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 | 96.7 | |
| ||
Text | 89.7 | |
| ||
Snapshot | 86.5 | |
| ||
Room | 76.5 | |
| ||
Photography | 70.6 | |
| ||
Adaptation | 67 | |
| ||
Photographic paper | 59.4 | |
| ||
Stock photography | 59.4 | |
| ||
Art | 58.1 | |
| ||
History | 57.6 | |
| ||
Square | 55.4 | |
|
Color Analysis
Face analysis
Amazon

AWS Rekognition
Age | 6-13 |
Gender | Female, 53.1% |
Surprised | 45.1% |
Happy | 45.1% |
Confused | 45.1% |
Calm | 47.7% |
Disgusted | 45.1% |
Angry | 45.2% |
Sad | 51.7% |

AWS Rekognition
Age | 35-52 |
Gender | Female, 50.2% |
Calm | 45.2% |
Confused | 45.2% |
Happy | 45.2% |
Disgusted | 46.1% |
Sad | 46.9% |
Angry | 51.2% |
Surprised | 45.2% |

AWS Rekognition
Age | 27-44 |
Gender | Female, 50.2% |
Calm | 49.5% |
Angry | 49.5% |
Happy | 49.5% |
Sad | 50.4% |
Surprised | 49.5% |
Confused | 49.5% |
Disgusted | 49.5% |

AWS Rekognition
Age | 10-15 |
Gender | Male, 50.4% |
Disgusted | 49.5% |
Surprised | 49.5% |
Sad | 49.8% |
Angry | 49.9% |
Happy | 49.5% |
Confused | 49.7% |
Calm | 49.6% |

AWS Rekognition
Age | 15-25 |
Gender | Female, 50.4% |
Confused | 49.5% |
Sad | 50.3% |
Disgusted | 49.5% |
Angry | 49.6% |
Happy | 49.5% |
Calm | 49.5% |
Surprised | 49.5% |

AWS Rekognition
Age | 26-43 |
Gender | Male, 50.1% |
Calm | 49.6% |
Surprised | 49.6% |
Happy | 49.6% |
Angry | 49.6% |
Confused | 49.7% |
Sad | 50% |
Disgusted | 49.6% |

AWS Rekognition
Age | 9-14 |
Gender | Male, 50.5% |
Calm | 49.6% |
Disgusted | 49.6% |
Angry | 49.8% |
Happy | 49.5% |
Sad | 49.7% |
Surprised | 49.6% |
Confused | 49.6% |

AWS Rekognition
Age | 30-47 |
Gender | Female, 53.2% |
Angry | 45.1% |
Happy | 45.1% |
Confused | 45% |
Surprised | 45.1% |
Sad | 54.4% |
Disgusted | 45.1% |
Calm | 45.2% |

AWS Rekognition
Age | 20-38 |
Gender | Male, 50.3% |
Confused | 49.6% |
Disgusted | 49.5% |
Calm | 50% |
Sad | 49.7% |
Angry | 49.6% |
Happy | 49.6% |
Surprised | 49.6% |

AWS Rekognition
Age | 26-43 |
Gender | Male, 50.2% |
Calm | 49.7% |
Angry | 50% |
Happy | 49.5% |
Sad | 49.6% |
Surprised | 49.5% |
Confused | 49.6% |
Disgusted | 49.5% |

AWS Rekognition
Age | 26-43 |
Gender | Female, 50.1% |
Confused | 49.5% |
Calm | 49.8% |
Disgusted | 49.6% |
Sad | 49.9% |
Happy | 49.6% |
Angry | 49.5% |
Surprised | 49.6% |

AWS Rekognition
Age | 23-38 |
Gender | Female, 50.1% |
Happy | 49.5% |
Disgusted | 49.6% |
Angry | 49.6% |
Confused | 49.5% |
Calm | 49.8% |
Surprised | 49.6% |
Sad | 49.9% |

AWS Rekognition
Age | 26-43 |
Gender | Female, 50.2% |
Angry | 49.8% |
Calm | 49.6% |
Confused | 49.6% |
Happy | 49.6% |
Sad | 49.7% |
Disgusted | 49.8% |
Surprised | 49.6% |

AWS Rekognition
Age | 15-25 |
Gender | Female, 50.3% |
Confused | 49.5% |
Surprised | 49.5% |
Angry | 49.5% |
Happy | 49.5% |
Sad | 50.3% |
Calm | 49.5% |
Disgusted | 49.5% |

AWS Rekognition
Age | 12-22 |
Gender | Female, 50.2% |
Confused | 49.5% |
Happy | 49.6% |
Surprised | 49.5% |
Calm | 49.6% |
Angry | 49.5% |
Sad | 50.2% |
Disgusted | 49.6% |

AWS Rekognition
Age | 17-27 |
Gender | Female, 50.4% |
Sad | 50.2% |
Disgusted | 49.5% |
Calm | 49.6% |
Confused | 49.5% |
Happy | 49.6% |
Surprised | 49.5% |
Angry | 49.6% |

AWS Rekognition
Age | 16-27 |
Gender | Female, 50.4% |
Calm | 49.6% |
Happy | 49.5% |
Confused | 49.5% |
Sad | 50.3% |
Angry | 49.5% |
Surprised | 49.5% |
Disgusted | 49.5% |

AWS Rekognition
Age | 26-43 |
Gender | Male, 50.4% |
Calm | 49.7% |
Disgusted | 49.6% |
Sad | 49.8% |
Happy | 49.5% |
Confused | 49.6% |
Surprised | 49.6% |
Angry | 49.8% |

AWS Rekognition
Age | 48-68 |
Gender | Female, 50.5% |
Disgusted | 49.5% |
Confused | 49.5% |
Happy | 49.5% |
Calm | 50.4% |
Surprised | 49.5% |
Sad | 49.5% |
Angry | 49.5% |

AWS Rekognition
Age | 14-25 |
Gender | Male, 50.1% |
Sad | 49.6% |
Angry | 49.6% |
Calm | 49.6% |
Confused | 49.9% |
Happy | 49.7% |
Disgusted | 49.6% |
Surprised | 49.6% |

AWS Rekognition
Age | 16-27 |
Gender | Female, 50.2% |
Disgusted | 49.7% |
Confused | 49.6% |
Calm | 49.6% |
Surprised | 49.5% |
Happy | 49.5% |
Sad | 49.7% |
Angry | 49.9% |
Feature analysis
Categories
Imagga
paintings art | 78.1% | |
| ||
text visuals | 20% | |
|
Captions
Microsoft
created on 2019-06-05
a vintage photo of a box | 50.7% | |
|
Text analysis
Amazon

Needs

City

Examples

York

New

Special

the

of

Adaptation

Examples of the Adaptation of Education to Special City Needs

Publie

Brooklyn

Sehools

Education

to

New York City Publie Sehools 736.61

Lesson

and

Brooklyn Vocotron School- Sewing and Lesson

School-

Sewing

Vocotron

C 195

736.61

OOO

New York City Public Schools
Examples of the Adaptation of Education to Special City Needs
C 19S
Brooklyn Vocation School-Sewing and Mending Lesson

Examples

the

to

Special

C

19S

Brooklyn

Vocation

New

York

City

Public

Schools

of

Adaptation

Education

Needs

School-Sewing

and

Mending

Lesson