| | --- |
| | dataset_info: |
| | features: |
| | - name: image |
| | dtype: image |
| | - name: mask |
| | dtype: image |
| | - name: sents |
| | sequence: string |
| | - name: img_size |
| | sequence: int64 |
| | - name: img_path |
| | dtype: string |
| | - name: num_sents |
| | dtype: int64 |
| | - name: cat |
| | dtype: |
| | class_label: |
| | names: |
| | '0': person |
| | '1': bicycle |
| | '2': car |
| | '3': motorcycle |
| | '4': airplane |
| | '5': bus |
| | '6': train |
| | '7': truck |
| | '8': boat |
| | '9': traffic light |
| | '10': fire hydrant |
| | '11': street sign |
| | '12': stop sign |
| | '13': parking meter |
| | '14': bench |
| | '15': bird |
| | '16': cat |
| | '17': dog |
| | '18': horse |
| | '19': sheep |
| | '20': cow |
| | '21': elephant |
| | '22': bear |
| | '23': zebra |
| | '24': giraffe |
| | '25': hat |
| | '26': backpack |
| | '27': umbrella |
| | '28': shoe |
| | '29': eye glasses |
| | '30': handbag |
| | '31': tie |
| | '32': suitcase |
| | '33': frisbee |
| | '34': skis |
| | '35': snowboard |
| | '36': sports ball |
| | '37': kite |
| | '38': baseball bat |
| | '39': baseball glove |
| | '40': skateboard |
| | '41': surfboard |
| | '42': tennis racket |
| | '43': bottle |
| | '44': plate |
| | '45': wine glass |
| | '46': cup |
| | '47': fork |
| | '48': knife |
| | '49': spoon |
| | '50': bowl |
| | '51': banana |
| | '52': apple |
| | '53': sandwich |
| | '54': orange |
| | '55': broccoli |
| | '56': carrot |
| | '57': hot dog |
| | '58': pizza |
| | '59': donut |
| | '60': cake |
| | '61': chair |
| | '62': couch |
| | '63': potted plant |
| | '64': bed |
| | '65': mirror |
| | '66': dining table |
| | '67': window |
| | '68': desk |
| | '69': toilet |
| | '70': door |
| | '71': tv |
| | '72': laptop |
| | '73': mouse |
| | '74': remote |
| | '75': keyboard |
| | '76': cell phone |
| | '77': microwave |
| | '78': oven |
| | '79': toaster |
| | '80': sink |
| | '81': refrigerator |
| | '82': blender |
| | '83': book |
| | '84': clock |
| | '85': vase |
| | '86': scissors |
| | '87': teddy bear |
| | '88': hair drier |
| | '89': toothbrush |
| | '90': hair brush |
| | '91': banner |
| | '92': blanket |
| | '93': branch |
| | '94': bridge |
| | '95': building-other |
| | '96': bush |
| | '97': cabinet |
| | '98': cage |
| | '99': cardboard |
| | '100': carpet |
| | '101': ceiling-other |
| | '102': ceiling-tile |
| | '103': cloth |
| | '104': clothes |
| | '105': clouds |
| | '106': counter |
| | '107': cupboard |
| | '108': curtain |
| | '109': desk-stuff |
| | '110': dirt |
| | '111': door-stuff |
| | '112': fence |
| | '113': floor-marble |
| | '114': floor-other |
| | '115': floor-stone |
| | '116': floor-tile |
| | '117': floor-wood |
| | '118': flower |
| | '119': fog |
| | '120': food-other |
| | '121': fruit |
| | '122': furniture-other |
| | '123': grass |
| | '124': gravel |
| | '125': ground-other |
| | '126': hill |
| | '127': house |
| | '128': leaves |
| | '129': light |
| | '130': mat |
| | '131': metal |
| | '132': mirror-stuff |
| | '133': moss |
| | '134': mountain |
| | '135': mud |
| | '136': napkin |
| | '137': net |
| | '138': paper |
| | '139': pavement |
| | '140': pillow |
| | '141': plant-other |
| | '142': plastic |
| | '143': platform |
| | '144': playingfield |
| | '145': railing |
| | '146': railroad |
| | '147': river |
| | '148': road |
| | '149': rock |
| | '150': roof |
| | '151': rug |
| | '152': salad |
| | '153': sand |
| | '154': sea |
| | '155': shelf |
| | '156': sky-other |
| | '157': skyscraper |
| | '158': snow |
| | '159': solid-other |
| | '160': stairs |
| | '161': stone |
| | '162': straw |
| | '163': structural-other |
| | '164': table |
| | '165': tent |
| | '166': textile-other |
| | '167': towel |
| | '168': tree |
| | '169': vegetable |
| | '170': wall-brick |
| | '171': wall-concrete |
| | '172': wall-other |
| | '173': wall-panel |
| | '174': wall-stone |
| | '175': wall-tile |
| | '176': wall-wood |
| | '177': water-other |
| | '178': waterdrops |
| | '179': window-blind |
| | '180': window-other |
| | '181': wood |
| | - name: seg_id |
| | dtype: int64 |
| | - name: mask_path |
| | dtype: string |
| | splits: |
| | - name: testA_object_part |
| | num_bytes: 5922400482.75 |
| | num_examples: 11641 |
| | - name: testB_part_only |
| | num_bytes: 2174144982.25 |
| | num_examples: 4119 |
| | - name: testA_part_only |
| | num_bytes: 4919679761.5 |
| | num_examples: 9666 |
| | - name: val_part_only |
| | num_bytes: 6590282037.25 |
| | num_examples: 12691 |
| | download_size: 2358360855 |
| | dataset_size: 19606507263.75 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: testA_part_only |
| | path: data/testA_part_only-* |
| | - split: testB_part_only |
| | path: data/testB_part_only-* |
| | - split: val_part_only |
| | path: data/val_part_only-* |
| | - split: testA_object_part |
| | path: data/testA_object_part-* |
| | --- |
| | |
