Machine Generated Data
Tags
Amazon
created on 2022-06-04
Blackboard | 99.1 | |
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Display | 87.6 | |
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Monitor | 87.6 | |
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Electronics | 87.6 | |
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Screen | 87.6 | |
|
Clarifai
created on 2023-10-31
Imagga
created on 2022-06-04
Google
created on 2022-06-04
Picture frame | 95.6 | |
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Rectangle | 87.3 | |
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Grey | 84.2 | |
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Wood | 83.1 | |
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Tints and shades | 77 | |
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Font | 77 | |
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Handwriting | 70.8 | |
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Pattern | 70.4 | |
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Monochrome photography | 68.7 | |
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Blackboard | 66.9 | |
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Visual arts | 65.4 | |
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Window | 63.3 | |
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Room | 63.2 | |
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Monochrome | 63 | |
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Circle | 61.7 | |
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Darkness | 60.4 | |
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Square | 59.3 | |
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Art | 55 | |
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Number | 50.6 | |
|
Microsoft
created on 2022-06-04
monitor | 98.4 | |
| ||
wall | 98 | |
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indoor | 97.1 | |
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text | 96.9 | |
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black | 91.4 | |
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handwriting | 90.7 | |
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screenshot | 84.1 | |
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white | 82 | |
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blackboard | 63.3 | |
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old | 45.4 | |
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flat | 43.7 | |
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picture frame | 14.1 | |
|
Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20026140/77,99,892,662/full/0/native.jpg)
Monitor | 87.6% | |
|
Categories
Imagga
interior objects | 59.6% | |
| ||
text visuals | 17.4% | |
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streetview architecture | 16% | |
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pets animals | 2.4% | |
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food drinks | 1.5% | |
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paintings art | 1.3% | |
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cars vehicles | 1.2% | |
|
Captions
Microsoft
created on 2022-06-04
a flat screen tv sitting on top of a blackboard | 59.8% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20026140/781,655,49,22/full/0/native.jpg)
79.11
![](https://ids.lib.harvard.edu/ids/iiif/20026140/822,599,14,7/full/0/native.jpg)
135
![](https://ids.lib.harvard.edu/ids/iiif/20026140/825,581,13,7/full/0/native.jpg)
80
![](https://ids.lib.harvard.edu/ids/iiif/20026140/821,565,7,4/full/0/native.jpg)
Les
![](https://ids.lib.harvard.edu/ids/iiif/20026140/824,558,15,5/full/0/native.jpg)
KALL
![](https://ids.lib.harvard.edu/ids/iiif/20026140/821,565,22,6/full/0/native.jpg)
Les my
![](https://ids.lib.harvard.edu/ids/iiif/20026140/832,565,11,6/full/0/native.jpg)
my
![](https://ids.lib.harvard.edu/ids/iiif/20026140/799,605,15,5/full/0/native.jpg)
الله
![](https://ids.lib.harvard.edu/ids/iiif/20026140/823,574,20,5/full/0/native.jpg)
LOTTE
![](https://ids.lib.harvard.edu/ids/iiif/20026140/726,571,18,6/full/0/native.jpg)
and
![](https://ids.lib.harvard.edu/ids/iiif/20026140/293,456,36,11/full/0/native.jpg)
Am
![](https://ids.lib.harvard.edu/ids/iiif/20026140/721,557,28,11/full/0/native.jpg)
TREENT
![](https://ids.lib.harvard.edu/ids/iiif/20026140/821,566,30,11/full/0/native.jpg)
A11
![](https://ids.lib.harvard.edu/ids/iiif/20026140/214,292,636,389/full/0/native.jpg)
****
ALBA
Am
AN
***
吃...
My fe
TREENT
HE
A11
79.11
![](https://ids.lib.harvard.edu/ids/iiif/20026140/215,293,27,9/full/0/native.jpg)
****
![](https://ids.lib.harvard.edu/ids/iiif/20026140/275,361,25,10/full/0/native.jpg)
ALBA
![](https://ids.lib.harvard.edu/ids/iiif/20026140/293,462,13,11/full/0/native.jpg)
AN
![](https://ids.lib.harvard.edu/ids/iiif/20026140/512,450,20,8/full/0/native.jpg)
***
![](https://ids.lib.harvard.edu/ids/iiif/20026140/621,408,25,16/full/0/native.jpg)
吃
![](https://ids.lib.harvard.edu/ids/iiif/20026140/643,408,28,16/full/0/native.jpg)
...
![](https://ids.lib.harvard.edu/ids/iiif/20026140/634,460,20,11/full/0/native.jpg)
My
![](https://ids.lib.harvard.edu/ids/iiif/20026140/682,453,13,10/full/0/native.jpg)
fe
![](https://ids.lib.harvard.edu/ids/iiif/20026140/781,437,19,10/full/0/native.jpg)
HE
![](https://ids.lib.harvard.edu/ids/iiif/20026140/784,659,50,22/full/0/native.jpg)
79.11