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README.md
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|
| 1 |
+
---
|
| 2 |
+
configs:
|
| 3 |
+
- config_name: default
|
| 4 |
+
data_files:
|
| 5 |
+
- split: fishing_equipment
|
| 6 |
+
path: data/fishing_equipment-*
|
| 7 |
+
- split: playgrounds
|
| 8 |
+
path: data/playgrounds-*
|
| 9 |
+
- split: fruit_trees
|
| 10 |
+
path: data/fruit_trees-*
|
| 11 |
+
- split: cleaning_after_toilet
|
| 12 |
+
path: data/cleaning_after_toilet-*
|
| 13 |
+
- split: dinner_guests
|
| 14 |
+
path: data/dinner_guests-*
|
| 15 |
+
- split: idols
|
| 16 |
+
path: data/idols-*
|
| 17 |
+
- split: freezer
|
| 18 |
+
path: data/freezer-*
|
| 19 |
+
- split: hand_washing
|
| 20 |
+
path: data/hand_washing-*
|
| 21 |
+
- split: lock_on_front_door
|
| 22 |
+
path: data/lock_on_front_door-*
|
| 23 |
+
- split: children_room
|
| 24 |
+
path: data/children_room-*
|
| 25 |
+
- split: coats_and_jackets
|
| 26 |
+
path: data/coats_and_jackets-*
|
| 27 |
+
- split: hand_palm
|
| 28 |
+
path: data/hand_palm-*
|
| 29 |
+
- split: play_area
|
| 30 |
+
path: data/play_area-*
|
| 31 |
+
- split: bed
|
| 32 |
+
path: data/bed-*
|
| 33 |
+
- split: car_keys
|
| 34 |
+
path: data/car_keys-*
|
| 35 |
+
- split: meat_markets
|
| 36 |
+
path: data/meat_markets-*
|
| 37 |
+
- split: earings
|
| 38 |
+
path: data/earings-*
|
| 39 |
+
- split: hallway
|
| 40 |
+
path: data/hallway-*
|
| 41 |
+
- split: salt
|
| 42 |
+
path: data/salt-*
|
| 43 |
+
- split: cleaning_equipment
|
| 44 |
+
path: data/cleaning_equipment-*
|
| 45 |
+
- split: water_sources
|
| 46 |
+
path: data/water_sources-*
|
| 47 |
+
- split: chickens
|
| 48 |
+
path: data/chickens-*
|
| 49 |
+
- split: toilet_paper
|
| 50 |
+
path: data/toilet_paper-*
|
| 51 |
+
- split: backyard
|
| 52 |
+
path: data/backyard-*
|
| 53 |
+
- split: living_room
|
| 54 |
+
path: data/living_room-*
|
| 55 |
+
- split: refrigerator
|
| 56 |
+
path: data/refrigerator-*
|
| 57 |
+
- split: bathroom_privacy
|
| 58 |
+
path: data/bathroom_privacy-*
|
| 59 |
+
- split: next_big_thing_you_are_planning_to_buy
|
| 60 |
+
path: data/next_big_thing_you_are_planning_to_buy-*
|
| 61 |
+
- split: nature_sceneries
|
| 62 |
+
path: data/nature_sceneries-*
|
| 63 |
+
- split: bread_bowls
|
| 64 |
+
path: data/bread_bowls-*
|
| 65 |
+
- split: portraits
|
| 66 |
+
path: data/portraits-*
|
| 67 |
+
- split: boat
|
| 68 |
+
path: data/boat-*
|
| 69 |
+
- split: books
|
| 70 |
+
path: data/books-*
|
| 71 |
+
- split: necklaces
|
| 72 |
+
path: data/necklaces-*
|
| 73 |
+
- split: plate_of_food
|
| 74 |
+
path: data/plate_of_food-*
|
| 75 |
+
- split: place_where_serving_guests
|
| 76 |
+
path: data/place_where_serving_guests-*
|
| 77 |
+
- split: medication
|
| 78 |
+
path: data/medication-*
|
| 79 |
+
- split: meat_storages
|
| 80 |
+
path: data/meat_storages-*
|
| 81 |
+
