git clone  --recursive https://github.com/takumayagi/hand_object_contact_prediction.git

for vid in `cat configs/valid_vids.txt`; do bash preprocessing/extract_rgb_frames.bash $vid; done
for vid in `cat configs/test_vids.txt`; do bash preprocessing/extract_rgb_frames.bash $vid; done

for vid in `cat configs/trusted_train_vids.txt`; do bash preprocessing/extract_rgb_frames.bash $vid; done

# Caution: take up large space (~400GBs)
for vid in `cat configs/noisy_train_vids.txt`; do bash preprocessing/extract_rgb_frames.bash $vid; done

# Same for test, trusted_train, and noisy_train
# For trusted labels (test, valid, trusted_train)
# Don't forget to add --gt
for vid in `cat configs/valid_vids.txt`; do python preprocessing/extract_flow_frames.py $vid --gt; done

# For pseudo-labels
# Extracting flows for noisy_train will take up large space
for vid in `cat configs/noisy_train_vids.txt`; do python preprocessing/extract_flow_frames.py $vid; done

python train.py --model CrUnionLSTMHO --eval --resume pretrained/proposed_model.pth
python train.py --model CrUnionLSTMHORGB --eval --resume pretrained/rgb_model.pth  # RGB baseline
python train.py --model CrUnionLSTMHOFlow --eval --resume pretrained/flow_model.pth  # Flow baseline

python train.py --model CrUnionLSTMHO --eval --resume pretrained/proposed_model.pth --vis

python train.py --model CrUnionLSTMHO --dir_name proposed --semisupervised --iter_supervision 5000 --iter_warmup 0 --plc --update_clean --init_delta 0.05  --asymp_labeled_flip --nb_iters 800000 --lr_step_list 40000 --save_model --finetune_noisy_net --delta_th 0.01 --iter_snapshot 20000 --iter_evaluation 20000 --min_clean_label_ratio 0.25

# Train
python train_v1.py --model UnionLSTMHO --dir_name supervised_trainval --train_vids configs/trusted_train_vids.txt --nb_iters 25000 --save_model --iter_warmup 5000 --supervised

# Trainval
python train_v1.py --model UnionLSTMHO --dir_name supervised_trainval --train_vids configs/trusted_trainval_vids.txt --nb_iters 25000 --save_model --iter_warmup 5000 --eval_vids configs/test_vids.txt --supervised

python train.py --model UnionLSTMHO --dir_name noisy_pretrain --train_vids configs/noisy_train_vids_55.txt --nb_iters 40000 --save_model --only_boundary
python train.py --model UnionLSTMHO --dir_name clean_pretrain --train_vids configs/trusted_train_vids.txt --nb_iters 25000 --save_model --iter_warmup 2500 --supervised

@inproceedings{yagi2021hand,
  title = {Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction},
  author = {Yagi, Takuma and Hasan, Md. Tasnimul and Sato, Yoichi},
  booktitle = {Proceedings of the British Machine Vision Conference},
  year={2021}
}