michelecafagna26/git-base-captioning-ft-hl-rationales
Image-to-Text
•
Updated
•
112
Datasets:
image
imagewidth (px) 125
640
| captions
dict | confidence
dict | purity
dict | diversity
dict |
|---|---|---|---|---|
{
"scene": [
"in a beach",
"the picture was taken on the beach.",
"it is taken by a lake"
],
"action": [
"holding an umbrella",
"the lady is posing with he sun umbrella.",
"she us holding a parasol"
],
"rationale": [
"so they won't get a sun burn",
"she is enjoying and getting pictures of her vacation.",
"she is vacationing and it is sunny"
],
"object": [
"Woman in swim suit holding parasol on sunny day.",
"A woman posing for the camera, holding a pink, open umbrella and wearing a bright, floral, ruched bathing suit, by a life guard stand with lake, green trees, and a blue sky with a few clouds behind.",
"A woman in a floral swimsuit holds a pink umbrella.",
"A woman with an umbrella near the sea",
"A girl in a bathing suit with a pink umbrella."
]
} | {
"scene": [
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5
],
"action": [
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],
"rationale": [
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]
} | {
"scene": [
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-0.861034095287323,
-1.4165101051330566
],
"action": [
-1.041449785232544,
-1.1261067390441895,
-1.4078788757324219
],
"rationale": [
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-1.0123827457427979,
-0.9732668995857239
]
} | {
"scene": 3.855562158454097,
"action": 4.156282867624861,
"rationale": 5.762013077365682
} |
|
{
"scene": [
"in a farm field",
"on an outdoor equestrian course",
"the picture is taken on a ranch"
],
"action": [
"they are riding horses",
"they are demonstrating a trick",
"they are riding horses"
],
"rationale": [
"they are in showing off the horses skills",
"because they are in a competition",
"they areruding in a horse competition"
],
"object": [
"A couple of men riding horses on top of a green field.",
"two horses and their riders on some grass",
"Two men are on horses that are reared back.",
"A pair of horses performing tricks in a field. ",
"Two costumed horse riders make their horses stand on their hind legs."
]
} | {
"scene": [
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],
"action": [
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],
"rationale": [
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]
} | {
"scene": [
-1.1826231479644775,
-1.3592839241027832,
-1.3880681991577148
],
"action": [
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-1.348478078842163,
-0.7811778783798218
],
"rationale": [
-1.2109265327453613,
-1.1879997253417969,
-1.3540403842926025
]
} | {
"scene": 4.551763202773033,
"action": 62.628449627654696,
"rationale": 19.256759861669575
} |
|
{
"scene": [
"the picture was taken in the forest.",
"in a forest",
"the picture is taken in a forest"
],
"action": [
"the people are riding elephants.",
"driving elephant",
"they are riding on elephants."
],
"rationale": [
"they are on vacation.",
"for adventure",
"they are on a vacation"
],
"object": [
"They are brave for riding in the jungle on those elephants.",
"SOME PEOPLE IN THE WOODS RIDING TWO ELEPHANTS",
"Some people who are riding on top of elephants.",
"there are people riding elephants in the middle of a forest",
"Several elephants in the jungle carrying people on their backs"
]
} | {
"scene": [
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],
"action": [
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],
"rationale": [
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]
} | {
"scene": [
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-0.02607009932398796
],
"action": [
-0.39525604248046875,
-1.1087113618850708,
-0.4356062412261963
],
"rationale": [
-0.25897926092147827,
-1.1663357019424438,
-0.3382628858089447
]
} | {
"scene": 19.934150871323627,
"action": 11.461471282672413,
"rationale": 25.960026102380166
} |
|
{
"scene": [
"in a skateboard park",
"in a skating ground",
"it is taken in a skateboard park"
],
"action": [
"they are performing skateboard tricks",
"playing skating",
"they are doing tricks on a skateboard"
],
"rationale": [
"to practice their skills",
"trying to reached the goal",
"they have no school today"
],
"object": [
"A young man riding a skateboard into the air.",
"a group of teenagers jumping a ramp on their skateboards",
"A time lapse image of a guy on a skate board.",
"Group of boys performing skateboard trick on ramp with graffiti on it",
"some male skateboarders are doing some tricks and grafitti"
]
} | {
"scene": [
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],
"action": [
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],
"rationale": [
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]
} | {
"scene": [
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-0.8499500155448914,
-1.0522150993347168
],
"action": [
-0.3885204493999481,
-1.2655720710754395,
-0.44647759199142456
],
"rationale": [
-1.4696638584136963,
-1.4052119255065918,
-1.718639612197876
]
} | {
"scene": 48.99259467249772,
"action": 10.351514769172105,
"rationale": 4.4187180705148625
} |
|
{
"scene": [
"near a river",
"in the town' waterfront",
"in the lakeside park"
],
"action": [
"there are some people walking with dogs",
"they are going for walk",
"a man is walking, another sitting by the lakeside as more people are in the park"
],
"rationale": [
"some people are standing in front of the sun",
"they are exercising",
"they are all enjoying the sunset"
],
"object": [
"A skate park next to a body of water and green park.",
"Sky view of a walkway along the shore of a river.",
"A wide walkway allows for walks along the river.",
"A waterfront walkway and garden area next to a river.",
"some grass and a person in a blue shirt walking a dog and water"
]
} | {
"scene": [
5,
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4
],
"action": [
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],
"rationale": [
5,
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4
]
} | {
"scene": [
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-1.2758477926254272
],
"action": [
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-1.4369380474090576,
-0.9727466702461243
],
"rationale": [
-0.986436128616333,
-1.585521936416626,
-1.0661474466323853
]
} | {
"scene": 16.76478605134306,
"action": 2.3697210268747617,
"rationale": 8.801620360784563
} |
|
{
"scene": [
"in a restaurant",
"restaurant",
"the picture was taken in a restaurant."
