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Conference Papers Year : 2022

OmniPrint: A Configurable Printed Character Synthesizer


We introduce OmniPrint, a synthetic data generator of isolated printed characters, geared toward machine learning research. It draws inspiration from famous datasets such as MNIST, SVHN and Omniglot, but offers the capability of generating a wide variety of printed characters from various languages, fonts and styles, with customized distortions. We include 935 fonts from 27 scripts and many types of distortions. As a proof of concept, we show various use cases, including an example of meta-learning dataset designed for the upcoming MetaDL NeurIPS 2021 competition. OmniPrint is available at
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hal-03506905 , version 1 (03-01-2022)


  • HAL Id : hal-03506905 , version 1


Haozhe Sun, Wei-Wei Tu, Isabelle Guyon. OmniPrint: A Configurable Printed Character Synthesizer. Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1), Dec 2021, Online, France. ⟨hal-03506905⟩
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