Machine Generated Data
Tags
Amazon
created on 2019-06-17
Clarifai
created on 2019-06-17
Imagga
created on 2019-06-17
landscape | 40.2 | |
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tree | 35.4 | |
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sky | 31.5 | |
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sand | 24.5 | |
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park | 21.4 | |
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desert | 21.2 | |
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scenic | 21.1 | |
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swine | 20.9 | |
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warthog | 20.7 | |
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travel | 20.4 | |
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scenery | 19.9 | |
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clouds | 19.5 | |
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trees | 18.7 | |
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mountain | 18.5 | |
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rock | 18.3 | |
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countryside | 16.5 | |
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national | 16.3 | |
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ungulate | 16 | |
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forest | 15.8 | |
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environment | 15.6 | |
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scene | 15.6 | |
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snow | 15.5 | |
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wilderness | 15.2 | |
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mountains | 14.8 | |
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old | 14.6 | |
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rural | 14.1 | |
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field | 13.4 | |
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country | 13.2 | |
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outdoor | 13 | |
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horizon | 12.6 | |
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fog | 12.6 | |
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sun | 12.5 | |
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wild | 12.2 | |
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beach | 12.1 | |
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land | 11.8 | |
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mist | 11.6 | |
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earth | 11.6 | |
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vacation | 11.5 | |
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giraffe | 11.4 | |
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outdoors | 11.2 | |
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grass | 11.1 | |
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grunge | 11.1 | |
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winter | 11.1 | |
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summer | 10.9 | |
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vintage | 10.8 | |
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weather | 10.7 | |
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soil | 10.6 | |
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cold | 10.3 | |
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season | 10.1 | |
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peaceful | 10.1 | |
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natural | 10 | |
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aged | 10 | |
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yellow | 9.9 | |
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tourism | 9.9 | |
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sunset | 9.9 | |
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foggy | 9.9 | |
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orange | 9.2 | |
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texture | 9 | |
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placental | 8.9 | |
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autumn | 8.8 | |
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hills | 8.7 | |
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stone | 8.7 | |
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day | 8.6 | |
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weathered | 8.6 | |
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dry | 8.4 | |
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plants | 8.4 | |
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cliff | 8.1 | |
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light | 8 | |
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arid | 7.8 | |
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antique | 7.8 | |
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cloud | 7.8 | |
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lonely | 7.7 | |
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dune | 7.7 | |
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house | 7.6 | |
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rocks | 7.5 | |
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grain | 7.4 | |
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brown | 7.4 | |
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rough | 7.3 | |
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fall | 7.2 | |
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morning | 7.2 | |
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sea | 7.2 | |
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ocean | 7.2 | |
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canyon | 7 | |
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Google
created on 2019-06-17
Painting | 86.4 | |
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Art | 81.6 | |
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Illustration | 77.6 | |
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Tree | 74.7 | |
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Visual arts | 68.6 | |
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Adaptation | 67 | |
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Printmaking | 64.4 | |
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Plant | 62.4 | |
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Stock photography | 62.1 | |
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Artwork | 52.3 | |
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Color Analysis
Feature analysis
Categories
Imagga
nature landscape | 61.5% | |
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beaches seaside | 23.9% | |
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paintings art | 11.4% | |
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streetview architecture | 1.4% | |
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Captions
Microsoft
created on 2019-06-17
an old photo of a book | 29.8% | |
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an old photo of a horse | 29.7% | |
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old photo of a book | 28.1% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20414425/416,747,113,40/full/0/native.jpg)
Chartier
![](https://ids.lib.harvard.edu/ids/iiif/20414425/533,743,153,44/full/0/native.jpg)
ollanctois
![](https://ids.lib.harvard.edu/ids/iiif/20414425/356,749,328,54/full/0/native.jpg)
fe Chartier ollanctois
![](https://ids.lib.harvard.edu/ids/iiif/20414425/799,805,24,14/full/0/native.jpg)
ches
![](https://ids.lib.harvard.edu/ids/iiif/20414425/899,795,46,21/full/0/native.jpg)
Pscat
![](https://ids.lib.harvard.edu/ids/iiif/20414425/859,800,36,18/full/0/native.jpg)
Mar
![](https://ids.lib.harvard.edu/ids/iiif/20414425/759,802,37,16/full/0/native.jpg)
Borlin
![](https://ids.lib.harvard.edu/ids/iiif/20414425/686,799,258,22/full/0/native.jpg)
s: Borlin ches in Mar Pscat
![](https://ids.lib.harvard.edu/ids/iiif/20414425/828,800,26,18/full/0/native.jpg)
in
![](https://ids.lib.harvard.edu/ids/iiif/20414425/358,752,51,50/full/0/native.jpg)
fe
![](https://ids.lib.harvard.edu/ids/iiif/20414425/687,800,19,18/full/0/native.jpg)
s:
![](https://ids.lib.harvard.edu/ids/iiif/20414425/363,749,582,76/full/0/native.jpg)
12.Chartier Aollandes
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Berlin che
wenda
![](https://ids.lib.harvard.edu/ids/iiif/20414425/764,805,34,19/full/0/native.jpg)
Berlin
![](https://ids.lib.harvard.edu/ids/iiif/20414425/797,805,22,18/full/0/native.jpg)
che
![](https://ids.lib.harvard.edu/ids/iiif/20414425/714,811,39,14/full/0/native.jpg)
wenda
![](https://ids.lib.harvard.edu/ids/iiif/20414425/363,749,169,50/full/0/native.jpg)
12.Chartier
![](https://ids.lib.harvard.edu/ids/iiif/20414425/558,749,131,42/full/0/native.jpg)
Aollandes
![](https://ids.lib.harvard.edu/ids/iiif/20414425/935,802,10,18/full/0/native.jpg)
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