Machine Generated Data
Tags
Amazon
created on 2022-01-22
Imagga
created on 2022-01-22
wardrobe | 58.2 | |
| ||
furniture | 41.5 | |
| ||
furnishing | 32.7 | |
| ||
boutique | 24.1 | |
| ||
business | 17.6 | |
| ||
hanger | 16.5 | |
| ||
travel | 14.1 | |
| ||
people | 12.3 | |
| ||
coat hanger | 12.1 | |
| ||
water | 12 | |
| ||
interior | 11.5 | |
| ||
store | 11.3 | |
| ||
device | 11.3 | |
| ||
support | 10.9 | |
| ||
train | 10.2 | |
| ||
city | 10 | |
| ||
transportation | 9.8 | |
| ||
equipment | 9.4 | |
| ||
clothing | 9.4 | |
| ||
industry | 9.4 | |
| ||
architecture | 9.4 | |
| ||
clothes | 9.4 | |
| ||
speed | 9.1 | |
| ||
transport | 9.1 | |
| ||
black | 9.1 | |
| ||
shop | 9.1 | |
| ||
landscape | 8.9 | |
| ||
group | 8.9 | |
| ||
urban | 8.7 | |
| ||
journey | 8.5 | |
| ||
row | 8.4 | |
| ||
dark | 8.3 | |
| ||
station | 8.2 | |
| ||
world | 8.2 | |
| ||
tourism | 8.2 | |
| ||
park | 8.2 | |
| ||
railroad | 7.8 | |
| ||
rock | 7.8 | |
| ||
scene | 7.8 | |
| ||
fashion | 7.5 | |
| ||
technology | 7.4 | |
| ||
inside | 7.4 | |
| ||
light | 7.3 | |
| ||
center | 7.3 | |
| ||
suit | 7.2 | |
| ||
women | 7.1 | |
| ||
adult | 7.1 | |
| ||
sky | 7 | |
| ||
modern | 7 | |
|
Google
created on 2022-01-22
Shirt | 94.3 | |
| ||
Coat | 93 | |
| ||
Sleeve | 86.9 | |
| ||
Rectangle | 84.6 | |
| ||
Black-and-white | 84 | |
| ||
Style | 83.8 | |
| ||
Clothes hanger | 79.8 | |
| ||
Font | 76.7 | |
| ||
Tints and shades | 75.8 | |
| ||
Tie | 75.6 | |
| ||
Monochrome photography | 72.4 | |
| ||
Monochrome | 70.5 | |
| ||
Stock photography | 63.3 | |
| ||
Automotive design | 61.6 | |
| ||
Room | 60.6 | |
| ||
Ceiling | 59.8 | |
| ||
T-shirt | 58.5 | |
| ||
Shadow | 56.8 | |
| ||
Public transport | 56 | |
| ||
Sportswear | 55.6 | |
|
Microsoft
created on 2022-01-22
text | 98.3 | |
| ||
black and white | 94.3 | |
| ||
monochrome | 88.8 | |
| ||
clothing | 85.3 | |
| ||
person | 78.5 | |
| ||
street | 72.3 | |
| ||
man | 71.4 | |
|
Face analysis
Amazon

AWS Rekognition
Age | 45-51 |
Gender | Male, 99.4% |
Calm | 89.8% |
Happy | 6% |
Sad | 3.2% |
Confused | 0.3% |
Disgusted | 0.3% |
Surprised | 0.2% |
Angry | 0.1% |
Fear | 0.1% |

Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very unlikely |
Feature analysis
Amazon

Person | 97.9% | |
|
Captions
Microsoft
a person sitting at a train station | 27.9% | |
|
Text analysis
Amazon

MILDEW

MILDEW PROOF

PROOF

MOTHPROOF

CLEANING

ALSO

MOTH

BETWEEN

BUILT-IN

EXTRA

ALSO MOTH MILDEWPROOFED

COMBATS

AT

CLEANINGS

ALL AT

ALL

NO

ATION

MILDEWPROOFED

COMBATS PERSPIR ATION ODORS BETWEEN CLEANINGS

NO EXTRA COST

BUILT-IN DEODORANT

ODORS

PERSPIR

COST

DEODORANT

GARMENTS

BAKE A

CLEANES BY 25

MILDEW PROOF
CLEANING
MOTHPROOF
MILDEW PROOF
TUILT-IN DEODORANT
CLEANING
WEL
COMBATS PERSBAION ODONUN G
MOTHPROOF
ALSO MOTH MILDEWPROOFED ALLAT
NO EXTRA COIT
MJI7--YT37A'2 -- XAGO

MILDEW

PROOF

CLEANING

MOTHPROOF

TUILT-IN

DEODORANT

WEL

COMBATS

PERSBAION

ODONUN

G

ALSO

MOTH

MILDEWPROOFED

ALLAT

NO

EXTRA

COIT

MJI7--YT37A'2

--

XAGO