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PyLaia - POPP

This model performs Handwritten Text Recognition on French census documents.

Model description

The model was trained using the PyLaia library on the POPP generic.

For training, text-lines were resized with a fixed height of 128 pixels, keeping the original aspect ratio.

split N lines
train 3,835
val 480
test 479

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

Evaluation results

The model achieves the following results:

set Language model CER (%) WER (%) N lines
test no 16.49 36.26 479
test yes 16.09 34.52 479

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-popp

Collection including Teklia/pylaia-popp