Human Generated Data

Title

Races, Negroes: United States. Virginia. Hampton. Hampton Normal and Industrial School: Agencies Promoting Assimilation of the Negro. Training for Commercial and Industrial Employment. Hampton Normal and Agricultural Institute, Hampton, Va.: Second and Third Year Tailors.
Date

1899-1900
People

Artist: Frances Benjamin Johnston, American 1864 - 1952
Classification

Photographs
Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.469.1

Human Generated Data

Title

Races, Negroes: United States. Virginia. Hampton. Hampton Normal and Industrial School: Agencies Promoting Assimilation of the Negro. Training for Commercial and Industrial Employment. Hampton Normal and Agricultural Institute, Hampton, Va.: Second and Third Year Tailors.

People

Artist: Frances Benjamin Johnston, American 1864 - 1952

Date

1899-1900

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.469.1

Machine Generated Data

Tags

Amazon
created on 2019-06-05

Building 99.4
Factory 99.4
Assembly Line 99.4
Person 99
Human 99
Person 95.2
Person 95.1
Person 91.4
Person 91.1
Person 90.4
Person 90
Painting 89.4
Art 89.4
Person 86.3
Person 85.3
Person 84.2
Workshop 82.5
Person 81.3
Person 80.6
Person 76.5
Person 75.1
Clinic 72.1
Manufacturing 69.6
Person 67.2
Person 66.1
Person 61.7
Indoors 58.3
Lab 58
Room 57.9
Housing 55.8
Person 55.5
Person 45

Clarifai
created on 2019-06-05

people 100
group 99.1
many 99.1
group together 98.9
adult 97.7
furniture 96.5
man 96
room 94.5
administration 93
woman 91.9
several 90.4
military 89.3
leader 87.9
child 87.4
chair 86.8
crowd 83.9
war 82.6
home 81.7
recreation 81.3
vehicle 81

Imagga
created on 2019-06-05

shop 26.8
interior 22.1
mercantile establishment 20.5
room 20.1
barbershop 17.5
building 16.3
house 15.9
business 15.2
table 14.4
place of business 13.7
people 13.4
drawing 12.7
glass 12.6
old 12.5
chair 12.5
vintage 12.4
window 12.3
grunge 11.9
design 11.8
architecture 11.7
city 11.6
sketch 11.6
structure 11.5
indoors 11.4
home 11.2
restaurant 10.9
travel 10.6
men 10.3
light 10
history 9.8
modern 9.8
classroom 9.7
decor 9.7
urban 9.6
empty 9.4
furniture 9.3
office 9.2
male 9.2
frame 9.1
transportation 9
man 8.7
ancient 8.6
station 8.4
inside 8.3
pattern 8.2
retro 8.2
aged 8.1
art 8
hall 7.9
work 7.8
black 7.8
scene 7.8
bakery 7.5
floor 7.4
occupation 7.3
speed 7.3

Google
created on 2019-06-05

Photograph 95.1
Snapshot 86
Room 78
Photography 62.4
Building 55.4

Microsoft
created on 2019-06-05

person 98.7
indoor 96.8
clothing 84.9
man 75.5
group 61.5

Color Analysis

Face analysis

Amazon

AWS Rekognition

Age 35-52
Gender Female, 50.9%
Happy 45.1%
Sad 51.1%
Disgusted 45.2%
Calm 46.3%
Surprised 45.1%
Confused 45.3%
Angry 46.9%

AWS Rekognition

Age 26-43
Gender Male, 50.9%
Happy 45.1%
Surprised 45.1%
Confused 45.2%
Disgusted 45.1%
Calm 46.7%
Angry 45.3%
Sad 52.6%

AWS Rekognition

Age 15-25
Gender Male, 50.3%
Calm 49.7%
Disgusted 49.5%
Surprised 49.5%
Confused 49.5%
Angry 49.7%
Sad 50%
Happy 49.5%

AWS Rekognition

Age 35-55
Gender Female, 53.6%
Disgusted 45.4%
Confused 45.3%
Sad 52.5%
Angry 45.5%
Happy 45.3%
Surprised 45.3%
Calm 45.7%

AWS Rekognition

Age 45-63
Gender Male, 52.2%
Angry 45.8%
Happy 45.2%
Disgusted 45.3%
Confused 45.5%
Calm 48.8%
Surprised 45.4%
Sad 49%

AWS Rekognition

Age 38-59
Gender Male, 50.3%
Confused 49.5%
Happy 49.5%
Sad 50.2%
Disgusted 49.5%
Angry 49.5%
Calm 49.7%
Surprised 49.5%

AWS Rekognition

Age 15-25
Gender Female, 50.5%
Surprised 49.5%
Disgusted 49.5%
Sad 50.1%
Calm 49.6%
Confused 49.5%
Angry 49.6%
Happy 49.6%

AWS Rekognition

Age 26-43
Gender Female, 50.4%
Happy 49.8%
Angry 49.7%
Calm 49.5%
Sad 49.5%
Surprised 49.6%
Confused 49.5%
Disgusted 49.8%

AWS Rekognition

Age 20-38
Gender Female, 50.2%
Surprised 49.6%
Calm 49.6%
Happy 49.6%
Angry 49.7%
Sad 49.5%
Disgusted 49.9%
Confused 49.6%

AWS Rekognition

Age 4-9
Gender Female, 50%
Happy 50.3%
Disgusted 49.6%
Angry 49.5%
Confused 49.5%
Calm 49.6%
Surprised 49.5%
Sad 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.1%
Calm 49.6%
Sad 50.2%
Surprised 49.5%
Angry 49.6%
Happy 49.6%
Confused 49.6%
Disgusted 49.5%

AWS Rekognition

Age 20-38
Gender Male, 50.4%
Calm 49.6%
Confused 49.6%
Happy 49.6%
Surprised 49.5%
Angry 49.6%
Disgusted 49.6%
Sad 49.9%

AWS Rekognition

Age 35-52
Gender Male, 50.5%
Angry 49.6%
Surprised 49.5%
Calm 49.6%
Happy 49.5%
Confused 49.6%
Disgusted 49.5%
Sad 50.2%

AWS Rekognition

Age 35-52
Gender Female, 50.5%
Angry 49.6%
Surprised 49.5%
Disgusted 49.7%
Calm 49.7%
Sad 49.9%
Happy 49.6%
Confused 49.5%

AWS Rekognition

Age 27-44
Gender Female, 50.5%
Confused 49.6%
Disgusted 49.6%
Surprised 49.5%
Sad 49.9%
Angry 49.7%
Happy 49.6%
Calm 49.6%

AWS Rekognition

Age 20-38
Gender Male, 50.3%
Sad 50.3%
Disgusted 49.5%
Surprised 49.5%
Happy 49.5%
Confused 49.6%
Calm 49.6%
Angry 49.5%

AWS Rekognition

Age 23-38
Gender Female, 50.2%
Calm 49.6%
Disgusted 49.5%
Happy 49.5%
Confused 49.5%
Surprised 49.5%
Sad 50.4%
Angry 49.5%

Feature analysis

Amazon

Person 99%
Painting 89.4%

Categories

Imagga

interior objects 79.6%
streetview architecture 14.1%
text visuals 1.6%
food drinks 1.5%
paintings art 1.1%

Text analysis

Amazon

Third
Second
and
Second and Third Year Tailors.
Tailors.
Year
w

Google

Second and Third Year Tailors.
Second
and
Third
Year
Tailors.