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--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: label |
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dtype: |
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class_label: |
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names: |
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'0': The Eiffel Tower |
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'1': The Great Wall of China |
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'2': The Mona Lisa |
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'3': aircraft carrier |
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'4': airplane |
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'5': alarm clock |
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'6': ambulance |
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'7': angel |
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'8': animal migration |
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'9': ant |
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'10': anvil |
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'11': apple |
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'12': arm |
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'13': asparagus |
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'14': axe |
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'15': backpack |
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'16': banana |
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'17': bandage |
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'18': barn |
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'19': baseball bat |
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'20': baseball |
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'21': basket |
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'22': basketball |
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'23': bat |
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'24': bathtub |
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'25': beach |
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'26': bear |
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'27': beard |
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'28': bed |
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'29': bee |
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'30': belt |
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'31': bench |
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'32': bicycle |
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'33': binoculars |
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'34': bird |
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'35': birthday cake |
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'36': blackberry |
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'37': blueberry |
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'38': book |
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'39': boomerang |
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'40': bottlecap |
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'41': bowtie |
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'42': bracelet |
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'43': brain |
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'44': bread |
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'45': bridge |
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'46': broccoli |
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'47': broom |
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'48': bucket |
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'49': bulldozer |
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'50': bus |
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'51': bush |
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'52': butterfly |
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'53': cactus |
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'54': cake |
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'55': calculator |
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'56': calendar |
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'57': camel |
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'58': camera |
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'59': camouflage |
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'60': campfire |
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'61': candle |
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'62': cannon |
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'63': canoe |
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'64': car |
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'65': carrot |
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'66': castle |
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'67': cat |
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'68': ceiling fan |
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'69': cell phone |
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'70': cello |
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'71': chair |
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'72': chandelier |
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'73': church |
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'74': circle |
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'75': clarinet |
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'76': clock |
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'77': cloud |
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'78': coffee cup |
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'79': compass |
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'80': computer |
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'81': cookie |
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'82': cooler |
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'83': couch |
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'84': cow |
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'85': crab |
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'86': crayon |
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'87': crocodile |
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'88': crown |
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'89': cruise ship |
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'90': cup |
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'91': diamond |
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'92': dishwasher |
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'93': diving board |
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'94': dog |
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'95': dolphin |
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'96': donut |
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'97': door |
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'98': dragon |
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'99': dresser |
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'100': drill |
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'101': drums |
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'102': duck |
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'103': dumbbell |
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'104': ear |
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'105': elbow |
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'106': elephant |
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'107': envelope |
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'108': eraser |
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'109': eye |
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'110': eyeglasses |
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'111': face |
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'112': fan |
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'113': feather |
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'114': fence |
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'115': finger |
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'116': fire hydrant |
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'117': fireplace |
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'118': firetruck |
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'119': fish |
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'120': flamingo |
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'121': flashlight |
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'122': flip flops |
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'123': floor lamp |
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'124': flower |
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'125': flying saucer |
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'126': foot |
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'127': fork |
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'128': frog |
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'129': frying pan |
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'130': garden hose |
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'131': garden |
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'132': giraffe |
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'133': goatee |
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'134': golf club |
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'135': grapes |
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'136': grass |
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'137': guitar |
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'138': hamburger |
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'139': hammer |
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'140': hand |
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'141': harp |
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'142': hat |
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'143': headphones |
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'144': hedgehog |
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'145': helicopter |
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'146': helmet |
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'147': hexagon |
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'148': hockey puck |
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'149': hockey stick |
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'150': horse |
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'151': hospital |
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'152': hot air balloon |
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'153': hot dog |
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'154': hot tub |
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'155': hourglass |
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'156': house plant |
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'157': house |
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'158': hurricane |
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'159': ice cream |
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'160': jacket |
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'161': jail |
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'162': kangaroo |
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'163': key |
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'164': keyboard |
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'165': knee |
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'166': knife |
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'167': ladder |
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'168': lantern |
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'169': laptop |
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'170': leaf |
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'171': leg |
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'172': light bulb |
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'173': lighter |
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'174': lighthouse |
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'175': lightning |
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'176': line |
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'177': lion |
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'178': lipstick |
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'179': lobster |
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'180': lollipop |
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'181': mailbox |
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'182': map |
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'183': marker |
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'184': matches |
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'185': megaphone |
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'186': mermaid |
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'187': microphone |
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'188': microwave |
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'189': monkey |
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'190': moon |
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'191': mosquito |
