--- configs: - config_name: default data_files: - split: cups_mugs_glasses path: data/cups_mugs_glasses-* - split: street_detail path: data/street_detail-* - split: sheep path: data/sheep-* - split: bathroom_toilet path: data/bathroom_toilet-* - split: freezer path: data/freezer-* - split: baking_tables path: data/baking_tables-* - split: light_source_in_kitchen path: data/light_source_in_kitchen-* - split: work_area path: data/work_area-* - split: contraceptives path: data/contraceptives-* - split: coins path: data/coins-* - split: backyard path: data/backyard-* - split: bike path: data/bike-* - split: foodstores path: data/foodstores-* - split: toothbrush path: data/toothbrush-* - split: cattle path: data/cattle-* - split: most_played_songs_on_the_radio path: data/most_played_songs_on_the_radio-* - split: plate_of_food path: data/plate_of_food-* - split: shaving path: data/shaving-* - split: car path: data/car-* - split: frontdoor_keys path: data/frontdoor_keys-* - split: goats path: data/goats-* - split: couch path: data/couch-* - split: lock_on_front_door path: data/lock_on_front_door-* - split: mosquito_protection path: data/mosquito_protection-* - split: plates path: data/plates-* - split: bad_outdoor_air_obstructions path: data/bad_outdoor_air_obstructions-* - split: ceiling path: data/ceiling-* - split: radio path: data/radio-* - split: bowls path: data/bowls-* - split: daylight_ostructions path: data/daylight_ostructions-* - split: kitchen_sink path: data/kitchen_sink-* - split: smoke_and_steam_exit path: data/smoke_and_steam_exit-* - split: alcoholic_drinks path: data/alcoholic_drinks-* - split: dish_racks path: data/dish_racks-* - split: thing_i_dream_about_having path: data/thing_i_dream_about_having-* - split: next_big_thing_you_are_planning_to_buy path: data/next_big_thing_you_are_planning_to_buy-* - split: surroundings path: data/surroundings-* - split: skies_outside path: data/skies_outside-* - split: wall_ path: data/wall_-* - split: earings path: data/earings-* - split: bread_ready path: data/bread_ready-* - split: hand_back path: data/hand_back-* - split: dinner_guests path: data/dinner_guests-* - split: rug path: data/rug-* - split: cleaning_floors path: data/cleaning_floors-* - split: paper path: data/paper-* - split: moped_motorcycle path: data/moped_motorcycle-* - split: waste_dumps path: data/waste_dumps-* - split: snacks path: data/snacks-* - split: soccer_balls path: data/soccer_balls-* - split: get_water path: data/get_water-* - split: source_of_cool path: data/source_of_cool-* - split: hand_palm path: data/hand_palm-* - split: cigarettes path: data/cigarettes-* - split: drinks path: data/drinks-* - split: chickens path: data/chickens-* - split: tattoos path: data/tattoos-* - split: home path: data/home-* - split: place_where_serving_guests path: data/place_where_serving_guests-* - split: smog_bad_air_breathing_protection path: data/smog_bad_air_breathing_protection-* - split: roof path: data/roof-* - split: family_snapshots path: data/family_snapshots-* - split: carrying_water path: data/carrying_water-* - split: hand_washing path: data/hand_washing-* - split: horses path: data/horses-* - split: medication path: data/medication-* - split: dish_washing_brush_cloth path: data/dish_washing_brush_cloth-* - split: nicest_shoes path: data/nicest_shoes-* - split: water_outlet path: data/water_outlet-* - split: tv path: data/tv-* - split: air_fresheners_scents path: