Edit model card

PyLaia - IAM

This model performs Handwritten Text Recognition in English on modern documents.

Model description

The model was trained using the PyLaia library on the RWTH split of the IAM database.

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

split N lines
train 6,482
val 976
test 2,915

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

Evaluation results

The model achieves the following results:

set Language model CER (%) WER (%) N lines
test no 8.44 24.51 2,915
test yes 7.50 20.98 2,915

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"
}
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference API
Inference API (serverless) does not yet support PyLaia models for this pipeline type.

Dataset used to train Teklia/pylaia-iam

Collection including Teklia/pylaia-iam