A demo for end-to-end English and Chinese text spotting using ABCNet. This is served as a base setting for others to train their own model on Chinese or other language. Official ABCNet_v2 models has been released in AdelaiDet.

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.

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.

bash demo.sh

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”:

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}
}

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

• ReCTs [images&label](1.7G) [Origin_of_dataset]

• LSVT [images&label](8.2G) [Origin_of_dataset]

• ArT [images&label](1.5G) [Origin_of_dataset]

• SynChinese130k [images&label](25G) [Origin_of_dataset]

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.