data/air_fresheners_scents-* - split: portraits path: data/portraits-* - split: celebrity_posters path: data/celebrity_posters-* - split: boat path: data/boat-* - split: trash_waste path: data/trash_waste-* - split: shower path: data/shower-* - split: front_door path: data/front_door-* - split: electric_wires path: data/electric_wires-* - split: photo_guide_images path: data/photo_guide_images-* - split: meat_markets path: data/meat_markets-* - split: cooking_utensils path: data/cooking_utensils-* - split: fishes path: data/fishes-* - split: stove_hob path: data/stove_hob-* - split: water_sources_for_doing_dishes path: data/water_sources_for_doing_dishes-* - split: parking_lot path: data/parking_lot-* - split: spices path: data/spices-* - split: water_sources path: data/water_sources-* - split: pet_foods path: data/pet_foods-* - split: milk_cows_or_bulls path: data/milk_cows_or_bulls-* - split: vegetable_markets path: data/vegetable_markets-* - split: wall_decoration path: data/wall_decoration-* - split: hair_brush_comb path: data/hair_brush_comb-* - split: meat_storages path: data/meat_storages-* - split: bedroom path: data/bedroom-* - split: cooking_pots path: data/cooking_pots-* - split: music_equipment path: data/music_equipment-* - split: arm_watch path: data/arm_watch-* - split: rehabilitation_technology path: data/rehabilitation_technology-* - split: elevators path: data/elevators-* - split: cleaning_after_toilet path: data/cleaning_after_toilet-* - split: storage_room path: data/storage_room-* - split: bread_bowls path: data/bread_bowls-* - split: refrigerator path: data/refrigerator-* - split: dish_washing_soap path: data/dish_washing_soap-* - split: bed path: data/bed-* - split: horse_stables path: data/horse_stables-* - split: oven path: data/oven-* - split: jewelry path: data/jewelry-* - split: bed_kids path: data/bed_kids-* - split: wedding_photos path: data/wedding_photos-* - split: children_room path: data/children_room-* - split: wall_clock path: data/wall_clock-* - split: living_room path: data/living_room-* - split: cleaning_equipment path: data/cleaning_equipment-* - split: baking_sheets path: data/baking_sheets-* - split: make_up path: data/make_up-* - split: soap_for_hands_and_body path: data/soap_for_hands_and_body-* - split: toys path: data/toys-* - split: agriculture_land path: data/agriculture_land-* - split: clothes path: data/clothes-* - split: guest_bed path: data/guest_bed-* - split: fishing_equipment path: data/fishing_equipment-* - split: ventilation path: data/ventilation-* - split: knifes path: data/knifes-* - split: necklaces path: data/necklaces-* - split: most_loved_toy path: data/most_loved_toy-* - split: armchair path: data/armchair-* - split: bed_hq path: data/bed_hq-* - split: air_cleaning_equipments path: data/air_cleaning_equipments-* - split: everyday_shoes path: data/everyday_shoes-* - split: instrument path: data/instrument-* - split: social_drink path: data/social_drink-* - split: drinking_water path: data/drinking_water-* - split: newspapers path: data/newspapers-* - split: washing_detergent path: data/washing_detergent-* - split: transport_of_heavy_things path: data/transport_of_heavy_things-* - split: floor path: data/floor-* - split: hallway path: data/hallway-* - split: salt path: data/salt-* - split: pen_pencils path: data/pen_pencils-* - split: cooking path: data/cooking-* - split: visit path: data/visit-* - split: cosmetics path: