Introduction to nilvana™ flow ─ Main nodes
In this article we are going to cover the following topics:
Visual Learners! Here is the tech demo
Introduction
There are 8 nodes under nilvana's categorization; camera configuration, face recognition, image preview, blacklists, white or black list, whitelists, facial web hooks and gatekeeper, respectively. There are dependencies linked between the nodes, therefore, please follow the steps accordingly.
In this article, we are going to introduce camera configuration, face recognition and image preview.
▽ 8 nodes under nilvana's categorization
▽ Hover your mouse on the node, there will be a dialog box with brief introduction
▽ Click on the book button, the details of node display on the right
▽ Drag the node into the flow
▽ Update settings by double clicking on the node
Camera configuration
This node is developed for controlling your camera, make sure that your USB camera is connected to your atom device before turning the power on. The first thing you need to do after adding this node to your flow is assign an MQTT broker address. This broker is already installed on your edge device, therefore you can simply input localhost to the Server field. You can either control the frame rate by adjusting the Interval field manually or by checking the face detection box for auto-detection. Once the face detection function is enabled, this node will only pass image data to the downstream node when it detects a face inside the camera. Don't forget to deploy your modifications and toggle the node.
▽ Add the camera configuration node to flow
▽ Set the MQTT broker
▽ The MQTT broker has been installed, easily fill with localhost
▽ Press the Done button to finish configuration
▽ Don't forget to deploy your settings
▽ You will see the "Successfully deployed"
Face recognition
Once you've set up the camera configuration node, you can add this node to the flow to recognize known faces. Thanks to the face enrollment kits running on the workstation, you would only need to input the workstation IP address.
▽ Add the face recognition node to the flow
▽ Fill with the IP address of Workstation
Image preview
After finishing face recognition settings, you can obtain face information when the system recognizes a known face. By adding the image preview into the flow, you can see the recognized face position and name under the node. Modify the parameters in the width column if you want to adjust the display size of the preview frame.
▽ Add the image preview node to flow
▽ Add the line to connect face recognition and image preview
▽ Don't forget to deploy the modifications
▽ Click on the box in front of the camera configuration to activate the camera
▽ Now, you can see the image preview of the recognition
