Machine Generated Data
Tags
Amazon
created on 2022-01-22
Clarifai
created on 2023-10-26
Imagga
created on 2022-01-22
mug shot | 100 | |
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photograph | 91 | |
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representation | 73.4 | |
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creation | 47.2 | |
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portrait | 31.7 | |
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people | 26.8 | |
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adult | 25.9 | |
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person | 24.6 | |
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attractive | 23.8 | |
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hair | 22.2 | |
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model | 20.2 | |
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pretty | 19.6 | |
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face | 19.2 | |
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fashion | 18.1 | |
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lady | 17.9 | |
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man | 17.5 | |
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sexy | 16.9 | |
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bow tie | 16.7 | |
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money | 16.2 | |
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currency | 15.3 | |
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black | 15.1 | |
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old | 14.6 | |
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wig | 14.2 | |
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male | 14.2 | |
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clothing | 14 | |
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business | 14 | |
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happy | 13.8 | |
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human | 13.5 | |
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one | 13.4 | |
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cute | 12.9 | |
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brunette | 12.2 | |
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looking | 12 | |
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expression | 11.9 | |
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necktie | 11.9 | |
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skin | 11.8 | |
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love | 11.8 | |
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dollar | 11.1 | |
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women | 11.1 | |
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bill | 10.5 | |
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body | 10.4 | |
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eyes | 10.3 | |
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smiling | 10.1 | |
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banking | 10.1 | |
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cash | 10.1 | |
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studio | 9.9 | |
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hairpiece | 9.8 | |
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style | 9.6 | |
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elegant | 9.4 | |
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alone | 9.1 | |
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sensual | 9.1 | |
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sensuality | 9.1 | |
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posing | 8.9 | |
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couple | 8.7 | |
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exchange | 8.6 | |
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smile | 8.6 | |
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senior | 8.4 | |
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makeup | 8.2 | |
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lifestyle | 8 | |
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mother | 7.8 | |
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modern | 7.7 | |
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grandma | 7.7 | |
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finance | 7.6 | |
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erotic | 7.6 | |
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world | 7.6 | |
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feminine | 7.5 | |
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vintage | 7.4 | |
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mature | 7.4 | |
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close | 7.4 | |
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cheerful | 7.3 | |
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attire | 7.3 | |
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gorgeous | 7.3 | |
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success | 7.2 | |
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office | 7.2 | |
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gray | 7.2 | |
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wealth | 7.2 | |
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bank | 7.2 | |
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happiness | 7.1 | |
|
Google
created on 2022-01-22
Forehead | 98.5 | |
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Jaw | 87.9 | |
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Coat | 87.8 | |
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Art | 84.5 | |
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Facial hair | 75.8 | |
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Vintage clothing | 73.5 | |
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Painting | 71.9 | |
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Self-portrait | 71 | |
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Blazer | 70.9 | |
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Monochrome | 70.1 | |
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Illustration | 69.3 | |
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Visual arts | 69.1 | |
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Drawing | 68.7 | |
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Monochrome photography | 63 | |
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Moustache | 62.6 | |
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Room | 62 | |
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Paper | 61.4 | |
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History | 60.5 | |
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Portrait | 59.6 | |
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Paper product | 59.5 | |
|
Color Analysis
Face analysis
Amazon
Microsoft
![](https://ids.lib.harvard.edu/ids/iiif/18821158/288,267,116,155/full/0/native.jpg)
AWS Rekognition
Age | 47-53 |
Gender | Male, 98.8% |
Calm | 99.6% |
Sad | 0.1% |
Surprised | 0.1% |
Angry | 0.1% |
Happy | 0% |
Confused | 0% |
Disgusted | 0% |
Fear | 0% |
![](https://ids.lib.harvard.edu/ids/iiif/18821158/277,300,121,121/full/0/native.jpg)
Microsoft Cognitive Services
Age | 48 |
Gender | Male |
![](https://ids.lib.harvard.edu/ids/iiif/18821158/259,239,172,199/full/0/native.jpg)
Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very unlikely |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18821158/123,202,457,545/full/0/native.jpg)
Person | 95.5% | |
|
Categories
Imagga
paintings art | 54.5% | |
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people portraits | 37.4% | |
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pets animals | 4.3% | |
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food drinks | 1.3% | |
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text visuals | 1.1% | |
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Captions
Microsoft
created on 2022-01-22
Alois Senefelder taking a selfie | 67.5% | |
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a close up of Alois Senefelder | 67.4% | |
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Alois Senefelder posing for a picture | 67.3% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18821158/249,812,69,15/full/0/native.jpg)
ALOIS
![](https://ids.lib.harvard.edu/ids/iiif/18821158/328,834,17,13/full/0/native.jpg)
der
![](https://ids.lib.harvard.edu/ids/iiif/18821158/518,808,42,21/full/0/native.jpg)
Negler
![](https://ids.lib.harvard.edu/ids/iiif/18821158/259,910,66,31/full/0/native.jpg)
Inventor
![](https://ids.lib.harvard.edu/ids/iiif/18821158/249,808,311,21/full/0/native.jpg)
ALOIS SENEFELDER nation Negler
![](https://ids.lib.harvard.edu/ids/iiif/18821158/197,758,26,13/full/0/native.jpg)
1834
![](https://ids.lib.harvard.edu/ids/iiif/18821158/328,812,136,15/full/0/native.jpg)
SENEFELDER
![](https://ids.lib.harvard.edu/ids/iiif/18821158/473,810,43,17/full/0/native.jpg)
nation
![](https://ids.lib.harvard.edu/ids/iiif/18821158/278,826,156,34/full/0/native.jpg)
Erfender der Pethographiel.
