Machine Generated Data
Tags
Amazon
created on 2019-06-05
Clarifai
created on 2019-06-05
Imagga
created on 2019-06-05
Google
created on 2019-06-05
Photograph | 96.3 | |
| ||
Text | 90.3 | |
| ||
Snapshot | 86.2 | |
| ||
Room | 81.5 | |
| ||
Collection | 69.3 | |
| ||
History | 64.5 | |
| ||
Table | 63.8 | |
| ||
Art | 58.1 | |
| ||
Furniture | 56.7 | |
| ||
Illustration | 54.5 | |
|
Color Analysis
Face analysis
Amazon

AWS Rekognition
Age | 11-18 |
Gender | Female, 50.1% |
Calm | 49.5% |
Happy | 49.8% |
Angry | 49.6% |
Disgusted | 49.5% |
Surprised | 49.5% |
Confused | 49.5% |
Sad | 49.9% |

AWS Rekognition
Age | 17-27 |
Gender | Female, 50.2% |
Calm | 49.7% |
Disgusted | 49.9% |
Confused | 49.6% |
Happy | 49.6% |
Angry | 49.6% |
Sad | 49.6% |
Surprised | 49.5% |

AWS Rekognition
Age | 19-36 |
Gender | Male, 50.1% |
Happy | 49.5% |
Sad | 50.3% |
Disgusted | 49.5% |
Angry | 49.6% |
Surprised | 49.5% |
Calm | 49.5% |
Confused | 49.5% |

AWS Rekognition
Age | 26-43 |
Gender | Female, 50% |
Surprised | 49.5% |
Happy | 49.8% |
Disgusted | 49.5% |
Calm | 49.8% |
Sad | 49.7% |
Angry | 49.6% |
Confused | 49.6% |

AWS Rekognition
Age | 20-38 |
Gender | Female, 50.3% |
Confused | 49.6% |
Surprised | 49.6% |
Sad | 49.9% |
Calm | 49.6% |
Happy | 49.6% |
Angry | 49.6% |
Disgusted | 49.6% |

AWS Rekognition
Age | 23-38 |
Gender | Male, 50.4% |
Surprised | 49.5% |
Sad | 50.1% |
Happy | 49.6% |
Confused | 49.5% |
Calm | 49.6% |
Angry | 49.6% |
Disgusted | 49.5% |

AWS Rekognition
Age | 26-44 |
Gender | Female, 50.4% |
Sad | 49.9% |
Calm | 49.7% |
Disgusted | 49.6% |
Confused | 49.6% |
Angry | 49.6% |
Surprised | 49.6% |
Happy | 49.6% |

AWS Rekognition
Age | 26-44 |
Gender | Female, 50% |
Angry | 49.6% |
Disgusted | 49.5% |
Sad | 49.6% |
Happy | 49.5% |
Confused | 49.5% |
Surprised | 49.5% |
Calm | 50.2% |
Feature analysis
Categories
Imagga
text visuals | 86.7% | |
| ||
streetview architecture | 6.4% | |
| ||
paintings art | 5.7% | |
|
Captions
Microsoft
created on 2019-06-05
a store inside of a box | 51.2% | |
| ||
a display in a store | 51.1% | |
| ||
a sign above a store | 51% | |
|
Text analysis
Amazon

Needs

Publie

York

Edueation

City

the

of

Examples of the Adaptation Edueation to Special City Needs

Sehools

to

New York Cit Publie Sehools

Adaptation

Examples

Washing

Special

Cit

Shrls

House Washing Dishes.

mhe

New

Aaptatmct

Dishes.

3.73.6.50

House

-Woshing

Souplesof mhe Aaptatmct cf

cf

GED 3.73.6.50

haHan

Soutatin

Cfi1

GED

Soutatin TO Cfi1

Souplesof

PShe Shrls wYc

TO

PShe

IE

IE 27

wYc

27

anhlien

Atie

NYC
Pashe Sahrols
57
Publie Schools
New York City
Education to Speeial City Needs
hOples of he Adephatm of
E
Housekerpirg- Washing
Houeekeoping Washing Dishes
Puelie Scheela
yest Manhattan
37
Hanhafian

NYC

Pashe

Sahrols

57

Publie

Schools

New

York

City

Education

to

Speeial

Needs

hOples

of

he

Adephatm

E

Housekerpirg-

Washing

Houeekeoping

Dishes

Puelie

Scheela

yest

Manhattan

37

Hanhafian