code: def predict_results(batch_heatmaps):
      (
          batch_size,
          num_joints,
          heatmap_height,
          heatmap_width,
      ) = batch_heatmaps.shape
      preds, maxvals = get_max_preds(batch_heatmaps)
      return preds[0] * 4, num_joints
  
file_path: PaddleHub/modules/image/keypoint_detection/human_pose_estimation_resnet50_mpii/processor.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import base64
  import os
  import time
  from collections import OrderedDict
  import cv2
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: predict_results(batch_heatmaps) and returns: unknown,  num_joints