docstr: Return the categories of measurements that this module produces
  
  object_name - return measurements made on this object (or 'Image' for image measurements)
docstr_tok: ["Return","the","categories","of","measurements","that","this","module","produces","object_name","-","return","measurements","made","on","this","object","(","or","'Image","'","for","image","measurements",")"]
code: def get_categories(self, pipeline, object_name):
      """Return the categories of measurements that this module produces
  
      object_name - return measurements made on this object (or 'Image' for image measurements)
      """
      if self.contrast_choice == BY_MODEL:
          if object_name == IMAGE:
              if (
                  self.create_class_sets.value
                  and len(self.desired_classes) > 0
              ):
                  return [M_CATEGORY, C_COUNT]
              return [M_CATEGORY]
          if object_name == self.object_name.value:
              if (
                  self.create_class_sets.value
                  and len(self.desired_classes) > 0
              ):
                  return [M_CATEGORY, C_CHILDREN]
              return [M_CATEGORY]
          elif object_name in [
              group.class_objects_name for group in self.desired_classes
          ]:
              if self.create_class_sets.value:
                  return [C_LOCATION, C_NUMBER, C_PARENT]
              return []
      else:
          if (
              (object_name == IMAGE)
              or (
                  self.contrast_choice == BY_SINGLE_MEASUREMENT
                  and object_name
                  in [
                      group.object_name.value
                      for group in self.single_measurements
                  ]
              )
              or (
                  self.contrast_choice == BY_TWO_MEASUREMENTS
                  and object_name == self.object_name
              )
          ):
              return [M_CATEGORY]
  
      return []
  
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 28 for calling the ClassifyObjects obj's underlying member method code with example usage: obj.get_categories(pipeline, object_name) and returns: list, list, list, list, list, list, list, list