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.
We suggest to use this calibration support for any Traffic monitoring use case as well as Barrierless parking use case.
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.