bump opendbc

# Conflicts:
#	opendbc_repo

.github/workflows/selfdrive_tests.yaml

@@ -227,7 +227,7 @@ jobs:
     - name: Build openpilot
       run: ${{ env.RUN }} "scons -j$(nproc)"
     - name: Test car models
-      timeout-minutes: ${{ contains(runner.name, 'nsc') && (steps.routes-cache.outputs.cache-hit == 'true') && 1 || 20 }}
+      timeout-minutes: ${{ contains(runner.name, 'nsc') && (steps.routes-cache.outputs.cache-hit == 'true') && 1 || 6 }}
       run: |
         ${{ env.RUN }} "MAX_EXAMPLES=1 $PYTEST selfdrive/car/tests/test_models.py && \
                         chmod -R 777 /tmp/comma_download_cache"

RELEASES.md

@@ -1,12 +1,16 @@
-Version 0.9.9 (2025-04-XX)
+Version 0.9.9 (2025-04-30)
 ========================
+* New driving model
 * Tesla Model 3 and Y support thanks to lukasloetkolben!
+* Coming soon
+  * New driving model supervised by MLSIM
+  * An online learner for steering actuator delay
 
 Version 0.9.8 (2025-02-28)
 ========================
 * New driving model
   * Model now gates applying positive acceleration in Chill mode
-* New driving monitoring model
+* New driver monitoring model
   * Reduced false positives related to passengers
 * Image processing pipeline moved to the ISP
   * More GPU time for bigger driving models

cereal/log.capnp

@@ -59,6 +59,7 @@ struct OnroadEvent @0xc4fa6047f024e718 {
     pcmEnable @23;
     pcmDisable @24;
     radarFault @25;
+    radarTempUnavailable @93;
     brakeHold @26;
     parkBrake @27;
     manualRestart @28;
@@ -728,7 +729,7 @@ struct PeripheralState {
 struct RadarState @0x9a185389d6fdd05f {
   mdMonoTime @6 :UInt64;
   carStateMonoTime @11 :UInt64;
-  radarErrors @12 :List(Car.RadarData.Error);
+  radarErrors @13 :Car.RadarData.Error;
 
   leadOne @3 :LeadData;
   leadTwo @4 :LeadData;
@@ -762,6 +763,7 @@ struct RadarState @0x9a185389d6fdd05f {
   calPercDEPRECATED @9 :Int8;
   canMonoTimesDEPRECATED @10 :List(UInt64);
   cumLagMsDEPRECATED @5 :Float32;
+  radarErrorsDEPRECATED @12 :List(Car.RadarData.ErrorDEPRECATED);
 }
 
 struct LiveCalibrationData {

launch_chffrplus.sh

@@ -34,25 +34,25 @@ function launch {
   # Check to see if there's a valid overlay-based update available. Conditions
   # are as follows:
   #
-  # 1. The BASEDIR init file has to exist, with a newer modtime than anything in
-  #    the BASEDIR Git repo. This checks for local development work or the user
+  # 1. The DIR init file has to exist, with a newer modtime than anything in
+  #    the DIR Git repo. This checks for local development work or the user
   #    switching branches/forks, which should not be overwritten.
   # 2. The FINALIZED consistent file has to exist, indicating there's an update
   #    that completed successfully and synced to disk.
 
-  if [ -f "${BASEDIR}/.overlay_init" ]; then
-    find ${BASEDIR}/.git -newer ${BASEDIR}/.overlay_init | grep -q '.' 2> /dev/null
+  if [ -f "${DIR}/.overlay_init" ]; then
+    find ${DIR}/.git -newer ${DIR}/.overlay_init | grep -q '.' 2> /dev/null
     if [ $? -eq 0 ]; then
-      echo "${BASEDIR} has been modified, skipping overlay update installation"
+      echo "${DIR} has been modified, skipping overlay update installation"
     else
       if [ -f "${STAGING_ROOT}/finalized/.overlay_consistent" ]; then
         if [ ! -d /data/safe_staging/old_openpilot ]; then
           echo "Valid overlay update found, installing"
           LAUNCHER_LOCATION="${BASH_SOURCE[0]}"
 
-          mv $BASEDIR /data/safe_staging/old_openpilot
-          mv "${STAGING_ROOT}/finalized" $BASEDIR
-          cd $BASEDIR
+          mv $DIR /data/safe_staging/old_openpilot
+          mv "${STAGING_ROOT}/finalized" $DIR
+          cd $DIR
 
           echo "Restarting launch script ${LAUNCHER_LOCATION}"
           unset AGNOS_VERSION

launch_env.sh

@@ -7,7 +7,7 @@ export OPENBLAS_NUM_THREADS=1
 export VECLIB_MAXIMUM_THREADS=1
 
 if [ -z "$AGNOS_VERSION" ]; then
-  export AGNOS_VERSION="11.10"
+  export AGNOS_VERSION="11.11"
 fi
 
 export STAGING_ROOT="/data/safe_staging"

pyproject.toml

@@ -99,11 +99,13 @@ dev = [
   "av",
   "azure-identity",
   "azure-storage-blob",
+  "dbus-next",
   "dictdiffer",
   "lru-dict",
   "matplotlib",
   "parameterized >=0.8, <0.9",
   "pyautogui",
+  "pygame",
   "pyopencl; platform_machine != 'aarch64'", # broken on arm64
   "pytools < 2024.1.11; platform_machine != 'aarch64'", # pyopencl use a broken version
   "pywinctl",

release/build_release.sh

@@ -40,8 +40,6 @@ rm -f panda/board/obj/panda.bin.signed
 rm -f panda/board/obj/panda_h7.bin.signed
 
