Machine Generated Data
Tags
Amazon
created on 2019-06-07
Person | 98.2 | |
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Human | 98.2 | |
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Person | 98 | |
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Person | 97.1 | |
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Person | 97 | |
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Person | 96.5 | |
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Person | 96.4 | |
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Person | 96 | |
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Person | 95.5 | |
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Person | 95 | |
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Person | 94.8 | |
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Person | 94.7 | |
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Apparel | 94.5 | |
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Suit | 94.5 | |
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Clothing | 94.5 | |
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Coat | 94.5 | |
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Overcoat | 94.5 | |
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Suit | 92.6 | |
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Person | 91.6 | |
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Suit | 87.8 | |
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People | 79 | |
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Tie | 76.3 | |
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Accessories | 76.3 | |
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Accessory | 76.3 | |
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Suit | 74.1 | |
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Tie | 68.2 | |
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Sitting | 65.8 | |
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Military Uniform | 60.9 | |
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Military | 60.9 | |
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Jury | 59.6 | |
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Crowd | 57.9 | |
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Footwear | 57.5 | |
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Shoe | 57.5 | |
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Audience | 56.7 | |
|
Clarifai
created on 2019-06-07
Imagga
created on 2019-06-07
military uniform | 34.8 | |
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uniform | 33.3 | |
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man | 30.9 | |
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people | 30.1 | |
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kin | 28.6 | |
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person | 27.1 | |
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male | 24.1 | |
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clothing | 23.8 | |
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adult | 21.7 | |
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group | 19.3 | |
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business | 18.2 | |
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room | 17.1 | |
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happy | 16.9 | |
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couple | 15.7 | |
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portrait | 15.5 | |
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men | 14.6 | |
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brass | 14.1 | |
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businessman | 14.1 | |
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consumer goods | 14.1 | |
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covering | 13.6 | |
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family | 13.3 | |
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happiness | 13.3 | |
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classroom | 13.3 | |
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student | 11.8 | |
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team | 11.6 | |
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smiling | 11.6 | |
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love | 11 | |
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wind instrument | 11 | |
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old | 10.4 | |
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women | 10.3 | |
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black | 10.2 | |
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youth | 10.2 | |
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dress | 9.9 | |
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professional | 9.7 | |
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home | 9.6 | |
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boy | 9.5 | |
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indoor | 9.1 | |
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fashion | 9 | |
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cheerful | 8.9 | |
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new | 8.9 | |
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interior | 8.8 | |
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together | 8.7 | |
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lifestyle | 8.7 | |
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bride | 8.6 | |
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senior | 8.4 | |
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attractive | 8.4 | |
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musical instrument | 8.3 | |
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camera | 8.3 | |
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vintage | 8.3 | |
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girls | 8.2 | |
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businesswoman | 8.2 | |
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child | 8 | |
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indoors | 7.9 | |
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standing | 7.8 | |
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education | 7.8 | |
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30s | 7.7 | |
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four | 7.7 | |
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meeting | 7.5 | |
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human | 7.5 | |
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fun | 7.5 | |
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silhouette | 7.4 | |
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wedding | 7.3 | |
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school | 7.3 | |
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success | 7.2 | |
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office | 7.2 | |
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life | 7.2 | |
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looking | 7.2 | |
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smile | 7.1 | |
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mother | 7.1 | |
|
Color Analysis
Face analysis
Amazon
Microsoft

AWS Rekognition
Age | 48-68 |
Gender | Male, 52.1% |
Angry | 45.8% |
Calm | 45.3% |
Happy | 45.1% |
Sad | 47.2% |
Disgusted | 51% |
Surprised | 45.1% |
Confused | 45.4% |

AWS Rekognition
Age | 45-65 |
Gender | Male, 54.9% |
Surprised | 45.4% |
Angry | 45.2% |
Calm | 51.5% |
Sad | 45.4% |
Confused | 45.4% |
Disgusted | 45.1% |
Happy | 47% |