data/cosmetics-* - split: latest_furniture_bought path: data/latest_furniture_bought-* - split: play_area path: data/play_area-* - split: soccer_supporter_items path: data/soccer_supporter_items-* - split: water_purifier_solutions path: data/water_purifier_solutions-* - split: snack_stores path: data/snack_stores-* - split: wall path: data/wall-* - split: sitting_area path: data/sitting_area-* - split: wheel_barrow path: data/wheel_barrow-* - split: car_decorations path: data/car_decorations-* - split: markets path: data/markets-* - split: fields path: data/fields-* - split: replaced path: data/replaced-* - split: wardrobe path: data/wardrobe-* - split: tooth_paste path: data/tooth_paste-* - split: worship_places path: data/worship_places-* - split: source_of_heat path: data/source_of_heat-* - split: toilet path: data/toilet-* - split: piercings path: data/piercings-* - split: baking_tools path: data/baking_tools-* - split: lightsources_by_bed path: data/lightsources_by_bed-* - split: light_source_in_livingroom path: data/light_source_in_livingroom-* - split: favourite_sports_clubs path: data/favourite_sports_clubs-* - split: tabloids path: data/tabloids-* - split: books path: data/books-* - split: menstruation_pads_tampax path: data/menstruation_pads_tampax-* - split: power_outlet path: data/power_outlet-* - split: toilet_paper path: data/toilet_paper-* - split: arm_watches path: data/arm_watches-* - split: electricity_wires path: data/electricity_wires-* - split: wall_inside path: data/wall_inside-* - split: computer path: data/computer-* - split: meat_or_fish path: data/meat_or_fish-* - split: sources_of_drinking_water path: data/sources_of_drinking_water-* - split: kitchen path: data/kitchen-* - split: ingredients path: data/ingredients-* - split: baby_powder path: data/baby_powder-* - split: bathroom_privacy path: data/bathroom_privacy-* - split: vegetable_plot path: data/vegetable_plot-* - split: car_keys path: data/car_keys-* - split: icons path: data/icons-* - split: favorite_home_decorations path: data/favorite_home_decorations-* - split: tractors path: data/tractors-* - split: bills_of_money path: data/bills_of_money-* - split: cutlery path: data/cutlery-* - split: family path: data/family-* - split: teeth path: data/teeth-* - split: place_where_eating_dinner path: data/place_where_eating_dinner-* - split: grains path: data/grains-* - split: washing_clothes_cleaning path: data/washing_clothes_cleaning-* - split: fruits_and_vegetables path: data/fruits_and_vegetables-* - split: light_sources path: data/light_sources-* - split: tools path: data/tools-* - split: drying path: data/drying-* - split: street_view path: data/street_view-* - split: phone path: data/phone-* - split: idols path: data/idols-* - split: pet path: data/pet-* - split: other_transport path: data/other_transport-* - split: most_loved_item path: data/most_loved_item-* - split: glasses_or_lenses path: data/glasses_or_lenses-* - split: things_i_wish_i_had path: data/things_i_wish_i_had-* - split: table_with_food path: data/table_with_food-* - split: youth_culture path: data/youth_culture-* - split: equipment path: data/equipment-* - split: shoes path: data/shoes-* - split: coats_and_jackets path: data/coats_and_jackets-* - split: dishwasher path: data/dishwasher-* - split: vegetables path: data/vegetables-* - split: fruit_trees path: data/fruit_trees-* - split: nature_sceneries path: data/nature_sceneries-* - split: