Merge branch 'master-r' into multilang-ja-20250321

# Conflicts:
#	opendbc_repo
#	panda

.github/workflows/auto_pr_review.yaml

@@ -1,7 +1,7 @@
 name: "PR review"
 on:
   pull_request_target:
-    types: [opened, reopened, synchronize, edited, edited]
+    types: [opened, reopened, synchronize, edited]
 
 jobs:
   labeler:
@@ -50,4 +50,3 @@ jobs:
               * all the tests are passing
               * the change is [something we merge](https://github.com/commaai/openpilot/blob/master/docs/CONTRIBUTING.md#what-gets-merged)
               * include a route or your device' dongle ID if relevant
-      

.github/workflows/selfdrive_tests.yaml

@@ -90,21 +90,29 @@ jobs:
     - uses: actions/checkout@v4
       with:
         submodules: true
+    - run: echo "CACHE_COMMIT_DATE=$(git log -1 --pretty='format:%cd' --date=format:'%Y-%m-%d-%H:%M')" >> $GITHUB_ENV
     - name: Homebrew cache
       uses: ./.github/workflows/auto-cache
       with:
         path: ~/Library/Caches/Homebrew
+        key: brew-macos-${{ env.CACHE_COMMIT_DATE }}-${{ github.sha }}
+        restore-keys: |
+          brew-macos-${{ env.CACHE_COMMIT_DATE }}
+          brew-macos
     - name: Install dependencies
       run: ./tools/mac_setup.sh
       env:
         # package install has DeprecationWarnings
         PYTHONWARNINGS: default
     - run: git lfs pull
-    - run: echo "CACHE_COMMIT_DATE=$(git log -1 --pretty='format:%cd' --date=format:'%Y-%m-%d-%H:%M')" >> $GITHUB_ENV
     - name: Getting scons cache
       uses: ./.github/workflows/auto-cache
       with:
         path: /tmp/scons_cache
+        key: scons-${{ runner.arch }}-macos-${{ env.CACHE_COMMIT_DATE }}-${{ github.sha }}
+        restore-keys: |
+          scons-${{ runner.arch }}-macos-${{ env.CACHE_COMMIT_DATE }}
+          scons-${{ runner.arch }}-macos
     - name: Building openpilot
       run: . .venv/bin/activate && scons -j$(nproc)
 

.github/workflows/ui_preview.yaml

@@ -82,7 +82,7 @@ jobs:
         if: github.event_name == 'pull_request_target'
         id: find_diff
         run: >-
-          sudo apt-get install -y imagemagick
+          sudo apt-get update && sudo apt-get install -y imagemagick
 
           scenes=$(find ${{ github.workspace }}/pr_ui/*.png -type f -printf "%f\n" | cut -d '.' -f 1 | grep -v 'pair_device')
           A=($scenes)

cereal/log.capnp

@@ -2278,6 +2278,21 @@ struct LiveTorqueParametersData {
   useParams @12 :Bool;
 }
 
+struct LiveDelayData {
+  lateralDelay @0 :Float32;
+  validBlocks @1 :Int32;
+  status @2 :Status;
+
+  lateralDelayEstimate @3 :Float32;
+  points @4 :List(Float32);
+
+  enum Status {
+    unestimated @0;
+    estimated @1;
+    invalid @2;
+  }
+}
+
 struct LiveMapDataDEPRECATED {
   speedLimitValid @0 :Bool;
   speedLimit @1 :Float32;
@@ -2508,6 +2523,7 @@ struct Event {
     gnssMeasurements @91 :GnssMeasurements;
     liveParameters @61 :LiveParametersData;
     liveTorqueParameters @94 :LiveTorqueParametersData;
+    liveDelay @146 : LiveDelayData;
     cameraOdometry @63 :CameraOdometry;
     thumbnail @66: Thumbnail;
     onroadEvents @134: List(OnroadEvent);

msgq_repo

@@ -1 +1 @@
-Subproject commit ad9020c430362d17c0edf97747d344389234be4d
+Subproject commit 94e738992ca8a12c2d9bb7bdeeaab4713543773e

opendbc_repo

@@ -1 +1 @@
-Subproject commit 0235e0e5d54d92f0df689426f79e9ba298b26b77
+Subproject commit 4179672dae72e29b8ff9072d9be154515312e350

panda

@@ -1 +1 @@
-Subproject commit 998ac9d5d82f10d7dd926ac66800b1efa20ff9b2
+Subproject commit 8a583aaa8c1a27a3d13747b7ecead6a3d73a4e81

rednose_repo

@@ -1 +1 @@
-Subproject commit 05fd60278a95190cc5a61f40730c82eaa1d986e1
+Subproject commit 8b860529199569401d5d8e105bc1be600fca49a8

selfdrive/locationd/calibrationd.py

@@ -11,7 +11,7 @@ import capnp
 import numpy as np
 from typing import NoReturn
 
-from cereal import log
+from cereal import log, car
 import cereal.messaging as messaging
 from openpilot.common.conversions import Conversions as CV
 from openpilot.common.params import Params
@@ -258,16 +258,18 @@ def main() -> NoReturn:
   config_realtime_process([0, 1, 2, 3], 5)
 
   pm = messaging.PubMaster(['liveCalibration'])
-  sm = messaging.SubMaster(['cameraOdometry', 'carState', 'carParams'], poll='cameraOdometry')
+  sm = messaging.SubMaster(['cameraOdometry', 'carState'], poll='cameraOdometry')
+
+  params_reader = Params()
+  CP = messaging.log_from_bytes(params_reader.get("CarParams", block=True), car.CarParams)
 
   calibrator = Calibrator(param_put=True)
+  calibrator.not_car = CP.notCar
 
   while 1:
     timeout = 0 if sm.frame == -1 else 100
     sm.update(timeout)
 
-    calibrator.not_car = sm['carParams'].notCar
-
     if sm.updated['cameraOdometry']:
       calibrator.handle_v_ego(sm['carState'].vEgo)
       new_rpy = calibrator.handle_cam_odom(sm['cameraOdometry'].trans,

selfdrive/locationd/models/car_kf.py

@@ -160,19 +160,18 @@ class CarKalman(KalmanFilter):
 
     gen_code(generated_dir, name, f_sym, dt, state_sym, obs_eqs, dim_state, dim_state, global_vars=global_vars)
 
