setup.sh

python -m pip install -r requirements.txt
mkdir $1/cleanfid/
mkdir $1/cleanfid/stats/
mkdir -p datasets/
rm -rf datasets/* # clear directory content
gdown https://drive.google.com/uc\?id\=1hbzc_P1FuxMkcabkgn9ZKinBwW683j45 -O datasets/
tar zxvf datasets/CUB_200_2011.tgz
mv CUB_200_2011/ datasets/
python resize_dataset.py --input_folder datasets/CUB_200_2011/images --output_folder datasets/CUB_200_2011_32/ --res 32
rm -rf datasets/cub.tgz
rm -rf datasets/CUB_200_2011_32/Mallard_0130_76836.jpg datasets/CUB_200_2011_32/Brewer_Blackbird_0028_2682.jpg datasets/CUB_200_2011_32/Clark_Nutcracker_0020_85099.jpg datasets/CUB_200_2011_32/Ivory_Gull_0040_49180.jpg datasets/CUB_200_2011_32/Pelagic_Cormorant_0022_23802.jpg datasets/CUB_200_2011_32/Western_Gull_0002_54825.jpg datasets/CUB_200_2011_32/Ivory_Gull_0085_49456.jpg datasets/CUB_200_2011_32/White_Necked_Raven_0070_102645.jpg
cp cub_clean_custom_na.npz /home/maillab/anaconda3/envs/VisualLearning/lib/python3.9/site-packages/cleanfid/stats/cub_clean_custom_na.npz