 VERSION=$(cat common/version.h | awk -F[\"-]  '{print $2}')
-echo "#define COMMA_VERSION \"$VERSION-release\"" > common/version.h
-
 echo "[-] committing version $VERSION T=$SECONDS"
 git add -f .
 git commit -a -m "openpilot v$VERSION release"
@@ -92,14 +90,9 @@ git add -f .
 git commit --amend -m "openpilot v$VERSION"
 
 # Run tests
-TEST_FILES="tools/"
-cd $SOURCE_DIR
-cp -pR -n --parents $TEST_FILES $BUILD_DIR/
 cd $BUILD_DIR
 RELEASE=1 pytest -n0 -s selfdrive/test/test_onroad.py
-#system/manager/test/test_manager.py
-pytest selfdrive/car/tests/test_car_interfaces.py
-rm -rf $TEST_FILES
+#pytest selfdrive/car/tests/test_car_interfaces.py
 
 if [ ! -z "$RELEASE_BRANCH" ]; then
   echo "[-] pushing release T=$SECONDS"

release/release_files.py

@@ -8,6 +8,7 @@ ROOT = HERE + "/.."
 
 blacklist = [
   ".git/",
+  ".github/workflows/",
 
   "matlab.*.md",
 

selfdrive/car/card.py

@@ -15,7 +15,7 @@ from opendbc.car import DT_CTRL, structs
 from opendbc.car.can_definitions import CanData, CanRecvCallable, CanSendCallable
 from opendbc.car.carlog import carlog
 from opendbc.car.fw_versions import ObdCallback
-from opendbc.car.car_helpers import get_car, get_radar_interface
+from opendbc.car.car_helpers import get_car, interfaces
 from opendbc.car.interfaces import CarInterfaceBase, RadarInterfaceBase
 from opendbc.safety import ALTERNATIVE_EXPERIENCE
 from openpilot.selfdrive.pandad import can_capnp_to_list, can_list_to_can_capnp
@@ -99,7 +99,7 @@ class Car:
           cached_params = _cached_params
 
       self.CI = get_car(*self.can_callbacks, obd_callback(self.params), experimental_long_allowed, num_pandas, cached_params)
-      self.RI = get_radar_interface(self.CI.CP)
+      self.RI = interfaces[self.CI.CP.carFingerprint].RadarInterface(self.CI.CP)
       self.CP = self.CI.CP
 
       # continue onto next fingerprinting step in pandad
@@ -227,7 +227,7 @@ class Car:
 
     if RD is not None:
       tracks_msg = messaging.new_message('liveTracks')
-      tracks_msg.valid = len(RD.errors) == 0
+      tracks_msg.valid = not any(RD.errors.to_dict().values())
       tracks_msg.liveTracks = RD
       self.pm.send('liveTracks', tracks_msg)
 

selfdrive/car/tests/test_car_interfaces.py

@@ -34,14 +34,14 @@ class TestCarInterfaces:
             phases=(Phase.reuse, Phase.generate, Phase.shrink))
   @given(data=st.data())
   def test_car_interfaces(self, car_name, data):
-    CarInterface, CarController, CarState, RadarInterface = interfaces[car_name]
+    CarInterface = interfaces[car_name]
 
     args = get_fuzzy_car_interface_args(data.draw)
 
     car_params = CarInterface.get_params(car_name, args['fingerprints'], args['car_fw'],
                                          experimental_long=args['experimental_long'], docs=False)
     car_params = car_params.as_reader()
-    car_interface = CarInterface(car_params, CarController, CarState)
+    car_interface = CarInterface(car_params)
     assert car_params
     assert car_interface
 

selfdrive/car/tests/test_models.py

@@ -1,5 +1,4 @@
 import time
-import capnp
 import os
 import pytest
 import random
@@ -67,7 +66,7 @@ class TestCarModelBase(unittest.TestCase):
   platform: Platform | None = None
   test_route: CarTestRoute | None = None
 