-  def __init__(self, generated_dir, steer_ratio=15, stiffness_factor=1, angle_offset=0, P_initial=None):
-    dim_state = self.initial_x.shape[0]
-    dim_state_err = self.P_initial.shape[0]
-    x_init = self.initial_x
-    x_init[States.STEER_RATIO] = steer_ratio
-    x_init[States.STIFFNESS] = stiffness_factor
-    x_init[States.ANGLE_OFFSET] = angle_offset
-
-    if P_initial is not None:
-      self.P_initial = P_initial
-    # init filter
-    self.filter = EKF_sym_pyx(generated_dir, self.name, self.Q, self.initial_x, self.P_initial,
-                              dim_state, dim_state_err, global_vars=self.global_vars, logger=cloudlog)
+  def __init__(self, generated_dir):
+    dim_state, dim_state_err = CarKalman.initial_x.shape[0], CarKalman.P_initial.shape[0]
+    self.filter = EKF_sym_pyx(generated_dir, CarKalman.name, CarKalman.Q, CarKalman.initial_x, CarKalman.P_initial,
+                              dim_state, dim_state_err, global_vars=CarKalman.global_vars, logger=cloudlog)
+
+  def set_globals(self, mass, rotational_inertia, center_to_front, center_to_rear, stiffness_front, stiffness_rear):
+    self.filter.set_global("mass", mass)
+    self.filter.set_global("rotational_inertia", rotational_inertia)
+    self.filter.set_global("center_to_front", center_to_front)
+    self.filter.set_global("center_to_rear", center_to_rear)
+    self.filter.set_global("stiffness_front", stiffness_front)
+    self.filter.set_global("stiffness_rear", stiffness_rear)
 
 
 if __name__ == "__main__":

selfdrive/locationd/paramsd.py

@@ -1,8 +1,8 @@
 #!/usr/bin/env python3
 import os
-import math
 import json
 import numpy as np
+import capnp
 
 import cereal.messaging as messaging
 from cereal import car, log
@@ -13,12 +13,11 @@ from openpilot.selfdrive.locationd.models.constants import GENERATED_DIR
 from openpilot.selfdrive.locationd.helpers import PoseCalibrator, Pose
 from openpilot.common.swaglog import cloudlog
 
-
 MAX_ANGLE_OFFSET_DELTA = 20 * DT_MDL  # Max 20 deg/s
-ROLL_MAX_DELTA = math.radians(20.0) * DT_MDL  # 20deg in 1 second is well within curvature limits
-ROLL_MIN, ROLL_MAX = math.radians(-10), math.radians(10)
-ROLL_LOWERED_MAX = math.radians(8)
-ROLL_STD_MAX = math.radians(1.5)
+ROLL_MAX_DELTA = np.radians(20.0) * DT_MDL  # 20deg in 1 second is well within curvature limits
+ROLL_MIN, ROLL_MAX = np.radians(-10), np.radians(10)
+ROLL_LOWERED_MAX = np.radians(8)
+ROLL_STD_MAX = np.radians(1.5)
 LATERAL_ACC_SENSOR_THRESHOLD = 4.0
 OFFSET_MAX = 10.0
 OFFSET_LOWERED_MAX = 8.0
@@ -26,40 +25,58 @@ MIN_ACTIVE_SPEED = 1.0
 LOW_ACTIVE_SPEED = 10.0
 
 
-class ParamsLearner:
-  def __init__(self, CP, steer_ratio, stiffness_factor, angle_offset, P_initial=None):
-    self.kf = CarKalman(GENERATED_DIR, steer_ratio, stiffness_factor, angle_offset, P_initial)
+class VehicleParamsLearner:
+  def __init__(self, CP: car.CarParams, steer_ratio: float, stiffness_factor: float, angle_offset: float, P_initial: np.ndarray | None = None):
+    self.kf = CarKalman(GENERATED_DIR)
+
+    self.x_initial = CarKalman.initial_x.copy()
+    self.x_initial[States.STEER_RATIO] = steer_ratio
+    self.x_initial[States.STIFFNESS] = stiffness_factor
+    self.x_initial[States.ANGLE_OFFSET] = angle_offset
+    self.P_initial = P_initial if P_initial is not None else CarKalman.P_initial
 
-    self.kf.filter.set_global("mass", CP.mass)
-    self.kf.filter.set_global("rotational_inertia", CP.rotationalInertia)
-    self.kf.filter.set_global("center_to_front", CP.centerToFront)
-    self.kf.filter.set_global("center_to_rear", CP.wheelbase - CP.centerToFront)
-    self.kf.filter.set_global("stiffness_front", CP.tireStiffnessFront)
-    self.kf.filter.set_global("stiffness_rear", CP.tireStiffnessRear)
+    self.kf.set_globals(
+      mass=CP.mass,
+      rotational_inertia=CP.rotationalInertia,
+      center_to_front=CP.centerToFront,
+      center_to_rear=CP.wheelbase - CP.centerToFront,
+      stiffness_front=CP.tireStiffnessFront,
+      stiffness_rear=CP.tireStiffnessRear
+    )
 
-    self.active = False
+    self.min_sr, self.max_sr = 0.5 * CP.steerRatio, 2.0 * CP.steerRatio
 
     self.calibrator = PoseCalibrator()
 
-    self.speed = 0.0
-    self.yaw_rate = 0.0
-    self.yaw_rate_std = 0.0
-    self.roll = 0.0
-    self.steering_angle = 0.0
+    self.observed_speed = 0.0
+    self.observed_yaw_rate = 0.0
+    self.observed_roll = 0.0
+
+    self.avg_offset_valid = True
+    self.total_offset_valid = True
+    self.roll_valid = True
+
+    self.reset(None)
+
+  def reset(self, t: float | None):
+    self.kf.init_state(self.x_initial, covs=self.P_initial, filter_time=t)
 
-  def handle_log(self, t, which, msg):
+    self.angle_offset, self.roll, self.active = np.degrees(self.x_initial[States.ANGLE_OFFSET].item()), 0.0, False
+    self.avg_angle_offset = self.angle_offset
+
+  def handle_log(self, t: float, which: str, msg: capnp._DynamicStructReader):
     if which == 'livePose':
       device_pose = Pose.from_live_pose(msg)
       calibrated_pose = self.calibrator.build_calibrated_pose(device_pose)
 
