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All Projects → williamyang1991 → TET-GAN

williamyang1991 / TET-GAN

Licence: MIT License
[AAAI 2019] TET-GAN: Text Effects Transfer via Stylization and Destylization

Programming Languages

python
139335 projects - #7 most used programming language

Labels

ganstyle-transfertext-effectstext-effectaaai2019

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View All Similar Projects ➔

TET-GAN

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]

It is provided for educational/research purpose only. Please consider citing our paper if you find the software useful for your work.

Usage:

Prerequisites

  • Python 2.7
  • Pytorch 0.4.1
  • matplotlib
  • scipy
  • opencv-python
  • Pillow

Install

  • Clone this repo:
git clone https://github.com/williamyang1991/TET-GAN.git
cd TET-GAN/src

Testing Example

  • Download a pre-trained model from [Google Drive] or [Baidu Cloud] to ../save/
  • Style Transfer with default parameters
    • Results can be found in ../output/

python test.py
  • Destylization with default parameters
python test.py --c2s 0
  • Transfer the style of 26.jpg onto the text image 2.png and save the result as 26_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

Training Examples

Full Training

  • Prepare dataset in ../data/dataset/ where the images are arranged in this way (See [Dataset] for one example)
dataset/style1/train/1.png
dataset/style1/train/2.png
...
dataset/style2/train/1.png
dataset/style2/train/2.png
...
  • The training image consists of a text image and a style image as follows

  • Train TET-GAN with default parameters
python train.py

Saved model can be found at ../save/

  • Use --help to view more training options
python train.py --help

Oneshot Training

  • Download a pre-trained model from [Google Drive] or [Baidu Cloud] to ../save/

    • Specify the pretrained model to load using the option --load_model_name

  • Finetune TET-GAN on a new style/glyph image pair (supervised oneshot training)

python oneshotfinetune.py --style_name ../data/oneshotstyle/1-train.png

Saved model can be found at ../save/

  • Finetune TET-GAN on a new style image without its glyph counterpart (unsupervised oneshot training)
python oneshotfinetune.py --style_name ../data/oneshotstyle/1-train.png --supervise 0

Saved model can be found at ../save/

  • Use --help to view more finetuning options
python oneshotfinetune.py --help

Contact

Shuai Yang

[email protected]

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].