shampoo path: data/shampoo-* - split: switch_on_off path: data/switch_on_off-* - split: playgrounds path: data/playgrounds-* dataset_info: features: - name: id dtype: string - name: country_name dtype: string - name: country_id dtype: string - name: region_id dtype: string - name: type dtype: string - name: image dtype: image - name: topics dtype: string - name: place dtype: string - name: income dtype: string splits: - name: cups_mugs_glasses num_bytes: 994285249.0 num_examples: 333 - name: street_detail num_bytes: 1168591117.0 num_examples: 290 - name: sheep num_bytes: 12738586.0 num_examples: 4 - name: bathroom_toilet num_bytes: 1129143553.0 num_examples: 350 - name: freezer num_bytes: 515874223.0 num_examples: 187 - name: baking_tables num_bytes: 3017644.0 num_examples: 1 - name: light_source_in_kitchen num_bytes: 883391525.0 num_examples: 304 - name: work_area num_bytes: 527291086.0 num_examples: 168 - name: contraceptives num_bytes: 56130849.0 num_examples: 25 - name: coins num_bytes: 4296291.0 num_examples: 1 - name: backyard num_bytes: 834683499.0 num_examples: 208 - name: bike num_bytes: 536280770.0 num_examples: 149 - name: foodstores num_bytes: 17300865.0 num_examples: 3 - name: toothbrush num_bytes: 1119100599.0 num_examples: 379 - name: cattle num_bytes: 33022033.0 num_examples: 12 - name: most_played_songs_on_the_radio num_bytes: 2804770.0 num_examples: 1 - name: plate_of_food num_bytes: 965241961.0 num_examples: 298 - name: shaving num_bytes: 630435242.0 num_examples: 216 - name: car num_bytes: 356818254.0 num_examples: 154 - name: frontdoor_keys num_bytes: 208792828.0 num_examples: 147 - name: goats num_bytes: 94614657.0 num_examples: 24 - name: couch num_bytes: 1038410012.0 num_examples: 306 - name: lock_on_front_door num_bytes: 1099656984.0 num_examples: 362 - name: mosquito_protection num_bytes: 541301592.0 num_examples: 163 - name: plates num_bytes: 1033692373.0 num_examples: 342 - name: bad_outdoor_air_obstructions num_bytes: 1141009.0 num_examples: 6 - name: ceiling num_bytes: 1154394188.0 num_examples: 362 - name: radio num_bytes: 534624094.0 num_examples: 164 - name: bowls num_bytes: 69506612.0 num_examples: 24 - name: daylight_ostructions num_bytes: 2457632.0 num_examples: 6 - name: kitchen_sink num_bytes: 1077526669.0 num_examples: 334 - name: smoke_and_steam_exit num_bytes: 735515901.0 num_examples: 233 - name: alcoholic_drinks num_bytes: 206764191.0 num_examples: 72 - name: dish_racks num_bytes: 1070639074.0 num_examples: 336 - name: thing_i_dream_about_having num_bytes: 472486186.0 num_examples: 159 - name: next_big_thing_you_are_planning_to_buy num_bytes: 426843198.0 num_examples: 153 - name: surroundings num_bytes: 60100849.0 num_examples: 13 - name: skies_outside num_bytes: 3351593.0 num_examples: 7 - name: wall_ num_bytes: 2818789640.0 num_examples: 877 - name: earings num_bytes: 395054544.0 num_examples: 136 - name: bread_ready num_bytes: 17031177.0 num_examples: 4 - name: hand_back num_bytes: 1091816070.0 num_examples: 358 - name: dinner_guests num_bytes: 142874232.0 num_examples: 48 - name: rug num_bytes: 720029591.0 num_examples: 193 - name: cleaning_floors num_bytes: 422989995.0 num_examples: 124 - name: paper num_bytes: 1595217257.0 num_examples: 505 - name: moped_motorcycle num_bytes: 244103066.0 num_examples: 82 - name: waste_dumps num_bytes: 484227664.0 num_examples: 127 - name: snacks num_bytes: 37990707.0 num_examples: 11 - name: soccer_balls