Dataset Viewer
Auto-converted to Parquet
imagenet_label_idx
stringlengths
1
5
label
stringlengths
3
175
image
imagewidth (px)
37
2.31k
6355
display_window, shop_window, shopwindow, show_window
14407
snowdrift
15592
flibbertigibbet, foolish_woman
3377
wisent, aurochs, Bison_bonasus
9226
pillbox, toque, turban
15939
king, queen, world-beater
8087
lamp
7445
hammer
18523
coelogyne
10174
segmental_arch
16
contact_sport
6571
earmuff
15839
hotelier, hotelkeeper, hotel_manager, hotelman, hosteller
8737
national_monument
13545
process_cheese, processed_cheese
6355
display_window, shop_window, shopwindow, show_window
17342
zamia
14522
Biloxi
5902
control_room
4373
artillery, heavy_weapon, gun, ordnance
13863
sherry
15866
inamorato
8298
love_seat, loveseat, tete-a-tete, vis-a-vis
15474
embryologist
1704
ctenophore, comb_jelly
12633
lemon_curd, lemon_cheese
1925
black-crowned_night_heron, Nycticorax_nycticorax
18157
western_mugwort, white_sage, cudweed, prairie_sage, Artemisia_ludoviciana, Artemisia_gnaphalodes
10342
shrapnel
12709
toast
13599
sweetening, sweetener
12661
bread, breadstuff, staff_of_life
5535
chanter, melody_pipe
3688
coati, coati-mondi, coati-mundi, coon_cat, Nasua_narica
11222
theater, theatre, house
13485
deviled_egg, stuffed_egg
6049
crock, earthenware_jar
19128
scrub_oak
11874
window_envelope
1445
cuckoo
14163
magnetic_pole
13949
gimlet
6960
floor, flooring
924
arboreal_salamander, Aneides_lugubris
5086
broadcloth
8950
overshoe
8523
messuage
2128
killer_whale, killer, orca, grampus, sea_wolf, Orcinus_orca
19146
cork_oak, Quercus_suber
9901
Roman_arch, semicircular_arch
5411
case_knife
715
hill_myna, Indian_grackle, grackle, Gracula_religiosa
6572
earphone, earpiece, headphone, phone
10896
stroboscope, strobe, strobe_light
1847
blue_crab, Callinectes_sapidus
153
handball
13806
blush_wine, pink_wine, rose, rose_wine
5411
case_knife
2350
poodle, poodle_dog
1574
whistling_swan, Cygnus_columbianus_columbianus
6698
Erlenmeyer_flask
14706
South_American_Indian
8483
measuring_instrument, measuring_system, measuring_device
4671
battlement, crenelation, crenellation
9621
rabbit_ears
5057
brick
6392
dolmen, cromlech, portal_tomb
16563
pudge
17938
four_o'clock
6678
entertainment_center
15045
bookbinder
8820
nude, nude_painting
10475
slipknot
19119
bear_oak, Quercus_ilicifolia
13685
macaroni_and_cheese
15571
finder
1622
Tasmanian_devil, ursine_dasyure, Sarcophilus_hariisi
15110
captive
3232
buckskin
13931
cocktail
15822
homegirl
12609
suet_pudding
3613
siamang, Hylobates_syndactylus, Symphalangus_syndactylus
18110
bleeding_heart, lyreflower, lyre-flower, Dicentra_spectabilis
13747
taco
16553
protozoologist
10765
steak_knife
13368
marinade
2300
Old_English_sheepdog, bobtail
607
New_World_flycatcher, flycatcher, tyrant_flycatcher, tyrant_bird
3219
cow_pony
7799
igloo, iglu
14082
oolong
12399
eggdrop_soup
2350
poodle, poodle_dog
13086
pineapple, ananas
16164
ministrant
1947
European_gallinule, Porphyrio_porphyrio
9216
pier_table
9273
pistol, handgun, side_arm, shooting_iron
End of preview. Expand in Data Studio

Introduction

This is a tiny subset of ImageNet (imagenet-w21-wds). For each label, there are 20 sampled images. Those labels that have less than 20 images are skipped.

Citation

Please cite the paper if you use this dataset.

@article{imagenet15russakovsky,
    Author = {Olga Russakovsky and Jia Deng and Hao Su and Jonathan Krause and Sanjeev Satheesh and Sean Ma and Zhiheng Huang and Andrej Karpathy and Aditya Khosla and Michael Bernstein and Alexander C. Berg and Li Fei-Fei},
    Title = { {ImageNet Large Scale Visual Recognition Challenge} },
    Year = {2015},
    journal   = {International Journal of Computer Vision (IJCV)},
    doi = {10.1007/s11263-015-0816-y},
    volume={115},
    number={3},
    pages={211-252}
}
Downloads last month
62