- split: hand_back
|
| 82 |
+
path: data/hand_back-*
|
| 83 |
+
- split: kitchen
|
| 84 |
+
path: data/kitchen-*
|
| 85 |
+
- split: stove_hob
|
| 86 |
+
path: data/stove_hob-*
|
| 87 |
+
- split: jewelry
|
| 88 |
+
path: data/jewelry-*
|
| 89 |
+
- split: sitting_area
|
| 90 |
+
path: data/sitting_area-*
|
| 91 |
+
- split: cattle
|
| 92 |
+
path: data/cattle-*
|
| 93 |
+
- split: source_of_heat
|
| 94 |
+
path: data/source_of_heat-*
|
| 95 |
+
- split: drinks
|
| 96 |
+
path: data/drinks-*
|
| 97 |
+
- split: bowls
|
| 98 |
+
path: data/bowls-*
|
| 99 |
+
- split: tractors
|
| 100 |
+
path: data/tractors-*
|
| 101 |
+
- split: shampoo
|
| 102 |
+
path: data/shampoo-*
|
| 103 |
+
- split: toilet
|
| 104 |
+
path: data/toilet-*
|
| 105 |
+
- split: baking_tables
|
| 106 |
+
path: data/baking_tables-*
|
| 107 |
+
- split: wardrobe
|
| 108 |
+
path: data/wardrobe-*
|
| 109 |
+
- split: arm_watches
|
| 110 |
+
path: data/arm_watches-*
|
| 111 |
+
- split: armchair
|
| 112 |
+
path: data/armchair-*
|
| 113 |
+
- split: shower
|
| 114 |
+
path: data/shower-*
|
| 115 |
+
- split: visit
|
| 116 |
+
path: data/visit-*
|
| 117 |
+
- split: music_equipment
|
| 118 |
+
path: data/music_equipment-*
|
| 119 |
+
- split: bathroom_toilet
|
| 120 |
+
path: data/bathroom_toilet-*
|
| 121 |
+
- split: electric_wires
|
| 122 |
+
path: data/electric_wires-*
|
| 123 |
+
- split: cooking_pots
|
| 124 |
+
path: data/cooking_pots-*
|
| 125 |
+
- split: other_transport
|
| 126 |
+
path: data/other_transport-*
|
| 127 |
+
- split: daylight_ostructions
|
| 128 |
+
path: data/daylight_ostructions-*
|
| 129 |
+
- split: bread_ready
|
| 130 |
+
path: data/bread_ready-*
|
| 131 |
+
- split: work_area
|
| 132 |
+
path: data/work_area-*
|
| 133 |
+
- split: pet_foods
|
| 134 |
+
path: data/pet_foods-*
|
| 135 |
+
- split: air_fresheners_scents
|
| 136 |
+
path: data/air_fresheners_scents-*
|
| 137 |
+
- split: dishwasher
|
| 138 |
+
path: data/dishwasher-*
|
| 139 |
+
- split: street_view
|
| 140 |
+
path: data/street_view-*
|
| 141 |
+
- split: foodstores
|
| 142 |
+
path: data/foodstores-*
|
| 143 |
+
- split: shoes
|
| 144 |
+
path: data/shoes-*
|
| 145 |
+
- split: pet
|
| 146 |
+
path: data/pet-*
|
| 147 |
+
- split: couch
|
| 148 |
+
path: data/couch-*
|
| 149 |
+
- split: thing_i_dream_about_having
|
| 150 |
+
path: data/thing_i_dream_about_having-*
|
| 151 |
+
- split: glasses_or_lenses
|
| 152 |
+
path: data/glasses_or_lenses-*
|
| 153 |
+
- split: instrument
|
| 154 |
+
path: data/instrument-*
|
| 155 |
+
- split: vegetable_markets
|
| 156 |
+
path: data/vegetable_markets-*
|
| 157 |
+
- split: washing_clothes_cleaning
|
| 158 |
+
path: data/washing_clothes_cleaning-*
|
| 159 |
+
- split: most_played_songs_on_the_radio
|
| 160 |
+
path: data/most_played_songs_on_the_radio-*
|
| 161 |
+
- split: equipment
|
| 162 |
+
path: data/equipment-*
|
