Machine Generated Data
Tags
Amazon
created on 2023-10-06
Car | 98.8 | |
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Transportation | 98.8 | |
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Vehicle | 98.8 | |
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Car | 98.4 | |
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Machine | 98.4 | |
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Spoke | 98.4 | |
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Wheel | 98.2 | |
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Car | 98.1 | |
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Wheel | 97.3 | |
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Person | 97.1 | |
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Wheel | 95.7 | |
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Wheel | 92.5 | |
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Wheel | 92.1 | |
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Wheel | 91.6 | |
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Architecture | 90.4 | |
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Building | 90.4 | |
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Factory | 90.4 | |
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Antique Car | 90.3 | |
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Model T | 88.8 | |
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Car | 87.6 | |
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Wheel | 85.4 | |
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Alloy Wheel | 81.7 | |
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Car Wheel | 81.7 | |
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Tire | 81.7 | |
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Wheel | 80.7 | |
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Hot Rod | 77.8 | |
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Wheel | 77.1 | |
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Person | 76.6 | |
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Wheel | 69.5 | |
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Person | 65.3 | |
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City | 57.6 | |
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Road | 57.2 | |
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Street | 57.2 | |
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Urban | 57.2 | |
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Car Dealership | 57.1 | |
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Manufacturing | 57.1 | |
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Sedan | 56.8 | |
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Indoors | 56.7 | |
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Coupe | 56.7 | |
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Sports Car | 56.7 | |
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License Plate | 55.2 | |
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Clarifai
created on 2018-05-11
vehicle | 99.9 | |
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transportation system | 99.8 | |
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car | 99.6 | |
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people | 97.1 | |
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driver | 96.3 | |
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group together | 95.1 | |
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monochrome | 92.5 | |
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street | 91.8 | |
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road | 89.9 | |
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nostalgia | 89.4 | |
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retro | 89.1 | |
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traffic | 89 | |
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engine | 85.4 | |
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truck | 85.2 | |
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vintage | 85.1 | |
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convertible | 85 | |
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many | 82.1 | |
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adult | 82.1 | |
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man | 80.6 | |
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travel | 80.2 | |
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Imagga
created on 2023-10-06
car | 100 | |
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motor vehicle | 76.3 | |
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auto | 49.8 | |
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truck | 49.3 | |
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vehicle | 48.5 | |
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automobile | 43.1 | |
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transportation | 43.1 | |
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tire | 42.9 | |
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model t | 40.5 | |
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drive | 35 | |
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road | 34.3 | |
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wheel | 33 | |
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tow truck | 32.8 | |
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transport | 32 | |
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wheeled vehicle | 26.3 | |
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speed | 24.7 | |
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motor | 23.2 | |
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hoop | 21.4 | |
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driving | 20.3 | |
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traffic | 18.1 | |
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cars | 16.6 | |
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engine | 16.4 | |
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limousine | 16.2 | |
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fast | 15.9 | |
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band | 15.8 | |
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travel | 15.5 | |
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old | 15.3 | |
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street | 14.7 | |
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luxury | 14.6 | |
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bumper | 13.6 | |
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wheels | 12.7 | |
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machine | 12.2 | |
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classic | 12.1 | |
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parked | 11.8 | |
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sport | 11.5 | |
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garage | 11.3 | |
