Machine Generated Data
Tags
Amazon
created on 2022-01-08
Clarifai
created on 2023-10-25
negative | 99.9 | |
| ||
movie | 99.7 | |
| ||
filmstrip | 99.2 | |
| ||
photograph | 99 | |
| ||
slide | 98.4 | |
| ||
noisy | 98.1 | |
| ||
art | 97.6 | |
| ||
people | 97.1 | |
| ||
exposed | 96.9 | |
| ||
cinematography | 96.8 | |
| ||
window | 96.6 | |
| ||
collage | 96.6 | |
| ||
analogue | 96.5 | |
| ||
street | 95.8 | |
| ||
monochrome | 95.4 | |
| ||
old | 95.1 | |
| ||
vintage | 94.8 | |
| ||
architecture | 94 | |
| ||
city | 93.8 | |
| ||
rust | 91.6 | |
|
Imagga
created on 2022-01-08
equipment | 82.1 | |
| ||
electronic equipment | 69 | |
| ||
amplifier | 45.2 | |
| ||
sequencer | 41.4 | |
| ||
apparatus | 34.6 | |
| ||
technology | 21.5 | |
| ||
equalizer | 20.8 | |
| ||
film | 19.6 | |
| ||
digital | 18.6 | |
| ||
computer | 16.8 | |
| ||
radio receiver | 15.8 | |
| ||
network | 15.7 | |
| ||
old | 15.3 | |
| ||
sound | 15 | |
| ||
retro | 14.7 | |
| ||
receiver | 14.5 | |
| ||
negative | 14 | |
| ||
music | 13.5 | |
| ||
business | 13.4 | |
| ||
data | 12.8 | |
| ||
grunge | 12.8 | |
| ||
cinema | 12.7 | |
| ||
device | 12.6 | |
| ||
strip | 12.6 | |
| ||
movie | 12.6 | |
| ||
audio | 12.4 | |
| ||
black | 12 | |
| ||
entertainment | 12 | |
| ||
industry | 11.9 | |
| ||
vintage | 11.6 | |
| ||
synthesizer | 11 | |
| ||
connection | 11 | |
| ||
board | 10.8 | |
| ||
filmstrip | 10.8 | |
| ||
set | 10.7 | |
| ||
hardware | 10.6 | |
| ||
art | 10.4 | |
| ||
close | 10.3 | |
| ||
camera | 10.2 | |
| ||
frame | 10 | |
| ||
switch | 9.8 | |
| ||
noise | 9.8 | |
| ||
information | 9.7 | |
| ||
office | 9.6 | |
| ||
cable | 9.5 | |
| ||
object | 9.5 | |
| ||
border | 9 | |
| ||
texture | 9 | |
| ||
radio | 8.8 | |
| ||
electronic instrument | 8.8 | |
| ||
slide | 8.8 | |
| ||
antique | 8.6 | |
| ||
control | 8.6 | |
| ||
electronics | 8.5 | |
| ||
card | 8.5 | |
| ||
electronic | 8.4 | |
| ||
server | 8.1 | |
| ||
graphic | 8 | |
| ||
design | 7.9 | |
| ||
paper | 7.8 | |
| ||
scratch | 7.8 | |
| ||
tape | 7.8 | |
| ||
video | 7.7 | |
| ||
screen | 7.7 | |
| ||
finance | 7.6 | |
| ||
room | 7.3 | |
| ||
dirty | 7.2 | |
|
Google
created on 2022-01-08
Window | 88.1 | |
| ||
Rectangle | 87.6 | |
| ||
Font | 81.1 | |
| ||
Photographic film | 80.7 | |
| ||
Tints and shades | 73.9 | |
| ||
Art | 67.5 | |
| ||
Room | 67 | |
| ||
History | 66.5 | |
| ||
Negative | 65.8 | |
| ||
Monochrome photography | 64.8 | |
| ||
Display device | 64.6 | |
| ||
Monochrome | 62.1 | |
| ||
Facade | 60.2 | |
| ||
Square | 59.9 | |
| ||
Visual arts | 58.2 | |
| ||
Photographic paper | 56.8 | |
| ||
Glass | 53.6 | |
| ||
Paper product | 52 | |
|
Microsoft
created on 2022-01-08
text | 99.6 | |
| ||
screenshot | 96.4 | |
| ||
vending machine | 13.5 | |
| ||
kitchen appliance | 10.5 | |
|
Color Analysis
Face analysis
Amazon

