code: def create_settings(self):
      self.objects_x = LabelSubscriber(
          "Select initial object set",
          "None",
          doc="""Select an object set which you want to add objects to.""",
      )
  
      self.objects_y = LabelSubscriber(
          "Select object set to combine",
          "None",
          doc="""Select an object set which you want to add to the initial set.""",
      )
  
      self.merge_method = Choice(
          "Select how to handle overlapping objects",
          choices=["Merge", "Preserve", "Discard", "Segment"],
          doc="""\
  When combining sets of objects, it is possible that both sets had an object in the
  same location. Use this setting to choose how to handle objects which overlap with
  each other.
          
  - Selecting "Merge" will make overlapping objects combine into a single object, taking
    on the label of the object from the initial set. When an added object would overlap
    with multiple objects from the initial set, each pixel of the added object will be
    assigned to the closest object from the initial set. This is primarily useful when
    the same objects appear in both sets.
          
  - Selecting "Preserve" will protect the initial object set. Any overlapping regions
    from the second set will be ignored in favour of the object from the initial set.
          
  - Selecting "Discard" will only add objects which do not have any overlap with objects
    in the initial object set.
          
  - Selecting "Segment" will combine both object sets and attempt to re-draw segmentation to
    separate objects which overlapped. Note: This is less reliable when more than
    two objects were overlapping. If two object sets genuinely occupy the same space
    it may be better to consider them seperately.
           """,
      )
  
      self.output_object = LabelName(
          "Name the combined object set",
          "CombinedObjects",
          doc="""\
  Enter the name for the combined object set. These objects will be available for use in
  subsequent modules.""",
      )
  
imports: import numpy
  import scipy.ndimage
  import skimage.morphology
  import skimage.segmentation
  from cellprofiler_core.module import Identify
  from cellprofiler_core.object import Objects
  from cellprofiler_core.setting.choice import Choice
  from cellprofiler_core.setting.subscriber import LabelSubscriber
  from cellprofiler_core.setting.text import LabelName
  from cellprofiler_core.utilities.core.module.identify import add_object_count_measurements
  from cellprofiler_core.utilities.core.module.identify import get_object_measurement_columns
  from cellprofiler_core.utilities.core.module.identify import add_object_location_measurements
  from cellprofiler_library.modules import combineobjects
label_desc: Use image node_id 1 for calling the CombineObjects obj's underlying member method code with example usage: obj.create_settings() without return types