],
"action": [
"she is going to eat pizza",
"slicing pizza",
"the subject is cutting a pizza."
],
"rationale": [
"to get energy and maintain good health",
"having meal",
"the subject is cutting the pizza to serve it to people at the table."
],
"object": [
"Woman cutting pizza with fork and knife sitting next to young girl",
"A woman and child sitting at a table with a pizza in front of them.",
"A lady and a child are sitting.The lady is cutting pizza pieces.",
"A woman cutting a pizza with a fork and knife.",
"A woman cutting a pizza with a fork and knife "
]
} | {
"scene": [
4,
5,
5
],
"action": [
4,
3,
5
],
"rationale": [
4,
3,
5
]
} | {
"scene": [
-1.0109511613845825,
-1.0785855054855347,
-1.0653202533721924
],
"action": [
-1.493504285812378,
-1.0917596817016602,
-0.9540096521377563
],
"rationale": [
-1.604188323020935,
-1.7056682109832764,
-1.5388290882110596
]
} | {
"scene": 29.337057893113105,
"action": 3.924030570301945,
"rationale": 2.154054808154877
} |
|
{
"scene": [
"the picture was taken at a school office meeting.",
"the couple is at your house",
"in the cafeteria of an office"
],
"action": [
"the subject is standing next to her retirement cake next to her husband.",
"she is cutting a cake",
"they are cutting a cake"
],
"rationale": [
"the subject is about to cake her retirement cake and past it to her co-workers and love ones.",
"it's her birthday",
"they are leaving the office"
],
"object": [
"a man and woman cut into a big cake ",
"A man and woman standing in front of a cake.",
"A women who is cutting into a cake.",
"two people standing near a table with a cake ",
"A woman cutting into a cake with a man standing behind her"
]
} | {
"scene": [
2,
4,
4
],
"action": [
5,
5,
5
],
"rationale": [
2,
4,
3
]
} | {
"scene": [
-1.3097336292266846,
-1.6852571964263916,
-1.4965158700942993
],
"action": [
-1.4123449325561523,
-1.1255333423614502,
-1.2370984554290771
],
"rationale": [
-1.2600679397583008,
-1.9957356452941895,
-1.7387490272521973
]
} | {
"scene": 3.3490344297168764,
"action": 12.753431387594826,
"rationale": 2.2475186432506145
} |
|
{
"scene": [
"in a cafe",
"in a road hotel",
"it is beach restaurant"
],
"action": [
"they are eating",
"he is sitting",
"he went off in between having tea"
],
"rationale": [
"they are on vacation",
"he is shooting a photo",
"somebody called him for help"
],
"object": [
"A piece of cake and coffee are on an outdoor table.",
"Slice of cake next to large filled cup on wooden table.",
"A dessert and a cup of coffee sit next to a book and a purse.",
"A slice of cake and mug sitting on a wooden table outside.",
"a close up of a slice of cake on a plate"
]
} | {
"scene": [
5,
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4
],
"action": [
5,
5,
4
],
"rationale": [
3,
5,
4
]
} | {
"scene": [
-1.3277307748794556,
-1.4174814224243164,
-1.5776684284210205
],
"action": [
-1.7923378944396973,
-1.6580591201782227,
-1.3660777807235718
],
"rationale": [
-1.7388051748275757,
-1.49904203414917,
-1.349377155303955
]
} | {
"scene": 16.76478605134306,
"action": 5.412989186545265,
"rationale": 0
} |
|
{
"scene": [
"in a park",
"in a soccer field",
"a field"
],
"action": [
"playing with other kids",
"they are flying kits",
"flying a kite"
],
"rationale": [
"because they are kids and like to play",
"they are enjoying the windy weather",
"it is a windy day"
],
"object": [
"People gathered outside in a big field on a cloudy day",
"People are flying kites on a high school field.",
"People flying kites in a field on a cloudy day.",
"A host of kites being flown on a field by people.",
"a bunch of people are at a grass field "
]
} | {
"scene": [
5,
4,
5
],
"action": [
5,
5,
5
],
"rationale": [
5,
3,
5
]
} | {
"scene": [
-1.2536096572875977,
-1.167571783065796,
-1.327923059463501
],
"action": [
-1.7002489566802979,
-1.574987769126892,
-1.5772111415863037
],
"rationale": [
-1.8112235069274902,
-0.9492457509040833,
-0.8452576994895935
]
} | {
"scene": 32.23894033779449,
"action": 7.04872424653493,
"rationale": 7.849076841340517
} |
|
{
"scene": [
"on a train through the woods.",
"in the forest",
"in the forest"
],
"action": [
"riding on a train looking out the window.",
"he is driving",
"look at the naturals"
],
"rationale": [
"to get a better view of the forest.",
"he wants to go his destination",
"look around the forest"
],
"object": [
"A stop sign directs pedestrians as a train travels by.",
"A stop sign sits in the middle of the forest. ",
"A stop sign sitting near some tall trees.",
"A man leans out of a vehicle near a short stop sign in a forest.",
"A stop sign is shown close to the ground."
