Face Analytics

Introduction

Face Analytics is a Catalyst Zia Services component that performs facial detection in images, and implements advanced computational analysis on the detected faces to identify and predict the following attributes:

• Coordinates of the face and the facial features
• Smile detection
• Age detection
• Gender detection

Zia maps a series of interest points in a detected face and performs an in-depth analysis on their relative positions to generate the results for the attributes. It implements several AI algorithms for this purpose, and compares the detected localized landmarks with samples from machine learning datasets to arrive at predictions of the smile, age, and gender detections.

Face Analytics also provides the confidence levels of each attribute prediction that enables you to make informed decisions. Face Analytics can detect up to 10 faces in an image, and it provides predictions of the attributes for each detected face.

Catalyst provides Face Analytics in the Java, Node.js and Python SDK packages, and you can integrate it in your Catalyst web or Android application. The Catalyst console provides easy access to code templates for these environments that you can implement in your application’s code. You can also test Face Analytics using sample images in the console, and obtain the predictions of the attributes mentioned above, for the detected faces.

You can refer to the Java SDK documentation, Node.js SDK documentation and Python SDK documentation for code samples of Face Analytics. Refer to the API documentation to learn about the API available for Face Analytics.

You can learn more about the other components of Catalyst Zia Services from this page.