Human Generated Data

Title

Untitled (workers at American Express Company)

Date

1925

People

Artist: Hamblin Studio, American active 1930s

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.1908

Human Generated Data

Title

Untitled (workers at American Express Company)

People

Artist: Hamblin Studio, American active 1930s

Date

1925

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.1908

Machine Generated Data

Tags

Amazon
created on 2021-12-14

Person 96
Human 96
Person 95.6
Interior Design 93.7
Indoors 93.7
Person 91.4
Person 87.5
Person 80.2
Nature 74.9
Person 72
Room 65.8
Building 58.9
Restaurant 58.8
Shop 57.9
Outdoors 57.9
Cafe 56.8
Art 56
Cafeteria 55.7
Person 48.7

Clarifai
created on 2023-10-25

people 99.7
group 98.1
room 97.8
adult 97
war 95.6
monochrome 95
man 93.6
many 92.7
furniture 91.6
administration 90.9
vehicle 90.1
indoors 89.9
home 88.1
street 87.3
woman 87.1
no person 85.7
desk 84.4
chair 84.1
wear 84
school 82.8

Imagga
created on 2021-12-14

shop 75.6
barbershop 64.2
interior 61
mercantile establishment 59.3
room 46.9
house 45.1
furniture 42
home 39.1
place of business 39
table 38.4
chair 36.3
decor 36.2
modern 34.3
floor 31.6
window 30.1
design 29.3
building 28.6
restaurant 28.4
architecture 28.3
luxury 27.4
inside 25.8
indoor 25.6
lamp 24.8
wood 24.2
bakery 23.3
apartment 21.1
sofa 21
residential 20.1
light 20
structure 19.9
counter 19.7
decoration 18.8
wall 18.8
establishment 18.7
indoors 18.4
living 18
style 17.8
3d 17
estate 16.1
kitchen 15.8
cafeteria 15.6
carpet 14.6
comfortable 14.3
glass 14
empty 13.7
elegant 13.7
lighting 13.5
tile 13.3
contemporary 13.2
domestic 12.7
residence 12.6
nobody 12.4
door 12.4
real 12.3
chairs 11.7
space 11.6
decorate 11.4
urban 11.4
elegance 10.9
stylish 10.8
furnishings 10.8
city 10.8
couch 10.6
new 10.5
dining 10.5
oven 10.1
cabinet 10
sink 9.8
wooden 9.7
expensive 9.6
hotel 9.5
supermarket 9.5
clean 9.2
business 9.1
refrigerator 9.1
cabinets 8.9
upscale 8.9
rug 8.9
hardwood 8.8
seat 8.7
vase 8.7
windows 8.6
hall 8.6
mirror 8.6
construction 8.6
relax 8.4
place 8.4
fireplace 8.4
lights 8.3
plant 8.2
steel 8
drawer 7.9
stove 7.9
living room 7.8
render 7.8
old 7.7
dinner 7.6
lifestyles 7.6
fashion 7.5
relaxation 7.5
bar 7.4
warm 7.4
office 7.3
food 7.2
lifestyle 7.2
area 7.2
family 7.1

Google
created on 2021-12-14

Microsoft
created on 2021-12-14

text 99.8
furniture 87.2
white 75.9
table 67.4
drawing 66
chair 63.7
library 60.9
black and white 53.5
old 42.5

Color Analysis

Face analysis

Amazon

Google

AWS Rekognition

Age 29-45
Gender Male, 61.6%
Calm 66.4%
Happy 18.7%
Sad 3.4%
Confused 3.2%
Angry 3%
Surprised 2.6%
Disgusted 1.8%
Fear 0.9%

AWS Rekognition

Age 46-64
Gender Male, 79.4%
Calm 89.8%
Sad 7.3%
Happy 0.9%
Confused 0.7%
Angry 0.5%
Fear 0.4%
Surprised 0.3%
Disgusted 0.1%

AWS Rekognition

Age 32-48
Gender Male, 84.4%
Calm 55%
Happy 29%
Confused 8%
Sad 4.4%
Angry 1.2%
Disgusted 0.9%
Surprised 0.9%
Fear 0.6%

AWS Rekognition

Age 27-43
Gender Female, 63.6%
Sad 76.5%
Calm 11.1%
Fear 7.8%
Happy 1.8%
Angry 1.2%
Confused 0.9%
Disgusted 0.5%
Surprised 0.3%

AWS Rekognition

Age 37-55
Gender Male, 95.3%
Sad 75.9%
Calm 12.2%
Fear 7.7%
Angry 3%
Confused 0.6%
Happy 0.3%
Surprised 0.2%
Disgusted 0.2%

AWS Rekognition

Age 51-69
Gender Male, 97.3%
Calm 95%
Happy 1.3%
Angry 1.3%
Sad 1.2%
Confused 0.8%
Disgusted 0.2%
Surprised 0.2%
Fear 0.1%

AWS Rekognition

Age 52-70
Gender Male, 95.8%
Calm 83.2%
Sad 6.1%
Confused 3.5%
Happy 2.3%
Angry 1.7%
Disgusted 1.6%
Fear 1%
Surprised 0.5%

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Unlikely

Feature analysis

Amazon

Person 96%

Categories

Imagga

interior objects 100%

Captions

Text analysis

Amazon

DISTRICT
SAL
Swift
No.
ACL
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-
No
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THINK
DESTRICT
la
KEEP EGGS DET
UNE
NEEDS
No. la
COURTEOUS-ALWAYS
UNE PUILTER NEEDS FRESH II
DE COURTEOUS-ALWAYS
ft
DE
KHH
BEER - -
INSTRUCT
TLEST -
..
DET
EGGS
ح KHH HAHH
INSTRUCT .
the
HAHH
adidas the
STORE
PUILTER
.
ح
adidas
RESTRICT
- FBC CARTELLA
FBC
II
FINT
LAINS
FINT SUV
SUV
STERE
TLEST
NE
RECE
CARTELLA
BEER

Google

ACL SAL DISTICT DISTRICT DISTRICT BISTRIET DISTRICT No. No DISTRICT KEEP EEES E DISTRICT N PACE No. DISTRICT TECT No. DISTRICT BE COURTEDUS - ALWATS DISTRICT DISTRICT No. INE POR NEED FRH DISTRIET Swift
ACL
SAL
DISTICT
DISTRICT
BISTRIET
No.
No
KEEP
EEES
E
N
PACE
TECT
BE
COURTEDUS
-
ALWATS
INE
POR
NEED
FRH
DISTRIET
Swift