| 163 |
+
- split: car
|
| 164 |
+
path: data/car-*
|
| 165 |
+
- split: table_with_food
|
| 166 |
+
path: data/table_with_food-*
|
| 167 |
+
- split: switch_on_off
|
| 168 |
+
path: data/switch_on_off-*
|
| 169 |
+
- split: coins
|
| 170 |
+
path: data/coins-*
|
| 171 |
+
- split: smoke_and_steam_exit
|
| 172 |
+
path: data/smoke_and_steam_exit-*
|
| 173 |
+
- split: washing_detergent
|
| 174 |
+
path: data/washing_detergent-*
|
| 175 |
+
- split: air_cleaning_equipments
|
| 176 |
+
path: data/air_cleaning_equipments-*
|
| 177 |
+
- split: tv
|
| 178 |
+
path: data/tv-*
|
| 179 |
+
- split: lightsources_by_bed
|
| 180 |
+
path: data/lightsources_by_bed-*
|
| 181 |
+
- split: wall_
|
| 182 |
+
path: data/wall_-*
|
| 183 |
+
- split: floor
|
| 184 |
+
path: data/floor-*
|
| 185 |
+
- split: clothes
|
| 186 |
+
path: data/clothes-*
|
| 187 |
+
- split: tattoos
|
| 188 |
+
path: data/tattoos-*
|
| 189 |
+
- split: toothbrush
|
| 190 |
+
path: data/toothbrush-*
|
| 191 |
+
- split: trash_waste
|
| 192 |
+
path: data/trash_waste-*
|
| 193 |
+
- split: light_source_in_livingroom
|
| 194 |
+
path: data/light_source_in_livingroom-*
|
| 195 |
+
- split: dish_racks
|
| 196 |
+
path: data/dish_racks-*
|
| 197 |
+
- split: drinking_water
|
| 198 |
+
path: data/drinking_water-*
|
| 199 |
+
- split: phone
|
| 200 |
+
path: data/phone-*
|
| 201 |
+
- split: surroundings
|
| 202 |
+
path: data/surroundings-*
|
| 203 |
+
- split: tabloids
|
| 204 |
+
path: data/tabloids-*
|
| 205 |
+
- split: pen_pencils
|
| 206 |
+
path: data/pen_pencils-*
|
| 207 |
+
- split: tooth_paste
|
| 208 |
+
path: data/tooth_paste-*
|
| 209 |
+
- split: make_up
|
| 210 |
+
path: data/make_up-*
|
| 211 |
+
- split: worship_places
|
| 212 |
+
path: data/worship_places-*
|
| 213 |
+
- split: cigarettes
|
| 214 |
+
path: data/cigarettes-*
|
| 215 |
+
- split: sheep
|
| 216 |
+
path: data/sheep-*
|
| 217 |
+
- split: cups_mugs_glasses
|
| 218 |
+
path: data/cups_mugs_glasses-*
|
| 219 |
+
- split: baking_tools
|
| 220 |
+
path: data/baking_tools-*
|
| 221 |
+
- split: goats
|
| 222 |
+
path: data/goats-*
|
| 223 |
+
- split: dish_washing_brush_cloth
|
| 224 |
+
path: data/dish_washing_brush_cloth-*
|
| 225 |
+
- split: plates
|
| 226 |
+
path: data/plates-*
|
| 227 |
+
- split: waste_dumps
|
| 228 |
+
path: data/waste_dumps-*
|
| 229 |
+
- split: icons
|
| 230 |
+
path: data/icons-*
|
| 231 |
+
- split: meat_or_fish
|
| 232 |
+
path: data/meat_or_fish-*
|
| 233 |
+
- split: wheel_barrow
|
| 234 |
+
path: data/wheel_barrow-*
|
| 235 |
+
- split: water_sources_for_doing_dishes
|
| 236 |
+
path: data/water_sources_for_doing_dishes-*
|
| 237 |
+
- split: soccer_balls
|
| 238 |
+
path: data/soccer_balls-*
|
| 239 |
+
- split: wall_decoration
|
| 240 |
+
path: data/wall_decoration-*
|
| 241 |
+
- split: horses
|
| 242 |
+
path: data/horses-*
|
| 243 |
+
- split: bed_kids
|
