Note: The current software works well with PyTorch 1.4.
If you use this code for your research, please cite:
- Linux or macOS
- Python 3
- CPU or NVIDIA GPU + CUDA CuDNN
- 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.
- For pip users, please type the command
- To view training results and loss plots, run
python -m visdom.serverand 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_ganhttps://github.com/JinshanZeng/Stroke_Based_Chinese_Character_Generation_Dataset
Best practice for training and testing your models.
Before you post a new question, please first look at the above Q & A and existing GitHub issues.
If you use this code for your research, please cite our papers.
https://arxiv.org/abs/2012.08687
**CycleGAN-Torch **CycleGAN and pix2pix in PyTorch
Our code is inspired by pytorch--CycleGAN-and-pix2pix.