code: def apply_bbox_pred(self, bbox_pred, ind=None):
      box_deltas = bbox_pred
      box_deltas[:, 0::4] = (
          box_deltas[:, 0::4] * config.TRAIN.BBOX_STDS[0]
      )
      box_deltas[:, 1::4] = (
          box_deltas[:, 1::4] * config.TRAIN.BBOX_STDS[1]
      )
      box_deltas[:, 2::4] = (
          box_deltas[:, 2::4] * config.TRAIN.BBOX_STDS[2]
      )
      box_deltas[:, 3::4] = (
          box_deltas[:, 3::4] * config.TRAIN.BBOX_STDS[3]
      )
      if ind is None:
          boxes = self.ori_anchors
      else:
          boxes = self.ori_anchors[ind]
      # print('in apply',self.stride, box_deltas.shape, boxes.shape)
  
      widths = boxes[:, 2] - boxes[:, 0] + 1.0
      heights = boxes[:, 3] - boxes[:, 1] + 1.0
      ctr_x = boxes[:, 0] + 0.5 * (widths - 1.0)
      ctr_y = boxes[:, 1] + 0.5 * (heights - 1.0)
  
      dx = box_deltas[:, 0:1]
      dy = box_deltas[:, 1:2]
      dw = box_deltas[:, 2:3]
      dh = box_deltas[:, 3:4]
  
      pred_ctr_x = dx * widths[:, np.newaxis] + ctr_x[:, np.newaxis]
      pred_ctr_y = dy * heights[:, np.newaxis] + ctr_y[:, np.newaxis]
      pred_w = np.exp(dw) * widths[:, np.newaxis]
      pred_h = np.exp(dh) * heights[:, np.newaxis]
  
      pred_boxes = np.zeros(box_deltas.shape)
      # x1
      pred_boxes[:, 0:1] = pred_ctr_x - 0.5 * (pred_w - 1.0)
      # y1
      pred_boxes[:, 1:2] = pred_ctr_y - 0.5 * (pred_h - 1.0)
      # x2
      pred_boxes[:, 2:3] = pred_ctr_x + 0.5 * (pred_w - 1.0)
      # y2
      pred_boxes[:, 3:4] = pred_ctr_y + 0.5 * (pred_h - 1.0)
      return pred_boxes
  
imports: from __future__ import print_function
  import sys
  import mxnet
  import numpy
  import datetime
  from distutils.util import strtobool
  from ..config import config, generate_config
  from ..processing.generate_anchor import generate_anchors, anchors_plane
  from ..processing.bbox_transform import bbox_overlaps, bbox_transform, landmark_transform
label_desc: Use image node_id 2 for calling the CascadeRefineOperator obj's underlying member method code with example usage: obj.apply_bbox_pred(bbox_pred, ind) and returns: pred_boxes