Human Generated Data

Title

Charity, Children: Germany. Berlin. Friedrichs-Waisenhaus zu Rummelsburg: Friedrichs-Waisenhaus zu Rummelsburg (Municipal Orphanage, Berlin, Germany): Mealtime.
Date

c. 1900
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, 3.2002.631.2

Human Generated Data

Title

Charity, Children: Germany. Berlin. Friedrichs-Waisenhaus zu Rummelsburg: Friedrichs-Waisenhaus zu Rummelsburg (Municipal Orphanage, Berlin, Germany): Mealtime.

People

Artist: Unidentified Artist,

Date

c. 1900

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.631.2

Machine Generated Data

Tags

Amazon
created on 2019-06-07

Human 99.8
Person 99.8
Person 98.6
Person 97.8
Person 97
Person 96.9
Person 94.6
Floor 94.2
Person 92.4
Building 91.8
Factory 90.2
Person 86.3
Art 85
Painting 85
Person 83.5
Flooring 80.2
Person 80.1
Person 78.9
Person 75.3
Person 72.7
Person 72.6
Person 71.1
Person 70.2
Food 66.7
Meal 66.7
Person 65.7
Sailor Suit 64.7
People 64.4
Person 64.1
Person 63.7
Person 61.7
Crowd 61.5
Apparel 59.8
Clothing 59.8
Person 58.3
Restaurant 58.1
Cafeteria 58.1
Indoors 56.7
Assembly Line 56.3
Room 55.8
Person 42.4

Clarifai
created on 2019-06-07

people 100
many 99.9
group 99.8
group together 99.5
adult 98.6
military 95.8
man 95.4
wear 95.2
several 94.3
administration 92.8
room 91.9
vehicle 91.8
war 91.8
woman 89.7
leader 89.5
furniture 89.4
indoors 88.1
watercraft 86.9
uniform 86.1
home 84

Imagga
created on 2019-06-07

hall 74.3
table 24.5
chair 23.9
room 23.1
interior 21.2
architecture 17.3
house 16.8
furniture 16
restaurant 15.4
city 15
building 14.5
modern 13.3
floor 13
deck 12.9
home 12.8
wall 12.7
seat 12.7
decor 12.4
design 11.8
glass 11.7
classroom 11.4
travel 11.3
old 11.1
window 11
wood 10.8
wooden 10.5
structure 10.4
style 10.4
dinner 10.1
life 10.1
indoor 10
water 10
tourism 9.9
chairs 9.8
barroom 9.7
brick 9.6
residential 9.6
luxury 9.4
residence 9
people 8.9
urban 8.7
hotel 8.6
empty 8.6
construction 8.5
culture 8.5
tables 7.9
food 7.8
lunch 7.7
elegant 7.7
stone 7.7
lamp 7.6
relax 7.6
eat 7.5
landscape 7.4
light 7.3
decoration 7.3
transportation 7.2
summer 7.1
day 7.1
indoors 7

Google
created on 2019-06-07

Photograph 95.9
Snapshot 82.9
Stock photography 70.9
Black-and-white 56.4

Microsoft
created on 2019-06-07

building 99.3
floor 95.5
person 91.6
indoor 89.4
clothing 84.6
white 79.7
old 78.9
people 74.7
black 72.3
group 60.1
man 54.3

Color Analysis

Face analysis

Amazon

AWS Rekognition

Age 26-43
Gender Female, 50.5%
Calm 49.7%
Confused 49.5%
Happy 49.5%
Angry 49.5%
Surprised 49.5%
Disgusted 49.5%
Sad 50.2%

AWS Rekognition

Age 19-36
Gender Female, 50.2%
Calm 49.7%
Sad 50.3%
Surprised 49.5%
Disgusted 49.5%
Angry 49.5%
Confused 49.5%
Happy 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50%
Surprised 49.6%
Calm 49.7%
Sad 49.7%
Happy 49.6%
Confused 49.7%
Angry 49.7%
Disgusted 49.6%

AWS Rekognition

Age 16-27
Gender Female, 50.1%
Disgusted 49.5%
Confused 49.5%
Angry 49.5%
Calm 49.5%
Sad 50.5%
Surprised 49.5%
Happy 49.5%

AWS Rekognition

Age 12-22
Gender Female, 50.1%
Sad 50.4%
Angry 49.5%
Calm 49.5%
Surprised 49.5%
Disgusted 49.5%
Happy 49.5%
Confused 49.5%

AWS Rekognition

Age 20-38
Gender Male, 50.4%
Happy 49.5%
Surprised 49.5%
Confused 49.5%
Angry 49.5%
Sad 49.6%
Disgusted 49.5%
Calm 50.2%

AWS Rekognition

Age 20-38
Gender Female, 53%
Disgusted 45.3%
Surprised 45.4%
Sad 47.3%
Confused 45.3%
Calm 47.4%
Happy 48.2%
Angry 46%

AWS Rekognition

Age 20-38
Gender Male, 50.3%
Sad 49.8%
Surprised 49.6%
Calm 49.9%
Disgusted 49.6%
Confused 49.5%
Angry 49.7%
Happy 49.5%

AWS Rekognition

Age 26-43
Gender Male, 50.1%
Calm 49.7%
Angry 49.6%
Disgusted 49.6%
Surprised 49.6%
Happy 49.7%
Confused 49.5%
Sad 49.8%

AWS Rekognition

Age 14-25
Gender Female, 50.3%
Sad 49.6%
Calm 50.1%
Angry 49.5%
Disgusted 49.5%
Confused 49.6%
Surprised 49.6%
Happy 49.6%

