class_docstr: Process and show the image batch and its associated label using matplotlib.
code: def __init__(self, labels_map: Dict[int, Tuple[int, int, int]]):
      super().__init__()
  
      self.max_cols: int = 4  # maximum number of columns we accept
      self.block_viz_window: bool = (
          True  # parameter to allow user to block visualisation windows
      )
      self.labels_map: Dict[int, Tuple[int, int, int]] = labels_map
  
file_path: lightning-flash/src/flash/image/segmentation/viz.py
imports: from typing import Any, Dict, List, Tuple, Union
  import numpy
  import torch
  from torch import Tensor
  from flash.core.data.base_viz import BaseVisualization
  from flash.core.data.io.input import DataKeys
  from flash.core.utilities.imports import _MATPLOTLIB_AVAILABLE, Image, requires
  from flash.core.utilities.stages import RunningStage
  from flash.image.segmentation.output import SegmentationLabelsOutput
label_desc: Use image node_id 1 to create a new SegmentationMatplotlibVisualization object from inherited base classes: BaseVisualization with example: obj = SegmentationMatplotlibVisualization(labels_map)