class_docstr: !
  @brief Class represents segmentation algorithm syncsegm. 
  @details syncsegm is a bio-inspired algorithm that is based on double-layer oscillatory network that uses modified Kuramoto model.
           Algorithm extracts colors and colored objects. It uses only CCORE (C++ implementation of pyclustering) parts to implement the algorithm.
  
           CCORE option is True by default to use sync network in the pyclustering core - C/C++ shared library for processing that significantly increases performance.
  
  Example:
  @code
      # create oscillatory for image segmentaion - extract colors (radius 128) and objects (radius 4), 
      # and ignore noise (segments with size that is less than 10 pixels)
      algorithm = syncsegm(128, 4, 10);
      
      # extract segments (colors and objects)
      analyser = algorithm(path_to_file);
      
      # obtain segmentation results (only colors - from the first layer)
      color_segments = analyser.allocate_colors(0.01, 10);
      draw_image_mask_segments(path_to_file, color_segments);
      
      # obtain segmentation results (objects - from the second layer)
      object_segments = analyser.allocate_objects(0.01, 10);
      draw_image_mask_segments(path_to_file, object_segments);
  @endcode
docstr: !
  @brief Extracts coordinates of specified image segment.
  
  @param[in] image_size (list): Image size presented as a [width x height].
  @param[in] color_segment (list): Image segment whose coordinates should be extracted.
  
  @return (list) Coordinates of each pixel.
docstr_tok: ["!","@","brief","Extracts","coordinates","of","specified","image","segment",".","@","param","[","in","]","image_size","(","list",")",":","Image","size","presented","as","a","[","width","x","height","]",".","@","param","[","in","]","color_segment","(","list",")",":","Image","segment","whose","coordinates","should","be","extracted",".","@","return","(","list",")","Coordinates","of","each","pixel","."]
code: def __extract_location_coordinates(self, image_size, color_segment):
      """!
      @brief Extracts coordinates of specified image segment.
  
      @param[in] image_size (list): Image size presented as a [width x height].
      @param[in] color_segment (list): Image segment whose coordinates should be extracted.
  
      @return (list) Coordinates of each pixel.
  
      """
      coordinates = []
      for index in color_segment:
          y = floor(index / image_size[0])
          x = index - y * image_size[0]
  
          coordinates.append([x, y])
  
      return coordinates
  
imports: from math import floor
  from PIL import Image
  from pyclustering.cluster.syncnet import syncnet
  from pyclustering.core.wrapper import ccore_library
  from pyclustering.nnet import solve_type, initial_type
  from pyclustering.nnet.sync import sync_visualizer
  from pyclustering.utils import read_image
label_desc: Use image node_id 6 for calling the syncsegm obj's underlying member method code with example usage: obj.__extract_location_coordinates(image_size, color_segment) and returns: coordinates