Human Generated Data

Title

Carrying of the Cross

Date

16th-17th century

People

Artist: Johann Sadeler I, Netherlandish 1550 - 1600-8

Artist after: Maerten de Vos, Netherlandish 1532 - 1603

Classification

Prints

Credit Line

Harvard Art Museums/Fogg Museum, Gift of Belinda L. Randall from the collection of John Witt Randall, R4902

Human Generated Data

Title

Carrying of the Cross

People

Artist: Johann Sadeler I, Netherlandish 1550 - 1600-8

Artist after: Maerten de Vos, Netherlandish 1532 - 1603

Date

16th-17th century

Classification

Prints

Machine Generated Data

Tags

Amazon
created on 2019-11-10

Human 98.8
Person 98.8
Art 98.7
Painting 98.3
Person 97.4
Person 96.5
Person 95.5
Person 78.6
Person 65.1
Archaeology 58.2

Clarifai
created on 2019-11-10

people 100
print 99.8
art 99.8
illustration 99.8
group 99.3
engraving 99.2
man 98.1
adult 97.9
woodcut 97.3
many 96
sword 95.9
soldier 94.9
military 93.7
kneeling 93.6
painting 93.3
weapon 93.2
administration 92.6
war 91.7
force 90.5
leader 90.1

Imagga
created on 2019-11-10

sketch 67.7
drawing 48.9
sculpture 41.6
representation 39.9
art 37.3
statue 33.9
comic book 33
architecture 23.5
religion 23.3
ancient 22.5
monument 22.4
history 22.4
old 21.6
stone 19.9
decoration 19.6
religious 18.7
landmark 17.2
figure 17.1
temple 16.6
church 15.7
carving 14.9
tourism 14.9
culture 14.5
holy 14.5
god 14.4
travel 14.1
famous 14
city 13.3
print media 13.2
detail 12.9
historic 12.8
spiritual 12.5
memorial 12.3
graffito 12.2
artistic 12.2
saint 11.5
faith 11.5
historical 11.3
spirituality 10.6
building 10.3
cemetery 10
tourist 10
newspaper 9.9
antique 9.9
marble 9.7
gold 9
book jacket 9
carved 8.8
angel 8.8
design 8.8
symbol 8.8
catholic 8.8
wall 8.6
artwork 8.2
style 8.2
structure 8.1
close 8
cathedral 7.8
belief 7.8
golden 7.7
palace 7.7
product 7.6
fountain 7.5
vintage 7.4
cash 7.3
creation 7.3
black 7.2
jacket 7

Google
created on 2019-11-10

Microsoft
created on 2019-11-10

text 100
book 99.8
person 97.1
old 94.5
drawing 93.7
clothing 91.9
sketch 91.1
man 90.4
posing 85.2
cartoon 80.4
group 69.5
engraving 61.4
illustration 56.9
vintage 55.8

Face analysis

Amazon

Microsoft

AWS Rekognition

Age 26-40
Gender Male, 54.1%
Calm 47.1%
Surprised 45.3%
Disgusted 45.1%
Happy 46.2%
Angry 50.3%
Confused 45.1%
Sad 45.7%
Fear 45.3%

AWS Rekognition

Age 26-40
Gender Male, 52.8%
Happy 45%
Sad 45%
Disgusted 45%
Calm 55%
Surprised 45%
Angry 45%
Confused 45%
Fear 45%

AWS Rekognition

Age 38-56
Gender Male, 54.8%
Sad 45%
Fear 45%
Happy 45.9%
Disgusted 45%
Confused 45%
Calm 54%
Angry 45.1%
Surprised 45%

AWS Rekognition

Age 50-68
Gender Male, 54.4%
Happy 45%
Confused 45%
Surprised 45%
Sad 45%
Calm 54.9%
Fear 45%
Angry 45%
Disgusted 45%

