AI Data for Untitled (elevated view of guests at tables in large banquet hall) | AI Explorer

Machine Generated Data

Color Analysis

Face analysis

Amazon

Google

AWS Rekognition

Age	29-39
Gender	Male, 96.8%
Calm	37.8%
Sad	31.5%
Surprised	7.6%
Happy	6.8%
Disgusted	6.7%
Fear	4.9%
Confused	2.5%
Angry	2.2%

AWS Rekognition

Age	31-41
Gender	Male, 98.7%
Calm	80.1%
Happy	15.2%
Sad	1.7%
Confused	1.4%
Surprised	0.7%
Disgusted	0.5%
Angry	0.4%
Fear	0.1%

AWS Rekognition

Age	50-58
Gender	Male, 99.5%
Sad	81.5%
Happy	13.7%
Confused	3.5%
Disgusted	0.4%
Surprised	0.3%
Fear	0.3%
Angry	0.2%
Calm	0.2%

AWS Rekognition

Age	33-41
Gender	Male, 73.7%
Calm	73.4%
Happy	17.3%
Sad	6.2%
Confused	1.4%
Disgusted	0.8%
Surprised	0.3%
Angry	0.3%
Fear	0.2%

AWS Rekognition

Age	4-10
Gender	Female, 91.8%
Calm	36.6%
Confused	29.5%
Fear	14.9%
Angry	6.7%
Disgusted	4.4%
Sad	3.7%
Surprised	2.6%
Happy	1.6%

AWS Rekognition

Age	30-40
Gender	Female, 67.2%
Calm	98.3%
Sad	0.5%
Confused	0.3%
Disgusted	0.2%
Happy	0.2%
Surprised	0.2%
Angry	0.1%
Fear	0.1%

AWS Rekognition

Age	35-43
Gender	Male, 99.9%
Calm	94.8%
Sad	4.5%
Happy	0.2%
Confused	0.2%
Disgusted	0.2%
Angry	0%
Fear	0%
Surprised	0%

AWS Rekognition

Age	36-44
Gender	Male, 77.1%
Calm	94.4%
Sad	3.7%
Surprised	0.6%
Fear	0.4%
Confused	0.2%
Angry	0.2%
Disgusted	0.2%
Happy	0.2%

AWS Rekognition

Age	23-31
Gender	Male, 64.1%
Sad	53%
Calm	17.4%
Happy	15.2%
Confused	5.8%
Angry	2.7%
Fear	2.7%
Disgusted	2.2%
Surprised	1%

AWS Rekognition

Age	30-40
Gender	Female, 88.8%
Calm	45.7%
Fear	21.6%
Disgusted	14.6%
Sad	8%
Happy	3.7%
Surprised	2.5%
Angry	2.2%
Confused	1.6%

AWS Rekognition

Age	37-45
Gender	Female, 91.3%
Calm	96.8%
Happy	0.9%
Angry	0.7%
Surprised	0.7%
Sad	0.5%
Disgusted	0.2%
Confused	0.2%
Fear	0.1%

AWS Rekognition

Age	11-19
Gender	Female, 75.1%
Happy	73.5%
Calm	19.2%
Sad	4.1%
Confused	1.3%
Angry	0.5%
Fear	0.5%
Surprised	0.4%
Disgusted	0.4%

AWS Rekognition

Age	39-47
Gender	Male, 72.3%
Calm	99.9%
Sad	0.1%
Surprised	0%
Disgusted	0%
Confused	0%
Happy	0%
Angry	0%
Fear	0%

AWS Rekognition

Age	13-21
Gender	Female, 68.3%
Calm	80.9%
Happy	9.4%
Sad	4.6%
Angry	1.7%
Confused	1.3%
Surprised	0.8%
Fear	0.7%
Disgusted	0.7%

AWS Rekognition

Age	23-31
Gender	Female, 88.6%
Calm	99.5%
Surprised	0.1%
Happy	0.1%
Disgusted	0.1%
Sad	0.1%
Confused	0.1%
Fear	0%
Angry	0%

AWS Rekognition

Age	31-41
Gender	Male, 79.2%
Calm	97.5%
Confused	0.9%
Happy	0.4%
Sad	0.4%
Angry	0.4%
Fear	0.2%
Disgusted	0.1%
Surprised	0.1%

AWS Rekognition

Age	18-24
Gender	Male, 81.6%
Sad	61%
Confused	23.7%
Calm	8.1%
Fear	2.5%
Happy	1.6%
Angry	1.2%
Disgusted	1%
Surprised	0.8%

AWS Rekognition

Age	35-43
Gender	Male, 87.2%
Calm	67.6%
Happy	11.9%
Fear	8%
Sad	7.1%
Surprised	1.8%
Confused	1.8%
Disgusted	1.4%
Angry	0.5%

