
# CASIA-HWDB2 handwritten text recognition

This model performs Handwritten Text Recognition in Chinese.

## Model description

The model was trained using the PyLaia library on the [CASIA-HWDB1](http://www.nlpr.ia.ac.cn/databases/handwriting/Offline_database.html) document images.

Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.

| split | N lines | 
| ----- | ------: | 
| train | 33,425  |
| val   |  8,325  |
| test  | 10,449  |

An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the CASIA-HWDB2 training set.

## Evaluation results

The model achieves the following results:

| set   | Language model | CER (%)    | N lines   |
|:------|:---------------|:----------:|----------:|
| test  | no             | 4.61       | 10,449    |
| test  | yes            | 1.53       | 10,449    |

## How to use

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

## Cite us

```bibtex
@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"
}
```
{"language": ["zh"], "license": "mit", "library_name": "PyLaia", "tags": ["PyLaia", "PyTorch", "Handwritten text recognition"], "datasets": ["Teklia/CASIA"], "metrics": ["CER"]}
PyLaia PyTorch Handwritten text recognition zh dataset:Teklia/CASIA license:mit has_space region:us
TAGS
#PyLaia #PyTorch #Handwritten text recognition #zh #dataset-Teklia/CASIA #license-mit #has_space #region-us 

CASIA-HWDB2 handwritten text recognition
========================================


This model performs Handwritten Text Recognition in Chinese.


Model description
-----------------


The model was trained using the PyLaia library on the CASIA-HWDB1 document images.


Training images 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 CASIA-HWDB2 training set.


Evaluation results
------------------


The model achieves the following results:



How to use
----------


Please refer to the documentation.


Cite us
-------



TAGS
#PyLaia #PyTorch #Handwritten text recognition #zh #dataset-Teklia/CASIA #license-mit #has_space #region-us 
