Smashcima
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10513440" target="_blank" >RIV/00216208:11320/25:10513440 - isvavai.cz</a>
Result on the web
<a href="http://hdl.handle.net/11234/1-5835" target="_blank" >http://hdl.handle.net/11234/1-5835</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Smashcima
Original language description
Smashcima is a library and framework for synthesizing images containing handwritten music for creating synthetic training data for OMR models. It is primarily intended to be used as part of optical music recognition workflows, esp. with domain adaptation in mind. The target user is therefore a machine-learning, document processing, library sciences, or computational musicology researcher with minimal skills in python programming. Smashcima brings a unique new capability for optical music recognition (OMR): synthesizing a near-realistic image of handwritten sheet music from just a MusicXML file. As opposed to notation editors, which work with a fixed set of fonts and a set of layout rules, it can adapt handwriting styles from existing OMR datasets to arbitrary music (beyond the music encoded in existing OMR datasets), and randomize layout to simulate the imprecisions of handwriting, while guaranteeing the semantic correctness of the output rendering. Crucially, the rendered image is provided also with
Czech name
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Czech description
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Classification
Type
R - Software
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/DH23P03OVV008" target="_blank" >DH23P03OVV008: OmniOMR - optical music recognition using machine learning for digital libraries</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Internal product ID
[http://hdl.handle.net/11234/1-5
Technical parameters
Výsledek volně dostupný na adrese http://hdl.handle.net/11234/1-5835.
Economical parameters
1000000
Owner IČO
00216208
Owner name
Univerzita Karlova