+      yaw_rate, yaw_rate_std = calibrated_pose.angular_velocity.z, calibrated_pose.angular_velocity.z_std
       yaw_rate_valid = msg.angularVelocityDevice.valid
-      yaw_rate_valid = yaw_rate_valid and 0 < self.yaw_rate_std < 10  # rad/s
-      yaw_rate_valid = yaw_rate_valid and abs(self.yaw_rate) < 1  # rad/s
-      if yaw_rate_valid:
-        self.yaw_rate, self.yaw_rate_std = calibrated_pose.angular_velocity.z, calibrated_pose.angular_velocity.z_std
-      else:
+      yaw_rate_valid = yaw_rate_valid and 0 < yaw_rate_std < 10  # rad/s
+      yaw_rate_valid = yaw_rate_valid and abs(yaw_rate) < 1  # rad/s
+      if not yaw_rate_valid:
         # This is done to bound the yaw rate estimate when localizer values are invalid or calibrating
-        self.yaw_rate, self.yaw_rate_std = 0.0, np.radians(10.0)
+        yaw_rate, yaw_rate_std = 0.0, np.radians(10.0)
+      self.observed_yaw_rate = yaw_rate
 
       localizer_roll, localizer_roll_std = device_pose.orientation.x, device_pose.orientation.x_std
       localizer_roll_std = np.radians(1) if np.isnan(localizer_roll_std) else localizer_roll_std
@@ -72,18 +89,18 @@ class ParamsLearner:
         # This is done to bound the road roll estimate when localizer values are invalid
         roll = 0.0
         roll_std = np.radians(10.0)
-      self.roll = np.clip(roll, self.roll - ROLL_MAX_DELTA, self.roll + ROLL_MAX_DELTA)
+      self.observed_roll = np.clip(roll, self.observed_roll - ROLL_MAX_DELTA, self.observed_roll + ROLL_MAX_DELTA)
 
       if self.active:
         if msg.posenetOK:
           self.kf.predict_and_observe(t,
                                       ObservationKind.ROAD_FRAME_YAW_RATE,
-                                      np.array([[-self.yaw_rate]]),
-                                      np.array([np.atleast_2d(self.yaw_rate_std**2)]))
+                                      np.array([[-self.observed_yaw_rate]]),
+                                      np.array([np.atleast_2d(yaw_rate_std**2)]))
 
           self.kf.predict_and_observe(t,
                                       ObservationKind.ROAD_ROLL,
-                                      np.array([[self.roll]]),
+                                      np.array([[self.observed_roll]]),
                                       np.array([np.atleast_2d(roll_std**2)]))
         self.kf.predict_and_observe(t, ObservationKind.ANGLE_OFFSET_FAST, np.array([[0]]))
 
@@ -99,20 +116,79 @@ class ParamsLearner:
       self.calibrator.feed_live_calib(msg)
 
     elif which == 'carState':
-      self.steering_angle = msg.steeringAngleDeg
-      self.speed = msg.vEgo
+      steering_angle = msg.steeringAngleDeg
 
-      in_linear_region = abs(self.steering_angle) < 45
-      self.active = self.speed > MIN_ACTIVE_SPEED and in_linear_region
+      in_linear_region = abs(steering_angle) < 45
+      self.observed_speed = msg.vEgo
+      self.active = self.observed_speed > MIN_ACTIVE_SPEED and in_linear_region
 
       if self.active:
-        self.kf.predict_and_observe(t, ObservationKind.STEER_ANGLE, np.array([[math.radians(msg.steeringAngleDeg)]]))
-        self.kf.predict_and_observe(t, ObservationKind.ROAD_FRAME_X_SPEED, np.array([[self.speed]]))
+        self.kf.predict_and_observe(t, ObservationKind.STEER_ANGLE, np.array([[np.radians(steering_angle)]]))
+        self.kf.predict_and_observe(t, ObservationKind.ROAD_FRAME_X_SPEED, np.array([[self.observed_speed]]))
 
     if not self.active:
       # Reset time when stopped so uncertainty doesn't grow
-      self.kf.filter.set_filter_time(t)
-      self.kf.filter.reset_rewind()
+      self.kf.filter.set_filter_time(t)  # type: ignore
+      self.kf.filter.reset_rewind()      # type: ignore
+
+  def get_msg(self, valid: bool, debug: bool = False) -> capnp._DynamicStructBuilder:
+    x = self.kf.x
+    P = np.sqrt(self.kf.P.diagonal())
+    if not np.all(np.isfinite(x)):
+      cloudlog.error("NaN in liveParameters estimate. Resetting to default values")
+      self.reset(self.kf.t)
+      x = self.kf.x
+
+    self.avg_angle_offset = np.clip(np.degrees(x[States.ANGLE_OFFSET].item()),
+                                self.avg_angle_offset - MAX_ANGLE_OFFSET_DELTA, self.avg_angle_offset + MAX_ANGLE_OFFSET_DELTA)
+    self.angle_offset = np.clip(np.degrees(x[States.ANGLE_OFFSET].item() + x[States.ANGLE_OFFSET_FAST].item()),
+                        self.angle_offset - MAX_ANGLE_OFFSET_DELTA, self.angle_offset + MAX_ANGLE_OFFSET_DELTA)
+    self.roll = np.clip(float(x[States.ROAD_ROLL].item()), self.roll - ROLL_MAX_DELTA, self.roll + ROLL_MAX_DELTA)
+    roll_std = float(P[States.ROAD_ROLL].item())
+    if self.active and self.observed_speed > LOW_ACTIVE_SPEED:
+      # Account for the opposite signs of the yaw rates
+      # At low speeds, bumping into a curb can cause the yaw rate to be very high
+      sensors_valid = bool(abs(self.observed_speed * (x[States.YAW_RATE].item() + self.observed_yaw_rate)) < LATERAL_ACC_SENSOR_THRESHOLD)
+    else:
+      sensors_valid = True
+    self.avg_offset_valid = check_valid_with_hysteresis(self.avg_offset_valid, self.avg_angle_offset, OFFSET_MAX, OFFSET_LOWERED_MAX)
+    self.total_offset_valid = check_valid_with_hysteresis(self.total_offset_valid, self.angle_offset, OFFSET_MAX, OFFSET_LOWERED_MAX)
+    self.roll_valid = check_valid_with_hysteresis(self.roll_valid, self.roll, ROLL_MAX, ROLL_LOWERED_MAX)
+
+    msg = messaging.new_message('liveParameters')
+
+    msg.valid = valid
+
+    liveParameters = msg.liveParameters
+    liveParameters.posenetValid = True
+    liveParameters.sensorValid = sensors_valid
+    liveParameters.steerRatio = float(x[States.STEER_RATIO].item())
+    liveParameters.stiffnessFactor = float(x[States.STIFFNESS].item())
+    liveParameters.roll = float(self.roll)
+    liveParameters.angleOffsetAverageDeg = float(self.avg_angle_offset)
+    liveParameters.angleOffsetDeg = float(self.angle_offset)
+    liveParameters.steerRatioValid = self.min_sr <= liveParameters.steerRatio <= self.max_sr
+    liveParameters.stiffnessFactorValid = 0.2 <= liveParameters.stiffnessFactor <= 5.0
+    liveParameters.angleOffsetAverageValid = bool(self.avg_offset_valid)
+    liveParameters.angleOffsetValid = bool(self.total_offset_valid)
+    liveParameters.valid = all((
+      liveParameters.angleOffsetAverageValid,
+      liveParameters.angleOffsetValid ,
+      self.roll_valid,
+      roll_std < ROLL_STD_MAX,
+      liveParameters.stiffnessFactorValid,
+      liveParameters.steerRatioValid,
+    ))
+    liveParameters.steerRatioStd = float(P[States.STEER_RATIO].item())
+    liveParameters.stiffnessFactorStd = float(P[States.STIFFNESS].item())
+    liveParameters.angleOffsetAverageStd = float(P[States.ANGLE_OFFSET].item())
+    liveParameters.angleOffsetFastStd = float(P[States.ANGLE_OFFSET_FAST].item())
+    if debug:
+      liveParameters.debugFilterState = log.LiveParametersData.FilterState.new_message()
+      liveParameters.debugFilterState.value = x.tolist()
+      liveParameters.debugFilterState.std = P.tolist()
+
+    return msg
 
