- JinHong Min, github: alswlsghd320
- ChaeYeong Yoon, github: chaeyeongyoon
- KiHwan Kim, github: luceinaltis
git clone https://github.com/alswlsghd320/CycleGAN_Pytorch.git
cd CycleGAN_Pytorch
pip install -r requirements.txt
#Train
python train.py --epoch 0
--n_epochs 100
--dataset_path '.'
--pretrained_path None
--batch_size 8
...
"--epoch", type=int, default=0, help="epoch to start training from"
"--n_epochs", type=int, default=100, help="number of epochs of training"
"--dataset_path", type=str, default='.', help="path of the dataset"
"--pretrained_path", type=str, default=None, help="folder path of pretrained model(.pth)"
"--batch_size", type=int, default=8, help="size of the batches"
"--num_workers", type=int, default=4, help="the number of cpu workers"
"--lr", type=float, default=0.0002, help="adam: learning rate"
"--b1", type=float, default=0.5, help="adam: decay of first order momentum of gradient"
"--b2", type=float, default=0.999, help="adam: decay of first order momentum of gradient"
"--decay_epoch", type=int, default=10, help="epoch from which to start lr decay"
"--img_height", type=int, default=256, help="size of image height"
"--img_width", type=int, default=256, help="size of image width"
"--channels", type=int, default=3, help="number of image channels"
"--is_cuda", type=bool, default=True, help="whether to use cuda or not"
"--instance_init", type=bool, default=True, help="whether to initialize instance normalization or not"
"--sample_interval", type=int, default=500, help="interval between sampling model outputs"
"--n_residual_blocks", type=int, default=9, help="number of residual blocks in generator"
"--lambda_cyc", type=float, default=10.0, help="cycle loss weight"
"--use_identity", type=bool, default=False, help="You can use identity loss for photo painting"
"--lambda_id", type=float, default=5.0, help="identity loss weight"
"--save_model", type=bool, default=True, help="save model"
"--save_interval", type=int, default=10, help="interval between saving model checkpoints"
#Test
python test.py # You must enter one of <image, folder, dataset_path>.
"--image", type=str, default=None, help="image path"
"--folder", type=str, default=None, help="folder path"
"--dataset_path", type=str, default=None, help="path of the dataset"
"--model_path", type=str, default='.', help="path of the dataset"
"--img_height", type=int, default=256, help="size of image height"
"--img_width", type=int, default=256, help="size of image width"
"--channels", type=int, default=3, help="number of image channels"
"--is_cuda", type=bool, default=True, help="whether to use cuda or not"
"--instance_init", type=bool, default=True, help="whether to initialize instance normalization or not"
"--n_residual_blocks", type=int, default=9, help="number of residual blocks in generator"
https://arxiv.org/abs/1703.10593
@article{DBLP:journals/corr/ZhuPIE17,
author = {Jun{-}Yan Zhu and
Taesung Park and
Phillip Isola and
Alexei A. Efros},
title = {Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial
Networks},
journal = {CoRR},
volume = {abs/1703.10593},
year = {2017},
url = {http://arxiv.org/abs/1703.10593},
archivePrefix = {arXiv},
eprint = {1703.10593},
timestamp = {Mon, 13 Aug 2018 16:48:06 +0200},
biburl = {https://dblp.org/rec/journals/corr/ZhuPIE17.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}