Pytorch implementation of LARGE SCALE GAN TRAINING FOR HIGH FIDELITY NATURAL IMAGE SYNTHESIS (BigGAN)
for 128*128*3 resolution
python main.py --batch_size 64 --dataset imagenet --adv_loss hinge --version biggan_imagenet --image_path /data/datasets
python main.py --batch_size 64 --dataset lsun --adv_loss hinge --version biggan_lsun --image_path /data1/datasets/lsun/lsun
python main.py --batch_size 64 --dataset lsun --adv_loss hinge --version biggan_lsun --parallel True --gpus 0,1,2,3 --use_tensorboard True
LSUN Pretrained model Download
Some methods in the paper to avoid model collapse, please see the paper and retrain your model.
LSUN DATASETS(two classes): classroom and church_outdoor