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---
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- Handwritten text recognition
metrics:
- CER
- WER
language:
- fr
datasets:
- Teklia/Himanis
---
# Himanis handwritten text recognition
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](https://demo.arkindex.org/browse/5000e248-a624-4df1-8679-1b34679817ef?top_level=true&folder=true) (French)
* [HOME Alcar](https://demo.arkindex.org/browse/46b9b1f4-baeb-4342-a501-e2f15472a276?top_level=true&folder=true) (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](https://atr.pages.teklia.com/pylaia/).
## Cite us
```bibtex
@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"
}
``` |