pylaia-norhand-v2 / README.md
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metadata
library_name: PyLaia
license: mit
tags:
  - PyLaia
  - PyTorch
  - atr
  - htr
  - ocr
  - historical
  - handwritten
metrics:
  - CER
  - WER
language:
  - 'no'
datasets:
  - Teklia/NorHand_v2
pipeline_tag: image-to-text

PyLaia - NorHand v2

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

Model description

The model was trained using the PyLaia library on the NorHand v2 dataset.

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

set lines horizontal lines
train 146,693 145,061
val 15,119 14,980
test 1,830 1,793

An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the NorHand v2 training set.

Evaluation results

The model achieves the following results:

set Language model CER (%) WER (%) lines
test no 3.82 12.00 1,573
test yes 3.13 9.29 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}
}