# Tools for working with Optical Music Recognition datasets
[](https://travis-ci.org/apacha/OMR-Datasets) [](https://codecov.io/gh/apacha/OMR-Datasets) [](https://badge.fury.io/py/omrdatasettools) [](http://omr-datasets.readthedocs.io/en/latest/?badge=latest) [](https://raw.githubusercontent.com/apacha/OMR-Datasets/master/LICENSE.txt)
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.
## Development setup
Create virtual environment running
```bash
python3.11 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```
## Running tests
Changelog
=========
1.4.0
-----
Adding several new datasets, upgrading to Python 3.11, and refactoring downloader to use Pathlib and support tar-gz.
1.3.1
-----
Bugfixing an error that generates incorrect MUSCIMA++ image masks because
images were incorrectly associated with each other.
1.3.0
-----
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.
1.2.2
-----
Fixed incorrect import statement in `__init__.py`
1.2.1
-----
Fixed dependency problem during `setup.py` that prevented the package from being
installed if the dependent libraries are not yet installed (which defeats
the purpose of declaring dependencies in setup.py).
Changing to semantic versioning with three numbers.
1.2 is now considered 1.2.0.
1.2
---
Attempting to declare dependencies in `setup.py` properly
1.1
---
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.
1.0
---
Dramatically simplified the tools for downloading datasets.
Removed mostly unused code and re-organized project structure and documentation.
0.19
----
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.
0.18
----
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](https://github.com/apacha/OMR-Datasets/releases)
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"description": "# Tools for working with Optical Music Recognition datasets\n\n[](https://travis-ci.org/apacha/OMR-Datasets) [](https://codecov.io/gh/apacha/OMR-Datasets) [](https://badge.fury.io/py/omrdatasettools) [](http://omr-datasets.readthedocs.io/en/latest/?badge=latest) [](https://raw.githubusercontent.com/apacha/OMR-Datasets/master/LICENSE.txt) \n\nA collection of tools that simplify the downloading and handling of datasets used for Optical Music Recognition (OMR).\nThese tools are available as Python package ``omrdatasettools`` on PyPi.\n\nThey simplify the most common tasks such as downloading and extracting a dataset, \ngenerating images from textual representations or visualizing those datasets. \n\n## Development setup\nCreate virtual environment running\n\n```bash\npython3.11 -m venv venv\nsource venv/bin/activate\npip install -r requirements.txt\n```\n\n## Running tests\n\nChangelog\n=========\n1.4.0\n-----\nAdding several new datasets, upgrading to Python 3.11, and refactoring downloader to use Pathlib and support tar-gz.\n\n1.3.1\n-----\nBugfixing an error that generates incorrect MUSCIMA++ image masks because \nimages were incorrectly associated with each other.\n\n1.3.0\n-----\nAdded download capabilities of DeepScores V1 with extended vocabulary and\nopened the downloader, so you can download custom datasets, as well as utilize\nother methods from it that were previously private.\n\n1.2.2\n-----\nFixed incorrect import statement in `__init__.py`\n\n1.2.1\n-----\nFixed dependency problem during `setup.py` that prevented the package from being \ninstalled if the dependent libraries are not yet installed (which defeats\nthe purpose of declaring dependencies in setup.py).\nChanging to semantic versioning with three numbers. \n1.2 is now considered 1.2.0.\n\n1.2\n---\nAttempting to declare dependencies in `setup.py` properly\n\n1.1\n---\nUpdated MuscimaPlusPlusSymbolImageGenerator to work with MUSCIMA++ 2.0.\nAdded quality-of-life improvement suggested by @yvan674 to make importing \ncommon classes such as the downloader easier.\n\n\n1.0\n---\nDramatically simplified the tools for downloading datasets. \nRemoved mostly unused code and re-organized project structure and documentation.\n\n0.19\n----\nNew Image generator that can take MUSCIMA++ v2.0 images and \ngenerate masks for instance segmentation of staffs, as well as\nmasks for semantic segmentation for all objects.\n\n0.18\n----\nChanging MUSCIMA++ Downloader to accept a string instead of integer for enabling\nfuture versioning of the dataset beyond integers, e.g., \"2.1\".\n\nPrevious releases\n-----------------\nFor information on previous releases, check out the [Github Repository](https://github.com/apacha/OMR-Datasets/releases)\n",
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