Machine Generated Data
Tags
Color Analysis
Face analysis
Amazon
Microsoft
AWS Rekognition
| Age | 45-63 |
| Gender | Male, 98.3% |
| Sad | 4.9% |
| Calm | 73.8% |
| Angry | 3.3% |
| Surprised | 4.5% |
| Confused | 12.7% |
| Happy | 0.3% |
| Disgusted | 0.4% |
AWS Rekognition
| Age | 35-52 |
| Gender | Male, 99.7% |
| Happy | 10.7% |
| Sad | 10.4% |
| Calm | 51.4% |
| Confused | 6.4% |
| Disgusted | 3.5% |
| Angry | 8.4% |
| Surprised | 9.2% |
AWS Rekognition
| Age | 29-45 |
| Gender | Male, 99.7% |
| Happy | 0.2% |
| Calm | 92.6% |
| Confused | 1.2% |
| Angry | 2.2% |
| Sad | 1.9% |
| Disgusted | 0.7% |
| Surprised | 1.2% |
AWS Rekognition
| Age | 26-43 |
| Gender | Male, 96.8% |
| Sad | 0.3% |
| Disgusted | 0.1% |
| Surprised | 0.2% |
| Confused | 0.5% |
| Angry | 0.3% |
| Happy | 0% |
| Calm | 98.6% |
AWS Rekognition
| Age | 26-43 |
| Gender | Female, 95.2% |
| Disgusted | 3.4% |
| Sad | 7.4% |
| Calm | 55% |
| Surprised | 12.8% |
| Happy | 3.2% |
| Confused | 11.3% |
| Angry | 7% |
AWS Rekognition
| Age | 35-52 |
| Gender | Male, 98.3% |
| Happy | 1.2% |
| Surprised | 5.8% |
| Angry | 6% |
| Calm | 28.1% |
| Disgusted | 2.9% |
| Sad | 47.2% |
| Confused | 8.8% |
AWS Rekognition
| Age | 26-43 |
| Gender | Male, 94.4% |
| Sad | 5.5% |
| Angry | 4.3% |
| Happy | 5.4% |
| Calm | 63.1% |
| Surprised | 8.3% |
| Disgusted | 1.4% |
| Confused | 12% |
AWS Rekognition
| Age | 26-43 |
| Gender | Male, 98.7% |
| Confused | 6.5% |
| Sad | 17.7% |
| Disgusted | 0.8% |
| Happy | 0.7% |
| Angry | 3% |
| Surprised | 8.2% |
| Calm | 63.2% |
AWS Rekognition
| Age | 38-59 |
| Gender | Male, 78.7% |
| Disgusted | 0.4% |
| Confused | 0.9% |
| Angry | 2.4% |
| Surprised | 1.4% |
| Happy | 1.5% |
| Sad | 3.5% |
| Calm | 89.8% |
Microsoft Cognitive Services
| Age | 38 |
| Gender | Female |
Microsoft Cognitive Services
| Age | 40 |
| Gender | Female |
Microsoft Cognitive Services
| Age | 34 |
| Gender | Female |
Microsoft Cognitive Services
| Age | 46 |
| Gender | Female |
Microsoft Cognitive Services
| Age | 39 |
| Gender | Male |
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 likely |
| 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
| events parties | 27.5% | |
| people portraits | 27.1% | |
| food drinks | 25.6% | |
| interior objects | 9.4% | |
| paintings art | 7.9% | |
| text visuals | 1.4% | |
| pets animals | 0.6% | |
| macro flowers | 0.4% | |
| nature landscape | 0.1% | |
| cars vehicles | 0.1% | |
Captions
Microsoft
created on 2018-02-09
| a close up of items on a table | 75.5% | |
| a bunch of items that are on a table | 74.6% | |
| a bunch of items that are sitting on a table | 64.5% | |
Text analysis
Amazon