num_bytes: 11121861.0 num_examples: 3 - name: get_water num_bytes: 312942447.0 num_examples: 80 - name: source_of_cool num_bytes: 786516004.0 num_examples: 250 - name: hand_palm num_bytes: 1045670614.0 num_examples: 357 - name: cigarettes num_bytes: 124000767.0 num_examples: 30 - name: drinks num_bytes: 218115579.0 num_examples: 75 - name: chickens num_bytes: 271724783.0 num_examples: 71 - name: tattoos num_bytes: 175056398.0 num_examples: 51 - name: home num_bytes: 1873360607.0 num_examples: 550 - name: place_where_serving_guests num_bytes: 452285557.0 num_examples: 147 - name: smog_bad_air_breathing_protection num_bytes: 240117.0 num_examples: 2 - name: roof num_bytes: 983562313.0 num_examples: 302 - name: family_snapshots num_bytes: 392643354.0 num_examples: 109 - name: carrying_water num_bytes: 3082174.0 num_examples: 1 - name: hand_washing num_bytes: 1060102199.0 num_examples: 347 - name: horses num_bytes: 7103900.0 num_examples: 3 - name: medication num_bytes: 935436600.0 num_examples: 291 - name: dish_washing_brush_cloth num_bytes: 1118661909.0 num_examples: 351 - name: nicest_shoes num_bytes: 1178886748.0 num_examples: 350 - name: water_outlet num_bytes: 967359266.0 num_examples: 305 - name: tv num_bytes: 881350311.0 num_examples: 292 - name: air_fresheners_scents num_bytes: 115395.0 num_examples: 1 - name: portraits num_bytes: 27532067.0 num_examples: 9 - name: celebrity_posters num_bytes: 6966565.0 num_examples: 1 - name: boat num_bytes: 23087642.0 num_examples: 5 - name: trash_waste num_bytes: 964196788.0 num_examples: 291 - name: shower num_bytes: 995696782.0 num_examples: 329 - name: front_door num_bytes: 2269861804.0 num_examples: 732 - name: electric_wires num_bytes: 8854810.0 num_examples: 2 - name: photo_guide_images num_bytes: 215474454.0 num_examples: 75 - name: meat_markets num_bytes: 4634793.0 num_examples: 1 - name: cooking_utensils num_bytes: 1023598264.0 num_examples: 301 - name: fishes num_bytes: 159058192.0 num_examples: 58 - name: stove_hob num_bytes: 1175724856.0 num_examples: 381 - name: water_sources_for_doing_dishes num_bytes: 15657524.0 num_examples: 7 - name: parking_lot num_bytes: 448364538.0 num_examples: 126 - name: spices num_bytes: 1138126845.0 num_examples: 360 - name: water_sources num_bytes: 39337550.0 num_examples: 12 - name: pet_foods num_bytes: 208829264.0 num_examples: 64 - name: milk_cows_or_bulls num_bytes: 19719273.0 num_examples: 6 - name: vegetable_markets num_bytes: 3934905.0 num_examples: 1 - name: wall_decoration num_bytes: 1133852833.0 num_examples: 352 - name: hair_brush_comb num_bytes: 1069311270.0 num_examples: 331 - name: meat_storages num_bytes: 5019867.0 num_examples: 2 - name: bedroom num_bytes: 1383727529.0 num_examples: 399 - name: cooking_pots num_bytes: 1263802321.0 num_examples: 384 - name: music_equipment num_bytes: 517230560.0 num_examples: 172 - name: arm_watch num_bytes: 298661802.0 num_examples: 101 - name: rehabilitation_technology num_bytes: 10884034.0 num_examples: 8 - name: elevators num_bytes: 3346981.0 num_examples: 3 - name: cleaning_after_toilet num_bytes: 21874227.0 num_examples: 14 - name: storage_room num_bytes: 772429217.0 num_examples: 225 - name: bread_bowls num_bytes: 4171755.0 num_examples: 1 - name: refrigerator num_bytes: 704561864.0 num_examples: 262 - name: dish_washing_soap num_bytes: 1028112295.0 num_examples: 337 - name: bed num_bytes: 2798532320.0 num_examples: 832 - name: horse_stables num_bytes: 