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A collection of tools that simplify the downloading and handling of datasets used for Optical Music Recognition (OMR).

Project description

Tools for working with Optical Music Recognition datasets

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A collection of tools that simplify the downloading and handling of datasets used for Optical Music Recognition (OMR). These tools are available as Python package omrdatasettools on PyPi.

They simplify the most common tasks such as downloading and extracting a dataset, generating images from textual representations or visualizing those datasets.



Bugfixing an error that generates incorrect MUSCIMA++ image masks because images were incorrectly associated with each other.


Added download capabilities of DeepScores V1 with extended vocabulary and opened the downloader, so you can download custom datasets, as well as utilize other methods from it that were previously private.


Fixed incorrect import statement in


Fixed dependency problem during that prevented the package from being installed if the dependent libraries are not yet installed (which defeats the purpose of declaring dependencies in Changing to semantic versioning with three numbers. 1.2 is now considered 1.2.0.


Attempting to declare dependencies in properly


Updated MuscimaPlusPlusSymbolImageGenerator to work with MUSCIMA++ 2.0. Added quality-of-life improvement suggested by @yvan674 to make importing common classes such as the downloader easier.


Dramatically simplified the tools for downloading datasets. Removed mostly unused code and re-organized project structure and documentation.


New Image generator that can take MUSCIMA++ v2.0 images and generate masks for instance segmentation of staffs, as well as masks for semantic segmentation for all objects.


Changing MUSCIMA++ Downloader to accept a string instead of integer for enabling future versioning of the dataset beyond integers, e.g., "2.1".

Previous releases

For information on previous releases, check out the Github Repository

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omrdatasettools-1.3.1.tar.gz (42.5 kB view hashes)

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