metadata

library_name: PyLaia
license: mit
tags:
  - PyLaia
  - PyTorch
  - atr
  - htr
  - ocr
  - historical
  - handwritten
metrics:
  - CER
  - WER
language:
  - fr
base_model: Teklia/pylaia-norhand-v3
datasets:
  - Teklia/PELLET-Casimir-Marius-line
pipeline_tag: image-to-text

PyLaia - PELLET Casimir Marius

This model performs Handwritten Text Recognition in French. Trained following Teklia's tutorial.

Model description

The model has been trained using the PyLaia library on the PELLET Casimir Marius - Line level dataset.

Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.

set	lines
train	842
val	125
test	122

Evaluation results

The model achieves the following results:

set	CER (%)	WER (%)	text_line
train	24.17	58.12	842
val	22.90	58.75	125
test	18.78	50.00	122

How to use?

Please refer to the PyLaia documentation to use this model.

Cite us!

@inproceedings{pylaia2024,
    author = {Tarride, Solène and Schneider, Yoann and Generali-Lince, Marie and Boillet, Mélodie and Abadie, Bastien and Kermorvant, Christopher},
    title = {{Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library}},
    booktitle = {Document Analysis and Recognition - ICDAR 2024},
    year = {2024},
    publisher = {Springer Nature Switzerland},
    address = {Cham},
    pages = {387--404},
    isbn = {978-3-031-70549-6}
}