code: def display_classifier_model(self, workspace, figure):
      if get_headless():
          return
      import wx
  
      cmap = figure.return_cmap()
  
      figure.set_subplots((2, 2))
  
      input_labels = workspace.display_data.input_objects
      ax = figure.subplot_imshow_labels(
          0, 0, input_labels, self.object_name.value
      )
  
      class_labels = workspace.display_data.labeled_classes
      figure.subplot_imshow_labels(
          1,
          0,
          class_labels,
          "Classified Objects",
          sharexy=ax,
          colormap=cmap,
      )
      class_counts = workspace.display_data.class_counts
      ids_dict = workspace.display_data.identities
      data = list(
          zip(
              [""] * len(class_counts),
              ids_dict.values(),
              ids_dict.keys(),
              class_counts,
          )
      )
      figure.subplot_table(
          1,
          1,
          data,
          col_labels=("     ", "ID", "Class Name", "Count"),
      )
      # Fetch the grid object and recolour the left column to match the displayed plot cmap
      table = figure.widgets[-1][-1]
      for i in ids_dict.values():
          color = cmap(i)
          col = wx.Colour(
              color[0] * 255, color[1] * 255, color[2] * 255
          )
          table.SetCellBackgroundColour(i - 1, 0, col)
  
imports: import functools
  import os
  import numpy
  from cellprofiler.modules import _help
  from cellprofiler.utilities.rules import Rules
  from cellprofiler_core.constants.measurement import COLTYPE_FLOAT, M_LOCATION_CENTER_X, M_LOCATION_CENTER_Y, COLTYPE_VARCHAR, C_COUNT, C_CHILDREN, C_LOCATION, C_NUMBER, C_PARENT, FTR_OBJECT_NUMBER, FTR_CENTER_X, FTR_CENTER_Y, FTR_CENTER_Z
  from cellprofiler_core.constants.measurement import COLTYPE_INTEGER
  from cellprofiler_core.constants.measurement import IMAGE
  from cellprofiler_core.image import Image
  from cellprofiler_core.module import Module
  from cellprofiler_core.object import Objects
  from cellprofiler_core.preferences import get_default_colormap, get_headless
  from cellprofiler_core.setting import Binary
  from cellprofiler_core.setting import Divider
  from cellprofiler_core.setting import HiddenCount
  from cellprofiler_core.setting import Measurement
  from cellprofiler_core.setting import SettingsGroup
  from cellprofiler_core.setting import ValidationError
  from cellprofiler_core.setting.choice import Choice
  from cellprofiler_core.setting.do_something import DoSomething
  from cellprofiler_core.setting.do_something import RemoveSettingButton
  from cellprofiler_core.setting.subscriber import LabelSubscriber
  from cellprofiler_core.setting.text import Alphanumeric, Directory, Filename, LabelName
  from cellprofiler_core.setting.text import Float
  from cellprofiler_core.setting.text import ImageName
  from cellprofiler_core.setting.text import Integer
  from cellprofiler_core.setting.text import Text
  from cellprofiler_core.constants.measurement import FF_CHILDREN_COUNT
  from cellprofiler_core.constants.measurement import FF_COUNT
  from cellprofiler_core.constants.measurement import FF_PARENT
  from cellprofiler_core.module.image_segmentation import ImageSegmentation
label_desc: Use image node_id 16 for calling the ClassifyObjects obj's underlying member method code with example usage: obj.display_classifier_model(workspace, figure) without return types