In order to configure the stream properely for best data accuracy there are two options which will support you in the configuration process.
For easy calibration, you can use our Live calibration in the top right corner drop down of the preview frame. As you can see in the screenshot below, this mode offers visibility about what objects the software is able to detect in the current previewed frame.
We suggest to use this calibration view especially for calibrating your Single & Multispace use case configurations with Region of Interests.
The detected objects are surrounded by a so-called bounding box. Any bounding box also displays the center of the object. In order to distinguish the objects, we offer the calibration more in differentiated colors of the main classes. Any event that gets delivered via MQTT is triggered by the center of the object (dot in the center of the bounding box).
The track calibration feature gives the option to overlay a relevant amount of object tracks on the screen. With the overlay of the tracks, it will be clearly visible where in the frame the objects are detected the best. According to this input, it is much easier to configure your needed use cases properly and have good results with the first configuration try.
With track calibration history enabled you will be able to access the track calibration for every hour of the past 24 hours.
Enable the feature for camera streams
A slider allows you access the track calibrations of the last 24 hours
The track calibration images will be stored on the edge device and are only accessible through the Control Center. Make sure that viewing, storing, and processing of these images for up to 24 hours is compliant with your applicable data privacy regulations.
The color of the tracks are split by object class so that they can be distinguished between cars, trucks, buses, people and bicycles.
The colors of the tracks and bounding boxes are differentiated per main class. Find the legend for the colors on the question mark in the preview frame as shown in the Screenshot below.