code: def make_workspace_classifier(
      object_dict={}, image_dict={}, grouplist=[]
  ):
      """Make a workspace for testing FilterByObjectMeasurement"""
      module = cellprofiler.modules.classifyobjects.ClassifyObjects()
      module.contrast_choice.value = (
          cellprofiler.modules.classifyobjects.BY_MODEL
      )
      module.object_name.value = OBJECTS_NAME
      module.create_class_sets.value = True
      for group in range(len(grouplist)):
          if group >= len(module.desired_classes):
              settings_group = cellprofiler_core.setting.SettingsGroup()
              settings_group.can_delete = False
              settings_group.append(
                  "class_name",
                  cellprofiler_core.setting.choice.Choice(
                      "text", grouplist
                  ),
              )
              settings_group.append(
                  "class_objects_name",
                  cellprofiler_core.setting.text.LabelName(
                      "text", "dummy"
                  ),
              )
              module.desired_classes.append(settings_group)
          module.desired_classes[group].class_name.value = str(
              grouplist[group]
          )
          module.desired_classes[group].class_objects_name.value = str(
              grouplist[group]
          )
      pipeline = cellprofiler_core.pipeline.Pipeline()
      object_set = cellprofiler_core.object.ObjectSet()
      image_set_list = cellprofiler_core.image.ImageSetList()
      image_set = image_set_list.get_image_set(0)
      workspace = cellprofiler_core.workspace.Workspace(
          pipeline,
          module,
          image_set,
          object_set,
          cellprofiler_core.measurement.Measurements(),
          image_set_list,
      )
      for key in list(image_dict.keys()):
          image_set.add(
              key, cellprofiler_core.image.Image(image_dict[key])
          )
      for key in list(object_dict.keys()):
          o = cellprofiler_core.object.Objects()
          o.segmented = object_dict[key]
          object_set.add_objects(o, key)
      return workspace, module
  
imports: import contextlib
  import os
  import pickle
  import tempfile
  import numpy
  import pytest
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import COLTYPE_FLOAT, COLTYPE_INTEGER
  import cellprofiler.modules.classifyobjects
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.setting
  import cellprofiler_core.workspace
label_desc: Use image node_id 2 for calling a global function with example usage: make_workspace_classifier(object_dict, image_dict, grouplist) and returns: workspace,  module