Machine Generated Data
Tags
Amazon
created on 2019-07-20
Paint Container | 97.4 | |
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Palette | 97.2 | |
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Rug | 83.4 | |
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Jar | 67.8 | |
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Clarifai
created on 2019-07-20
no person | 98.3 | |
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business | 92.9 | |
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empty | 91 | |
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indoors | 90 | |
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glass items | 89 | |
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paper | 88.9 | |
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family | 88.5 | |
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contemporary | 87.8 | |
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desktop | 86.2 | |
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glass | 85.9 | |
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retro | 82.6 | |
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isolated | 81.6 | |
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container | 81.5 | |
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blank | 81.2 | |
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design | 81.2 | |
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illustration | 80.1 | |
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wood | 77.5 | |
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technology | 77.2 | |
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color | 76.7 | |
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plastic | 76.7 | |
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Imagga
created on 2019-07-20
jelly | 42.9 | |
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spread | 37.4 | |
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jar | 36.2 | |
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conserve | 27.7 | |
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container | 27.5 | |
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substance | 27.3 | |
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glass | 27.2 | |
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bottle | 26.3 | |
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food | 16.9 | |
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drink | 13.4 | |
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medicine | 13.2 | |
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fruit | 13 | |
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sweet | 12.6 | |
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health | 12.5 | |
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ingredient | 12.3 | |
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healthy | 12 | |
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preserve | 11.8 | |
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jam | 11.7 | |
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powder | 11.5 | |
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taste | 11.1 | |
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product | 10.8 | |
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liquid | 10.7 | |
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natural | 10.7 | |
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care | 10.7 | |
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medical | 10.6 | |
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therapy | 10.4 | |
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money | 10.2 | |
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lid | 9.8 | |
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close | 9.7 | |
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can | 9.6 | |
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table | 9.5 | |
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beverage | 9.3 | |
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eat | 9.2 | |
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fresh | 9.1 | |
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bottles | 8.8 | |
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aromatherapy | 8.6 | |
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hygiene | 8.5 | |
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traditional | 8.3 | |
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against | 8.3 | |
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full | 8.2 | |
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spa | 8.1 | |
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body | 8 | |
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chip | 7.9 | |
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marmalade | 7.9 | |
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toiletry | 7.8 | |
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nutrition | 7.5 | |
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relaxation | 7.5 | |
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aroma | 7.5 | |
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vessel | 7.4 | |
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water | 7.3 | |
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object | 7.3 | |
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meal | 7.3 | |
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playing | 7.3 | |
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wealth | 7.2 | |
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Microsoft
created on 2019-07-20
indoor | 96.3 | |
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bottle | 80 | |
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food storage containers | 66.7 | |
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mason jar | 59.7 | |
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Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/48477930/168,136,1068,1395/full/0/native.jpg)
Rug | 83.4% | |
|
Categories
Imagga
interior objects | 99.7% | |
|
Captions
Microsoft
created on 2019-07-20
a close up of food | 25.2% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/48477930/202,717,0,0/full/0/native.jpg)
cm.
![](https://ids.lib.harvard.edu/ids/iiif/48477930/192,758,0,1/full/0/native.jpg)
5
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1622,669,309,97/full/0/native.jpg)
SEPIA
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1626,881,369,77/full/0/native.jpg)
WEBERCO
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1625,881,394,77/full/0/native.jpg)
WEBERCO Co
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1939,883,80,60/full/0/native.jpg)
Co
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1827,960,183,33/full/0/native.jpg)
2DO
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1701,774,178,73/full/0/native.jpg)
yul
![](https://ids.lib.harvard.edu/ids/iiif/48477930/623,1343,403,99/full/0/native.jpg)
ov
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1709,780,74,70/full/0/native.jpg)
y4
![](https://ids.lib.harvard.edu/ids/iiif/48477930/203,1445,41,28/full/0/native.jpg)
0
![](https://ids.lib.harvard.edu/ids/iiif/48477930/203,623,1824,850/full/0/native.jpg)
SEPIA
y4 Ih
WEBER CO
5 cm.
0
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1634,677,303,93/full/0/native.jpg)
SEPIA
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1801,781,83,62/full/0/native.jpg)
Ih
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1637,887,302,86/full/0/native.jpg)
WEBER
![](https://ids.lib.harvard.edu/ids/iiif/48477930/1952,875,74,88/full/0/native.jpg)
CO
![](https://ids.lib.harvard.edu/ids/iiif/48477930/204,721,43,30/full/0/native.jpg)
5
![](https://ids.lib.harvard.edu/ids/iiif/48477930/215,623,37,88/full/0/native.jpg)
cm.