Machine Generated Data
Tags
Amazon
created on 2023-10-23
Water | 100 | |
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Waterfront | 100 | |
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Sailboat | 100 | |
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Transportation | 100 | |
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Vehicle | 100 | |
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Watercraft | 99.2 | |
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Boat | 97.7 | |
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Outdoors | 97.7 | |
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Pier | 94 | |
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Canal | 90.7 | |
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Nature | 88.2 | |
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Person | 84.4 | |
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Path | 80.4 | |
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Sea | 73.3 | |
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Person | 71 | |
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Barge | 56.9 | |
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Sidewalk | 56.6 | |
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Fishing | 56.4 | |
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Leisure Activities | 56.4 | |
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Yacht | 56.2 | |
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Dinghy | 55.8 | |
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Towpath | 55.1 | |
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Beach | 55.1 | |
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Coast | 55.1 | |
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Shoreline | 55.1 | |
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Harbor | 55 | |
|
Clarifai
created on 2023-10-14
no person | 97.9 | |
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water | 96.9 | |
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monochrome | 96.6 | |
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boat | 94.6 | |
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people | 94.4 | |
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street | 94.3 | |
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rain | 92.8 | |
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transportation system | 90.5 | |
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retro | 90 | |
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watercraft | 89 | |
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vehicle | 87.2 | |
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winter | 87 | |
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ship | 86.8 | |
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reflection | 86.8 | |
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river | 85.6 | |
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one | 84.4 | |
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old | 84.1 | |
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travel | 83.4 | |
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art | 83.2 | |
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city | 83 | |
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Imagga
created on 2019-02-03
Google
created on 2019-02-03
Black-and-white | 80.7 | |
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Photography | 73.8 | |
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Stock photography | 65.4 | |
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Monochrome photography | 57.8 | |
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Vehicle | 56.3 | |
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Boat | 54.9 | |
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Watercraft | 50.5 | |
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Still life photography | 50.2 | |
|
Microsoft
created on 2019-02-03
black and white | 17.7 | |
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monochrome | 7 | |
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boat | 5.8 | |
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street | 5.7 | |
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water | 3.8 | |
|
Color Analysis
Feature analysis
Categories
Imagga
food drinks | 72.2% | |
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interior objects | 24.3% | |
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paintings art | 2.5% | |
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Captions
Microsoft
created on 2019-02-03
a boat sitting on top of a table | 25.1% | |
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a boat sitting on top of a counter | 25% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/16022281/128,426,29,24/full/0/native.jpg)
NO
![](https://ids.lib.harvard.edu/ids/iiif/16022281/128,398,140,52/full/0/native.jpg)
NO TRESPASSING
![](https://ids.lib.harvard.edu/ids/iiif/16022281/133,466,60,28/full/0/native.jpg)
DEFACING
![](https://ids.lib.harvard.edu/ids/iiif/16022281/158,398,109,45/full/0/native.jpg)
TRESPASSING
![](https://ids.lib.harvard.edu/ids/iiif/16022281/231,429,30,17/full/0/native.jpg)
MASS
![](https://ids.lib.harvard.edu/ids/iiif/16022281/215,439,13,9/full/0/native.jpg)
OF
![](https://ids.lib.harvard.edu/ids/iiif/16022281/234,446,13,6/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/16022281/132,422,129,49/full/0/native.jpg)
COMMONWEALTH - OF - MASS
![](https://ids.lib.harvard.edu/ids/iiif/16022281/204,448,59,27/full/0/native.jpg)
REMOVING
![](https://ids.lib.harvard.edu/ids/iiif/16022281/134,439,82,32/full/0/native.jpg)
COMMONWEALTH
![](https://ids.lib.harvard.edu/ids/iiif/16022281/193,467,11,10/full/0/native.jpg)
of
![](https://ids.lib.harvard.edu/ids/iiif/16022281/130,438,135,63/full/0/native.jpg)
DEFACING - of 200 REMOVING 400 -
![](https://ids.lib.harvard.edu/ids/iiif/16022281/150,478,50,19/full/0/native.jpg)
- -
![](https://ids.lib.harvard.edu/ids/iiif/16022281/170,453,36,17/full/0/native.jpg)
PENALTY
![](https://ids.lib.harvard.edu/ids/iiif/16022281/211,448,19,11/full/0/native.jpg)
400
![](https://ids.lib.harvard.edu/ids/iiif/16022281/201,475,12,8/full/0/native.jpg)
200
![](https://ids.lib.harvard.edu/ids/iiif/16022281/212,464,38,16/full/0/native.jpg)
adidas
![](https://ids.lib.harvard.edu/ids/iiif/16022281/130,422,59,33/full/0/native.jpg)
NO TR
![](https://ids.lib.harvard.edu/ids/iiif/16022281/130,428,33,27/full/0/native.jpg)
NO
![](https://ids.lib.harvard.edu/ids/iiif/16022281/160,422,29,24/full/0/native.jpg)
TR