Machine Generated Data
Tags
Amazon
created on 2022-05-27
Person | 99.1 | |
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Human | 99.1 | |
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Person | 97.9 | |
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Water | 97.4 | |
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Person | 96.8 | |
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Person | 96 | |
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Waterfront | 94.5 | |
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Nature | 93.8 | |
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Person | 92.6 | |
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Outdoors | 90.6 | |
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Person | 90.1 | |
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Person | 89.5 | |
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Pier | 86.9 | |
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Dock | 86.9 | |
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Port | 86.9 | |
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Person | 82 | |
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Person | 78.7 | |
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Person | 78.4 | |
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Person | 77.3 | |
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Person | 68.5 | |
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Harbor | 65.5 | |
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Building | 61.9 | |
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Cruiser | 61.7 | |
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Navy | 61.7 | |
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Transportation | 61.7 | |
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Vehicle | 61.7 | |
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Ship | 61.7 | |
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Military | 61.7 | |
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Person | 61.7 | |
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Landscape | 59 | |
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Panoramic | 57.7 | |
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Scenery | 57.7 | |
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Imagga
created on 2022-05-27
Google
created on 2022-05-27
Urban design | 78 | |
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Building | 70.8 | |
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Rectangle | 69.3 | |
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Vehicle | 66.3 | |
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Art | 65.9 | |
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History | 65.2 | |
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Stock photography | 63.9 | |
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Paper product | 62.5 | |
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Engineering | 58.9 | |
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Visual arts | 57.3 | |
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Room | 57.2 | |
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Font | 53.4 | |
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Mixed-use | 50.8 | |
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Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/17817281/639,582,8,14/full/0/native.jpg)
AWS Rekognition
Age | 25-35 |
Gender | Male, 95.9% |
Calm | 42% |
Sad | 24.8% |
Disgusted | 20.9% |
Surprised | 8.9% |
Angry | 7.6% |
Fear | 6.3% |
Happy | 3.1% |
Confused | 1.8% |
![](https://ids.lib.harvard.edu/ids/iiif/17817281/606,574,8,11/full/0/native.jpg)
AWS Rekognition
Age | 33-41 |
Gender | Male, 94.5% |
Calm | 98.5% |
Surprised | 6.3% |
Fear | 5.9% |
Sad | 2.4% |
Disgusted | 0.2% |
Happy | 0.2% |
Angry | 0.1% |
Confused | 0.1% |
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/17817281/622,576,43,107/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/594,571,35,95/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/398,479,27,87/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/465,623,64,141/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/83,459,57,160/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/376,493,19,58/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/430,395,22,56/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/642,427,30,87/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/366,576,40,108/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/326,508,36,56/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/10,322,43,161/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/81,341,36,60/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/17817281/365,471,26,78/full/0/native.jpg)
Person | 99.1% | |
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Categories
Imagga
paintings art | 90.3% | |
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streetview architecture | 5.2% | |
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nature landscape | 2.3% | |
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Captions
Microsoft
created on 2022-05-27
a vintage photo of a train yard | 77.3% | |
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a vintage photo of a train | 77.2% | |
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a vintage photo of a train yard in a city | 75.6% | |
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Text analysis
![](https://ids.lib.harvard.edu/ids/iiif/17817281/320,261,81,124/full/0/native.jpg)
LY!
![](https://ids.lib.harvard.edu/ids/iiif/17817281/320,281,80,105/full/0/native.jpg)
LY
![](https://ids.lib.harvard.edu/ids/iiif/17817281/322,262,79,47/full/0/native.jpg)
!