Human Generated Data

Title

Races, Immigration: United States. New York. New York City. Immigrant Station: Regulation of Immigration at the Port of Entry. United States Immigrant Station, New York City: A dining room for detained and excluded women.
Date

c. 1903
People

Artist: J. H. Adams, American active 1900s
Classification

Photographs
Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.2393.1

Human Generated Data

Title

Races, Immigration: United States. New York. New York City. Immigrant Station: Regulation of Immigration at the Port of Entry. United States Immigrant Station, New York City: A dining room for detained and excluded women.

People

Artist: J. H. Adams, American active 1900s

Date

c. 1903

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.2393.1

Machine Generated Data

Tags

Amazon
created on 2019-06-04

Person 99.5
Human 99.5
Person 98.6
Person 98.5
Person 96.7
Person 96.1
Person 95.5
Furniture 90.2
Table 85.9
Room 85
Indoors 85
Person 79.6
Restaurant 78.8
Person 78.3
Person 77.1
Sitting 71.2
Person 66.7
Person 66.2
People 62.8
Food 61.7
Meal 61.7
Dining Table 59.5
Classroom 59.2
School 59.2
Cafeteria 58.8
Apparel 56.4
Clothing 56.4
Person 55
Person 54.2
Person 44

Clarifai
created on 2019-06-04

people 99.9
group 98.5
adult 97.1
many 96.5
group together 94.2
woman 91.5
man 91.5
administration 91.2
leader 87.3
several 86.5
child 81.5
furniture 80.8
wear 79.7
sit 78.8
war 77.9
military 72.8
room 72
education 70.2
five 68.6
outfit 64.9

Imagga
created on 2019-06-04

furniture 100
table 95.4
room 79.4
interior 75.3
dining table 67.9
house 46
chair 43.8
home 43.1
decor 38.9
furnishing 34
lamp 32.7
luxury 29.2
wood 28.4
floor 27.9
dining 27.6
design 27.6
inside 26.7
living 26.6
modern 26
bedroom 25.1
sofa 24.9
window 23.8
chairs 23.5
style 23
hotel 22.9
indoor 22.8
residential 21.1
restaurant 20.5
apartment 19.2
comfortable 19.1
light 18.7
seat 18.7
wooden 18.5
decoration 18.1
empty 18.1
indoors 17.6
glass 15.9
architecture 15.6
dinner 15.4
kitchen 15.3
decorate 15.2
relax 15.2
bed 15.2
wall 15.1
relaxation 14.3
pillow 13.8
vase 13.6
rest 13.4
contemporary 13.2
cabinet 13
food 12.9
living room 12.7
plant 12.7
couch 12.6
comfort 12.5
tables 11.8
fireplace 11.8
panel 11.8
drink 11.7
sleep 11.7
nobody 11.7
elegant 11.1
upscale 10.9
stylish 10.9
rug 10.9
cozy 10.8
residence 10.7
carpet 10.7
elegance 10.1
eat 10.1
stove 9.8
luxurious 9.7
door 9.5
hall 9.5
banquet 9.4
stool 9.2
counter 9.1
domestic 9.1
dining room 8.9
drawer 8.9
accommodation 8.9
flowers 8.7
setting 8.7
day 8.6
tile 8.6
space 8.5
flower 8.5
place 8.4
classic 8.4
classroom 8.2
coffee table 7.9
cabinets 7.9
ceiling 7.9
3d 7.8
designer 7.7
party 7.7
expensive 7.7
structure 7.6
service 7.4
cook 7.3
lifestyle 7.2
cushion 7.1

Google
created on 2019-06-04

Table 82.6
Room 76.5
Furniture 66
Meal 61.5
Dining room 58.7
Supper 53.9
Restaurant 50.1

Microsoft
created on 2019-06-04

table 98.4
clothing 97.1
indoor 93.4
person 92
old 78.1
woman 70.5
man 67.6
dining table 19.6
restaurant 17.1
dining room 8.2

Color Analysis

Face analysis

Amazon

Microsoft

Google

AWS Rekognition

Age 45-63
Gender Male, 50.8%
Calm 45.6%
Sad 54%
Angry 45.2%
Disgusted 45%
Confused 45.1%
Happy 45%
Surprised 45.1%

