Datasets:
File size: 13,207 Bytes
969c5d4 9c4afd6 969c5d4 9c4afd6 969c5d4 9c4afd6 969c5d4 9c4afd6 969c5d4 4382ca2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 |
---
language:
- en
size_categories:
- 10K<n<100K
task_categories:
- image-classification
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': abbey
'1': airplane cabin
'2': airport terminal
'3': alley
'4': amphitheater
'5': amusement arcade
'6': amusement park
'7': anechoic chamber
'8': apartment building outdoor
'9': apse indoor
'10': aquarium
'11': aqueduct
'12': arch
'13': archive
'14': arrival gate outdoor
'15': art gallery
'16': art school
'17': art studio
'18': assembly line
'19': athletic field outdoor
'20': atrium public
'21': attic
'22': auditorium
'23': auto factory
'24': badlands
'25': badminton court indoor
'26': baggage claim
'27': bakery shop
'28': balcony exterior
'29': balcony interior
'30': ball pit
'31': ballroom
'32': bamboo forest
'33': banquet hall
'34': bar
'35': barn
'36': barndoor
'37': baseball field
'38': basement
'39': basilica
'40': basketball court outdoor
'41': bathroom
'42': batters box
'43': bayou
'44': bazaar indoor
'45': bazaar outdoor
'46': beach
'47': beauty salon
'48': bedroom
'49': berth
'50': biology laboratory
'51': bistro indoor
'52': boardwalk
'53': boat deck
'54': boathouse
'55': bookstore
'56': booth indoor
'57': botanical garden
'58': bow window indoor
'59': bow window outdoor
'60': bowling alley
'61': boxing ring
'62': brewery indoor
'63': bridge
'64': building facade
'65': bullring
'66': burial chamber
'67': bus interior
'68': butchers shop
'69': butte
'70': cabin outdoor
'71': cafeteria
'72': campsite
'73': campus
'74': canal natural
'75': canal urban
'76': candy store
'77': canyon
'78': car interior backseat
'79': car interior frontseat
'80': carrousel
'81': casino indoor
'82': castle
'83': catacomb
'84': cathedral indoor
'85': cathedral outdoor
'86': cavern indoor
'87': cemetery
'88': chalet
'89': cheese factory
'90': chemistry lab
'91': chicken coop indoor
'92': chicken coop outdoor
'93': childs room
'94': church indoor
'95': church outdoor
'96': classroom
'97': clean room
'98': cliff
'99': cloister indoor
'100': closet
'101': clothing store
'102': coast
'103': cockpit
'104': coffee shop
'105': computer room
'106': conference center
'107': conference room
'108': construction site
'109': control room
'110': control tower outdoor
'111': corn field
'112': corral
'113': corridor
'114': cottage garden
'115': courthouse
'116': courtroom
'117': courtyard
'118': covered bridge exterior
'119': creek
'120': crevasse
'121': crosswalk
'122': cubicle office
'123': dam
'124': delicatessen
'125': dentists office
'126': desert sand
'127': desert vegetation
'128': diner indoor
'129': diner outdoor
'130': dinette home
'131': dinette vehicle
'132': dining car
'133': dining room
'134': discotheque
'135': dock
'136': doorway outdoor
'137': dorm room
'138': driveway
'139': driving range outdoor
'140': drugstore
'141': electrical substation
'142': elevator door
'143': elevator interior
'144': elevator shaft
'145': engine room
'146': escalator indoor
'147': excavation
'148': factory indoor
'149': fairway
'150': fastfood restaurant
'151': field cultivated
'152': field wild
'153': fire escape
'154': fire station
'155': firing range indoor
'156': fishpond
'157': florist shop indoor
'158': food court
'159': forest broadleaf
'160': forest needleleaf
'161': forest path
'162': forest road
'163': formal garden
'164': fountain
'165': galley
'166': game room
'167': garage indoor
'168': garbage dump
'169': gas station
'170': gazebo exterior
'171': general store indoor
'172': general store outdoor
'173': gift shop
'174': golf course
'175': greenhouse indoor
'176': greenhouse outdoor
'177': gymnasium indoor
'178': hangar indoor
'179': hangar outdoor
'180': harbor
'181': hayfield
'182': heliport
'183': herb garden
'184': highway
'185': hill
'186': home office
'187': hospital
'188': hospital room
'189': hot spring
'190': hot tub outdoor
'191': hotel outdoor
'192': hotel room
'193': house
'194': hunting lodge outdoor
'195': ice cream parlor
'196': ice floe
'197': ice shelf
'198': ice skating rink indoor
'199': ice skating rink outdoor
'200': iceberg
'201': igloo
'202': industrial area
'203': inn outdoor
'204': islet
'205': jacuzzi indoor
'206': jail cell
'207': jail indoor
'208': jewelry shop
'209': kasbah
'210': kennel indoor
'211': kennel outdoor
'212': kindergarden classroom
'213': kitchen
'214': kitchenette
'215': labyrinth outdoor
'216': lake natural
'217': landfill
'218': landing deck
'219': laundromat
'220': lecture room
'221': library indoor
