class_docstr: Process and show the image batch and its associated label using matplotlib.
code: def show_load_sample(
      self,
      samples: List[Any],
      running_stage: RunningStage,
      limit_nb_samples: int,
      figsize: Tuple[int, int] = (6.4, 4.8),
  ):
      win_title: str = f"{running_stage} - show_load_sample"
      self._show_images_and_labels(
          samples, len(samples), win_title, limit_nb_samples, figsize
      )
  
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 4 for calling the SegmentationMatplotlibVisualization obj's underlying member method code with example usage: obj.show_load_sample(samples, running_stage, limit_nb_samples, figsize) without return types