Machine Generated Data
Tags
Amazon
created on 2021-12-14
Clarifai
created on 2023-10-22
Imagga
created on 2021-12-14
aviator | 34.9 | |
| ||
person | 24.5 | |
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people | 20.1 | |
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adult | 18.1 | |
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man | 18.1 | |
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male | 17 | |
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dark | 15 | |
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car | 14.3 | |
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black | 14 | |
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fashion | 12.8 | |
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lifestyle | 12.3 | |
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sky | 12.1 | |
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sexy | 12 | |
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sitting | 12 | |
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travel | 12 | |
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one | 11.9 | |
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business | 11.5 | |
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vehicle | 11 | |
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model | 10.9 | |
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businessman | 10.6 | |
| ||
pretty | 10.5 | |
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outdoors | 10.4 | |
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dress | 9.9 | |
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silhouette | 9.9 | |
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attractive | 9.8 | |
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lady | 9.7 | |
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hair | 9.5 | |
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water | 9.3 | |
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device | 9 | |
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sunset | 9 | |
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transportation | 9 | |
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looking | 8.8 | |
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body | 8.8 | |
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corporate | 8.6 | |
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elegant | 8.6 | |
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face | 8.5 | |
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sport | 8.4 | |
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holding | 8.3 | |
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human | 8.2 | |
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movie | 8.2 | |
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transport | 8.2 | |
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sun | 8.2 | |
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smile | 7.8 | |
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rifle | 7.7 | |
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professional | 7.7 | |
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seat | 7.6 | |
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suit | 7.6 | |
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elegance | 7.6 | |
| ||
happy | 7.5 | |
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light | 7.5 | |
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landscape | 7.4 | |
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occupation | 7.3 | |
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clothing | 7.3 | |
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gun | 7.2 | |
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support | 7.1 | |
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portrait | 7.1 | |
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happiness | 7 | |
|
Google
created on 2021-12-14
Hood | 88.6 | |
| ||
Organism | 86.4 | |
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Gesture | 85.3 | |
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Black-and-white | 82.8 | |
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Font | 82.4 | |
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Adaptation | 79.4 | |
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Motor vehicle | 75.5 | |
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Snapshot | 74.3 | |
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Flash photography | 73 | |
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Automotive design | 71.5 | |
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Monochrome photography | 70.2 | |
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Automotive tire | 69.8 | |
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Vehicle door | 67.9 | |
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Photo caption | 66.8 | |
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Stock photography | 65.4 | |
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Monochrome | 63.1 | |
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Rectangle | 62.7 | |
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Auto part | 58.9 | |
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Brand | 57.6 | |
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Bumper | 57.4 | |
|
Color Analysis
Feature analysis
Categories
Imagga
pets animals | 34.1% | |
| ||
cars vehicles | 29.4% | |
| ||
paintings art | 24.3% | |
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food drinks | 8.5% | |
| ||
people portraits | 1.1% | |
|
Captions
Microsoft
created on 2021-12-14
a hand holding a photo of a person | 42.9% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/44118842/584,588,37,27/full/0/native.jpg)
CLASS
![](https://ids.lib.harvard.edu/ids/iiif/44118842/624,610,33,26/full/0/native.jpg)
AND
![](https://ids.lib.harvard.edu/ids/iiif/44118842/530,591,28,22/full/0/native.jpg)
2160
![](https://ids.lib.harvard.edu/ids/iiif/44118842/534,560,18,15/full/0/native.jpg)
ML
![](https://ids.lib.harvard.edu/ids/iiif/44118842/542,580,63,45/full/0/native.jpg)
INDUSTRIES
![](https://ids.lib.harvard.edu/ids/iiif/44118842/514,585,50,28/full/0/native.jpg)
FE 2160
![](https://ids.lib.harvard.edu/ids/iiif/44118842/514,560,172,83/full/0/native.jpg)
ML 2 UPO CLASS 7 AND 7
![](https://ids.lib.harvard.edu/ids/iiif/44118842/511,572,132,67/full/0/native.jpg)
LAD INDUSTRIES INC.
![](https://ids.lib.harvard.edu/ids/iiif/44118842/600,614,30,24/full/0/native.jpg)
INC.
![](https://ids.lib.harvard.edu/ids/iiif/44118842/510,594,33,20/full/0/native.jpg)
MART
![](https://ids.lib.harvard.edu/ids/iiif/44118842/621,609,7,8/full/0/native.jpg)
7
![](https://ids.lib.harvard.edu/ids/iiif/44118842/520,585,16,14/full/0/native.jpg)
FE
![](https://ids.lib.harvard.edu/ids/iiif/44118842/526,572,21,18/full/0/native.jpg)
LAD
![](https://ids.lib.harvard.edu/ids/iiif/44118842/401,528,12,7/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/44118842/553,572,8,8/full/0/native.jpg)
2
![](https://ids.lib.harvard.edu/ids/iiif/44118842/408,520,5,4/full/0/native.jpg)
P
![](https://ids.lib.harvard.edu/ids/iiif/44118842/558,572,30,24/full/0/native.jpg)
UPO
![](https://ids.lib.harvard.edu/ids/iiif/44118842/504,605,30,19/full/0/native.jpg)
LIE
![](https://ids.lib.harvard.edu/ids/iiif/44118842/409,521,19,12/full/0/native.jpg)
THE
![](https://ids.lib.harvard.edu/ids/iiif/44118842/468,525,27,16/full/0/native.jpg)
HAND
![](https://ids.lib.harvard.edu/ids/iiif/44118842/448,515,25,14/full/0/native.jpg)
and
![](https://ids.lib.harvard.edu/ids/iiif/44118842/521,560,153,91/full/0/native.jpg)
MEDG CLASS1 AND 2
M NOLURES NC.
RTM
![](https://ids.lib.harvard.edu/ids/iiif/44118842/538,560,61,46/full/0/native.jpg)
MEDG
![](https://ids.lib.harvard.edu/ids/iiif/44118842/589,590,56,44/full/0/native.jpg)
CLASS1
![](https://ids.lib.harvard.edu/ids/iiif/44118842/634,616,30,29/full/0/native.jpg)
AND
![](https://ids.lib.harvard.edu/ids/iiif/44118842/653,627,21,23/full/0/native.jpg)
2
![](https://ids.lib.harvard.edu/ids/iiif/44118842/535,579,15,13/full/0/native.jpg)
M
![](https://ids.lib.harvard.edu/ids/iiif/44118842/550,585,62,48/full/0/native.jpg)
NOLURES
![](https://ids.lib.harvard.edu/ids/iiif/44118842/601,615,40,34/full/0/native.jpg)
NC.
![](https://ids.lib.harvard.edu/ids/iiif/44118842/521,586,40,31/full/0/native.jpg)
RTM