Awesome
ABCNet
The full code has been released in the Adet, including the models of CTW1500 and Total-text, all the training data we used, evaluation scripts, results of detection, etc. More updates will also be conducted on Adet as well. This repo will not be maintained anymore.
Run Demo
Check Installation for installation instructions.
bash vis_demo.sh
We assume that your symlinked datasets/totaltext
directory has the following structure:
totaltext
|_ test_images
| |_ 0000000.jpg
| |_ ...
| |_ 0000299.jpg
|_ annotations
| |_ total_test.json
Model [Google Drive]
Totaltext test data [Google Drive]
Syntext-150k (Part1: 54,327 [imgs][annos]. Part2: 94,723 [imgs][annos].)
BezierAlign Example
python tools/tests/single_demo_bezier.py
<img src="demo/BezierAlign_result.png" width="50%">
Description
<img src="demo/24.png" width="81%">Generated Results Download
Bezier-curve generated script link.
CTW1500 visualization results [link] (original training images can be downloaded Here)
Totaltext visualization results [link]
Cite
@article{liu2020abcnet,
title = {ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network},
author = {Liu, Yuliang* and Chen, Hao* and Shen, Chunhua and He, Tong and Jin, Lianwen and Wang, Liangwei},
journal = {arXiv preprint arXiv:2002.10200},
year = {2020}
}
- *represents the authors contributed equally.
Copyright
Any suggestion is welcome. Please send email to liu.yuliang@mail.scut.edu.cn
For commercial purpose usage, please contact Dr. Lianwen Jin: eelwjin@scut.edu.cn
Copyright 2019, Deep Learning and Vision Computing Lab, South China China University of Technology. http://www.dlvc-lab.net