code: def templateSyncsegmSegmentation(
      image_source,
      radius_color,
      radius_object,
      noise_size,
      expected_color_segments,
      expected_object_segments,
      collect_dynamic,
      ccore_flag,
  ):
      result_testing = False
      color_segments, object_segments = [], []
  
      for _ in range(0, 10, 1):
          algorithm = syncsegm(
              radius_color, radius_object, noise_size, ccore=ccore_flag
          )
          analyser = algorithm.process(
              image_source, collect_dynamic, 0.9995, 0.9995
          )
  
          color_segments = analyser.allocate_colors()
          object_segments = analyser.allocate_objects(0.2)
  
          if (len(color_segments) != expected_color_segments) or (
              len(object_segments) != expected_object_segments
          ):
              continue
  
          result_testing = True
          break
  
      assertion.eq(expected_color_segments, len(color_segments))
      assertion.eq(expected_object_segments, len(object_segments))
      assertion.true(result_testing)
  
imports: import matplotlib
  from pyclustering.tests.assertion import assertion
  from pyclustering.nnet.syncsegm import syncsegm, syncsegm_visualizer
  from pyclustering.utils import draw_image_mask_segments
label_desc: Use image node_id 1 for calling the SyncsegmTestTemplates obj's underlying member method code with example usage: obj.templateSyncsegmSegmentation(image_source, radius_color, radius_object, noise_size, expected_color_segments, expected_object_segments, collect_dynamic, ccore_flag) without return types