code: def main(opt):
      scene = neuman_helper.NeuManReader.read_scene(
          opt.scene_dir,
          tgt_size=None,
          normalize=True,
          smpl_type="optimized",
      )
      scene_pcd = o3d.geometry.PointCloud()
      scene_pcd.points = o3d.utility.Vector3dVector(
          scene.point_cloud[:, :3]
      )
      scene_pcd.colors = o3d.utility.Vector3dVector(
          scene.point_cloud[:, 3:] / 255
      )
  
      human_pcds = []
      cam_poly_list = []
      cmap = matplotlib.cm.get_cmap("Spectral")
      for i, cap in enumerate(scene.captures):
          temp = o3d.geometry.PointCloud()
          temp.points = o3d.utility.Vector3dVector(
              scene.verts[i][:, :3]
          )
          rgba = cmap(i / len(scene.captures))
          color = np.zeros_like(scene.verts[i][:, :3])
          color[:, 0] = rgba[0]
          color[:, 1] = rgba[1]
          color[:, 2] = rgba[2]
          temp.colors = o3d.utility.Vector3dVector(color)
          human_pcds.append(temp)
          cam_pts = np.array(cap.camera_poly(0.1))
          lns = [
              [0, 1],
              [0, 2],
              [0, 3],
              [0, 4],
              [1, 2],
              [2, 3],
              [3, 4],
              [4, 1],
          ]
          cam_poly = o3d.geometry.LineSet()
          cam_poly.points = o3d.utility.Vector3dVector(cam_pts)
          cam_poly.lines = o3d.utility.Vector2iVector(lns)
          cam_poly_list.append(cam_poly)
      o3d.visualization.draw_geometries(
          [scene_pcd, *human_pcds, *cam_poly_list]
      )
  
imports: import argparse
  import imageio
  import open3d
  import numpy
  import matplotlib
  from data_io import neuman_helper
label_desc: Use image node_id 1 for calling a global function with example usage: main(opt) without return types