Datasets:
red_caps

Task Categories: image-to-text
Languages: en
Multilinguality: monolingual
Size Categories: 10M<n<100M
Licenses: cc-by-4.0
Language Creators: found
Annotations Creators: found
Source Datasets: original
Dataset Preview Go to dataset viewer
image_id (string)author (string)image_url (image)raw_caption (string)caption (string)subreddit (class label)score (int)created_utc (json)permalink (string)crosspost_parents (json)
h63b1
None
USSR time abandoned appliances in some factory [602px × 400px]
ussr time abandoned appliances in some factory
0 (abandonedporn)
10
1304778854
/r/AbandonedPorn/comments/h63b1/ussr_time_abandoned_appliances_in_some_factory/
h63gy
None
Abandoned alley in Porto, Portugal [1067px × 1572px]
abandoned alley in porto, portugal
0 (abandonedporn)
11
1304779505
/r/AbandonedPorn/comments/h63gy/abandoned_alley_in_porto_portugal_1067px_1572px/
h63j5
None
MIG 21 at an abandoned Russian military base [1024px × 768px]
mig 21 at an abandoned russian military base
0 (abandonedporn)
11
1304779814
/r/AbandonedPorn/comments/h63j5/mig_21_at_an_abandoned_russian_military_base/
h66gx
None
Me standing in front of one of many hangars in abandoned USSR military airport in Vaiņode, Latvia, EU [2592px × 1944px]
me standing in front of one of many hangars in abandoned ussr military airport in vainode, latvia, eu
0 (abandonedporn)
8
1304789605
/r/AbandonedPorn/comments/h66gx/me_standing_in_front_of_one_of_many_hangars_in/
h6kzq
None
Abandoned BRDM-2 in Pripyat, Ukraine [1200px × 900px]
abandoned brdm-2 in pripyat, ukraine
0 (abandonedporn)
10
1304842770
/r/AbandonedPorn/comments/h6kzq/abandoned_brdm2_in_pripyat_ukraine_1200px_900px/
h6l1p
None
Bathroom in Chernobyl, Ukraine
bathroom in chernobyl, ukraine
0 (abandonedporn)
13
1304843139
/r/AbandonedPorn/comments/h6l1p/bathroom_in_chernobyl_ukraine/
h6ral
None
Abandoned barn in Gadsden County, FL [500x440]
abandoned barn in gadsden county, fl
0 (abandonedporn)
12
1304879305
/r/AbandonedPorn/comments/h6ral/abandoned_barn_in_gadsden_county_fl_500x440/
h6rvv
None
Soviet gas mask left on the ground [2592px × 1944px]
soviet gas mask left on the ground
0 (abandonedporn)
12
1304881243
/r/AbandonedPorn/comments/h6rvv/soviet_gas_mask_left_on_the_ground_2592px_1944px/
h6s07
None
Inside abandoned electronics factory, Riga, LV [2592px × 1944px]
inside abandoned electronics factory, riga, lv
0 (abandonedporn)
14
1304881610
/r/AbandonedPorn/comments/h6s07/inside_abandoned_electronics_factory_riga_lv/
h8718
None
Railway tunnel in Clinton, Massachusetts
railway tunnel in clinton, massachusetts
0 (abandonedporn)
19
1305043157
/r/AbandonedPorn/comments/h8718/railway_tunnel_in_clinton_massachusetts/
h873w
None
Train in Onverwacht, Suriname [2383px × 1787px]
train in onverwacht, suriname
0 (abandonedporn)
14
1305043347
/r/AbandonedPorn/comments/h873w/train_in_onverwacht_suriname_2383px_1787px/
h8753
None
Abandoned forest bridge [1843px × 1152px]
abandoned forest bridge
0 (abandonedporn)
22
1305043413
/r/AbandonedPorn/comments/h8753/abandoned_forest_bridge_1843px_1152px/
h96vi
None
Church in Philippines [2016px × 1512px]
church in philippines
0 (abandonedporn)
20
1305143640
/r/AbandonedPorn/comments/h96vi/church_in_philippines_2016px_1512px/
h96wl
None
Ships in the sea [2560px × 1920px]
ships in the sea
0 (abandonedporn)
26
1305143708
/r/AbandonedPorn/comments/h96wl/ships_in_the_sea_2560px_1920px/
h970n
None
Portrairge waterford, Aral sea [1600px × 1200px]
portrairge waterford, aral sea
0 (abandonedporn)
11
1305143961
/r/AbandonedPorn/comments/h970n/portrairge_waterford_aral_sea_1600px_1200px/
h973e
None
HDR ship in Aral sea [1600px × 1068px]
hdr ship in aral sea
0 (abandonedporn)
7
1305144118
/r/AbandonedPorn/comments/h973e/hdr_ship_in_aral_sea_1600px_1068px/
han5s
None
Foggy USSR bunker in the sea, Karosta, Latvia [3072px × 2304px]
foggy ussr bunker in the sea, karosta, latvia
0 (abandonedporn)
22
1305304195
/r/AbandonedPorn/comments/han5s/foggy_ussr_bunker_in_the_sea_karosta_latvia/
han7h
None
Theater [2257px × 1505px]
theater
0 (abandonedporn)
20
1305304320
/r/AbandonedPorn/comments/han7h/theater_2257px_1505px/
han9q
None
Unfinished 5 story house, Karosta, Latvia [1246px × 701px]
unfinished 5 story house, karosta, latvia
0 (abandonedporn)
13
1305304481
/r/AbandonedPorn/comments/han9q/unfinished_5_story_house_karosta_latvia_1246px/
hc0od
None
Abandoned Clown Train (x-post from /r/wtf)
abandoned clown train
0 (abandonedporn)
20
1305490519
/r/AbandonedPorn/comments/hc0od/abandoned_clown_train_xpost_from_rwtf/
hhhtu
matttebbetts
x-post, awesome abandoned castle
x-post, awesome abandoned castle
0 (abandonedporn)
6
1306094893
/r/AbandonedPorn/comments/hhhtu/xpost_awesome_abandoned_castle/
hjzlj
None
Old coal mine [1600px × 1200px]
old coal mine
0 (abandonedporn)
17
1306348724
/r/AbandonedPorn/comments/hjzlj/old_coal_mine_1600px_1200px/
hk488
None
Namibia diamond mines [3000px × 2249px]
namibia diamond mines
0 (abandonedporn)
29
1306358800
/r/AbandonedPorn/comments/hk488/namibia_diamond_mines_3000px_2249px/
ihcga
Satanicbearmaster
Abandoned mill in Ballymore, Ireland.
abandoned mill in ballymore, ireland.
0 (abandonedporn)
19
1309888523
