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 \