docstr: Creates 3D bounding boxes based on carla vehicle list and camera.
docstr_tok: ["Creates","3D","bounding","boxes","based","on","carla","vehicle","list","and","camera","."]
code: def get_bounding_boxes(
      individual_rss_states, camera_transform, calibration, world
  ):
      """
      Creates 3D bounding boxes based on carla vehicle list and camera.
      """
      bounding_boxes = []
      for state in individual_rss_states:
          if (
              state.actor_calculation_mode
              != ad.rss.map.RssMode.NotRelevant
              and state.is_dangerous
          ):
              other_actor = state.get_actor(world)
              if other_actor:
                  bounding_boxes.append(
                      RssBoundingBoxVisualizer.get_bounding_box(
                          other_actor, camera_transform, calibration
                      )
                  )
      # filter objects behind camera
      bounding_boxes = [
          bb for bb in bounding_boxes if all(bb[:, 2] > 0)
      ]
      return bounding_boxes
  
imports: import glob
  import os
  import sys
  from enum import Enum
  import math
  import numpy
  import pygame
  import weakref
  import carla
  from carla import ad
label_desc: Use image node_id 4 for calling the RssBoundingBoxVisualizer obj's underlying member method code with example usage: obj.get_bounding_boxes(individual_rss_states, camera_transform, calibration, world) and returns: bounding_boxes