mung 1.2.1

Tools for the Music Notation Graph representation of music notation, used primarily for optical music recognition.

MuNG

The mung (Music Notation Graph) package implements a graph representation of music notation that is especially amenable to Optical Music Recognition (OMR). It was used for instance in the MUSCIMA++ dataset of music notation.

Requires Python >= 3.6 and was tested with Python 3.11.

Getting started

1. Install this package: pip install mung
2. Download the MUSCIMA++ dataset.
3. Run through the tutorial.

Fundamentally, the Music Notatation Graph is a very simple construct:

It stores the primitives that can be detected by a Music Object Detector as nodes and then store the relations between those nodes. But the devil is in the details. To better understand what kind of relations are useful and which kind of relations are stored for common western music notation, check out the annotator instruction from MUSCIMarker.

Dataset

The dataset itself is available for download here and due to its derived nature, licensed differently:

Introduction to MUSCIMA++ Video

Watch Jan give a 30 minute introduction into this dataset on YouTube, which explains many design decisions and thoughts that directly affected the creation of the MuNG format:

Changelog

This changelog does not refer to the older muscima package.

1.2.1

New release with adapted Mung Parser to support other dataset too (Musigraph and DoReMi).

1.2

New release with updated libraries and executed tests with Python 3.11

1.1

Performance improvements for loading image masks from RLE string.

1.0

First public release of mung package, which is equivalent to the muscima-package, but updated to comply with the version 2.0 of the MUSCIMA++ dataset.