code: import numpy as np
  from common.realtime import DT_CTRL, DT_DMON
  from selfdrive.controls.lib.drive_helpers import create_event, EventTypes as ET
  from common.filter_simple import FirstOrderFilter
  from common.stat_live import RunningStatFilter
  
  _AWARENESS_TIME = 100.  # 1.6 minutes limit without user touching steering wheels make the car enter a terminal status
  _AWARENESS_PRE_TIME_TILL_TERMINAL = 25.  # a first alert is issued 25s before expiration
  _AWARENESS_PROMPT_TIME_TILL_TERMINAL = 15.  # a second alert is issued 15s before start decelerating the car
  _DISTRACTED_TIME = 11.
  _DISTRACTED_PRE_TIME_TILL_TERMINAL = 8.
  _DISTRACTED_PROMPT_TIME_TILL_TERMINAL = 6.
  
  _FACE_THRESHOLD = 0.4
  _EYE_THRESHOLD = 0.4
  _BLINK_THRESHOLD = 0.2 # 0.225
  _PITCH_WEIGHT = 1.35 # 1.5  # pitch matters a lot more
  _METRIC_THRESHOLD = 0.4
  _PITCH_POS_ALLOWANCE = 0.04 # 0.08  # rad, to not be too sensitive on positive pitch
  _PITCH_NATURAL_OFFSET = 0.12  # 0.1   # people don't seem to look straight when they drive relaxed, rather a bit up
  _YAW_NATURAL_OFFSET = 0.08  # people don't seem to look straight when they drive relaxed, rather a bit to the right (center of car)
  
  _DISTRACTED_FILTER_TS = 0.25  # 0.6Hz
  
  _POSE_CALIB_MIN_SPEED = 13 # 30 mph
  _POSE_OFFSET_MIN_COUNT = 600 # valid data counts before calibration completes, 1 seg is 600 counts
  _POSE_OFFSET_MAX_COUNT = 3600 # stop deweighting new data after 6 min, aka "short term memory"
  
  _RECOVERY_FACTOR_MAX = 5. # relative to minus step change
  _RECOVERY_FACTOR_MIN = 1.25 # relative to minus step change
  
  MAX_TERMINAL_ALERTS = 3      # not allowed to engage after 3 terminal alerts
  
  # model output refers to center of cropped image, so need to apply the x displacement offset
  RESIZED_FOCAL = 320.0
  H, W, FULL_W = 320, 160, 426
  
  class DistractedType(object):
    NOT_DISTRACTED = 0
    BAD_POSE = 1
    BAD_BLINK = 2
  
  def head_orientation_from_descriptor(angles_desc, pos_desc, rpy_calib):
    # the output of these angles are in device frame
    # so from driver's perspective, pitch is up and yaw is right
  
    pitch_prnet = angles_desc[0]
    yaw_prnet = angles_desc[1]
    roll_prnet = angles_desc[2]
  
    face_pixel_position = ((pos_desc[0] + .5)*W - W + FULL_W, (pos_desc[1]+.5)*H)
    yaw_focal_angle = np.arctan2(face_pixel_position[0] - FULL_W/2, RESIZED_FOCAL)
    pitch_focal_angle = np.arctan2(face_pixel_position[1] - H/2, RESIZED_FOCAL)
  
    roll = roll_prnet
    pitch = pitch_prnet + pitch_focal_angle
    yaw = -yaw_prnet + yaw_focal_angle
  
    # no calib for roll
    pitch -= rpy_calib[1]
    yaw -= rpy_calib[2]
    return np.array([roll, pitch, yaw])
  
  class DriverPose():
    def __init__(self):
      self.yaw = 0.
      self.pitch = 0.
      self.roll = 0.
      self.pitch_offseter = RunningStatFilter(max_trackable=_POSE_OFFSET_MAX_COUNT)
      self.yaw_offseter = RunningStatFilter(max_trackable=_POSE_OFFSET_MAX_COUNT)
  
  class DriverBlink():
    def __init__(self):
      self.left_blink = 0.
      self.right_blink = 0.
  
  class DriverStatus():
    def __init__(self):
      self.pose = DriverPose()
      self.pose_calibrated = self.pose.pitch_offseter.filtered_stat.n > _POSE_OFFSET_MIN_COUNT and \
                              self.pose.yaw_offseter.filtered_stat.n > _POSE_OFFSET_MIN_COUNT
      self.blink = DriverBlink()
      self.awareness = 1.
      self.awareness_active = 1.
      self.driver_distracted = False
      self.driver_distraction_filter = FirstOrderFilter(0., _DISTRACTED_FILTER_TS, DT_DMON)
      self.face_detected = False
      self.terminal_alert_cnt = 0
      self.step_change = 0.
      self.active_monitoring_mode = True
      self.threshold_prompt = _DISTRACTED_PROMPT_TIME_TILL_TERMINAL / _DISTRACTED_TIME
  
      self.is_rhd_region = False
      self.is_rhd_region_checked = False
  
      self._set_timers(active_monitoring=True)
  
    def _set_timers(self, active_monitoring):
      if self.active_monitoring_mode and self.awareness <= self.threshold_prompt:
        if active_monitoring:
          self.step_change = DT_CTRL / _DISTRACTED_TIME
        else:
          self.step_change = 0.
        return # no exploit after orange alert
      elif self.awareness <= 0.:
        return
  
      if active_monitoring:
        # when falling back from passive mode to active mode, reset awareness to avoid false alert
        if not self.active_monitoring_mode:
          self.awareness = self.awareness_active
  
