ValueError: expected 4D input (got 3D input)

yolo4d YOLO4D is a deep learning approach that uses 4D tensors to incorporate temporal information in 3D object detection from LiDAR point clouds. It extends YOLO v2 with Convolutional LSTM. In addition to the YOLO framework, the field of object detection and image processing has developed several other notable methods. Techniques such as R-CNN (Region-based

yolo4d, Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLOv8 is.