code: def test_declump_none(
      image,
      module,
      image_set,
      workspace,
  ):
      module.use_advanced.value = True
  
      module.declump_method.value = "None"
  
      module.x_name.value = "input_image"
  
      module.y_name.value = "watershed"
  
      if image.multichannel:
          image.pixel_data = skimage.color.rgb2gray(image.pixel_data)
  
      # Watershed requires a thresholded input
      input_image = image.pixel_data > skimage.filters.threshold_otsu(
          image.pixel_data
      )
  
      image_set.add(
          "input_image",
          cellprofiler_core.image.Image(
              image=input_image,
              convert=False,
              dimensions=image.dimensions,
          ),
      )
  
      module.run(workspace)
  
      actual = workspace.get_objects("watershed")
  
      expected = scipy.ndimage.label(input_image)[0]
  
      numpy.testing.assert_array_equal(actual.segmented, expected)
  
imports: import mahotas
  import numpy
  import numpy.testing
  import pytest
  import scipy.ndimage
  import skimage.color
  import skimage.feature
  import skimage.filters
  import skimage.filters.rank
  import skimage.segmentation
  import skimage.transform
  import cellprofiler_core.image
  import cellprofiler.modules.watershed
label_desc: Use image node_id 14 for calling a global function with example usage: test_declump_none(image, module, image_set, workspace) without return types