Datasets:
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---
dataset_info:
features:
- name: image
dtype: image
- name: unique_id
dtype: string
- name: text
dtype: string
- name: text_line_id
dtype: string
- name: raw_text
dtype: string
- name: text_transform
dtype: string
- name: font_path
dtype: string
- name: font_size
dtype: int64
- name: text_color
dtype: string
- name: background_color
dtype: string
- name: top_margin
dtype: int64
- name: bottom_margin
dtype: int64
- name: left_margin
dtype: int64
- name: right_margin
dtype: int64
- name: bbox_left
dtype: int64
- name: bbox_top
dtype: int64
- name: bbox_right
dtype: int64
- name: bbox_bottom
dtype: int64
- name: image_width
dtype: int64
- name: image_height
dtype: int64
- name: undistorted_file_name
dtype: string
- name: augraphy_log_path
dtype: string
- name: distorted_bbox_left
dtype: float64
- name: distorted_bbox_top
dtype: float64
- name: distorted_bbox_right
dtype: float64
- name: distorted_bbox_bottom
dtype: float64
- name: language_code
dtype: string
splits:
- name: train
num_bytes: 10298088981.391
num_examples: 307387
- name: validation
num_bytes: 1353982194.08
num_examples: 40765
- name: test
num_bytes: 2455873836.834
num_examples: 84534
download_size: 13836005253
dataset_size: 14107945012.305
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
license: cc-by-3.0
task_categories:
- image-to-text
tags:
- OCR
- ATR
- Sámi
- synthetic
pretty_name: Synthetic OCR data for North, South, Lule and Inari Sámi
size_categories:
- 100K<n<1M
language:
- sma
- sme
- smj
- smn
- smi
- se
---
# Synthetic text images for North, South, Lule and Inari Sámi
This dataset contains synthetic line images meant for fitting OCR models for North, South, Lule and Inari Sámi.
Clean line images are created using Pillow and they are subsequently distorted using Augraphy [[1]].
## Text sources
The text in this dataset comes from [Giellatekno]'s corpus. Specifically, we used the data files of the `converted/`-directories of [[2]][[3]][[4]][[5]] (commit hashes `32f4af263cefae6ab9182638e2451ff151757adc`, `00dac0e9e74b4a89214ad7d34de27b83362b3f3a`, `4303edf80ae5eee2a036663c7b38756a0aa2a189`, `7e3437ce8c7dc7692ccbd2505412c03e9e617be6`).
## Splits
The dataset is split randomly by file so 71 % of the files (307387 lines) are in the training split, 9 % of the files (40765 lines) are in the validation split and 20 % of the files (84534 lines) are in the test split.
Each split has a unique set of typefaces and text/background colors.
## Language distribution
The language distribution for the different languages are
| Language Code | Num train lines | Num val lines | Num test lines |
|---------------|-----------------------|---------------------|----------------------|
| sma | 76971 | 10992 | 21981 |
| sme | 76949 | 10992 | 21990 |
| smj | 76970 | 9081 | 20465 |
| smn | 76497 | 9700 | 20098 |
## Code
The code to create this dataset is available on our [GitHub Repo] (commit hash `90341bc19d6368c7848dcc2459065058486a89ea`).
## Referencing the dataset
If you use this dataset in your research, then please cite both
"Enstad T, Trosterud T, Røsok MI, Beyer Y, Roald M. Comparative analysis of optical character recognition methods for Sámi texts from the National Library of Norway. Accepted for publication in Proceedings of the 25th Nordic Conference on Computational Linguistics (NoDaLiDa) 2025."
(see the [paper repository]) and the SIKOR dataset the Sámi text is from:
"SIKOR UiT The Arctic University of Norway and the Norwegian Saami Parliament's Saami text collection, http://gtweb.uit.no/korp, Version 01.12.2021 [Data set]."
Also note that the SIKOR dataset to get Sámi text for the images is (CC-BY 3.0) licensed.
## Dataset license
The dataset is licensed with a CC-BY 3.0 license.
[1]: https://github.com/sparkfish/augraphy
[2]: https://github.com/giellalt/corpus-sma
[3]: https://github.com/giellalt/corpus-sme
[4]: https://github.com/giellalt/corpus-smj
[5]: https://github.com/giellalt/corpus-smn
[Giellatekno]: https://giellatekno.uit.no/
[GitHub Repo]: https://github.com/Sprakbanken/synthetic_text_images
[paper repository]: https://github.com/Sprakbanken/nodalida25_sami_ocr |