| library_name: PyLaia | |
| license: mit | |
| tags: | |
| - PyLaia | |
| - PyTorch | |
| - Handwritten text recognition | |
| metrics: | |
| - CER | |
| - WER | |
| language: | |
| - 'fr' | |
| # POPP handwritten text recognition | |
| This model performs Handwritten Text Recognition on French census documents. | |
| ## Model description | |
| The model was trained using the PyLaia library on the [POPP generic](https://github.com/Shulk97/POPP-datasets/). | |
| For training, text-lines were resized with a fixed height of 128 pixels, keeping the original aspect ratio. | |
| 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](https://atr.pages.teklia.com/pylaia/). | |