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|
dataset=$1
#/home/lens/Desktop/dataset-random.pl
if [ ! -d "./datasets/$dataset/" ]; then
python datasets/combine_A_and_B.py \
--fold_A "$HOME/Desktop/thumbs/$dataset/A" \
--fold_B "$HOME/Desktop/thumbs/$dataset/B" \
--fold_AB "./datasets/$dataset/"
fi
if [ ! -f "./checkpoints/$dataset/latest_net_G.pth" ]; then
python train.py \
--dataroot "./datasets/$dataset" \
--name "$dataset" \
--model pix2pix \
--dataset_mode aligned \
--which_model_netG unet_256 \
--which_direction AtoB \
--loadSize 264 \
--fineSize 256 \
--lambda_B 100 \
--no_lsgan --norm batch --pool_size 0
else
python train.py \
--dataroot "./datasets/$dataset" \
--name "$dataset" \
--model pix2pix \
--dataset_mode aligned \
--which_model_netG unet_256 \
--which_direction AtoB \
--loadSize 264 \
--fineSize 256 \
--lambda_B 100 \
--which_epoch latest \
--continue_train \
--no_lsgan --norm batch --pool_size 0
fi
#python test.py \
# --dataroot "/home/lens/Desktop/thumbs/$dataset/A/train/" \
# --name "$dataset" \
# --start_img "/home/lens/Desktop/thumbs/$dataset/A/train/frame_1008.png" \
# --how_many 1000 \
# --model test \
# --aspect_ratio 1.777777 \
# --which_model_netG unet_256 \
# --which_direction AtoB \
# --dataset_mode recursive \
# --norm batch
# --loadSize 256 \
# --fineSize 256 \
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