/r/AbandonedPorn/comments/ihcga/abandoned_mill_in_ballymore_ireland/
int4a
DivineMayhem
Abandoned Pool at Western Center
abandoned pool at western center
0 (abandonedporn)
24
1310506284
/r/AbandonedPorn/comments/int4a/abandoned_pool_at_western_center/
iz09c
opals25
Deconstruction
deconstruction
0 (abandonedporn)
7
1311580501
/r/AbandonedPorn/comments/iz09c/deconstruction/
iz7mu
JeremyEye
Abandoned Brewery in Mahanoy City, PA
abandoned brewery in mahanoy city, pa
0 (abandonedporn)
47
1311605467
/r/AbandonedPorn/comments/iz7mu/abandoned_brewery_in_mahanoy_city_pa/
izc1u
None
Buttons [1944 x 2592]
buttons
0 (abandonedporn)
4
1311614624
/r/AbandonedPorn/comments/izc1u/buttons_1944_x_2592/
izc8j
None
I have found Гражданский Противогаз-5 the other day [2592 x 1944]
i have found -5 the other day
0 (abandonedporn)
10
1311614988
/r/AbandonedPorn/comments/izc8j/i_have_found_гражданский_противогаз5_the_other/
j0ip0
L4MB
Charles Camsell Hospital, Edmonton
charles camsell hospital, edmonton
0 (abandonedporn)
23
1311714457
/r/AbandonedPorn/comments/j0ip0/charles_camsell_hospital_edmonton/
j144m
None
Old infirmary building in a derelict leadworks - Newcastle, UK [4209x2806]
old infirmary building in a derelict leadworks - newcastle, uk
0 (abandonedporn)
20
1311771263
/r/AbandonedPorn/comments/j144m/old_infirmary_building_in_a_derelict_leadworks/
j1pl5
skylr
View of Denver from Roof of Abandoned Rubber Factory
view of denver from roof of abandoned rubber factory
0 (abandonedporn)
51
1311815270
/r/AbandonedPorn/comments/j1pl5/view_of_denver_from_roof_of_abandoned_rubber/
j3y6s
meltingice
Sunken Pride (shrimping boat)
sunken pride
0 (abandonedporn)
7
1312006212
/r/AbandonedPorn/comments/j3y6s/sunken_pride_shrimping_boat/
j45xd
BlueScreen
Geauga Lake Amusment Park Midway circa 2010 [2274x1706]
geauga lake amusment park midway circa 2010
0 (abandonedporn)
13
1312040209
/r/AbandonedPorn/comments/j45xd/geauga_lake_amusment_park_midway_circa_2010/
j5aoi
videoj
Bodie Ca. General Store [1024x1024]
bodie ca. general store
0 (abandonedporn)
35
1312165508
/r/AbandonedPorn/comments/j5aoi/bodie_ca_general_store_1024x1024/
j5bps
BlueScreen
Rusting Remnants - Found in the woods at Punderson State Park [2350x1405]
rusting remnants - found in the woods at punderson state park
0 (abandonedporn)
28
1312167835
/r/AbandonedPorn/comments/j5bps/rusting_remnants_found_in_the_woods_at_punderson/
j6jqd
BlueScreen
Antique Car Ride at the (Now Defunct) Geauga Lake Park, in Ohio [2538x1903]
antique car ride at the geauga lake park, in ohio
0 (abandonedporn)
18
1312276325
/r/AbandonedPorn/comments/j6jqd/antique_car_ride_at_the_now_defunct_geauga_lake/
j6jsc
BlueScreen
Geauga Lake Park Main Entrance [2571x1928]
geauga lake park main entrance
0 (abandonedporn)
9
1312276555
/r/AbandonedPorn/comments/j6jsc/geauga_lake_park_main_entrance_2571x1928/
j72qr
FraeRitter
Old freedom. Abandoned bus, Czechia. [3264x2448]
old freedom. abandoned bus, czechia.
0 (abandonedporn)
31
1312319829
/r/AbandonedPorn/comments/j72qr/old_freedom_abandoned_bus_czechia_3264x2448/
j839q
Azorian77
Aral Sea, Rusting Shipwreck [1600x1200]
aral sea, rusting shipwreck
0 (abandonedporn)
57
1312403555
/r/AbandonedPorn/comments/j839q/aral_sea_rusting_shipwreck_1600x1200/
j86qq
soupyhands
Lincolnshire County Lunatic Asylum [1600x1049]
lincolnshire county lunatic asylum
0 (abandonedporn)
20
1312410015
/r/AbandonedPorn/comments/j86qq/lincolnshire_county_lunatic_asylum_1600x1049/
j8mtt
None
Deserted buildings near the Gold King Mine, Arizona [1164×788]
deserted buildings near the gold king mine, arizona
0 (abandonedporn)
27
1312446853
/r/AbandonedPorn/comments/j8mtt/deserted_buildings_near_the_gold_king_mine/
j93u9
skylr
Palmerton, PA: Zinc Smelting Plant (Crosspost from r/abandoned)
palmerton, pa: zinc smelting plant
0 (abandonedporn)
19
1312485863
/r/AbandonedPorn/comments/j93u9/palmerton_pa_zinc_smelting_plant_crosspost_from/
j9acx
skylr
Buildings at Fort Ord in Monterey, California [1024 x 680]
buildings at fort ord in monterey, california
0 (abandonedporn)
5
1312497800
/r/AbandonedPorn/comments/j9acx/buildings_at_fort_ord_in_monterey_california_1024/
j9v8o
None
The Hayden Flour Mill, downtown Tempe, AZ [1600x1200]
the hayden flour mill, downtown tempe, az
0 (abandonedporn)
16
1312553550
/r/AbandonedPorn/comments/j9v8o/the_hayden_flour_mill_downtown_tempe_az_1600x1200/
ja0yi
skylr
Sterling Sugar Mill, Sterling Colorado by Drew Winners [680 x 1024]
sterling sugar mill, sterling colorado by drew winners
0 (abandonedporn)
12
1312564441
/r/AbandonedPorn/comments/ja0yi/sterling_sugar_mill_sterling_colorado_by_drew/
jadjh
sixstringkeys
Tracks to Nowhere.
tracks to nowhere.
0 (abandonedporn)
68
1312590449
/r/AbandonedPorn/comments/jadjh/tracks_to_nowhere/
jawpf
skylr
Atlas D Missile Silo [1024 x 465]
atlas d missile silo
0 (abandonedporn)
35
1312652274
/r/AbandonedPorn/comments/jawpf/atlas_d_missile_silo_1024_x_465/
jaxt8
skylr
Abandoned Power Plant [1024 x 768]
abandoned power plant
0 (abandonedporn)
20
1312654937
/r/AbandonedPorn/comments/jaxt8/abandoned_power_plant_1024_x_768/
jay8e
skylr
Abandoned Dog Track, Loveland, CO [1000 x 750]
abandoned dog track, loveland, co
