After doing some samples using Face API for face detection and Emotion APIs for emotions detection, now is the time for a review by the capabilities provided by Vision API.
This Project Oxford service allows you to analyze images and the result of this analysis shows information such as the categories associated with the image, perform some pornographic score, analysis of dominant colours, etc.
For example, the following image is a collage with pictures of the London rugby world cup from a month ago. In addition to the analysis of faces and emotions, in the 3rd column, we show the information of the results of the analysis with Vision API.
In it we can see that the detected category is outdoor, and in addition it has also detected faces.
Name : outdoor_sportsfield; Score : 0.7890625
Age : 17; Gender : Female
Age : 41; Gender : Male
Age : 10; Gender : Female
Age : 6; Gender : Female
In the case of my image in a Ford Mustang, again faces, emotions, and the car category are detected.
In upcoming posts I will comment on the detail of the use of this API, however an interesting detail is that we already have some NuGet packages for working with these APIs. Still they are not PCLs, so we use only in Desktop projects, but with 10 minutes of work, you can create your PCL implementation
An example analysis of landscapes and people you can see in the video below
The source code is avilable in GitHub https://github.com/elbruno/ProjectOxford
Greetings @ Madrid !
- Project Oxford
- My Azure ML Vision APIs series
- Adding Vision API capabilities in our apps
- My Azure ML Emotion APIs series
- My Azure ML Face APIs series