 
 def check_valid_with_hysteresis(current_valid: bool, val: float, threshold: float, lowered_threshold: float):
@@ -123,6 +199,65 @@ def check_valid_with_hysteresis(current_valid: bool, val: float, threshold: floa
   return current_valid
 
 
+# TODO: Remove this function after few releases (added in 0.9.9)
+def migrate_cached_vehicle_params_if_needed(params_reader: Params):
+  last_parameters_data = params_reader.get("LiveParameters")
+  if last_parameters_data is None:
+    return
+
+  try:
+    last_parameters_dict = json.loads(last_parameters_data)
+    last_parameters_msg = messaging.new_message('liveParameters')
+    last_parameters_msg.liveParameters.valid = True
+    last_parameters_msg.liveParameters.steerRatio = last_parameters_dict['steerRatio']
+    last_parameters_msg.liveParameters.stiffnessFactor = last_parameters_dict['stiffnessFactor']
+    last_parameters_msg.liveParameters.angleOffsetAverageDeg = last_parameters_dict['angleOffsetAverageDeg']
+    params_reader.put("LiveParameters", last_parameters_msg.to_bytes())
+  except Exception:
+    pass
+
+
+def retrieve_initial_vehicle_params(params_reader: Params, CP: car.CarParams, replay: bool, debug: bool):
+  last_parameters_data = params_reader.get("LiveParameters")
+  last_carparams_data = params_reader.get("CarParamsPrevRoute")
+
+  steer_ratio, stiffness_factor, angle_offset_deg, p_initial = CP.steerRatio, 1.0, 0.0, None
+
+  retrieve_success = False
+  if last_parameters_data is not None and last_carparams_data is not None:
+    try:
+      with log.Event.from_bytes(last_parameters_data) as last_lp_msg, car.CarParams.from_bytes(last_carparams_data) as last_CP:
+        lp = last_lp_msg.liveParameters
+        # Check if car model matches
+        if last_CP.carFingerprint != CP.carFingerprint:
+          raise Exception("Car model mismatch")
+
+        # Check if starting values are sane
+        min_sr, max_sr = 0.5 * CP.steerRatio, 2.0 * CP.steerRatio
+        steer_ratio_sane = min_sr <= lp.steerRatio <= max_sr
+        if not steer_ratio_sane:
+          raise Exception(f"Invalid starting values found {lp}")
+
+        initial_filter_std = np.array(lp.debugFilterState.std)
+        if debug and len(initial_filter_std) != 0:
+          p_initial = np.diag(initial_filter_std)
+
+        steer_ratio, stiffness_factor, angle_offset_deg = lp.steerRatio, lp.stiffnessFactor, lp.angleOffsetAverageDeg
+        retrieve_success = True
+    except Exception as e:
+      cloudlog.error(f"Failed to retrieve initial values: {e}")
+
+  if not replay:
+    # When driving in wet conditions the stiffness can go down, and then be too low on the next drive
+    # Without a way to detect this we have to reset the stiffness every drive
+    stiffness_factor = 1.0
+
+  if not retrieve_success:
+    cloudlog.info("Parameter learner resetting to default values")
+
+  return steer_ratio, stiffness_factor, angle_offset_deg, p_initial
+
+
 def main():
   config_realtime_process([0, 1, 2, 3], 5)
 
@@ -133,59 +268,12 @@ def main():
   sm = messaging.SubMaster(['livePose', 'liveCalibration', 'carState'], poll='livePose')
 
   params_reader = Params()
-  # wait for stats about the car to come in from controls
-  cloudlog.info("paramsd is waiting for CarParams")
   CP = messaging.log_from_bytes(params_reader.get("CarParams", block=True), car.CarParams)
-  cloudlog.info("paramsd got CarParams")
 
-  min_sr, max_sr = 0.5 * CP.steerRatio, 2.0 * CP.steerRatio
+  migrate_cached_vehicle_params_if_needed(params_reader)
 
-  params = params_reader.get("LiveParameters")
-
-  # Check if car model matches
-  if params is not None:
-    params = json.loads(params)
-    if params.get('carFingerprint', None) != CP.carFingerprint:
-      cloudlog.info("Parameter learner found parameters for wrong car.")
-      params = None
-
-  # Check if starting values are sane
-  if params is not None:
-    try:
-      steer_ratio_sane = min_sr <= params['steerRatio'] <= max_sr
-      if not steer_ratio_sane:
-        cloudlog.info(f"Invalid starting values found {params}")
-        params = None
-    except Exception as e:
-      cloudlog.info(f"Error reading params {params}: {str(e)}")
-      params = None
-
-  # TODO: cache the params with the capnp struct
-  if params is None:
-    params = {
-      'carFingerprint': CP.carFingerprint,
-      'steerRatio': CP.steerRatio,
-      'stiffnessFactor': 1.0,
-      'angleOffsetAverageDeg': 0.0,
-    }
-    cloudlog.info("Parameter learner resetting to default values")
-
-  if not REPLAY:
-    # When driving in wet conditions the stiffness can go down, and then be too low on the next drive
-    # Without a way to detect this we have to reset the stiffness every drive
-    params['stiffnessFactor'] = 1.0
-
-  pInitial = None
-  if DEBUG:
-    pInitial = np.array(params['debugFilterState']['std']) if 'debugFilterState' in params else None
-
-  learner = ParamsLearner(CP, params['steerRatio'], params['stiffnessFactor'], math.radians(params['angleOffsetAverageDeg']), pInitial)
-  angle_offset_average = params['angleOffsetAverageDeg']
-  angle_offset = angle_offset_average
-  roll = 0.0
-  avg_offset_valid = True
-  total_offset_valid = True
-  roll_valid = True
+  steer_ratio, stiffness_factor, angle_offset_deg, pInitial = retrieve_initial_vehicle_params(params_reader, CP, REPLAY, DEBUG)
+  learner = VehicleParamsLearner(CP, steer_ratio, stiffness_factor, np.radians(angle_offset_deg), pInitial)
 
