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OmniPrint: A Configurable Printed Character Synthesizer
Haozhe Sun · Wei-Wei Tu · Isabelle Guyon

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 https://github.com/SunHaozhe/OmniPrint.

Author Information

Haozhe Sun (Paris-Saclay University)
Wei-Wei Tu (4Paradigm Inc.)
Isabelle Guyon (UPSud, INRIA, University Paris-saclay and ChaLearn)

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