class_docstr: Rescales an image observation to a given size. The target size does not
  necessarily keep the aspect ratio of the original observation.
  Warning: this requires the input observation to be of type uint8 due to scipy requirements!
docstr: :param output_observation_space: the output observation space
code: def __init__(
      self, output_observation_space: PlanarMapsObservationSpace
  ):
      """
      :param output_observation_space: the output observation space
      """
      super().__init__()
      self.output_observation_space = output_observation_space
  
      if not isinstance(
          output_observation_space, PlanarMapsObservationSpace
      ):
          raise ValueError(
              "The rescale filter only applies to observation spaces that inherit from "
              "PlanarMapsObservationSpace. This includes observations which consist of a set of 2D "
              "images or an RGB image. Instead the output observation space was defined as: {}".format(
                  output_observation_space.__class__
              )
          )
  
      self.planar_map_output_shape = copy.copy(
          self.output_observation_space.shape
      )
      self.planar_map_output_shape = np.delete(
          self.planar_map_output_shape,
          self.output_observation_space.channels_axis,
      )
  
file_path: coach/rl_coach/filters/observation/observation_rescale_to_size_filter.py
imports: import copy
  from skimage.transform import resize
  import numpy
  from rl_coach.core_types import ObservationType
  from rl_coach.filters.observation.observation_filter import ObservationFilter
  from rl_coach.spaces import ObservationSpace, PlanarMapsObservationSpace, ImageObservationSpace
label_desc: Use image node_id 1 to create a new ObservationRescaleToSizeFilter object from inherited base classes: ObservationFilter with example: obj = ObservationRescaleToSizeFilter(output_observation_space)