Human Generated Data

Title

Industrial Problems, Welfare Work: United States. Ohio. Dayton. National Cash Register Company: Welfare Institutions of the National Cash Register Company, Dayton, Ohio.: Departments: Typewriters
Date

c. 1903
People

Artist: Unidentified Artist,

Classification

Photographs
Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.328.B.4

Human Generated Data

Title

Industrial Problems, Welfare Work: United States. Ohio. Dayton. National Cash Register Company: Welfare Institutions of the National Cash Register Company, Dayton, Ohio.: Departments: Typewriters

People

Artist: Unidentified Artist,

Date

c. 1903

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.328.B.4

Machine Generated Data

Tags

Amazon
created on 2022-06-25

Building 99.2
Factory 99
Person 98.7
Human 98.7
Person 98.2
Person 98
Person 97.3
Person 95.7
Assembly Line 94.6
Person 94.5
Person 93.8
Person 91.9
Person 84.9
Person 84.7
Room 81.9
Indoors 81.9
Person 76.3
Person 63.5
Person 42.3

Clarifai
created on 2025-01-10

people 100
many 99.7
group 99.6
group together 98.7
adult 98.6
room 96.9
furniture 96.9
man 96.3
war 96.1
education 94.7
vehicle 92.8
home 92.6
several 92.3
school 92
administration 91.4
woman 87.4
newspaper 86.3
employee 85.6
child 85.3
sit 83.4

Imagga
created on 2022-06-25

shop 65.7
restaurant 54.4
mercantile establishment 47.9
interior 45.1
bakery 40.6
building 37.7
place of business 31.8
chair 31.6
table 30.2
house 29.2
furniture 29
home 27.1
room 24.6
decor 23.9
barbershop 22.4
structure 22
style 20
design 19.7
dining 19
decoration 18.8
stall 18.3
luxury 18
kitchen 18
clinic 17.6
architecture 17.2
glass 17.1
indoor 16.4
food 16.4
dinner 16.2
floor 15.8
chairs 15.7
cafeteria 15.6
establishment 15.6
modern 15.4
hotel 15.3
wood 15
window 15
inside 14.7
lamp 13.3
wooden 13.2
party 12.9
empty 12.9
elegant 12.8
light 12.7
old 12.5
service 12
bar 12
eat 11.7
drink 11.7
city 11.6
setting 11.6
residential 11.5
indoors 11.4
contemporary 11.3
lunch 10.3
wall 10.3
library 10.1
traditional 10
tables 9.8
catering 9.8
urban 9.6
banquet 9.5
counter 9.4
place 9.3
relax 9.3
cook 9.1
reception 8.8
dine 8.8
flowers 8.7
patio 8.5
plate 8.5
china 8.5
wedding 8.3
stylish 8.1
family 8
drawer 7.9
stove 7.9
oven 7.8
serve 7.8
nobody 7.8
bookshop 7.7
windows 7.7
apartment 7.7
comfortable 7.6
fine 7.6
decorate 7.6
real 7.6
stone 7.6
meal 7.4
town 7.4
retro 7.4
celebration 7.2
seat 7.1

Google
created on 2022-06-25

Building 83.4
Table 83
Monochrome photography 72.3
Monochrome 72.2
Event 71.8
Room 69
Design 68.4
Mass production 65.5
History 64.3
Window 63.8
Class 57.6
Collection 52
Hall 51.9
Office equipment 51

Microsoft
created on 2022-06-25

indoor 91.7
window 82.6
library 65.6
old 57.7
building 51.2
restaurant 18.8
dining room 9

Color Analysis

Face analysis

Amazon

Google

AWS Rekognition

Age 33-41
Gender Female, 62.8%
Sad 100%
Surprised 6.6%
Fear 6.2%
Calm 4.1%
Disgusted 0.9%
Angry 0.7%
Confused 0.2%
Happy 0.1%

AWS Rekognition

Age 4-12
Gender Female, 100%
Sad 99.8%
Calm 26.8%
Surprised 6.6%
Fear 6.1%
Angry 0.8%
Disgusted 0.4%
Confused 0.4%
Happy 0.3%