0 (abandonedporn)
31
1312655980
/r/AbandonedPorn/comments/jay8e/abandoned_dog_track_loveland_co_1000_x_750/
jb4oz
soniccows
left for the elements... [2707x1800]
left for the elements...
0 (abandonedporn)
70
1312672327
/r/AbandonedPorn/comments/jb4oz/left_for_the_elements_2707x1800/
jbhdc
Highonthedownlow
"Pleasure Beach" [1183 x 602]
"pleasure beach"
0 (abandonedporn)
27
1312715026
/r/AbandonedPorn/comments/jbhdc/pleasure_beach_1183_x_602/
jbi97
None
Farmhouse [1600x919]
farmhouse
0 (abandonedporn)
62
1312720113
/r/AbandonedPorn/comments/jbi97/farmhouse_1600x919/
jbikj
None
Two Guns, Arizona [1200x769]
two guns, arizona
0 (abandonedporn)
50
1312721795
/r/AbandonedPorn/comments/jbikj/two_guns_arizona_1200x769/
jbkht
kraven420
Abandoned high-rise, Eastern Germany
abandoned high-rise, eastern germany
0 (abandonedporn)
11
1312729558
/r/AbandonedPorn/comments/jbkht/abandoned_highrise_eastern_germany/
jbsup
skylr
Abandoned Farm in Leyden, Colorado
abandoned farm in leyden, colorado
0 (abandonedporn)
19
1312752058
/r/AbandonedPorn/comments/jbsup/abandoned_farm_in_leyden_colorado/
jc3v1
None
Michigan Central Station, Detroit [3006x1998]
michigan central station, detroit
0 (abandonedporn)
66
1312778436
/r/AbandonedPorn/comments/jc3v1/michigan_central_station_detroit_3006x1998/
jd2b6
_Q1000_
Staten Island Boat Graveyard, NY [1440x900]
staten island boat graveyard, ny
0 (abandonedporn)
55
1312856409
/r/AbandonedPorn/comments/jd2b6/staten_island_boat_graveyard_ny_1440x900/
jdyf8
skylr
Great Western Sugar Mill, Longmont, Colorado [600 x 450]
great western sugar mill, longmont, colorado
0 (abandonedporn)
28
1312928226
/r/AbandonedPorn/comments/jdyf8/great_western_sugar_mill_longmont_colorado_600_x/
jea9c
priapic_horse
UFO pod houses in San Zhi
ufo pod houses in san zhi
0 (abandonedporn)
40
1312952918
/r/AbandonedPorn/comments/jea9c/ufo_pod_houses_in_san_zhi/
jfb2l
SlowGT
Abandoned smelting plant in Newtown, CT [2916x1944]
abandoned smelting plant in newtown, ct
0 (abandonedporn)
81
1313032589
/r/AbandonedPorn/comments/jfb2l/abandoned_smelting_plant_in_newtown_ct_2916x1944/
jgmwj
None
Hunting lodge in Dob Park, North Yorkshire [1024x861]
hunting lodge in dob park, north yorkshire
0 (abandonedporn)
55
1313143045
/r/AbandonedPorn/comments/jgmwj/hunting_lodge_in_dob_park_north_yorkshire_1024x861/
jh8of
allisgolden
Abandoned Nuclear Plant
abandoned nuclear plant
0 (abandonedporn)
104
1313190981
/r/AbandonedPorn/comments/jh8of/abandoned_nuclear_plant/
jhbl5
SlowGT
Another shot of the smelting plant in CT
another shot of the smelting plant in ct
0 (abandonedporn)
18
1313198293
/r/AbandonedPorn/comments/jhbl5/another_shot_of_the_smelting_plant_in_ct/
jhdhs
Camio
Enchanted Forest Amusement Park, Maryland [Collection]
enchanted forest amusement park, maryland
0 (abandonedporn)
17
1313203051
/r/AbandonedPorn/comments/jhdhs/enchanted_forest_amusement_park_maryland/
jjgy6
anfeline
Old street car (xpost from MachinePorn)[1024x683]
old street car
0 (abandonedporn)
62
1313425131
/r/AbandonedPorn/comments/jjgy6/old_street_car_xpost_from_machineporn1024x683/
jjuxr
skylr
Abandoned Russian Space Shuttle Project [1100 x 733]
abandoned russian space shuttle project
0 (abandonedporn)
19
1313449526
/r/AbandonedPorn/comments/jjuxr/abandoned_russian_space_shuttle_project_1100_x_733/
jk4lb
Looorney
Lady Rana Shipwrecked at Sharjah, UAE [1100x674]
lady rana shipwrecked at sharjah, uae
0 (abandonedporn)
60
1313468284
/r/AbandonedPorn/comments/jk4lb/lady_rana_shipwrecked_at_sharjah_uae_1100x674/
jke2p
None
Tank [3872 x 2592]
tank
0 (abandonedporn)
32
1313496935
/r/AbandonedPorn/comments/jke2p/tank_3872_x_2592/
jkv3c
None
Chinese Factory [1000x797] © Edward Burtynsky
chinese factory edward burtynsky
0 (abandonedporn)
34
1313528242
/r/AbandonedPorn/comments/jkv3c/chinese_factory_1000x797_edward_burtynsky/
jlvzy
skylr
Abandoned Space Shuttle Launch Site, Russia [1100 x 733]
abandoned space shuttle launch site, russia
0 (abandonedporn)
70
1313608189
/r/AbandonedPorn/comments/jlvzy/abandoned_space_shuttle_launch_site_russia_1100_x/
jn369
k-dawg
Satan's Cave [2048 x 1536]
satan's cave
0 (abandonedporn)
4
1313697092
/r/AbandonedPorn/comments/jn369/satans_cave_2048_x_1536/
joo2h
omnomolog
Repost from pics - Alcatraz industry room
repost from pics - alcatraz industry room
0 (abandonedporn)
43
1313822652
/r/AbandonedPorn/comments/joo2h/repost_from_pics_alcatraz_industry_room/
joxcf
chiuta
Old House in Ohio
old house in ohio
0 (abandonedporn)
35
1313857695
/r/AbandonedPorn/comments/joxcf/old_house_in_ohio/
jp602
nickskater09
1965 Buick Skylark left for dead [1280x960]
1965 buick skylark left for dead
0 (abandonedporn)
24
1313878807
/r/AbandonedPorn/comments/jp602/1965_buick_skylark_left_for_dead_1280x960/
jpbuu
None
Ancient Maya Ruins of Yaxchilan, Mexico [4000x3000]
ancient maya ruins of yaxchilan, mexico
0 (abandonedporn)
45
1313893803
/r/AbandonedPorn/comments/jpbuu/ancient_maya_ruins_of_yaxchilan_mexico_4000x3000/
jqplg
Russss
Red Sands Sea Fort in the Thames Estuary [2000x1342]
red sands sea fort in the thames estuary
0 (abandonedporn)
143
1314030821
/r/AbandonedPorn/comments/jqplg/red_sands_sea_fort_in_the_thames_estuary_2000x1342/
