code: def __call__(self, output, center, scale):
      preds, maxvals = self.get_final_preds(output, center, scale)
      return np.concatenate((preds, maxvals), axis=-1), np.mean(
          maxvals, axis=1
      )
  
imports: from scipy.optimize import linear_sum_assignment
  from collections import abc, defaultdict
  import cv2
  import numpy
  import math
  import paddle
  import paddle.nn
  from keypoint_preprocess import get_affine_mat_kernel, get_affine_transform
label_desc: Use image node_id 8 for calling the HRNetPostProcess obj's underlying member method code with example usage: obj.__call__(output, center, scale) and returns: np,  np