code: def thin(binimg, max_iter=-1):
      """
      skel = thin(binimg)
  
      Skeletonisation by thinning
  
      Parameters
      ----------
      binimg : ndarray
          Binary input image
      max_iter : int, optional
          Maximum number of iterations (set to a negative number, the default, to
          run full skeletonization)
  
      Returns
      -------
      skel : Skeletonised version of `binimg`
      """
      from .bbox import bbox
      from ._thin import thin as _thin
  
      res = np.zeros_like(binimg)
      min0, max0, min1, max1 = bbox(binimg)
      r, c = (max0 - min0, max1 - min1)
  
      image_exp = np.zeros((r + 2, c + 2), bool)
      image_exp[1 : r + 1, 1 : c + 1] = binimg[min0:max0, min1:max1]
      imagebuf = np.empty((r + 2, c + 2), bool)
  
      _thin(image_exp, imagebuf, int(max_iter))
      res[min0:max0, min1:max1] = image_exp[1 : r + 1, 1 : c + 1]
      return res
  
label_desc: Use image node_id 1 for calling a global function with example usage: thin(binimg, max_iter) and returns: res