code: def plot_all_heatmaps(image, detections, figsize=0.1, num_classes=6):
      """Plot."""
      if figsize:
          print(figsize)
      figure, axis = plt.subplots(
          1, num_classes, figsize=(num_classes * 5, 5)
      )
      for class_id in range(num_classes):
          for k, color in [
              ["centers_sigmoid", [0, 1, 0]],
              ["centers_nms", [1, 0, 0]],
          ]:
              axis[class_id].imshow(
                  np.concatenate(
                      [
                          image.astype(float) / 255.0,
                          0.5 * np.ones([256, 256, 1]),
                      ],
                      axis=-1,
                  )
              )
              centers = detections[k][:, :, class_id].numpy()
              axis[class_id].imshow(
                  resize_heatmap(centers, color=color)
              )
      return figure
  
imports: import os
  import pickle
  import re
  import matplotlib.pyplot
  import numpy
  import tensorflow
  from tensorflow_graphics.projects.points_to_3Dobjects.utils import tf_utils
  from google3.pyglib import gfile
label_desc: Use image node_id 11 for calling a global function with example usage: plot_all_heatmaps(image, detections, figsize, num_classes) and returns: figure