Machine Generated Data
Tags
Amazon
created on 2022-06-04
Imagga
created on 2022-06-04
Google
created on 2022-06-04
Building | 93.6 | |
| ||
Black | 89.6 | |
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Black-and-white | 82.2 | |
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Monochrome | 77.3 | |
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Monochrome photography | 74.3 | |
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Event | 70.8 | |
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Pollution | 68.7 | |
| ||
History | 64.5 | |
| ||
Stock photography | 63.5 | |
| ||
House | 62.5 | |
| ||
Darkness | 62.3 | |
| ||
Art | 61.2 | |
| ||
Sky | 59.1 | |
| ||
Rubble | 58.9 | |
| ||
Landscape | 56.6 | |
| ||
Electricity | 55.5 | |
| ||
Window | 55.2 | |
| ||
Illustration | 52.6 | |
| ||
Night | 52 | |
| ||
Slope | 51.6 | |
|
Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20489092/559,399,57,120/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/20489092/123,370,33,101/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/20489092/432,384,34,120/full/0/native.jpg)
![](https://ids.lib.harvard.edu/ids/iiif/20489092/379,526,50,84/full/0/native.jpg)
Person | 95.9% | |
|
Categories
Imagga
streetview architecture | 43.1% | |
| ||
paintings art | 29.7% | |
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nature landscape | 15.9% | |
| ||
beaches seaside | 6.9% | |
| ||
cars vehicles | 3.3% | |
|
Captions
Microsoft
created on 2022-06-04
a vintage photo of an old building | 86.1% | |
| ||
a vintage photo of a building | 85.2% | |
| ||
a vintage photo of an old building in the background | 84% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20489092/37,196,52,11/full/0/native.jpg)
LUNCH
![](https://ids.lib.harvard.edu/ids/iiif/20489092/31,277,82,17/full/0/native.jpg)
SOCONY
![](https://ids.lib.harvard.edu/ids/iiif/20489092/5,118,116,24/full/0/native.jpg)
Goodrich
![](https://ids.lib.harvard.edu/ids/iiif/20489092/40,138,79,20/full/0/native.jpg)
Silvertowns
![](https://ids.lib.harvard.edu/ids/iiif/20489092/45,106,75,18/full/0/native.jpg)
Reduced Now
![](https://ids.lib.harvard.edu/ids/iiif/20489092/68,255,49,21/full/0/native.jpg)
STATION
![](https://ids.lib.harvard.edu/ids/iiif/20489092/25,254,92,23/full/0/native.jpg)
FILLING ST STATION
![](https://ids.lib.harvard.edu/ids/iiif/20489092/25,254,56,23/full/0/native.jpg)
FILLING ST
![](https://ids.lib.harvard.edu/ids/iiif/20489092/870,695,79,31/full/0/native.jpg)
18548
![](https://ids.lib.harvard.edu/ids/iiif/20489092/4,105,117,19/full/0/native.jpg)
Forces Reduced Now
![](https://ids.lib.harvard.edu/ids/iiif/20489092/4,106,41,13/full/0/native.jpg)
Forces
![](https://ids.lib.harvard.edu/ids/iiif/20489092/3,89,123,211/full/0/native.jpg)
clamp
Velces Reduced Now
Goodrich
Silvertowns
ASVANGIN
LUNCH
FILLING STATION
SOCONY
![](https://ids.lib.harvard.edu/ids/iiif/20489092/53,90,35,12/full/0/native.jpg)
clamp
![](https://ids.lib.harvard.edu/ids/iiif/20489092/7,108,42,16/full/0/native.jpg)
Velces
![](https://ids.lib.harvard.edu/ids/iiif/20489092/48,110,51,15/full/0/native.jpg)
Reduced
![](https://ids.lib.harvard.edu/ids/iiif/20489092/97,111,27,16/full/0/native.jpg)
Now
![](https://ids.lib.harvard.edu/ids/iiif/20489092/7,119,118,27/full/0/native.jpg)
Goodrich
![](https://ids.lib.harvard.edu/ids/iiif/20489092/42,141,81,19/full/0/native.jpg)
Silvertowns
![](https://ids.lib.harvard.edu/ids/iiif/20489092/33,168,91,18/full/0/native.jpg)
ASVANGIN
![](https://ids.lib.harvard.edu/ids/iiif/20489092/38,197,57,16/full/0/native.jpg)
LUNCH
![](https://ids.lib.harvard.edu/ids/iiif/20489092/29,259,45,20/full/0/native.jpg)
FILLING
![](https://ids.lib.harvard.edu/ids/iiif/20489092/73,260,49,20/full/0/native.jpg)
STATION
![](https://ids.lib.harvard.edu/ids/iiif/20489092/33,278,85,21/full/0/native.jpg)
SOCONY