docstr: DARK postpocessing, Zhang et al. Distribution-Aware Coordinate
  Representation for Human Pose Estimation (CVPR 2020).
docstr_tok: ["DARK","postpocessing",",","Zhang","et","al",".","Distribution-Aware","Coordinate","Representation","for","Human","Pose","Estimation","(","CVPR","2020",")","."]
code: def dark_postprocess(self, hm, coords, kernelsize):
      """DARK postpocessing, Zhang et al. Distribution-Aware Coordinate
      Representation for Human Pose Estimation (CVPR 2020).
      """
  
      hm = self.gaussian_blur(hm, kernelsize)
      hm = np.maximum(hm, 1e-10)
      hm = np.log(hm)
      for n in range(coords.shape[0]):
          for p in range(coords.shape[1]):
              coords[n, p] = self.dark_parse(hm[n][p], coords[n][p])
      return coords
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import numpy
  import math
  import cv2
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
  from ..keypoint_utils import transform_preds
  from ..None import layers
  from paddle.nn import functional
label_desc: Use image node_id 5 for calling the HRNetPostProcess obj's underlying member method code with example usage: obj.dark_postprocess(hm, coords, kernelsize) and returns: coords