| 244 |
+
path: data/bed_kids-*
|
| 245 |
+
- split: contraceptives
|
| 246 |
+
path: data/contraceptives-*
|
| 247 |
+
- split: nicest_shoes
|
| 248 |
+
path: data/nicest_shoes-*
|
| 249 |
+
- split: computer
|
| 250 |
+
path: data/computer-*
|
| 251 |
+
- split: baby_powder
|
| 252 |
+
path: data/baby_powder-*
|
| 253 |
+
- split: family_snapshots
|
| 254 |
+
path: data/family_snapshots-*
|
| 255 |
+
- split: moped_motorcycle
|
| 256 |
+
path: data/moped_motorcycle-*
|
| 257 |
+
- split: most_loved_item
|
| 258 |
+
path: data/most_loved_item-*
|
| 259 |
+
- split: menstruation_pads_tampax
|
| 260 |
+
path: data/menstruation_pads_tampax-*
|
| 261 |
+
- split: youth_culture
|
| 262 |
+
path: data/youth_culture-*
|
| 263 |
+
- split: baking_sheets
|
| 264 |
+
path: data/baking_sheets-*
|
| 265 |
+
- split: tools
|
| 266 |
+
path: data/tools-*
|
| 267 |
+
- split: grains
|
| 268 |
+
path: data/grains-*
|
| 269 |
+
- split: radio
|
| 270 |
+
path: data/radio-*
|
| 271 |
+
- split: rug
|
| 272 |
+
path: data/rug-*
|
| 273 |
+
- split: water_outlet
|
| 274 |
+
path: data/water_outlet-*
|
| 275 |
+
- split: milk_cows_or_bulls
|
| 276 |
+
path: data/milk_cows_or_bulls-*
|
| 277 |
+
- split: oven
|
| 278 |
+
path: data/oven-*
|
| 279 |
+
- split: roof
|
| 280 |
+
path: data/roof-*
|
| 281 |
+
- split: dish_washing_soap
|
| 282 |
+
path: data/dish_washing_soap-*
|
| 283 |
+
- split: smog_bad_air_breathing_protection
|
| 284 |
+
path: data/smog_bad_air_breathing_protection-*
|
| 285 |
+
- split: parking_lot
|
| 286 |
+
path: data/parking_lot-*
|
| 287 |
+
- split: paper
|
| 288 |
+
path: data/paper-*
|
| 289 |
+
- split: knifes
|
| 290 |
+
path: data/knifes-*
|
| 291 |
+
- split: wall_inside
|
| 292 |
+
path: data/wall_inside-*
|
| 293 |
+
- split: snacks
|
| 294 |
+
path: data/snacks-*
|
| 295 |
+
- split: fishes
|
| 296 |
+
path: data/fishes-*
|
| 297 |
+
- split: frontdoor_keys
|
| 298 |
+
path: data/frontdoor_keys-*
|
| 299 |
+
- split: photo_guide_images
|
| 300 |
+
path: data/photo_guide_images-*
|
| 301 |
+
- split: cutlery
|
| 302 |
+
path: data/cutlery-*
|
| 303 |
+
- split: water_purifier_solutions
|
| 304 |
+
path: data/water_purifier_solutions-*
|
| 305 |
+
- split: place_where_eating_dinner
|
| 306 |
+
path: data/place_where_eating_dinner-*
|
| 307 |
+
- split: front_door
|
| 308 |
+
path: data/front_door-*
|
| 309 |
+
- split: family
|
| 310 |
+
path: data/family-*
|
| 311 |
+
- split: home
|
| 312 |
+
path: data/home-*
|
| 313 |
+
- split: latest_furniture_bought
|
| 314 |
+
path: data/latest_furniture_bought-*
|
| 315 |
+
- split: cooking
|
| 316 |
+
path: data/cooking-*
|
| 317 |
+
- split: sources_of_drinking_water
|
| 318 |
+
path: data/sources_of_drinking_water-*
|
| 319 |
+
- split: vegetables
|
| 320 |
+
path: data/vegetables-*
|
| 321 |
+
- split: everyday_shoes
|
| 322 |
+
path: data/everyday_shoes-*
|
