Machine Generated Data
Tags
Amazon
created on 2019-11-02
Clarifai
created on 2019-11-02
Imagga
created on 2019-11-02
comic book | 47.1 | |
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billboard | 44.4 | |
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signboard | 37 | |
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daily | 32.3 | |
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structure | 31.3 | |
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stall | 30.9 | |
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money | 24.7 | |
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currency | 24.2 | |
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finance | 22 | |
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business | 21.9 | |
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bank | 19.7 | |
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architecture | 19.6 | |
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banking | 19.3 | |
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print media | 18.8 | |
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building | 18.4 | |
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cash | 18.3 | |
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city | 18.3 | |
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word | 17 | |
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financial | 16.9 | |
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dollar | 16.7 | |
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paper | 15.7 | |
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hundred | 15.5 | |
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bill | 15.2 | |
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conceptual | 15 | |
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cloud | 14.6 | |
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exchange | 14.3 | |
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representation | 14.1 | |
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style | 14.1 | |
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design | 14.1 | |
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tags | 13.8 | |
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definition | 13.7 | |
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neon | 13.7 | |
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wealth | 13.5 | |
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tag | 13.4 | |
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glowing | 12.9 | |
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shining | 12.6 | |
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dollars | 12.6 | |
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stylized | 12.5 | |
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graphic | 12.4 | |
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savings | 12.1 | |
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economy | 12.1 | |
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church | 12 | |
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investment | 11.9 | |
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house | 11.7 | |
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bright | 11.4 | |
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urban | 11.4 | |
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shiny | 11.1 | |
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note | 11 | |
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franklin | 10.8 | |
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light | 10.7 | |
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bills | 10.7 | |
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us | 10.6 | |
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window | 10.5 | |
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old | 10.4 | |
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art | 10.4 | |
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buildings | 10.4 | |
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town | 10.2 | |
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market | 9.8 | |
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payment | 9.6 | |
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shop | 9.5 | |
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commerce | 9.3 | |
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tower | 8.9 | |
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trade | 8.6 | |
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newspaper | 8.6 | |
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culture | 8.5 | |
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travel | 8.4 | |
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famous | 8.4 | |
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historic | 8.2 | |
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religion | 8.1 | |
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close | 8 | |
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interest | 7.8 | |
