Machine Generated Data
Tags
Amazon
created on 2020-04-26
Clarifai
created on 2020-04-26
Imagga
created on 2020-04-26
sketch | 100 | |
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drawing | 95.8 | |
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representation | 88.8 | |
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grunge | 40 | |
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texture | 36.1 | |
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old | 34.1 | |
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antique | 30.5 | |
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aged | 27.2 | |
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paper | 26.7 | |
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retro | 26.2 | |
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vintage | 25.8 | |
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dirty | 24.4 | |
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pattern | 22.6 | |
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ancient | 22.5 | |
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blank | 21.4 | |
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rough | 21 | |
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brown | 19.9 | |
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wall | 19.7 | |
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design | 19.1 | |
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damaged | 19.1 | |
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grungy | 19 | |
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surface | 17.6 | |
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wallpaper | 17.6 | |
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textured | 17.5 | |
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map | 17.5 | |
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material | 17 | |
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worn | 15.3 | |
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structure | 15.2 | |
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frame | 15 | |
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space | 14.7 | |
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empty | 14.6 | |
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art | 13.8 | |
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line | 13.7 | |
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border | 13.6 | |
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aging | 13.4 | |
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dirt | 13.4 | |
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backdrop | 13.2 | |
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sheet | 13.2 | |
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construction | 12.8 | |
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architecture | 12.5 | |
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canvas | 12.3 | |
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decorative | 11.7 | |
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text | 11.4 | |
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paint | 10.9 | |
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black | 10.8 | |
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scratch | 10.7 | |
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color | 10.6 | |
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parchment | 10.6 | |
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backgrounds | 10.5 | |
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detail | 10.5 | |
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page | 10.2 | |
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industrial | 10 | |
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decoration | 9.8 | |
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burnt | 9.7 | |
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sepia | 9.7 | |
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stained | 9.6 | |
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spot | 9.6 | |
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grain | 9.2 | |
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note | 9.2 | |
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sky | 8.9 | |
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torn | 8.7 | |
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old fashioned | 8.6 | |
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industry | 8.5 | |
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document | 8.4 | |
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silhouette | 8.3 | |
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style | 8.2 | |
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tower | 8.1 | |
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graphic | 8 | |
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nobody | 7.8 | |
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crack | 7.8 | |
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edge | 7.7 | |
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used | 7.7 | |
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winter | 7.7 | |
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rusty | 7.6 | |
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weathered | 7.6 | |
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power | 7.6 | |
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electricity | 7.6 | |
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electric | 7.5 | |
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metal | 7.2 | |
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building | 7.1 | |
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wire | 7.1 | |
|
Google
created on 2020-04-26
Sketch | 93.5 | |
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Drawing | 92 | |
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Line art | 82.6 | |
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Artwork | 72.6 | |
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Architecture | 65.5 | |
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Art | 62.5 | |
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Illustration | 60.2 | |
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Color Analysis
Feature analysis
Categories
Imagga
text visuals | 86.2% | |
| ||
paintings art | 9.9% | |
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streetview architecture | 3.5% | |
|
Captions
Microsoft
created on 2020-04-26
a close up of text on a white background | 66.9% | |
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a close up of text on a black background | 59.3% | |
| ||
a close up of text on a white surface | 59.2% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20220096/19,959,48,25/full/0/native.jpg)
im
![](https://ids.lib.harvard.edu/ids/iiif/20220096/15,985,61,26/full/0/native.jpg)
Aprie
![](https://ids.lib.harvard.edu/ids/iiif/20220096/20,954,173,33/full/0/native.jpg)
im (rghCnn
![](https://ids.lib.harvard.edu/ids/iiif/20220096/16,984,190,26/full/0/native.jpg)
Aprie An
![](https://ids.lib.harvard.edu/ids/iiif/20220096/157,987,48,24/full/0/native.jpg)
An
![](https://ids.lib.harvard.edu/ids/iiif/20220096/73,956,121,33/full/0/native.jpg)
(rghCnn
![](https://ids.lib.harvard.edu/ids/iiif/20220096/348,340,64,47/full/0/native.jpg)
1
![](https://ids.lib.harvard.edu/ids/iiif/20220096/329,413,100,15/full/0/native.jpg)
IVoooU
![](https://ids.lib.harvard.edu/ids/iiif/20220096/14,346,402,674/full/0/native.jpg)
11
7im Cighfa coln
April l.8.45 ANr.
![](https://ids.lib.harvard.edu/ids/iiif/20220096/354,346,62,44/full/0/native.jpg)
11
![](https://ids.lib.harvard.edu/ids/iiif/20220096/17,962,55,35/full/0/native.jpg)
7im
![](https://ids.lib.harvard.edu/ids/iiif/20220096/72,960,73,37/full/0/native.jpg)
Cighfa
![](https://ids.lib.harvard.edu/ids/iiif/20220096/147,965,48,33/full/0/native.jpg)
coln
![](https://ids.lib.harvard.edu/ids/iiif/20220096/14,988,69,32/full/0/native.jpg)
April
![](https://ids.lib.harvard.edu/ids/iiif/20220096/80,988,80,32/full/0/native.jpg)
l.8.45
![](https://ids.lib.harvard.edu/ids/iiif/20220096/158,988,50,32/full/0/native.jpg)
ANr.