A demo for end-to-end English and Chinese text spotting using ABCNet.

Overview

ABCNet_Chinese

A demo for end-to-end English and Chinese text spotting using ABCNet. This is an old model that was trained a long ago, which serves as a base setting for others to train their own model on Chinese or other language. Official ABCNet_v2 models will be updated in AdelaiDet.

Installation

Install detectron2 using the provided version (support visualizing Chinese text):

python -m pip install -e d2

Install this repo:

python setup.py build develop

If the above succeed, you can now run the demo using the provided model.

Model

This is our model that can be used for evaluation or pretraining.

wget https://drive.google.com/file/d/1iWX2n_BmyltVwQmfj8_oM9z7cJlq1P0m/view?usp=sharing -O model_chn.pth

Simply put the model in the root directory of the repo.

Demo

bash demo.sh

Example results

If you successfully run the demo, you will get the output below:

Other results (same project but not using the provide model):

Document-like Ancient words, e.g., “彝文”:

Cite

If you find this repo useful, please cite:

@article{liu2021abcnet,
  title={ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting},
  author={Liu, Yuliang and Shen, Chunhua and Jin, Lianwen and He, Tong and Chen, Peng and Liu, Chongyu and Chen, Hao},
  journal={arXiv preprint arXiv:2105.03620},
  year={2021}
}

Data

We provide the converted json files of ArT, LSVT, and ReCTS that we have used for training ABCNet_Chinese.

License

For academic use, this project is licensed under the 2-clause BSD License - see the LICENSE file for details. For commercial use, please contact Chunhua Shen.

Owner
Yuliang Liu
MMLab; South China University of Technology; University of Adelaide
Yuliang Liu
2021海华AI挑战赛·中文阅读理解·技术组·第三名

文字是人类用以记录和表达的最基本工具,也是信息传播的重要媒介。透过文字与符号,我们可以追寻人类文明的起源,可以传播知识与经验,读懂文字是认识与了解的第一步。对于人工智能而言,它的核心问题之一就是认知,而认知的核心则是语义理解。

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