Machine Generated Data
Tags
Amazon
created on 2019-04-05
Clarifai
created on 2018-03-22
people | 99.7 | |
| ||
military | 99.1 | |
| ||
war | 99 | |
| ||
vehicle | 98.5 | |
| ||
soldier | 98.3 | |
| ||
adult | 97.9 | |
| ||
man | 96.5 | |
| ||
group together | 95.6 | |
| ||
transportation system | 95.5 | |
| ||
skirmish | 92.9 | |
| ||
two | 92.7 | |
| ||
military vehicle | 92.6 | |
| ||
group | 91.7 | |
| ||
one | 90.6 | |
| ||
weapon | 88.6 | |
| ||
army | 88.1 | |
| ||
military uniform | 87.9 | |
| ||
uniform | 87.5 | |
| ||
gun | 87.4 | |
| ||
woman | 86.2 | |
|
Imagga
created on 2018-03-22
Google
created on 2018-03-22
black and white | 92.6 | |
| ||
monochrome photography | 82.5 | |
| ||
dust | 79.4 | |
| ||
vehicle | 75.8 | |
| ||
fog | 72.7 | |
| ||
monochrome | 66.6 | |
| ||
sand | 59.7 | |
| ||
motor vehicle | 57.5 | |
| ||
stock photography | 56.1 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/16084301/176,232,14,19/full/0/native.jpg)
AWS Rekognition
Age | 26-43 |
Gender | Female, 50.5% |
Sad | 49.6% |
Calm | 50% |
Happy | 49.6% |
Confused | 49.6% |
Angry | 49.5% |
Disgusted | 49.5% |
Surprised | 49.6% |
Feature analysis
Categories
Imagga
paintings art | 80.8% | |
| ||
streetview architecture | 9.5% | |
| ||
nature landscape | 8.9% | |
| ||
beaches seaside | 0.6% | |
| ||
pets animals | 0.1% | |
|
Captions
Microsoft
created on 2018-03-22
an old photo of a truck | 64.3% | |
| ||
a group of people in a vehicle | 44.5% | |
| ||
a group of people sitting at a vehicle | 36.7% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/16084301/13,724,41,18/full/0/native.jpg)
Aye,
![](https://ids.lib.harvard.edu/ids/iiif/16084301/44,695,51,15/full/0/native.jpg)
gemes
![](https://ids.lib.harvard.edu/ids/iiif/16084301/44,708,52,15/full/0/native.jpg)
Thuons:
![](https://ids.lib.harvard.edu/ids/iiif/16084301/12,724,125,20/full/0/native.jpg)
Aye, r4 /970
![](https://ids.lib.harvard.edu/ids/iiif/16084301/10,694,85,15/full/0/native.jpg)
War gemes
![](https://ids.lib.harvard.edu/ids/iiif/16084301/57,724,34,16/full/0/native.jpg)
r4
![](https://ids.lib.harvard.edu/ids/iiif/16084301/865,692,59,16/full/0/native.jpg)
Bebaw
![](https://ids.lib.harvard.edu/ids/iiif/16084301/10,695,28,12/full/0/native.jpg)
War
![](https://ids.lib.harvard.edu/ids/iiif/16084301/170,704,45,17/full/0/native.jpg)
mLin
![](https://ids.lib.harvard.edu/ids/iiif/16084301/126,708,42,19/full/0/native.jpg)
square
![](https://ids.lib.harvard.edu/ids/iiif/16084301/865,690,133,22/full/0/native.jpg)
Bebaw Nyeet
![](https://ids.lib.harvard.edu/ids/iiif/16084301/98,722,39,13/full/0/native.jpg)
/970
![](https://ids.lib.harvard.edu/ids/iiif/16084301/933,692,64,21/full/0/native.jpg)
Nyeet
![](https://ids.lib.harvard.edu/ids/iiif/16084301/10,704,204,25/full/0/native.jpg)
It Thuons: /8 square mLin
![](https://ids.lib.harvard.edu/ids/iiif/16084301/103,710,18,12/full/0/native.jpg)
/8
![](https://ids.lib.harvard.edu/ids/iiif/16084301/11,708,28,11/full/0/native.jpg)
It
![](https://ids.lib.harvard.edu/ids/iiif/16084301/80,701,16,11/full/0/native.jpg)
es
![](https://ids.lib.harvard.edu/ids/iiif/16084301/80,701,16,11/full/0/native.jpg)
es