code: def test_mask_with_objects():
      numpy.random.seed()
      input_image = numpy.random.uniform(size=(20, 10))
      input_objects = numpy.zeros((20, 10), dtype=int)
      input_objects[2:7, 3:8] = 1
      input_objects[12:17, 3:8] = 2
      workspace, module = make_workspace(
          input_image, crop_objects=input_objects
      )
      module.shape.value = cellprofiler.modules.crop.SH_OBJECTS
      module.objects_source.value = CROP_OBJECTS
      module.remove_rows_and_columns.value = (
          cellprofiler.modules.crop.RM_NO
      )
      module.run(workspace)
      output_image = workspace.image_set.get_image(OUTPUT_IMAGE)
      assert output_image.has_masking_objects
      assert numpy.all(input_objects == output_image.labels)
      assert numpy.all(output_image.mask == (input_objects > 0))
  
imports: import numpy
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import GROUP_INDEX, GROUP_NUMBER, COLTYPE_INTEGER
  import cellprofiler.modules.crop
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.workspace
label_desc: Use image node_id 16 for calling a global function with example usage: test_mask_with_objects() without return types