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'192': motorbike |
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'193': mountain |
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'194': mouse |
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'195': moustache |
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'196': mouth |
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'197': mug |
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'198': mushroom |
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'199': nail |
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'200': necklace |
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'201': nose |
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'202': ocean |
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'203': octagon |
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'204': octopus |
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'205': onion |
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'206': oven |
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'207': owl |
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'208': paint can |
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'209': paintbrush |
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'210': palm tree |
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'211': panda |
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'212': pants |
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'213': paper clip |
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'214': parachute |
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'215': parrot |
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'216': passport |
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'217': peanut |
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'218': pear |
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'219': peas |
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'220': pencil |
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'221': penguin |
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'222': piano |
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'223': pickup truck |
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'224': picture frame |
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'225': pig |
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'226': pillow |
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'227': pineapple |
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'228': pizza |
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'229': pliers |
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'230': police car |
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'231': pond |
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'232': pool |
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'233': popsicle |
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'234': postcard |
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'235': potato |
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'236': power outlet |
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'237': purse |
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'238': rabbit |
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'239': raccoon |
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'240': radio |
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'241': rain |
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'242': rainbow |
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'243': rake |
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'244': remote control |
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'245': rhinoceros |
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'246': rifle |
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'247': river |
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'248': roller coaster |
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'249': rollerskates |
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'250': sailboat |
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'251': sandwich |
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'252': saw |
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'253': saxophone |
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'254': school bus |
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'255': scissors |
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'256': scorpion |
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'257': screwdriver |
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'258': sea turtle |
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'259': see saw |
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'260': shark |
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'261': sheep |
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'262': shoe |
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'263': shorts |
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'264': shovel |
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'265': sink |
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'266': skateboard |
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'267': skull |
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'268': skyscraper |
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'269': sleeping bag |
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'270': smiley face |
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'271': snail |
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'272': snake |
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'273': snorkel |
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'274': snowflake |
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'275': snowman |
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'276': soccer ball |
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'277': sock |
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'278': speedboat |
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'279': spider |
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'280': spoon |
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'281': spreadsheet |
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'282': square |
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'283': squiggle |
|
'284': squirrel |
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'285': stairs |
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'286': star |
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'287': steak |
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'288': stereo |
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'289': stethoscope |
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'290': stitches |
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'291': stop sign |
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'292': stove |
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'293': strawberry |
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'294': streetlight |
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'295': string bean |
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'296': submarine |
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'297': suitcase |
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'298': sun |
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'299': swan |
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'300': sweater |
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'301': swing set |
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'302': sword |
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'303': syringe |
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'304': t-shirt |
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'305': table |
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'306': teapot |
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'307': teddy-bear |
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'308': telephone |
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'309': television |
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'310': tennis racquet |
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'311': tent |
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'312': tiger |
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'313': toaster |
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'314': toe |
|
'315': toilet |
|
'316': tooth |
|
'317': toothbrush |
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'318': toothpaste |
|
'319': tornado |
|
'320': tractor |
|
'321': traffic light |
|
'322': train |
|
'323': tree |
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'324': triangle |
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'325': trombone |
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'326': truck |
|
'327': trumpet |
|
'328': umbrella |
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'329': underwear |
|
'330': van |
|
'331': vase |
|
'332': violin |
|
'333': washing machine |
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'334': watermelon |
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'335': waterslide |
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'336': whale |
|
'337': wheel |
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'338': windmill |
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'339': wine bottle |
|
'340': wine glass |
|
'341': wristwatch |
|
'342': yoga |
|
'343': zebra |
|
'344': zigzag |
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splits: |
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- name: train |
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num_bytes: 72173714.5 |
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num_examples: 34500 |
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download_size: 70106975 |
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dataset_size: 72173714.5 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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# Dataset Card for Quick, Draw! Dataset |
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This dataset card aims to provide comprehensive information about the Quick, Draw! dataset, a collection of hand-drawn sketches used for training and evaluating sketch classification models. |
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## Dataset Details |
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### Dataset Description |
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The Quick, Draw! dataset is a large-scale collection of hand-drawn sketches curated by Google Creative Lab. The dataset includes over 50 million unique sketches across 345 object categories, contributed by participants from around the world. The primary purpose of this dataset is to facilitate research in the field of computer vision, particularly for tasks related to sketch recognition and classification. |
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- **Curated by:** Google Creative Lab |
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- **Shared by [optional]:** Google |
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### Dataset Sources |
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- **Source:** [The Quick, Draw! Dataset](https://github.com/googlecreativelab/quickdraw-dataset) |
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## Uses |
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### Direct Use |
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The dataset is intended for use in developing and evaluating sketch recognition algorithms. It is suitable for tasks such as: |
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- Training sketch classification models |
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- Evaluating the performance of sketch recognition systems |
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- Conducting research in computer vision and machine learning related to hand-drawn images |
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### Out-of-Scope Use |
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The dataset is not suitable for use cases that require high-resolution images or photographs. It is also not intended for tasks unrelated to sketch recognition, such as natural image classification. |
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## Original Dataset Structure |
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The dataset is organized into categories, each containing a collection of hand-drawn sketches. Each sketch is a black-and-white image representing an object from one of the predefined categories. |
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- **Number of Categories:** 345 |
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- **Number of Sketches:** 50 million |
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### Dataset Splits |
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In this dataset, the Quick, Draw! dataset is provided as a single training set without predefined splits for training, validation, or testing. Due to the large size of the original dataset, I randomly selected 100 samples per category to train within limited resources, resulting in a total of 34,500 sketches. |
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- **Train Set:** |
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- **Number of Examples:** 34,500 |
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