AWS Rekognition

Age 26-43
Gender Female, 50.4%
Calm 49.7%
Disgusted 49.5%
Angry 49.5%
Sad 50%
Surprised 49.6%
Confused 49.6%
Happy 49.5%

AWS Rekognition

Age 38-59
Gender Female, 50.3%
Surprised 49.5%
Calm 49.6%
Sad 49.9%
Happy 49.7%
Confused 49.6%
Angry 49.6%
Disgusted 49.6%

AWS Rekognition

Age 23-38
Gender Female, 50.4%
Surprised 49.6%
Angry 49.6%
Calm 49.6%
Sad 50%
Confused 49.5%
Disgusted 49.6%
Happy 49.6%

AWS Rekognition

Age 19-36
Gender Female, 50.5%
Calm 50%
Disgusted 49.6%
Sad 49.7%
Happy 49.6%
Surprised 49.5%
Angry 49.6%
Confused 49.6%

AWS Rekognition

Age 23-38
Gender Female, 50.5%
Surprised 49.5%
Disgusted 49.7%
Sad 49.6%
Angry 49.9%
Calm 49.6%
Happy 49.6%
Confused 49.5%

AWS Rekognition

Age 23-38
Gender Female, 50.2%
Sad 49.9%
Confused 49.5%
Calm 49.6%
Angry 49.6%
Disgusted 49.6%
Happy 49.7%
Surprised 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50%
Disgusted 49.9%
Surprised 49.5%
Angry 49.6%
Happy 49.6%
Sad 49.7%
Calm 49.6%
Confused 49.6%

AWS Rekognition

Age 17-27
Gender Male, 50.1%
Disgusted 49.6%
Confused 49.7%
Surprised 49.7%
Calm 49.7%
Happy 49.7%
Angry 49.6%
Sad 49.7%

AWS Rekognition

Age 20-38
Gender Female, 50.4%
Sad 50%
Surprised 49.5%
Calm 49.6%
Disgusted 49.7%
Confused 49.5%
Angry 49.6%
Happy 49.6%

AWS Rekognition

Age 35-52
Gender Female, 50.4%
Sad 50.2%
Confused 49.5%
Disgusted 49.5%
Angry 49.6%
Happy 49.5%
Surprised 49.5%
Calm 49.7%

AWS Rekognition

Age 20-38
Gender Female, 50.5%
Surprised 49.6%
Calm 49.6%
Sad 49.7%
Happy 49.6%
Confused 49.8%
Angry 49.5%
Disgusted 49.5%

AWS Rekognition

Age 35-52
Gender Female, 50%
Sad 49.7%
Surprised 49.7%
Disgusted 49.6%
Confused 49.5%
Happy 49.5%
Calm 49.8%
Angry 49.7%

AWS Rekognition

Age 35-52
Gender Male, 50.4%
Calm 49.5%
Surprised 49.5%
Confused 49.5%
Angry 49.5%
Sad 49.8%
Happy 49.5%
Disgusted 50.2%

AWS Rekognition

Age 17-27
Gender Female, 50%
Disgusted 49.7%
Surprised 49.5%
Happy 49.5%
Calm 49.7%
Angry 49.5%
Sad 50%
Confused 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.5%
Disgusted 49.9%
Calm 49.7%
Confused 49.5%
Sad 49.6%
Angry 49.6%
Surprised 49.5%
Happy 49.7%

AWS Rekognition

Age 26-43
Gender Female, 50.2%
Surprised 49.5%
Disgusted 49.5%
Happy 49.5%
Sad 50.3%
Angry 49.6%
Calm 49.6%
Confused 49.5%

AWS Rekognition

Age 27-44
Gender Female, 50.1%
Angry 49.5%
Surprised 49.5%
Sad 49.5%
Confused 49.5%
Happy 49.5%
Calm 50.3%
Disgusted 49.6%

AWS Rekognition

Age 35-52
Gender Female, 50.2%
Confused 49.5%
Surprised 49.5%
Happy 49.5%
Sad 50%
Disgusted 49.5%
Angry 49.5%
Calm 49.8%

AWS Rekognition

Age 30-47
Gender Female, 50.2%
Angry 49.6%
Happy 49.5%
Confused 49.5%
Disgusted 49.6%
Sad 50%
Surprised 49.5%
Calm 49.6%

AWS Rekognition

Age 26-43
Gender Female, 50.1%
Happy 49.5%
Calm 49.5%
Disgusted 49.6%
Angry 49.5%
Surprised 49.5%
Sad 50.4%
Confused 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.4%
Happy 49.5%
Calm 50.1%
Disgusted 49.6%
Angry 49.5%
Surprised 49.5%
Sad 49.6%
Confused 49.5%

AWS Rekognition

Age 23-38
Gender Female, 50.4%
Angry 49.5%
Sad 49.6%
Happy 49.5%
Surprised 49.5%
Disgusted 49.5%
Confused 49.6%
Calm 50.3%

AWS Rekognition

Age 35-52
Gender Female, 50.4%
Disgusted 49.6%
Happy 49.6%
Confused 49.5%
Sad 49.8%
Angry 49.6%
Surprised 49.6%
Calm 49.9%

AWS Rekognition

Age 26-43
Gender Female, 50.3%
Confused 49.5%
Disgusted 50.1%
Surprised 49.5%
Sad 49.7%
Happy 49.5%
Angry 49.6%
Calm 49.5%

Feature analysis

Amazon

Person 99.8%
Painting 85%