Human Generated Data

Title

The Miracle of Loaves and Fishes

Date

1500-1530s

People

Artist: Unidentified Artist,

Classification

Paintings

Credit Line

Harvard Art Museums/Fogg Museum, Gift of the Monastery of St. Mary and St. John, 1955.180.B

Human Generated Data

Title

The Miracle of Loaves and Fishes

People

Artist: Unidentified Artist,

Date

1500-1530s

Classification

Paintings

Credit Line

Harvard Art Museums/Fogg Museum, Gift of the Monastery of St. Mary and St. John, 1955.180.B

Machine Generated Data

Tags

Amazon
created on 2020-04-24

Human 99.5
Person 99.5
Person 99.4
Person 98.5
Art 97.3
Person 96.3
Person 93.4
Painting 90.9
Person 87
Person 73.6
Person 57.8
Person 43.3

Clarifai
created on 2020-04-24

people 100
group 99.9
print 99.5
adult 99.2
art 98.2
many 98
engraving 97.3
man 96.7
illustration 95
woman 93.7
leader 92.2
several 92.2
painting 92
administration 90.2
furniture 86.7
war 85.6
lithograph 84.5
facial hair 84.2
interaction 83.2
wear 82.7

Imagga
created on 2020-04-24

window 42.3
old 27.9
architecture 27.3
door 24.4
framework 21.5
building 21.2
ancient 20.8
vintage 19.8
historic 17.4
antique 17.3
wall 17.1
religion 17
house 16.7
supporting structure 15.5
bell 15.4
art 14.4
history 14.3
shop 14.3
detail 13.7
city 13.3
church 12.9
aged 12.7
acoustic device 12
grunge 11.9
dirty 11.7
call 11.6
entrance 11.6
religious 11.2
structure 11
decoration 10.9
mercantile establishment 10.6
architectural 10.6
texture 10.4
retro 9.8
sculpture 9.7
home 9.6
stone 9.4
tourism 9.1
signaling device 8.9
temple 8.9
wooden 8.8
brick 8.5
historical 8.5
travel 8.4
famous 8.4
wood 8.3
device 8.1
artistic 7.8
black 7.8
glass 7.8
statue 7.7
construction 7.7
saint 7.7
culture 7.7
windows 7.7
destination 7.5
people 7.3
landmark 7.2
icon 7.1
interior 7.1
place of business 7.1

Google
created on 2020-04-24

Microsoft
created on 2020-04-24

drawing 98.8
text 97.6
sketch 97.5
person 96.3
clothing 94.7
window 91.6
cartoon 82.4
man 78
human face 73.8
old 67.7
posing 47.1
painting 24.3

Color Analysis

Face analysis

Amazon

Microsoft

AWS Rekognition

Age 33-49
Gender Male, 94.4%
Confused 4%
Calm 8.9%
Sad 1.3%
Disgusted 0.3%
Happy 0.6%
Surprised 35%
Fear 18.3%
Angry 31.6%

AWS Rekognition

Age 23-35
Gender Female, 50%
Disgusted 45%
Angry 45%
Happy 45%
Sad 45%
Confused 45%
Calm 45%
Fear 54.6%
Surprised 45.3%

AWS Rekognition

Age 22-34
Gender Male, 54%
Disgusted 45.1%
Confused 45.2%
Fear 45.4%
Calm 46.7%
Happy 48%
Surprised 49.1%
Sad 45.3%
Angry 45.1%

AWS Rekognition

Age 43-61
Gender Male, 53.7%
Disgusted 45%
Happy 45.1%
Calm 46.1%
Fear 45.2%
Confused 49.2%
Sad 45.1%
Surprised 49.2%
Angry 45.1%

AWS Rekognition

Age 41-59
Gender Male, 54.5%
Angry 45.3%
Happy 45.4%
Calm 50.5%
Sad 48.4%
Disgusted 45%
Surprised 45.3%
Fear 45.1%
Confused 45.1%

AWS Rekognition

Age 32-48
Gender Male, 54.9%
Fear 45.1%
Disgusted 45%
Happy 45.6%
Calm 45.1%
Sad 45%
Surprised 53.3%
Angry 45.9%
Confused 45%

AWS Rekognition

Age 19-31
Gender Male, 54.6%
Fear 45%
Disgusted 45%
Angry 54.8%
Happy 45%
Surprised 45%
Calm 45.1%
Sad 45%
Confused 45%

AWS Rekognition

Age 23-37
Gender Female, 53.1%
Angry 45.1%
Fear 45.1%
Confused 45%
Sad 45.4%
Surprised 45%
Disgusted 45%
Happy 45.1%
Calm 54.3%

AWS Rekognition

Age 32-48
Gender Male, 50.4%
Angry 49.5%
Surprised 49.5%
Confused 49.5%
Disgusted 49.5%
Happy 49.5%
Calm 50.4%
Fear 49.5%
Sad 49.6%

AWS Rekognition

Age 21-33
Gender Female, 50.4%
Surprised 49.6%
Angry 49.5%
Disgusted 49.5%
Calm 49.8%
Happy 49.5%
Fear 49.6%
Confused 49.6%
Sad 50%

AWS Rekognition

Age 20-32
Gender Female, 50.5%
Confused 45.2%
Fear 45.2%
Calm 48.2%
Disgusted 45.1%
Surprised 45.5%
Happy 45.1%
Sad 48.8%
Angry 46.8%

AWS Rekognition

Age 5-15
Gender Female, 50.1%
Confused 49.5%
Calm 49.6%
Fear 49.7%
Angry 49.5%
Surprised 49.5%
Disgusted 49.6%
Happy 49.5%
Sad 50.1%

AWS Rekognition

Age 23-37
Gender Female, 50.2%
Angry 50.4%
Happy 49.5%
Calm 49.5%
Confused 49.5%
Fear 49.5%
Sad 49.5%
Surprised 49.5%
Disgusted 49.5%

AWS Rekognition

Age 9-19
Gender Male, 50.5%
Disgusted 49.5%
Confused 49.5%
Happy 49.5%
Surprised 49.5%
Angry 49.5%
Fear 49.5%
Sad 50.4%
Calm 49.5%

AWS Rekognition

Age 50-68
Gender Male, 54.4%
Fear 45%
Disgusted 45%
Sad 45.2%
Confused 45%
Calm 53.8%
Happy 45.1%
Surprised 45.7%
Angry 45.1%

Microsoft Cognitive Services

Age 57
Gender Male

Feature analysis

Amazon

Person 99.5%
Painting 90.9%

Categories