class_docstr: Merge text components and construct boundaries of text instances.
  
  Args:
      link_thr (float): The edge score threshold.
docstr: Rescale boundaries via scale_factor.
  
  Args:
      boundaries (list[list[float]]): The boundary list. Each boundary
      with size 2k+1 with k>=4.
      scale_factor(ndarray): The scale factor of size (4,).
  
  Returns:
      boundaries (list[list[float]]): The scaled boundaries.
docstr_tok: ["Rescale","boundaries","via","scale_factor",".","Args",":","boundaries","(","list","[","list","[","float","]","]",")",":","The","boundary","list",".","Each","boundary","with","size","2k+1","with","k",">","=4",".","scale_factor","(","ndarray",")",":","The","scale","factor","of","size","(","4",",",")",".","Returns",":","boundaries","(","list","[","list","[","float","]","]",")",":","The","scaled","boundaries","."]
code: def resize_boundary(self, boundaries, scale_factor):
      """Rescale boundaries via scale_factor.
  
      Args:
          boundaries (list[list[float]]): The boundary list. Each boundary
          with size 2k+1 with k>=4.
          scale_factor(ndarray): The scale factor of size (4,).
  
      Returns:
          boundaries (list[list[float]]): The scaled boundaries.
      """
      boxes = []
      scores = []
      for b in boundaries:
          sz = len(b)
          scores.append(b[-1])
          b = (
              (
                  np.array(b[: sz - 1])
                  * (
                      np.tile(
                          scale_factor[:2], int((sz - 1) / 2)
                      ).reshape(1, sz - 1)
                  )
              )
              .flatten()
              .tolist()
          )
          boxes.append(np.array(b).reshape([-1, 2]))
      return boxes, scores
  
imports: import functools
  import operator
  import numpy
  import paddle
  from numpy.linalg import norm
  import cv2
label_desc: Use image node_id 3 for calling the DRRGPostprocess obj's underlying member method code with example usage: obj.resize_boundary(boundaries, scale_factor) and returns: boxes,  scores