Machine Generated Data
Tags
Amazon
created on 2021-04-03
Clarifai
created on 2021-04-03
Imagga
created on 2021-04-03
book jacket | 100 | |
| ||
jacket | 82.3 | |
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wrapping | 61 | |
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covering | 41.1 | |
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vintage | 30.6 | |
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old | 27.9 | |
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stamp | 26.1 | |
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23.9 | ||
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letter | 22.9 | |
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postmark | 22.7 | |
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retro | 22.1 | |
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postage | 20.6 | |
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paper | 20.4 | |
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postal | 19.6 | |
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art | 18.5 | |
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envelope | 18.4 | |
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drawing | 17.9 | |
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grunge | 17 | |
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sketch | 16.9 | |
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ancient | 16.4 | |
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antique | 16.3 | |
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philately | 15.8 | |
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money | 15.3 | |
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symbol | 14.8 | |
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printed | 14.8 | |
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post | 13.3 | |
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aged | 12.7 | |
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currency | 12.6 | |
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history | 12.5 | |
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man | 12.1 | |
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representation | 12.1 | |
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global | 11.8 | |
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circa | 11.8 | |
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shows | 11.8 | |
| ||
creation | 11.7 | |
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card | 11.2 | |
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banking | 11 | |
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stamps | 10.8 | |
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closeup | 10.8 | |
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business | 10.3 | |
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dollar | 10.2 | |
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design | 10.1 | |
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cash | 10.1 | |
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close | 9.7 | |
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unique | 9.5 | |
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sculpture | 9.4 | |
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culture | 9.4 | |
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product | 9.3 | |
| ||
message | 9.1 | |
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bank | 9.1 | |
| ||
one | 9 | |
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detail | 8.8 | |
| ||
exchange | 8.6 | |
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face | 8.5 | |
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book | 8.4 | |
| ||
finance | 8.4 | |
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black | 8.4 | |
| ||
texture | 8.3 | |
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paint | 8.1 | |
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religion | 8.1 | |
| ||
icon | 7.9 | |
| ||
philatelic | 7.9 | |
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states | 7.7 | |
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cutting | 7.7 | |
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dollars | 7.7 | |
| ||
us | 7.7 | |
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communications | 7.7 | |
| ||
historic | 7.3 | |
| ||
office | 7.2 | |
| ||
dirty | 7.2 | |
| ||
comic book | 7.2 | |
| ||
portrait | 7.1 | |
|
Google
created on 2021-04-03
Sleeve | 87.2 | |
| ||
Collar | 78.8 | |
| ||
Art | 78.6 | |
| ||
Font | 73.9 | |
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Overcoat | 73.4 | |
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Vintage clothing | 69.4 | |
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Painting | 68.2 | |
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Drawing | 65.2 | |
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Illustration | 64.5 | |
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Paper product | 63.9 | |
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Visual arts | 63.2 | |
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Paper | 63 | |
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Pattern | 62.9 | |
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History | 62.4 | |
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Costume design | 60.3 | |
| ||
Printmaking | 59.7 | |
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Duster | 58.4 | |
| ||
Book | 56.6 | |
| ||
Frock coat | 55.4 | |
| ||
Vintage advertisement | 54.5 | |
|
Color Analysis
Face analysis
Amazon
AWS Rekognition
Age | 46-64 |
Gender | Male, 91.3% |
Calm | 84.7% |
Angry | 11.5% |
Disgusted | 2.4% |
Sad | 0.5% |
Surprised | 0.5% |
Happy | 0.2% |
Fear | 0.1% |
Confused | 0.1% |
AWS Rekognition
Age | 21-33 |
Gender | Male, 95.9% |
Calm | 49.6% |
Happy | 26% |
Sad | 12% |
Angry | 4.6% |
Disgusted | 4.6% |
Surprised | 1.9% |
Fear | 1.1% |
Confused | 0.3% |
Feature analysis
Amazon
Person | 99.4% | |
|
Text analysis
Amazon
Mais
rendre
portez
comment
devoirs!
mes
A
votre ?
Merci et la votre ?
A yous rendre mes devoirs! couvrez-yous!
Merci
la
et
vous
portez-vous ?
BIRE
bien?....
Eb! comment yous portez-vous ?
couvrez-yous!
et.....
D'EN
corme
Mais corme vous vavez : et..... vous VOUS bien?....
Eb!
yous
OOUSTOORE D'EN BIRE B3EJ3
vavez :
B3EJ3
OOUSTOORE
VOUS
--
BIRE
!
?
A
vous
mes
devoirs!
couvrez-vous
comme
13 --
« 01STOIRE D'EN BIRE DEUX
Eh ! comment vous portez-vous ?
Merci ! et la votre ?
A vous rendre mes devoirs! couvrez-vous !
- Mais comme vous voyez ; et... .. vous vous portez bien ?....
13
«
01STOIRE
D'EN
DEUX
Eh
comment
portez-vous
Merci
et
la
votre
rendre
-
Mais
voyez
;
et...
..
portez
bien
?....