]
} | {
"scene": [
5,
5,
5
],
"action": [
5,
5,
5
],
"rationale": [
5,
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5
]
} | {
"scene": [
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-0.9027702808380127,
-0.9284951090812683
],
"action": [
-1.36388099193573,
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],
"rationale": [
-0.44276177883148193,
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]
} | {
"scene": 29.615165360116254,
"action": 3.8275613602956104,
"rationale": 7.849076841340517
} |
|
{
"scene": [
"in a room",
"in a military office",
"the picture was taken on stage."
],
"action": [
"cutting a tie",
"pretending to cut a mans tie with a giant pair of scissors",
"the subject is addressing the audience."
],
"rationale": [
"to have fun",
"for fun, as a joke, to make people laugh",
"it is a ribbon cutting ceremony."
],
"object": [
"a female in military uniform cutting a businessman's neck tie",
"A woman in a soldier's uniform pretends to cut the tie of a man using an enormous pair of scissors.",
"A funny picture of a woman holding a large pair of scissors attempting to cut a mans tie.",
"A woman soldier holding up a pair of giant scissors to someone's tie.",
"A man in a suit and a woman in military clothes."
]
} | {
"scene": [
5,
5,
5
],
"action": [
5,
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5
],
"rationale": [
4,
5,
4
]
} | {
"scene": [
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-1.5754902362823486,
-1.577151894569397
],
"action": [
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-1.4495207071304321,
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],
"rationale": [
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]
} | {
"scene": 11.28768345850495,
"action": 2.911790334920635,
"rationale": 3.426113474170997
} |
|
{
"scene": [
"the picture is being taken at the ski resort.",
"it is taken at a ski resort",
"in a ski park"
],
"action": [
"the people are resting from a day of snow boarding.",
"they are leaning agsinst a snowboard rack",
"there is no people in the picture, so the subject is not there"
],
"rationale": [
"the people are resting because it was a long day on the slopes.",
"their owners are eating lunch",
"he do not like pictures"
],
"object": [
"Six snowboards are propped in the snow on a rail.",
"Five skateboards on a rack in a snow covered mountain ",
"There are skateboards leaning on a metal bar.",
"A row of snow boards sticking out of the snow.",
"Snowboards sticking in the snow by a rack "
]
} | {
"scene": [
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5
],
"action": [
4,
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5
],
"rationale": [
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5
]
} | {
"scene": [
-0.41199275851249695,
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-0.8869255185127258
],
"action": [
-1.2728495597839355,
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],
"rationale": [
-1.5379788875579834,
-1.8569715023040771,
-1.783599615097046
]
} | {
"scene": 10.941077080912248,
"action": 1.922553362585415,
"rationale": 2.1890915786867984
} |
|
{
"scene": [
"bus station",
"in a bus station",
"platform"
],
"action": [
"wait for the bus",
"waiting for a bus",
"wating for bus"
],
"rationale": [
"wait for the bus",
"to reached the destination",
"opedents"
],
"object": [
"A female traveler leaning on a luggage cart.",
"A woman is waiting with a cart full of luggage.",
"A woman next to a cart of luggage at a bus stop.",
"the woman is standing with her luggage ",
"A woman wearing a yellow shirt standing next to luggage."
]
} | {
"scene": [
5,
5,
4
],
"action": [
5,
5,
4
],
"rationale": [
4,
5,
4
]
} | {
"scene": [
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-1.5931881666183472
],
"action": [
-0.6844797730445862,
-0.5882531404495239,
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],
"rationale": [
-1.5718700885772705,
-1.4510016441345215,
-1.7393431663513184
]
} | {
"scene": 36.55552228545125,
"action": 9.276642805332752,
"rationale": 6.608102052593235
} |
|
{
"scene": [
"in a beach",
"on a beach",
"in a beach"
],
"action": [
"they are taking sunbath",
"many people are sunbathing on the beach",
"they are sun tanning"
],
"rationale": [
"they are in summer vacation.",
"they are enjoying a day at the beach",
"they are on vacation relaxing"
],
"object": [
"Beautiful women wearing bikinis frolicking on a sandy beach.",
"Groups of people sit on a beach in the sand.",
"people in bikinis at a beach under umbrellas",
"Women are walking towards seats on the beach.",
"People sunbathing and sitting under umbrellas at a city beach."
