Machine Generated Data
Tags
Amazon
created on 2022-03-04
Human | 99.4 | |
| ||
Person | 99.4 | |
| ||
Asphalt | 98.8 | |
| ||
Tarmac | 98.8 | |
| ||
Pedestrian | 97.7 | |
| ||
Road | 97 | |
| ||
Automobile | 95.8 | |
| ||
Vehicle | 95.8 | |
| ||
Car | 95.8 | |
| ||
Transportation | 95.8 | |
| ||
Shorts | 95.5 | |
| ||
Clothing | 95.5 | |
| ||
Apparel | 95.5 | |
| ||
Person | 93.4 | |
| ||
Person | 92.1 | |
| ||
Person | 91.2 | |
| ||
Person | 90 | |
| ||
Person | 88.1 | |
| ||
Person | 85.3 | |
| ||
Person | 84 | |
| ||
Car | 81.1 | |
| ||
Intersection | 80.4 | |
| ||
Person | 79 | |
| ||
Person | 72.2 | |
| ||
Person | 72 | |
| ||
Person | 71.3 | |
| ||
People | 70.8 | |
| ||
Person | 69.2 | |
| ||
Path | 64.4 | |
| ||
Machine | 59.8 | |
| ||
Wheel | 59.8 | |
| ||
Wheel | 59.2 | |
| ||
Person | 45.7 | |
|
Imagga
created on 2022-03-04
architecture | 26.9 | |
| ||
travel | 26 | |
| ||
city | 25.8 | |
| ||
building | 22.5 | |
| ||
sky | 21 | |
| ||
urban | 20.1 | |
| ||
water | 19.3 | |
| ||
landscape | 17.1 | |
| ||
sea | 16.4 | |
| ||
road | 16.3 | |
| ||
conveyance | 15.7 | |
| ||
shopping cart | 15.5 | |
| ||
gymnasium | 14.5 | |
| ||
structure | 14.3 | |
| ||
wheeled vehicle | 13.9 | |
| ||
chairlift | 13.7 | |
| ||
river | 13.3 | |
| ||
skyline | 13.3 | |
| ||
tourism | 13.2 | |
| ||
runner | 13.1 | |
| ||
boat | 13 | |
| ||
tourist | 12.8 | |
| ||
tower | 12.5 | |
| ||
ocean | 12.5 | |
| ||
handcart | 12.4 | |
| ||
athlete | 12 | |
| ||
construction | 12 | |
| ||
street | 12 | |
| ||
athletic facility | 11.9 | |
| ||
waterfront | 11.8 | |
| ||
day | 11.8 | |
| ||
landmark | 11.7 | |
| ||
ship | 11.6 | |
| ||
bridge | 11.6 | |
| ||
facility | 11.6 | |
| ||
port | 11.6 | |
| ||
night | 11.5 | |
| ||
business | 11.5 | |
| ||
vacation | 11.5 | |
| ||
cityscape | 11.4 | |
| ||
winter | 11.1 | |
| ||
house | 10.9 | |
| ||
ski tow | 10.9 | |
| ||
transportation | 10.8 | |
| ||
harbor | 10.6 | |
| ||
downtown | 10.6 | |
| ||
office | 10.4 | |
| ||
destination | 10.3 | |
| ||
boats | 9.7 | |
| ||
summer | 9.6 | |
| ||
cloud | 9.5 | |
| ||
light | 9.4 | |
| ||
stage | 9.3 | |
| ||
transport | 9.1 | |
| ||
snow | 9.1 | |
| ||
intersection | 8.8 | |
| ||
highway | 8.7 | |
| ||
platform | 8.5 | |
| ||
buildings | 8.5 | |
| ||
marina | 8.5 | |
| ||
bay | 8.5 | |
| ||
container | 8.4 | |
| ||
modern | 8.4 | |
| ||
town | 8.3 | |
| ||
island | 8.2 | |
| ||
sunset | 8.1 | |
| ||
equipment | 8 | |
| ||
center | 8 | |
| ||
contestant | 7.9 | |
| ||
sail | 7.8 | |
| ||
industry | 7.7 | |
| ||
skyscraper | 7.7 | |
| ||
outdoor | 7.6 | |
| ||
outdoors | 7.6 | |
| ||
evening | 7.5 | |
| ||
pier | 7.4 | |
| ||
new | 7.3 | |
| ||
people | 7.2 | |
| ||
scenic | 7 | |
|
Google
created on 2022-03-04
Black | 89.6 | |
| ||
Line | 82 | |
| ||
Rectangle | 78.8 | |
| ||
Tints and shades | 74.9 | |
| ||
Monochrome photography | 74 | |
| ||
Monochrome | 72.9 | |
| ||
Building | 70.7 | |
| ||
Font | 66.5 | |
| ||
Stock photography | 63.7 | |
| ||
Room | 63 | |
| ||
Paper product | 62.7 | |
| ||
History | 61.2 | |
| ||
Street | 57.2 | |
| ||
Photographic paper | 56.8 | |
| ||
Pole | 56 | |
| ||
Square | 54.2 | |
|
Microsoft
created on 2022-03-04
text | 100 | |
| ||
black and white | 95.4 | |
| ||
car | 85.8 | |
| ||
vehicle | 84.2 | |
| ||
white | 72.9 | |
| ||
sky | 70.1 | |
| ||
black | 65.9 | |
| ||
land vehicle | 53.2 | |
| ||
display | 32.3 | |
| ||
image | 30.2 | |
|
Face analysis
Amazon

AWS Rekognition
Age | 13-21 |
Gender | Female, 75.3% |
Calm | 68.1% |
Fear | 24.9% |
Happy | 2.6% |
Sad | 2.4% |
Surprised | 0.6% |
Angry | 0.6% |
Disgusted | 0.4% |
Confused | 0.4% |
Feature analysis
Captions
Microsoft
a group of people walking in front of a crowd | 78.7% | |
| ||
a group of people standing in front of a crowd | 68.4% | |
| ||
a group of people in front of a crowd | 68.3% | |
|
Text analysis
Amazon

TYDOL

CROSSING

DRUG

LISTEN

NYAL

3

DRESS

C60

DICHLEY'S

DICHLEY'S BEAR C60

BEAR

TYDOL
NYAL
DRUG
3

NYAL

DRUG

3

TYDOL