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--- |
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library_name: PyLaia |
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license: mit |
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tags: |
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- PyLaia |
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- PyTorch |
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- atr |
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- htr |
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- ocr |
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- historical |
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- handwritten |
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metrics: |
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- CER |
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- WER |
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language: |
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- fr |
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base_model: Teklia/pylaia-norhand-v3 |
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datasets: |
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- Teklia/PELLET-Casimir-Marius-line |
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pipeline_tag: image-to-text |
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--- |
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# PyLaia - PELLET Casimir Marius |
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This model performs Handwritten Text Recognition in French. Trained following [Teklia's tutorial](https://doc.arkindex.org/tutorial/). |
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## Model description |
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The model has been trained using the PyLaia library on the [PELLET Casimir Marius - Line level](https://huggingface.co/datasets/Teklia/PELLET-Casimir-Marius-line) dataset. |
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Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio. |
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| set | lines | |
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| :---- | ----: | |
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| train | 842 | |
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| val | 125 | |
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| test | 122 | |
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## Evaluation results |
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The model achieves the following results: |
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| set | CER (%) | WER (%) | text_line | |
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| :---- | ------: | ------: | --------: | |
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| train | 24.17 | 58.12 | 842 | |
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| val | 22.90 | 58.75 | 125 | |
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| test | 18.78 | 50.00 | 122 | |
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## How to use? |
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Please refer to the [PyLaia documentation](https://atr.pages.teklia.com/pylaia/usage/prediction/) to use this model. |
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## Cite us! |
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```bibtex |
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@inproceedings{pylaia2024, |
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author = {Tarride, Solène and Schneider, Yoann and Generali-Lince, Marie and Boillet, Mélodie and Abadie, Bastien and Kermorvant, Christopher}, |
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title = {{Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library}}, |
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booktitle = {Document Analysis and Recognition - ICDAR 2024}, |
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year = {2024}, |
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publisher = {Springer Nature Switzerland}, |
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address = {Cham}, |
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pages = {387--404}, |
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isbn = {978-3-031-70549-6} |
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} |
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``` |
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<style> |
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table { |
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width: 50%; |
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} |
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</style> |
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