AI Data for Untitled (men seated at dining tables at convention) | AI Explorer

Machine Generated Data

Color Analysis

Face analysis

Amazon

Google

AWS Rekognition

Age	56-64
Gender	Male, 99.9%
Confused	59.8%
Calm	24.1%
Surprised	8.6%
Sad	3.8%
Angry	1.4%
Fear	1.3%
Disgusted	0.9%
Happy	0.2%

AWS Rekognition

Age	36-44
Gender	Male, 99.3%
Happy	71.4%
Sad	8.4%
Calm	6.4%
Surprised	5.5%
Angry	3.5%
Disgusted	1.9%
Fear	1.6%
Confused	1.3%

AWS Rekognition

Age	39-47
Gender	Male, 98.4%
Calm	99.8%
Happy	0.1%
Sad	0%
Confused	0%
Angry	0%
Surprised	0%
Disgusted	0%
Fear	0%

AWS Rekognition

Age	49-57
Gender	Male, 94.8%
Calm	65.9%
Sad	33.4%
Confused	0.2%
Happy	0.2%
Angry	0.1%
Surprised	0.1%
Disgusted	0.1%
Fear	0%

AWS Rekognition

Age	33-41
Gender	Female, 77.5%
Sad	85.6%
Calm	4.3%
Disgusted	3.4%
Confused	1.8%
Angry	1.7%
Surprised	1.4%
Happy	1%
Fear	0.9%

AWS Rekognition

Age	50-58
Gender	Male, 79.1%
Calm	99.9%
Sad	0.1%
Surprised	0%
Confused	0%
Happy	0%
Angry	0%
Disgusted	0%
Fear	0%

AWS Rekognition

Age	39-47
Gender	Male, 93.4%
Calm	99.4%
Angry	0.4%
Confused	0.1%
Sad	0%
Disgusted	0%
Surprised	0%
Happy	0%
Fear	0%

AWS Rekognition

Age	47-53
Gender	Male, 99.8%
Calm	88.8%
Confused	5%
Happy	2.2%
Sad	1.6%
Disgusted	1.1%
Angry	0.7%
Surprised	0.4%
Fear	0.2%

AWS Rekognition

Age	47-53
Gender	Male, 76%
Calm	96.2%
Happy	1.5%
Disgusted	0.8%
Surprised	0.7%
Confused	0.3%
Angry	0.3%
Sad	0.1%
Fear	0.1%

AWS Rekognition

Age	41-49
Gender	Male, 99.6%
Calm	99%
Happy	0.5%
Sad	0.3%
Confused	0.1%
Disgusted	0%
Angry	0%
Surprised	0%
Fear	0%

AWS Rekognition

Age	23-31
Gender	Female, 94.1%
Calm	93.8%
Happy	4.4%
Sad	1%
Angry	0.2%
Confused	0.2%
Surprised	0.1%
Fear	0.1%
Disgusted	0.1%

AWS Rekognition

Age	34-42
Gender	Female, 50.7%
Calm	58.5%
Happy	17.9%
Sad	12.2%
Surprised	4.7%
Confused	4.3%
Angry	1.2%
Disgusted	0.9%
Fear	0.2%

AWS Rekognition

Age	23-31
Gender	Male, 90.4%
Sad	62%
Calm	24.1%
Angry	5.6%
Confused	4.9%
Happy	1.4%
Disgusted	0.8%
Surprised	0.6%
Fear	0.5%

AWS Rekognition

Age	38-46
Gender	Male, 81.3%
Calm	87.3%
Happy	5.9%
Sad	3.9%
Confused	1.2%
Disgusted	0.8%
Angry	0.3%
Surprised	0.3%
Fear	0.2%

AWS Rekognition

Age	21-29
Gender	Female, 98.4%
Calm	99.8%
Sad	0.1%
Surprised	0%
Confused	0%
Angry	0%
Disgusted	0%
Fear	0%
Happy	0%

AWS Rekognition

Age	47-53
Gender	Male, 96.1%
Calm	32.4%
Happy	26.7%
Confused	18.5%
Sad	9.8%
Angry	5.1%
Surprised	4.1%
Disgusted	2%
Fear	1.4%

AWS Rekognition

Age	27-37
Gender	Male, 98.8%
Calm	57.7%
Sad	26.9%
Happy	5.5%
Surprised	2.6%
Angry	2.5%
Disgusted	2.4%
Fear	1.5%
Confused	1%

AWS Rekognition

Age	33-41
Gender	Male, 88%
Calm	95.5%
Happy	3.4%
Sad	0.5%
Surprised	0.2%
Confused	0.1%
Disgusted	0.1%
Fear	0.1%
Angry	0.1%

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	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	Unlikely
Headwear	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	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	Very unlikely

Google Vision

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

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	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

