Human Generated Data

Title

Education, Industrial: United States. New York. New York City. Vacation Schools: New York City Public Schools. Examples of the Adaptation of Education to Special City Needs: Brooklyn Vacation School - Raffia Work.
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, 3.2002.358

Human Generated Data

Title

Education, Industrial: United States. New York. New York City. Vacation Schools: New York City Public Schools. Examples of the Adaptation of Education to Special City Needs: Brooklyn Vacation School - Raffia Work.

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, 3.2002.358

Machine Generated Data

Tags

Amazon
created on 2019-06-04

Restaurant 98
Human 94.3
Crowd 94.3
Room 93.6
Indoors 93.6
Audience 87.7
Person 84.1
Classroom 81.5
School 81.5
Cafeteria 79.1
Cafe 72
Person 69.6
Text 69
Concert 68.8
Person 66.7
Person 66.2
Person 65.6
Speech 63.6
Lecture 63.6
Person 63.3
Person 60.2
Theater 56.6
Food 56
Food Court 55.3
Furniture 55.3
Table 55.3
Person 44.6

Clarifai
created on 2019-06-04

people 98.5
many 97.7
group 96.8
print 96.2
adult 92.7
illustration 92.5
cavalry 91.2
art 90.6
man 90.5
lithograph 89.2
text 88.2
military 88
war 86.8
paper 86.5
crowd 85.2
landscape 84.5
mammal 84
bill 83.2
no person 81.7
wear 81

Imagga
created on 2019-06-04

newspaper 47.7
book jacket 41.1
product 35.6
jacket 32
creation 29
grunge 28.9
old 25.8
daily 24.8
vintage 24.8
wrapping 24.3
comic book 23.8
paper 21.9
retro 21.3
antique 19
texture 16.7
covering 16.4
aged 16.3
dirty 16.3
frame 15.8
design 15.8
ancient 15.6
art 13.7
black 13.2
pattern 12.3
business 12.1
space 11.6
blank 11.1
money 11.1
letter 11
rough 10.9
textured 10.5
bill 10.5
grungy 10.4
decoration 10.4
wall 10.3
card 10.2
structure 10.1
paint 10
border 9.9
material 9.8
text 9.6
print media 9.5
old fashioned 9.5
dollar 9.3
building 9.2
cash 9.1
history 8.9
web site 8.9
brown 8.8
scratch 8.8
forest 8.7
messy 8.7
worn 8.6
damaged 8.6
poster 8.5
drawing 8.3
silhouette 8.3
sign 8.3
menu 8.2
currency 8.1
graphic 8
postmark 7.9
postage 7.9
postal 7.8
artistic 7.8
color 7.8
travel 7.7
stamp 7.7
empty 7.7
wallpaper 7.7
mail 7.7
finance 7.6
landscape 7.4
man 7.4
bank 7.2

Google
created on 2019-06-04

Photograph 96.2
Text 94.1
Snapshot 83.9
Room 74.4
History 73.3
Collection 68.1
Photography 67.8
Art 67.7
Adaptation 67
Paper product 66
Crowd 62.7
Paper 61.1
Illustration 54.5
Tourist attraction 52.8

Microsoft
created on 2019-06-04

handwriting 85.5
scene 76.7
person 74.8
room 41.6

Color Analysis

Face analysis

Amazon

AWS Rekognition

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

AWS Rekognition

Age 14-23
Gender Female, 50.2%
Calm 49.8%
Happy 49.6%
Surprised 49.6%
Sad 49.6%
Angry 49.7%
Disgusted 49.7%
Confused 49.5%

AWS Rekognition

Age 10-15
Gender Male, 50.2%
Happy 49.6%
Angry 49.7%
Confused 49.6%
Disgusted 49.6%
Sad 49.8%
Calm 49.6%
Surprised 49.6%

AWS Rekognition

Age 6-13
Gender Female, 50.5%
Disgusted 49.6%
Confused 49.5%
Surprised 49.5%
Calm 49.7%
Happy 49.6%
Angry 49.7%
Sad 49.8%

AWS Rekognition

Age 23-38
Gender Female, 50.3%
Disgusted 49.6%
Happy 49.5%
Calm 49.6%
Angry 49.6%
Confused 49.5%
Sad 50.1%
Surprised 49.6%

AWS Rekognition

Age 16-27
Gender Male, 50%
Angry 49.6%
Sad 50.3%
Disgusted 49.5%
Calm 49.5%
Happy 49.5%
Surprised 49.5%
Confused 49.5%

AWS Rekognition

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

AWS Rekognition

Age 10-15
Gender Female, 50.4%
Angry 49.6%
Surprised 49.6%
Disgusted 49.5%
Happy 49.5%
Sad 49.8%
Confused 49.6%
Calm 49.9%