AWS Rekognition

Age 28-44
Gender Female, 51.5%
Calm 45.1%
Disgusted 45.9%
Fear 45.6%
Confused 45%
Surprised 45.9%
Happy 45%
Sad 45%
Angry 52.4%

AWS Rekognition

Age 23-35
Gender Male, 50.2%
Disgusted 49.5%
Sad 49.5%
Angry 50.2%
Calm 49.6%
Fear 49.5%
Surprised 49.5%
Happy 49.5%
Confused 49.5%

AWS Rekognition

Age 51-69
Gender Male, 54.8%
Surprised 45%
Happy 45%
Angry 45%
Disgusted 45%
Calm 55%
Confused 45%
Fear 45%
Sad 45%

AWS Rekognition

Age 5-15
Gender Male, 50.3%
Angry 50%
Disgusted 49.5%
Sad 49.7%
Surprised 49.5%
Confused 49.5%
Happy 49.5%
Calm 49.7%
Fear 49.5%

AWS Rekognition

Age 58-76
Gender Male, 52.7%
Disgusted 45.1%
Happy 45.7%
Calm 53.4%
Fear 45.1%
Angry 45.4%
Sad 45.4%
Confused 45%
Surprised 45%

AWS Rekognition

Age 25-39
Gender Female, 50.2%
Sad 50.2%
Disgusted 49.5%
Fear 49.6%
Happy 49.5%
Confused 49.5%
Angry 49.6%
Surprised 49.5%
Calm 49.5%

AWS Rekognition

Age 16-28
Gender Female, 50.3%
Angry 50.3%
Confused 49.5%
Calm 49.5%
Happy 49.5%
Surprised 49.5%
Disgusted 49.6%
Sad 49.5%
Fear 49.5%

AWS Rekognition

Age 17-29
Gender Female, 50.4%
Fear 49.5%
Disgusted 50.3%
Confused 49.5%
Sad 49.5%
Calm 49.7%
Happy 49.5%
Surprised 49.5%
Angry 49.5%

AWS Rekognition

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

AWS Rekognition

Age 23-35
Gender Female, 50.1%
Confused 49.5%
Sad 49.6%
Fear 49.9%
Surprised 49.5%
Disgusted 49.5%
Calm 49.6%
Angry 49.6%
Happy 49.7%

Microsoft Cognitive Services

Age 30
Gender Female

Feature analysis

Amazon

Person 98.8%
Painting 98.3%

Captions

Microsoft

a vintage photo of a group of people posing for the camera 90.9%
a vintage photo of a group of people posing for a picture 90.8%
a vintage photo of a group of people posing for a photo 89.4%

Text analysis

Amazon

MATTH.
baiulantem
hominem
abduxerunt,
portaret
hune
autem
inuenerunt
fuam
yrenaum,
acceperunt
nomine
Et
Et acceperunt Iefum, et abduxerunt, baiulantem crucem fuam Ereuntes autem inuenerunt hominem
1582
eus
Sadler
crucem
et
Simonem :
yrenaum, nomine Simonem : hune adegorunt vt portaret crucem eus MATTH. xxVi
Iefum,
Ereuntes
vt
adegorunt
I. Sadler feaf:
I.
xxVi
inuentors
nt xrcud: 1582 vas inuentors
vas
feaf:
nt xrcud:

Google

I.
fealy
er
vor
imuentors
MATTH
eus.
crucem
I. Sadler fealy er xrud. 1582 A de vor imuentors hominem crucem fuam. (Exeuntes portaret абдахегиnс, баiulantem аutem тиепerunt Et acrperunt Ifam, et Func adegerunt vt Simonem MATTH XXVII Сyrenӕuт, потіnе eus. crucem
1582
de
Et
acrperunt
Сyrenӕuт,
fuam.
portaret
абдахегиnс,
et
Func
xrud.
(Exeuntes
adegerunt
vt
Sadler
A
hominem
баiulantem
аutem
тиепerunt
Ifam,
Simonem
XXVII
потіnе