---
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- Handwritten text recognition
metrics:
- CER
- WER
language:
- la
---

# HOME-Alcar handwritten text recognition

This model performs Handwritten Text Recognition in Latin on medieval documents.

## Model description

The model was trained using the PyLaia library on two medieval datasets:
* [Himanis](https://demo.arkindex.org/browse/5000e248-a624-4df1-8679-1b34679817ef?top_level=true&folder=true) (French)
* [HOME Alcar](https://demo.arkindex.org/browse/46b9b1f4-baeb-4342-a501-e2f15472a276?top_level=true&folder=true) (Latin)

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 HOME Alcar training set.

## Evaluation results

The model achieves the following results:

| set   | Language model | CER (%)    | WER (%) | N lines   |
|:------|:---------------|:----------:|:-------:|----------:|
| test  | no             | 8.35       | 26.15   |      6932 |
| test  | yes            | 7.85       | 23.20   |      6932 |

## How to use

Please refer to the [documentation](https://atr.pages.teklia.com/pylaia/).