Human Generated Data

Title

Education, Industrial: United States. New York. New York City. Public Schools, Adaptation to Special City Needs: New York City Public Schools. Examples of the Adaptation of Education to Special City Needs: Class from Wadleigh High School, Manhattan.: Aquarium, Manhattan.
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, 3.2002.1473.2

Human Generated Data

Title

Education, Industrial: United States. New York. New York City. Public Schools, Adaptation to Special City Needs: New York City Public Schools. Examples of the Adaptation of Education to Special City Needs: Class from Wadleigh High School, Manhattan.: Aquarium, Manhattan.

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, 3.2002.1473.2

Machine Generated Data

Tags

Amazon
created on 2019-06-04

Person 98.9
Human 98.9
Person 98.6
Room 98.2
Indoors 98.2
Person 98
Person 97.7
Classroom 97.3
School 97.3
Person 97
Person 82
Person 81.3
Person 81
Person 80
Person 79.5
Person 79.4
Court 74.2
Shoe 68.1
Apparel 68.1
Clothing 68.1
Footwear 68.1
Lab 57.5

Clarifai
created on 2019-06-04

people 100
many 99.6
group 99.5
administration 99.2
leader 99.2
group together 98.7
adult 98.1
furniture 96.6
room 94
man 92.9
military 91.4
several 91.4
chair 90.6
wear 90.4
woman 88.7
education 88.3
home 86.5
war 85.3
outfit 84.1
sit 83.1

Imagga
created on 2019-06-04

room 100
classroom 90.3
interior 75.2
chair 45.1
table 43.7
house 43.5
furniture 43.1
kitchen 42.4
home 42.3
decor 33.6
dining 32.3
modern 32.2
floor 29.8
design 28.1
wood 27.5
inside 26.7
indoor 26.5
center 23.6
stove 22.9
contemporary 22.6
hall 22.5
style 21.5
restaurant 21.5
luxury 21.4
decoration 20.3
indoors 20.2
glass 19.4
cook 19.2
apartment 19.2
cabinet 19.1
counter 18.4
architecture 18
oven 16.7
window 16.5
lamp 16.2
food 15.7
seat 15.1
light 14.7
chairs 14.7
comfortable 14.3
wooden 14.1
empty 13.7
sink 13.7
residential 13.4
refrigerator 12.8
domestic 12.7
dinner 12.6
nobody 12.4
wall 12.4
cafeteria 12.1
stool 12
plant 11.9
tile 11.9
cabinets 11.9
drawer 11.9
faucet 11.8
steel 11.5
expensive 11.5
cooking 11.4
elegance 10.9
clean 10.9
stylish 10.9
3d 10.8
luxurious 10.7
residence 10.7
decorate 10.5
estate 10.4
classic 10.2
drink 10
appliances 9.9
tables 9.8
stainless 9.7
elegant 9.4
space 9.3
eat 9.2
island 9.2
office 8.9
dining room 8.9
render 8.6
appliance 8.6
microwave 8
lifestyle 7.9
structure 7.9
granite 7.8
lighting 7.7
hotel 7.6
living 7.6
hospital 7.4
new 7.3
metal 7.2
shelf 7.1
life 7

Google
created on 2019-06-04

Photograph 95.4
Snapshot 83.3
Furniture 78.6
Room 76.5
Vintage clothing 63.3
History 57.6

Microsoft
created on 2019-06-04

table 98.8
furniture 98.6
floor 95.8
wall 95.7
old 95.5
indoor 89.4
person 83.4
black 82.8
clothing 79.8
group 73.8
white 71.9
desk 67.7
chair 64.9
vintage 29.7
several 13.4

Color Analysis

Face analysis

Amazon

AWS Rekognition

Age 26-43
Gender Male, 51.5%
Confused 45.2%
Calm 48.6%
Disgusted 45.2%
Happy 45.1%
Angry 45.5%
Sad 50.3%
Surprised 45.1%

AWS Rekognition

Age 35-52
Gender Female, 50.8%
Angry 45.5%
Sad 51.9%
Happy 45.2%
Confused 45.2%
Calm 46.6%
Disgusted 45.3%
Surprised 45.3%

AWS Rekognition

Age 26-43
Gender Female, 50.1%
Calm 51.4%
Disgusted 45.5%
Angry 46%
Sad 46.1%
Happy 45.1%
Confused 45.5%
Surprised 45.3%

AWS Rekognition

Age 26-43
Gender Male, 54.4%
Confused 45.1%
Sad 45.3%
Angry 45.4%
Disgusted 45.5%
Calm 53.2%
Surprised 45.2%
Happy 45.3%

AWS Rekognition

Age 26-43
Gender Female, 50.7%
Disgusted 45.3%
Happy 45.1%
Confused 45.3%
Sad 51.6%
Angry 45.4%
Surprised 45.2%
Calm 47.2%

AWS Rekognition

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

AWS Rekognition

Age 30-47
Gender Male, 50.3%
Disgusted 49.6%
Happy 49.7%
Sad 49.8%
Calm 49.9%
Angry 49.5%
Confused 49.5%
Surprised 49.5%

AWS Rekognition

Age 35-52
Gender Female, 50.3%
Angry 49.6%
Sad 49.7%
Surprised 49.5%
Confused 49.5%
Disgusted 49.6%
Happy 49.5%
Calm 50.1%

AWS Rekognition

Age 16-27
Gender Female, 50.1%
Angry 49.5%
Sad 49.6%
Disgusted 49.5%
Calm 50.2%
Happy 49.5%
Surprised 49.5%
Confused 49.6%

AWS Rekognition

Age 35-53
Gender Female, 50.1%
Confused 49.5%
Calm 49.5%
Disgusted 49.5%
Happy 49.6%
Angry 49.5%
Sad 50.2%
Surprised 49.5%

AWS Rekognition

Age 26-43
Gender Female, 50.1%
Sad 49.6%
Surprised 49.6%
Calm 49.6%
Happy 50%
Disgusted 49.6%
Confused 49.5%
Angry 49.5%

AWS Rekognition

Age 26-43
Gender Female, 54.8%
Happy 45.6%
Confused 46%
Surprised 45.4%
Angry 45.7%
Calm 48.4%
Sad 48.6%
Disgusted 45.3%

Feature analysis

Amazon

Person 98.9%
Shoe 68.1%

Categories

Imagga

interior objects 100%

Text analysis

Amazon

58
MAN.
AaUaRiUM MAN.
AaUaRiUM

Google

C 58 AaUARIUM MAN.
C
58
AaUARIUM
MAN.