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sports | 11.1 | |
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power | 10.9 | |
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vintage | 10.8 | |
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retro | 10.7 | |
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expensive | 10.5 | |
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strip | 10.5 | |
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antique | 10.4 | |
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motion | 10.3 | |
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black | 10.2 | |
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design | 10.1 | |
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roadster | 9.9 | |
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headlight | 9.8 | |
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hood | 9.8 | |
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rural | 9.7 | |
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style | 9.6 | |
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highway | 9.6 | |
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urban | 9.6 | |
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sky | 9.6 | |
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light | 9.4 | |
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model | 9.3 | |
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city | 9.1 | |
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parking | 8.9 | |
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driver | 8.7 | |
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trailer truck | 8.7 | |
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broken | 8.7 | |
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show | 8.5 | |
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chrome | 8.5 | |
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modern | 8.4 | |
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sedan | 8.4 | |
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tires | 7.9 | |
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wreck | 7.9 | |
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automotive | 7.9 | |
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accident | 7.8 | |
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ride | 7.8 | |
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stop | 7.7 | |
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race | 7.6 | |
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outdoors | 7.5 | |
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racer | 7.4 | |
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metal | 7.2 | |
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trailer | 7.2 | |
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sports car | 7.2 | |
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shiny | 7.1 | |
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Google
created on 2018-05-11
car | 98.6 | |
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motor vehicle | 98 | |
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vehicle | 95.4 | |
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vintage car | 90.6 | |
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black and white | 85.1 | |
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automotive design | 79.3 | |
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classic | 79 | |
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automotive exterior | 66 | |
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monochrome photography | 63.1 | |
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compact car | 61.8 | |
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classic car | 53 | |
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Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/43158641/910,364,10,14/full/0/native.jpg)
AWS Rekognition
Age | 2-10 |
Gender | Male, 99.8% |
Angry | 34.8% |
Calm | 30.8% |
Happy | 14.8% |
Disgusted | 12.4% |
Surprised | 7.3% |
Fear | 6.3% |
Sad | 3.1% |
Confused | 1.3% |
Feature analysis
Categories
Imagga
paintings art | 68.3% | |
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cars vehicles | 31.3% | |
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Captions
Microsoft
created on 2018-05-11
a white and black truck parked in front of a car | 73.2% | |
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a white and black truck parked in front of a building | 73.1% | |
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a white and black truck parked in a parking lot | 73% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/43158641/791,141,116,50/full/0/native.jpg)
CREAM
![](https://ids.lib.harvard.edu/ids/iiif/43158641/384,173,69,42/full/0/native.jpg)
25
![](https://ids.lib.harvard.edu/ids/iiif/43158641/736,141,171,52/full/0/native.jpg)
ICE CREAM
![](https://ids.lib.harvard.edu/ids/iiif/43158641/737,163,46,26/full/0/native.jpg)
ICE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/722,139,54,20/full/0/native.jpg)
HOME
![](https://ids.lib.harvard.edu/ids/iiif/43158641/604,100,95,40/full/0/native.jpg)
LONDON
![](https://ids.lib.harvard.edu/ids/iiif/43158641/775,137,54,20/full/0/native.jpg)
MADE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/311,32,41,25/full/0/native.jpg)
Bread
![](https://ids.lib.harvard.edu/ids/iiif/43158641/150,160,66,17/full/0/native.jpg)
STORE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/278,178,77,33/full/0/native.jpg)
WILDMANS
![](https://ids.lib.harvard.edu/ids/iiif/43158641/287,127,248,50/full/0/native.jpg)
WILDMAN'S
![](https://ids.lib.harvard.edu/ids/iiif/43158641/299,31,53,26/full/0/native.jpg)
in Bread
![](https://ids.lib.harvard.edu/ids/iiif/43158641/308,10,59,33/full/0/native.jpg)
Difference
![](https://ids.lib.harvard.edu/ids/iiif/43158641/300,33,14,17/full/0/native.jpg)
in
![](https://ids.lib.harvard.edu/ids/iiif/43158641/383,161,176,60/full/0/native.jpg)
25 $100
![](https://ids.lib.harvard.edu/ids/iiif/43158641/19,164,63,16/full/0/native.jpg)
ONDON
![](https://ids.lib.harvard.edu/ids/iiif/43158641/283,214,32,15/full/0/native.jpg)
EVERYTHING
![](https://ids.lib.harvard.edu/ids/iiif/43158641/633,343,23,5/full/0/native.jpg)
COFFEE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/598,155,60,36/full/0/native.jpg)
CAND
![](https://ids.lib.harvard.edu/ids/iiif/43158641/380,475,29,22/full/0/native.jpg)
5582
![](https://ids.lib.harvard.edu/ids/iiif/43158641/300,18,8,12/full/0/native.jpg)
a
![](https://ids.lib.harvard.edu/ids/iiif/43158641/19,160,197,21/full/0/native.jpg)
ONDON DEP'T. STORE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/443,162,116,58/full/0/native.jpg)
$100
![](https://ids.lib.harvard.edu/ids/iiif/43158641/812,336,40,10/full/0/native.jpg)
HOME MADE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/665,136,165,24/full/0/native.jpg)
PURE HOME MADE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/89,162,55,17/full/0/native.jpg)
DEP'T.
