PyLaia
Collection
The PyLaia collection contains models designed for Automatic Text Recognition (ATR) from line images.
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15 items
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Updated
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3
This model performs Handwritten Text Recognition in Norwegian. It was developed during the HUGIN-MUNIN project.
The model has been trained using the PyLaia library on the NorHand v3 dataset.
Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
set | lines | horizontal lines |
---|---|---|
train | 224,173 | 223,971 |
val | 22,828 | 22,811 |
test | 1,573 | 1,573 |
An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the NorHand v3 training set.
The model achieves the following results:
set | Language model | CER (%) | WER (%) | lines |
---|---|---|---|---|
test | no | 7.52 | 22.99 | 1,573 |
test | yes | 6.36 | 18.11 | 1,573 |
Please refer to the PyLaia documentation to use this model.
@inproceedings{pylaia2024,
author = {Tarride, Solène and Schneider, Yoann and Generali-Lince, Marie and Boillet, Mélodie and Abadie, Bastien and Kermorvant, Christopher},
title = {{Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library}},
booktitle = {Document Analysis and Recognition - ICDAR 2024},
year = {2024},
publisher = {Springer Nature Switzerland},
address = {Cham},
pages = {387--404},
isbn = {978-3-031-70549-6}
}