⚠️ Spleeter 2.1.0 release introduces some breaking changes, including new CLI option naming for input, and the drop of dedicated GPU package. Please read CHANGELOG for more details.
Spleeter is Deezer source separation library with pretrained models written in Python and uses Tensorflow. 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)
- Vocals / drums / bass / other separation (4 stems)
- Vocals / drums / bass / piano / other separation (5 stems)
2 stems and 4 stems models have high performances on the musdb 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 as well as directly in your own development pipeline as a Python library. It can be installed with pip or be used with Docker.
Device MacBook Air (M1, 2020)
Operating System MacOS 12.6
Python 3.9.0
Anaconda 22.11.1
FFMPEG 5.1.2
libsndfile 2.1.0
install dependencies
brew install ffmpeg libsndfile
conda create -n py39 python=3.9
conda activate py39
conda install -c apple tensorflow-deps==2.9.0
clone
git clone --depth 1 --branch tf_2.9_m1 https://github.com/tracyart/spleeter.git
install spleeter from local file
python -m pip install ./spleeter
check spleeter version
spleeter --version
Spleeter Version: 2.3.2
pretrained model download page
dir
pretrained_model/2stems
pretrained_model/4stems
pretrained_model/5stems