code: def _get_box(data, biases, n, location, lw, lh, w, h):
      bx = (
          location[2] + data[location[0]][0][location[1]][location[2]]
      ) / lw
      by = (
          location[1] + data[location[0]][1][location[1]][location[2]]
      ) / lh
      bw = (
          np.exp(data[location[0]][2][location[1]][location[2]])
          * biases[2 * n]
          / w
      )
      bh = (
          np.exp(data[location[0]][3][location[1]][location[2]])
          * biases[2 * n + 1]
          / h
      )
      return Box(bx, by, bw, bh)
  
imports: from __future__ import division
  import math
  from collections import namedtuple
  from functools import cmp_to_key
  import numpy
label_desc: Use image node_id 7 for calling a global function with example usage: _get_box(data, biases, n, location, lw, lh, w, h) and returns: Box