AWS Rekognition

Age 48-56
Gender Female, 92.4%
Sad 100%
Surprised 6.3%
Fear 5.9%
Calm 1.7%
Confused 0.8%
Angry 0.1%
Happy 0.1%
Disgusted 0.1%

AWS Rekognition

Age 48-54
Gender Female, 82.8%
Sad 100%
Surprised 6.3%
Fear 5.9%
Calm 0.9%
Angry 0.1%
Confused 0.1%
Disgusted 0.1%
Happy 0%

AWS Rekognition

Age 6-14
Gender Male, 77.3%
Calm 82.5%
Sad 8.2%
Fear 6.7%
Surprised 6.4%
Confused 3.3%
Happy 0.9%
Angry 0.7%
Disgusted 0.4%

AWS Rekognition

Age 21-29
Gender Female, 90.3%
Sad 98.2%
Calm 29.4%
Surprised 6.9%
Fear 6.8%
Confused 4.6%
Disgusted 3.6%
Angry 3.3%
Happy 0.9%

AWS Rekognition

Age 16-24
Gender Male, 66.9%
Calm 55.2%
Sad 34.7%
Angry 9%
Surprised 7.1%
Fear 7%
Happy 4.3%
Disgusted 2.4%
Confused 2.3%

AWS Rekognition

Age 39-47
Gender Male, 88.2%
Sad 98.6%
Disgusted 28.6%
Surprised 7.3%
Fear 6.1%
Calm 5.2%
Confused 3.8%
Angry 2.4%
Happy 0.7%

AWS Rekognition

Age 16-22
Gender Male, 99.4%
Calm 53.2%
Angry 36.6%
Surprised 6.7%
Fear 6.1%
Sad 4%
Happy 2.1%
Confused 1.3%
Disgusted 0.7%

AWS Rekognition

Age 16-24
Gender Male, 90%
Sad 100%
Surprised 6.5%
Fear 6.1%
Disgusted 3.5%
Angry 2.4%
Calm 1.8%
Confused 0.3%
Happy 0.2%

AWS Rekognition

Age 19-27
Gender Male, 98.8%
Sad 61%
Calm 44%
Angry 13.1%
Surprised 7.8%
Fear 6.8%
Confused 3.8%
Disgusted 2.6%
Happy 1.4%

AWS Rekognition

Age 18-26
Gender Female, 99.5%
Sad 85.7%
Calm 27.2%
Fear 11.1%
Surprised 9.4%
Disgusted 6.3%
Angry 5.3%
Happy 5.3%
Confused 1.1%

AWS Rekognition

Age 18-26
Gender Male, 99.3%
Sad 77.4%
Calm 55.6%
Fear 6.7%
Surprised 6.6%
Angry 2.1%
Confused 2.1%
Happy 1%
Disgusted 1%

AWS Rekognition

Age 23-33
Gender Male, 98.3%
Calm 42.3%
Confused 41.1%
Surprised 6.8%
Happy 6.3%
Fear 6.3%
Sad 5.2%
Angry 0.9%
Disgusted 0.9%

AWS Rekognition

Age 2-8
Gender Male, 87.3%
Calm 82.3%
Fear 7.8%
Surprised 6.7%
Angry 4.3%
Sad 3.3%
Confused 2.8%
Happy 1.3%
Disgusted 0.7%

AWS Rekognition

Age 19-27
Gender Male, 98.3%
Sad 99.9%
Calm 21.1%
Surprised 6.4%
Fear 5.9%
Confused 1.3%
Angry 0.7%
Disgusted 0.3%
Happy 0.2%

AWS Rekognition

Age 23-31
Gender Male, 79.9%
Sad 99.7%
Calm 26.6%
Surprised 6.5%
Fear 6.1%
Angry 2.7%
Happy 1.6%
Confused 0.9%
Disgusted 0.8%