jukpq
SialoquentProof
The Fisher 21 Body Plant, Detroit MI. You never forget your first... [1600x1067]
the fisher 21 body plant, detroit mi. you never forget your first...
0 (abandonedporn)
21
1314316998
/r/AbandonedPorn/comments/jukpq/the_fisher_21_body_plant_detroit_mi_you_never/
juykx
None
Sunken [993x1050]
sunken
0 (abandonedporn)
37
1314349634
/r/AbandonedPorn/comments/juykx/sunken_993x1050/
juyna
None
School for Girls [1600x1200]
school for girls
0 (abandonedporn)
284
1314349892
/r/AbandonedPorn/comments/juyna/school_for_girls_1600x1200/
jw036
None
Deserted Boats [1400x900]
deserted boats
0 (abandonedporn)
35
1314436157
/r/AbandonedPorn/comments/jw036/deserted_boats_1400x900/
jwaj7
rozbryzg
Abandoned stage
abandoned stage
0 (abandonedporn)
150
1314470203
/r/AbandonedPorn/comments/jwaj7/abandoned_stage/
jww2r
Hyperguy20
90 year old abandoned factory preserved by the volcanic ash, White Island, New Zealand
90 year old abandoned factory preserved by the volcanic ash, white island, new zealand
0 (abandonedporn)
76
1314522441
/r/AbandonedPorn/comments/jww2r/90_year_old_abandoned_factory_preserved_by_the/
jxg30
dickjones
Abandoned farm house. I would have gotten pictures from the inside but was wearing sandals. :(
abandoned farm house. i would have gotten pictures from the inside but was wearing sandals. :(
0 (abandonedporn)
57
1314577314
/r/AbandonedPorn/comments/jxg30/abandoned_farm_house_i_would_have_gotten_pictures/
jxm64
theskippertoo
Remnants of abandoned and razed neighborhood outside of Cleveland, OH [2707 x 1800]
remnants of abandoned and razed neighborhood outside of cleveland, oh
0 (abandonedporn)
80
1314589649
/r/AbandonedPorn/comments/jxm64/remnants_of_abandoned_and_razed_neighborhood/
k2hqf
popcapps
Andrew Carnegie's vacation home (Johnstown, PA)
andrew carnegie's vacation home
0 (abandonedporn)
58
1314974517
/r/AbandonedPorn/comments/k2hqf/andrew_carnegies_vacation_home_johnstown_pa/
k2rj1
None
Abandoned house ~ Hoadley, AB
abandoned house ~ hoadley, ab
0 (abandonedporn)
13
1314990722
/r/AbandonedPorn/comments/k2rj1/abandoned_house_hoadley_ab/
k3fg9
Ewish32
Train tracks to no where [800x533]
train tracks to no where
0 (abandonedporn)
70
1315046741
/r/AbandonedPorn/comments/k3fg9/train_tracks_to_no_where_800x533/
k3qf9
Mind_Virus
This Mill was Abandoned in 1866. in Sorrento, Italy [965x1286]
this mill was abandoned in 1866. in sorrento, italy
0 (abandonedporn)
190
1315078268
/r/AbandonedPorn/comments/k3qf9/this_mill_was_abandoned_in_1866_in_sorrento_italy/
k41jx
mod83
Found some WWII tunnels in rural Hong Kong. They were inscribed with London landmarks by homesick soldiers.
found some wwii tunnels in rural hong kong. they were inscribed with london landmarks by homesick soldiers.
0 (abandonedporn)
18
1315104707
/r/AbandonedPorn/comments/k41jx/found_some_wwii_tunnels_in_rural_hong_kong_they/
k46br
BlueScreen
A long dead Sherman [1600x1200]
a long dead sherman
0 (abandonedporn)
189
1315117231
/r/AbandonedPorn/comments/k46br/a_long_dead_sherman_1600x1200/
k4e9n
Merru
Abandoned Power Plant In Yonkers.
abandoned power plant in yonkers.
0 (abandonedporn)
11
1315148504
/r/AbandonedPorn/comments/k4e9n/abandoned_power_plant_in_yonkers/
k4z4v
None
Amusement park in Germany [1932x1348]
amusement park in germany
0 (abandonedporn)
29
1315193746
/r/AbandonedPorn/comments/k4z4v/amusement_park_in_germany_1932x1348/
k4za7
None
Staircase in the once elegant reception area of the Bracebridge Health Asylum, Lincolnshire. Built 1852, closed 1989. [2000x1332]
staircase in the once elegant reception area of the bracebridge health asylum, lincolnshire. built 1852, closed 1989.
0 (abandonedporn)
180
1315194026
/r/AbandonedPorn/comments/k4za7/staircase_in_the_once_elegant_reception_area_of/
k546e
MooseBear
Desolate Bridge [900×597]
desolate bridge
0 (abandonedporn)
38
1315205520
/r/AbandonedPorn/comments/k546e/desolate_bridge_900597/
k55th
None
A basket ball court in a Nazi military barracks, Germany, looks like an old grass mat after years of water damage. [1900x2759]
a basket ball court in a nazi military barracks, germany, looks like an old grass mat after years of water damage.
0 (abandonedporn)
49
1315210180
/r/AbandonedPorn/comments/k55th/a_basket_ball_court_in_a_nazi_military_barracks/
k5dyn
JTPlatnum
Red Apple Rest(stop) near Bear Mountain, NY
red apple rest near bear mountain, ny
0 (abandonedporn)
34
1315235999
/r/AbandonedPorn/comments/k5dyn/red_apple_reststop_near_bear_mountain_ny/
k5llz
None
"Voodoo House" in Mauritius [1024x677]
"voodoo house" in mauritius
0 (abandonedporn)
30
1315250045
/r/AbandonedPorn/comments/k5llz/voodoo_house_in_mauritius_1024x677/
k5mfm
JTPlatnum
The beach outside Bayview Projects in Coney Island, NY [1227 x 814]
the beach outside bayview projects in coney island, ny
0 (abandonedporn)
43
1315251611
/r/AbandonedPorn/comments/k5mfm/the_beach_outside_bayview_projects_in_coney/
k5yv3
JTPlatnum
Abandoned private airport hangar in Brooklyn, NY [2513x1885]
abandoned private airport hangar in brooklyn, ny
0 (abandonedporn)
61
1315275458
/r/AbandonedPorn/comments/k5yv3/abandoned_private_airport_hangar_in_brooklyn_ny/
End of preview (truncated to 100 rows)

