Human Generated Data

Title

War: Germany. Berlin. Prussian Guard Regiment: Life in a Regiment of the Prussian Guard: At mess: Canteen in rear of room.
Date

c. 1903
People

Artist: Waldemar Franz Herman Titzenthaler, German 1869 - 1937
Classification

Photographs
Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.3313.2

Human Generated Data

Title

War: Germany. Berlin. Prussian Guard Regiment: Life in a Regiment of the Prussian Guard: At mess: Canteen in rear of room.

People

Artist: Waldemar Franz Herman Titzenthaler, German 1869 - 1937

Date

c. 1903

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.3313.2

Machine Generated Data

Tags

Amazon
created on 2019-06-05

Human 99.6
Person 99.6
Person 98.1
Person 97.8
Person 97
Room 95
Indoors 95
Classroom 94.8
School 94.8
Person 94.2
Person 93.9
Person 92.4
Building 92.3
Person 85.6
Person 77.1
Factory 74.1
People 70.5
Person 70.3
Cafeteria 66.3
Restaurant 66.3
Person 64.5
Person 64.4
Person 61.5
Food 55.4

Clarifai
created on 2019-06-05

people 99.9
many 99.8
group together 98.8
group 98.7
adult 98
woman 95
man 93.7
furniture 90.9
leader 89.9
crowd 87.4
indoors 87.3
wear 87
administration 85.2
military 84.6
uniform 84.6
chair 83.7
room 81.1
war 80.2
several 80
child 79.6

Imagga
created on 2019-06-05

chandelier 75.5
interior 53.9
lighting fixture 53.4
room 41.6
fixture 39.9
house 33.4
furniture 31.3
home 30.3
table 29.7
decor 27.4
hall 26.8
chair 23.7
luxury 23.1
architecture 22.6
case 22.5
design 22.5
wood 20.8
lamp 20
floor 19.5
glass 19.2
residential 18.2
elegant 18
indoor 17.3
window 16.8
inside 16.5
hotel 16.2
decoration 15.9
light 15.4
living 15.2
style 14.1
residence 13.6
sofa 13.5
comfortable 13.4
modern 13.3
structure 12.8
wall 12.5
dining 12.4
restaurant 12.3
building 12.2
contemporary 12.2
classic 12.1
chairs 11.7
carpet 11.7
expensive 11.5
wooden 11.4
decorate 11.4
panel 11.3
rug 10.8
apartment 10.5
estate 10.4
elegance 10.1
flower 10
balcony 10
kitchen 9.8
vase 9.8
indoors 9.7
couch 9.7
upscale 8.9
seat 8.8
luxurious 8.8
flowers 8.7
real 8.5
food 8.5
dinner 8.4
old 8.4
lights 8.3
bed 7.9
bedroom 7.9
antique 7.8
empty 7.7
counter 7.7
relax 7.6
place 7.4
gold 7.4

Google
created on 2019-06-05

Photograph 95
Room 78
Class 73.5
Event 67
Crowd 57.8
State school 54.4
School 53
Team 52.3

Microsoft
created on 2019-06-05

person 99.1
indoor 92.7
clothing 92.2
group 88.5
old 71.7
man 69.9
people 60.6
school 50.6
posing 41.6
team 30.4
several 15.1
crowd 0.7

Color Analysis

Face analysis

Amazon

AWS Rekognition

Age 45-65
Gender Male, 50.7%
Disgusted 45.3%
Confused 45.2%
Surprised 45.1%
Calm 45.2%
Happy 45.1%
Angry 45.7%
Sad 53.4%

AWS Rekognition

Age 23-38
Gender Male, 50.1%
Angry 50.3%
Disgusted 45.4%
Sad 47.1%
Confused 45.3%
Happy 45.4%
Surprised 45.3%
Calm 46.4%

