Machine Generated Data
Tags
Amazon
created on 2023-10-23
Clarifai
created on 2023-10-15
Imagga
created on 2019-02-03
negative | 100 | |
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film | 100 | |
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photographic paper | 76 | |
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photographic equipment | 50.7 | |
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frame | 20 | |
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strip | 17.5 | |
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movie | 17.4 | |
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black | 16.8 | |
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graphic | 16.8 | |
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sky | 16.6 | |
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vintage | 16.5 | |
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border | 15.4 | |
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slide | 14.6 | |
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grunge | 14.5 | |
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building | 14.1 | |
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old | 13.9 | |
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camera | 13.9 | |
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photographic | 13.7 | |
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architecture | 13.3 | |
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screen | 13 | |
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scene | 13 | |
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texture | 12.5 | |
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art | 12.4 | |
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retro | 12.3 | |
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text | 12.2 | |
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landscape | 11.9 | |
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design | 11.8 | |
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cinema | 11.7 | |
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structure | 11.7 | |
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space | 11.6 | |
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business | 11.5 | |
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damaged | 11.4 | |
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clip | 11.2 | |
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blank | 11.1 | |
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tree | 10.8 | |
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horizon | 10.8 | |
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silhouette | 10.8 | |
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urban | 10.5 | |
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skyline | 10.4 | |
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roll | 10.4 | |
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antique | 10.4 | |
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35mm | 9.9 | |
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filmstrip | 9.8 | |
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picket fence | 9.8 | |
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fence | 9.8 | |
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skyscraper | 9.8 | |
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rural | 9.7 | |
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industry | 9.4 | |
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entertainment | 9.2 | |
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field | 9.2 | |
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city | 9.1 | |
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element | 9.1 | |
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dirty | 9 | |
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empty | 8.6 | |
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panorama | 8.6 | |
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outdoor | 8.4 | |
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pattern | 8.2 | |
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backgrounds | 8.1 | |
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grass | 7.9 | |
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country | 7.9 | |
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color | 7.8 | |
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clouds | 7.6 | |
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idyllic | 7.5 | |
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symbol | 7.4 | |
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land | 7.4 | |
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banner | 7.4 | |
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aged | 7.2 | |
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material | 7.1 | |
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season | 7 | |
|
Google
created on 2019-02-03
Photograph | 95.9 | |
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Text | 89.7 | |
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Black-and-white | 78.1 | |
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Egret | 74.5 | |
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Adaptation | 74.1 | |
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Photography | 73.8 | |
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Bird | 71.8 | |
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Monochrome photography | 69.6 | |
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Stock photography | 66.6 | |
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Picture frame | 54.8 | |
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Monochrome | 54.4 | |
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Rectangle | 53.4 | |
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Heron | 51.6 | |
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Water bird | 51.6 | |
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Photo caption | 51.3 | |
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Microsoft
created on 2019-02-03
black and white | 19.2 | |
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monochrome | 12.8 | |
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window | 4.4 | |
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art | 3.1 | |
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Color Analysis
Feature analysis
Categories
Imagga
interior objects | 95.5% | |
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streetview architecture | 2.1% | |
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paintings art | 1.6% | |
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Captions
Microsoft
created on 2019-02-03
a close up of a bridge | 35.3% | |
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a close up of a fence | 35.2% | |
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a close up of a white fence | 35.1% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/15488978/994,178,13,8/full/0/native.jpg)
or
![](https://ids.lib.harvard.edu/ids/iiif/15488978/774,4,40,9/full/0/native.jpg)
MAGON
![](https://ids.lib.harvard.edu/ids/iiif/15488978/179,10,24,6/full/0/native.jpg)
ИАЯ
![](https://ids.lib.harvard.edu/ids/iiif/15488978/138,9,65,7/full/0/native.jpg)
MJIR ИАЯ
![](https://ids.lib.harvard.edu/ids/iiif/15488978/222,9,6,6/full/0/native.jpg)
x
![](https://ids.lib.harvard.edu/ids/iiif/15488978/270,8,40,9/full/0/native.jpg)
MADOH
![](https://ids.lib.harvard.edu/ids/iiif/15488978/138,9,32,7/full/0/native.jpg)
MJIR
![](https://ids.lib.harvard.edu/ids/iiif/15488978/221,8,89,9/full/0/native.jpg)
x 1ЯТ MADOH
![](https://ids.lib.harvard.edu/ids/iiif/15488978/888,177,37,9/full/0/native.jpg)
AUI<
![](https://ids.lib.harvard.edu/ids/iiif/15488978/241,9,20,7/full/0/native.jpg)
1ЯТ
![](https://ids.lib.harvard.edu/ids/iiif/15488978/710,5,47,9/full/0/native.jpg)
YT3RAS
![](https://ids.lib.harvard.edu/ids/iiif/15488978/589,181,28,5/full/0/native.jpg)
CI
![](https://ids.lib.harvard.edu/ids/iiif/15488978/889,178,121,13/full/0/native.jpg)
Agt
or
![](https://ids.lib.harvard.edu/ids/iiif/15488978/889,178,24,13/full/0/native.jpg)
Agt
![](https://ids.lib.harvard.edu/ids/iiif/15488978/994,178,16,12/full/0/native.jpg)
or