code: def unflip_data(data):
      """
      Average original data and flipped data
          data: [2N, 17*3]
      Return
          result: [N, 17*3]
      """
      left_joints = [4, 5, 6, 11, 12, 13]
      right_joints = [1, 2, 3, 14, 15, 16]
  
      data = data.copy().reshape((2, -1, 17, 3))
      data[1, :, :, 0] *= -1  # flip x of all joints
      data[1, :, left_joints + right_joints] = data[
          1, :, right_joints + left_joints
      ]
      data = np.mean(data, axis=0)
      data = data.reshape((-1, 17 * 3))
  
      return data
  
file_path: TensorLayer/tensorlayer/app/human_pose_estimation/common.py
imports: import tensorflow
  import numpy
  import pickle
  import matplotlib.pyplot
  import os
  import matplotlib.gridspec
label_desc: Use image node_id 3 for calling a global function with example usage: unflip_data(data) and returns: data