# spleeter

**Repository Path**: hnaxing/spleeter

## Basic Information

- **Project Name**: spleeter
- **Description**: 音轨分离软件 spleeter，只需输入一段命令就可以将音乐的人声和各种乐器声分离，支持 mp3、wav、ogg 等常见音频格式
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: https://www.oschina.net/p/spleeter
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 15
- **Created**: 2019-11-18
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<img src="https://github.com/deezer/spleeter/raw/master/images/spleeter_logo.png" height="80" />

[![CircleCI](https://circleci.com/gh/deezer/spleeter/tree/master.svg?style=shield)](https://circleci.com/gh/deezer/spleeter/tree/master) [![PyPI version](https://badge.fury.io/py/spleeter.svg)](https://badge.fury.io/py/spleeter) [![Conda](https://img.shields.io/conda/vn/conda-forge/spleeter)](https://anaconda.org/conda-forge/spleeter) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/spleeter) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deezer/spleeter/blob/master/spleeter.ipynb)

## About

**Spleeter** is the [Deezer](https://www.deezer.com/) source separation library with pretrained models
written in [Python](https://www.python.org/) and uses [Tensorflow](https://tensorflow.org/). It makes it easy
to train source separation model (assuming you have a dataset of isolated sources), and provides
already trained state of the art model for performing various flavour of separation :

* Vocals (singing voice) / accompaniment separation ([2 stems](https://github.com/deezer/spleeter/wiki/2.-Getting-started#using-2stems-model))
* Vocals / drums / bass / other separation ([4 stems](https://github.com/deezer/spleeter/wiki/2.-Getting-started#using-4stems-model))
* Vocals / drums / bass / piano / other separation ([5 stems](https://github.com/deezer/spleeter/wiki/2.-Getting-started#using-5stems-model))

2 stems and 4 stems models have state of the art performances on the [musdb](https://sigsep.github.io/datasets/musdb.html) dataset. **Spleeter** is also very fast as it can perform separation of audio files to 4 stems 100x faster than real-time when run on a GPU. 

We designed **Spleeter** so you can use it straight from [command line](https://github.com/deezer/spleeter/wiki/2.-Getting-started#usage)
as well as directly in your own development pipeline as a [Python library](https://github.com/deezer/spleeter/wiki/4.-API-Reference#separator). It can be installed with [Conda](https://github.com/deezer/spleeter/wiki/1.-Installation#using-conda),
with [pip](https://github.com/deezer/spleeter/wiki/1.-Installation#using-pip) or be used with
[Docker](https://github.com/deezer/spleeter/wiki/2.-Getting-started#using-docker-image).

## Quick start 

Want to try it out ? Just clone the repository and install a
[Conda](https://github.com/deezer/spleeter/wiki/1.-Installation#using-conda)
environment to start separating audio file as follows:

```bash
git clone https://github.com/Deezer/spleeter
conda env create -f spleeter/conda/spleeter-cpu.yaml
conda activate spleeter-cpu
spleeter separate -i spleeter/audio_example.mp3 -p spleeter:2stems -o output
```
You should get two separated audio files (`vocals.wav` and `accompaniment.wav`)
in the `output/audio_example` folder.

For a more detailed documentation, please check the [repository wiki](https://github.com/deezer/spleeter/wiki)

Want to try it out but don't want to install anything ? we've setup a [Google Colab](https://colab.research.google.com/github/deezer/spleeter/blob/master/spleeter.ipynb)

## Reference


- Deezer Research - Source Separation Engine Story - deezer.io blog post:
    * [English version](https://deezer.io/releasing-spleeter-deezer-r-d-source-separation-engine-2b88985e797e)
    * [Japanese version](http://dzr.fm/splitterjp)
- [Music Source Separation tool with pre-trained models / ISMIR2019 extended abstract](http://archives.ismir.net/ismir2019/latebreaking/000036.pdf)

If you use **Spleeter** in your work, please cite:

```BibTeX
@misc{spleeter2019,
  title={Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained Models},
  author={Romain Hennequin and Anis Khlif and Felix Voituret and Manuel Moussallam},
  howpublished={Late-Breaking/Demo ISMIR 2019},
  month={November},
  note={Deezer Research},
  year={2019}
}
```

## License
The code of **Spleeter** is MIT-licensed.

## Disclaimer
If you plan to use Spleeter on copyrighted material, make sure you get proper authorization from right owners beforehand.

## Note
This repository include a demo audio file `audio_example.mp3` which is an excerpt
from Slow Motion Dream by Steven M Bryant (c) copyright 2011 Licensed under a Creative
Commons Attribution (3.0) license. http://dig.ccmixter.org/files/stevieb357/34740
Ft: CSoul,Alex Beroza & Robert Siekawitch