This repository combines the software contributions for open-unmix, a reference implementation for deep learning based music source separation.
We choose PyTorch to serve as a reference implementation for this submission due to its balance between simplicity and modularity. Furthermore, we already ported the core model to NNabla and plan to release a port for Tensorflow 2.0, once the framework is released. Note that the ports will not include pre-trained models as we cannot make sure the ports would yield identical results, thus leaving a single baseline model for researchers to compare with
Open-Unmix for Pytorch
musdb dataset parser
A python package to parse and process the MUSDB18 dataset, the largest open access dataset for music source separation.
- Code: musdb
- Status: released on pypi in version 0.3.1
museval objective evaluation
- Code: museval
- Status: released on pypi in version 0.3.0
norbert: wiener filter implementations
- Code: norbert
- Status: released on pypi in version 0.2.1
to create the paper locally
docker run -v $PWD:/data openbases/openbases-pdf pdf