Human Generated Data

Title

Christ Condemned to Death

Date

17th century

People

Artist: Jacques Callot, French 1592 - 1635

Classification

Prints

Human Generated Data

Title

Christ Condemned to Death

People

Artist: Jacques Callot, French 1592 - 1635

Date

17th century

Classification

Prints

Machine Generated Data

Tags

Amazon

Painting 95.3
Art 95.3
Person 94.9
Human 94.9
Person 94.6
Person 90.5
Person 87.8
Person 85.5
Person 83.3
Person 82.9
Person 70.8
Person 66.4
Person 64.5
Text 61.9
Architecture 61.3
Building 61.3
Person 55.6
Person 52.6
Person 51.6

Clarifai

people 100
many 100
group 99.9
print 99.9
engraving 99.2
adult 99.1
cavalry 98.9
art 98.7
illustration 98.6
crowd 98.2
man 98.2
administration 97.7
military 97.4
leader 97
soldier 97
weapon 92
skirmish 91.6
war 88.7
slavery 88.5
victory 88.5

Imagga

sketch 100
drawing 90
representation 63.7
treasury 32
depository 25.1
architecture 24.2
old 23
history 22.4
vintage 22.3
building 20
art 19.8
grunge 19.6
facility 19.3
ancient 19
landmark 19
travel 17.6
city 16.6
antique 15.7
snow 15.5
paper 14.1
tourism 14
famous 14
retro 13.9
structure 13.7
historical 13.2
design 12.9
statue 12.1
winter 11.9
landscape 11.9
texture 11.8
house 11.8
sky 11.5
scene 11.2
money 11.1
sculpture 10.9
stone 10.6
us 10.6
construction 10.3
pattern 10.3
culture 10.3
black 10.2
street 10.1
frame 10
currency 9.9
urban 9.6
symbol 9.4
finance 9.3
river 9.2
historic 9.2
dirty 9
style 8.9
cold 8.6
decoration 8.5
temple 8.5
tree 8.5
monument 8.4
dollar 8.4
decorative 8.4
bank 8.1
water 8
memorial 8
column 8
business 7.9
forest 7.8
season 7.8
capital 7.6
exterior 7.4
letter 7.3
cash 7.3
tourist 7.2
paint 7.2
border 7.2
religion 7.2
tower 7.2
marble 7.1

Google

Microsoft

text 100
book 99.7

Face analysis

Amazon

Microsoft

AWS Rekognition

Age 4-9
Gender Female, 50%
Sad 49.5%
Disgusted 50.3%
Calm 49.6%
Angry 49.5%
Surprised 49.5%
Happy 49.5%
Confused 49.5%

AWS Rekognition

Age 4-9
Gender Female, 50%
Calm 49.5%
Angry 49.5%
Disgusted 49.5%
Sad 50.3%
Confused 49.5%
Surprised 49.6%
Happy 49.5%

AWS Rekognition

Age 20-38
Gender Male, 50.5%
Angry 49.7%
Surprised 49.6%
Confused 49.6%
Sad 49.7%
Calm 49.8%
Disgusted 49.6%
Happy 49.6%

AWS Rekognition

Age 20-38
Gender Male, 50.4%
Confused 49.5%
Angry 49.5%
Calm 49.8%
Sad 49.7%
Disgusted 49.5%
Happy 49.9%
Surprised 49.6%

AWS Rekognition

Age 35-52
Gender Male, 50.2%
Surprised 49.5%
Calm 50.4%
Disgusted 49.5%
Sad 49.5%
Happy 49.5%
Angry 49.5%
Confused 49.5%

AWS Rekognition

Age 20-38
Gender Female, 50.3%
Surprised 49.6%
Calm 49.8%
Sad 49.6%
Disgusted 49.7%
Angry 49.7%
Happy 49.5%
Confused 49.6%

AWS Rekognition

Age 26-43
Gender Female, 50.1%
Confused 49.5%
Sad 50%
Surprised 49.5%
Happy 49.5%
Disgusted 49.5%
Calm 49.9%
Angry 49.5%

AWS Rekognition

Age 12-22
Gender Female, 50.1%
Happy 49.5%
Sad 50%
Surprised 49.5%
Calm 49.9%
Disgusted 49.5%
Confused 49.5%
Angry 49.5%

AWS Rekognition

Age 26-44
Gender Female, 50.2%
Confused 49.6%
Sad 50.1%
Surprised 49.5%
Disgusted 49.6%
Happy 49.6%
Calm 49.5%
Angry 49.7%

AWS Rekognition

Age 14-23
Gender Male, 50.4%
Surprised 49.6%
Confused 49.6%
Disgusted 49.5%
Calm 49.9%
Sad 49.8%
Happy 49.5%
Angry 49.6%

AWS Rekognition

Age 14-23
Gender Male, 50%
Confused 49.5%
Sad 49.5%
Surprised 49.5%
Happy 49.5%
Disgusted 49.5%
Angry 49.5%
Calm 50.5%

AWS Rekognition

Age 35-52
Gender Female, 50%
Confused 49.5%
Happy 50.3%
Calm 49.5%
Sad 49.6%
Angry 49.5%
Disgusted 49.5%
Surprised 49.5%

AWS Rekognition

Age 35-52
Gender Male, 50.5%
Confused 49.5%
Happy 49.5%
Disgusted 49.5%
Angry 49.6%
Calm 50%
Sad 49.8%
Surprised 49.5%

AWS Rekognition

Age 23-38
Gender Male, 54.9%
Confused 45.4%
Sad 51.9%
Surprised 45.3%
Disgusted 45.1%
Calm 46.3%
Angry 45.8%
Happy 45.3%

AWS Rekognition

Age 49-69
Gender Female, 53.6%
Disgusted 48.1%
Confused 45.9%
Sad 46.9%
Happy 46.3%
Surprised 45.9%
Angry 45.9%
Calm 46%

AWS Rekognition

Age 23-38
Gender Male, 50.4%
Happy 49.5%
Angry 49.5%
Surprised 49.5%
Sad 50.4%
Disgusted 49.5%
Calm 49.5%
Confused 49.5%

Microsoft Cognitive Services

Age 19
Gender Male

Microsoft Cognitive Services

Age 34
Gender Male

Feature analysis

Amazon

Painting 95.3%
Person 94.9%

Captions

Microsoft

an old photo of a book 57.1%
an old photo of a person 57%
a close up of a book 49.6%

Text analysis

Amazon

Non
Nulla
ille
lauat
lympha
manus,
foedat,
Non lauat ille manus, sed Christi sanguine foedat,
Nulla potrest tantum lympha lauare Scelus
Scelus
potrest
sed
tantum
Christi
lauare
Callor
sanguine
Callor fre:
fre:

Google

manus
foedat
potest
tantum
lympha
lauat
Nulla
1%
Caller
ille
Christi
sanouine
Scelus
Non
1% Caller Non lauat ille manus sed Christi sanouine foedat Nulla potest tantum lympha lauare Scelus
sed
lauare