AWS Rekognition
Age | 23-33 |
Gender | Male, 100% |
Calm | 70.1% |
Sad | 13% |
Angry | 5.2% |
Confused | 4.2% |
Happy | 3.5% |
Surprised | 1.4% |
Disgusted | 1.4% |
Fear | 1.2% |

AWS Rekognition
Age | 36-44 |
Gender | Male, 99.4% |
Disgusted | 50.1% |
Calm | 14.3% |
Sad | 12.1% |
Angry | 6.2% |
Fear | 5.4% |
Surprised | 4.5% |
Confused | 4.2% |
Happy | 3.2% |

AWS Rekognition
Age | 28-38 |
Gender | Male, 99.4% |
Sad | 50.5% |
Calm | 37.4% |
Happy | 7.5% |
Confused | 1.4% |
Angry | 1.3% |
Disgusted | 0.9% |
Fear | 0.8% |
Surprised | 0.3% |

AWS Rekognition
Age | 20-28 |
Gender | Male, 99.4% |
Calm | 58.1% |
Sad | 20.9% |
Angry | 8.6% |
Confused | 7.4% |
Disgusted | 1.9% |
Happy | 1.6% |
Surprised | 0.8% |
Fear | 0.6% |

AWS Rekognition
Age | 19-27 |
Gender | Female, 63.6% |
Calm | 57.1% |
Sad | 15.5% |
Happy | 14.3% |
Fear | 5.4% |
Confused | 3.7% |
Surprised | 1.4% |
Angry | 1.3% |
Disgusted | 1.3% |

AWS Rekognition
Age | 24-34 |
Gender | Female, 54.1% |
Calm | 90.4% |
Sad | 9.2% |
Confused | 0.1% |
Happy | 0.1% |
Disgusted | 0.1% |
Fear | 0% |
Angry | 0% |
Surprised | 0% |

AWS Rekognition
Age | 6-12 |
Gender | Female, 63.8% |
Calm | 94% |
Happy | 4.9% |
Sad | 0.7% |
Fear | 0.1% |
Disgusted | 0.1% |
Angry | 0.1% |
Confused | 0.1% |
Surprised | 0.1% |

AWS Rekognition
Age | 28-38 |
Gender | Male, 98.7% |
Calm | 36.3% |
Happy | 36% |
Disgusted | 7.1% |
Sad | 6.6% |
Angry | 6.4% |
Fear | 3.5% |
Surprised | 2.3% |
Confused | 1.7% |

AWS Rekognition
Age | 25-35 |
Gender | Female, 65.7% |
Calm | 62.1% |
Surprised | 10.9% |
Sad | 8.8% |
Happy | 7.4% |
Fear | 3.9% |
Angry | 3.4% |
Disgusted | 1.9% |
Confused | 1.7% |

AWS Rekognition
Age | 18-26 |
Gender | Male, 90% |
Calm | 92.9% |
Sad | 2.5% |
Confused | 1.2% |
Fear | 1% |
Disgusted | 0.8% |
Angry | 0.6% |
Happy | 0.5% |
Surprised | 0.4% |

Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very likely |

Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very unlikely |

Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very unlikely |
Feature analysis
Categories
Imagga
cars vehicles | 59.4% | |
| ||
interior objects | 39.9% | |
|
Captions
Microsoft
created on 2022-01-08
graphical user interface | 53.8% | |
|
Text analysis
Amazon

FILM

PRIM

32

FILM SAFEBY

SAFEBY

SAFEBA FILM
PRIM
32

SAFEBA

FILM

PRIM

32