code: def run_model_test_single(
      self,
      use_flip_test=True,
      use_norm_score=False,
      use_detector_score=True,
  ):
      img_input_feats = process_embeddings(
          self.embs,
          self.embs_f,
          use_flip_test=use_flip_test,
          use_norm_score=use_norm_score,
          use_detector_score=use_detector_score,
          face_scores=self.face_scores,
      )
      template_norm_feats, unique_templates, _ = image2template_feature(
          img_input_feats, self.templates, self.medias
      )
      score = verification_11(
          template_norm_feats, unique_templates, self.p1, self.p2
      )
      return score
  
imports: import os
  import cv2
  import numpy
  import pandas
  from tqdm import tqdm
  from skimage import transform
  from sklearn.preprocessing import normalize
  from sklearn.metrics import roc_curve, auc
label_desc: Use image node_id 2 for calling the IJB_test obj's underlying member method code with example usage: obj.run_model_test_single(use_flip_test, use_norm_score, use_detector_score) and returns: score