| 323 |
+
- split: elevators
|
| 324 |
+
path: data/elevators-*
|
| 325 |
+
- split: favorite_home_decorations
|
| 326 |
+
path: data/favorite_home_decorations-*
|
| 327 |
+
- split: wedding_photos
|
| 328 |
+
path: data/wedding_photos-*
|
| 329 |
+
- split: bedroom
|
| 330 |
+
path: data/bedroom-*
|
| 331 |
+
- split: carrying_water
|
| 332 |
+
path: data/carrying_water-*
|
| 333 |
+
- split: rehabilitation_technology
|
| 334 |
+
path: data/rehabilitation_technology-*
|
| 335 |
+
- split: markets
|
| 336 |
+
path: data/markets-*
|
| 337 |
+
- split: bike
|
| 338 |
+
path: data/bike-*
|
| 339 |
+
- split: bed_hq
|
| 340 |
+
path: data/bed_hq-*
|
| 341 |
+
- split: mosquito_protection
|
| 342 |
+
path: data/mosquito_protection-*
|
| 343 |
+
- split: kitchen_sink
|
| 344 |
+
path: data/kitchen_sink-*
|
| 345 |
+
- split: get_water
|
| 346 |
+
path: data/get_water-*
|
| 347 |
+
- split: hair_brush_comb
|
| 348 |
+
path: data/hair_brush_comb-*
|
| 349 |
+
- split: spices
|
| 350 |
+
path: data/spices-*
|
| 351 |
+
- split: most_loved_toy
|
| 352 |
+
path: data/most_loved_toy-*
|
| 353 |
+
- split: shaving
|
| 354 |
+
path: data/shaving-*
|
| 355 |
+
- split: teeth
|
| 356 |
+
path: data/teeth-*
|
| 357 |
+
- split: wall_clock
|
| 358 |
+
path: data/wall_clock-*
|
| 359 |
+
- split: drying
|
| 360 |
+
path: data/drying-*
|
| 361 |
+
- split: soap_for_hands_and_body
|
| 362 |
+
path: data/soap_for_hands_and_body-*
|
| 363 |
+
- split: transport_of_heavy_things
|
| 364 |
+
path: data/transport_of_heavy_things-*
|
| 365 |
+
- split: horse_stables
|
| 366 |
+
path: data/horse_stables-*
|
| 367 |
+
- split: newspapers
|
| 368 |
+
path: data/newspapers-*
|
| 369 |
+
- split: car_decorations
|
| 370 |
+
path: data/car_decorations-*
|
| 371 |
+
- split: toys
|
| 372 |
+
path: data/toys-*
|
| 373 |
+
- split: cleaning_floors
|
| 374 |
+
path: data/cleaning_floors-*
|
| 375 |
+
- split: alcoholic_drinks
|
| 376 |
+
path: data/alcoholic_drinks-*
|
| 377 |
+
- split: cosmetics
|
| 378 |
+
path: data/cosmetics-*
|
| 379 |
+
- split: soccer_supporter_items
|
| 380 |
+
path: data/soccer_supporter_items-*
|
| 381 |
+
- split: bad_outdoor_air_obstructions
|
| 382 |
+
path: data/bad_outdoor_air_obstructions-*
|
| 383 |
+
- split: social_drink
|
| 384 |
+
path: data/social_drink-*
|
| 385 |
+
- split: cooking_utensils
|
| 386 |
+
path: data/cooking_utensils-*
|
| 387 |
+
- split: skies_outside
|
| 388 |
+
path: data/skies_outside-*
|
| 389 |
+
- split: arm_watch
|
| 390 |
+
path: data/arm_watch-*
|
| 391 |
+
- split: guest_bed
|
| 392 |
+
path: data/guest_bed-*
|
| 393 |
+
- split: ingredients
|
| 394 |
+
path: data/ingredients-*
|
| 395 |
+
- split: replaced
|
| 396 |
+
path: data/replaced-*
|
| 397 |
+
- split: power_outlet
|
| 398 |
+
path: data/power_outlet-*
|
| 399 |
+
- split: ventilation
|
| 400 |
+
path: data/ventilation-*
|
| 401 |
+
