Datasets:
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license: cc-by-4.0
task_categories:
- image-to-text
language:
- en
tags:
- music
- optical-music-recognition
- OMR
- MusicXML
- sheet-music
pretty_name: OpenScore String Quartets (OMR Evaluation)
size_categories:
- n<1K
dataset_info:
features:
- name: image_imslp
dtype: image
- name: image_mscore
dtype: image
- name: musicxml
dtype: string
- name: filename
dtype: string
splits:
- name: train
num_examples: 252
---
# OpenScore String Quartets (OMR Evaluation)
This dataset is derived from the [OpenScore String Quartets](https://github.com/OpenScore/StringQuartets) corpus (Gotham et al., 2023), a collection of string quartets by "long 19th century" composers. It is designed for evaluating Optical Music Recognition (OMR) systems.
We extract a subset of the OpenScore String Quartets that contains both scanned images of real scores and the corresponding MusicXML ground truth. We also render clean images from the MusicXML files using MuseScore. This gives two evaluation settings:
- **Camera** (`image_imslp`): scanned page images from [IMSLP](https://imslp.org/), reflecting real-world conditions (noise, aging, varying scan quality).
- **Rendered** (`image_mscore`): clean page images rendered from the ground-truth MusicXML via MuseScore.
## Dataset Structure
| Column | Type | Description |
|---|---|---|
| `image_imslp` | `Image` | Scanned page image from IMSLP (camera) |
| `image_mscore` | `Image` | Clean rendered page image from MuseScore |
| `musicxml` | `string` | Ground-truth MusicXML content |
| `filename` | `string` | Composition and page identifier |
The dataset contains **252** page-level examples.
## Usage
```python
from datasets import load_dataset
ds = load_dataset("guangyangmusic/OpenScore-StringQuartets", split="train")
# access an example
example = ds[0]
example["image_imslp"].show() # scanned image
example["image_mscore"].show() # rendered image
print(example["musicxml"][:200])
print(example["filename"])
```
## Source
The original OpenScore String Quartets corpus is available at [https://github.com/OpenScore/StringQuartets](https://github.com/OpenScore/StringQuartets) and on [MuseScore](https://musescore.com/openscore-string-quartets).
## License
The underlying [OpenScore String Quartets](https://github.com/OpenScore/StringQuartets) scores are in the public domain under [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/).
This repository is a **derived** resource (subset selection, IMSLP page images, MuseScore renders, aligned MusicXML strings, and packaging). We release it under [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/). You may share and adapt it if you give **appropriate credit**, including **this dataset** and the **original OpenScore corpus** (see citation below).
## Citation
If you use this dataset, please cite **both** this release (Legato evaluation subset) and the original OpenScore String Quartets corpus.
**This dataset / Legato paper:**
```bibtex
@misc{yang2025legatolargescaleendtoendgeneralizable,
title={LEGATO: Large-scale End-to-end Generalizable Approach to Typeset OMR},
author={Guang Yang and Victoria Ebert and Nazif Tamer and Brian Siyuan Zheng and Luiza Pozzobon and Noah A. Smith},
year={2025},
eprint={2506.19065},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2506.19065},
}
```
**Original OpenScore String Quartets corpus:**
```bibtex
@inproceedings{gotham_openscore_2023,
address = {Milan, Italy},
title = {The "{OpenScore} {String} {Quartet}" {Corpus}},
isbn = {9798400708336},
url = {https://dl.acm.org/doi/10.1145/3625135.3625155},
doi = {10.1145/3625135.3625155},
booktitle = {Proceedings of the 10th International Conference on Digital Libraries for Musicology},
publisher = {ACM},
author = {Gotham, Mark R. H. and Redbond, Maureen and Bower, Bruno and Jonas, Peter},
month = nov,
year = {2023},
pages = {49--57},
}
```
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