]
} | {
"scene": [
5,
5,
5
],
"action": [
5,
5,
4
],
"rationale": [
5,
5,
3
]
} | {
"scene": [
-0.5847224593162537,
-0.4179289937019348,
-0.5924130082130432
],
"action": [
-1.0160077810287476,
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],
"rationale": [
-0.8462914824485779,
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]
} | {
"scene": 0,
"action": 10.649051737437876,
"rationale": 9.334178025925228
} |
|
{
"scene": [
"in park",
"at the park",
"in a garden"
],
"action": [
"he is throwing the throw disk",
"a man is throwing frisbee",
"trying to catch a frisbee"
],
"rationale": [
"he is playing in park with throw disk",
"he wants to show off his skills",
"he is practicing to master in the game"
],
"object": [
"A man tossing an orange frisbee on top of a lush green field.",
"a man standing in a yard with a red frisbee",
"A full view of a man throwing a Frisbee.",
"A person is throwing a Frisbee at night. ",
"Man playing with flying red disk outdoors in evening."
]
} | {
"scene": [
3,
5,
5
],
"action": [
3,
5,
4
],
"rationale": [
3,
5,
4
]
} | {
"scene": [
-1.066572904586792,
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-1.238563060760498
],
"action": [
-1.2106170654296875,
-0.6762368083000183,
-0.8825339674949646
],
"rationale": [
-1.535841941833496,
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-1.192993402481079
]
} | {
"scene": 0,
"action": 10.825978373090527,
"rationale": 6.446582776912681
} |
|
{
"scene": [
"in a photo studio",
"it is taken in a wine cellar.",
"inside a club"
],
"action": [
"he's doing his best pose",
"he is holding up a glass of wine and examining it.",
"he is holding a wine glass in his left hand"
],
"rationale": [
"is an advertisement for a famous wine brand",
"he is inspecting the colour and clarity of the wine in the glass.",
"he want to have some more drinks"
],
"object": [
"A man holding a glass of wine on it's side.",
"A man tilting a glass of wine.to the side.",
"A person holding a partially filled wine glass.",
"a male in a white shirt is holding a glass of wine",
"A man tips a clear wine glass to observe its makeup. "
]
} | {
"scene": [
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5
],
"action": [
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],
"rationale": [
5,
3,
5
]
} | {
"scene": [
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-1.6072415113449097
],
"action": [
-1.6704065799713135,
-0.5528365969657898,
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],
"rationale": [
-1.4404528141021729,
-1.1068860292434692,
-1.5103800296783447
]
} | {
"scene": 10.649051737437876,
"action": 10.217753029685468,
"rationale": 2.280134809249892
} |
|
{
"scene": [
"at a park",
"in the playground",
"the pictire is taken on a soccer field."
],
"action": [
"playing with a football",
"playing football",
"they are practicing soccer."
],
"rationale": [
"for enjoyment",
"he wants to play",
"they are doing it for excercise and to improve skills."
],
"object": [
"A young boy playing soccer on a grassy field",
"A group of kids playing soccer on a field.",
"Small child in soccer uniform kicking at yellow ball. ",
"A young man kicking a soccer ball around a field.",
"There are several young boys practicing soccer, some with their dads."
]
} | {
"scene": [
5,
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],
"action": [
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4
],
"rationale": [
5,
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]
} | {
"scene": [
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],
"action": [
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],
"rationale": [
-1.6757936477661133,
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]
} | {
"scene": 5.035625662261279,
"action": 6.9161417925511355,
"rationale": 4.035682266239977
} |
|
{
"scene": [
"outside a family house",
"at the outside of a house",
"outside a house"
],
"action": [
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-0.48480477929115295,
-1.1865196228027344
],
"rationale": [
-1.2502951622009277,
-1.4515783786773682,
-1.6644870042800903
]
} | {
"scene": 11.369781110415222,
"action": 2.9125725568275076,
"rationale": 2.843940121811021
} |
|
{
"scene": [
"in a beach",
"on the beach",
"in the ocean"
],
"action": [
"he is skating",
"he is surfing",
"a man is surfing the waves"
],
"rationale": [
"he was in vacation",
"to play sports",
"he wants to spend his leisure interestingly"
],
"object": [
"A man is riding on a surfboard in the ocean.",
"A young man riding a surf board on a small wave.",
"a person riding a surf board on a wave ",
"a man riding a colorful surfboard in the water",
"A man is surfing with his yellow and black striped surfboard"
]
} | {
"scene": [
5,
4,
3
],
"action": [
5,
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3
],
"rationale": [
5,
4,
3
]
} | {
"scene": [
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-1.0078301429748535
],
"action": [
-1.7513728141784668,
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],
"rationale": [
-1.4722915887832642,
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-0.8767021894454956
]
} | {
"scene": 0,
"action": 20.598848617040787,
"rationale": 5.643841729252477
} |
|
{
"scene": [
"in a hotel",
"in a kitchen.",
"in a table"
],
"action": [
"they are enjoying",
"it's on the table.",
"making a juice"
],
"rationale": [
"they are on a dinner",
"it's preparing a juice.",
"to drink"
],
"object": [
"A silver and clear drink container with a black tray of fruit next to it.",
"Two fruits sit in a bowl beside a blender.",
"An old fashioned type of blender in front of an old sign.",
"A small blender with a bowl of fruit next to it",
"A blender sitting on top of a wooden floor."