2030907.0 num_examples: 1 - name: oven num_bytes: 408380446.0 num_examples: 142 - name: jewelry num_bytes: 566520264.0 num_examples: 189 - name: bed_kids num_bytes: 901139651.0 num_examples: 250 - name: wedding_photos num_bytes: 266849446.0 num_examples: 83 - name: children_room num_bytes: 677706326.0 num_examples: 196 - name: wall_clock num_bytes: 567309624.0 num_examples: 184 - name: living_room num_bytes: 976352363.0 num_examples: 279 - name: cleaning_equipment num_bytes: 808855439.0 num_examples: 240 - name: baking_sheets num_bytes: 2760341.0 num_examples: 1 - name: make_up num_bytes: 324344448.0 num_examples: 97 - name: soap_for_hands_and_body num_bytes: 1043814773.0 num_examples: 363 - name: toys num_bytes: 904248551.0 num_examples: 286 - name: agriculture_land num_bytes: 237876904.0 num_examples: 53 - name: clothes num_bytes: 1022544251.0 num_examples: 323 - name: guest_bed num_bytes: 504616118.0 num_examples: 164 - name: fishing_equipment num_bytes: 4282534.0 num_examples: 1 - name: ventilation num_bytes: 24058628.0 num_examples: 10 - name: knifes num_bytes: 621867863.0 num_examples: 181 - name: necklaces num_bytes: 468137237.0 num_examples: 139 - name: most_loved_toy num_bytes: 766935172.0 num_examples: 238 - name: armchair num_bytes: 1116948741.0 num_examples: 332 - name: bed_hq num_bytes: 18768649.0 num_examples: 4 - name: air_cleaning_equipments num_bytes: 562027.0 num_examples: 4 - name: everyday_shoes num_bytes: 1282284689.0 num_examples: 365 - name: instrument num_bytes: 201768650.0 num_examples: 64 - name: social_drink num_bytes: 865071477.0 num_examples: 280 - name: drinking_water num_bytes: 958784447.0 num_examples: 309 - name: newspapers num_bytes: 25233082.0 num_examples: 7 - name: washing_detergent num_bytes: 967584026.0 num_examples: 315 - name: transport_of_heavy_things num_bytes: 66846208.0 num_examples: 21 - name: floor num_bytes: 1330556621.0 num_examples: 377 - name: hallway num_bytes: 126639302.0 num_examples: 49 - name: salt num_bytes: 997626560.0 num_examples: 343 - name: pen_pencils num_bytes: 937874666.0 num_examples: 288 - name: cooking num_bytes: 2251982244.0 num_examples: 679 - name: visit num_bytes: 4464796725.109 num_examples: 1321 - name: cosmetics num_bytes: 362582452.0 num_examples: 123 - name: latest_furniture_bought num_bytes: 325501347.0 num_examples: 107 - name: play_area num_bytes: 807546710.0 num_examples: 216 - name: soccer_supporter_items num_bytes: 3500438.0 num_examples: 3 - name: water_purifier_solutions num_bytes: 278055.0 num_examples: 2 - name: snack_stores num_bytes: 288627.0 num_examples: 1 - name: wall num_bytes: 3920557387.358 num_examples: 1154 - name: sitting_area num_bytes: 1008819886.0 num_examples: 299 - name: wheel_barrow num_bytes: 201248243.0 num_examples: 45 - name: car_decorations num_bytes: 5448714.0 num_examples: 1 - name: markets num_bytes: 35468731.0 num_examples: 8 - name: fields num_bytes: 5822273.0 num_examples: 1 - name: replaced num_bytes: 4438189.0 num_examples: 3 - name: wardrobe num_bytes: 1161924263.0 num_examples: 362 - name: tooth_paste num_bytes: 992504555.0 num_examples: 334 - name: worship_places num_bytes: 269510881.0 num_examples: 77 - name: source_of_heat num_bytes: 453347786.0 num_examples: 145 - name: toilet num_bytes: 2922917220.0 num_examples: 943 - name: piercings num_bytes: 181157725.0 num_examples: 68 - name: baking_tools num_bytes: 2321733.0 num_examples: 1 - name: lightsources_by_bed