CAFS-GAN

Overview

This project includes source codes and pre-trained model of CAFS-GAN.

Environment

natsort==8.3.1
numpy==1.22.3
opencv-python==4.6.0.66
pytorch==1.13.0
scipy==1.9.3
tqdm==4.64.1

Datasets

• SSAF. A high quality multi-style artistic font dataset.
• Fonts. A computer-generated multi-color font dataset.

Organization of data

CAFS-GAN 
│
└───data_training
|    │
|    └───subfolder1
|    |      image1.png
|    |      image2.png
|    |      ...
|    └───subfolder2
|    |      image1.png
|    |      image2.png
|    |      ...
|    ...
|    └───subfolder8
|    |      image1.png
|    |      image2.png
|    |      ...
└───data_testing
|     │
|     └───subfolder1
|     |      image1.png
|     |      image2.png
|     |      ...
|     └───subfolder2
|     |      image1.png
|     |      image2.png
|     |      ...
|     ...
|     └───subfolder9
|     |      image1.png
|     |      image2.png
|     |      ...
└───datasets
└───models
...

Training

This code fixes model parameters in the middle of training, saves the model, and tests it. The default parameters are set in the main.py file.

python main.py

BibTeX

@inproceedings{xxx2023xxx,
  title     = {Compositional Zero-Shot Artistic Font Synthesis},
  author    = {Li, Xiang and Wu, Lei and Wang, Changshuo and Meng, Lei and Meng, Xiangxu},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  year      = {2023},
  note      = {Main Track},
}