metadata

library_name: PyLaia
license: mit
tags:
  - PyLaia
  - PyTorch
  - atr
  - htr
  - ocr
  - historical
  - handwritten
metrics:
  - CER
  - WER
language:
  - 'no'
datasets:
  - Teklia/NorHand_v3
pipeline_tag: image-to-text

PyLaia - NorHand v3

This model performs Handwritten Text Recognition in Norwegian. It was developed during the HUGIN-MUNIN project.

Model description

The model has been trained using the PyLaia library on the NorHand v3 dataset.

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

set	lines	horizontal lines
train	224,173	223,971
val	22,828	22,811
test	1,573	1,573

An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the NorHand v3 training set.

Evaluation results

The model achieves the following results:

set	Language model	CER (%)	WER (%)	N lines
test	no	7.52	22.99	1,573
test	yes	6.36	18.11	1,573

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}
}