metadata

license: apache-2.0
language:
  - multilingual
  - af
  - am
  - ar
  - as
  - azb
  - be
  - bg
  - bm
  - bn
  - bo
  - bs
  - ca
  - ceb
  - cs
  - cy
  - da
  - de
  - du
  - el
  - en
  - eo
  - es
  - et
  - eu
  - fa
  - fi
  - fr
  - ga
  - gd
  - gl
  - ha
  - hi
  - hr
  - ht
  - hu
  - id
  - ig
  - is
  - it
  - iw
  - ja
  - jv
  - ka
  - ki
  - kk
  - km
  - ko
  - la
  - lb
  - ln
  - lo
  - lt
  - lv
  - mi
  - mr
  - ms
  - mt
  - my
  - 'no'
  - oc
  - pa
  - pl
  - pt
  - qu
  - ro
  - ru
  - sa
  - sc
  - sd
  - sg
  - sk
  - sl
  - sm
  - so
  - sq
  - sr
  - ss
  - sv
  - sw
  - ta
  - te
  - th
  - ti
  - tl
  - tn
  - tpi
  - tr
  - ts
  - tw
  - uk
  - ur
  - uz
  - vi
  - war
  - wo
  - xh
  - yo
  - zh
  - zu
task_categories:
  - image-to-text
tags:
  - ocr
size_categories:
  - 1M<n<10M

Synthdog Multilingual

The Synthdog dataset created for training in Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model.

Using the official Synthdog code, we created >1 million training samples for improving OCR capabilities in Large Vision-Language Models.

Dataset Details

We provide the images for download in two .tar.gz files. Download and extract them in folders of the same name (so tar xvzf images.tar.gz -C images; tar xvzf images.tar.gz -C images_non_latin). The image path in the dataset expects images to be in those respective folders for unique identification.

Every language has the following amount of samples: 500,000 for English, 10,000 for non-Latin scripts, and 5,000 otherwise.

Text is taken from Wikipedia of the respective languages. Font is GoNotoKurrent-Regular.

Note: Right-to-left written scripts (Arabic, Hebrew, ...) are unfortunatly writte correctly right-to-left but also bottom-to-top. We were not able to fix this issue. However, empirical results in Centurio suggest that this data is still helpful for improving model performance.

Citation

BibTeX:

@article{centurio2025,
  author       = {Gregor Geigle and
                  Florian Schneider and
                  Carolin Holtermann and
                  Chris Biemann and
                  Radu Timofte and
                  Anne Lauscher and
                  Goran Glava\v{s}},
  title        = {Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model},
  journal      = {arXiv},
  volume       = {abs/2501.05122},
  year         = {2025},
  url          = {https://arxiv.org/abs/2501.05122},
  eprinttype    = {arXiv},
  eprint       = {2501.05122},
}