text: from math import atan2, sqrt
  
  from cereal import car
  from common.numpy_fast import interp
  from common.realtime import DT_DMON
  from common.filter_simple import FirstOrderFilter
  from common.stat_live import RunningStatFilter
  
  EventName = car.CarEvent.EventName
  
  # ******************************************************************************************
  #  NOTE: To fork maintainers.
  #  Disabling or nerfing safety features may get you and your users banned from our servers.
  #  We recommend that you do not change these numbers from the defaults.
  # ******************************************************************************************
  
  _AWARENESS_TIME = 500.  # passive wheel touch total timeout
  _AWARENESS_PRE_TIME_TILL_TERMINAL = 12.
  _AWARENESS_PROMPT_TIME_TILL_TERMINAL = 6.
  _DISTRACTED_TIME = 35.
  _DISTRACTED_PRE_TIME_TILL_TERMINAL = 8.
  _DISTRACTED_PROMPT_TIME_TILL_TERMINAL = 6.
  
  _FACE_THRESHOLD = 0.5
  _PARTIAL_FACE_THRESHOLD = 0.5
  _EYE_THRESHOLD = 0.5
  _SG_THRESHOLD = 0.5
  _BLINK_THRESHOLD = 0.5
  _BLINK_THRESHOLD_SLACK = 0.65
  _BLINK_THRESHOLD_STRICT = 0.5
  _PITCH_WEIGHT = 1.35  # pitch matters a lot more
  _POSESTD_THRESHOLD = 0.14
  _E2E_POSE_THRESHOLD = 0.9
  _E2E_EYES_THRESHOLD = 0.75
  _METRIC_THRESHOLD = 0.4
  _METRIC_THRESHOLD_SLACK = 0.55
  _METRIC_THRESHOLD_STRICT = 0.4
  _PITCH_POS_ALLOWANCE = 0.12  # rad, to not be too sensitive on positive pitch
  _PITCH_NATURAL_OFFSET = 0.02  # 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)
  
  _HI_STD_FALLBACK_TIME = 10  # fall back to wheel touch if model is uncertain for a long time
  _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
  MAX_TERMINAL_DURATION = 300  # 30s
  
  # 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:
    NOT_DISTRACTED = 0
    BAD_POSE = 1
    BAD_BLINK = 2
  
  def face_orientation_from_net(angles_desc, pos_desc, rpy_calib, is_rhd):
    # the output of these angles are in device frame
    # so from driver's perspective, pitch is up and yaw is right
  
    pitch_net, yaw_net, roll_net = angles_desc
  
    face_pixel_position = ((pos_desc[0] + .5)*W - W + FULL_W, (pos_desc[1]+.5)*H)
    yaw_focal_angle = atan2(face_pixel_position[0] - FULL_W//2, RESIZED_FOCAL)
    pitch_focal_angle = atan2(face_pixel_position[1] - H//2, RESIZED_FOCAL)
  
    pitch = pitch_net + pitch_focal_angle
    yaw = -yaw_net + yaw_focal_angle
  
    # no calib for roll
    pitch -= rpy_calib[1]
    yaw -= rpy_calib[2] * (1 - 2 * int(is_rhd))  # lhd -> -=, rhd -> +=
    return roll_net, pitch, yaw
  
  class DriverPose():
    def __init__(self):
      self.yaw = 0.
      self.pitch = 0.
      self.roll = 0.
      self.yaw_std = 0.
      self.pitch_std = 0.
      self.roll_std = 0.
      self.pitch_offseter = RunningStatFilter(max_trackable=_POSE_OFFSET_MAX_COUNT)
      self.yaw_offseter = RunningStatFilter(max_trackable=_POSE_OFFSET_MAX_COUNT)
      self.low_std = True
      self.cfactor = 1.
  
  class DriverBlink():
    def __init__(self):
      self.left_blink = 0.
      self.right_blink = 0.
      self.cfactor = 1.
  
  class DriverStatus():
    def __init__(self, rhd=False):
      self.is_rhd_region = rhd
      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.awareness_passive = 1.
      self.driver_distracted = False
      self.driver_distraction_filter = FirstOrderFilter(0., _DISTRACTED_FILTER_TS, DT_DMON)
      self.face_detected = False
      self.face_partial = False
      self.terminal_alert_cnt = 0
      self.terminal_time = 0
      self.step_change = 0.
      self.active_monitoring_mode = True
      self.is_model_uncertain = False
      self.hi_stds = 0
      self.threshold_prompt = _DISTRACTED_PROMPT_TIME_TILL_TERMINAL / _DISTRACTED_TIME
  
      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_DMON / _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_passive = self.awareness
          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_DMON / _DISTRACTED_TIME
        self.active_monitoring_mode = True
      else:
        if self.active_monitoring_mode:
          self.awareness_active = self.awareness
          self.awareness = self.awareness_passive
  
        self.threshold_pre = _AWARENESS_PRE_TIME_TILL_TERMINAL / _AWARENESS_TIME
        self.threshold_prompt = _AWARENESS_PROMPT_TIME_TILL_TERMINAL / _AWARENESS_TIME
        self.step_change = DT_DMON / _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
      else:
        pitch_error = pose.pitch - self.pose.pitch_offseter.filtered_stat.mean()
        yaw_error = pose.yaw - self.pose.yaw_offseter.filtered_stat.mean()
  
