code: def compute_iou_3D(box, boxes, box_volume, boxes_volume):
      """Calculates IoU of the given box with the array of the given boxes.
      box: 1D vector [y1, x1, y2, x2, z1, z2] (typically gt box)
      boxes: [boxes_count, (y1, x1, y2, x2, z1, z2)]
      box_area: float. the area of 'box'
      boxes_area: array of length boxes_count.
  
      Note: the areas are passed in rather than calculated here for
            efficency. Calculate once in the caller to avoid duplicate work.
      """
      # Calculate intersection areas
      y1 = np.maximum(box[0], boxes[:, 0])
      y2 = np.minimum(box[2], boxes[:, 2])
      x1 = np.maximum(box[1], boxes[:, 1])
      x2 = np.minimum(box[3], boxes[:, 3])
      z1 = np.maximum(box[4], boxes[:, 4])
      z2 = np.minimum(box[5], boxes[:, 5])
      intersection = (
          np.maximum(x2 - x1, 0)
          * np.maximum(y2 - y1, 0)
          * np.maximum(z2 - z1, 0)
      )
      union = box_volume + boxes_volume[:] - intersection[:]
      iou = intersection / union
  
      return iou
  
imports: import numpy
  import scipy.misc
  import scipy.ndimage
  import torch
  from torch.autograd import Variable
  import torch.nn
label_desc: Use image node_id 2 for calling a global function with example usage: compute_iou_3D(box, boxes, box_volume, boxes_volume) and returns: iou