metadata
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- Handwritten text recognition
metrics:
- CER
language:
- zh
datasets:
- Teklia/CASIA
CASIA-HWDB2 handwritten text recognition
This model performs Handwritten Text Recognition in Chinese.
Model description
The model was trained using the PyLaia library on the CASIA-HWDB1 document images.
Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
| split | N lines |
|---|---|
| train | 33,425 |
| val | 8,325 |
| test | 10,449 |
An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the CASIA-HWDB2 training set.
Evaluation results
The model achieves the following results:
| set | Language model | CER (%) | N lines |
|---|---|---|---|
| test | no | 4.61 | 10,449 |
| test | yes | 1.53 | 10,449 |
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"
}