Dataset Card for RedCaps

Dataset Summary

RedCaps is a large-scale dataset of 12M image-text pairs collected from Reddit. Images and captions from Reddit depict and describe a wide variety of objects and scenes. The data is collected from a manually curated set of subreddits (350 total), which give coarse image labels and allow steering of the dataset composition without labeling individual instances. RedCaps data is created by the people, for the people – it contains everyday things that users like to share on social media, for example hobbies (r/crafts) and pets (r/shiba). Captions often contain specific and fine-grained descriptions (northern cardinal, taj mahal). Subreddit names provide relevant image labels (r/shiba) even when captions may not (mlem!), and sometimes may group many visually unrelated images through a common semantic meaning (r/perfectfit).

Dataset Preprocessing

This dataset doesn't download the images locally by default. Instead, it exposes URLs to the images. To fetch the images, use the following code:

from concurrent.futures import ThreadPoolExecutor
from functools import partial
import io
import urllib

import PIL.Image

from datasets import load_dataset
from datasets.utils.file_utils import get_datasets_user_agent


USER_AGENT = get_datasets_user_agent()


def fetch_single_image(image_url, timeout=None, retries=0):
    for _ in range(retries + 1):
        try:
            request = urllib.request.Request(
                image_url,
                data=None,
                headers={"user-agent": USER_AGENT},
            )
            with urllib.request.urlopen(request, timeout=timeout) as req:
                image = PIL.Image.open(io.BytesIO(req.read()))
            break
        except Exception:
            image = None
    return image


def fetch_images(batch, num_threads, timeout=None, retries=0):
    fetch_single_image_with_args = partial(fetch_single_image, timeout=timeout, retries=retries)
    with ThreadPoolExecutor(max_workers=num_threads) as executor:
        batch["image"] = list(executor.map(fetch_single_image_with_args, batch["image_url"]))
    return batch


num_threads = 20
dset = load_dataset("red_caps", "rabbits_2017")
dset = dset.map(fetch_images, batched=True, batch_size=100, fn_kwargs={"num_threads": num_threads})

