Machine Generated Data
Tags
Amazon
created on 2019-06-05
Person | 99.5 | |
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Human | 99.5 | |
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Person | 99.3 | |
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Person | 99.1 | |
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Person | 98.8 | |
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Person | 98.3 | |
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Person | 97.9 | |
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People | 97.7 | |
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Person | 97.6 | |
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Person | 97.5 | |
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Person | 96.8 | |
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Person | 95.2 | |
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Family | 87.4 | |
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Poster | 86.1 | |
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Advertisement | 86.1 | |
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Person | 81.1 | |
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Person | 75.5 | |
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Art | 75 | |
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Painting | 75 | |
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Person | 72.5 | |
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Military Uniform | 70.8 | |
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Military | 70.8 | |
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Sailor Suit | 65.1 | |
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Officer | 60.7 | |
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Armored | 58.5 | |
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Army | 58.5 | |
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Troop | 58.5 | |
|
Clarifai
created on 2019-06-05
Imagga
created on 2019-06-05
graffito | 30.4 | |
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decoration | 26.5 | |
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old | 24.4 | |
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shop | 18.1 | |
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art | 16 | |
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vintage | 14.9 | |
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ancient | 14.7 | |
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sculpture | 14.6 | |
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statue | 14.5 | |
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grunge | 13.6 | |
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man | 13.4 | |
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city | 13.3 | |
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military uniform | 12.9 | |
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dirty | 12.6 | |
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history | 12.5 | |
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monument | 12.1 | |
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uniform | 11.8 | |
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people | 11.7 | |
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antique | 11.2 | |
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rifle | 11.2 | |
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wall | 11.1 | |
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historic | 11 | |
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mercantile establishment | 10.8 | |
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travel | 10.6 | |
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person | 10.5 | |
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clothing | 10.5 | |
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historical | 10.3 | |
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architecture | 10.1 | |
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aged | 9.9 | |
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room | 9.7 | |
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gun | 9.7 | |
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business | 9.7 | |
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world | 9.5 | |
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building | 9.5 | |
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violin | 9.2 | |
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tourism | 9.1 | |
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retro | 9 | |
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scene | 8.6 | |
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barbershop | 8.6 | |
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male | 8.5 | |
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black | 8.4 | |
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bowed stringed instrument | 8.2 | |
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tourist | 8.2 | |
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musical instrument | 8 | |
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weapon | 7.9 | |
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urban | 7.9 | |
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portrait | 7.8 | |
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men | 7.7 | |
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war | 7.7 | |
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stringed instrument | 7.7 | |
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firearm | 7.6 | |
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texture | 7.6 | |
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window | 7.6 | |
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stone | 7.6 | |
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shoe shop | 7.5 | |
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paint | 7.2 | |
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detail | 7.2 | |
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private | 7.2 | |
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place of business | 7.2 | |
|
Google
created on 2019-06-05
Photograph | 96.6 | |
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People | 93.1 | |
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Snapshot | 86.7 | |
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Room | 71.4 | |
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Photography | 62.4 | |
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Family | 60.9 | |
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Art | 58.1 | |
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History | 57.6 | |
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Child | 57.3 | |
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Vintage clothing | 55.9 | |
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Collection | 50 | |
|
Color Analysis
Face analysis
Amazon
Microsoft

AWS Rekognition
Age | 12-22 |
Gender | Male, 53.2% |
Sad | 48.8% |
Confused | 45.5% |
Angry | 45.4% |
Calm | 50.1% |
Surprised | 45.1% |
Happy | 45.1% |
Disgusted | 45.1% |

AWS Rekognition
Age | 15-25 |
Gender | Female, 52% |
Sad | 47.6% |
Confused | 45.3% |
Angry | 50.8% |
Calm | 45.3% |
Surprised | 45.4% |
Happy | 45.5% |
Disgusted | 45.2% |

AWS Rekognition
Age | 20-38 |
Gender | Female, 51.5% |
Angry | 45.6% |
Calm | 45.1% |
Disgusted | 45% |
Happy | 45% |
Confused | 45.1% |
Sad | 54.2% |
Surprised | 45% |

AWS Rekognition
Age | 17-27 |
Gender | Female, 54.6% |
Calm | 45.7% |
Confused | 45.1% |
Sad | 53.9% |
Surprised | 45.1% |
Happy | 45% |
Disgusted | 45% |
Angry | 45.2% |

AWS Rekognition
Age | 23-38 |
Gender | Male, 54.3% |
Calm | 45.1% |
Confused | 45.3% |
Sad | 54.2% |
Surprised | 45% |
Happy | 45% |
Disgusted | 45% |
Angry | 45.3% |

AWS Rekognition
Age | 23-38 |
Gender | Male, 52.9% |
Calm | 51.9% |
Disgusted | 45.4% |
Sad | 46.1% |
Angry | 45.6% |
Happy | 45.2% |
Confused | 45.5% |
Surprised | 45.3% |

AWS Rekognition
Age | 10-15 |
Gender | Female, 53% |
Calm | 45.6% |
Sad | 52.5% |
Angry | 46.5% |
Confused | 45.2% |
Happy | 45.1% |
Disgusted | 45.1% |
Surprised | 45.1% |

AWS Rekognition
Age | 4-7 |
Gender | Female, 52.8% |
Angry | 47.3% |
Sad | 48.4% |
Calm | 47.9% |
Surprised | 45.3% |
Confused | 45.4% |
Disgusted | 45.2% |
Happy | 45.6% |

AWS Rekognition
Age | 10-15 |
Gender | Female, 54.9% |
Disgusted | 45% |
Sad | 54.3% |
Calm | 45.4% |
Surprised | 45% |
Angry | 45.1% |
Happy | 45.1% |
Confused | 45.1% |

AWS Rekognition
Age | 26-43 |
Gender | Male, 54.4% |
Surprised | 45% |
Sad | 45.4% |
Angry | 45.1% |
Happy | 45.1% |
Confused | 45% |
Disgusted | 45% |
Calm | 54.3% |

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

AWS Rekognition
Age | 20-38 |
Gender | Male, 53.8% |
Calm | 47% |
Surprised | 45.6% |
Confused | 45.6% |
Sad | 47.4% |
Angry | 48.9% |
Disgusted | 45.3% |
Happy | 45.1% |

Microsoft Cognitive Services
Age | 6 |
Gender | Female |

Microsoft Cognitive Services
Age | 5 |
Gender | Female |

Microsoft Cognitive Services
Age | 8 |
Gender | Female |

Microsoft Cognitive Services
Age | 27 |
Gender | Female |

Microsoft Cognitive Services
Age | 24 |
Gender | Female |

Microsoft Cognitive Services
Age | 31 |
Gender | Female |

Microsoft Cognitive Services
Age | 10 |
Gender | Female |

Microsoft Cognitive Services
Age | 12 |
Gender | Female |

Microsoft Cognitive Services
Age | 10 |
Gender | Female |

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 |

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
interior objects | 95.6% | |
| ||
paintings art | 2.1% | |
| ||
food drinks | 1.2% | |
|
Captions
Microsoft
created on 2019-06-05
a vintage photo of a group of people posing for the camera | 89.2% | |
| ||
a vintage photo of a group of people posing for a picture | 89.1% | |
| ||
an old photo of a group of people posing for the camera | 88.9% | |
|
Text analysis
Amazon

The

beginning

The beginning in dressmohing.

dressmohing.

in

The beginning in dress making

The

beginning

in

dress

making