AWS Rekognition

Age 26-43
Gender Male, 54.2%
Confused 45.1%
Disgusted 45.5%
Calm 52.9%
Angry 45.2%
Happy 45.7%
Surprised 45.2%
Sad 45.3%

AWS Rekognition

Age 23-38
Gender Male, 54.6%
Disgusted 45.2%
Surprised 45.2%
Calm 47.7%
Angry 45.9%
Happy 45.2%
Sad 50.4%
Confused 45.4%

AWS Rekognition

Age 26-43
Gender Female, 51.6%
Calm 52%
Confused 45.2%
Angry 45.4%
Surprised 45.3%
Disgusted 45.8%
Sad 46.2%
Happy 45.2%

AWS Rekognition

Age 11-18
Gender Male, 51.8%
Disgusted 45.9%
Surprised 45.4%
Angry 46.7%
Confused 45.5%
Sad 49.7%
Calm 46.6%
Happy 45.1%

AWS Rekognition

Age 35-52
Gender Female, 50.1%
Angry 49.6%
Calm 49.5%
Sad 49.7%
Confused 49.5%
Disgusted 49.6%
Happy 50%
Surprised 49.5%

AWS Rekognition

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

AWS Rekognition

Age 57-77
Gender Female, 50%
Sad 45.4%
Surprised 45.3%
Confused 45.2%
Disgusted 53.1%
Happy 45.3%
Calm 45.2%
Angry 45.5%

AWS Rekognition

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

AWS Rekognition

Age 29-45
Gender Female, 50.4%
Happy 49.6%
Calm 49.5%
Sad 50.3%
Angry 49.5%
Confused 49.5%
Surprised 49.5%
Disgusted 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.2%
Disgusted 49.6%
Surprised 49.6%
Angry 49.6%
Confused 49.6%
Sad 49.7%
Calm 49.7%
Happy 49.6%

AWS Rekognition

Age 29-45
Gender Male, 50.4%
Confused 49.6%
Happy 49.6%
Sad 49.6%
Surprised 49.6%
Angry 49.6%
Disgusted 49.6%
Calm 49.9%

AWS Rekognition

Age 35-52
Gender Female, 54.4%
Disgusted 46%
Surprised 45.3%
Sad 46.3%
Calm 50.7%
Angry 46%
Happy 45.4%
Confused 45.2%

AWS Rekognition

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

AWS Rekognition

Age 19-36
Gender Female, 50.4%
Sad 50.2%
Calm 49.6%
Happy 49.6%
Disgusted 49.5%
Surprised 49.5%
Confused 49.5%
Angry 49.6%

AWS Rekognition

Age 26-44
Gender Male, 50.2%
Sad 50.2%
Disgusted 49.6%
Confused 49.5%
Surprised 49.5%
Calm 49.6%
Happy 49.5%
Angry 49.6%

AWS Rekognition

Age 26-43
Gender Female, 53.1%
Surprised 45.2%
Confused 45.2%
Sad 53.4%
Disgusted 45.4%
Calm 45.2%
Angry 45.4%
Happy 45.2%

AWS Rekognition

Age 30-47
Gender Female, 50.3%
Disgusted 49.6%
Angry 49.6%
Surprised 49.5%
Happy 49.6%
Sad 49.7%
Calm 50%
Confused 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.1%
Happy 49.8%
Surprised 49.6%
Angry 49.6%
Sad 49.6%
Confused 49.6%
Calm 49.9%
Disgusted 49.6%

AWS Rekognition

Age 35-52
Gender Male, 50%
Happy 49.6%
Angry 49.6%
Calm 49.7%
Confused 49.5%
Surprised 49.6%
Disgusted 49.6%
Sad 49.9%

AWS Rekognition

Age 45-65
Gender Male, 50.4%
Surprised 49.6%
Confused 49.6%
Sad 50%
Calm 49.5%
Disgusted 49.5%
Happy 49.6%
Angry 49.6%

