pip install -r requirements.txt

data
 └─ hico_20160224_det
     |─ annotations
     |   |─ trainval_hico.json
     |   |─ test_hico.json
     |   └─ corre_hico.npy
     :

qpic
 |─ data
 │   └─ v-coco
 |       |─ data
 |       |   |─ instances_vcoco_all_2014.json
 |       |   :
 |       |─ prior.pickle
 |       |─ images
 |       |   |─ train2014
 |       |   |   |─ COCO_train2014_000000000009.jpg
 |       |   |   :
 |       |   └─ val2014
 |       |       |─ COCO_val2014_000000000042.jpg
 |       |       :
 |       |─ annotations
 :       :

PYTHONPATH=data/v-coco \
        python convert_vcoco_annotations.py \
        --load_path data/v-coco/data \
        --prior_path data/v-coco/prior.pickle \
        --save_path data/v-coco/annotations

python convert_parameters.py \
        --load_path params/detr-r50-e632da11.pth \
        --save_path params/detr-r50-pre-2stage-q64.pth \
        --num_queries 64

python convert_parameters.py \
        --load_path params/detr-r50-e632da11.pth \
        --save_path params/detr-r50-pre-2stage.pth \
        --dataset vcoco

python -m torch.distributed.launch \
        --nproc_per_node=8 \
        --use_env \
        main.py \
        --pretrained params/detr-r50-pre-2stage-q64.pth \
        --output_dir logs \
        --dataset_file hico \
        --hoi_path data/hico_20160224_det \
        --num_obj_classes 80 \
        --num_verb_classes 117 \
        --backbone resnet50 \
        --num_queries 64 \
        --dec_layers_hopd 3 \
        --dec_layers_interaction 3 \
        --epochs 90 \
        --lr_drop 60 \
        --use_nms_filter

python -m torch.distributed.launch \
        --nproc_per_node=8 \
        --use_env \
        main.py \
        --pretrained logs/checkpoint_last.pth \
        --output_dir logs/ \
        --dataset_file hico \
        --hoi_path data/hico_20160224_det \
        --num_obj_classes 80 \
        --num_verb_classes 117 \
        --backbone resnet50 \
        --num_queries 64 \
        --dec_layers_hopd 3 \
        --dec_layers_interaction 3 \
        --epochs 10 \
        --freeze_mode 1 \
        --obj_reweight \
        --verb_reweight \
        --use_nms_filter

python -m torch.distributed.launch \
        --nproc_per_node=8 \
        --use_env \
        main.py \
        --pretrained params/detr-r50-pre-2stage.pth \
        --output_dir logs \
        --dataset_file vcoco \
        --hoi_path data/v-coco \
        --num_obj_classes 81 \
        --num_verb_classes 29 \
        --backbone resnet50 \
        --num_queries 100 \
        --dec_layers_hopd 3 \
        --dec_layers_interaction 3 \
        --epochs 90 \
        --lr_drop 60 \
        --use_nms_filter

python -m torch.distributed.launch \
        --nproc_per_node=8 \
        --use_env \
        main.py \
        --pretrained logs/checkpoint_last.pth \
        --output_dir logs/ \
        --dataset_file vcoco \
        --hoi_path data/v-coco \
        --num_obj_classes 81 \
        --num_verb_classes 29 \
        --backbone resnet50 \
        --num_queries 100 \
        --dec_layers_hopd 3 \
        --dec_layers_interaction 3 \
        --epochs 10 \
        --freeze_mode 1 \
        --verb_reweight \
        --use_nms_filter

python -m torch.distributed.launch \
        --nproc_per_node=8 \
        --use_env \
        main.py \
        --pretrained pretrained/hico_cdn_s.pth \
        --dataset_file hico \
        --hoi_path data/hico_20160224_det \
        --num_obj_classes 80 \
        --num_verb_classes 117 \
        --backbone resnet50 \
        --num_queries 64 \
        --dec_layers_hopd 3 \
        --dec_layers_interaction 3 \
        --eval \
        --use_nms_filter

python generate_vcoco_official.py \
        --param_path pretrained/vcoco_cdn_s.pth \
        --save_path vcoco.pickle \
        --hoi_path data/v-coco \
        --dec_layers_hopd 3 \
        --dec_layers_interaction 3 \
        --use_nms_filter

cd data/v-coco
python vsrl_eval.py vcoco.pickle

@article{zhang2021mining,
  title={Mining the Benefits of Two-stage and One-stage HOI Detection},
  author={Zhang, Aixi and Liao, Yue and Liu, Si and Lu, Miao and Wang, Yongliang and Gao, Chen and Li, Xiaobo},
  journal={arXiv preprint arXiv:2108.05077},
  year={2021}
}