class_docstr: Args:
      input_shape (int): network input image size
      ori_shape (int): ori image shape of before padding
      scale_factor (float): scale factor of ori image
      enable_mkldnn (bool): whether to open MKLDNN
class_docstr_tok: ["Args",":","input_shape","(","int",")",":","network","input","image","size","ori_shape","(","int",")",":","ori","image","shape","of","before","padding","scale_factor","(","float",")",":","scale","factor","of","ori","image","enable_mkldnn","(","bool",")",":","whether","to","open","MKLDNN"]
code: def __call__(self, lanes_list):
      lanes = self.get_lanes(lanes_list)
      return lanes
  
imports: import numpy
  import paddle
  import paddle.nn
  from scipy.special import softmax
  from scipy.interpolate import InterpolatedUnivariateSpline
label_desc: Use image node_id 5 for calling the CLRNetPostProcess obj's underlying member method code with example usage: obj.__call__(lanes_list) and returns: lanes