Machine Generated Data
Tags
Amazon
created on 2022-01-09
Mobile Phone | 93.7 | |
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Electronics | 93.7 | |
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Phone | 93.7 | |
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Cell Phone | 93.7 | |
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Building | 82.4 | |
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Monitor | 68.6 | |
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Display | 68.6 | |
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Screen | 68.6 | |
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Hangar | 59.9 | |
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Leisure Activities | 58.2 | |
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Ice Skating | 55.1 | |
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Sport | 55.1 | |
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Skating | 55.1 | |
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Sports | 55.1 | |
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Clarifai
created on 2023-10-25
street | 98.5 | |
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winter | 97.7 | |
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monochrome | 97.7 | |
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light | 97.7 | |
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snow | 96.4 | |
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city | 95.6 | |
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locomotive | 95.6 | |
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dark | 94.8 | |
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train | 93.2 | |
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subway system | 91.9 | |
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no person | 91.1 | |
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ice | 91.1 | |
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abstract | 90.6 | |
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urban | 90.5 | |
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old | 89.9 | |
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architecture | 89.6 | |
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photograph | 89.4 | |
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track | 88.4 | |
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signalise | 87.7 | |
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shadow | 87.7 | |
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Imagga
created on 2022-01-09
equipment | 28.5 | |
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device | 23.8 | |
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digital | 22.7 | |
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technology | 21.5 | |
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black | 20.7 | |
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digital clock | 20.7 | |
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film | 18.5 | |
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clock | 17.9 | |
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screen | 15.1 | |
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timepiece | 14.9 | |
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old | 14.6 | |
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black box | 14.1 | |
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recorder | 13.7 | |
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electronic equipment | 13.4 | |
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business | 13.4 | |
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computer | 12.1 | |
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board | 11.3 | |
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television | 11.3 | |
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radio | 11.2 | |
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dirty | 10.8 | |
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broadcasting | 10.8 | |
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night | 10.6 | |
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grunge | 10.2 | |
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vintage | 9.9 | |
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travel | 9.9 | |
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reel | 9.8 | |
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retro | 9.8 | |
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ventilator | 9.6 | |
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radio receiver | 9.4 | |
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number | 9.3 | |
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data | 9.1 | |
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display | 8.9 | |
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memory | 8.9 | |
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information | 8.8 | |
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close | 8.6 | |
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space | 8.5 | |
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camera | 8.5 | |
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design | 8.4 | |
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modern | 8.4 | |
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dark | 8.3 | |
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transportation | 8.1 | |
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bank | 8.1 | |
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photographic equipment | 7.6 | |
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photographic paper | 7.6 | |
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receiver | 7.5 | |
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electronic | 7.5 | |
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safety | 7.4 | |
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banking | 7.3 | |
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telecommunication | 7.3 | |
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object | 7.3 | |
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metal | 7.2 | |
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signboard | 7.2 | |
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instrument | 7.2 | |
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science | 7.1 | |
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web | 7.1 | |
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button | 7 | |
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Google
created on 2022-01-09
Rectangle | 89.3 | |
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Font | 79.3 | |
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Tints and shades | 75.4 | |
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Metal | 65 | |
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Fashion accessory | 63.2 | |
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Brand | 62.9 | |
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Automotive design | 61.9 | |
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Square | 59.2 | |
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Logo | 56.8 | |
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Slope | 54.8 | |
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Monochrome photography | 53 | |
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Automotive lighting | 50.1 | |
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Microsoft
created on 2022-01-09
text | 95.8 | |
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black and white | 87.9 | |
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billboard | 84.4 | |
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screenshot | 77.6 | |
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monochrome | 55.9 | |
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street | 55.5 | |
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Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18789077/348,233,210,234/full/0/native.jpg)
Mobile Phone | 93.7% | |
|
Categories
Imagga
text visuals | 59.3% | |
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interior objects | 19.4% | |
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cars vehicles | 14.9% | |
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food drinks | 4.4% | |
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events parties | 1.1% | |
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Captions
Microsoft
created on 2022-01-09
a sign on the side of a ramp | 56.1% | |
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a person holding a sign | 27.2% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/18789077/396,276,34,21/full/0/native.jpg)
12:09
![](https://ids.lib.harvard.edu/ids/iiif/18789077/440,251,25,13/full/0/native.jpg)
BLUES
![](https://ids.lib.harvard.edu/ids/iiif/18789077/364,283,34,18/full/0/native.jpg)
ISLANDERS
![](https://ids.lib.harvard.edu/ids/iiif/18789077/451,360,15,10/full/0/native.jpg)
-
![](https://ids.lib.harvard.edu/ids/iiif/18789077/398,265,27,15/full/0/native.jpg)
123
![](https://ids.lib.harvard.edu/ids/iiif/18789077/400,330,72,37/full/0/native.jpg)
TOMORROW
![](https://ids.lib.harvard.edu/ids/iiif/18789077/382,296,7,8/full/0/native.jpg)
5
![](https://ids.lib.harvard.edu/ids/iiif/18789077/409,280,34,19/full/0/native.jpg)
SEINO
![](https://ids.lib.harvard.edu/ids/iiif/18789077/378,361,72,49/full/0/native.jpg)
Ropper
![](https://ids.lib.harvard.edu/ids/iiif/18789077/490,340,20,12/full/0/native.jpg)
drink,
![](https://ids.lib.harvard.edu/ids/iiif/18789077/466,359,5,4/full/0/native.jpg)
.
![](https://ids.lib.harvard.edu/ids/iiif/18789077/464,350,26,18/full/0/native.jpg)
If
![](https://ids.lib.harvard.edu/ids/iiif/18789077/440,365,14,9/full/0/native.jpg)
In
![](https://ids.lib.harvard.edu/ids/iiif/18789077/481,346,15,11/full/0/native.jpg)
2m
![](https://ids.lib.harvard.edu/ids/iiif/18789077/369,278,78,135/full/0/native.jpg)
AERS
5 12:09
BEIMO
TOMO
Rpper
![](https://ids.lib.harvard.edu/ids/iiif/18789077/369,286,30,20/full/0/native.jpg)
AERS
![](https://ids.lib.harvard.edu/ids/iiif/18789077/395,288,15,17/full/0/native.jpg)
5
![](https://ids.lib.harvard.edu/ids/iiif/18789077/402,279,31,21/full/0/native.jpg)
12:09
![](https://ids.lib.harvard.edu/ids/iiif/18789077/416,285,26,16/full/0/native.jpg)
BEIMO
![](https://ids.lib.harvard.edu/ids/iiif/18789077/409,347,33,21/full/0/native.jpg)
TOMO
![](https://ids.lib.harvard.edu/ids/iiif/18789077/381,368,66,45/full/0/native.jpg)
Rpper