]
} | {
"scene": [
3,
5,
5
],
"action": [
4,
5,
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],
"rationale": [
3,
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5
]
} | {
"scene": [
-1.560173749923706,
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],
"action": [
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],
"rationale": [
-1.700355887413025,
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-1.7084741592407227
]
} | {
"scene": 29.940298211620984,
"action": 0,
"rationale": 4.589127624193197
} |
|
{
"scene": [
"on a lake or river.",
"photo is taken on a body of water.",
"its in a ocean"
],
"action": [
"he is drinking a bottle of water and steering his boat.",
"a man is sitting in a boat.",
"he is sitting in the boat"
],
"rationale": [
"he has been fishing and is moving to another location.",
"man is getting ready to go fishing in his boat.",
"he is enjoying and seeing the nature"
],
"object": [
"A man is sitting in a boat on a river and drinking a bottle of water.",
"A man in a blue hat on a small boat.",
"A man that is sitting in a boat wearing a hat.",
"A man holding a bottle is boating on a lake.",
"A man siting on top of a boat on top of a lake."
]
} | {
"scene": [
5,
5,
3
],
"action": [
5,
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],
"rationale": [
5,
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]
} | {
"scene": [
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],
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],
"rationale": [
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]
} | {
"scene": 8.15746610990924,
"action": 15.84008351965364,
"rationale": 2.409937962953139
} |
|
{
"scene": [
"the image is taken on a tennis court.",
"on the field",
"a a grass tennis court"
],
"action": [
"playing a game of tennis. there are 3 people sitting off to the side watching the game. the people sitting off to the side seemed to be well dressed and talking about the game.",
"he is playing batiminton",
"serving to his opponent"
],
"rationale": [
"the tennis player is competing.",
"he is training",
"it is his turn to serve"
],
"object": [
"A person on a court with a tennis racket.",
"A man that is holding a racquet standing in the grass.",
"A tennis player hits the ball during a match.",
"The tennis player is poised to serve a ball.",
"Man in white playing tennis on a court."
]
} | {
"scene": [
5,
5,
5
],
"action": [
4,
5,
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],
"rationale": [
4,
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]
} | {
"scene": [
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],
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-1.0868761539459229,
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],
"rationale": [
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]
} | {
"scene": 10.452498041939908,
"action": 1.2388330307522724,
"rationale": 3.8367178054997066
} |
|
{
"scene": [
"the picture is taken near the mountain.",
"the picture is taken in a grass valley.",
"in a lane"
],
"action": [
"the cows are grazing in the lawn.",
"the subjects are eating the grass.",
"looking at the cow"
],
"rationale": [
"if they eat grass,they will provide milk to human beings.",
"the cows are very hungry.",
"brought the cow to grasp"
],
"object": [
"A herd of cows standing on a grass covered field.",
"Group of cows in a field with a man in the background.",
"a number of cows in a field with a person behind them",
"A heard of cows stands in front of a man with a tractor.",
"A herd of skinny cows are grazing on the grass."
]
} | {
"scene": [
5,
5,
5
],
"action": [
5,
5,
5
],
"rationale": [
5,
5,
5
]
} | {
"scene": [
-0.7681860327720642,
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],
"action": [
-0.8449391722679138,
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],
"rationale": [
-0.9811797738075256,
-1.0701611042022705,
-1.797325849533081
]
} | {
"scene": 28.167835284527474,
"action": 3.7088441739676585,
"rationale": 2.881006538682842
} |
|
{
"scene": [
"river side",
"on a river",
"in a lake"
],
"action": [
"sitting in a canoe",
"they are fishing",
"they are fishing"
],
"rationale": [
"ready for migration from one place to another",
"they are working",
"they are working"
],
"object": [
"A couple of boats are on a a river",
"Two rowboats parked on the side of a small river with people in each of the boats.",
"A GROUP OF PEOPLE ON SMALL FISHING BOATS LOOKING AT A FIERY COMING TOWARDS THEM",
"A boat of women are pushing off of the shore.",
"A few people are on small boats in a channel."
