--- library_name: PyLaia license: mit tags: - PyLaia - PyTorch - atr - htr - ocr - historical - handwritten metrics: - CER - WER language: - 'fr' datasets: - Teklia/Belfort pipeline_tag: image-to-text --- # PyLaia - Belfort This model performs Handwritten Text Recognition in French on historical documents. ## Model description The model was trained using the PyLaia library on the [Belfort](https://zenodo.org/records/8041668) dataset. Training images were resized with a fixed height of {dimension} pixels, keeping the original aspect ratio. Vertical lines are discarded. | set | lines | | :----- | ------: | | train | 25,800 | | val | 3,102 | | test | 3,819 | An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the Belfort training set. ## Evaluation results The model achieves the following results: | set | Language model | CER (%) | WER (%) | lines | |:------|:---------------| ----------:| -------:|----------:| | test | no | 10.54 | 28.12 | 3,819 | | test | yes | 9.52 | 23.73 | 3,819 | ## How to use? Please refer to the [PyLaia documentation](https://atr.pages.teklia.com/pylaia/usage/prediction/) to use this model. ## Cite us! ```bibtex @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} } ``` ```bibtex @inproceedings{belfort-2023, author = {Tarride, Solène and Faine, Tristan and Boillet, Mélodie and Mouchère, Harold and Kermorvant, Christopher}, title = {Handwritten Text Recognition from Crowdsourced Annotations}, year = {2023}, isbn = {9798400708411}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3604951.3605517}, doi = {10.1145/3604951.3605517}, booktitle = {Proceedings of the 7th International Workshop on Historical Document Imaging and Processing}, pages = {1–6}, numpages = {6}, keywords = {Crowdsourcing, Handwritten Text Recognition, Historical Documents, Neural Networks, Text Aggregation}, series = {HIP '23} } ```