4012193
doi
10.5281/zenodo.4012193
oai:zenodo.org:4012193
Satyawan, Yvan Putra
ZHAW Datalab
Pacha, Alexander
TU Wien
Schmidhuber, Jürgen
The Swiss AI Lab IDSIA (USI & SUPSI)
Stadelmann, Thilo
ZHAW Datalab
DeepScoresV2
Tuggener, Lukas
ZHAW Datalab & USi
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Music Object Regognition
Deep Learning
Object Detection
OMR
DeepScores
Deep Scores
<p>The DeepScoresV2 Dataset for Music Object Detection contains digitally rendered images of written sheet music, together with the corresponding ground truth to fit various types of machine learning models. A total of 151 Million different instances of music symbols, belonging to 135 different classes are annotated. The total Dataset contains 255,385 Images. <strong>For most researches, the dense version, containing 1714 of the most diverse and interesting images, should suffice.</strong></p>
<p>The dataset contains ground in the form of:</p>
<ul>
<li>Non-oriented bounding boxes</li>
<li>Oriented bounding boxes</li>
<li>Semantic segmentation</li>
<li>Instance segmentation</li>
</ul>
<p>The accompaning paper <em>The DeepScoresV2 Dataset and Benchmark for Music Object Detection </em>published at ICPR2020 can be found here:</p>
<p><a href="https://digitalcollection.zhaw.ch/handle/11475/20647">https://digitalcollection.zhaw.ch/handle/11475/20647</a></p>
<p> </p>
<p>A toolkit for convenient loading and inspection of the data can be found here:</p>
<p><a href="https://github.com/yvan674/obb_anns">https://github.com/yvan674/obb_anns</a></p>
<p>Code to train baseline models can be found here:</p>
<p><a href="https://github.com/tuggeluk/mmdetection/tree/DSV2_Baseline_FasterRCNN">https://github.com/tuggeluk/mmdetection/tree/DSV2_Baseline_FasterRCNN</a></p>
<p><a href="https://github.com/tuggeluk/DeepWatershedDetection/tree/dwd_old">https://github.com/tuggeluk/DeepWatershedDetection/tree/dwd_old</a></p>
<p> </p>
<p> </p>
The authors are grateful for the support through Innosuisse grant No. 34301.1 IP-ICT "RealScore", EuropeanResearch Council Advanced Grant 742870, and the continued fruitful collaboration with ScorePad AG.
Zenodo
2020-09-02
info:eu-repo/semantics/other
4012192
2.0
1686150428.933354
80925561304
md5:a229b605e7bfc5d1ce019d1b86253cf2
https://zenodo.org/records/4012193/files/ds2_complete.tar.gz
741814529
md5:7237318e381e6e0848ec30eb82decb83
https://zenodo.org/records/4012193/files/ds2_dense.tar.gz
public
10.5281/zenodo.4012192
isVersionOf
doi