metadata
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- atr
- htr
- ocr
- historical
- handwritten
metrics:
- CER
- WER
language:
- fr
datasets:
- Teklia/Himanis
pipeline_tag: image-to-text
PyLaia - Himanis
This model performs Handwritten Text Recognition in French on medieval documents.
Model description
The model was trained using the PyLaia library on two medieval datasets:
- Himanis (French)
- HOME Alcar (Latin)
For training, text-lines were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the Himanis training set.
Evaluation results
The model achieves the following results:
set | Language model | CER (%) | WER (%) | N lines |
---|---|---|---|---|
test | no | 9.87 | 29.25 | 2241 |
test | yes | 8.87 | 24.37 | 2241 |
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"
}