Hi everyone,
I’m currently working on a project that integrates OpenCV to perform real-time object detection during my Roblox gameplay. The goal is to identify specific in-game elements like enemies, collectibles, or obstacles and automate reactions in response to these detections. I’ve been using OpenCV’s cv2.dnn module with YOLOv4, but I’m facing performance challenges, particularly with maintaining a high frame rate when processing the video stream in real-time.
I’m running this setup alongside a modified Roblox (“delta executer”) game software that automates certain actions based on the object detections. While it works well, I’m curious if anyone here has experience optimizing OpenCV’s performance for gaming environments. Any advice on hardware setups, CUDA usage, or even alternative models that might be better suited for real-time applications would be greatly appreciated.
Looking forward to hearing your suggestions!