This library provides tools for working with common MIR datasets, including tools for:
- downloading datasets to a common location and format
- validating that the files for a dataset are all present
- loading annotation files to a common format, consistent with the format required by mir_eval
- parsing track level metadata for detailed evaluations.
This libary was presented in our ISMIR 2019 paper
pip install mirdata
- ⭐ Table of supported datasets ⭐
- API documentation
- How do I add a new loader?
- How do I get access to a dataset if the download function says it’s not available?
- Can you send me the data for a dataset which is not available?
- How do I request a new dataset?
- What do I do if my data fails validation?
- How do you choose the data that is used to create the checksums?
- Does mirdata provide data loaders for pytorch/Tensorflow?
- Why didn’t you release a version of this library in MATLAB/C/Java/R?
- A download link is broken for a loader’s
.download()function. What do I do?
- Why the name, mirdata?
- If I find a mistake in an annotation, should I fix it in the loader?
- Does mirdata support data which lives off-disk?