code: def visualize_cameras(caps, size=1):
      fig = plt.figure()
      ax = fig.add_subplot(projection="3d")
      for i, cap in enumerate(caps):
          color = next(ax._get_lines.prop_cycler)["color"]
          pts = np.array(cap.camera_poly(size))
          ax.scatter(pts[:, 0], pts[:, 1], pts[:, 2], c=color)
          for j in range(1, 5):
              ax.plot(
                  [pts[0, 0], pts[j, 0]],
                  [pts[0, 1], pts[j, 1]],
                  [pts[0, 2], pts[j, 2]],
                  c=color,
              )
          ax.plot(
              [pts[1, 0], pts[2, 0]],
              [pts[1, 1], pts[2, 1]],
              [pts[1, 2], pts[2, 2]],
              c=color,
          )
          ax.plot(
              [pts[2, 0], pts[3, 0]],
              [pts[2, 1], pts[3, 1]],
              [pts[2, 2], pts[3, 2]],
              c=color,
          )
          ax.plot(
              [pts[3, 0], pts[4, 0]],
              [pts[3, 1], pts[4, 1]],
              [pts[3, 2], pts[4, 2]],
              c=color,
          )
          ax.plot(
              [pts[4, 0], pts[1, 0]],
              [pts[4, 1], pts[1, 1]],
              [pts[4, 2], pts[1, 2]],
              c=color,
          )
      set_axes_equal(ax)
      plt.show()
  
imports: import os
  import random
  import numpy
  import open3d
  import torch
  import pytorch3d
  import matplotlib.pyplot
  import matplotlib
  from scipy import ndimage
  from tqdm import tqdm
  from models.smpl import SMPL, vertices2joints
label_desc: Use image node_id 9 for calling a global function with example usage: visualize_cameras(caps, size) without return types