]
} | {
"scene": [
5,
4,
5
],
"action": [
5,
4,
5
],
"rationale": [
3,
4,
5
]
} | {
"scene": [
-1.2616820335388184,
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-1.237011194229126
],
"action": [
-1.8240752220153809,
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-0.7329948544502258
],
"rationale": [
-1.1406760215759277,
-0.8437130451202393,
-0.8950782418251038
]
} | {
"scene": 0,
"action": 54.10822690539399,
"rationale": 24.98375039765567
} |
|
{
"scene": [
"the picture is taken in a skating practice area.",
"in a skate lane",
"in a skating place"
],
"action": [
"the subjects are skating on the skate board.",
"they're skating",
"they are skating"
],
"rationale": [
"the subjects are participating in a competition.",
"they're praticing their sport so they can be really good at it",
"they are on a class"
],
"object": [
"Two young children on a ramp with their skate boards.",
"Young boys in raincoats skate boarding on a half pipe",
"a person on a skate board rides up a ramp",
"A kid dressed in black is on his skateboard on a skateboard ramp.",
"A couple of kids on skateboards riding together."
]
} | {
"scene": [
5,
5,
5
],
"action": [
5,
5,
5
],
"rationale": [
5,
5,
5
]
} | {
"scene": [
-0.7809543013572693,
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],
"action": [
-0.7278643250465393,
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-1.033302664756775
],
"rationale": [
-0.968246340751648,
-1.3244123458862305,
-1.5426926612854004
]
} | {
"scene": 19.245008972987524,
"action": 11.40346971989556,
"rationale": 2.736426268587265
} |
|
{
"scene": [
"the picture was taken in city.",
"in the street",
"picture taken on a road in an urban setting."
],
"action": [
"the truck is moving.",
"he is driving a truck",
"a truck travels down a city street."
],
"rationale": [
"the truck is trying to get somewhere.",
"to take material from place to place",
"the truck is on its way to a job."
],
"object": [
"a blue red and white truck and some buildings",
"A red and blue dump truck traveling along a city street.",
"A work truck turning down a city street.",
"A haul truck driving through a wet street.",
"A red and blue dump truck marked 'Ardula' is shown on a city street."
]
} | {
"scene": [
5,
5,
5
],
"action": [
5,
5,
3
],
"rationale": [
5,
5,
3
]
} | {
"scene": [
-0.9171448945999146,
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-0.3534574508666992
],
"action": [
-0.9995108246803284,
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],
"rationale": [
-0.7130962610244751,
-0.8951459527015686,
-0.6805176138877869
]
} | {
"scene": 3.4849325105941777,
"action": 9.372355419839153,
"rationale": 12.736617334707145
} |
|
{
"scene": [
"tennis court",
"on a racket court",
"on a tennis court"
],
"action": [
"practicing sport",
"playing racket",
"he is playing tennis"
],
"rationale": [
"practicing sport for your health",
"hits the racket on the ball",
"he is trying to have fun"
],
"object": [
"A person about to swing a tennis racket",
"A tennis player swinging at the tennis ball.",
"A boy swings a tennis racket as he plays inside a tennis court",
"A person on a court swinging a tennis racket.",
"A tennis player holds his racket back on a court."
]
} | {
"scene": [
4,
4,
5
],
"action": [
5,
5,
5
],
"rationale": [
4,
5,
5
]
} | {
"scene": [
-0.8909040689468384,
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],
"action": [
-1.2501002550125122,
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-1.2964191436767578
],
"rationale": [
-1.5494364500045776,
-1.6825876235961914,
-1.2640223503112793
]
} | {
"scene": 24.513042902179816,
"action": 14.058533129758727,
"rationale": 0
} |
|
{
"scene": [
"on the beach",
"on the beach",
"taken from a sea"
],
"action": [
"he is surfing",
"carrying a surfboard",
"he is surfing"
],
"rationale": [
"he is trying to have fun",
"just finish surfing",
"he is doing it for entertainment"
],
"object": [
"A man holding a white surfboard standing in the ocean.",
"A surfer in a wet suit carries his board out of the surf. ",
"A surfer walks through sea foam with his board",
"A man is wading in water carrying a surfboard.",
"A man with a surf board standing in the surf."
]
} | {
"scene": [
5,
5,
5
],
"action": [
5,
5,
4
],
"rationale": [
5,
5,
5
]
} | {
"scene": [
-0.7826378345489502,
-0.7443636655807495,
-1.256828784942627
],
"action": [
-0.6213048100471497,
-1.0894012451171875,
-0.5692230463027954
],
"rationale": [
-0.7770560383796692,
-1.6920788288116455,
-1.2102972269058228
]
} | {
"scene": 54.10822690539399,
"action": 0,
"rationale": 8.24564318136398
} |
|
{
"scene": [
"in a photographic studio",
"in a function hall",
"the picture is taken in an office."
],
"action": [
"held a flower",
"a man is taking ovation",
"the person is standing before a higher official."
],
"rationale": [
"for any advertising campaign",
"he is going to start the function as a guest",
"he has done some mistake in his work."