- split: bills_of_money
|
| 402 |
+
path: data/bills_of_money-*
|
| 403 |
+
- split: light_source_in_kitchen
|
| 404 |
+
path: data/light_source_in_kitchen-*
|
| 405 |
+
- split: agriculture_land
|
| 406 |
+
path: data/agriculture_land-*
|
| 407 |
+
- split: street_detail
|
| 408 |
+
path: data/street_detail-*
|
| 409 |
+
- split: light_sources
|
| 410 |
+
path: data/light_sources-*
|
| 411 |
+
- split: ceiling
|
| 412 |
+
path: data/ceiling-*
|
| 413 |
+
- split: things_i_wish_i_had
|
| 414 |
+
path: data/things_i_wish_i_had-*
|
| 415 |
+
- split: wall
|
| 416 |
+
path: data/wall-*
|
| 417 |
+
- split: piercings
|
| 418 |
+
path: data/piercings-*
|
| 419 |
+
- split: vegetable_plot
|
| 420 |
+
path: data/vegetable_plot-*
|
| 421 |
+
- split: fields
|
| 422 |
+
path: data/fields-*
|
| 423 |
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- split: source_of_cool
|
| 424 |
+
path: data/source_of_cool-*
|
| 425 |
+
- split: storage_room
|
| 426 |
+
path: data/storage_room-*
|
| 427 |
+
- split: fruits_and_vegetables
|
| 428 |
+
path: data/fruits_and_vegetables-*
|
| 429 |
+
- split: favourite_sports_clubs
|
| 430 |
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path: data/favourite_sports_clubs-*
|
| 431 |
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- split: snack_stores
|
| 432 |
+
path: data/snack_stores-*
|
| 433 |
+
- split: electricity_wires
|
| 434 |
+
path: data/electricity_wires-*
|
| 435 |
+
- split: celebrity_posters
|
| 436 |
+
path: data/celebrity_posters-*
|
| 437 |
+
dataset_info:
|
| 438 |
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features:
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| 439 |
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| 449 |
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| 450 |
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| 451 |
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| 452 |
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| 453 |
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|
| 454 |
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dtype: string
|
| 455 |
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| 456 |
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| 457 |
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+
num_bytes: 135961086.0
|
| 1096 |
+
num_examples: 46
|
| 1097 |
+
- name: snack_stores
|
| 1098 |
+
num_bytes: 288627.0
|
| 1099 |
+
num_examples: 1
|
| 1100 |
+
- name: electricity_wires
|
| 1101 |
+
num_bytes: 2244483.0
|
| 1102 |
+
num_examples: 1
|
| 1103 |
+
- name: celebrity_posters
|
| 1104 |
+
num_bytes: 6966565.0
|
| 1105 |
+
num_examples: 1
|
| 1106 |
+
download_size: 7376078939
|
| 1107 |
+
dataset_size: 134294971337.46701
|
| 1108 |
+
---
|
| 1109 |
+
# Dataset Card for "dollarstreet"
|
| 1110 |
+
|
| 1111 |
+
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|