Machine Generated Data
Tags
Amazon
created on 2019-03-26
Clarifai
created on 2019-03-26
Imagga
created on 2019-03-26
structure | 58.8 | |
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billboard | 56.9 | |
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barn | 52.2 | |
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signboard | 46.4 | |
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farm building | 40.5 | |
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building | 37.2 | |
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sky | 31.4 | |
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landscape | 27.6 | |
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trailer truck | 24 | |
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clouds | 22 | |
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sunset | 20.7 | |
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travel | 20.5 | |
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water | 20.1 | |
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architecture | 18.8 | |
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truck | 18.8 | |
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city | 18.3 | |
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coast | 15.3 | |
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trees | 15.1 | |
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shipping | 15.1 | |
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scenic | 14.9 | |
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motor vehicle | 14.4 | |
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river | 14.3 | |
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sea | 14.1 | |
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sunrise | 14.1 | |
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tourism | 14.1 | |
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summer | 13.5 | |
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lake | 12.8 | |
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scenery | 12.6 | |
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environment | 12.4 | |
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tree | 12.3 | |
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urban | 12.3 | |
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scene | 12.1 | |
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sun | 12.1 | |
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field | 11.7 | |
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horizon | 11.7 | |
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outdoor | 11.5 | |
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vacation | 11.5 | |
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dusk | 11.5 | |
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cloud | 11.2 | |
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old | 11.2 | |
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grass | 11.1 | |
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landmark | 10.9 | |
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ocean | 10.8 | |
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light | 10.7 | |
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mountain | 10.7 | |
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ship | 10.6 | |
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buildings | 10.4 | |
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boat | 10.3 | |
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beach | 10.1 | |
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countryside | 10.1 | |
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dark | 10 | |
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outdoors | 9.7 | |
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country | 9.7 | |
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storm | 9.6 | |
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downtown | 9.6 | |
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skyline | 9.5 | |
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black | 9 | |
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tower | 9 | |
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farm | 8.9 | |
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rural | 8.8 | |
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fog | 8.7 | |
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stage | 8.5 | |
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coastline | 8.5 | |
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weather | 8.4 | |
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land | 8.3 | |
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park | 8.2 | |
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reflection | 8.1 | |
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night | 8 | |
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forest | 7.8 | |
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twilight | 7.8 | |
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culture | 7.7 | |
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famous | 7.5 | |
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mountains | 7.4 | |
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island | 7.3 | |
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morning | 7.2 | |
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history | 7.2 | |
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spring | 7.1 | |
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season | 7 | |
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Google
created on 2019-03-26
Photograph | 95.6 | |
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Photography | 72.5 | |
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Black-and-white | 68.3 | |
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House | 68.3 | |
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Room | 65.7 | |
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Stock photography | 64 | |
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Home | 63.7 | |
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Building | 57 | |
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Photographic paper | 55.7 | |
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History | 54.1 | |
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Color Analysis
Feature analysis
Categories
Imagga
text visuals | 97.4% | |
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beaches seaside | 1% | |
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Captions
Microsoft
created on 2019-03-26
a black and white photo of a person | 69.9% | |
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a black sign with white text | 69.8% | |
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a black and white photo | 69.7% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18833090/251,467,73,20/full/0/native.jpg)
SHORE
![](https://ids.lib.harvard.edu/ids/iiif/18833090/328,467,82,21/full/0/native.jpg)
MOTEL
![](https://ids.lib.harvard.edu/ids/iiif/18833090/191,467,55,23/full/0/native.jpg)
LAKE
![](https://ids.lib.harvard.edu/ids/iiif/18833090/610,467,72,21/full/0/native.jpg)
SOUTH
![](https://ids.lib.harvard.edu/ids/iiif/18833090/190,467,583,24/full/0/native.jpg)
LAKE SHORE MOTEL CHAMBERLAIN, SOUTH DAKOTA
![](https://ids.lib.harvard.edu/ids/iiif/18833090/444,467,160,24/full/0/native.jpg)
CHAMBERLAIN,
![](https://ids.lib.harvard.edu/ids/iiif/18833090/686,467,88,21/full/0/native.jpg)
DAKOTA
![](https://ids.lib.harvard.edu/ids/iiif/18833090/494,303,60,27/full/0/native.jpg)
I
![](https://ids.lib.harvard.edu/ids/iiif/18833090/1011,204,0,0/full/0/native.jpg)
aes
![](https://ids.lib.harvard.edu/ids/iiif/18833090/426,300,237,30/full/0/native.jpg)
t I II
![](https://ids.lib.harvard.edu/ids/iiif/18833090/418,249,37,15/full/0/native.jpg)
La
![](https://ids.lib.harvard.edu/ids/iiif/18833090/584,304,79,29/full/0/native.jpg)
II
![](https://ids.lib.harvard.edu/ids/iiif/18833090/426,303,54,25/full/0/native.jpg)
t
![](https://ids.lib.harvard.edu/ids/iiif/18833090/199,472,579,22/full/0/native.jpg)
LAKE SHORE MOTEL
CHAMBERLAIN, SOUTH DAKOTA
![](https://ids.lib.harvard.edu/ids/iiif/18833090/199,472,48,21/full/0/native.jpg)
LAKE
![](https://ids.lib.harvard.edu/ids/iiif/18833090/255,472,71,19/full/0/native.jpg)
SHORE
![](https://ids.lib.harvard.edu/ids/iiif/18833090/334,472,81,21/full/0/native.jpg)
MOTEL
![](https://ids.lib.harvard.edu/ids/iiif/18833090/450,473,159,21/full/0/native.jpg)
CHAMBERLAIN,
![](https://ids.lib.harvard.edu/ids/iiif/18833090/615,473,70,18/full/0/native.jpg)
SOUTH
![](https://ids.lib.harvard.edu/ids/iiif/18833090/692,473,86,18/full/0/native.jpg)
DAKOTA