To prepare FFHQ dataset, you can follow: FFHQ
Follow the command lines below
DTLS (16 --> 128)
python main.py --mode train --hr_size 128 --lr_size 16 --stride 4 --train_steps 100001 --save_folder 'DTLS_16_128' --data_path 'your_dataset_directory' --batch_size 16
Follow the command lines below
DTLS 16 --> 128
python main.py --mode eval --hr_size 128 --lr_size 16 --load_path 'pretrained_weight/DTLS_128.pt' --save_folder 'DTLS_16_128_results' --input_image 'your_images_folder'
my train python main.py --mode train --hr_size 128 --lr_size 16 --stride 4 --train_steps 100001 --save_folder 'DTLS_16_128' --data_path ./training_set/ --batch_size 16
python main_smiling.py --mode train --hr_size 128 --lr_size 16 --stride 4 --train_steps 100001 --save_folder 'DTLS_smiling' --data_path ./fake_dataset_128/ --batch_size 16
python main_smiling.py --mode train --hr_size 128 --lr_size 16 --stride 4 --train_steps 100001 --save_folder 'myDTLS_smiling' --data_path ./fake_dataset_128/ --batch_size 16
python main_smiling.py --mode train --train_steps 100001 --save_folder 'myDTLS_smiling' --data_path ./fake_dataset_128/ --batch_size 16