AWS Rekognition

Age	21-29
Gender	Female, 93.6%
Calm	76.5%
Happy	21.5%
Sad	0.6%
Fear	0.3%
Confused	0.3%
Angry	0.3%
Disgusted	0.3%
Surprised	0.2%

AWS Rekognition

Age	20-28
Gender	Female, 82%
Calm	34.2%
Angry	22.5%
Sad	20.8%
Fear	10.7%
Confused	7.8%
Disgusted	1.6%
Happy	1.3%
Surprised	1.2%

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Likely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very likely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Likely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Google Vision

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Likely

Feature analysis

Amazon

Person	99.6%

Captions

Microsoft
created on 2022-01-23

a group of people standing in front of a crowd	94.7%

a group of people in an old photo of a crowd	94.6%

a group of people in front of a crowd	94.5%

Text analysis

Amazon

YT3R

Google

T S ALS

ALS

Title Untitled (elevated view of guests at tables in large banquet hall)	Date 1948-1950
People Artist: Martin Schweig, American 20th century	Classification Photographs
Credit Line Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.9256

Person	99.6

Human	99.6

Person	99.1

Person	98.7

Audience	97

Crowd	97

Interior Design	95.4

Indoors	95.4

Person	95.1

Person	94.8

Classroom	93

Room	93

School	93

Plant	87.3

Person	75.2

Person	73.4

People	73.3

Flower	67

Blossom	67

Person	66.6

Silhouette	62.8

Person	62.5

Person	60.1

Flower Arrangement	59

Speech	57.9

Hall	56.5

Suit	56.3

Clothing	56.3

Coat	56.3

Overcoat	56.3

Apparel	56.3

Sitting	56.1

Seminar	55.7

Lecture	55.7

Person	54.2

Person	54.2

people	99.9

many	99

group	98.9

woman	96.7

adult	96.2

child	93.7

man	91.5

music	91

group together	88.6

administration	84.3

leader	83.1

audience	82.8

boy	80.7

crowd	80.5

ceremony	79.9

wedding	79

furniture	78.7

wear	77.9

musician	77.9

education	75.8

musical instrument	51.1

wind instrument	33.5

man	23.5

people	20.6

male	20.6

brass	19.9

person	19.7

sax	17.3

stringed instrument	16.9

accordion	15.6

black	15.6

music	15.5

adult	14.3

percussion instrument	13.9

group	12.9

keyboard instrument	12.8

teacher	12.5

bowed stringed instrument	12.5

concert	11.6

night	11.5

cornet	11.3

blackboard	10.9

stage	10.7

rock	10.4

business	10.3

men	10.3

guitar	10.1

musician	10

singer	9.7

device	9.7

couple	9.6

love	9.5

marimba	9.4

art	9.1

silhouette	9.1

retro	9

job	8.8

businessman	8.8

violin	8.8

musical	8.6

dance	8.5

grunge	8.5

design	8.4

studio	8.4

house	8.3

vintage	8.3

indoor	8.2

style	8.2

interior	8

hair	7.9

hands	7.8

play	7.7

modern	7.7

old	7.7

performance	7.7

outfit	7.6

show	7.6

chair	7.6

club	7.5

smoke	7.4

professional	7.4

Flower	94

Plant	90.5

Botany	88

Black-and-white	83.4

Art	82.4

Adaptation	79.3

Monochrome photography	74

Monochrome	73.6

Painting	72.8

Room	70.1

Event	68.6

Visual arts	67.3

Font	67.3

Illustration	67.2

Chair	64.4

Stock photography	62.2

History	61.4

Still life photography	60.9

Petal	60.1

Photographic paper	58

text	98.7

person	98

people	81.8

crowd	79

group	78.2

white	70.3

funeral	67.6

old	51.7

crowded	25.9

clothes	22.7

streetview architecture	57.2%

paintings art	19.5%

text visuals	12.3%

interior objects	5.8%

people portraits	1.5%

Human Generated Data

Title

Untitled (elevated view of guests at tables in large banquet hall)

Date

1948-1950

People

Artist: Martin Schweig, American 20th century

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.9256

Human Generated Data

Title

Untitled (elevated view of guests at tables in large banquet hall)

People

Artist: Martin Schweig, American 20th century

Date

1948-1950

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.9256

Machine Generated Data

Tags

Amazoncreated on 2022-01-23

Clarifaicreated on 2023-10-26

Imaggacreated on 2022-01-23

Googlecreated on 2022-01-23

Microsoftcreated on 2022-01-23

Color Analysis

Face analysis

Amazon

Google

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Google Vision

Feature analysis

Amazon

Categories

Imagga

Captions

Microsoftcreated on 2022-01-23

Text analysis

Amazon
created on 2022-01-23

Clarifai
created on 2023-10-26

Imagga
created on 2022-01-23

Google
created on 2022-01-23

Microsoft
created on 2022-01-23

Microsoft
created on 2022-01-23