Feature analysis

Amazon

Person	99%

Chair	92.8%

Captions

Microsoft
created on 2022-01-22

a group of people standing in front of a crowd	90.5%

a group of people standing in front of a crowd of people	89%

a group of people in front of a crowd	88.9%

Text analysis

Amazon

EXPENSE

SCOUT

300

250

BOY SCOUT

PROPOSED

350

100

ALTERNATE

750

BOY

RETAIL

1949 ALTERNATE

1949

150

LIASON

SECTY EXPENSE

888888

CVIC

PUBLICITY

SECTY

DEFICIT

1989 PROPOSED BLOGET

CINIC LIASON

RETAIL TRADES

350 00

BLOGET

SKY

CVIC LANSON

i50 50

1989

CINIC

i50

SKY EXPENCE

AODO 888888

ALTERNATS

TRADES

COMMONITY

NETAL

COMMINDTY

- THE KAZ

LANSON

EXPENCE

COMMONITY SERVICE

AGRICULTURE

2,390

KAZ

SERVICE

45-26

NETAL Seco

WHEN

ARCIATURE

THE

1890

KODAK-SVEELA

20.00

WIT

392

KOWN

COST MS WIT

Seco

CONTING

COST MS

30.00

2.39c

AODO

154

Title Untitled (men seated at dining tables at convention)	Date 1949
People Artist: Orrion Barger, American active 1913 - 1984	Classification Photographs
Credit Line Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.6230

Person	99

Human	99

Person	98.2

Person	98.1

Person	98

Person	97.9

Person	97.2

Furniture	96

Person	95.7

Person	93.9

Indoors	93.4

Classroom	93.4

School	93.4

Room	93.4

Chair	92.8

Person	92.6

Chair	87.6

Person	86.1

Person	85.1

Person	82.2

Chair	80.4

Table	77

Restaurant	76.7

Cafeteria	71.3

Person	71.2

Person	67.3

Chair	66.7

Person	66.4

Meal	59.6

Food	59.6

Female	58.8

Dining Table	55.9

People	55.5

people	100

many	99.6

group	99.1

group together	99.1

adult	98.3

man	97.1

education	96.2

woman	95.8

administration	95.6

furniture	94

elementary school	93.4

leader	92.1

child	91.8

classroom	91.5

room	91.2

chair	90.7

school	90.1

teacher	87.7

league	85.6

wear	85.4

classroom	47.5

room	44.2

marimba	41.1

man	39.7

percussion instrument	36.1

male	35.4

musical instrument	30.3

people	30.1

blackboard	29.3

person	28.3

businessman	26.5

business	24.3

table	22.6

education	20.8

adult	20.3

student	20

teacher	19.2

group	18.5

men	18

meeting	17.9

school	15.9

office	15.3

job	14.1

smiling	13.7

casual	13.5

desk	13.4

happy	13.1

sitting	12.9

looking	12.8

work	12.6

modern	12.6

chair	12.5

team	12.5

class	12.5

center	12.4

interior	12.4

senior	12.2

indoor	11.9

board	11.7

lifestyle	11.5

indoors	11.4

hand	11.4

businesspeople	11.4

computer	11.2

mature	11.1

women	11.1

portrait	11

businesswoman	10.9

teaching	10.7

colleagues	10.7

success	10.4

old	10.4

college	10.4

handsome	9.8

40s	9.7

discussion	9.7

new	9.7

technology	9.6

talking	9.5

laptop	9.3

teamwork	9.3

professional	9.2

holding	9.1

hall	9

working	8.8

home	8.8

together	8.8

couple	8.7

boy	8.7

chart	8.6

smile	8.5

plan	8.5

restaurant	8.5

building	8.4

manager	8.4

20s	8.2

cheerful	8.1

suit	8.1

university	8

to	8

discussing	7.8

happiness	7.8

conference	7.8

corporate	7.7

engineer	7.7

diagram	7.7

two	7.6

finance	7.6

sign	7.5

study	7.5

occupation	7.3

black	7.2

idea	7.1

family	7.1

Furniture	95.4

Table	94

Chair	92.8

Coat	89.6

Suit	85.9

Black-and-white	83.1

Event	73.5

Monochrome	72.5

Monochrome photography	71.3

Vintage clothing	70

Recreation	69.4

Room	67.7

History	66.4

Font	65.2

Games	63.8

Stock photography	62.9

Sitting	60.6

Team	59.1

Art	59

Photo caption	55.3

person	98.4

table	92

text	91.5

clothing	77.3

group	69.6

chair	65

man	62.2

furniture	61.3

restaurant	16.3

crowd	0.7

streetview architecture	48.4%

people portraits	17.7%

events parties	12.6%

paintings art	10.2%

interior objects	5.7%

text visuals	2%

pets animals	1.7%

Human Generated Data

Title

Untitled (men seated at dining tables at convention)

Date

1949

People

Artist: Orrion Barger, American active 1913 - 1984

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.6230

Human Generated Data

Title

Untitled (men seated at dining tables at convention)

People

Artist: Orrion Barger, American active 1913 - 1984

Date

1949

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.6230

Machine Generated Data

Tags

Amazoncreated on 2022-01-22

Clarifaicreated on 2023-10-26

Imaggacreated on 2022-01-22

Googlecreated on 2022-01-22

Microsoftcreated on 2022-01-22

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

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 2022-01-22

Text analysis

Amazon

Amazon
created on 2022-01-22

Clarifai
created on 2023-10-26

Imagga
created on 2022-01-22

Google
created on 2022-01-22

Microsoft
created on 2022-01-22

Microsoft
created on 2022-01-22