Machine Generated Data
Tags
Amazon
created on 2023-10-06
Clarifai
created on 2018-05-10
people | 100 | |
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one | 99.5 | |
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adult | 99.3 | |
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wear | 98.4 | |
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man | 98 | |
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two | 96.9 | |
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artisan | 96.1 | |
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sewing machine | 95.9 | |
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grinder | 95.4 | |
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raw material | 94.8 | |
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production | 94.8 | |
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concentration | 94.3 | |
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room | 92.7 | |
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industry | 92.6 | |
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group | 92.1 | |
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furniture | 91.3 | |
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employee | 90.7 | |
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military | 90.5 | |
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three | 90.5 | |
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war | 89.5 | |
|
Imagga
created on 2023-10-06
loom | 34.8 | |
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machine | 33.9 | |
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textile machine | 28.4 | |
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work | 26.3 | |
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machinist | 26 | |
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man | 24.9 | |
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industry | 24.7 | |
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metal | 22.5 | |
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steel | 22.1 | |
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industrial | 21.8 | |
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device | 20.3 | |
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worker | 19.5 | |
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factory | 19.1 | |
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old | 18.8 | |
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working | 18.6 | |
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equipment | 17.6 | |
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construction | 17.1 | |
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building | 16.6 | |
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job | 15 | |
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person | 14.8 | |
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male | 14.2 | |
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iron | 14.1 | |
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people | 13.9 | |
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men | 13.7 | |
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manufacturing | 13.7 | |
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repair | 13.4 | |
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safety | 12.9 | |
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occupation | 12.8 | |
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light | 12.7 | |
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heat | 12 | |
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welder | 11.9 | |
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manual | 11.7 | |
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labor | 11.7 | |
| ||
skill | 11.6 | |
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tools | 11.4 | |
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power | 10.9 | |
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hot | 10.9 | |
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craft | 10.9 | |
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welding | 10.9 | |
| ||
product | 10.8 | |
| ||
mask | 10.8 | |
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newspaper | 10.5 | |
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fire | 10.3 | |
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carpenter | 10.3 | |
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protection | 10 | |
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structure | 9.9 | |
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black | 9.7 | |
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vehicle | 9.3 | |
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tool | 9.2 | |
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gloves | 8.7 | |
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technical | 8.7 | |
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site | 8.4 | |
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adult | 8.4 | |
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house | 8.4 | |
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seller | 8.2 | |
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engineer | 8.1 | |
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weld | 7.9 | |
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business | 7.9 | |
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spark | 7.9 | |
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sparks | 7.9 | |
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urban | 7.9 | |
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mechanic | 7.8 | |
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helmet | 7.7 | |
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engineering | 7.6 | |
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build | 7.6 | |
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creation | 7.5 | |
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flame | 7.5 | |
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car | 7.5 | |
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human | 7.5 | |
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smoke | 7.4 | |
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technology | 7.4 | |
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dirty | 7.2 | |
|
Google
created on 2018-05-10
black and white | 87.8 | |
| ||
monochrome photography | 68.1 | |
| ||
artisan | 60.6 | |
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monochrome | 59.9 | |
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stock photography | 56.3 | |
| ||
human behavior | 54 | |
|
Color Analysis
Face analysis
Amazon
Microsoft

AWS Rekognition
Age | 16-22 |
Gender | Female, 94.5% |
Calm | 98.1% |
Surprised | 6.3% |
Fear | 5.9% |
Sad | 2.7% |
Happy | 0.1% |
Confused | 0% |
Angry | 0% |
Disgusted | 0% |

Microsoft Cognitive Services
Age | 34 |
Gender | Male |

Google Vision
Surprise | Very unlikely |
Anger | Very unlikely |
Sorrow | Very unlikely |
Joy | Very unlikely |
Headwear | Very unlikely |
Blurred | Very unlikely |
Feature analysis
Categories
Imagga
paintings art | 80.9% | |
| ||
food drinks | 5.3% | |
| ||
interior objects | 5.2% | |
| ||
cars vehicles | 4.4% | |
| ||
pets animals | 1.3% | |
|
Captions
Microsoft
created on 2018-05-10
a black and white photo of a man | 65.7% | |
| ||
a man sitting on a bench | 40.3% | |
| ||
black and white photo of a man | 40.2% | |
|
Text analysis
Amazon

MOTO

NATION

of

a

NATIO

NATIO