   while True:
     sm.update()
@@ -196,72 +284,13 @@ def main():
           learner.handle_log(t, which, sm[which])
 
     if sm.updated['livePose']:
-      x = learner.kf.x
-      P = np.sqrt(learner.kf.P.diagonal())
-      if not all(map(math.isfinite, x)):
-        cloudlog.error("NaN in liveParameters estimate. Resetting to default values")
-        learner = ParamsLearner(CP, CP.steerRatio, 1.0, 0.0)
-        x = learner.kf.x
-
-      angle_offset_average = np.clip(math.degrees(x[States.ANGLE_OFFSET].item()),
-                                  angle_offset_average - MAX_ANGLE_OFFSET_DELTA, angle_offset_average + MAX_ANGLE_OFFSET_DELTA)
-      angle_offset = np.clip(math.degrees(x[States.ANGLE_OFFSET].item() + x[States.ANGLE_OFFSET_FAST].item()),
-                          angle_offset - MAX_ANGLE_OFFSET_DELTA, angle_offset + MAX_ANGLE_OFFSET_DELTA)
-      roll = np.clip(float(x[States.ROAD_ROLL].item()), roll - ROLL_MAX_DELTA, roll + ROLL_MAX_DELTA)
-      roll_std = float(P[States.ROAD_ROLL].item())
-      if learner.active and learner.speed > LOW_ACTIVE_SPEED:
-        # Account for the opposite signs of the yaw rates
-        # At low speeds, bumping into a curb can cause the yaw rate to be very high
-        sensors_valid = bool(abs(learner.speed * (x[States.YAW_RATE].item() + learner.yaw_rate)) < LATERAL_ACC_SENSOR_THRESHOLD)
-      else:
-        sensors_valid = True
-      avg_offset_valid = check_valid_with_hysteresis(avg_offset_valid, angle_offset_average, OFFSET_MAX, OFFSET_LOWERED_MAX)
-      total_offset_valid = check_valid_with_hysteresis(total_offset_valid, angle_offset, OFFSET_MAX, OFFSET_LOWERED_MAX)
-      roll_valid = check_valid_with_hysteresis(roll_valid, roll, ROLL_MAX, ROLL_LOWERED_MAX)
-
-      msg = messaging.new_message('liveParameters')
-
-      liveParameters = msg.liveParameters
-      liveParameters.posenetValid = True
-      liveParameters.sensorValid = sensors_valid
-      liveParameters.steerRatio = float(x[States.STEER_RATIO].item())
-      liveParameters.stiffnessFactor = float(x[States.STIFFNESS].item())
-      liveParameters.roll = float(roll)
-      liveParameters.angleOffsetAverageDeg = float(angle_offset_average)
-      liveParameters.angleOffsetDeg = float(angle_offset)
-      liveParameters.steerRatioValid = min_sr <= liveParameters.steerRatio <= max_sr
-      liveParameters.stiffnessFactorValid = 0.2 <= liveParameters.stiffnessFactor <= 5.0
-      liveParameters.angleOffsetAverageValid = bool(avg_offset_valid)
-      liveParameters.angleOffsetValid = bool(total_offset_valid)
-      liveParameters.valid = all((
-        liveParameters.angleOffsetAverageValid,
-        liveParameters.angleOffsetValid ,
-        roll_valid,
-        roll_std < ROLL_STD_MAX,
-        liveParameters.stiffnessFactorValid,
-        liveParameters.steerRatioValid,
-      ))
-      liveParameters.steerRatioStd = float(P[States.STEER_RATIO].item())
-      liveParameters.stiffnessFactorStd = float(P[States.STIFFNESS].item())
-      liveParameters.angleOffsetAverageStd = float(P[States.ANGLE_OFFSET].item())
-      liveParameters.angleOffsetFastStd = float(P[States.ANGLE_OFFSET_FAST].item())
-      if DEBUG:
-        liveParameters.debugFilterState = log.LiveParametersData.FilterState.new_message()
-        liveParameters.debugFilterState.value = x.tolist()
-        liveParameters.debugFilterState.std = P.tolist()
-
-      msg.valid = sm.all_checks()
+      msg = learner.get_msg(sm.all_checks(), debug=DEBUG)
 
+      msg_dat = msg.to_bytes()
       if sm.frame % 1200 == 0:  # once a minute
-        params = {
-          'carFingerprint': CP.carFingerprint,
-          'steerRatio': liveParameters.steerRatio,
-          'stiffnessFactor': liveParameters.stiffnessFactor,
-          'angleOffsetAverageDeg': liveParameters.angleOffsetAverageDeg,
-        }
-        params_reader.put_nonblocking("LiveParameters", json.dumps(params))
-
-      pm.send('liveParameters', msg)
+        params_reader.put_nonblocking("LiveParameters", msg_dat)
+
+      pm.send('liveParameters', msg_dat)
 
 
 if __name__ == "__main__":

