metadata
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- atr
- htr
- ocr
- historical
- printed
metrics:
- CER
- WER
language:
- de
datasets:
- Teklia/NewsEyeAustrian
pipeline_tag: image-to-text
PyLaia - NewsEye Austrian
This model performs Handwritten Text Recognition in Austrian German.
Model description
The model has been trained using the PyLaia library on the NewsEye / READ OCR training dataset from Austrian Newspapers (19th C.) dataset.
Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
set | lines |
---|---|
train | 52,834 |
val | 4,667 |
An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the NewsEye training set.
Evaluation results
The model achieves the following results:
set | Language model | CER (%) | WER (%) | lines |
---|---|---|---|---|
val | no | 1.82 | 7.77 | 4,667 |
val | yes | 1.77 | 7.01 | 4,667 |
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}
}