Machine Generated Data
Tags
Amazon
created on 2023-10-24
Clarifai
created on 2023-10-15
Imagga
created on 2019-02-03
architecture | 64.8 | |
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building | 36.3 | |
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construction | 27.4 | |
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structure | 27 | |
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city | 24.9 | |
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house | 22.7 | |
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urban | 21.9 | |
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modern | 21 | |
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sky | 20.4 | |
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home | 20.1 | |
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travel | 19.7 | |
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town | 17.6 | |
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design | 17.5 | |
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business | 16.4 | |
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project | 15.4 | |
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architectural | 15.4 | |
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hall | 15.3 | |
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office | 14.9 | |
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window | 14.6 | |
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drawing | 14.4 | |
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plan | 14.2 | |
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sketch | 14 | |
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tourism | 13.2 | |
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perspective | 13.2 | |
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wall | 12.9 | |
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snow | 12.7 | |
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architect | 12.6 | |
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interior | 12.4 | |
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cityscape | 12.3 | |
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high | 12.1 | |
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center | 12 | |
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glass | 11.7 | |
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vacation | 11.5 | |
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buildings | 11.3 | |
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street | 11 | |
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tower | 10.7 | |
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residential | 10.5 | |
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scene | 10.4 | |
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light | 10 | |
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built | 9.6 | |
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apartment | 9.6 | |
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sunny | 9.5 | |
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paper | 9.5 | |
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roof | 9.4 | |
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holiday | 9.3 | |
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exterior | 9.2 | |
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old | 9.1 | |
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transportation | 9 | |
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blueprint | 8.8 | |
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negative | 8.7 | |
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work | 8.6 | |
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sea | 8.6 | |
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empty | 8.6 | |
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floor | 8.4 | |
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transport | 8.2 | |
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landscape | 8.2 | |
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new | 8.1 | |
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business district | 8.1 | |
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corporate | 7.7 | |
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village | 7.7 | |
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concrete | 7.7 | |
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engineering | 7.6 | |
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power | 7.6 | |
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metal | 7.2 | |
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detail | 7.2 | |
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road | 7.2 | |
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room | 7.2 | |
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Google
created on 2019-02-03
White | 96.8 | |
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Motor vehicle | 90.1 | |
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House | 82.8 | |
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Home | 76.1 | |
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Vehicle | 73 | |
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Car | 70.8 | |
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Building | 69.9 | |
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Black-and-white | 68.3 | |
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Architecture | 65.5 | |
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Monochrome | 60.1 | |
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Family car | 57.4 | |
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Roof | 54.4 | |
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Microsoft
created on 2019-02-03
white | 63.3 | |
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black and white | 63.3 | |
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snow | 31.3 | |
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winter | 24.6 | |
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car | 18.1 | |
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monochrome | 16.4 | |
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street | 15.1 | |
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Color Analysis
Feature analysis
Categories
Imagga
interior objects | 68.6% | |
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streetview architecture | 28.5% | |
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paintings art | 1.5% | |
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Captions
Microsoft
created on 2019-02-03
a white car in front of a building | 92.6% | |
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a small white car in front of a building | 87.6% | |
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a close up of a white car in front of a building | 87.5% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/15487228/225,350,22,12/full/0/native.jpg)
ONE
![](https://ids.lib.harvard.edu/ids/iiif/15487228/225,363,21,10/full/0/native.jpg)
WAY
![](https://ids.lib.harvard.edu/ids/iiif/15487228/150,378,19,19/full/0/native.jpg)
Kraft
![](https://ids.lib.harvard.edu/ids/iiif/15487228/192,290,35,30/full/0/native.jpg)
CAMEIS
![](https://ids.lib.harvard.edu/ids/iiif/15487228/133,393,36,21/full/0/native.jpg)
Mayonnaise
![](https://ids.lib.harvard.edu/ids/iiif/15487228/194,321,31,15/full/0/native.jpg)
adidas
![](https://ids.lib.harvard.edu/ids/iiif/15487228/152,351,106,49/full/0/native.jpg)
ONE
lat
![](https://ids.lib.harvard.edu/ids/iiif/15487228/228,351,30,16/full/0/native.jpg)
ONE
![](https://ids.lib.harvard.edu/ids/iiif/15487228/152,380,20,20/full/0/native.jpg)
lat