AWS Rekognition

Age 19-27
Gender Female, 66%
Calm 61.6%
Sad 45.3%
Surprised 8%
Fear 6.1%
Angry 4.4%
Disgusted 2.9%
Confused 1.4%
Happy 0.6%

AWS Rekognition

Age 20-28
Gender Male, 81.4%
Sad 75.8%
Calm 36.9%
Surprised 10.3%
Fear 8.2%
Happy 6.9%
Confused 4.3%
Angry 3.8%
Disgusted 1.7%

AWS Rekognition

Age 6-14
Gender Male, 93.8%
Calm 45.1%
Confused 42.2%
Surprised 7.3%
Fear 7%
Sad 3.7%
Angry 2.3%
Happy 0.8%
Disgusted 0.8%

AWS Rekognition

Age 6-14
Gender Male, 92.8%
Calm 50.4%
Angry 25.2%
Sad 8.7%
Surprised 7.5%
Fear 6.8%
Confused 4.4%
Disgusted 3.7%
Happy 1.3%

AWS Rekognition

Age 18-24
Gender Male, 97.6%
Calm 80.2%
Sad 14.5%
Surprised 6.4%
Fear 6%
Angry 2.1%
Confused 1.4%
Happy 0.9%
Disgusted 0.5%

AWS Rekognition

Age 16-22
Gender Male, 88.5%
Calm 59.6%
Sad 35.7%
Confused 11.2%
Surprised 6.8%
Fear 6.2%
Angry 2.2%
Disgusted 1.5%
Happy 0.9%

AWS Rekognition

Age 16-24
Gender Male, 98.8%
Calm 92.4%
Surprised 6.4%
Fear 6.2%
Sad 3.2%
Happy 1.3%
Angry 1.1%
Disgusted 0.7%
Confused 0.5%

AWS Rekognition

Age 2-8
Gender Male, 77.8%
Calm 99%
Surprised 6.3%
Fear 6.1%
Sad 2.2%
Confused 0.1%
Angry 0.1%
Disgusted 0.1%
Happy 0%

AWS Rekognition

Age 12-20
Gender Female, 55.2%
Calm 82%
Sad 8.1%
Fear 6.9%
Surprised 6.7%
Confused 1.7%
Disgusted 1.3%
Angry 1%
Happy 0.9%

AWS Rekognition

Age 6-14
Gender Female, 53.9%
Calm 97.9%
Surprised 6.3%
Fear 5.9%
Sad 2.2%
Disgusted 0.7%
Happy 0.6%
Angry 0.2%
Confused 0.1%

AWS Rekognition

Age 7-17
Gender Male, 77.3%
Calm 87.9%
Surprised 6.7%
Fear 6.2%
Sad 4.9%
Confused 1.9%
Angry 1%
Happy 0.9%
Disgusted 0.7%

AWS Rekognition

Age 16-24
Gender Female, 77.3%
Calm 73.6%
Sad 7.2%
Surprised 6.8%
Fear 6.3%
Happy 5.6%
Angry 5.1%
Confused 3.6%
Disgusted 1.2%

AWS Rekognition

Age 6-14
Gender Female, 66.9%
Calm 91.4%
Surprised 6.5%
Fear 6.2%
Sad 3.7%
Angry 1.3%
Confused 0.8%
Disgusted 0.7%
Happy 0.5%

AWS Rekognition

Age 22-30
Gender Male, 98.7%
Calm 98%
Surprised 6.3%
Fear 5.9%
Sad 2.4%
Angry 0.5%
Happy 0.2%
Confused 0.2%
Disgusted 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 Possible

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 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 Likely

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 Likely

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 Unlikely

Google Vision

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

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 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 Likely

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 Unlikely

Google Vision

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

Feature analysis

Amazon

Person
Person 98.7%
Person 98.2%
Person 98%
Person 97.3%
Person 95.7%
Person 94.5%
Person 93.8%
Person 91.9%
Person 84.9%
Person 84.7%
Person 76.3%
Person 63.5%
Person 42.3%

Categories

Imagga

interior objects 97.9%
streetview architecture 2%