Machine Generated Data
Tags
Amazon
created on 2019-11-19
Human | 99.6 | |
| ||
Person | 99.6 | |
| ||
Person | 99.6 | |
| ||
Person | 96.5 | |
| ||
Building | 95.6 | |
| ||
Machine | 90.3 | |
| ||
Wheel | 90.3 | |
| ||
Person | 89.5 | |
| ||
Architecture | 87.1 | |
| ||
Person | 83.5 | |
| ||
Person | 79 | |
| ||
Countryside | 77 | |
| ||
Rural | 77 | |
| ||
Nature | 77 | |
| ||
Shelter | 77 | |
| ||
Outdoors | 77 | |
| ||
Transportation | 75.7 | |
| ||
Vehicle | 75.7 | |
| ||
Truck | 75.7 | |
| ||
Urban | 74.7 | |
| ||
Person | 71.8 | |
| ||
Person | 67.4 | |
| ||
City | 66.7 | |
| ||
Town | 66.7 | |
| ||
Car | 63.4 | |
| ||
Automobile | 63.4 | |
| ||
Path | 61.9 | |
| ||
Downtown | 61.7 | |
| ||
Banister | 58 | |
| ||
Handrail | 58 | |
| ||
Amusement Park | 57.9 | |
| ||
Dome | 57.3 | |
| ||
Spoke | 55.2 | |
| ||
Person | 53.8 | |
|
Clarifai
created on 2019-11-19
no person | 97.6 | |
| ||
people | 97.4 | |
| ||
street | 94.6 | |
| ||
monochrome | 93.2 | |
| ||
transportation system | 91.4 | |
| ||
indoors | 88.9 | |
| ||
industry | 88.4 | |
| ||
vehicle | 87.5 | |
| ||
war | 86.7 | |
| ||
outdoors | 85.2 | |
| ||
architecture | 84.4 | |
| ||
city | 84.1 | |
| ||
business | 83.9 | |
| ||
group | 83.3 | |
| ||
travel | 82.6 | |
| ||
dark | 81.6 | |
| ||
steel | 81.5 | |
| ||
group together | 80.9 | |
| ||
many | 80.5 | |
| ||
urban | 78.7 | |
|
Imagga
created on 2019-11-19
cable | 99.8 | |
| ||
structure | 39.7 | |
| ||
wire | 39.3 | |
| ||
steel | 39 | |
| ||
electricity | 38.8 | |
| ||
sky | 38.5 | |
| ||
tower | 37.6 | |
| ||
power | 37 | |
| ||
high | 36.4 | |
| ||
industry | 35.1 | |
| ||
voltage | 31.4 | |
| ||
architecture | 31.1 | |
| ||
line | 31 | |
| ||
energy | 29.5 | |
| ||
industrial | 29.1 | |
| ||
electric | 28.1 | |
| ||
metal | 26.6 | |
| ||
construction | 26.6 | |
| ||
urban | 26.3 | |
| ||
building | 26.2 | |
| ||
city | 25.9 | |
| ||
electrical | 25.9 | |
| ||
pylon | 24.7 | |
| ||
bridge | 22 | |
| ||
tall | 19.8 | |
| ||
cables | 19.6 | |
| ||
lines | 17.1 | |
| ||
station | 16.9 | |
| ||
supply | 15.5 | |
| ||
engineering | 14.3 | |
| ||
transmission | 13.8 | |
| ||
sunset | 13.5 | |
| ||
park | 13.2 | |
| ||
pole | 12.7 | |
| ||
technology | 12.6 | |
| ||
volts | 11.9 | |
| ||
towers | 11.8 | |
| ||
glass | 11.7 | |
| ||
frame | 11.7 | |
| ||
generation | 11.5 | |
| ||
buildings | 11.4 | |
| ||
modern | 11.2 | |
| ||
iron | 11.2 | |
| ||
danger | 10.9 | |
| ||
wires | 10.8 | |
| ||
distribution | 10.8 | |
| ||
generator | 10.8 | |
| ||
current | 10.8 | |
| ||
silhouette | 10.8 | |
| ||
equipment | 10.7 | |
| ||
support | 10.7 | |
| ||
environment | 9.9 | |
| ||
mast | 9.8 | |
| ||
business | 9.7 | |
| ||
factory | 9.7 | |
| ||
dusk | 9.5 | |
| ||
crane | 9.5 | |
| ||
window | 9.5 | |
| ||
network | 9.3 | |
| ||
device | 9.2 | |
| ||
high voltage | 8.9 | |
| ||
pier | 8.9 | |
| ||
tract | 8.8 | |
| ||
grid | 8.7 | |
| ||
fuel | 8.7 | |
| ||
cloud | 8.6 | |
| ||
clouds | 8.5 | |
| ||
old | 8.4 | |
| ||
exterior | 8.3 | |
| ||
plant | 8.2 | |
| ||
landmark | 8.1 | |
| ||
new | 8.1 | |
| ||
transformer | 7.9 | |
| ||
skyscraper | 7.8 | |
| ||
travel | 7.8 | |
| ||
ferris wheel | 7.7 | |
| ||
famous | 7.5 | |
| ||
town | 7.4 | |
| ||
connection | 7.3 | |
| ||
sun | 7.3 | |
| ||
road | 7.2 | |
|
Google
created on 2019-11-19
Black | 95.4 | |
| ||
Black-and-white | 89 | |
| ||
Monochrome | 88.1 | |
| ||
Snapshot | 82 | |
| ||
Architecture | 78.7 | |
| ||
Monochrome photography | 73.3 | |
| ||
Photography | 72.5 | |
| ||
Stock photography | 71.4 | |
| ||
Building | 63.7 | |
| ||
Street | 54.6 | |
| ||
Style | 52.5 | |
| ||
City | 51.3 | |
|
Microsoft
created on 2019-11-19
black and white | 96.2 | |
| ||
outdoor | 94.2 | |
| ||
text | 92.1 | |
| ||
white | 79 | |
| ||
city | 71.5 | |
| ||
street | 70.7 | |
| ||
monochrome | 65.5 | |
| ||
old | 59.7 | |
| ||
sky | 51.4 | |
| ||
billboard | 50.6 | |
|
Color Analysis
Face analysis
Amazon
AWS Rekognition
Age | 8-18 |
Gender | Female, 50% |
Disgusted | 49.5% |
Surprised | 49.6% |
Calm | 50% |
Sad | 49.6% |
Confused | 49.5% |
Fear | 49.5% |
Happy | 49.7% |
Angry | 49.6% |
Feature analysis
Text analysis
Amazon
SOCONY
SOBOL
SOBOL BROS
Telegram
BROS
World
DRUGS
CUT
SODA
CUT RATT
SOCONT
SOCONT VACLUM
RATT
VACLUM
SOBOL BROS
SOCONY
SOCONY
ONY-VACUUM
DRUGS
CUT RATE
SODA
World
Telegram
BRRAL
SOBOL
BROS
SOCONY
ONY-VACUUM
DRUGS
CUT
RATE
SODA
World
Telegram
BRRAL