code: def _extract_neighbours(regions):
      def intersect(a, b):
          if (
              (
                  a["min_x"] < b["min_x"] < a["max_x"]
                  and a["min_y"] < b["min_y"] < a["max_y"]
              )
              or (
                  a["min_x"] < b["max_x"] < a["max_x"]
                  and a["min_y"] < b["max_y"] < a["max_y"]
              )
              or (
                  a["min_x"] < b["min_x"] < a["max_x"]
                  and a["min_y"] < b["max_y"] < a["max_y"]
              )
              or (
                  a["min_x"] < b["max_x"] < a["max_x"]
                  and a["min_y"] < b["min_y"] < a["max_y"]
              )
          ):
              return True
          return False
  
      R = list(regions.items())
      neighbours = []
      for cur, a in enumerate(R[:-1]):
          for b in R[cur + 1 :]:
              if intersect(a[1], b[1]):
                  neighbours.append((a, b))
  
      return neighbours
  
imports: import sys
  from past.builtins import cmp
  import skimage.io
  import skimage.feature
  import skimage.color
  import skimage.transform
  import skimage.util
  import skimage.segmentation
  import numpy
label_desc: Use image node_id 11 for calling a global function with example usage: _extract_neighbours(regions) and returns: neighbours, False, True