Machine Generated Data
Tags
Amazon
created on 2019-07-25
Human | 97 | |
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Person | 97 | |
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Person | 95.6 | |
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Art | 85.5 | |
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Indoors | 83.8 | |
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Interior Design | 83.8 | |
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Advertisement | 76.9 | |
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Poster | 74.4 | |
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Leisure Activities | 67.2 | |
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Game | 65.7 | |
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Drawing | 64.4 | |
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Collage | 59.6 | |
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Painting | 58.9 | |
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Tapestry | 57.3 | |
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Ornament | 57.3 | |
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Jigsaw Puzzle | 55.2 | |
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Clarifai
created on 2019-07-25
Imagga
created on 2019-07-25
mosaic | 52.3 | |
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bookmark | 46.3 | |
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transducer | 41.2 | |
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electrical device | 30.9 | |
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paper | 29.8 | |
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vintage | 26.5 | |
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old | 25.8 | |
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stocking | 24.7 | |
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currency | 21.5 | |
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money | 21.3 | |
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finance | 20.3 | |
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device | 20 | |
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retro | 19.7 | |
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hosiery | 18.8 | |
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grunge | 18.7 | |
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art | 17.1 | |
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cash | 16.5 | |
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texture | 16 | |
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pattern | 15.7 | |
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card | 15.3 | |
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bank | 14.3 | |
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note | 13.8 | |
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13.4 | ||
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financial | 13.4 | |
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antique | 13 | |
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banking | 12.9 | |
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postage | 12.8 | |
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collection | 12.6 | |
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footwear | 12.4 | |
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ancient | 12.1 | |
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postmark | 11.8 | |
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decoration | 11.7 | |
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stamp | 11.6 | |
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notes | 11.5 | |
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fabric | 11.3 | |
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design | 11.3 | |
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business | 10.9 | |
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frame | 10.8 | |
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clothing | 10.5 | |
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instrumentality | 10.3 | |
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economy | 10.2 | |
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colorful | 10 | |
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wealth | 9.9 | |
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postal | 9.8 | |
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banknote | 9.7 | |
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exchange | 9.5 | |
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post | 9.5 | |
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color | 9.5 | |
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blank | 9.4 | |
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symbol | 9.4 | |
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letter | 9.2 | |
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traditional | 9.1 | |
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gold | 9 | |
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dirty | 9 | |
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stamps | 8.9 | |
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banknotes | 8.8 | |
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cotton | 8.7 | |
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pay | 8.6 | |
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bill | 8.6 | |
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wallpaper | 8.4 | |
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tile | 8.2 | |
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map | 8.2 | |
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history | 8.1 | |
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rug | 7.8 | |
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travel | 7.7 | |
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gift | 7.7 | |
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payment | 7.7 | |
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culture | 7.7 | |
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envelope | 7.4 | |
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document | 7.4 | |
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greeting | 7.4 | |
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yellow | 7.3 | |
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prayer rug | 7.3 | |
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border | 7.2 | |
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holiday | 7.2 | |
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material | 7.1 | |
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world | 7.1 | |
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handkerchief | 7.1 | |
|
Google
created on 2019-07-25
Art | 83.4 | |
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Illustration | 77.6 | |
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Miniature | 71 | |
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Textile | 70.4 | |
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History | 69.9 | |
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Games | 63.1 | |
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Ancient history | 52 | |
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Painting | 50.4 | |
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Face analysis
Amazon

AWS Rekognition
Age | 26-43 |
Gender | Female, 51% |
Disgusted | 45.2% |
Happy | 45.2% |
Sad | 45.4% |
Confused | 45.5% |
Calm | 48.5% |
Angry | 45.2% |
Surprised | 50.1% |

AWS Rekognition
Age | 35-52 |
Gender | Male, 54.5% |
Confused | 45.3% |
Angry | 45.5% |
Disgusted | 45.3% |
Sad | 47.1% |
Calm | 51.4% |
Happy | 45.2% |
Surprised | 45.3% |

AWS Rekognition
Age | 35-52 |
Gender | Female, 51.4% |
Angry | 46.2% |
Happy | 45.4% |
Confused | 46.5% |
Surprised | 46.2% |
Calm | 46% |
Disgusted | 45.7% |
Sad | 49% |
Feature analysis
Amazon


Person | 97% | |
|
Text analysis

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