Prerequisites

• Python 3
• NVIDIA GPU + CUDA cuDNN
• PyTorch 1.3.1

Run

1. train the model

python train.py --dataroot no_use --name celebahq_LGNet --model pix2pixglg --netG1 unet_256 --netG2 resnet_4blocks --netG3 unet256 --netD snpatch --gan_mode lsgan --input_nc 4 --no_dropout --direction AtoB --display_id 0 --gpu_ids 0

2. test the model

python test_and_save.py --dataroot no_use --name celebahq_LGNet --model pix2pixglg --netG1 unet_256 --netG2 resnet_4blocks --netG3 unet256 --gan_mode nogan --input_nc 4 --no_dropout --direction AtoB --gpu_ids 0

Download Datasets

We use Places2, CelebA-HQ, and Paris Street-View datasets. Liu et al. provides 12k irregular masks as the testing mask.