AWS Rekognition

Age 23-38
Gender Female, 50.1%
Sad 50.2%
Surprised 49.5%
Angry 49.6%
Disgusted 49.5%
Confused 49.5%
Happy 49.5%
Calm 49.6%

AWS Rekognition

Age 17-27
Gender Male, 50.5%
Sad 49.7%
Happy 49.5%
Disgusted 49.7%
Calm 49.6%
Angry 49.6%
Confused 49.8%
Surprised 49.6%

AWS Rekognition

Age 45-66
Gender Female, 50.2%
Angry 49.5%
Happy 49.5%
Surprised 49.5%
Calm 49.5%
Confused 49.5%
Sad 50.2%
Disgusted 49.7%

AWS Rekognition

Age 38-57
Gender Female, 50.5%
Disgusted 49.6%
Confused 49.5%
Happy 49.8%
Calm 49.5%
Surprised 49.6%
Sad 49.9%
Angry 49.6%

AWS Rekognition

Age 14-25
Gender Female, 50.5%
Disgusted 49.5%
Angry 49.7%
Sad 49.9%
Surprised 49.6%
Happy 49.6%
Calm 49.8%
Confused 49.5%

AWS Rekognition

Age 26-44
Gender Male, 50.1%
Angry 49.6%
Calm 49.7%
Sad 49.9%
Confused 49.6%
Disgusted 49.6%
Happy 49.6%
Surprised 49.6%

AWS Rekognition

Age 16-27
Gender Male, 50.1%
Calm 49.5%
Disgusted 49.5%
Confused 49.5%
Happy 49.5%
Angry 49.6%
Surprised 49.5%
Sad 50.3%

AWS Rekognition

Age 26-43
Gender Female, 50.7%
Sad 53.9%
Disgusted 45.1%
Surprised 45.3%
Angry 45.2%
Happy 45.2%
Calm 45.2%
Confused 45.2%

AWS Rekognition

Age 11-18
Gender Male, 50.5%
Confused 49.5%
Happy 49.5%
Sad 50.4%
Surprised 49.5%
Angry 49.5%
Disgusted 49.5%
Calm 49.5%

AWS Rekognition

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

AWS Rekognition

Age 35-52
Gender Female, 50.7%
Happy 45.2%
Disgusted 45.8%
Sad 52%
Confused 45.5%
Angry 45.8%
Surprised 45.3%
Calm 45.4%

AWS Rekognition

Age 11-18
Gender Female, 50.4%
Surprised 49.5%
Confused 49.6%
Sad 50%
Calm 49.6%
Happy 49.5%
Disgusted 49.6%
Angry 49.6%

AWS Rekognition

Age 26-43
Gender Male, 50.4%
Calm 49.9%
Confused 49.7%
Angry 49.5%
Surprised 49.6%
Disgusted 49.5%
Sad 49.8%
Happy 49.5%

AWS Rekognition

Age 29-45
Gender Female, 54.1%
Happy 45.2%
Calm 46%
Sad 51.8%
Angry 45.5%
Confused 45.3%
Surprised 45.4%
Disgusted 45.8%

AWS Rekognition

Age 49-69
Gender Female, 50.3%
Disgusted 49.5%
Angry 49.5%
Sad 50.4%
Surprised 49.5%
Happy 49.5%
Calm 49.5%
Confused 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.3%
Surprised 49.6%
Confused 49.6%
Sad 49.7%
Disgusted 50%
Calm 49.6%
Angry 49.6%
Happy 49.6%

Feature analysis

Amazon

Person
Person 99.6%
Person 98.1%
Person 97.8%
Person 97%
Person 94.2%
Person 93.9%
Person 92.4%
Person 85.6%
Person 77.1%
Person 70.3%
Person 64.5%
Person 64.4%
Person 61.5%

Categories

Imagga

interior objects 96.8%
people portraits 2.6%

Text analysis

Amazon

P8T98,
a.

Google

melea
melea