Some image links point to more than one image. You can process and downloaded those as follows:

from concurrent.futures import ThreadPoolExecutor
from functools import partial
import io
import os
import re
import urllib

import PIL.Image

import datasets
from datasets import load_dataset
from datasets.utils.file_utils import get_datasets_user_agent


USER_AGENT = get_datasets_user_agent()


def fetch_single_image(image_url, timeout=None, retries=0):
    for _ in range(retries + 1):
        try:
            request = urllib.request.Request(
                image_url,
                data=None,
                headers={"user-agent": USER_AGENT},
            )
            with urllib.request.urlopen(request, timeout=timeout) as req:
                image = PIL.Image.open(io.BytesIO(req.read()))
            break
        except Exception:
            image = None
    return image


def fetch_images(batch, num_threads, timeout=None, retries=0):
    fetch_single_image_with_args = partial(fetch_single_image, timeout=timeout, retries=retries)
    with ThreadPoolExecutor(max_workers=num_threads) as executor:
        batch["image"] = list(executor.map(lambda image_urls: [fetch_single_image_with_args(image_url) for image_url in image_urls], batch["image_url"]))
    return batch


def process_image_urls(batch):
    processed_batch_image_urls = []
    for image_url in batch["image_url"]:
        processed_example_image_urls = []
        image_url_splits = re.findall(r"http\S+", image_url)
        for image_url_split in image_url_splits:
            if "imgur" in image_url_split and "," in image_url_split:
                for image_url_part in image_url_split.split(","):
                    if not image_url_part:
                        continue
                    image_url_part = image_url_part.strip()
                    root, ext = os.path.splitext(image_url_part)
                    if not root.startswith("http"):
                      root = "http://i.imgur.com/" + root
                    root = root.split("#")[0]
                    if not ext:
                      ext = ".jpg"
                    ext = re.split(r"[?%]", ext)[0]
                    image_url_part = root + ext
                    processed_example_image_urls.append(image_url_part)
            else:
                processed_example_image_urls.append(image_url_split)
        processed_batch_image_urls.append(processed_example_image_urls)
    batch["image_url"] = processed_batch_image_urls
    return batch


dset = load_dataset("red_caps", "rabbits_2017")
dset = dset.map(process_image_urls, batched=True, num_proc=4)
features = dset["train"].features.copy()
features["image"] = datasets.Sequence(datasets.Image())
num_threads = 20
dset = dset.map(fetch_images, batched=True, batch_size=100, features=features, fn_kwargs={"num_threads": num_threads})

Note that in the above code, we use the datasets.Sequence feature to represent a list of images for the multi-image links.

Supported Tasks and Leaderboards

From the paper:

We have used our dataset to train deep neural networks that perform image captioning, and that learn transferable visual representations for a variety of downstream visual recognition tasks (image classification, object detection, instance segmentation).

We anticipate that the dataset could be used for a variety of vision-and-language (V&L) tasks, such as image or text retrieval or text-to-image synthesis.

Languages

All of the subreddits in RedCaps use English as their primary language.

Dataset Structure

Data Instances

Each instance in RedCaps represents a single Reddit image post:

{
  'image_id': 'bpzj7r',
  'author': 'djasz1',
  'image_url': 'https://i.redd.it/ho0wntksivy21.jpg',
  'raw_caption': 'Found on a friend’s property in the Keys FL. She is now happily living in my house.',
  'caption': 'found on a friend's property in the keys fl. she is now happily living in my house.', 'subreddit': 3,
  'score': 72,
  'created_utc': datetime.datetime(2019, 5, 18, 1, 36, 41),
  'permalink': '/r/airplants/comments/bpzj7r/found_on_a_friends_property_in_the_keys_fl_she_is/', 'crosspost_parents': None
}

Data Fields

  • image_id: Unique alphanumeric ID of the image post (assigned by Reddit).
  • author: Reddit username of the image post author.
  • image_url: Static URL for downloading the image associated with the post.
  • raw_caption: Textual description of the image, written by the post author.
  • caption: Cleaned version of "raw_caption" by us (see Q35).
  • subreddit: Name of subreddit where the post was submitted.
  • score: Net upvotes (discounting downvotes) received by the image post. This field is equal to None if the image post is a crosspost.
  • created_utc: Integer time epoch (in UTC) when the post was submitted to Reddit.
  • permalink: Partial URL of the Reddit post (https://reddit.com/).
  • crosspost_parents: List of parent posts. This field is optional.

Data Splits

All the data is contained in training set. The training set has nearly 12M (12,011,111) instances.

From the paper:

We intend our dataset to be primarily used for pre-training with one or more specific downstream task(s) in mind. Hence, all instances in our dataset would be used for training while the validation split is derived from downstream task(s). If users require a validation split, we recommend sampling it such that it follows the same subreddit distribution as entire dataset.

Dataset Creation

Curation Rationale

From the paper:

Large datasets of image-text pairs are widely used for pre-training generic representations that transfer to a variety of downstream vision and vision-and-language tasks. Existing public datasets of this kind were curated from search engine results (SBU Captions [1]) or HTML alt-text from arbitrary web pages (Conceptual Captions [2, 31]). They performed complex data filtering to deal with noisy web data. Due to aggressive filtering, their data collection is inefficient and diversity is artificially supressed. We argue that the quality of data depends on its source, and the human intent behind its creation. In this work, we explore Reddit – a social media platform, for curating high quality data. We introduce RedCaps – a large dataset of 12M image-text pairs from Reddit. While we expect the use-cases of RedCaps to be similar to existing datasets, we discuss how Reddit as a data source leads to fast and lightweight collection, better data quality, lets us easily steer the data distribution, and facilitates ethically responsible data curation.

