Semantic lidar problem in UE5 verison of CARLA

[Bestdriver411]

I used dev UE5 version of CARLA and changed nothing, just packaged it. When I use the Semantic lidar in map "Mine_01", things went wrong. It cannot distinguish between mountains and roads, and it will name the cloud of moutians and roads as label 10: Foliage, name the cloud of the vehicle as label 14: TrafficSign. As the pic below:

But things went right when I use the semantic camera at the same position. The camera could distinguish between mountains and roads.

Below is my code:

def semantic_camera_callback(data, world):
    if not world.start_collecting or not RECORD_SEM_CAM:
        return
    data.convert(cc.CityScapesPalette)
    img = np.frombuffer(data.raw_data, dtype=np.uint8)
    img = img.reshape((data.height, data.width, 4))[:, :, :3].copy()
    with cache_lock:
        sensor_cache['semantic_images'] = (data.frame, img)


def semantic_lidar_callback(data, world):
    if not world.start_collecting or not RECORD_SEM_LIDAR:
        return

    points_list = []
    for detection in data:
        points_list.append([
            detection.point.x,
            detection.point.y,
            detection.point.z,
            detection.cos_inc_angle, 
            float(detection.object_idx),  
            float(detection.object_tag)  
        ])
  
    if len(points_list) == 0:
            return
  
    points = np.array(points_list, dtype=np.float32)
  
    with cache_lock:
        sensor_cache['semantic_lidar'] = (data.frame, points)

...

    sem_cam_bp = blue_print_lib.find('sensor.camera.semantic_segmentation')
    sem_cam_bp.set_attribute('image_size_x', '800')
    sem_cam_bp.set_attribute('image_size_y', '600')
    sem_cam_bp.set_attribute('fov', '90')
    sem_cam_bp.set_attribute('sensor_tick', str(RECORD_INTERVAL))
    sem_cam_transform = carla.Transform(carla.Location(x=0, y=0, z=SEM_SENSOR_HEIGHT),
                                                carla.Rotation(pitch=-90, yaw=0, roll=0))
    sem_cam = sim_world.spawn_actor(sem_cam_bp, sem_cam_transform, attach_to=world.player)
    actor_list.append(sem_cam)
    sem_cam.listen(lambda data: semantic_camera_callback(data, world))
    
    sem_lidar_bp = blue_print_lib.find('sensor.lidar.ray_cast_semantic')
    sem_lidar_bp.set_attribute('channels', '64')
    sem_lidar_bp.set_attribute('points_per_second', '600000')
    sem_lidar_bp.set_attribute('rotation_frequency', '10')
    sem_lidar_bp.set_attribute('range', '100')
    sem_lidar_bp.set_attribute('horizontal_fov', '360')
    sem_lidar_bp.set_attribute('upper_fov', '30')
    sem_lidar_bp.set_attribute('lower_fov', '-30')
    sem_lidar_bp.set_attribute('sensor_tick', str(RECORD_INTERVAL))
    sem_lidar_transform = carla.Transform(carla.Location(x=0, y=0, z=SEM_SENSOR_HEIGHT),
                                                  carla.Rotation(pitch=0, yaw=0, roll=90))
    sem_lidar = sim_world.spawn_actor(sem_lidar_bp, sem_lidar_transform, attach_to=world.player)
    actor_list.append(sem_lidar)
    sem_lidar.listen(lambda data: semantic_lidar_callback(data, world))