AWS Rekognition

Age 26-43
Gender Male, 53.6%
Disgusted 45.8%
Calm 48.4%
Happy 45.3%
Angry 48.4%
Sad 45.6%
Confused 46.2%
Surprised 45.3%

AWS Rekognition

Age 26-43
Gender Female, 86.3%
Calm 38.6%
Disgusted 5.9%
Surprised 4.8%
Sad 23.8%
Happy 5.4%
Angry 7.1%
Confused 14.5%

AWS Rekognition

Age 26-43
Gender Female, 51.9%
Calm 46.8%
Confused 45.2%
Sad 51.9%
Angry 45.3%
Happy 45.4%
Disgusted 45.1%
Surprised 45.3%

AWS Rekognition

Age 35-52
Gender Female, 54%
Sad 48.4%
Confused 45.2%
Disgusted 45.5%
Happy 49.9%
Angry 45.7%
Calm 45.1%
Surprised 45.2%

AWS Rekognition

Age 57-77
Gender Female, 55%
Angry 45.2%
Disgusted 51.6%
Confused 45.2%
Calm 45.8%
Happy 45.6%
Surprised 45.1%
Sad 46.4%

AWS Rekognition

Age 29-45
Gender Female, 54.6%
Happy 45.5%
Surprised 45.2%
Calm 49.6%
Confused 45.1%
Disgusted 45.2%
Angry 45.3%
Sad 49.1%

AWS Rekognition

Age 35-52
Gender Female, 69.6%
Confused 3.5%
Angry 16.4%
Calm 11.2%
Disgusted 29.2%
Sad 29.3%
Happy 7.8%
Surprised 2.7%

AWS Rekognition

Age 35-52
Gender Female, 50.1%
Disgusted 49.8%
Calm 49.6%
Surprised 49.6%
Sad 49.7%
Confused 49.5%
Angry 49.8%
Happy 49.5%

AWS Rekognition

Age 20-38
Gender Male, 50.7%
Angry 45.4%
Happy 45.2%
Disgusted 48.4%
Confused 45.6%
Surprised 45.5%
Sad 45.6%
Calm 49.3%

AWS Rekognition

Age 45-66
Gender Female, 54.6%
Surprised 45.7%
Angry 45.4%
Calm 45.2%
Confused 45.2%
Disgusted 45.2%
Happy 45.6%
Sad 52.6%

AWS Rekognition

Age 4-7
Gender Female, 50.7%
Angry 47.5%
Disgusted 45.2%
Confused 45.5%
Calm 46.5%
Happy 45.2%
Surprised 45.2%
Sad 49.9%

AWS Rekognition

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

AWS Rekognition

Age 17-27
Gender Male, 50.1%
Confused 49.6%
Angry 49.7%
Calm 49.7%
Disgusted 49.6%
Sad 49.8%
Happy 49.6%
Surprised 49.6%

AWS Rekognition

Age 23-38
Gender Female, 50.4%
Sad 49.9%
Disgusted 49.8%
Surprised 49.5%
Angry 49.6%
Happy 49.5%
Calm 49.6%
Confused 49.6%

AWS Rekognition

Age 10-15
Gender Male, 50.3%
Surprised 49.6%
Confused 49.5%
Sad 49.7%
Disgusted 49.5%
Calm 49.6%
Angry 49.6%
Happy 49.8%

AWS Rekognition

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

AWS Rekognition

Age 26-43
Gender Female, 53%
Angry 45.5%
Sad 50.3%
Disgusted 45.7%
Happy 45.2%
Calm 47.3%
Confused 45.5%
Surprised 45.4%

AWS Rekognition

Age 11-18
Gender Female, 50.2%
Happy 49.5%
Surprised 49.5%
Angry 49.5%
Sad 49.6%
Confused 49.6%
Calm 50.2%
Disgusted 49.5%

AWS Rekognition

Age 23-38
Gender Female, 50.5%
Angry 49.6%
Calm 49.5%
Sad 50.1%
Confused 49.5%
Disgusted 49.6%
Happy 49.6%
Surprised 49.5%

Microsoft Cognitive Services

Age 37
Gender Female

Microsoft Cognitive Services

Age 35
Gender Female

Microsoft Cognitive Services

Age 33
Gender Female

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 Unlikely
Blurred Very unlikely

Feature analysis

Amazon

Person 99.5%
Dining Table 59.5%

Categories

Imagga

interior objects 98.8%