Machine Generated Data
Tags
Amazon
created on 2019-06-05
Person | 98.2 | |
| ||
Human | 98.2 | |
| ||
Transportation | 97.6 | |
| ||
Vehicle | 97.6 | |
| ||
Train | 97.6 | |
| ||
Person | 97.3 | |
| ||
Train Track | 92.8 | |
| ||
Rail | 92.8 | |
| ||
Railway | 92.8 | |
| ||
Clothing | 82.7 | |
| ||
Apparel | 82.7 | |
| ||
Wood | 78.8 | |
| ||
Shipping Container | 75.2 | |
| ||
Hardhat | 65.6 | |
| ||
Helmet | 65.6 | |
| ||
Construction | 61.9 | |
| ||
Worker | 57.3 | |
| ||
Freight Car | 55.6 | |
|
Clarifai
created on 2019-06-05
people | 99.9 | |
| ||
vehicle | 99.6 | |
| ||
transportation system | 99.6 | |
| ||
adult | 99.5 | |
| ||
railway | 99.4 | |
| ||
train | 98.9 | |
| ||
one | 98.1 | |
| ||
group | 96.1 | |
| ||
war | 96 | |
| ||
man | 95.6 | |
| ||
military | 95.1 | |
| ||
two | 93.6 | |
| ||
administration | 91.8 | |
| ||
wear | 90.7 | |
| ||
group together | 90.4 | |
| ||
weapon | 90.2 | |
| ||
three | 89.4 | |
| ||
soldier | 89.2 | |
| ||
interaction | 87.6 | |
| ||
wagon | 87.2 | |
|
Imagga
created on 2019-06-05
ship | 33.4 | |
| ||
vessel | 27.8 | |
| ||
boat | 24.1 | |
| ||
old | 21.6 | |
| ||
water | 20 | |
| ||
sky | 19.1 | |
| ||
transportation | 18.8 | |
| ||
sea | 18.8 | |
| ||
industrial | 18.2 | |
| ||
submarine | 18 | |
| ||
industry | 17.1 | |
| ||
transport | 16.4 | |
| ||
wreck | 16.2 | |
| ||
travel | 15.5 | |
| ||
vehicle | 15.2 | |
| ||
submersible | 14.7 | |
| ||
broom | 14.6 | |
| ||
harbor | 13.5 | |
| ||
ocean | 13.3 | |
| ||
cleaning implement | 12.9 | |
| ||
construction | 12.8 | |
| ||
building | 12.8 | |
| ||
dock | 12.6 | |
| ||
beach | 11.9 | |
| ||
landscape | 11.9 | |
| ||
sand | 11.7 | |
| ||
wood | 11.7 | |
| ||
port | 11.6 | |
| ||
warship | 11.5 | |
| ||
power | 10.9 | |
| ||
machine | 10.9 | |
| ||
steel | 10.6 | |
| ||
wooden | 10.5 | |
| ||
rope | 10.3 | |
| ||
equipment | 10.3 | |
| ||
coast | 9.9 | |
| ||
nautical | 9.7 | |
| ||
outdoors | 9.7 | |
| ||
metal | 9.7 | |
| ||
weathered | 9.5 | |
| ||
structure | 9.5 | |
| ||
architecture | 9.4 | |
| ||
winter | 9.4 | |
| ||
shore | 9.3 | |
| ||
factory | 9.3 | |
| ||
device | 9.2 | |
| ||
fisherman | 9.1 | |
| ||
vintage | 9.1 | |
| ||
river | 8.9 | |
| ||
work | 8.8 | |
| ||
sail | 8.7 | |
| ||
boats | 8.7 | |
| ||
cargo | 8.7 | |
| ||
scene | 8.7 | |
| ||
fishing | 8.7 | |
| ||
cloud | 8.6 | |
| ||
heavy | 8.6 | |
| ||
energy | 8.4 | |
| ||
track | 8.3 | |
| ||
vacation | 8.2 | |
| ||
wheeled vehicle | 8.1 | |
| ||
history | 8 | |
| ||
business | 7.9 | |
| ||
railroad | 7.9 | |
| ||
maritime | 7.9 | |
| ||
black | 7.8 | |
| ||
antique | 7.8 | |
| ||
cold | 7.7 | |
| ||
summer | 7.7 | |
| ||
outdoor | 7.6 | |
| ||
rusty | 7.6 | |
| ||
military vehicle | 7.6 | |
| ||
car | 7.5 | |
| ||
tourism | 7.4 | |
| ||
man | 7.4 | |
| ||
rural | 7 | |
|
Google
created on 2019-06-05
Color Analysis
Face analysis
Amazon
AWS Rekognition
Age | 19-36 |
Gender | Female, 51.2% |
Sad | 47.8% |
Happy | 45.1% |
Surprised | 45.2% |
Disgusted | 45.3% |
Angry | 45.9% |
Calm | 50.6% |
Confused | 45.2% |
Feature analysis
Text analysis
Amazon
US E
6
C&E
7795
C&E
7795