class_docstr: This class contains all needed functions to work with faces in a frame
code: def __init__(self, face_width=200):
      self.detector = None
  
      self.predictor = None
      self.age_net = None
      self.gender_net = None
  
      self.MODEL_MEAN_VALUES = (
          78.4263377603,
          87.7689143744,
          114.895847746,
      )
      self.age_list = [
          "(0, 2)",
          "(4, 6)",
          "(8, 12)",
          "(15, 20)",
          "(25, 32)",
          "(38, 43)",
          "(48, 53)",
          "(60, 100)",
      ]
      self.gender_list = ["Male", "Female"]
  
      self.desiredLeftEye = (0.35, 0.35)
      self.desiredFaceWidth = face_width
      self.desiredFaceHeight = None
  
      if self.desiredFaceHeight is None:
          self.desiredFaceHeight = self.desiredFaceWidth
      # For dlib’s 68-point facial landmark detector:
      self.FACIAL_LANDMARKS_68_IDXS = OrderedDict(
          [
              ("mouth", (48, 68)),
              ("right_eyebrow", (17, 22)),
              ("left_eyebrow", (22, 27)),
              ("right_eye", (36, 42)),
              ("left_eye", (42, 48)),
              ("nose", (27, 36)),
              ("jaw", (0, 17)),
          ]
      )
  
      # For dlib’s 5-point facial landmark detector:
      self.FACIAL_LANDMARKS_5_IDXS = OrderedDict(
          [("right_eye", (2, 3)), ("left_eye", (0, 1)), ("nose", (4))]
      )
  
      # last params
      self.last_age = None
      self.last_gender = None
      self.last_rects = None
      self.last_shape = None
      self.last_aligned_shape = None
  
file_path: heart-rate-measurement-camera/face_utilities.py
imports: import cv2
  import numpy
  import dlib
  from imutils import face_utils
  import imutils
  from collections import OrderedDict
label_desc: Use image node_id 1 to create a new Face_utilities object  with example: obj = Face_utilities(face_width)