Source Data

Initial Data Collection and Normalization

From the paper:

Data Collection Pipeline Reddit’s uniform structure allows us to parallelize data collection as independent tasks – each task involves collecting posts submitted to a single subreddit in one year. Our collection pipeline has three steps: (1) subreddit selection, (2) image post filtering, and (3) caption cleaning. Step 1. Subreddit selection: We collect data from a manually curated set of subreddits. Subreddits have their own rules, community norms, and moderators so curating subreddits allows us to steer the dataset’s composition without annotating individual instances. We select subreddits with a high volume of images posts, where images tend to be photographs (rather than memes, drawings, screenshots, etc) and post titles tend to describe image content (rather than making jokes, political commentary, etc). We do not select any NSFW, banned, or quarantined subreddits. We want to minimize the number of people that appear in RedCaps, so we omit subreddits whose primary purpose is to share or comment on images of people (such as celebrity pics or user selfies). We choose subreddits focused on general photography (r/pics, r/itookapicture), animals (r/axolotls, r/birdsofprey, r/dachshund), plants (r/roses, r/succulents), objects (r/classiccars, r/trains, r/mechanicalkeyboards), food (r/steak, r/macarons), scenery (r/cityporn1 , r/desertporn), or activities (r/carpentry, r/kayaking). In total we collect data from 350 subreddits; the full list can be found in Appendix A. Step 2. Image post filtering: We use Pushshift [41] and Reddit [42, 43] APIs to download all image posts submitted to our selected subreddits from 2008–2020. Posts are collected at least six months after their creation to let upvotes stabilize. We only collect posts with images hosted on three domains: Reddit (i.redd.it), Imgur (i.imgur.com), and Flickr (staticflickr.com). Some image posts contain multiple images (gallery posts) – in this case we only collect the first image and associate it with the caption. We discard posts with < 2 upvotes to avoid unappealing content, and we discard posts marked NSFW (by their authors or subreddit moderators) to avoid pornographic or disturbing content. Step 3. Caption cleaning: We expect Reddit post titles to be less noisy than other large-scale sources of image captions such as alt-text [2, 31], so we apply minimal text cleaning. We lowercase captions and use ftfy [44] to remove character accents, emojis, and non-latin characters, following [29, 35, 36]. Then we apply simple pattern matching to discard all sub-strings enclosed in brackets ((.), [.]). These sub-strings usually give non-semantic information: original content tags [oc], image resolutions (800x600 px), camera specs (shot with iPhone), self-promotion [Instagram: @user], and other references (link in comments). Finally, like [31] we replace social media handles (words starting with ‘@’) with a [USR] token to protect user privacy and reduce redundancy. Due to such filtering, ≈12K (0.1%) captions in our dataset are empty strings. We do not discard them, as subreddit names alone provide meaningful supervision. Unlike CC-3M or CC-12M that discard captions without nouns or that don’t overlap image tags, we do not discard any instances in this step. Through this pipeline, we collect 13.4M instances from 350 subreddits. Our collection pipeline is less resource-intensive than existing datasets – we do not require webpage crawlers, search engines, or large databases of indexed webpages. RedCaps is easily extensible in the future by selecting more subreddits and collecting posts from future years. Next, we perform additional filtering to mitigate user privacy risks and harmful stereotypes in RedCaps, resulting in final size of 12M instances.

Who are the source language producers?

Reddit is the singular data source for RedCaps.

Annotations

Annotation process

The dataset is built using fully automatic data collection pipeline which doesn't require any human annotators.

Who are the annotators?

The annotation process doesn't require any human annotators.

Personal and Sensitive Information

From the paper:

Does the dataset relate to people? The dataset pertains to people in that people wrote the captions and posted images to Reddit that we curate in RedCaps. We made specific design choices while curating RedCaps to avoid large quantities of images containing people: (a) We collect data from manually curated subreddits in which most contain primarily pertains to animals, objects, places, or activities. We exclude all subreddits whose primary purpose is to share and describe images of people (such as celebrity photos or user selfies). (b) We use an off-the-shelf face detector to find and remove images with potential presence of human faces. We manually checked 50K random images in RedCaps (Q16) and found 79 images with identifiable human faces – the entire dataset may have ≈19K (0.15%) images with identifiable people. Refer Section 2.2 in the main paper.

Is it possible to identify one or more natural persons, either directly or indirectly (i.e., in combination with other data) from the dataset? Yes, all instances in RedCaps include Reddit usernames of their post authors. This could be used to look up the Reddit user profile, and some Reddit users may have identifying information in their profiles. Some images may contain human faces which could be identified by appearance. However, note that all this information is already public on Reddit, and searching it in RedCaps is no easier than searching directly on Reddit.

Were the individuals in question notified about the data collection? No. Reddit users are anonymous by default, and are not required to share their personal contact information (email, phone numbers, etc.). Hence, the only way to notify the authors of RedCaps image posts is by sending them private messages on Reddit. This is practically difficult to do manually, and will be classified as spam and blocked by Reddit if attempted to programmatically send a templated message to millions of users.

Did the individuals in question consent to the collection and use of their data? Users did not explicitly consent to the use of their data in our dataset. However, by uploading their data on Reddit, they consent that it would appear on the Reddit plaform and will be accessible via the official Reddit API (which we use to collect RedCaps).

If consent was obtained, were the consenting individuals provided with a mechanism to revoke their consent in the future or for certain uses? Users have full control over the presence of their data in our dataset. If users wish to revoke their consent, they can delete the underlying Reddit post – it will be automatically removed dfrom RedCaps since we distributed images as URLs. Moreover, we provide an opt-out request form on our dataset website for anybody to request removal of an individual instance if it is potentially harmful (e.g. NSFW, violates privacy, harmful stereotypes, etc.).

