OmniPrint: A Configurable Printed Character Synthesizer - Laboratoire Interdisciplinaire des Sciences du Numérique Access content directly
Conference Papers Year : 2022

OmniPrint: A Configurable Printed Character Synthesizer

Abstract

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.
Fichier principal
Vignette du fichier
merged_file.pdf (3.52 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03506905 , version 1 (03-01-2022)

Identifiers

  • HAL Id : hal-03506905 , version 1

Cite

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⟩
145 View
107 Download

Share

Gmail Mastodon Facebook X LinkedIn More