![](https://ids.lib.harvard.edu/ids/iiif/18821158/329,914,14,27/full/0/native.jpg)
of
![](https://ids.lib.harvard.edu/ids/iiif/18821158/278,830,48,26/full/0/native.jpg)
Erfender
![](https://ids.lib.harvard.edu/ids/iiif/18821158/196,869,9,6/full/0/native.jpg)
..
![](https://ids.lib.harvard.edu/ids/iiif/18821158/259,899,179,59/full/0/native.jpg)
Inventor of fittery replay
![](https://ids.lib.harvard.edu/ids/iiif/18821158/286,853,14,9/full/0/native.jpg)
in
![](https://ids.lib.harvard.edu/ids/iiif/18821158/272,851,73,13/full/0/native.jpg)
gut in 6.November
![](https://ids.lib.harvard.edu/ids/iiif/18821158/231,869,10,7/full/0/native.jpg)
and
![](https://ids.lib.harvard.edu/ids/iiif/18821158/300,851,45,11/full/0/native.jpg)
6.November
![](https://ids.lib.harvard.edu/ids/iiif/18821158/272,851,15,13/full/0/native.jpg)
gut
![](https://ids.lib.harvard.edu/ids/iiif/18821158/347,829,88,28/full/0/native.jpg)
Pethographiel.
![](https://ids.lib.harvard.edu/ids/iiif/18821158/242,734,18,34/full/0/native.jpg)
&
![](https://ids.lib.harvard.edu/ids/iiif/18821158/244,870,13,5/full/0/native.jpg)
than
![](https://ids.lib.harvard.edu/ids/iiif/18821158/180,869,13,6/full/0/native.jpg)
THE
![](https://ids.lib.harvard.edu/ids/iiif/18821158/343,869,20,7/full/0/native.jpg)
I
![](https://ids.lib.harvard.edu/ids/iiif/18821158/330,871,12,6/full/0/native.jpg)
sum
![](https://ids.lib.harvard.edu/ids/iiif/18821158/398,870,9,6/full/0/native.jpg)
to
![](https://ids.lib.harvard.edu/ids/iiif/18821158/180,869,340,9/full/0/native.jpg)
THE .. Nature and than . DE Love sum I der to Zetalm Insurance et ft Hutsing
![](https://ids.lib.harvard.edu/ids/iiif/18821158/480,870,7,7/full/0/native.jpg)
ft
![](https://ids.lib.harvard.edu/ids/iiif/18821158/348,905,44,35/full/0/native.jpg)
fittery
![](https://ids.lib.harvard.edu/ids/iiif/18821158/291,872,4,4/full/0/native.jpg)
.
![](https://ids.lib.harvard.edu/ids/iiif/18821158/297,870,10,6/full/0/native.jpg)
DE
![](https://ids.lib.harvard.edu/ids/iiif/18821158/209,869,17,7/full/0/native.jpg)
Nature
![](https://ids.lib.harvard.edu/ids/iiif/18821158/307,869,20,8/full/0/native.jpg)
Love
![](https://ids.lib.harvard.edu/ids/iiif/18821158/438,870,27,7/full/0/native.jpg)
Insurance
![](https://ids.lib.harvard.edu/ids/iiif/18821158/391,904,47,44/full/0/native.jpg)
replay
![](https://ids.lib.harvard.edu/ids/iiif/18821158/489,871,31,7/full/0/native.jpg)
Hutsing
![](https://ids.lib.harvard.edu/ids/iiif/18821158/410,869,25,7/full/0/native.jpg)
Zetalm
![](https://ids.lib.harvard.edu/ids/iiif/18821158/467,871,10,6/full/0/native.jpg)
et
![](https://ids.lib.harvard.edu/ids/iiif/18821158/251,725,312,137/full/0/native.jpg)
Go y let
ALOIS SENEFELDER not on Negler
Efndeor dee Lithegaphadl
![](https://ids.lib.harvard.edu/ids/iiif/18821158/463,725,12,10/full/0/native.jpg)
Go
![](https://ids.lib.harvard.edu/ids/iiif/18821158/486,727,13,8/full/0/native.jpg)
y
![](https://ids.lib.harvard.edu/ids/iiif/18821158/496,727,20,8/full/0/native.jpg)
let
![](https://ids.lib.harvard.edu/ids/iiif/18821158/251,814,72,17/full/0/native.jpg)
ALOIS
![](https://ids.lib.harvard.edu/ids/iiif/18821158/330,814,138,17/full/0/native.jpg)
SENEFELDER
![](https://ids.lib.harvard.edu/ids/iiif/18821158/477,814,24,15/full/0/native.jpg)
not
![](https://ids.lib.harvard.edu/ids/iiif/18821158/504,820,12,7/full/0/native.jpg)
on
![](https://ids.lib.harvard.edu/ids/iiif/18821158/520,810,43,23/full/0/native.jpg)
Negler
![](https://ids.lib.harvard.edu/ids/iiif/18821158/281,832,50,29/full/0/native.jpg)
Efndeor
![](https://ids.lib.harvard.edu/ids/iiif/18821158/331,835,23,26/full/0/native.jpg)
dee
![](https://ids.lib.harvard.edu/ids/iiif/18821158/353,831,81,31/full/0/native.jpg)
Lithegaphadl