Considerations for Using the Data

Social Impact of Dataset

From the paper:

Has an analysis of the potential impact of the dataset and its use on data subjects (e.g., a data protection impact analysis) been conducted? No.

Discussion of Biases

From the paper:

Harmful Stereotypes: Another concern with Reddit data is that images or language may represent harmful stereotypes about gender, race, or other characteristics of people [48, 49, 51]. We select only non-NSFW subreddits with active moderation for collecting data. This stands in contrast to less curated uses of Reddit data, such as GPT-2 [35] whose training data includes at least 63K documents from banned or quarantined subreddits which may contain toxic language [53]. We attempt to further reduce harmful stereotypes in two ways:

  • NSFW images: We use the InceptionV3 [54] model from [55] to filter images detected as porn or hentai with confidence ≥ 0.9. Similar to face filtering, we estimated precision of our filtering and estimated amount of missed detections, shown in Table 1. The model detects 87K images with low precision (∼1%) – most detections are non-NSFW images with pink and beige hues.
  • Potentially derogatory language: We filter instances whose captions contain words or phrases from a common blocklist [56]. It is important to note that such coarse filtering might suppress language from marginalized groups reclaiming slurs [51]; however, as RedCaps is not intended to describe people, we believe this is a pragmatic tradeoff to avoid propagating harmful labels.

Reddit demographics: Reddit’s user demographics are not representative of the population at large. Compared to US adults, Reddit users skew male (69% vs 49%), young (58% 18-29 years old vs 22%), college educated (36% vs 28%), and politically liberal (41% vs 25%) [57]. Reddit users are predominantly white (63%) [57], and 49% of desktop traffic to Reddit comes from the United States [58]. All of the subreddits in RedCaps use English as their primary language. Taken together, these demographic biases likely also bias the types of objects and places that appear in images on Reddit, and the language used to describe these images. We do not offer explicit countermeasures to these biases, but users of RedCaps should keep in mind that size doesn’t guarantee diversity [51]. Subtler issues may also exist, such as imbalanced representation of demographic groups [59] or gender bias in object co-occurrence [60] or language [61]. These are hard to control in internet data, so we release RedCaps with explicit instructions on suitable use-cases; specifically requesting models not be trained to identify people, or make decisions that impact people. We document these instructions and other terms-of-use in a datasheet [45], provided in Appendix G.

Does the dataset contain data that, if viewed directly, might be offensive, insulting, threatening, or might otherwise cause anxiety? The scale of RedCaps means that we are unable to verify the contents of all images and captions. However we have tried to minimize the possibility that RedCaps contains data that might be offensive, insulting, threatening, or might cause anxiety via the following mitigations: (a) We manually curate the set of subreddits from which to collect data; we only chose subreddits that are not marked NSFW and which generally contain non-offensive content. (b) Within our curated subreddits, we did not include any posts marked NSFW. (c) We removed all instances whose captions contained any of the 400 potentially offensive words or phrases. Refer Section 2.2 in the main paper. (d) We remove all instances whose images were flagged NSFW by an off-the-shelf detector. We manually checked 50K random images in RedCaps and found one image containing nudity (exposed buttocks; no identifiable face). Refer Section 2.2 in the main paper

Does the dataset identify any subpopulations (e.g., by age, gender)? RedCaps does not explicitly identify any subpopulations. Since some images contain people and captions are free-form natural language written by Reddit users, it is possible that some captions may identify people appearing in individual images as part of a subpopulation.

Were any ethical review processes conducted (e.g., by an institutional review board)? We did not conduct a formal ethical review process via institutional review boards. However, as described in Section 2.2 of the main paper and Q16 we employed several filtering mechanisms to try and remove instances that could be problematic.

Other Known Limitations

From the paper:

Are there any errors, sources of noise, or redundancies in the dataset? RedCaps is noisy by design since image-text pairs on the internet are noisy and unstructured. Some instances may also have duplicate images and captions – Reddit users may have shared the same image post in multiple subreddits. Such redundancies constitute a very small fraction of the dataset, and should have almost no effect in training large-scale models.

Does the dataset contain data that might be considered confidential (e.g., data that is protected by legal privilege or by doctor-patient confidentiality, data that includes the content of individuals non-public communications)? No, the subreddits included in RedCaps do not cover topics that may be considered confidential. All posts were publicly shared on Reddit prior to inclusion in RedCaps.

Additional Information

Dataset Curators

From the paper:

Four researchers at the University of Michigan (affiliated as of 2021) have created RedCaps: Karan Desai, Gaurav Kaul, Zubin Aysola, and Justin Johnson.

Licensing Information

The image metadata is licensed under CC-BY 4.0 license. Additionally, uses of this dataset are subject to Reddit API terms (https://www.reddit.com/wiki/ api-terms) and users must comply with Reddit User Agreeement, Content Policy, and Privacy Policy – all accessible at https://www.redditinc.com/policies.

From the paper:

RedCaps should only be used for non-commercial research. RedCaps should not be used for any tasks that involve identifying features related to people (facial recognition, gender, age, ethnicity identification, etc.) or make decisions that impact people (mortgages, job applications, criminal sentences; or moderation decisions about user-uploaded data that could result in bans from a website). Any commercial and for-profit uses of RedCaps are restricted – it should not be used to train models that will be deployed in production systems as part of a product offered by businesses or government agencies.

Citation Information

@misc{desai2021redcaps,
      title={RedCaps: web-curated image-text data created by the people, for the people},
      author={Karan Desai and Gaurav Kaul and Zubin Aysola and Justin Johnson},
      year={2021},
      eprint={2111.11431},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Contributions

Thanks to @mariosasko for adding this dataset.

Update on GitHub
Papers with Code