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PyLaia - CASIA-HWDB2

This model performs Handwritten Text Recognition in Chinese.

Model description

The model was trained using the PyLaia library on the CASIA-HWDB2 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"
}
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Dataset used to train Teklia/pylaia-casia-hwdb2

Collection including Teklia/pylaia-casia-hwdb2