],
"object": [
"A man's tattoo is seen under his dress shirt sleeve as he holds a rose.",
"MAN HOLDING ROSE WEARING WHITE SHIRT AND BLACK TIE",
"Two hands that are holding a rose next to a tie.",
"A man with his hands crossed wearing a white shirt and a tie.",
"A shot of the waste of a formally dressed man. "
]
} | {
"scene": [
5,
4,
5
],
"action": [
3,
3,
5
],
"rationale": [
4,
3,
5
]
} | {
"scene": [
-1.3874306678771973,
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-1.0267741680145264
],
"action": [
-1.96633780002594,
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-1.1839678287506104
],
"rationale": [
-1.7676770687103271,
-1.361939549446106,
-1.0819430351257324
]
} | {
"scene": 9.625807217196785,
"action": 4.394734066956871,
"rationale": 1.859803087437424
} |
|
{
"scene": [
"at a ski resort.",
"in a skiing snow field area",
"on the snowfields in a ski resort."
],
"action": [
"they are skiing.",
"three friends are posing with their skis",
"three skiers with skis on posing for a photo whilst skiiing."
],
"rationale": [
"because they want to have fun.",
"they want to start their skiing competition",
"they are on a ski vacation."
],
"object": [
"People who are dressed for skiing standing in the snow.",
"Three skiers posing at the center of a skiing facility.",
"Three people standing next to each other on skis in the snow. ",
"Three young men on snow skis posing at the top of a snowy slope.",
"Three men wearing skis are standing in the snow."
]
} | {
"scene": [
5,
5,
4
],
"action": [
5,
4,
4
],
"rationale": [
4,
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4
]
} | {
"scene": [
-0.7110015153884888,
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-0.5796725749969482
],
"action": [
-1.3623359203338623,
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],
"rationale": [
-1.0240318775177002,
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-1.0003767013549805
]
} | {
"scene": 36.5333023244503,
"action": 3.6175673124725662,
"rationale": 15.166471346826793
} |
|
{
"scene": [
"on the sidewalk in front of outlet store fronts.",
"in front of a clothing store",
"on a city street."
],
"action": [
"sitting on the sidewalk texting on cell phone.",
"they are checking the cell phone",
"the ladies are sitting on the curb with their shopping bags, checking their cell phones."
],
"rationale": [
"waiting for their ride to come pick them up after going shopping.",
"they are waiting for the uber",
"they are waiting for a ride home."
],
"object": [
"Two girls sit on the ground looking at their phones.",
"Two girls take a break from shopping to text on their cell phones. ",
"A pair of women sitting on a curb looking at cell phones.",
"A couple of girls sitting on the curb with phones.",
"A COUPLE OF YOUNG LADIES SITTING ON A STEP PLAYING ON THERE PHONES"
]
} | {
"scene": [
5,
4,
5
],
"action": [
5,
4,
5
],
"rationale": [
4,
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]
} | {
"scene": [
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],
"action": [
-1.308173656463623,
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],
"rationale": [
-0.9852889776229858,
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-0.8350874185562134
]
} | {
"scene": 16.9377582718205,
"action": 11.811189809671863,
"rationale": 23.785501588089687
} |
End of preview. Expand
in Dataset Viewer.
Dataset Card for the High-Level Dataset
Dataset Description
The High-Level (HL) dataset aligns object-centric descriptions from COCO with high-level descriptions crowdsourced along 3 axes: scene, action, rationale
The HL dataset contains 14997 images from COCO and a total of 134973 crowdsourced captions (3 captions for each axis) aligned with ~749984 object-centric captions from COCO.
Each axis is collected by asking the following 3 questions:
- Where is the picture taken?
- What is the subject doing?
- Why is the subject doing it?
The high-level descriptions capture the human interpretations of the images. These interpretations contain abstract concepts not directly linked to physical objects. Each high-level description is provided with a confidence score, crowdsourced by an independent worker measuring the extent to which the high-level description is likely given the corresponding image, question, and caption. The higher the score, the more the high-level caption is close to the commonsense (in a Likert scale from 1-5).
- 🗃️ Repository: github.com/michelecafagna26/HL-dataset
- 📜 Paper: HL Dataset: Visually-grounded Description of Scenes, Actions and Rationales
- 🧭 Spaces: Dataset explorer
- 🖊️ Contact: [email protected]
Supported Tasks
- image captioning
- visual question answering
- multimodal text-scoring
- zero-shot evaluation
Languages
English
Dataset Structure
The dataset is provided with images from COCO and two metadata jsonl files containing the annotations
Data Instances
An instance looks like this:
{
"file_name": "COCO_train2014_000000138878.jpg",
"captions": {
"scene": [
"in a car",
"the picture is taken in a car",
"in an office."
],
"action": [
"posing for a photo",
"the person is posing for a photo",
"he's sitting in an armchair."
],
"rationale": [
"to have a picture of himself",
"he wants to share it with his friends",
"he's working and took a professional photo."
],
"object": [
"A man sitting in a car while wearing a shirt and tie.",
"A man in a car wearing a dress shirt and tie.",
"a man in glasses is wearing a tie",
"Man sitting in the car seat with button up and tie",
"A man in glasses and a tie is near a window."
