This is a pytorch implementation of the paper.
Shuai Yang, Jiaying Liu, Wenjing Wang and Zongming Guo. TET-GAN: Text Effects Transfer via Stylization and Destylization, Accepted by AAAI Conference on Artificial Intelligence (AAAI), 2019.
[Project] | [Paper] | [Dataset]
This code currently only provides functions for testing. We are cleanning up the training code and the full code will be released soon.
It is provided for educational/research purpose only. Please consider citing our paper if you find the software useful for your work.
- Python 2.7
- Pytorch 0.4.1
- matplotlib
- scipy
- opencv-python
- Pillow
- Clone this repo:
git clone https://github.com/williamyang1991/TET-GAN.git
cd TET-GAN/src
- Download a pre-trained model from [Google Drive] or [Baidu Cloud] to
./save/
- Style Transfer with default parameters
- Results can be found in
./output/
- Results can be found in
python test.py
- Destylization with default parameters
python test.py --c2s 0
- Transfer the style of
26.jpg
onto the text image2.png
and save the result as26_2.png
python test.py --style_name ../data/style/26.png --content_name ../data/content/2.png --name 26_2.png
- For black and white text images, use option
--content_type 1
python test.py --style_name ../data/style/1.png --content_name ../data/content/4.png --content_type 1
We are cleanning up the related code and it will be coming soon.
Shuai Yang