docstr: Visualize a dataset.
  
  Example:
      Minimal example for visualizing a dataset::
          import open3d.ml.torch as ml3d  # or open3d.ml.tf as ml3d
  
          dataset = ml3d.datasets.SemanticKITTI(dataset_path='/path/to/SemanticKITTI/')
          vis = ml3d.vis.Visualizer()
          vis.visualize_dataset(dataset, 'all', indices=range(100))
  
  Args:
      dataset: The dataset to use for visualization.
      split: The dataset split to be used, such as 'training'
      indices: An iterable with a subset of the data points to visualize, such as [0,2,3,4].
      width: The width of the visualization window.
      height: The height of the visualization window.
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code: def visualize_dataset(
      self, dataset, split, indices=None, width=1024, height=768
  ):
      """Visualize a dataset.
  
      Example:
          Minimal example for visualizing a dataset::
              import open3d.ml.torch as ml3d  # or open3d.ml.tf as ml3d
  
              dataset = ml3d.datasets.SemanticKITTI(dataset_path='/path/to/SemanticKITTI/')
              vis = ml3d.vis.Visualizer()
              vis.visualize_dataset(dataset, 'all', indices=range(100))
  
      Args:
          dataset: The dataset to use for visualization.
          split: The dataset split to be used, such as 'training'
          indices: An iterable with a subset of the data points to visualize, such as [0,2,3,4].
          width: The width of the visualization window.
          height: The height of the visualization window.
  
      """
      # Setup the labels
      lut = LabelLUT()
      color_map = dataset.color_map
      for id_color, val in dataset.label_to_names.items():
          lut.add_label(
              str(id_color), id_color, color=color_map[id_color]
          )
      self.set_lut("labels", lut)
  
      self._consolidate_bounding_boxes = True
      self._init_dataset(dataset, split, indices)
      self._visualize("Open3D - " + dataset.name, width, height)
  
file_path: lightning-flash/src/flash/pointcloud/segmentation/open3d_ml/app.py
imports: import torch
  from flash.core.data.data_module import DataModule
  from flash.core.data.io.input import DataKeys
  from flash.core.utilities.imports import _TOPIC_POINTCLOUD_AVAILABLE
label_desc: Use image node_id 1 for calling the Visualizer obj's underlying member method code with example usage: obj.visualize_dataset(dataset, split, indices, width, height) without return types