        self.threshold_pre = _DISTRACTED_PRE_TIME_TILL_TERMINAL / _DISTRACTED_TIME
        self.threshold_prompt = _DISTRACTED_PROMPT_TIME_TILL_TERMINAL / _DISTRACTED_TIME
        self.step_change = DT_CTRL / _DISTRACTED_TIME
        self.active_monitoring_mode = True
      else:
        if self.active_monitoring_mode:
          self.awareness_active = self.awareness
  
        self.threshold_pre = _AWARENESS_PRE_TIME_TILL_TERMINAL / _AWARENESS_TIME
        self.threshold_prompt = _AWARENESS_PROMPT_TIME_TILL_TERMINAL / _AWARENESS_TIME
        self.step_change = DT_CTRL / _AWARENESS_TIME
        self.active_monitoring_mode = False
  
    def _is_driver_distracted(self, pose, blink):
      if not self.pose_calibrated:
        pitch_error = pose.pitch - _PITCH_NATURAL_OFFSET
        yaw_error = pose.yaw - _YAW_NATURAL_OFFSET
        # add positive pitch allowance
        if pitch_error > 0.:
          pitch_error = max(pitch_error - _PITCH_POS_ALLOWANCE, 0.)
      else:
        pitch_error = pose.pitch - self.pose.pitch_offseter.filtered_stat.mean()
        yaw_error = pose.yaw - self.pose.yaw_offseter.filtered_stat.mean()
  
      pitch_error *= _PITCH_WEIGHT
      pose_metric = np.sqrt(yaw_error**2 + pitch_error**2)
  
      if pose_metric > _METRIC_THRESHOLD:
        return DistractedType.BAD_POSE
      elif blink.left_blink>_BLINK_THRESHOLD and blink.right_blink>_BLINK_THRESHOLD:
        return DistractedType.BAD_BLINK
      else:
        return DistractedType.NOT_DISTRACTED
  
    def get_pose(self, driver_monitoring, cal_rpy, car_speed, op_engaged):
      # 10 Hz
      if len(driver_monitoring.faceOrientation) == 0 or len(driver_monitoring.facePosition) == 0:
        return
  
      self.pose.roll, self.pose.pitch, self.pose.yaw = head_orientation_from_descriptor(driver_monitoring.faceOrientation, driver_monitoring.facePosition, cal_rpy)
      self.blink.left_blink = driver_monitoring.leftBlinkProb * (driver_monitoring.leftEyeProb>_EYE_THRESHOLD)
      self.blink.right_blink = driver_monitoring.rightBlinkProb * (driver_monitoring.rightEyeProb>_EYE_THRESHOLD)
      self.face_detected = driver_monitoring.faceProb > _FACE_THRESHOLD and not self.is_rhd_region
  
      self.driver_distracted = self._is_driver_distracted(self.pose, self.blink)>0
      # first order filters
      self.driver_distraction_filter.update(self.driver_distracted)
  
      # update offseter
      # only update when driver is actively driving the car above a certain speed
      if self.face_detected and car_speed>_POSE_CALIB_MIN_SPEED and not op_engaged:
        self.pose.pitch_offseter.push_and_update(self.pose.pitch)
        self.pose.yaw_offseter.push_and_update(self.pose.yaw)
  
      self.pose_calibrated = self.pose.pitch_offseter.filtered_stat.n > _POSE_OFFSET_MIN_COUNT and \
                              self.pose.yaw_offseter.filtered_stat.n > _POSE_OFFSET_MIN_COUNT
  
      self._set_timers(self.face_detected)
  
    def update(self, events, driver_engaged, ctrl_active, standstill):
      if (driver_engaged and self.awareness > 0) or not ctrl_active:
        # reset only when on disengagement if red reached
        self.awareness = 1.
        self.awareness_active = 1.
        return events
  
      driver_attentive = self.driver_distraction_filter.x < 0.37
      awareness_prev = self.awareness
  
      if (driver_attentive and self.face_detected and self.awareness > 0):
        # only restore awareness when paying attention and alert is not red
        self.awareness = min(self.awareness + ((_RECOVERY_FACTOR_MAX-_RECOVERY_FACTOR_MIN)*(1.-self.awareness)+_RECOVERY_FACTOR_MIN)*self.step_change, 1.)
        # don't display alert banner when awareness is recovering and has cleared orange
        if self.awareness > self.threshold_prompt:
          return events
  
      # should always be counting if distracted unless at standstill and reaching orange
      if (not self.face_detected or (self.driver_distraction_filter.x > 0.63 and self.driver_distracted and self.face_detected)) and \
         not (standstill and self.awareness - self.step_change <= self.threshold_prompt):
        self.awareness = max(self.awareness - self.step_change, -0.1)
  
      alert = None
      if self.awareness <= 0.:
        # terminal red alert: disengagement required
        alert = 'driverDistracted' if self.active_monitoring_mode else 'driverUnresponsive'
        if awareness_prev > 0.:
          self.terminal_alert_cnt += 1
      elif self.awareness <= self.threshold_prompt:
        # prompt orange alert
        alert = 'promptDriverDistracted' if self.active_monitoring_mode else 'promptDriverUnresponsive'
      elif self.awareness <= self.threshold_pre:
        # pre green alert
        alert = 'preDriverDistracted' if self.active_monitoring_mode else 'preDriverUnresponsive'
  
      if alert is not None:
        events.append(create_event(alert, [ET.WARNING]))
  
      return events
  
apis: numpy.array numpy.arctan2 numpy.sqrt