metadata

library_name: PyLaia
license: mit
tags:
  - PyLaia
  - PyTorch
  - atr
  - htr
  - ocr
  - historical
  - handwritten
metrics:
  - CER
  - WER
language:
  - la
  - fr
datasets:
  - Teklia/Alcar
pipeline_tag: image-to-text

PyLaia - HOME-Alcar

This model performs Handwritten Text Recognition in Latin 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 HOME Alcar training set.

Evaluation results

The model achieves the following results:

set	Language model	CER (%)	WER (%)	N lines
test	no	8.35	26.15	6,932
test	yes	7.85	23.20	6,932

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"
}