Machine Generated Data
Tags
Amazon
created on 2023-10-25
Clarifai
created on 2018-10-06
negative | 100 | |
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exposed | 99.9 | |
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collage | 99.7 | |
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filmstrip | 99.7 | |
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picture frame | 99.6 | |
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emulsion | 99.5 | |
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slide | 99.5 | |
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photograph | 99.2 | |
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no person | 98.5 | |
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movie | 97.9 | |
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retro | 97.7 | |
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monochrome | 97.3 | |
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sliding | 97.1 | |
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empty | 97 | |
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blank | 97 | |
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dirty | 96.8 | |
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moment | 96.7 | |
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margin | 96 | |
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cinematography | 95.8 | |
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nostalgia | 95.6 | |
|
Imagga
created on 2018-10-06
Google
created on 2018-10-06
photograph | 95.9 | |
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black and white | 94.3 | |
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text | 88.6 | |
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monochrome photography | 85.6 | |
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photography | 84.1 | |
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monochrome | 74.3 | |
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font | 57.7 | |
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angle | 55.3 | |
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jaw | 53.8 | |
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stock photography | 53 | |
|
Color Analysis
Feature analysis
Categories
Imagga
interior objects | 47.3% | |
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text visuals | 41.2% | |
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pets animals | 8.8% | |
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paintings art | 0.9% | |
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streetview architecture | 0.8% | |
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food drinks | 0.4% | |
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cars vehicles | 0.3% | |
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beaches seaside | 0.3% | |
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people portraits | 0.1% | |
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nature landscape | 0.1% | |
|
Captions
Microsoft
created on 2018-10-06
a flat screen tv sitting in front of a television | 72.4% | |
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a flat screen tv sitting on top of a television | 70.7% | |
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a flat screen television | 70.6% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/38979211/40,180,11,9/full/0/native.jpg)
21
![](https://ids.lib.harvard.edu/ids/iiif/38979211/627,179,15,7/full/0/native.jpg)
24
![](https://ids.lib.harvard.edu/ids/iiif/38979211/818,7,33,7/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979211/818,7,66,7/full/0/native.jpg)
PAN FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979211/860,7,24,6/full/0/native.jpg)
PAN
![](https://ids.lib.harvard.edu/ids/iiif/38979211/829,178,16,7/full/0/native.jpg)
25
![](https://ids.lib.harvard.edu/ids/iiif/38979211/436,179,15,7/full/0/native.jpg)
23
![](https://ids.lib.harvard.edu/ids/iiif/38979211/229,179,15,7/full/0/native.jpg)
22
![](https://ids.lib.harvard.edu/ids/iiif/38979211/525,178,22,7/full/0/native.jpg)
23A
![](https://ids.lib.harvard.edu/ids/iiif/38979211/721,178,25,8/full/0/native.jpg)
200
![](https://ids.lib.harvard.edu/ids/iiif/38979211/10,11,6,3/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/38979211/903,7,6,7/full/0/native.jpg)
x
![](https://ids.lib.harvard.edu/ids/iiif/38979211/327,179,25,7/full/0/native.jpg)
22A
![](https://ids.lib.harvard.edu/ids/iiif/38979211/10,9,52,8/full/0/native.jpg)
KODAK -
![](https://ids.lib.harvard.edu/ids/iiif/38979211/15,9,48,8/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979211/459,8,43,7/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979211/925,177,25,7/full/0/native.jpg)
250
![](https://ids.lib.harvard.edu/ids/iiif/38979211/520,7,35,7/full/0/native.jpg)
FROOM
![](https://ids.lib.harvard.edu/ids/iiif/38979211/921,7,72,7/full/0/native.jpg)
FS
![](https://ids.lib.harvard.edu/ids/iiif/38979211/34,7,837,14/full/0/native.jpg)
N FILM
KOD
KODA
![](https://ids.lib.harvard.edu/ids/iiif/38979211/861,8,10,10/full/0/native.jpg)
N
![](https://ids.lib.harvard.edu/ids/iiif/38979211/818,7,37,11/full/0/native.jpg)
FILM
![](https://ids.lib.harvard.edu/ids/iiif/38979211/534,7,26,11/full/0/native.jpg)
KOD
![](https://ids.lib.harvard.edu/ids/iiif/38979211/34,10,33,11/full/0/native.jpg)
KODA