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# MUSCIMA

The ``muscima`` (**Mu**sic **Sc**ore **Ima**ges) package implements a data model for the [MUSCIMA++](https://ufal.mff.cuni.cz/muscima)
dataset of music notation.

[![Build Status](https://travis-ci.org/hajicj/muscima.svg?branch=master)](https://travis-ci.org/hajicj/muscima)
[![PyPI version](https://badge.fury.io/py/muscima.svg)](https://badge.fury.io/py/muscima)
[![Documentation Status](https://readthedocs.org/projects/muscima/badge/?version=latest)](https://muscima.readthedocs.io/en/latest/index.html)
[![License: CC BY-NC-SA 4.0](https://img.shields.io/badge/License-MIT-brightgreen.svg)](LICENSE.txt)
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[![codecov](https://codecov.io/gh/hajicj/muscima/branch/master/graph/badge.svg)](https://codecov.io/gh/hajicj/muscima)

This package should work with both Python 2.7 and Python 3.6,
although the doctest-based test suite only works on Python 3.


## Getting started

1. Install this package: ``pip install muscima``
2. Download the [MUSCIMA++ dataset](https://lindat.mff.cuni.cz/repository/xmlui/handle/11372/LRT-2372).
3. Run through the [tutorial](https://muscima.readthedocs.io/en/latest/Tutorial.html#tutorial).



## Dataset
The dataset itself is available for download
[here](https://lindat.mff.cuni.cz/repository/xmlui/handle/11372/LRT-2372) and due to its derived nature, licensed differently:

[![abc](https://img.shields.io/badge/Dataset_Version-1.0-brightgreen.svg)](https://lindat.mff.cuni.cz/repository/xmlui/handle/11372/LRT-2372)
[![License: CC BY-NC-SA 4.0](https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-blue.svg)](https://creativecommons.org/licenses/by-nc-sa/4.0/)



Changelog
=========

(Note that there will be many small releases, as we attempt to always keep
the package up-to-date through pip.)

0.3.2
-----

* Added MANIFEST.in for easier distribution.

0.3.1
-----

* Fixing setup.py bugs with README.md and CHANGES.md file paths for long description.
* ``CropObject.join()`` now warns before exiting when the other CropObject
is from a different document.
* ``CropObject`` global namespace can now be set as well, through
``CropObject.set_dataset()``
* Updated README to describe the tests situation.


0.3.0
-----

First public release.

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