selfdrive/locationd/test/test_paramsd.py

@@ -0,0 +1,57 @@
+import random
+import numpy as np
+import json
+
+from cereal import messaging
+from openpilot.selfdrive.locationd.paramsd import retrieve_initial_vehicle_params, migrate_cached_vehicle_params_if_needed
+from openpilot.selfdrive.locationd.models.car_kf import CarKalman
+from openpilot.selfdrive.locationd.test.test_locationd_scenarios import TEST_ROUTE
+from openpilot.selfdrive.test.process_replay.migration import migrate, migrate_carParams
+from openpilot.common.params import Params
+from openpilot.tools.lib.logreader import LogReader
+
+
+def get_random_live_parameters(CP):
+  msg = messaging.new_message("liveParameters")
+  msg.liveParameters.steerRatio = (random.random() + 0.5) * CP.steerRatio
+  msg.liveParameters.stiffnessFactor = random.random()
+  msg.liveParameters.angleOffsetAverageDeg = random.random()
+  msg.liveParameters.debugFilterState.std = [random.random() for _ in range(CarKalman.P_initial.shape[0])]
+  return msg
+
+
+class TestParamsd:
+  def test_read_saved_params(self):
+    params = Params()
+
+    lr = migrate(LogReader(TEST_ROUTE), [migrate_carParams])
+    CP = next(m for m in lr if m.which() == "carParams").carParams
+
+    msg = get_random_live_parameters(CP)
+    params.put("LiveParameters", msg.to_bytes())
+    params.put("CarParamsPrevRoute", CP.as_builder().to_bytes())
+
+    migrate_cached_vehicle_params_if_needed(params) # this is not tested here but should not mess anything up or throw an error
+    sr, sf, offset, p_init = retrieve_initial_vehicle_params(params, CP, replay=True, debug=True)
+    np.testing.assert_allclose(sr, msg.liveParameters.steerRatio)
+    np.testing.assert_allclose(sf, msg.liveParameters.stiffnessFactor)
+    np.testing.assert_allclose(offset, msg.liveParameters.angleOffsetAverageDeg)
+    np.testing.assert_equal(p_init.shape, CarKalman.P_initial.shape)
+    np.testing.assert_allclose(np.diagonal(p_init), msg.liveParameters.debugFilterState.std)
+
+  # TODO Remove this test after the support for old format is removed
+  def test_read_saved_params_old_format(self):
+    params = Params()
+
+    lr = migrate(LogReader(TEST_ROUTE), [migrate_carParams])
+    CP = next(m for m in lr if m.which() == "carParams").carParams
+
+    msg = get_random_live_parameters(CP)
+    params.put("LiveParameters", json.dumps(msg.liveParameters.to_dict()))
+    params.put("CarParamsPrevRoute", CP.as_builder().to_bytes())
+
+    migrate_cached_vehicle_params_if_needed(params)
+    sr, sf, offset, _ = retrieve_initial_vehicle_params(params, CP, replay=True, debug=True)
+    np.testing.assert_allclose(sr, msg.liveParameters.steerRatio)
+    np.testing.assert_allclose(sf, msg.liveParameters.stiffnessFactor)
+    np.testing.assert_allclose(offset, msg.liveParameters.angleOffsetAverageDeg)

selfdrive/selfdrived/selfdrived.py

@@ -20,12 +20,12 @@ from openpilot.selfdrive.selfdrived.events import Events, ET
 from openpilot.selfdrive.selfdrived.state import StateMachine
 from openpilot.selfdrive.selfdrived.alertmanager import AlertManager, set_offroad_alert
 
+from openpilot.system.hardware import HARDWARE
 from openpilot.system.version import get_build_metadata
 
 REPLAY = "REPLAY" in os.environ
 SIMULATION = "SIMULATION" in os.environ
 TESTING_CLOSET = "TESTING_CLOSET" in os.environ
-IGNORE_PROCESSES = {"loggerd", "encoderd", "statsd"}
 LONGITUDINAL_PERSONALITY_MAP = {v: k for k, v in log.LongitudinalPersonality.schema.enumerants.items()}
 
 ThermalStatus = log.DeviceState.ThermalStatus
@@ -115,6 +115,12 @@ class SelfdriveD:
     self.state_machine = StateMachine()
     self.rk = Ratekeeper(100, print_delay_threshold=None)
 
+    # some comma three with NVMe experience NVMe dropouts mid-drive that
+    # cause loggerd to crash on write, so ignore it only on that platform
+    self.ignored_processes = set()
+    if HARDWARE.get_device_type() == 'tici' and os.path.exists('/dev/nvme0'):
+      self.ignored_processes = {'loggerd', }
+
     # Determine startup event
     self.startup_event = EventName.startup if build_metadata.openpilot.comma_remote and build_metadata.tested_channel else EventName.startupMaster
     if not car_recognized:
@@ -258,7 +264,7 @@ class SelfdriveD:
       if not_running != self.not_running_prev:
         cloudlog.event("process_not_running", not_running=not_running, error=True)
       self.not_running_prev = not_running
-    if self.sm.recv_frame['managerState'] and (not_running - IGNORE_PROCESSES):
+    if self.sm.recv_frame['managerState'] and (not_running - self.ignored_processes):
       self.events.add(EventName.processNotRunning)
     else:
       if not SIMULATION and not self.rk.lagging:

selfdrive/test/process_replay/process_replay.py

@@ -2,7 +2,6 @@
 import os
 import time
 import copy
-import json
 import heapq
 import signal
 from collections import Counter, OrderedDict
@@ -517,9 +516,10 @@ CONFIGS = [
   ),
   ProcessConfig(
     proc_name="calibrationd",
-    pubs=["carState", "cameraOdometry", "carParams"],
+    pubs=["carState", "cameraOdometry"],
     subs=["liveCalibration"],
     ignore=["logMonoTime"],
+    init_callback=get_car_params_callback,
     should_recv_callback=calibration_rcv_callback,
   ),
   ProcessConfig(
@@ -628,9 +628,7 @@ def get_custom_params_from_lr(lr: LogIterable, initial_state: str = "first") ->
   if len(live_calibration) > 0:
     custom_params["CalibrationParams"] = live_calibration[msg_index].as_builder().to_bytes()
   if len(live_parameters) > 0:
-    lp_dict = live_parameters[msg_index].to_dict()
-    lp_dict["carFingerprint"] = CP.carFingerprint
-    custom_params["LiveParameters"] = json.dumps(lp_dict)
+    custom_params["LiveParameters"] = live_parameters[msg_index].as_builder().to_bytes()
   if len(live_torque_parameters) > 0:
     custom_params["LiveTorqueParameters"] = live_torque_parameters[msg_index].as_builder().to_bytes()
 

selfdrive/test/process_replay/ref_commit

@@ -1 +1 @@
-1904f49bcc97370a842aeee1f831e9ced5a6cad6
+887623a18d82088dc5ed9ecdced55eb0d3f718b1

selfdrive/test/test_onroad.py

@@ -95,6 +95,7 @@ TIMINGS = {
   "modelV2": [2.5, 0.35],
   "driverStateV2": [2.5, 0.40],
   "livePose": [2.5, 0.35],
+  "liveParameters": [2.5, 0.35],
   "wideRoadCameraState": [1.5, 0.35],
 }
 

