Introduction into Creating a Video Analytics Plugin

This tutorial outlines a process developers can follow to create a video analytics plugin for use with Nx Meta products.

The tutorial will not teach the reader how to use neural networks and algorithms for computer vision tasks; instead, it will show developers how to use the Metadata SDK to write a video analytics plugin (which might use third-party neural network frameworks for real-world tasks). The plugin is a C++ shared library.

The plugin created will detect and track people, cats, and dogs.

For object detection, we will use the OpenCV DNN module in conjunction with the pre-trained MobileNet SSD Caffe model. For object tracking, we will use the tbm (tracked by matching) OpenCV module.

The following sections of the tutorial will cover the step-by-step to

• download the source code;
• prepare the workspace;
• start the project using a template;
• load and enable plugin inside VMS Server;
• add an object detector, send object metadata to the Server; and
• add object tracking functionality;
• add analytics event functionality.