      # positive pitch allowance
      if pitch_error > 0.:
        pitch_error = max(pitch_error - _PITCH_POS_ALLOWANCE, 0.)
      pitch_error *= _PITCH_WEIGHT
      pose_metric = sqrt(yaw_error**2 + pitch_error**2)
  
      if pose_metric > _METRIC_THRESHOLD*pose.cfactor:
        return DistractedType.BAD_POSE
      elif (blink.left_blink + blink.right_blink)*0.5 > _BLINK_THRESHOLD*blink.cfactor:
        return DistractedType.BAD_BLINK
      else:
        return DistractedType.NOT_DISTRACTED
  
    def set_policy(self, model_data):
      ep = min(model_data.meta.engagedProb, 0.8) / 0.8
      self.pose.cfactor = interp(ep, [0, 0.5, 1], [_METRIC_THRESHOLD_STRICT, _METRIC_THRESHOLD, _METRIC_THRESHOLD_SLACK])/_METRIC_THRESHOLD
      self.blink.cfactor = interp(ep, [0, 0.5, 1], [_BLINK_THRESHOLD_STRICT, _BLINK_THRESHOLD, _BLINK_THRESHOLD_SLACK])/_BLINK_THRESHOLD
  
    def get_pose(self, driver_state, cal_rpy, car_speed, op_engaged):
      if not all(len(x) > 0 for x in [driver_state.faceOrientation, driver_state.facePosition,
                                      driver_state.faceOrientationStd, driver_state.facePositionStd]):
        return
  
      self.face_partial = driver_state.partialFace > _PARTIAL_FACE_THRESHOLD
      self.face_detected = driver_state.faceProb > _FACE_THRESHOLD or self.face_partial
      self.pose.roll, self.pose.pitch, self.pose.yaw = face_orientation_from_net(driver_state.faceOrientation, driver_state.facePosition, cal_rpy, self.is_rhd_region)
      self.pose.pitch_std = driver_state.faceOrientationStd[0]
      self.pose.yaw_std = driver_state.faceOrientationStd[1]
      # self.pose.roll_std = driver_state.faceOrientationStd[2]
      model_std_max = max(self.pose.pitch_std, self.pose.yaw_std)
      self.pose.low_std = model_std_max < _POSESTD_THRESHOLD and not self.face_partial
      self.blink.left_blink = driver_state.leftBlinkProb * (driver_state.leftEyeProb > _EYE_THRESHOLD) * (driver_state.sunglassesProb < _SG_THRESHOLD)
      self.blink.right_blink = driver_state.rightBlinkProb * (driver_state.rightEyeProb > _EYE_THRESHOLD) * (driver_state.sunglassesProb < _SG_THRESHOLD)
  
      distracted_normal = (self._is_driver_distracted(self.pose, self.blink) > 0 and
                          driver_state.faceProb > _FACE_THRESHOLD and self.pose.low_std)
      distracted_E2E = ((driver_state.distractedPose > _E2E_POSE_THRESHOLD or driver_state.distractedEyes > _E2E_EYES_THRESHOLD) and
                       (self.face_detected and not self.face_partial))
      self.driver_distracted = distracted_normal or distracted_E2E
      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 self.pose.low_std and (not op_engaged or not self.driver_distracted):
        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.is_model_uncertain = self.hi_stds * DT_DMON > _HI_STD_FALLBACK_TIME
      self._set_timers(self.face_detected and not self.is_model_uncertain)
      if self.face_detected and not self.pose.low_std and not self.driver_distracted:
        self.hi_stds += 1
      elif self.face_detected and self.pose.low_std:
        self.hi_stds = 0
  
    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.
        self.awareness_passive = 1.
        return
  
      driver_attentive = self.driver_distraction_filter.x < 0.37
      awareness_prev = self.awareness
  
      if (driver_attentive and self.face_detected and self.pose.low_std 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.)
        if self.awareness == 1.:
          self.awareness_passive = min(self.awareness_passive + self.step_change, 1.)
        # don't display alert banner when awareness is recovering and has cleared orange
        if self.awareness > self.threshold_prompt:
          return
  
      standstill_exemption = standstill and self.awareness - self.step_change <= self.threshold_prompt
      certainly_distracted = self.driver_distraction_filter.x > 0.63 and self.driver_distracted and self.face_detected
      maybe_distracted = self.hi_stds * DT_DMON > _HI_STD_FALLBACK_TIME or not self.face_detected
      if certainly_distracted or maybe_distracted:
        # should always be counting if distracted unless at standstill and reaching orange
        if not standstill_exemption:
          self.awareness = max(self.awareness - self.step_change, -0.1)
  
      alert = None
      if self.awareness <= 0.:
        # terminal red alert: disengagement required
        alert = EventName.driverDistracted if self.active_monitoring_mode else EventName.driverUnresponsive
        self.terminal_time += 1
        if awareness_prev > 0.:
          self.terminal_alert_cnt += 1
      elif self.awareness <= self.threshold_prompt:
        # prompt orange alert
        alert = EventName.promptDriverDistracted if self.active_monitoring_mode else EventName.promptDriverUnresponsive
      elif self.awareness <= self.threshold_pre:
        # pre green alert
        alert = EventName.preDriverDistracted if self.active_monitoring_mode else EventName.preDriverUnresponsive
  
      if alert is not None:
        events.add(alert)
  