AWS Rekognition
Age | 35-52 |
Gender | Male, 54% |
Happy | 46% |
Sad | 50% |
Surprised | 45.2% |
Angry | 45.6% |
Calm | 47% |
Disgusted | 45.8% |
Confused | 45.4% |

AWS Rekognition
Age | 48-68 |
Gender | Male, 52.5% |
Disgusted | 45.1% |
Surprised | 45.3% |
Sad | 48.5% |
Confused | 45.2% |
Calm | 45.5% |
Happy | 50.1% |
Angry | 45.3% |

AWS Rekognition
Age | 35-52 |
Gender | Male, 55% |
Sad | 47.4% |
Surprised | 45.3% |
Calm | 46.9% |
Disgusted | 47.3% |
Confused | 45.4% |
Angry | 45.8% |
Happy | 46.9% |

AWS Rekognition
Age | 35-52 |
Gender | Male, 54.3% |
Happy | 45.8% |
Angry | 46% |
Calm | 49.7% |
Surprised | 45.4% |
Disgusted | 45.3% |
Sad | 47% |
Confused | 45.9% |

AWS Rekognition
Age | 38-59 |
Gender | Male, 54.4% |
Happy | 45.5% |
Surprised | 45.2% |
Sad | 47.2% |
Confused | 45.2% |
Disgusted | 46.4% |
Calm | 48.1% |
Angry | 47.3% |

AWS Rekognition
Age | 29-45 |
Gender | Male, 54.8% |
Surprised | 45% |
Happy | 45% |
Calm | 45.1% |
Angry | 45% |
Disgusted | 45% |
Sad | 54.8% |
Confused | 45% |

AWS Rekognition
Age | 57-77 |
Gender | Male, 54.5% |
Surprised | 45.2% |
Angry | 52.1% |
Sad | 45.4% |
Disgusted | 45.7% |
Happy | 45.3% |
Calm | 46.1% |
Confused | 45.3% |

AWS Rekognition
Age | 35-52 |
Gender | Male, 53.2% |
Calm | 48.8% |
Surprised | 46.4% |
Confused | 45.5% |
Angry | 45.9% |
Sad | 47% |
Happy | 45.6% |
Disgusted | 45.8% |

AWS Rekognition
Age | 38-57 |
Gender | Male, 54.6% |
Calm | 46.2% |
Sad | 45.2% |
Surprised | 45.2% |
Disgusted | 45.2% |
Angry | 52.7% |
Confused | 45.1% |
Happy | 45.5% |

AWS Rekognition
Age | 38-59 |
Gender | Male, 55% |
Disgusted | 45% |
Angry | 45.3% |
Sad | 48.8% |
Happy | 46.5% |
Calm | 49% |
Surprised | 45.1% |
Confused | 45.3% |

Microsoft Cognitive Services
Age | 54 |
Gender | Male |

Microsoft Cognitive Services
Age | 58 |
Gender | Male |

Microsoft Cognitive Services
Age | 50 |
Gender | Male |

Microsoft Cognitive Services
Age | 58 |
Gender | Male |

Microsoft Cognitive Services
Age | 58 |
Gender | Male |

Microsoft Cognitive Services
Age | 37 |
Gender | Male |

Microsoft Cognitive Services
Age | 55 |
Gender | Male |

Microsoft Cognitive Services
Age | 44 |
Gender | Male |

Microsoft Cognitive Services
Age | 51 |
Gender | Male |

Microsoft Cognitive Services
Age | 50 |
Gender | Male |

Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | 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 |

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 | 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 |

Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very unlikely |
Feature analysis
Categories
Imagga
people portraits | 69.8% | |
| ||
events parties | 23.9% | |
| ||
text visuals | 2% | |
| ||
interior objects | 1.5% | |
|
Captions
Microsoft
created on 2019-06-07
Jake Drauby et al. posing for a photo | 98.8% | |
| ||
Jake Drauby et al. posing for the camera | 98.7% | |
| ||
Jake Drauby et al. posing for a picture | 98.6% | |
|
Text analysis
Amazon

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Checkers

Club.

Chsss ond Checkers Club.

Chsss

Chess ond Checkers Club.

Chess

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Checkers

Club.