code: def test_ijv():
      numpy.random.seed(0)
      image = numpy.random.uniform(size=(50, 50, 3)).astype(
          numpy.float32
      )
      image[0, 0] = 1
      labels0 = numpy.zeros(image.shape[:2], int)
      labels0[20:30, 20:30] = 1
      labels1 = numpy.zeros(image.shape[:2], int)
      labels1[25:35, 25:35] = 2
      labels = [labels0, labels1]
      expected = image.copy()
      mask = numpy.zeros(image.shape[:2], bool)
      mask[20:30, 20] = True
      mask[20:30, 29] = True
      mask[20, 20:30] = True
      mask[29, 20:30] = True
      mask[25:35, 25] = True
      mask[25:35, 34] = True
      mask[25, 25:35] = True
      mask[34, 25:35] = True
      expected[mask, 0] = 1
      expected[mask, 1:] = 0
      workspace, module = make_workspace(image, labels=labels)
      module.wants_color.value = (
          cellprofiler.modules.overlayoutlines.WANTS_COLOR
      )
      module.outlines[0].color.value = "Red"
      module.line_mode.value = "Inner"
      module.run(workspace)
      output_image = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
      numpy.testing.assert_array_equal(
          output_image.pixel_data, expected
      )
  
imports: import io
  import numpy
  import numpy.testing
  import skimage.color
  import skimage.segmentation
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.module
  import cellprofiler.modules.overlayoutlines
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 13 for calling a global function with example usage: test_ijv() without return types