selfdrive/ui/translations/main_th.ts

@@ -117,31 +117,31 @@
     <name>DeveloperPanel</name>
     <message>
         <source>Joystick Debug Mode</source>
-        <translation type="unfinished"></translation>
+        <translation>โหมดดีบักจอยสติ๊ก</translation>
     </message>
     <message>
         <source>Longitudinal Maneuver Mode</source>
-        <translation type="unfinished"></translation>
+        <translation>โหมดการควบคุมการเร่ง/เบรค</translation>
     </message>
     <message>
         <source>openpilot Longitudinal Control (Alpha)</source>
-        <translation type="unfinished">ระบบควบคุมการเร่ง/เบรคโดย openpilot (Alpha)</translation>
+        <translation>ระบบควบคุมการเร่ง/เบรคโดย openpilot (Alpha)</translation>
     </message>
     <message>
         <source>WARNING: openpilot longitudinal control is in alpha for this car and will disable Automatic Emergency Braking (AEB).</source>
-        <translation type="unfinished">คำเตือน: การควบคุมการเร่ง/เบรคโดย openpilot สำหรับรถคันนี้ยังอยู่ในสถานะ alpha และระบบเบรคฉุกเฉินอัตโนมัติ (AEB) จะถูกปิด</translation>
+        <translation>คำเตือน: การควบคุมการเร่ง/เบรคโดย openpilot สำหรับรถคันนี้ยังอยู่ในสถานะ alpha และระบบเบรคฉุกเฉินอัตโนมัติ (AEB) จะถูกปิด</translation>
     </message>
     <message>
         <source>On this car, openpilot defaults to the car&apos;s built-in ACC instead of openpilot&apos;s longitudinal control. Enable this to switch to openpilot longitudinal control. Enabling Experimental mode is recommended when enabling openpilot longitudinal control alpha.</source>
-        <translation type="unfinished">โดยปกติสำหรับรถคันนี้ openpilot จะควบคุมการเร่ง/เบรคด้วยระบบ ACC จากโรงงาน แทนการควยคุมโดย openpilot เปิดสวิตซ์นี้เพื่อให้ openpilot ควบคุมการเร่ง/เบรค แนะนำให้เปิดโหมดทดลองเมื่อต้องการให้ openpilot ควบคุมการเร่ง/เบรค ซึ่งอยู่ในสถานะ alpha</translation>
+        <translation>โดยปกติสำหรับรถคันนี้ openpilot จะควบคุมการเร่ง/เบรคด้วยระบบ ACC จากโรงงาน แทนการควยคุมโดย openpilot เปิดสวิตซ์นี้เพื่อให้ openpilot ควบคุมการเร่ง/เบรค แนะนำให้เปิดโหมดทดลองเมื่อต้องการให้ openpilot ควบคุมการเร่ง/เบรค ซึ่งอยู่ในสถานะ alpha</translation>
     </message>
     <message>
         <source>Enable ADB</source>
-        <translation type="unfinished"></translation>
+        <translation>เปิด ADB</translation>
     </message>
     <message>
         <source>ADB (Android Debug Bridge) allows connecting to your device over USB or over the network. See https://docs.comma.ai/how-to/connect-to-comma for more info.</source>
-        <translation type="unfinished"></translation>
+        <translation>ADB (Android Debug Bridge) อนุญาตให้เชื่อมต่ออุปกรณ์ของคุณผ่าน USB หรือผ่านเครือข่าย ดูข้อมูลเพิ่มเติมที่ https://docs.comma.ai/how-to/connect-to-comma</translation>
     </message>
 </context>
 <context>
@@ -309,35 +309,37 @@
     <name>FirehosePanel</name>
     <message>
         <source>🔥 Firehose Mode 🔥</source>
-        <translation type="unfinished"></translation>
+        <translation>🔥 โหมดสายยางดับเพลิง 🔥</translation>
     </message>
     <message>
         <source>openpilot learns to drive by watching humans, like you, drive.
 
