Human Generated Data

Title

Descent From the Cross
Date

16th-17th century
People

Artist: Aegidius Sadeler, Flemish 1570 - 1629

Artist after: Jacopo Tintoretto, Italian 1519 - 1594
Classification

Prints
Credit Line

Harvard Art Museums/Fogg Museum, Gift of Belinda L. Randall from the collection of John Witt Randall, R4966

Human Generated Data

Title

Descent From the Cross

People

Artist: Aegidius Sadeler, Flemish 1570 - 1629

Artist after: Jacopo Tintoretto, Italian 1519 - 1594

Date

16th-17th century

Classification

Prints

Machine Generated Data

Tags

Amazon
created on 2019-10-30

Person 98.4
Human 98.4
Art 96.4
Painting 96.4
Person 95.1
Person 84.1
Person 81.1
Person 52

Clarifai
created on 2019-10-30

illustration 99.8
art 99.6
people 99.6
print 99.1
painting 98.1
engraving 97.1
group 96.4
man 96.2
book 96
religion 94.5
adult 94.4
woodcut 92.5
book bindings 92
god 90.9
visuals 90.8
old 89.8
cross 89.6
antique 89.4
book series 87
woman 85

Imagga
created on 2019-10-30

sketch 100
drawing 100
representation 90.3
statue 55
sculpture 52.7
art 32.3
architecture 31.4
history 26.8
ancient 26.8
city 25
old 23
landmark 22.6
monument 22.4
famous 21.4
stone 21.2
building 19.8
tourism 19.8
marble 19.5
travel 19
religion 18.8
culture 18.8
historic 18.3
carving 17.1
god 15.3
detail 15.3
historical 15.1
fountain 13.9
symbol 12.8
bronze 12.7
figure 12.5
column 12.3
decoration 12.2
roman 11.8
tourist 11.8
king 11.7
religious 11.3
sky 10.8
angel 10.8
temple 10.7
palace 10.6
horse 10.4
comic book 10.3
golden 10.3
church 10.2
holy 9.6
artistic 9.6
exterior 9.2
artwork 9.2
antique 8.9
catholic 8.8
facade 8.7
saint 8.7
book jacket 8.6
spirituality 8.6
capital 8.5
design 8.4
destination 8.4
decorative 8.4
vintage 8.3
square 8.1
man 8.1
museum 7.8
outdoor 7.7
attraction 7.6
traditional 7.5
town 7.4
gold 7.4
holiday 7.2
face 7.1

Google
created on 2019-10-30

Painting 87.4
Art 81.6
Stock photography 65.4
Illustration 57.7
Visual arts 55

Microsoft
created on 2019-10-30

text 100
book 99.8
drawing 99
sketch 98
cartoon 93
painting 92.6
person 91.7
clothing 78.7
old 62.2
man 59

Face analysis

Amazon

AWS Rekognition

Age 44-62
Gender Male, 52.8%
Fear 48.9%
Happy 45.2%
Surprised 45.6%
Calm 45.6%
Confused 45.2%
Disgusted 45.3%
Sad 46.2%
Angry 48%

AWS Rekognition

Age 22-34
Gender Male, 65.2%
Happy 0.8%
Calm 13.7%
Angry 2.8%
Surprised 54.7%
Sad 1.9%
Confused 1.4%
Disgusted 0.8%
Fear 23.8%

AWS Rekognition

Age 33-49
Gender Male, 53.3%
Fear 45.1%
Sad 50.8%
Calm 48.4%
Confused 45.1%
Disgusted 45%
Happy 45.4%
Angry 45.1%
Surprised 45%

AWS Rekognition

Age 33-49
Gender Male, 53.6%
Happy 45.4%
Sad 47.2%
Angry 45.2%
Calm 51.3%
Confused 45.2%
Disgusted 45.5%
Fear 45.2%
Surprised 45.1%

Feature analysis

Amazon

Person 98.4%
Painting 96.4%

Captions

Microsoft

a vintage photo of a man 86.4%
a vintage photo of a group of people posing for the camera 76.4%
a vintage photo of a group of people posing for a picture 76.3%

Text analysis

Amazon

INRI
CAVSA
NOSTRI
MEDIO
MVNDI
CARENS
VNICA
PRINCIPIOG
Sic IACVIT NOSTRI CAVSA MENS VNICA MVNDI Er FINE, ET MEDIO PRINCIPIOG CARENS
IACVIT
FINE,
Sic
MENS
ET
Er

Google

INRI Tintoret ET FINE, ET MEDIO, PRINCIPIOO CARENS G F ferms. SIC LACVIT NOSTRI CAVSA MENS VNICA MVNDI r
INRI
Tintoret
ET
FINE,
MEDIO,
PRINCIPIOO
CARENS
G
F
ferms.
SIC
LACVIT
NOSTRI
CAVSA
MENS
VNICA
MVNDI
r