Real-time poker card detection using YOLOv8, Pytorch and OpenCV. Built with Python for object recognition and ranking of poker hands.

This project uses real-time object detection with YOLOv8 to identify and evaluate poker hands from video streams. It classifies playing cards, ranks hands, and ensures high accuracy under varying conditions. Built with Python, OpenCV, and TensorFlow, it’s ideal for poker automation and AI-driven analysis.