AWS Rekognition

Age 23-38
Gender Female, 50.4%
Confused 49.5%
Angry 49.5%
Surprised 49.5%
Sad 50.2%
Disgusted 49.5%
Calm 49.7%
Happy 49.5%

AWS Rekognition

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

AWS Rekognition

Age 10-15
Gender Female, 50.4%
Sad 49.9%
Disgusted 49.7%
Confused 49.5%
Calm 49.6%
Happy 49.6%
Surprised 49.5%
Angry 49.6%

AWS Rekognition

Age 20-38
Gender Female, 50%
Calm 49.5%
Confused 49.5%
Happy 49.5%
Sad 50.2%
Surprised 49.5%
Disgusted 49.6%
Angry 49.6%

AWS Rekognition

Age 20-38
Gender Female, 50.4%
Sad 49.8%
Happy 49.6%
Calm 50.1%
Disgusted 49.5%
Angry 49.5%
Surprised 49.5%
Confused 49.5%

AWS Rekognition

Age 15-25
Gender Male, 50.1%
Happy 49.5%
Disgusted 49.5%
Surprised 49.5%
Angry 49.5%
Calm 49.5%
Sad 50.4%
Confused 49.5%

AWS Rekognition

Age 19-36
Gender Female, 50.3%
Surprised 49.5%
Angry 49.6%
Calm 49.7%
Confused 49.5%
Disgusted 49.6%
Happy 49.6%
Sad 50%

AWS Rekognition

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

AWS Rekognition

Age 23-38
Gender Male, 50.1%
Happy 49.5%
Calm 49.6%
Confused 49.6%
Disgusted 49.5%
Surprised 49.5%
Angry 49.5%
Sad 50.3%

AWS Rekognition

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

AWS Rekognition

Age 26-43
Gender Female, 50.2%
Confused 49.6%
Disgusted 49.8%
Sad 50%
Surprised 49.5%
Calm 49.5%
Happy 49.5%
Angry 49.6%

AWS Rekognition

Age 23-38
Gender Male, 50.3%
Disgusted 49.5%
Sad 50.2%
Calm 49.6%
Surprised 49.6%
Confused 49.6%
Angry 49.6%
Happy 49.5%

AWS Rekognition

Age 19-36
Gender Female, 50.5%
Happy 49.6%
Angry 49.6%
Confused 49.6%
Disgusted 49.6%
Sad 49.7%
Calm 49.8%
Surprised 49.6%

AWS Rekognition

Age 35-52
Gender Male, 50.3%
Disgusted 49.5%
Surprised 49.5%
Angry 49.6%
Happy 49.6%
Calm 49.9%
Sad 49.8%
Confused 49.6%

AWS Rekognition

Age 26-43
Gender Female, 50.3%
Sad 50.4%
Surprised 49.5%
Calm 49.5%
Happy 49.5%
Disgusted 49.5%
Confused 49.5%
Angry 49.5%

AWS Rekognition

Age 19-36
Gender Female, 50.4%
Happy 49.6%
Angry 49.6%
Calm 49.8%
Disgusted 49.6%
Sad 49.8%
Confused 49.5%
Surprised 49.6%

AWS Rekognition

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

AWS Rekognition

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

AWS Rekognition

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

AWS Rekognition

Age 17-27
Gender Female, 50.4%
Sad 50%
Disgusted 49.6%
Surprised 49.5%
Angry 49.6%
Happy 49.5%
Calm 49.7%
Confused 49.6%

AWS Rekognition

Age 14-25
Gender Male, 50.1%
Happy 49.5%
Calm 49.5%
Confused 49.5%
Disgusted 49.5%
Surprised 49.5%
Angry 49.5%
Sad 50.4%

AWS Rekognition

Age 35-52
Gender Female, 50.2%
Disgusted 49.6%
Happy 49.6%
Confused 49.5%
Sad 50%
Angry 49.6%
Surprised 49.5%
Calm 49.7%

AWS Rekognition

Age 26-43
Gender Female, 50.3%
Surprised 49.5%
Angry 49.6%
Calm 49.8%
Confused 49.5%
Disgusted 49.5%
Happy 49.5%
Sad 49.9%

AWS Rekognition

Age 19-36
Gender Female, 50.3%
Calm 49.7%
Happy 49.6%
Sad 49.6%
Surprised 49.6%
Disgusted 49.8%
Angry 49.6%
Confused 49.6%

Feature analysis

Amazon

Person 84.1%

Categories

Imagga

text visuals 85.3%
paintings art 9%
streetview architecture 2.2%

Captions

Microsoft
created on 2019-06-04

a group of people in a room 44.1%
a group of people posing for a photo 25.1%

Text analysis

Amazon

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Google

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