'222': library outdoor
'223': lido deck outdoor
'224': lift bridge
'225': lighthouse
'226': limousine interior
'227': living room
'228': lobby
'229': lock chamber
'230': locker room
'231': mansion
'232': manufactured home
'233': market indoor
'234': market outdoor
'235': marsh
'236': martial arts gym
'237': mausoleum
'238': medina
'239': moat water
'240': monastery outdoor
'241': mosque indoor
'242': mosque outdoor
'243': motel
'244': mountain
'245': mountain snowy
'246': movie theater indoor
'247': museum indoor
'248': music store
'249': music studio
'250': nuclear power plant outdoor
'251': nursery
'252': oast house
'253': observatory outdoor
'254': ocean
'255': office
'256': office building
'257': oil refinery outdoor
'258': oilrig
'259': operating room
'260': orchard
'261': outhouse outdoor
'262': pagoda
'263': palace
'264': pantry
'265': park
'266': parking garage indoor
'267': parking garage outdoor
'268': parking lot
'269': parlor
'270': pasture
'271': patio
'272': pavilion
'273': pharmacy
'274': phone booth
'275': physics laboratory
'276': picnic area
'277': pilothouse indoor
'278': planetarium outdoor
'279': playground
'280': playroom
'281': plaza
'282': podium indoor
'283': podium outdoor
'284': pond
'285': poolroom establishment
'286': poolroom home
'287': power plant outdoor
'288': promenade deck
'289': pub indoor
'290': pulpit
'291': putting green
'292': racecourse
'293': raceway
'294': raft
'295': railroad track
'296': rainforest
'297': reception
'298': recreation room
'299': residential neighborhood
'300': restaurant
'301': restaurant kitchen
'302': restaurant patio
'303': rice paddy
'304': riding arena
'305': river
'306': rock arch
'307': rope bridge
'308': ruin
'309': runway
'310': sandbar
'311': sandbox
'312': sauna
'313': schoolhouse
'314': sea cliff
'315': server room
'316': shed
'317': shoe shop
'318': shopfront
'319': shopping mall indoor
'320': shower
'321': skatepark
'322': ski lodge
'323': ski resort
'324': ski slope
'325': sky
'326': skyscraper
'327': slum
'328': snowfield
'329': squash court
'330': stable
'331': stadium baseball
'332': stadium football
'333': stage indoor
'334': staircase
'335': street
'336': subway interior
'337': subway station platform
'338': supermarket
'339': sushi bar
'340': swamp
'341': swimming pool indoor
'342': swimming pool outdoor
'343': synagogue indoor
'344': synagogue outdoor
'345': television studio
'346': temple east asia
'347': temple south asia
'348': tennis court indoor
'349': tennis court outdoor
'350': tent outdoor
'351': theater indoor procenium
'352': theater indoor seats
'353': thriftshop
'354': throne room
'355': ticket booth
'356': toll plaza
'357': topiary garden
'358': tower
'359': toyshop
'360': track outdoor
'361': train railway
'362': train station platform
'363': tree farm
'364': tree house
'365': trench
'366': underwater coral reef
'367': utility room
'368': valley
'369': van interior
'370': vegetable garden
'371': veranda
'372': veterinarians office
'373': viaduct
'374': videostore
'375': village
'376': vineyard
'377': volcano
'378': volleyball court indoor
'379': volleyball court outdoor
'380': waiting room
'381': warehouse indoor
'382': water tower
'383': waterfall block
'384': waterfall fan
'385': waterfall plunge
'386': watering hole
'387': wave
'388': wet bar
'389': wheat field
'390': wind farm
'391': windmill
'392': wine cellar barrel storage
'393': wine cellar bottle storage
'394': wrestling ring indoor
'395': yard
'396': youth hostel
splits:
- name: train
num_bytes: 8834961188.3
num_examples: 19850
- name: test
num_bytes: 8610045383.95
num_examples: 19850
download_size: 14498373101
dataset_size: 17445006572.25
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
# SUN397 dataset
The database contains 397 categories subset from the SUN dataset for Scene Recognition used in the following paper.
The number of images varies across categories, but there are at least 100 images per category, and 108,754 images in total.
All images are in jpg format. The images provided here are for research purposes only.
The file ClassName.txt contains the name list for the 397 categories.
Please cite the following paper if you use this dataset in your research.
J. Xiao, J. Hays, K. Ehinger, A. Oliva, and A. Torralba.
SUN Database: Large-scale Scene Recognition from Abbey to Zoo.
Proceedings of 23rd IEEE Conference on Computer Vision and Pattern Recognition (CVPR2010).
Please visit our project webpage for more information:
http://groups.csail.mit.edu/vision/SUN/
## Usage
```python
from datasets import load_dataset
dataset = load_dataset('tanganke/sun397')
``` |