the relationship of subject_id and object_id

[zhazhazhazhi]

I can't understand the relationship of this subject_id and object_id in your test_hico.json file. Whether there is a word list, can be one-to-one correspondence.

test_hico.json
what is means in the subject_id , object_id . What do the numbers inside mean?
Thank you

[YueLiao]

Hi, the subject_id and object_id is the index of the box annotations list. I have found the conventional annotation file is hard to understand, and I plan to update the annotation file recently.

[zhazhazhazhi]

thanks for your reply. I understand it , but i still have a problem. for example the bbox is the cup( category_id is 4), 4 Is it a cup? I find that the list of coco is't a cup . can you give us a list for object . Let the detected people and object have a word list where the ID can be found .

[YueLiao]

coco_class_dict={1: 'person', 2: 'bicycle', 3: 'car', 4: 'motorcycle', 5: 'airplane', 6: 'bus', 7: 'train', 8: 'truck', 9: 'boat', 10: 'traffic light', 11: 'fire hydrant', 13: 'stop sign', 14: 'parking meter', 15: 'bench', 16: 'bird', 17: 'cat', 18: 'dog', 19: 'horse', 20: 'sheep', 21: 'cow', 22: 'elephant', 23: 'bear', 24: 'zebra', 25: 'giraffe', 27: 'backpack', 28: 'umbrella', 31: 'handbag', 32: 'tie', 33: 'suitcase', 34: 'frisbee', 35: 'skis', 36: 'snowboard', 37: 'sports ball', 38: 'kite', 39: 'baseball bat', 40: 'baseball glove', 41: 'skateboard', 42: 'surfboard', 43: 'tennis racket', 44: 'bottle', 46: 'wine glass', 47: 'cup', 48: 'fork', 49: 'knife', 50: 'spoon', 51: 'bowl', 52: 'banana', 53: 'apple', 54: 'sandwich', 55: 'orange', 56: 'broccoli', 57: 'carrot', 58: 'hot dog', 59: 'pizza', 60: 'donut', 61: 'cake', 62: 'chair', 63: 'couch', 64: 'potted plant', 65: 'bed', 67: 'dining table', 70: 'toilet', 72: 'tv', 73: 'laptop', 74: 'mouse', 75: 'remote', 76: 'keyboard', 77: 'cell phone', 78: 'microwave', 79: 'oven', 80: 'toaster', 81: 'sink', 82: 'refrigerator', 84: 'book', 85: 'clock', 86: 'vase', 87: 'scissors', 88: 'teddy bear', 89: 'hair drier', 90: 'toothbrush'}

hico_verb_dict = {1: 'adjust', 2: 'assemble', 3: 'block', 4: 'blow', 5: 'board', 6: 'break', 7: 'brush_with', 8: 'buy', 9: 'carry', 10: 'catch', 11: 'chase', 12: 'check', 13: 'clean', 14: 'control', 15: 'cook', 16: 'cut', 17: 'cut_with', 18: 'direct', 19: 'drag', 20: 'dribble', 21: 'drink_with', 22: 'drive', 23: 'dry', 24: 'eat', 25: 'eat_at', 26: 'exit', 27: 'feed', 28: 'fill', 29: 'flip', 30: 'flush', 31: 'fly', 32: 'greet', 33: 'grind', 34: 'groom', 35: 'herd', 36: 'hit', 37: 'hold', 38: 'hop_on', 39: 'hose', 40: 'hug', 41: 'hunt', 42: 'inspect', 43: 'install', 44: 'jump', 45: 'kick', 46: 'kiss', 47: 'lasso', 48: 'launch', 49: 'lick', 50: 'lie_on', 51: 'lift', 52: 'light', 53: 'load', 54: 'lose', 55: 'make', 56: 'milk', 57: 'move', 58: 'no_interaction', 59: 'open', 60: 'operate', 61: 'pack', 62: 'paint', 63: 'park', 64: 'pay', 65: 'peel', 66: 'pet', 67: 'pick', 68: 'pick_up', 69: 'point', 70: 'pour', 71: 'pull', 72: 'push', 73: 'race', 74: 'read', 75: 'release', 76: 'repair', 77: 'ride', 78: 'row', 79: 'run', 80: 'sail', 81: 'scratch', 82: 'serve', 83: 'set', 84: 'shear', 85: 'sign', 86: 'sip', 87: 'sit_at', 88: 'sit_on', 89: 'slide', 90: 'smell', 91: 'spin', 92: 'squeeze', 93: 'stab', 94: 'stand_on', 95: 'stand_under', 96: 'stick', 97: 'stir', 98: 'stop_at', 99: 'straddle', 100: 'swing', 101: 'tag', 102: 'talk_on', 103: 'teach', 104: 'text_on', 105: 'throw', 106: 'tie', 107: 'toast', 108: 'train', 109: 'turn', 110: 'type_on', 111: 'walk', 112: 'wash', 113: 'watch', 114: 'wave', 115: 'wear', 116: 'wield', 117: 'zip'}

[zhazhazhazhi]

think you

[deep-practice]

'hoi_annotation': [{'subject_id': 1, 'object_id': 0, 'category_id': 5}, {'subject_id': 1, 'object_id': 0, 'category_id': 7}]

HOIW数据集里面的subject_id取值有哪些呢？ @YueLiao