Machine Generated Data
Tags
Amazon
created on 2019-06-17
Road | 99.4 | |
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Asphalt | 98.9 | |
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Tarmac | 98.9 | |
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Vehicle | 98.4 | |
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Transportation | 98.4 | |
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Car | 98.4 | |
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Automobile | 98.4 | |
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Human | 98.1 | |
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Person | 98.1 | |
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Intersection | 98.1 | |
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Car | 97.1 | |
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Car | 95.3 | |
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Car | 94.9 | |
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Person | 94.7 | |
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Car | 92.7 | |
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Car | 91.3 | |
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Person | 89.2 | |
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Machine | 85.5 | |
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Wheel | 85.5 | |
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Urban | 73.2 | |
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Building | 72 | |
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Car | 65.6 | |
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Freeway | 65.5 | |
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Highway | 65 | |
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Car | 57.7 | |
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City | 57.5 | |
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Town | 57.5 | |
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Wheel | 56 | |
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Sports Car | 55.9 | |
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Street | 55.1 | |
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Person | 54.5 | |
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Clarifai
created on 2019-06-17
Imagga
created on 2019-06-17
Google
created on 2019-06-17
White | 95.9 | |
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Photograph | 95.8 | |
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Black-and-white | 89 | |
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Snapshot | 85.1 | |
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Photography | 78.4 | |
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Monochrome | 75.8 | |
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Architecture | 65.5 | |
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Monochrome photography | 57.8 | |
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Street | 54.6 | |
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Style | 51 | |
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Rectangle | 50.5 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20414403/871,394,9,11/full/0/native.jpg)
AWS Rekognition
Age | 26-43 |
Gender | Female, 50% |
Sad | 49.7% |
Happy | 49.6% |
Disgusted | 49.7% |
Confused | 49.6% |
Angry | 49.6% |
Calm | 49.7% |
Surprised | 49.6% |
Feature analysis
Categories
Imagga
cars vehicles | 85.9% | |
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nature landscape | 9.9% | |
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beaches seaside | 2.2% | |
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streetview architecture | 1.2% | |
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Captions
Microsoft
created on 2019-06-17
a vintage photo of a street | 85.1% | |
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a vintage photo of a building | 83.6% | |
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a vintage photo of a city street | 80.8% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/20414403/711,339,44,17/full/0/native.jpg)
Mobiloil
![](https://ids.lib.harvard.edu/ids/iiif/20414403/776,443,29,25/full/0/native.jpg)
30
![](https://ids.lib.harvard.edu/ids/iiif/20414403/950,322,24,29/full/0/native.jpg)
P
![](https://ids.lib.harvard.edu/ids/iiif/20414403/599,339,55,18/full/0/native.jpg)
Magnolia
![](https://ids.lib.harvard.edu/ids/iiif/20414403/467,341,506,29/full/0/native.jpg)
Mobilubrication Magnolia Mobiloil P
![](https://ids.lib.harvard.edu/ids/iiif/20414403/930,357,30,19/full/0/native.jpg)
ICE
![](https://ids.lib.harvard.edu/ids/iiif/20414403/929,356,56,21/full/0/native.jpg)
ICE CR
![](https://ids.lib.harvard.edu/ids/iiif/20414403/961,355,25,19/full/0/native.jpg)
CR
![](https://ids.lib.harvard.edu/ids/iiif/20414403/775,439,83,29/full/0/native.jpg)
30 CLEAN ROOMS
![](https://ids.lib.harvard.edu/ids/iiif/20414403/468,350,65,12/full/0/native.jpg)
Mobilubrication
![](https://ids.lib.harvard.edu/ids/iiif/20414403/820,438,29,15/full/0/native.jpg)
CLEAN
![](https://ids.lib.harvard.edu/ids/iiif/20414403/832,453,27,12/full/0/native.jpg)
ROOMS
![](https://ids.lib.harvard.edu/ids/iiif/20414403/604,298,32,35/full/0/native.jpg)
T
![](https://ids.lib.harvard.edu/ids/iiif/20414403/19,364,0,0/full/0/native.jpg)
w:
![](https://ids.lib.harvard.edu/ids/iiif/20414403/472,341,521,130/full/0/native.jpg)
Magnolia
Mobiloil
Mebilubrication
ICE CR
MALYS
APP
30 REST ROOMS
![](https://ids.lib.harvard.edu/ids/iiif/20414403/606,341,50,20/full/0/native.jpg)
Magnolia
![](https://ids.lib.harvard.edu/ids/iiif/20414403/714,343,44,19/full/0/native.jpg)
Mobiloil
![](https://ids.lib.harvard.edu/ids/iiif/20414403/472,349,65,19/full/0/native.jpg)
Mebilubrication
![](https://ids.lib.harvard.edu/ids/iiif/20414403/922,359,39,22/full/0/native.jpg)
ICE
![](https://ids.lib.harvard.edu/ids/iiif/20414403/966,358,27,24/full/0/native.jpg)
CR
![](https://ids.lib.harvard.edu/ids/iiif/20414403/959,386,26,15/full/0/native.jpg)
MALYS
![](https://ids.lib.harvard.edu/ids/iiif/20414403/819,431,32,16/full/0/native.jpg)
APP
![](https://ids.lib.harvard.edu/ids/iiif/20414403/771,452,36,19/full/0/native.jpg)
30
![](https://ids.lib.harvard.edu/ids/iiif/20414403/814,452,24,19/full/0/native.jpg)
REST
![](https://ids.lib.harvard.edu/ids/iiif/20414403/836,453,25,18/full/0/native.jpg)
ROOMS