Datasets:
File size: 2,646 Bytes
d341e83 15212df d341e83 2c095d4 d341e83 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 | ---
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
<!-- Provide a quick summary of the dataset. -->
The Synthdog dataset created for training in [Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model](https://gregor-ge.github.io/Centurio/).
Using the [official Synthdog code](https://github.com/clovaai/donut/tree/master/synthdog), 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 `cat images.tar.gz.* | tar xvzf -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
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**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},
}
``` |