]
},
"confidence": {
"scene": [
5,
5,
4
],
"action": [
5,
5,
4
],
"rationale": [
5,
5,
4
]
},
"purity": {
"scene": [
-1.1760284900665283,
-1.0889461040496826,
-1.442818284034729
],
"action": [
-1.0115827322006226,
-0.5917857885360718,
-1.6931917667388916
],
"rationale": [
-1.0546956062316895,
-0.9740906357765198,
-1.2204363346099854
]
},
"diversity": {
"scene": 25.965358893403383,
"action": 32.713305568898775,
"rationale": 2.658757840479801
}
}
Data Fields
file_name: original COCO filenamecaptions: Dict containing all the captions for the image. Each axis can be accessed with the axis name and it contains a list of captions.confidence: Dict containing the captions confidence scores. Each axis can be accessed with the axis name and it contains a list of captions. Confidence scores are not provided for the object axis (COCO captions).tpurity score: Dict containing the captions purity scores. The purity score measures the semantic similarity of the captions within the same axis (Bleurt-based).diversity score: Dict containing the captions diversity scores. The diversity score measures the lexical diversity of the captions within the same axis (Self-BLEU-based).
Data Splits
There are 14997 images and 134973 high-level captions split into:
- Train-val: 13498 images and 121482 high-level captions
- Test: 1499 images and 13491 high-level captions
Dataset Creation
The dataset has been crowdsourced on Amazon Mechanical Turk. From the paper:
We randomly select 14997 images from the COCO 2014 train-val split. In order to answer questions related to actions and rationales we need to ensure the presence of a subject in the image. Therefore, we leverage the entity annotation provided in COCO to select images containing at least one person. The whole annotation is conducted on Amazon Mechanical Turk (AMT). We split the workload into batches in order to ease the monitoring of the quality of the data collected. Each image is annotated by three different annotators, therefore we collect three annotations per axis.
Curation Rationale
From the paper:
In this work, we tackle the issue of grounding high-level linguistic concepts in the visual modality, proposing the High-Level (HL) Dataset: a
V&L resource aligning existing object-centric captions with human-collected high-level descriptions of images along three different axes: scenes, actions and rationales. The high-level captions capture the human interpretation of the scene, providing abstract linguistic concepts complementary to object-centric captions used in current V&L datasets, e.g. in COCO. We take a step further, and we collect confidence scores to distinguish commonsense assumptions from subjective interpretations and we characterize our data under a variety of semantic and lexical aspects.
Source Data
- Images: COCO
- object axis annotations: COCO
- scene, action, rationale annotations: crowdsourced
- confidence scores: crowdsourced
- purity score and diversity score: automatically computed
Annotation process
From the paper:
Pilot: We run a pilot study with the double goal of collecting feedback and defining the task instructions. With the results from the pilot we design a beta version of the task and we run a small batch of cases on the crowd-sourcing platform. We manually inspect the results and we further refine the instructions and the formulation of the task before finally proceeding with the annotation in bulk. The final annotation form is shown in Appendix D.
Procedure: The participants are shown an image and three questions regarding three aspects or axes: scene, actions and rationales i,e. Where is the picture taken?, What is the subject doing?, Why is the subject doing it?. We explicitly ask the participants to use their personal interpretation of the scene and add examples and suggestions in the instructions to further guide the annotators. Moreover, differently from other VQA datasets like (Antol et al., 2015) and (Zhu et al., 2016), where each question can refer to different entities in the image, we systematically ask the same three questions about the same subject for each image. The full instructions are reported in Figure 1. For details regarding the annotation costs see Appendix A.
Who are the annotators?
Turkers from Amazon Mechanical Turk
Personal and Sensitive Information
There is no personal or sensitive information
Considerations for Using the Data
[More Information Needed]
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
From the paper:
Quantitying grammatical errors: We ask two expert annotators to correct grammatical errors in a sample of 9900 captions, 900 of which are shared between the two annotators. The annotators are shown the image caption pairs and they are asked to edit the caption whenever they identify a grammatical error. The most common errors reported by the annotators are:
- Misuse of prepositions
- Wrong verb conjugation
- Pronoun omissions
In order to quantify the extent to which the corrected captions differ from the original ones, we compute the Levenshtein distance (Levenshtein, 1966) between them. We observe that 22.5% of the sample has been edited and only 5% with a Levenshtein distance greater than 10. This suggests a reasonable level of grammatical quality overall, with no substantial grammatical problems. This can also be observed from the Levenshtein distance distribution reported in Figure 2. Moreover, the human evaluation is quite reliable as we observe a moderate inter-annotator agreement (alpha = 0.507, (Krippendorff, 2018) computed over the shared sample.
Dataset Curators
Michele Cafagna
Licensing Information
The Images and the object-centric captions follow the COCO terms of Use The remaining annotations are licensed under Apache-2.0 license.
Citation Information
@inproceedings{cafagna2023hl,
title={{HL} {D}ataset: {V}isually-grounded {D}escription of {S}cenes, {A}ctions and
{R}ationales},
author={Cafagna, Michele and van Deemter, Kees and Gatt, Albert},
booktitle={Proceedings of the 16th International Natural Language Generation Conference (INLG'23)},
address = {Prague, Czech Republic},
year={2023}
}
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