def get_point_coords_wrt_box(boxes_coords, point_coords):
    """
    Convert image-level absolute coordinates to box-normalized [0, 1] x [0, 1] point cooordinates.
    Args:
        boxes_coords (Tensor): A tensor of shape (R, 4) that contains bounding boxes.
            coordinates.
        point_coords (Tensor): A tensor of shape (R, P, 2) that contains
            image-normalized coordinates of P sampled points.
    Returns:
        point_coords_wrt_box (Tensor): A tensor of shape (R, P, 2) that contains
            [0, 1] x [0, 1] box-normalized coordinates of the P sampled points.
    """
    with torch.no_grad():
        point_coords_wrt_box = point_coords.clone()
        point_coords_wrt_box[:, :, 0] -= boxes_coords[:, None, 0]
        point_coords_wrt_box[:, :, 1] -= boxes_coords[:, None, 1]
        point_coords_wrt_box[:, :, 0] = point_coords_wrt_box[:, :, 0] / (
            boxes_coords[:, None, 2] - boxes_coords[:, None, 0]
        )
        point_coords_wrt_box[:, :, 1] = point_coords_wrt_box[:, :, 1] / (
            boxes_coords[:, None, 3] - boxes_coords[:, None, 1]
        )
    return point_coords_wrt_box

    Convert image-level absolute coordinates to box-normalized [0, 1] x [0, 1] point cooordinates.
    Args:
        boxes_coords (Tensor): A tensor of shape (R, 4) that contains bounding boxes.
            coordinates.
        point_coords (Tensor): A tensor of shape (R, P, 2) that contains
            image-normalized coordinates of P sampled points.
    Returns:
        point_coords_wrt_box (Tensor): A tensor of shape (R, P, 2) that contains
            [0, 1] x [0, 1] box-normalized coordinates of the P sampled points.
    
EVA-02/det/projects/PointSup/point_sup/point_utils.py