metadata
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- atr
- htr
- ocr
- historical
- handwritten
metrics:
- CER
- WER
language:
- 'no'
datasets:
- Teklia/NorHand_v3
pipeline_tag: image-to-text
PyLaia - NorHand v3
This model performs Handwritten Text Recognition in Norwegian. It was developed during the HUGIN-MUNIN project.
Model description
The model has been trained using the PyLaia library on the NorHand v3 document images.
Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
split | N lines | N 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.
Evaluation results
The model achieves the following results:
set | Language model | CER (%) | WER (%) | N lines |
---|---|---|---|---|
test | no | 7.52 | 22.99 | 1,573 |
test | yes | 6.36 | 18.11 | 1,573 |
How to use
Please refer to the documentation.
Cite us
@inproceedings{pylaia-lib,
author = "Tarride, Solène and Schneider, Yoann and Generali, Marie and Boillet, Melodie and Abadie, Bastien and Kermorvant, Christopher",
title = "Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library",
booktitle = "Submitted at ICDAR2024",
year = "2024"
}