.

Example using curl:

curl -X POST -F "file=@path_to_your_audio_file.mp3" http://localhost:5000/separate -o separated.zip