Machine Generated Data
Tags
Amazon
created on 2022-06-04
Metropolis | 97.6 | |
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Building | 97.6 | |
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Urban | 97.6 | |
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City | 97.6 | |
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Town | 97.6 | |
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Spire | 96 | |
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Steeple | 96 | |
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Architecture | 96 | |
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Tower | 96 | |
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Landscape | 94.6 | |
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Outdoors | 94.6 | |
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Nature | 94.6 | |
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Scenery | 92 | |
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Office Building | 77.7 | |
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Aerial View | 73.8 | |
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Person | 72 | |
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Human | 72 | |
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Water | 67.3 | |
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High Rise | 62.1 | |
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Neighborhood | 58.9 | |
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Castle | 58.8 | |
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Dome | 58.8 | |
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Fort | 55.1 | |
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Imagga
created on 2022-06-04
Google
created on 2022-06-04
Building | 95 | |
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Black | 89.7 | |
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Urban design | 83.5 | |
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Black-and-white | 82.6 | |
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Cityscape | 80.6 | |
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Window | 80.1 | |
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Tower block | 79.6 | |
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Facade | 78.3 | |
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Roof | 75.9 | |
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Font | 74 | |
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City | 73.9 | |
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Rectangle | 73.7 | |
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Metropolis | 72.4 | |
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Landscape | 72.1 | |
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Mixed-use | 69.2 | |
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Monochrome photography | 68.7 | |
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Monochrome | 65.8 | |
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History | 65.2 | |
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Arch | 63.9 | |
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Art | 63.1 | |
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Microsoft
created on 2022-06-04
black and white | 96.1 | |
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city | 94.1 | |
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outdoor | 89.5 | |
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building | 86.8 | |
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monochrome | 66.2 | |
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white | 61.4 | |
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cityscape | 53.8 | |
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house | 50.7 | |
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Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20489191/559,970,19,49/full/0/native.jpg)
Person | 72% | |
|
Categories
Imagga
interior objects | 92.6% | |
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paintings art | 4.4% | |
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streetview architecture | 2.6% | |
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Captions
Microsoft
created on 2022-06-04
a large building | 61% | |
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a close up of an old building | 60.9% | |
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a large building in the background | 60.8% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20489191/552,496,26,25/full/0/native.jpg)
OIL
![](https://ids.lib.harvard.edu/ids/iiif/20489191/627,595,10,8/full/0/native.jpg)
12
![](https://ids.lib.harvard.edu/ids/iiif/20489191/1,423,36,19/full/0/native.jpg)
D'S
![](https://ids.lib.harvard.edu/ids/iiif/20489191/0,447,50,31/full/0/native.jpg)
NE
![](https://ids.lib.harvard.edu/ids/iiif/20489191/626,550,28,13/full/0/native.jpg)
SAY!
![](https://ids.lib.harvard.edu/ids/iiif/20489191/7,783,30,12/full/0/native.jpg)
USE
![](https://ids.lib.harvard.edu/ids/iiif/20489191/628,563,25,10/full/0/native.jpg)
WANT
![](https://ids.lib.harvard.edu/ids/iiif/20489191/568,520,22,19/full/0/native.jpg)
CO
![](https://ids.lib.harvard.edu/ids/iiif/20489191/627,595,27,8/full/0/native.jpg)
12 JP
![](https://ids.lib.harvard.edu/ids/iiif/20489191/550,504,43,31/full/0/native.jpg)
PORTRAIT
![](https://ids.lib.harvard.edu/ids/iiif/20489191/726,913,10,35/full/0/native.jpg)
98888
![](https://ids.lib.harvard.edu/ids/iiif/20489191/329,377,46,13/full/0/native.jpg)
LEOPO
![](https://ids.lib.harvard.edu/ids/iiif/20489191/1,503,59,21/full/0/native.jpg)
TS
![](https://ids.lib.harvard.edu/ids/iiif/20489191/329,375,141,18/full/0/native.jpg)
LEOPO HORSE&CO.C.OTH
![](https://ids.lib.harvard.edu/ids/iiif/20489191/606,525,67,21/full/0/native.jpg)
DEARS
![](https://ids.lib.harvard.edu/ids/iiif/20489191/628,583,25,7/full/0/native.jpg)
1001
![](https://ids.lib.harvard.edu/ids/iiif/20489191/375,375,95,18/full/0/native.jpg)
HORSE&CO.C.OTH
![](https://ids.lib.harvard.edu/ids/iiif/20489191/628,575,28,7/full/0/native.jpg)
SANT
![](https://ids.lib.harvard.edu/ids/iiif/20489191/641,595,13,7/full/0/native.jpg)
JP
![](https://ids.lib.harvard.edu/ids/iiif/20489191/-9,374,426,427/full/0/native.jpg)
D'S
ONES
HTS:
Shester
LEOPOO HORSE
![](https://ids.lib.harvard.edu/ids/iiif/20489191/4,425,36,20/full/0/native.jpg)
D'S
![](https://ids.lib.harvard.edu/ids/iiif/20489191/-8,448,75,35/full/0/native.jpg)
ONES
![](https://ids.lib.harvard.edu/ids/iiif/20489191/-4,503,54,27/full/0/native.jpg)
HTS
![](https://ids.lib.harvard.edu/ids/iiif/20489191/48,503,14,25/full/0/native.jpg)
:
![](https://ids.lib.harvard.edu/ids/iiif/20489191/283,790,32,11/full/0/native.jpg)
Shester
![](https://ids.lib.harvard.edu/ids/iiif/20489191/328,374,50,22/full/0/native.jpg)
LEOPOO
![](https://ids.lib.harvard.edu/ids/iiif/20489191/378,377,39,22/full/0/native.jpg)
HORSE