Training YOLO for Lane Detection: Preprocess the lane images and annotate them for training YOLO. Train YOLO with the annotated dataset, adjusting parameters for optimal lane recognition. Evaluation: Evaluate YOLO's accuracy in lane detection using a separate validation dataset. Measure its real-time performance while detecting lanes, simulating movement if needed. Write a Python program that trains a YOLO for lane detection and evaluates YOLO accuracy in lane detection. Measure its real-time performance while detecting lanes, simulating movement.