Note: The current software works well with PyTorch 1.4.

If you use this code for your research, please cite:

Prerequisites

• Linux or macOS
• Python 3
• CPU or NVIDIA GPU + CUDA CuDNN

Getting Started

Installation

• Clone this repo:

git clone https://github.com/JinshanZeng/StrokeGAN
cd StrokeGAN

• Install PyTorch and 0.4+ and other dependencies (e.g., torchvision, visdom and dominate).
  • For pip users, please type the command pip install -r requirements.txt.
  • For Conda users, you can create a new Conda environment using conda env create -f environment.yml.

train/test

• To view training results and loss plots, run python -m visdom.server and click the URL http://localhost:8097.
• Train a model:

#train
python train.py --dataroot ./datasets/data --name data_cyclegan --model cycle_gan

• Test the model:

#!./scripts/test_cyclegan.sh
python test.py --dataroot ./datasets/data --name data_cyclegan --model cycle_gan

Datasets

https://github.com/JinshanZeng/Stroke_Based_Chinese_Character_Generation_Dataset

Training/Test Tips

Best practice for training and testing your models.

Frequently Asked Questions

Before you post a new question, please first look at the above Q & A and existing GitHub issues.

Citation

If you use this code for your research, please cite our papers.

https://arxiv.org/abs/2012.08687

Related Projects

**CycleGAN-Torch **CycleGAN and pix2pix in PyTorch

Acknowledgments

Our code is inspired by pytorch--CycleGAN-and-pix2pix.