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product | 7.7 | |
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sales | 7.7 | |
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loan | 7.7 | |
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united | 7.6 | |
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cityscape | 7.6 | |
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religious | 7.5 | |
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stock | 7.5 | |
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tourism | 7.4 | |
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success | 7.2 | |
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landmark | 7.2 | |
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colorful | 7.2 | |
|
Google
created on 2019-11-02
Poster | 94.8 | |
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Font | 75 | |
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Vintage advertisement | 63.4 | |
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Art | 58.1 | |
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Advertising | 56.6 | |
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Illustration | 50.4 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20419861/97,422,51,85/full/0/native.jpg)
AWS Rekognition
Age | 22-34 |
Gender | Female, 57.2% |
Surprised | 2.4% |
Angry | 0.8% |
Sad | 4.3% |
Calm | 90.9% |
Fear | 0.3% |
Disgusted | 0.3% |
Confused | 0.2% |
Happy | 0.8% |
Feature analysis
Amazon
Categories
Imagga
paintings art | 99.5% | |
|
Captions
Microsoft
created on 2019-11-02
a person and text | 25.1% | |
| ||
a close up of text on a white surface | 25% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20419861/494,788,144,71/full/0/native.jpg)
MEATS
![](https://ids.lib.harvard.edu/ids/iiif/20419861/656,786,35,58/full/0/native.jpg)
&
![](https://ids.lib.harvard.edu/ids/iiif/20419861/696,773,116,65/full/0/native.jpg)
POULT
![](https://ids.lib.harvard.edu/ids/iiif/20419861/709,312,79,32/full/0/native.jpg)
COUPONS
![](https://ids.lib.harvard.edu/ids/iiif/20419861/322,793,158,92/full/0/native.jpg)
Kosher
![](https://ids.lib.harvard.edu/ids/iiif/20419861/82,802,729,118/full/0/native.jpg)
Strictly Kosher MEATS & POULT
![](https://ids.lib.harvard.edu/ids/iiif/20419861/678,398,45,16/full/0/native.jpg)
FRESH
![](https://ids.lib.harvard.edu/ids/iiif/20419861/229,642,35,22/full/0/native.jpg)
79:
![](https://ids.lib.harvard.edu/ids/iiif/20419861/692,425,64,28/full/0/native.jpg)
EGGS
![](https://ids.lib.harvard.edu/ids/iiif/20419861/693,455,75,51/full/0/native.jpg)
53
![](https://ids.lib.harvard.edu/ids/iiif/20419861/676,398,99,62/full/0/native.jpg)
FRESH EGGS LARGE
![](https://ids.lib.harvard.edu/ids/iiif/20419861/732,394,45,15/full/0/native.jpg)
LARGE
![](https://ids.lib.harvard.edu/ids/iiif/20419861/90,802,226,100/full/0/native.jpg)
Strictly
![](https://ids.lib.harvard.edu/ids/iiif/20419861/498,657,42,21/full/0/native.jpg)
220
![](https://ids.lib.harvard.edu/ids/iiif/20419861/694,314,17,31/full/0/native.jpg)
D
![](https://ids.lib.harvard.edu/ids/iiif/20419861/687,296,99,50/full/0/native.jpg)
accePT. D COUPONS
![](https://ids.lib.harvard.edu/ids/iiif/20419861/348,31,352,106/full/0/native.jpg)
usen sios
![](https://ids.lib.harvard.edu/ids/iiif/20419861/312,172,200,138/full/0/native.jpg)
TF
![](https://ids.lib.harvard.edu/ids/iiif/20419861/316,148,384,159/full/0/native.jpg)
TF ME
![](https://ids.lib.harvard.edu/ids/iiif/20419861/528,206,164,125/full/0/native.jpg)
ME
![](https://ids.lib.harvard.edu/ids/iiif/20419861/694,297,41,13/full/0/native.jpg)
accePT.
![](https://ids.lib.harvard.edu/ids/iiif/20419861/216,192,28,86/full/0/native.jpg)
E
![](https://ids.lib.harvard.edu/ids/iiif/20419861/56,290,777,683/full/0/native.jpg)
accept...
COUPONS
.
FRESH LARGE
EGGS
53
7 9
2 2 0
Strictly Kosher MEATS&POULT
2s0
![](https://ids.lib.harvard.edu/ids/iiif/20419861/701,290,50,24/full/0/native.jpg)
accept...
![](https://ids.lib.harvard.edu/ids/iiif/20419861/738,395,42,19/full/0/native.jpg)
LARGE
![](https://ids.lib.harvard.edu/ids/iiif/20419861/698,428,61,30/full/0/native.jpg)
EGGS
![](https://ids.lib.harvard.edu/ids/iiif/20419861/683,453,85,61/full/0/native.jpg)
53
![](https://ids.lib.harvard.edu/ids/iiif/20419861/237,648,12,21/full/0/native.jpg)
7
![](https://ids.lib.harvard.edu/ids/iiif/20419861/248,645,19,27/full/0/native.jpg)
9
![](https://ids.lib.harvard.edu/ids/iiif/20419861/506,663,13,20/full/0/native.jpg)
2
![](https://ids.lib.harvard.edu/ids/iiif/20419861/530,657,15,25/full/0/native.jpg)
0
![](https://ids.lib.harvard.edu/ids/iiif/20419861/89,800,238,118/full/0/native.jpg)
Strictly
![](https://ids.lib.harvard.edu/ids/iiif/20419861/318,785,177,112/full/0/native.jpg)
Kosher
![](https://ids.lib.harvard.edu/ids/iiif/20419861/497,754,336,126/full/0/native.jpg)
MEATS&POULT
![](https://ids.lib.harvard.edu/ids/iiif/20419861/56,951,47,22/full/0/native.jpg)
2s0
![](https://ids.lib.harvard.edu/ids/iiif/20419861/703,298,91,55/full/0/native.jpg)
COUPONS
![](https://ids.lib.harvard.edu/ids/iiif/20419861/775,368,39,12/full/0/native.jpg)
.
![](https://ids.lib.harvard.edu/ids/iiif/20419861/685,399,43,20/full/0/native.jpg)
FRESH