code: def get_input(self, img):
      im = img.astype(np.float32)
      im_tensor = np.zeros((1, 3, im.shape[0], im.shape[1]))
      for i in range(3):
          im_tensor[0, i, :, :] = (
              im[:, :, 2 - i] / self.pixel_scale
              - self.pixel_means[2 - i]
          ) / self.pixel_stds[2 - i]
      # if self.debug:
      #  timeb = datetime.datetime.now()
      #  diff = timeb - timea
      #  print('X2 uses', diff.total_seconds(), 'seconds')
      data = nd.array(im_tensor)
      return data
  
imports: from __future__ import print_function
  import sys
  import os
  import datetime
  import time
  import numpy
  import mxnet
  from mxnet import ndarray
  import cv2
  from rcnn.logger import logger
  from rcnn.processing.bbox_transform import clip_boxes
  from rcnn.processing.generate_anchor import generate_anchors_fpn, anchors_plane
  from rcnn.processing.nms import gpu_nms_wrapper, cpu_nms_wrapper
  from rcnn.processing.bbox_transform import bbox_overlaps
label_desc: Use image node_id 2 for calling the RetinaFace obj's underlying member method code with example usage: obj.get_input(img) and returns: data