Machine Generated Data
Tags
Amazon
created on 2023-10-25
Clarifai
created on 2018-10-06
Imagga
created on 2018-10-06
wreckage | 53.8 | |
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part | 40.2 | |
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sky | 31.2 | |
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snow | 29.2 | |
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landscape | 29 | |
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water | 23.3 | |
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weather | 19.9 | |
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travel | 19.7 | |
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cloud | 17.2 | |
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sunset | 17.1 | |
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beach | 16.9 | |
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sea | 16.6 | |
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cold | 16.4 | |
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ocean | 16.1 | |
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clouds | 16.1 | |
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sun | 15.3 | |
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vintage | 14.9 | |
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light | 14.7 | |
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forest | 13.9 | |
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scene | 13.8 | |
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black | 13.8 | |
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winter | 13.6 | |
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web site | 13.2 | |
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vacation | 13.1 | |
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outdoor | 13 | |
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mountain | 12.7 | |
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old | 12.5 | |
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tourism | 12.4 | |
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machine | 12.3 | |
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summer | 12.2 | |
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sunrise | 12.2 | |
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land | 11.6 | |
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fog | 11.6 | |
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trees | 11.6 | |
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holiday | 11.5 | |
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snow thrower | 11.3 | |
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outdoors | 11.2 | |
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scenery | 10.8 | |
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sand | 10.7 | |
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moon | 10.7 | |
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river | 10.7 | |
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mist | 10.6 | |
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scenic | 10.5 | |
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boat | 10.4 | |
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adventure | 10.4 | |
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rock | 10.4 | |
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shore | 10.4 | |
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grunge | 10.2 | |
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season | 10.1 | |
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natural | 10 | |
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dark | 10 | |
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tree | 10 | |
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silhouette | 9.9 | |
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coast | 9.9 | |
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cool | 9.8 | |
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ice | 9.6 | |
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mountains | 9.3 | |
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lake | 9.2 | |
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device | 9.1 | |
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tranquil | 9 | |
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splash | 9 | |
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texture | 9 | |
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horizon | 9 | |
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recreation | 9 | |
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sunlight | 8.9 | |
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pattern | 8.9 | |
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dawn | 8.7 | |
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dusk | 8.6 | |
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art | 8.6 | |
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bright | 8.6 | |
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space | 8.5 | |
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coastline | 8.5 | |
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island | 8.2 | |
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retro | 8.2 | |
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morning | 8.1 | |
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wave | 7.8 | |
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frost | 7.7 | |
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tropical | 7.7 | |
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heaven | 7.6 | |
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relaxation | 7.5 | |
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city | 7.5 | |
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leisure | 7.5 | |
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evening | 7.5 | |
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park | 7.4 | |
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environment | 7.4 | |
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paint | 7.2 | |
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color | 7.2 | |
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vehicle | 7.2 | |
|
Google
created on 2018-10-06
photograph | 95.5 | |
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black and white | 93.2 | |
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text | 86.2 | |
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photography | 83.1 | |
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monochrome photography | 81.9 | |
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poster | 70.3 | |
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monochrome | 65 | |
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font | 61.3 | |
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stock photography | 59.1 | |
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computer wallpaper | 50.2 | |
|
Color Analysis
Categories
Imagga
paintings art | 44.8% | |
| ||
text visuals | 28.5% | |
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pets animals | 9.1% | |
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streetview architecture | 9.1% | |
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interior objects | 7.1% | |
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nature landscape | 0.5% | |
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food drinks | 0.4% | |
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beaches seaside | 0.2% | |
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people portraits | 0.2% | |
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events parties | 0.1% | |
|
Captions
Microsoft
created on 2018-10-06
a screen shot of a person | 57.2% | |
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a screen shot of a social media post | 57.1% | |
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a screen shot of a horse | 53.3% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/38979109/520,9,32,7/full/0/native.jpg)
PLUS
![](https://ids.lib.harvard.edu/ids/iiif/38979109/614,9,32,7/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979109/580,9,24,7/full/0/native.jpg)
PAN
![](https://ids.lib.harvard.edu/ids/iiif/38979109/471,9,39,8/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979109/628,182,16,7/full/0/native.jpg)
9A
![](https://ids.lib.harvard.edu/ids/iiif/38979109/228,182,17,9/full/0/native.jpg)
7A
![](https://ids.lib.harvard.edu/ids/iiif/38979109/734,182,12,8/full/0/native.jpg)
10
![](https://ids.lib.harvard.edu/ids/iiif/38979109/30,10,47,10/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979109/27,183,16,9/full/0/native.jpg)
6A
![](https://ids.lib.harvard.edu/ids/iiif/38979109/471,8,175,9/full/0/native.jpg)
KODAK PLUS x PAN FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979109/132,184,6,7/full/0/native.jpg)
7
![](https://ids.lib.harvard.edu/ids/iiif/38979109/831,181,21,8/full/0/native.jpg)
10A
![](https://ids.lib.harvard.edu/ids/iiif/38979109/378,183,6,6/full/0/native.jpg)
H
![](https://ids.lib.harvard.edu/ids/iiif/38979109/329,183,8,8/full/0/native.jpg)
8
![](https://ids.lib.harvard.edu/ids/iiif/38979109/564,10,6,7/full/0/native.jpg)
x
![](https://ids.lib.harvard.edu/ids/iiif/38979109/936,182,5,4/full/0/native.jpg)
1
![](https://ids.lib.harvard.edu/ids/iiif/38979109/32,9,978,189/full/0/native.jpg)
SAFETY FILM
KODAK PLUS X PAN FILM
KODAK SAFET
27
-> 7 A
→8
-9A
10
→ 10A
![](https://ids.lib.harvard.edu/ids/iiif/38979109/32,12,48,12/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979109/83,12,46,12/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979109/472,10,42,11/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979109/521,9,35,11/full/0/native.jpg)
PLUS
![](https://ids.lib.harvard.edu/ids/iiif/38979109/563,9,11,11/full/0/native.jpg)
X
![](https://ids.lib.harvard.edu/ids/iiif/38979109/580,9,28,11/full/0/native.jpg)
PAN
![](https://ids.lib.harvard.edu/ids/iiif/38979109/959,9,51,12/full/0/native.jpg)
SAFET
![](https://ids.lib.harvard.edu/ids/iiif/38979109/110,183,30,13/full/0/native.jpg)
27
![](https://ids.lib.harvard.edu/ids/iiif/38979109/208,186,10,6/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/38979109/214,182,16,12/full/0/native.jpg)
>
![](https://ids.lib.harvard.edu/ids/iiif/38979109/228,183,10,11/full/0/native.jpg)
7
![](https://ids.lib.harvard.edu/ids/iiif/38979109/238,183,11,11/full/0/native.jpg)
A
![](https://ids.lib.harvard.edu/ids/iiif/38979109/308,184,22,9/full/0/native.jpg)
→
![](https://ids.lib.harvard.edu/ids/iiif/38979109/328,183,13,12/full/0/native.jpg)
8
![](https://ids.lib.harvard.edu/ids/iiif/38979109/607,182,39,16/full/0/native.jpg)
-9A
![](https://ids.lib.harvard.edu/ids/iiif/38979109/734,182,17,13/full/0/native.jpg)
10
![](https://ids.lib.harvard.edu/ids/iiif/38979109/831,182,25,12/full/0/native.jpg)
10A