 Firehose Mode allows you to maximize your training data uploads to improve openpilot&apos;s driving models. More data means bigger models, which means better Experimental Mode.</source>
-        <translation type="unfinished"></translation>
+        <translation>openpilot เรียนรู้วิธีขับรถจากการเฝ้าดูการขับขี่ของมนุษย์เช่นคุณ
+
+โหมดสายยางดับเพลิงช่วยให้คุณอัปโหลดข้อมูลการฝึกฝนได้มากที่สุด เพื่อนำไปพัฒนาโมเดลการขับขี่ของ openpilot ข้อมูลที่มากขึ้นหมายถึงโมเดลที่ใหญ่ขึ้น และนั่นหมายถึงโหมดทดลองที่ดีขึ้น</translation>
     </message>
     <message>
         <source>Firehose Mode: ACTIVE</source>
-        <translation type="unfinished"></translation>
+        <translation>โหมดสายยางดับเพลิง: เปิดใช้งาน</translation>
     </message>
     <message>
         <source>ACTIVE</source>
-        <translation type="unfinished"></translation>
+        <translation>เปิดใช้งาน</translation>
     </message>
     <message>
         <source>For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.&lt;br&gt;&lt;br&gt;Firehose Mode can also work while you&apos;re driving if connected to a hotspot or unlimited SIM card.&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;b&gt;Frequently Asked Questions&lt;/b&gt;&lt;br&gt;&lt;br&gt;&lt;i&gt;Does it matter how or where I drive?&lt;/i&gt; Nope, just drive as you normally would.&lt;br&gt;&lt;br&gt;&lt;i&gt;Do all of my segments get pulled in Firehose Mode?&lt;/i&gt; No, we selectively pull a subset of your segments.&lt;br&gt;&lt;br&gt;&lt;i&gt;What&apos;s a good USB-C adapter?&lt;/i&gt; Any fast phone or laptop charger should be fine.&lt;br&gt;&lt;br&gt;&lt;i&gt;Does it matter which software I run?&lt;/i&gt; Yes, only upstream openpilot (and particular forks) are able to be used for training.</source>
-        <translation type="unfinished"></translation>
+        <translation>เพื่อประสิทธิภาพสูงสุด ควรนำอุปกรณ์เข้ามาข้างใน เชื่อมต่อกับอะแดปเตอร์ USB-C คุณภาพดี และ Wi-Fi สัปดาห์ละครั้ง&lt;br&gt;&lt;br&gt;โหมดสายยางดับเพลิงยังสามารถทำงานระหว่างขับรถได้ หากเชื่อมต่อกับฮอตสปอตหรือซิมการ์ดที่มีเน็ตไม่จำกัด&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;b&gt;คำถามที่พบบ่อย&lt;/b&gt;&lt;br&gt;&lt;br&gt;&lt;i&gt;วิธีการขับหรือสถานที่ขับขี่มีผลหรือไม่?&lt;/i&gt;ไม่มีผล แค่ขับขี่ตามปกติของคุณ&lt;br&gt;&lt;br&gt;&lt;i&gt;เซกเมนต์ทั้งหมดของฉันจะถูกดึงข้อมูลในโหมดสายยางดับเพลิงหรือไม่?&lt;/i&gt;ไม่ใช่ เราจะเลือกดึงข้อมูลเพียงบางส่วนจากเซกเมนต์ของคุณ&lt;br&gt;&lt;br&gt;&lt;i&gt;อะแดปเตอร์ USB-C แบบไหนดี?&lt;/i&gt;ที่ชาร์จเร็วของโทรศัพท์หรือแล็ปท็อปแบบใดก็ได้ สามารถใช้ได้&lt;br&gt;&lt;br&gt;&lt;i&gt;ซอฟต์แวร์ที่ใช้มีผลหรือไม่?&lt;/i&gt;มีผล เฉพาะ openpilot ตัวหลัก (และ fork เฉพาะบางตัว) เท่านั้น ที่สามารถนำข้อมูลไปใช้ฝึกฝนโมเดลได้</translation>
     </message>
     <message numerus="yes">
         <source>&lt;b&gt;%n segment(s)&lt;/b&gt; of your driving is in the training dataset so far.</source>
-        <translation type="unfinished">
-            <numerusform></numerusform>
+        <translation>
+            <numerusform>มีการขับขี่ของคุณ &lt;b&gt;%n เซกเมนต์&lt;/b&gt; อยู่ในชุดข้อมูลการฝึกฝนแล้วในขณะนี้</numerusform>
         </translation>
     </message>
     <message>
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to an unmetered network</source>
-        <translation type="unfinished"></translation>
+        <translation>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;ไม่เปิดใช้งาน&lt;/span&gt;: เชื่อมต่อกับเครือข่ายที่ไม่จำกัดข้อมูล</translation>
     </message>
 </context>
 <context>
@@ -485,11 +487,11 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
     </message>
     <message>
         <source>Waiting to start</source>
-        <translation type="unfinished"></translation>
+        <translation>รอเริ่มทำงาน</translation>
     </message>
     <message>
         <source>System Unresponsive</source>
-        <translation type="unfinished"></translation>
+        <translation>ระบบไม่ตอบสนอง</translation>
     </message>
 </context>
 <context>
@@ -512,7 +514,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
     </message>
     <message>
         <source>Please connect to Wi-Fi to complete initial pairing</source>
-        <translation type="unfinished"></translation>
+        <translation>กรุณาเชื่อมต่อ Wi-Fi เพื่อทำการจับคู่ครั้งแรกให้เสร็จสิ้น</translation>
     </message>
 </context>
 <context>
@@ -554,7 +556,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
     </message>
     <message>
         <source>Remote snapshots</source>
-        <translation type="unfinished"></translation>
+        <translation>ภาพถ่ายระยะไกล</translation>
     </message>
 </context>
 <context>
@@ -670,11 +672,11 @@ This may take up to a minute.</source>
     </message>
     <message>
         <source>Developer</source>
-        <translation type="unfinished"></translation>
+        <translation>นักพัฒนา</translation>
     </message>
     <message>
         <source>Firehose</source>
-        <translation type="unfinished"></translation>
+        <translation>สายยางดับเพลิง</translation>
     </message>
 </context>
 <context>
@@ -995,11 +997,11 @@ This may take up to a minute.</source>
     </message>
     <message>
         <source>Welcome to openpilot</source>
-        <translation type="unfinished"></translation>
+        <translation>ยินดีต้อนรับสู่ openpilot</translation>
     </message>
     <message>
         <source>You must accept the Terms and Conditions to use openpilot. Read the latest terms at &lt;span style=&apos;color: #465BEA;&apos;&gt;https://comma.ai/terms&lt;/span&gt; before continuing.</source>
-        <translation type="unfinished"></translation>
+        <translation>คุณต้องยอมรับข้อกำหนดและเงื่อนไขเพื่อใช้งาน openpilot อ่านข้อกำหนดล่าสุดได้ที่ &lt;span style=&apos;color: #465BEA;&apos;&gt;https://comma.ai/terms&lt;/span&gt; ก่อนดำเนินการต่อ</translation>
     </message>
 </context>
 <context>
@@ -1106,11 +1108,11 @@ This may take up to a minute.</source>
     </message>
     <message>
         <source>Always-On Driver Monitoring</source>
-        <translation type="unfinished"></translation>
+        <translation>การเฝ้าระวังผู้ขับขี่ตลอดเวลา</translation>
     </message>
     <message>
         <source>Enable driver monitoring even when openpilot is not engaged.</source>
-        <translation type="unfinished"></translation>
+        <translation>เปิดใช้งานการเฝ้าระวังผู้ขับขี่แม้เมื่อ openpilot ไม่ได้เข้าควบคุมอยู่</translation>
     </message>
 </context>
 <context>
@@ -1152,15 +1154,15 @@ This may take up to a minute.</source>
     <name>WiFiPromptWidget</name>
     <message>
         <source>Open</source>
-        <translation type="unfinished"></translation>
+        <translation>เปิด</translation>
     </message>
     <message>
         <source>Maximize your training data uploads to improve openpilot&apos;s driving models.</source>
-        <translation type="unfinished"></translation>
+        <translation>อัปโหลดข้อมูลการฝึกฝนให้ได้มากที่สุด เพื่อพัฒนาโมเดลการขับขี่ของ openpilot</translation>
     </message>
     <message>
         <source>&lt;span style=&apos;font-family: &quot;Noto Color Emoji&quot;;&apos;&gt;🔥&lt;/span&gt; Firehose Mode &lt;span style=&apos;font-family: Noto Color Emoji;&apos;&gt;🔥&lt;/span&gt;</source>
-        <translation type="unfinished"></translation>
+        <translation>&lt;span style=&apos;font-family: &quot;Noto Color Emoji&quot;;&apos;&gt;🔥&lt;/span&gt; โหมดสายยางดับเพลิง &lt;span style=&apos;font-family: Noto Color Emoji;&apos;&gt;🔥&lt;/span&gt;</translation>
     </message>
 </context>
 <context>

system/camerad/sensors/ox03c10_registers.h

@@ -65,7 +65,6 @@ const struct i2c_random_wr_payload init_array_ox03c10[] = {
   {0x3008, 0x80}, // io_pad_sel
 
   // FSIN (frame sync) with external pulses
-  {0x3822, 0x33},  // wait for pulse before first frame
   {0x3009, 0x2},
   {0x3015, 0x2},
   {0x383E, 0x80},
@@ -73,6 +72,9 @@ const struct i2c_random_wr_payload init_array_ox03c10[] = {
   {0x3882, 0x8}, {0x3883, 0x0D},
   {0x3836, 0x1F}, {0x3837, 0x40},
 
+  // causes issues on some devices
+  //{0x3822, 0x33},  // wait for pulse before first frame
+
   {0x3892, 0x44},
   {0x3823, 0x41},
 

tinygrad_repo

@@ -1 +1 @@
-Subproject commit 70266e9f94d5a247ccbb2f3a46e72a2fbdaf7a8e
+Subproject commit 0e34f9082e9730b5df9c055b094a43e4565e413b