README.md

---
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:
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    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
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    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
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  - name: radio
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    num_examples: 164
  - name: bowls
    num_bytes: 69506612.0
    num_examples: 24
  - name: daylight_ostructions
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    num_examples: 6
  - name: kitchen_sink
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    num_examples: 334
  - name: smoke_and_steam_exit
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    num_examples: 233
  - name: alcoholic_drinks
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  - name: dish_racks
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  - name: thing_i_dream_about_having
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    num_examples: 159
  - name: next_big_thing_you_are_planning_to_buy
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    num_examples: 153
  - name: surroundings
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    num_examples: 13
  - name: skies_outside
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  - name: wall_
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  - name: earings
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  - name: hand_back
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  - name: dinner_guests
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  - name: rug
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  - name: paper
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  - name: moped_motorcycle
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  - name: waste_dumps
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  - name: snacks
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  - name: soccer_balls
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  - name: source_of_cool
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  - name: hand_palm
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    num_examples: 357
  - name: cigarettes
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    num_examples: 30
  - name: drinks
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    num_examples: 75
  - name: chickens
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  - name: tattoos
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  - name: water_sources_for_doing_dishes
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  - name: parking_lot
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  - name: pet_foods
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  - name: milk_cows_or_bulls
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    num_examples: 6
  - name: vegetable_markets
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    num_examples: 1
  - name: wall_decoration
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  - name: hair_brush_comb
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  - name: bedroom
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  - name: music_equipment
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  - name: arm_watch
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  - name: rehabilitation_technology
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  - name: elevators
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  - name: cleaning_after_toilet
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  - name: storage_room
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  - name: bread_bowls
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  - name: refrigerator
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  - name: bed
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  - name: horse_stables
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  - name: oven
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  - name: jewelry
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  - name: bed_kids
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  - name: wedding_photos
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---
# Dataset Card for "dollarstreet"

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)