I worked on understanding the YOLOv8 structure and how to utilize it with the Isaac-ROS based environment. Specifically, I looked deeper into the launching and the scripts written for the visualization of the image detection that we got working before the break. I took the python visualization script and began translating it to C++ since we want the majority of our YOLOv8 code to be running in C++ for the speed. This script creates the visualizer class that subscribes to the detections_output topic and registers a callback for updates on this topic which allow the visualizer to display the bounding boxes. My next steps would be to write a new file for creating a publisher node that would take images from a camera and publish it to the “images” topic that our visualizer would take as an input.
