CVPR/lama-example

1# 0. folder preparation2mkdir -p places_standard_dataset/evaluation/hires/3mkdir -p places_standard_dataset/evaluation/random_thick_512/4mkdir -p places_standard_dataset/evaluation/random_thin_512/5mkdir -p places_standard_dataset/evaluation/random_medium_512/6mkdir -p places_standard_dataset/evaluation/random_thick_256/7mkdir -p places_standard_dataset/evaluation/random_thin_256/8mkdir -p places_standard_dataset/evaluation/random_medium_256/9 10# 1. sample 2000 new images11OUT=$(python3 fetch_data/eval_sampler.py)12echo ${OUT}13 14FILELIST=$(cat places_standard_dataset/original/eval_random_files.txt)15for i in $FILELIST16do17    $(cp ${i} places_standard_dataset/evaluation/hires/)18done19 20 21# 2. generate all kinds of masks22 23# all 51224python3 bin/gen_mask_dataset.py \25$(pwd)/configs/data_gen/random_thick_512.yaml \26places_standard_dataset/evaluation/hires \27places_standard_dataset/evaluation/random_thick_512/28 29python3 bin/gen_mask_dataset.py \30$(pwd)/configs/data_gen/random_thin_512.yaml \31places_standard_dataset/evaluation/hires \32places_standard_dataset/evaluation/random_thin_512/33 34python3 bin/gen_mask_dataset.py \35$(pwd)/configs/data_gen/random_medium_512.yaml \36places_standard_dataset/evaluation/hires \37places_standard_dataset/evaluation/random_medium_512/38 39python3 bin/gen_mask_dataset.py \40$(pwd)/configs/data_gen/random_thick_256.yaml \41places_standard_dataset/evaluation/hires \42places_standard_dataset/evaluation/random_thick_256/43 44python3 bin/gen_mask_dataset.py \45$(pwd)/configs/data_gen/random_thin_256.yaml \46places_standard_dataset/evaluation/hires \47places_standard_dataset/evaluation/random_thin_256/48 49python3 bin/gen_mask_dataset.py \50$(pwd)/configs/data_gen/random_medium_256.yaml \51places_standard_dataset/evaluation/hires \52places_standard_dataset/evaluation/random_medium_256/53