Machine Generated Data
Tags
Amazon
created on 2022-01-08
Clarifai
created on 2023-10-25
people | 99.8 | |
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monochrome | 98.9 | |
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group | 95.1 | |
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man | 94.7 | |
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adult | 94.4 | |
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illustration | 91.7 | |
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group together | 90.6 | |
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vehicle | 89.4 | |
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music | 85.6 | |
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war | 84.8 | |
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one | 84.2 | |
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many | 79.8 | |
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two | 79.2 | |
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street | 78.9 | |
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transportation system | 78.8 | |
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three | 77.9 | |
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several | 77.8 | |
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woman | 77.5 | |
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child | 75.4 | |
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vintage | 73.9 | |
|
Imagga
created on 2022-01-08
china cabinet | 40.1 | |
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shop | 33.6 | |
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cabinet | 31.9 | |
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furniture | 30.7 | |
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barbershop | 26.2 | |
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architecture | 24.3 | |
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mercantile establishment | 23.7 | |
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window | 22.5 | |
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building | 22.2 | |
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furnishing | 19.2 | |
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city | 18.3 | |
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old | 16.7 | |
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place of business | 15.8 | |
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metal | 13.7 | |
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industry | 12.8 | |
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house | 12.5 | |
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vintage | 11.6 | |
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case | 11.5 | |
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retro | 11.5 | |
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travel | 11.3 | |
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light | 10.7 | |
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room | 10.5 | |
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urban | 10.5 | |
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street | 10.1 | |
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historic | 10.1 | |
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steel | 9.7 | |
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business | 9.7 | |
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detail | 9.6 | |
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factory | 9.6 | |
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design | 9.6 | |
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ancient | 9.5 | |
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town | 9.3 | |
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equipment | 9.2 | |
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modern | 9.1 | |
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economy | 8.3 | |
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exterior | 8.3 | |
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inside | 8.3 | |
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tourism | 8.2 | |
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industrial | 8.2 | |
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technology | 8.2 | |
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religion | 8.1 | |
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history | 8 | |
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interior | 8 | |
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establishment | 7.9 | |
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art | 7.8 | |
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decoration | 7.4 | |
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bank | 7.3 | |
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machine | 7.3 | |
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antique | 7.2 | |
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landmark | 7.2 | |
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currency | 7.2 | |
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sky | 7 | |
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Google
created on 2022-01-08
Tire | 95 | |
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Wheel | 92.9 | |
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Automotive tire | 90.3 | |
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Vehicle | 88.7 | |
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Motor vehicle | 84.2 | |
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Hat | 82.9 | |
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Fedora | 77.5 | |
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Snapshot | 74.3 | |
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Tread | 72.4 | |
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Monochrome photography | 72.4 | |
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Automotive wheel system | 71.8 | |
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Monochrome | 70.9 | |
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Font | 69.4 | |
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Classic | 68 | |
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Auto part | 64.5 | |
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Stock photography | 63.1 | |
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Machine | 61.7 | |
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Metal | 61.1 | |
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Art | 60.1 | |
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Classic car | 60 | |
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Microsoft
created on 2022-01-08
text | 99.7 | |
| ||
person | 78.4 | |
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black and white | 73.9 | |
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clothing | 68.6 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18786557/427,370,12,16/full/0/native.jpg)
AWS Rekognition
Age | 23-33 |
Gender | Female, 80.4% |
Angry | 35.3% |
Fear | 27.5% |
Sad | 22.8% |
Disgusted | 4.7% |
Calm | 3.1% |
Happy | 2.3% |
Confused | 2.3% |
Surprised | 2% |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18786557/540,257,85,321/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18786557/335,252,113,249/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18786557/484,227,71,126/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18786557/606,363,61,169/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/18786557/598,426,66,199/full/0/native.jpg)
Person | 99.7% | |
|
Categories
Imagga
streetview architecture | 68.6% | |
| ||
paintings art | 30.1% | |
|
Captions
Microsoft
created on 2022-01-08
a group of people in a store | 29.8% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18786557/778,661,26,125/full/0/native.jpg)
32386
![](https://ids.lib.harvard.edu/ids/iiif/18786557/257,870,145,53/full/0/native.jpg)
UMBRELLAS
![](https://ids.lib.harvard.edu/ids/iiif/18786557/290,813,74,34/full/0/native.jpg)
RENT
![](https://ids.lib.harvard.edu/ids/iiif/18786557/527,389,40,23/full/0/native.jpg)
KIST
![](https://ids.lib.harvard.edu/ids/iiif/18786557/526,470,17,8/full/0/native.jpg)
ATHER
![](https://ids.lib.harvard.edu/ids/iiif/18786557/252,823,175,65/full/0/native.jpg)
TUBES-CHAIRS
![](https://ids.lib.harvard.edu/ids/iiif/18786557/493,465,69,21/full/0/native.jpg)
GRANGE and ATHER FLEVO
![](https://ids.lib.harvard.edu/ids/iiif/18786557/493,475,19,8/full/0/native.jpg)
GRANGE
![](https://ids.lib.harvard.edu/ids/iiif/18786557/513,473,11,7/full/0/native.jpg)
and
![](https://ids.lib.harvard.edu/ids/iiif/18786557/545,468,17,7/full/0/native.jpg)
FLEVO
![](https://ids.lib.harvard.edu/ids/iiif/18786557/291,16,173,20/full/0/native.jpg)
УТЕРА2-ЖАСО»
![](https://ids.lib.harvard.edu/ids/iiif/18786557/209,19,30,11/full/0/native.jpg)
aa
![](https://ids.lib.harvard.edu/ids/iiif/18786557/253,17,554,912/full/0/native.jpg)
KODVK-e
KIST
-RENT
TUBES CHAIRS
UMBRELLAS
32386
![](https://ids.lib.harvard.edu/ids/iiif/18786557/358,18,105,22/full/0/native.jpg)
KODVK-e
![](https://ids.lib.harvard.edu/ids/iiif/18786557/524,391,51,26/full/0/native.jpg)
KIST
![](https://ids.lib.harvard.edu/ids/iiif/18786557/286,814,85,37/full/0/native.jpg)
-RENT
![](https://ids.lib.harvard.edu/ids/iiif/18786557/257,838,91,51/full/0/native.jpg)
TUBES
![](https://ids.lib.harvard.edu/ids/iiif/18786557/341,829,89,51/full/0/native.jpg)
CHAIRS
![](https://ids.lib.harvard.edu/ids/iiif/18786557/253,875,168,54/full/0/native.jpg)
UMBRELLAS
![](https://ids.lib.harvard.edu/ids/iiif/18786557/778,661,29,128/full/0/native.jpg)
32386