num_bytes: 262728699.0 num_examples: 92 - name: light_source_in_livingroom num_bytes: 895836854.0 num_examples: 307 - name: favourite_sports_clubs num_bytes: 135961086.0 num_examples: 46 - name: tabloids num_bytes: 9384343.0 num_examples: 2 - name: books num_bytes: 1045990947.0 num_examples: 315 - name: menstruation_pads_tampax num_bytes: 400849572.0 num_examples: 125 - name: power_outlet num_bytes: 875197741.0 num_examples: 298 - name: toilet_paper num_bytes: 908650830.0 num_examples: 294 - name: arm_watches num_bytes: 55557790.0 num_examples: 30 - name: electricity_wires num_bytes: 2244483.0 num_examples: 1 - name: wall_inside num_bytes: 1174096181.0 num_examples: 358 - name: computer num_bytes: 552454079.0 num_examples: 186 - name: meat_or_fish num_bytes: 616043178.0 num_examples: 192 - name: sources_of_drinking_water num_bytes: 3045397.0 num_examples: 8 - name: kitchen num_bytes: 3049589855.0 num_examples: 967 - name: ingredients num_bytes: 17779940.0 num_examples: 3 - name: baby_powder num_bytes: 7773188.0 num_examples: 4 - name: bathroom_privacy num_bytes: 898900810.0 num_examples: 283 - name: vegetable_plot num_bytes: 283618018.0 num_examples: 71 - name: car_keys num_bytes: 58358512.0 num_examples: 58 - name: icons num_bytes: 47368214.0 num_examples: 188 - name: favorite_home_decorations num_bytes: 476751718.0 num_examples: 151 - name: tractors num_bytes: 8786272.0 num_examples: 1 - name: bills_of_money num_bytes: 11163171.0 num_examples: 2 - name: cutlery num_bytes: 926351889.0 num_examples: 301 - name: family num_bytes: 1622349409.0 num_examples: 493 - name: teeth num_bytes: 908538754.0 num_examples: 326 - name: place_where_eating_dinner num_bytes: 1171010449.0 num_examples: 369 - name: grains num_bytes: 1066679345.0 num_examples: 319 - name: washing_clothes_cleaning num_bytes: 986858417.0 num_examples: 314 - name: fruits_and_vegetables num_bytes: 664452138.0 num_examples: 210 - name: light_sources num_bytes: 707637325.0 num_examples: 220 - name: tools num_bytes: 900850525.0 num_examples: 252 - name: drying num_bytes: 860669230.0 num_examples: 270 - name: street_view num_bytes: 1270219060.0 num_examples: 353 - name: phone num_bytes: 1002531643.0 num_examples: 326 - name: idols num_bytes: 204194164.0 num_examples: 65 - name: pet num_bytes: 843309370.0 num_examples: 248 - name: other_transport num_bytes: 20219867.0 num_examples: 5 - name: most_loved_item num_bytes: 763492723.0 num_examples: 242 - name: glasses_or_lenses num_bytes: 406654084.0 num_examples: 148 - name: things_i_wish_i_had num_bytes: 13208034.0 num_examples: 5 - name: table_with_food num_bytes: 723749144.0 num_examples: 228 - name: youth_culture num_bytes: 6899000.0 num_examples: 1 - name: equipment num_bytes: 1330368532.0 num_examples: 413 - name: shoes num_bytes: 2424967583.0 num_examples: 709 - name: coats_and_jackets num_bytes: 60417863.0 num_examples: 26 - name: dishwasher num_bytes: 189437189.0 num_examples: 55 - name: vegetables num_bytes: 1619243098.0 num_examples: 492 - name: fruit_trees num_bytes: 347993315.0 num_examples: 100 - name: nature_sceneries num_bytes: 9080831.0 num_examples: 3 - name: shampoo num_bytes: 1009790811.0 num_examples: 339 - name: switch_on_off num_bytes: 879446769.0 num_examples: 297 - name: playgrounds num_bytes: 35287984.0 num_examples: 7 download_size: 17029671 dataset_size: 134309090433.467 --- # Dataset Card for "dollarstreet" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)