--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': airplane '1': alarm clock '2': angel '3': ant '4': apple '5': arm '6': armchair '7': ashtray '8': axe '9': backpack '10': banana '11': barn '12': baseball bat '13': basket '14': bathtub '15': bear (animal) '16': bed '17': bee '18': beer-mug '19': bell '20': bench '21': bicycle '22': binoculars '23': blimp '24': book '25': bookshelf '26': boomerang '27': bottle opener '28': bowl '29': brain '30': bread '31': bridge '32': bulldozer '33': bus '34': bush '35': butterfly '36': cabinet '37': cactus '38': cake '39': calculator '40': camel '41': camera '42': candle '43': cannon '44': canoe '45': car (sedan) '46': carrot '47': castle '48': cat '49': cell phone '50': chair '51': chandelier '52': church '53': cigarette '54': cloud '55': comb '56': computer monitor '57': computer-mouse '58': couch '59': cow '60': crab '61': crane (machine) '62': crocodile '63': crown '64': cup '65': diamond '66': dog '67': dolphin '68': donut '69': door '70': door handle '71': dragon '72': duck '73': ear '74': elephant '75': envelope '76': eye '77': eyeglasses '78': face '79': fan '80': feather '81': fire hydrant '82': fish '83': flashlight '84': floor lamp '85': flower with stem '86': flying bird '87': flying saucer '88': foot '89': fork '90': frog '91': frying-pan '92': giraffe '93': grapes '94': grenade '95': guitar '96': hamburger '97': hammer '98': hand '99': harp '100': hat '101': head '102': head-phones '103': hedgehog '104': helicopter '105': helmet '106': horse '107': hot air balloon '108': hot-dog '109': hourglass '110': house '111': human-skeleton '112': ice-cream-cone '113': ipod '114': kangaroo '115': key '116': keyboard '117': knife '118': ladder '119': laptop '120': leaf '121': lightbulb '122': lighter '123': lion '124': lobster '125': loudspeaker '126': mailbox '127': megaphone '128': mermaid '129': microphone '130': microscope '131': monkey '132': moon '133': mosquito '134': motorbike '135': mouse (animal) '136': mouth '137': mug '138': mushroom '139': nose '140': octopus '141': owl '142': palm tree '143': panda '144': paper clip '145': parachute '146': parking meter '147': parrot '148': pear '149': pen '150': penguin '151': person sitting '152': person walking '153': piano '154': pickup truck '155': pig '156': pigeon '157': pineapple '158': pipe (for smoking) '159': pizza '160': potted plant '161': power outlet '162': present '163': pretzel '164': pumpkin '165': purse '166': rabbit '167': race car '168': radio '169': rainbow '170': revolver '171': rifle '172': rollerblades '173': rooster '174': sailboat '175': santa claus '176': satellite '177': satellite dish '178': saxophone '179': scissors '180': scorpion '181': screwdriver '182': sea turtle '183': seagull '184': shark '185': sheep '186': ship '187': shoe '188': shovel '189': skateboard '190': skull '191': skyscraper '192': snail '193': snake '194': snowboard '195': snowman '196': socks '197': space shuttle '198': speed-boat '199': spider '200': sponge bob '201': spoon '202': squirrel '203': standing bird '204': stapler '205': strawberry '206': streetlight '207': submarine '208': suitcase '209': sun '210': suv '211': swan '212': sword '213': syringe '214': t-shirt '215': table '216': tablelamp '217': teacup '218': teapot '219': teddy-bear '220': telephone '221': tennis-racket '222': tent '223': tiger '224': tire '225': toilet '226': tomato '227': tooth '228': toothbrush '229': tractor '230': traffic light '231': train '232': tree '233': trombone '234': trousers '235': truck '236': trumpet '237': tv '238': umbrella '239': van '240': vase '241': violin '242': walkie talkie '243': wheel '244': wheelbarrow '245': windmill '246': wine-bottle '247': wineglass '248': wrist-watch '249': zebra splits: - name: train num_bytes: 480609419.0 num_examples: 16000 - name: validation num_bytes: 59693656.0 num_examples: 2000 - name: test num_bytes: 60354461.0 num_examples: 2000 download_size: 589082694 dataset_size: 600657536.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---