docstr: Return a numpy array containing the image that will be rendered to the screen.
  This can be different from the observation. For example, mujoco's observation is a measurements vector.
  :return: numpy array containing the image that will be rendered to the screen
docstr_tok: ["Return","a","numpy","array","containing","the","image","that","will","be","rendered","to","the","screen",".","This","can","be","different","from","the","observation",".","For","example",",","mujoco","'s","observation","is","a","measurements","vector",".",":","return",":","numpy","array","containing","the","image","that","will","be","rendered","to","the","screen"]
code: def get_rendered_image(self) -> np.ndarray:
      """
      Return a numpy array containing the image that will be rendered to the screen.
      This can be different from the observation. For example, mujoco's observation is a measurements vector.
      :return: numpy array containing the image that will be rendered to the screen
      """
      image = [self.state[camera.name] for camera in self.scene.sensors]
      image = np.vstack(image)
      return image
  
imports: import random
  import sys
  from os import path, environ
  from rl_coach.logger import screen
  from rl_coach.filters.action.partial_discrete_action_space_map import PartialDiscreteActionSpaceMap
  from rl_coach.filters.observation.observation_rgb_to_y_filter import ObservationRGBToYFilter
  from rl_coach.filters.observation.observation_to_uint8_filter import ObservationToUInt8Filter
  import os
  import signal
  import logging
  import subprocess
  import numpy
  from rl_coach.environments.environment import Environment, EnvironmentParameters, LevelSelection
  from rl_coach.spaces import BoxActionSpace, ImageObservationSpace, StateSpace, VectorObservationSpace
  from rl_coach.utils import get_open_port, force_list
  from enum import Enum
  from typing import List, Union
  from rl_coach.base_parameters import VisualizationParameters
  from rl_coach.filters.filter import InputFilter, NoOutputFilter
  from rl_coach.filters.observation.observation_rescale_to_size_filter import ObservationRescaleToSizeFilter
  from rl_coach.filters.observation.observation_stacking_filter import ObservationStackingFilter
label_desc: Use image node_id 10 for calling the CarlaEnvironment obj's underlying member method code with example usage: obj.get_rendered_image() and returns: image