code: def get(self, rimg, landmark):
      assert landmark.shape[0] == 68 or landmark.shape[0] == 5
      assert landmark.shape[1] == 2
      if landmark.shape[0] == 68:
          landmark5 = np.zeros((5, 2), dtype=np.float32)
          landmark5[0] = (landmark[36] + landmark[39]) / 2
          landmark5[1] = (landmark[42] + landmark[45]) / 2
          landmark5[2] = landmark[30]
          landmark5[3] = landmark[48]
          landmark5[4] = landmark[54]
      else:
          landmark5 = landmark
      tform = trans.SimilarityTransform()
      tform.estimate(landmark5, self.src)
      M = tform.params[0:2, :]
      img = cv2.warpAffine(
          rimg,
          M,
          (self.image_size[1], self.image_size[0]),
          borderValue=0.0,
      )
      img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
      img_flip = np.fliplr(img)
      img = np.transpose(img, (2, 0, 1))  # 3*112*112, RGB
      img_flip = np.transpose(img_flip, (2, 0, 1))
      input_blob = np.zeros(
          (2, 3, self.image_size[1], self.image_size[0]), dtype=np.uint8
      )
      input_blob[0] = img
      input_blob[1] = img_flip
      return input_blob
  
imports: import os
  import pickle
  import matplotlib
  import pandas
  import matplotlib.pyplot
  import timeit
  import sklearn
  import argparse
  from sklearn.metrics import roc_curve, auc
  from menpo.visualize.viewmatplotlib import sample_colours_from_colourmap
  from prettytable import PrettyTable
  from pathlib import Path
  import sys
  import warnings
  import cv2
  import numpy
  import torch
  from skimage import transform
  import backbones
label_desc: Use image node_id 2 for calling the Embedding obj's underlying member method code with example usage: obj.get(rimg, landmark) and returns: input_blob