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---
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- Handwritten text recognition
metrics:
- CER
- WER
language:
- 'fr'
datasets:
- Teklia/Belfort
---
# Belfort handwritten text recognition
This model performs Handwritten Text Recognition in French on historical documents.
## Model description
The model was trained using the PyLaia library on the [Belfort dataset](https://zenodo.org/records/8041668).
For training, text-lines were resized with a fixed height of 128 pixels, keeping the original aspect ratio. Vertical lines are discarded.
| split | N lines |
| ----- | ------: |
| train | 25,800 |
| val | 3,102 |
| test | 3,819 |
An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the Belfort training set.
## Evaluation results
The model achieves the following results:
| set | Language model | CER (%) | WER (%) | N lines |
|:------|:---------------|:----------:|:-------:|----------:|
| test | no | 10.54 | 28.12 | 3,819 |
| test | yes | 9.52 | 23.73 | 3,819 |
## 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"
}
```
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