Machine Generated Data
Tags
Amazon
created on 2019-06-05
Clarifai
created on 2019-06-05
Imagga
created on 2019-06-05
city | 32.4 | |
| ||
architecture | 30.7 | |
| ||
tower | 28.7 | |
| ||
building | 26.2 | |
| ||
sky | 22.9 | |
| ||
travel | 20.4 | |
| ||
tourism | 19 | |
| ||
old | 18.8 | |
| ||
structure | 17.8 | |
| ||
town | 17.6 | |
| ||
cityscape | 17 | |
| ||
history | 17 | |
| ||
buildings | 16.1 | |
| ||
wreckage | 15.6 | |
| ||
urban | 14.8 | |
| ||
construction | 14.5 | |
| ||
landmark | 13.5 | |
| ||
part | 13.5 | |
| ||
water | 13.3 | |
| ||
skyline | 13.3 | |
| ||
sea | 13.1 | |
| ||
church | 12.9 | |
| ||
house | 12.6 | |
| ||
river | 12.4 | |
| ||
bridge | 12.3 | |
| ||
business | 10.9 | |
| ||
sun | 10.5 | |
| ||
center | 10.3 | |
| ||
summer | 10.3 | |
| ||
famous | 10.2 | |
| ||
ship | 10 | |
| ||
silhouette | 9.9 | |
| ||
sunset | 9.9 | |
| ||
roof | 9.9 | |
| ||
landscape | 9.7 | |
| ||
design | 9.6 | |
| ||
scene | 9.5 | |
| ||
culture | 9.4 | |
| ||
light | 8.7 | |
| ||
monument | 8.4 | |
| ||
vintage | 8.3 | |
| ||
office | 8.2 | |
| ||
symbol | 8.1 | |
| ||
boat | 8.1 | |
| ||
home | 8 | |
| ||
st | 7.7 | |
| ||
cathedral | 7.7 | |
| ||
winter | 7.7 | |
| ||
capital | 7.6 | |
| ||
tourist | 7.5 | |
| ||
exterior | 7.4 | |
| ||
street | 7.4 | |
| ||
people | 7.2 | |
| ||
dome | 7.2 | |
| ||
modern | 7 | |
| ||
life | 7 | |
|
Google
created on 2019-06-05
Photograph | 96.1 | |
| ||
Snapshot | 87.7 | |
| ||
Text | 85.2 | |
| ||
Room | 80.1 | |
| ||
Adaptation | 67 | |
| ||
Stock photography | 66.6 | |
| ||
History | 64.5 | |
| ||
Interior design | 54.3 | |
|
Color Analysis
Face analysis
Amazon

AWS Rekognition
Age | 10-15 |
Gender | Male, 51.2% |
Disgusted | 46.3% |
Happy | 47.4% |
Angry | 46% |
Surprised | 45.6% |
Sad | 46.5% |
Confused | 45.6% |
Calm | 47.5% |

AWS Rekognition
Age | 15-25 |
Gender | Female, 52.1% |
Happy | 46.2% |
Sad | 49.6% |
Disgusted | 45.5% |
Calm | 47.8% |
Surprised | 45.2% |
Confused | 45.3% |
Angry | 45.4% |

AWS Rekognition
Age | 20-38 |
Gender | Female, 50.8% |
Calm | 50.4% |
Angry | 46.2% |
Happy | 45.3% |
Sad | 45.8% |
Surprised | 45.5% |
Confused | 45.2% |
Disgusted | 46.6% |

AWS Rekognition
Age | 26-43 |
Gender | Female, 50% |
Calm | 49.5% |
Disgusted | 49.5% |
Surprised | 49.5% |
Confused | 49.5% |
Angry | 49.5% |
Sad | 50.5% |
Happy | 49.5% |

AWS Rekognition
Age | 26-43 |
Gender | Female, 50.4% |
Disgusted | 49.5% |
Confused | 49.6% |
Happy | 49.5% |
Calm | 49.7% |
Surprised | 49.5% |
Sad | 50.1% |
Angry | 49.6% |

AWS Rekognition
Age | 26-43 |
Gender | Female, 50.3% |
Disgusted | 49.6% |
Confused | 49.5% |
Surprised | 49.6% |
Calm | 49.9% |
Happy | 49.5% |
Angry | 49.6% |
Sad | 49.7% |

AWS Rekognition
Age | 23-38 |
Gender | Female, 50.1% |
Calm | 49.9% |
Disgusted | 49.6% |
Sad | 49.7% |
Happy | 49.5% |
Confused | 49.6% |
Surprised | 49.6% |
Angry | 49.6% |

AWS Rekognition
Age | 20-38 |
Gender | Female, 50.4% |
Sad | 49.8% |
Angry | 49.6% |
Happy | 49.8% |
Surprised | 49.6% |
Confused | 49.6% |
Calm | 49.6% |
Disgusted | 49.6% |

AWS Rekognition
Age | 26-43 |
Gender | Female, 50.3% |
Sad | 49.8% |
Confused | 49.7% |
Angry | 49.9% |
Calm | 49.6% |
Surprised | 49.5% |
Happy | 49.5% |
Disgusted | 49.5% |
Feature analysis
Categories
Imagga
interior objects | 61.5% | |
| ||
paintings art | 35.3% | |
| ||
streetview architecture | 1.4% | |
|
Captions
Microsoft
created on 2019-06-05
a vintage photo of a group of people in a room | 55.7% | |
| ||
a vintage photo of some people in a room | 55.6% | |
| ||
a vintage photo of a group of people in a library | 31.6% | |
|
Text analysis
Amazon

future

boys

smaller

are

for

usefulness.

The smaller boys are trained for future usefulness.

trained

training

eight

The

of

age.

years

Vocational Vocati training commences at eight years of age.

commences

Vocati

at

Vocational

The smaller boys are trained for future usefulness.
Vocational training commences at eight years of age.

The

smaller

boys

are

trained

for

future

usefulness.

Vocational

training

commences

at

eight

years

of

age.