![](https://ids.lib.harvard.edu/ids/iiif/43158641/613,342,43,6/full/0/native.jpg)
GOOD COFFEE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/604,88,299,56/full/0/native.jpg)
LONDON CANDY KITCHEN
![](https://ids.lib.harvard.edu/ids/iiif/43158641/613,342,17,6/full/0/native.jpg)
GOOD
![](https://ids.lib.harvard.edu/ids/iiif/43158641/699,88,205,52/full/0/native.jpg)
CANDY KITCHEN
![](https://ids.lib.harvard.edu/ids/iiif/43158641/666,141,56,20/full/0/native.jpg)
PURE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/258,3,109,39/full/0/native.jpg)
oney a Difference
![](https://ids.lib.harvard.edu/ids/iiif/43158641/281,198,71,26/full/0/native.jpg)
510 25 F STORE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/298,201,32,20/full/0/native.jpg)
25 F
![](https://ids.lib.harvard.edu/ids/iiif/43158641/283,214,65,20/full/0/native.jpg)
EVERYTHING FOR
![](https://ids.lib.harvard.edu/ids/iiif/43158641/192,263,9,8/full/0/native.jpg)
S
![](https://ids.lib.harvard.edu/ids/iiif/43158641/241,260,19,10/full/0/native.jpg)
use
![](https://ids.lib.harvard.edu/ids/iiif/43158641/794,429,26,15/full/0/native.jpg)
Y-5278
![](https://ids.lib.harvard.edu/ids/iiif/43158641/281,199,22,16/full/0/native.jpg)
510
![](https://ids.lib.harvard.edu/ids/iiif/43158641/45,261,13,8/full/0/native.jpg)
LU
![](https://ids.lib.harvard.edu/ids/iiif/43158641/21,261,37,8/full/0/native.jpg)
ONOS LU
![](https://ids.lib.harvard.edu/ids/iiif/43158641/21,261,14,7/full/0/native.jpg)
ONOS
![](https://ids.lib.harvard.edu/ids/iiif/43158641/534,414,28,15/full/0/native.jpg)
176530
![](https://ids.lib.harvard.edu/ids/iiif/43158641/124,266,27,8/full/0/native.jpg)
STCA
![](https://ids.lib.harvard.edu/ids/iiif/43158641/259,11,42,18/full/0/native.jpg)
oney
![](https://ids.lib.harvard.edu/ids/iiif/43158641/315,221,8,8/full/0/native.jpg)
FOR
![](https://ids.lib.harvard.edu/ids/iiif/43158641/235,284,29,9/full/0/native.jpg)
DONOR
![](https://ids.lib.harvard.edu/ids/iiif/43158641/22,33,889,156/full/0/native.jpg)
n Bread
LONDON CANDY KITCHEN.
DIRE HOMEMADE
CHIOON DEP T. STOREWILDMAN'S
![](https://ids.lib.harvard.edu/ids/iiif/43158641/302,33,12,24/full/0/native.jpg)
n
![](https://ids.lib.harvard.edu/ids/iiif/43158641/315,34,38,27/full/0/native.jpg)
Bread
![](https://ids.lib.harvard.edu/ids/iiif/43158641/607,102,98,42/full/0/native.jpg)
LONDON
![](https://ids.lib.harvard.edu/ids/iiif/43158641/704,97,92,43/full/0/native.jpg)
CANDY
![](https://ids.lib.harvard.edu/ids/iiif/43158641/796,93,109,44/full/0/native.jpg)
KITCHEN
![](https://ids.lib.harvard.edu/ids/iiif/43158641/902,93,9,15/full/0/native.jpg)
.
![](https://ids.lib.harvard.edu/ids/iiif/43158641/668,142,55,23/full/0/native.jpg)
DIRE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/727,137,106,26/full/0/native.jpg)
HOMEMADE
![](https://ids.lib.harvard.edu/ids/iiif/43158641/22,140,62,49/full/0/native.jpg)
CHIOON
![](https://ids.lib.harvard.edu/ids/iiif/43158641/93,139,34,48/full/0/native.jpg)
DEP
![](https://ids.lib.harvard.edu/ids/iiif/43158641/130,139,19,47/full/0/native.jpg)
T.
![](https://ids.lib.harvard.edu/ids/iiif/43158641/152,127,380,58/full/0/native.jpg)
STOREWILDMAN'S