# # obtain interactability dataset
# python interactable_coco.py --input ./data/coco_merged/annotations/semantics.json --output ./data/coco_merged/annotations/interactable.json
# ls ./data/coco_merged/images/interactable
# if [ $? -ne 0 ]; then
#     cp -r ./data/coco_merged/images/semantics ./data/coco_merged/images/interactable
# fi

# # map interaction dataset from 61 to 54 classes
# python map_interaction.py

# # generate detection only annotations
# python 2detection.py --input ./data/coco_merged/annotations/interactable.json --output ./data/coco_det/annotations/interactable.json
# python 2detection.py --input ./data/coco_merged/annotations/interaction.json --output ./data/coco_det/annotations/interaction.json
# python 2detection.py --input ./data/coco_merged/annotations/semantics.json --output ./data/coco_det/annotations/semantics.json

# # generate correct segmentation annotations with polygon format
# python 2polyseg.py --input ./data/coco_merged/annotations/interactable.json --output ./data/coco_seg/annotations/interactable.json
# python 2polyseg.py --input ./data/coco_merged/annotations/interaction.json --output ./data/coco_seg/annotations/interaction.json
# python 2polyseg.py --input ./data/coco_merged/annotations/semantics.json --output ./data/coco_seg/annotations/semantics.json

# # split dataset into train
# export FORMAT=det
# export TASK=semantics
# python split_coco.py \
#     --ann_file ./data/coco_$FORMAT/annotations/$TASK.json \
#     --img_dir ./data/coco_merged/images/$TASK/ \
#     --output_path ./data/split_$TASK/ \
#     --fold_file './fold_app.csv' \
#     --train_fold '0,1,4,5,7,9' \
#     --val_fold '3' \
#     --test_fold '2,6,8'
# # use --gen to generate fold_file