Human Generated Data

Title

Untitled (group portrait of young children posed outdoors with nuns and priests)
Date

1950-1955
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, 4.2002.6582

Human Generated Data

Title

Untitled (group portrait of young children posed outdoors with nuns and priests)

People

Artist: Orrion Barger, American active 1913 - 1984

Date

1950-1955

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.6582

Machine Generated Data

Tags

Amazon
created on 2019-03-26

Human 97.6
Person 97.6
Person 97.1
Person 92.9
Person 92
Person 91.8
Person 91.1
Person 90.2
Person 88.7
Person 85.8
School 84
Room 84
Classroom 84
Indoors 84
Clothing 83.2
Apparel 83.2
Meal 81.3
Food 81.3
Kindergarten 77.4
Person 74
People 72.9
Furniture 72.7
Chair 72.7
Child 69.5
Kid 69.5
Person 67.2
Plant 67
Tree 67
Female 66.9
Person 66.7
Face 65.7
Person 65.4
Girl 63.3
Person 61.2
Crowd 58.2
Zoo 57.5
Animal 57.5
Person 47

Clarifai
created on 2019-03-26

people 99.7
group together 97.7
group 97.5
child 96.1
many 95.1
adult 95
woman 94.9
man 94.4
monochrome 86.2
wear 85.8
administration 84.9
portrait 84.9
music 83.7
street 83.5
several 83.5
boy 83.1
outfit 83
uniform 82.3
crowd 82.3
one 80.1

Imagga
created on 2019-03-26

chandelier 46.5
glass 42.9
equipment 39.5
pawn 37.4
lighting fixture 36.5
beaker 33.5
container 32.7
chemistry 30.9
laboratory 30.8
research 30.4
chemical 29.9
experiment 29.2
chessman 28.6
glassware 28.4
biology 27.5
fixture 27.3
science 26.7
flask 24.5
bottle 24.3
medical 23.8
water 22.7
liquid 22.6
lab 22.3
pharmacy 22.3
apparatus 20.6
h2o 19.6
glasses 19.4
aqua 19
biotechnology 18.6
medicine 18.5
scientific 18.4
development 18
acid 17.7
fluid 17.5
man 17.4
test 16.3
sample 15.5
transparent 15.2
sequencer 14.7
measure 14.4
game equipment 13.8
industry 13.6
discovery 13.6
scientist 12.7
tool 12.7
vessel 12.6
instrument 12.1
pharmaceutical 11.7
examination 11.7
tube 11.6
close 11.4
solution 11.4
sterilize 10.9
pharmacology 10.8
sterile 10.8
clear 10.5
wine 10.3
beakers 9.9
luxury 9.4
element 9.1
holder 8.9
colors 8.8
clinical 8.8
objects 8.7
health 8.3
bag 8.1
celebration 8
specimens 7.9
specimen 7.9
jar 7.8
black 7.8
gown 7.8
restaurant 7.8
scale 7.7
herbal 7.6
drops 7.5
clean 7.5
alcohol 7.3
decoration 7.3
metal 7.2
empty 7.1

Google
created on 2019-03-26

Photograph 96.5
Snapshot 84.7
Black-and-white 82.7
Team 82.2
Photography 70.6
Monochrome photography 69.6
Room 65.7
Stock photography 62.1
Monochrome 60.1
Interior design 52.6
Style 52.5

Microsoft
created on 2019-03-26

black and white 14.4
person 4.7
street 4.1
monochrome 3.9

Color Analysis

Face analysis

Amazon

AWS Rekognition

Age 35-52
Gender Male, 51.4%
Disgusted 46.4%
Angry 46.5%
Surprised 46.6%
Calm 47.8%
Happy 45.9%
Sad 46.1%
Confused 45.7%

AWS Rekognition

Age 26-43
Gender Female, 53%
Sad 47.4%
Confused 46.1%
Disgusted 45.9%
Calm 46.4%
Happy 45.5%
Angry 47.4%
Surprised 46.3%

AWS Rekognition

Age 26-43
Gender Female, 50.1%
Confused 46.1%
Disgusted 45.7%
Sad 48.2%
Angry 46.1%
Surprised 46.3%
Happy 45.3%
Calm 47.3%

AWS Rekognition

Age 26-43
Gender Male, 52.6%
Confused 45.2%
Disgusted 45.1%
Sad 45.1%
Angry 45.2%
Surprised 45.2%
Happy 53.2%
Calm 45.9%

AWS Rekognition

Age 35-52
Gender Female, 53.9%
Angry 46.5%
Happy 46.4%
Sad 50.2%
Calm 46.3%
Confused 45.3%
Disgusted 45.2%
Surprised 45.3%

AWS Rekognition

Age 26-43
Gender Female, 54.6%
Disgusted 45.6%
Confused 45.4%
Sad 46.5%
Happy 46.5%
Surprised 45.4%
Calm 50%
Angry 45.5%

AWS Rekognition

Age 26-43
Gender Female, 51.8%
Sad 50%
Disgusted 45.2%
Happy 45.4%
Angry 46.8%
Confused 45.2%
Calm 47.2%
Surprised 45.3%

AWS Rekognition

Age 16-27
Gender Female, 52.2%
Angry 45.6%
Surprised 45.6%
Sad 47.6%
Calm 49.9%
Confused 45.8%
Happy 45.3%
Disgusted 45.2%

AWS Rekognition

Age 38-59
Gender Female, 53.2%
Angry 45.5%
Sad 47.6%
Surprised 45.9%
Confused 45.5%
Calm 46.7%
Happy 48%
Disgusted 45.7%

AWS Rekognition

Age 35-52
Gender Male, 52.8%
Surprised 45.6%
Confused 45.3%
Disgusted 45.4%
Happy 46%
Sad 51.1%
Angry 45.6%
Calm 46%

AWS Rekognition

Age 26-43
Gender Female, 51.2%
Confused 45.5%
Angry 46%
Surprised 45.7%
Happy 47%
Calm 46.7%
Disgusted 45.7%
Sad 48.3%

AWS Rekognition

Age 26-43
Gender Female, 54.8%
Disgusted 45.2%
Surprised 45.4%
Calm 45.3%
Happy 49.7%
Sad 48.6%
Confused 45.2%
Angry 45.7%

AWS Rekognition

Age 26-43
Gender Male, 53.6%
Surprised 45.3%
Sad 51.4%
Calm 46.8%
Confused 45.3%
Disgusted 45.2%
Happy 45.3%
Angry 45.8%

AWS Rekognition

Age 15-25
Gender Female, 54%
Happy 45.9%
Calm 45.6%
Sad 50%
Angry 47.8%
Surprised 45.3%
Disgusted 45.2%
Confused 45.1%

AWS Rekognition

Age 26-44
Gender Male, 53.3%
Disgusted 45.4%
Happy 48.1%
Surprised 45.4%
Angry 45.7%
Sad 48.3%
Confused 45.4%
Calm 46.9%

AWS Rekognition

Age 26-43
Gender Male, 54.9%
Disgusted 45.3%
Happy 45%
Angry 45.1%
Sad 54%
Calm 45.1%
Confused 45.3%
Surprised 45.1%

AWS Rekognition

Age 26-43
Gender Female, 50.4%
Confused 45.4%
Calm 47.4%
Happy 46.5%
Disgusted 45.3%
Surprised 45.9%
Sad 48.7%
Angry 45.9%

Feature analysis

Amazon

Person 97.6%

Text analysis

Amazon

KODK-
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