Musdb

Latest version: v0.4.2

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0.4.2

This releases fixes the ability to get musdb18 in a different sample rate. e.g `mus = musdb.DB(download=True, subsets="test", sample_rate=16000)` does now correctly resample the audio on-the-fly

0.4.1

Downloading the preview dataset from zenodo was too slow, so we switched to gh releases

0.4.0

* fix a problem that was producing a wrong train test split 60
* update to newest version of stempeg resulting in 20-30% faster loading times when using compressed mp4 files 64
* smaller code clean ups 66 67 68 71

Thanks to TE-StefanUhlich hagenw csukuangfj

0.3.1

This releases upgrades the `stempeg` dependency to 0.1.7 to [address a bug](https://github.com/faroit/stempeg/pull/21) that could occur when using the chunking functionality in musdb.

0.3.0

New musdb is released which addresses a few things related to when using musdb inside your deep learning framework.

New features

* `musdb.DB()` directly loads the list of tracks. No need to call `load_musdb_tracks`.
* iterating over the track is simplified since the `musdb.DB` object is iterable and supports indexing
* `musdb.tools` now has a tool to convert a stems dataset to wav (or flac) automatically.
* we now provide a predefined train/validation split to foster reproducible research.
* musdb now supports chunking of the audio (both via `stempeg` for stems and `soundfile` for wavs) to efficiently load only parts of the audio
* A 7 seconds preview version of the musdb18 dataset is automatically downloaded and can be used on the fly. (this is fun for jupyter/colab!).

Incompatible changes

* support for python 2.7 was dropped
* `musdb.run` was removed since it was not used a lot and people used their own methods to do multiprocessing over different tracks.

0.2.3

Addressing 10

Thanks to f90

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