-  can_msgs: list[capnp.lib.capnp._DynamicStructReader]
+  can_msgs: list[tuple[int, list[CanData]]]
   fingerprint: dict[int, dict[int, int]]
   elm_frame: int | None
   car_safety_mode_frame: int | None
@@ -82,7 +81,8 @@ class TestCarModelBase(unittest.TestCase):
     experimental_long = False
     for msg in lr:
       if msg.which() == "can":
-        can_msgs.append(msg)
+        can = can_capnp_to_list((msg.as_builder().to_bytes(),))[0]
+        can_msgs.append((can[0], [CanData(*can) for can in can[1]]))
         if len(can_msgs) <= FRAME_FINGERPRINT:
           for m in msg.can:
             if m.src < 64:
@@ -146,15 +146,13 @@ class TestCarModelBase(unittest.TestCase):
         raise unittest.SkipTest
       raise Exception(f"missing test route for {cls.platform}")
 
-    car_fw, can_msgs, experimental_long = cls.get_testing_data()
+    car_fw, cls.can_msgs, experimental_long = cls.get_testing_data()
 
     # if relay is expected to be open in the route
     cls.openpilot_enabled = cls.car_safety_mode_frame is not None
 
-    cls.can_msgs = sorted(can_msgs, key=lambda msg: msg.logMonoTime)
-
-    cls.CarInterface, cls.CarController, cls.CarState, cls.RadarInterface = interfaces[cls.platform]
-    cls.CP = cls.CarInterface.get_params(cls.platform,  cls.fingerprint, car_fw, experimental_long, docs=False)
+    cls.CarInterface = interfaces[cls.platform]
+    cls.CP = cls.CarInterface.get_params(cls.platform, cls.fingerprint, car_fw, experimental_long, docs=False)
     assert cls.CP
     assert cls.CP.carFingerprint == cls.platform
 
@@ -165,7 +163,7 @@ class TestCarModelBase(unittest.TestCase):
     del cls.can_msgs
 
   def setUp(self):
-    self.CI = self.CarInterface(self.CP.copy(), self.CarController, self.CarState)
+    self.CI = self.CarInterface(self.CP.copy())
     assert self.CI
 
     # TODO: check safetyModel is in release panda build
@@ -199,8 +197,8 @@ class TestCarModelBase(unittest.TestCase):
     CC = structs.CarControl().as_reader()
 
     for i, msg in enumerate(self.can_msgs):
-      CS = self.CI.update(can_capnp_to_list((msg.as_builder().to_bytes(),)))
-      self.CI.apply(CC, msg.logMonoTime)
+      CS = self.CI.update(msg)
+      self.CI.apply(CC, msg[0])
 
       if CS.canValid:
         can_valid = True
@@ -212,32 +210,32 @@ class TestCarModelBase(unittest.TestCase):
     self.assertEqual(can_invalid_cnt, 0)
 
   def test_radar_interface(self):
-    RI = self.RadarInterface(self.CP)
+    RI = self.CarInterface.RadarInterface(self.CP)
     assert RI
 
     # Since OBD port is multiplexed to bus 1 (commonly radar bus) while fingerprinting,
     # start parsing CAN messages after we've left ELM mode and can expect CAN traffic
     error_cnt = 0
     for i, msg in enumerate(self.can_msgs[self.elm_frame:]):
-      rr: structs.RadarData | None = RI.update(can_capnp_to_list((msg.as_builder().to_bytes(),)))
+      rr: structs.RadarData | None = RI.update(msg)
       if rr is not None and i > 50:
-        error_cnt += structs.RadarData.Error.canError in rr.errors
+        error_cnt += rr.errors.canError
     self.assertEqual(error_cnt, 0)
 
   def test_panda_safety_rx_checks(self):
     if self.CP.dashcamOnly:
       self.skipTest("no need to check panda safety for dashcamOnly")
 
-    start_ts = self.can_msgs[0].logMonoTime
+    start_ts = self.can_msgs[0][0]
 
     failed_addrs = Counter()
     for can in self.can_msgs:
       # update panda timer
-      t = (can.logMonoTime - start_ts) / 1e3
+      t = (can[0] - start_ts) / 1e3
       self.safety.set_timer(int(t))
 
       # run all msgs through the safety RX hook
-      for msg in can.can:
+      for msg in can[1]:
         if msg.src >= 64:
           continue
 
@@ -266,13 +264,16 @@ class TestCarModelBase(unittest.TestCase):
 
   def test_panda_safety_tx_cases(self, data=None):
     """Asserts we can tx common messages"""
+    if self.CP.dashcamOnly:
+      self.skipTest("no need to check panda safety for dashcamOnly")
+
     if self.CP.notCar:
       self.skipTest("Skipping test for notCar")
 
     def test_car_controller(car_control):
       now_nanos = 0
       msgs_sent = 0
-      CI = self.CarInterface(self.CP, self.CarController, self.CarState)
+      CI = self.CarInterface(self.CP)
       for _ in range(round(10.0 / DT_CTRL)):  # make sure we hit the slowest messages
         CI.update([])
         _, sendcan = CI.apply(car_control, now_nanos)
@@ -386,8 +387,8 @@ class TestCarModelBase(unittest.TestCase):
 
     # warm up pass, as initial states may be different
     for can in self.can_msgs[:300]:
-      self.CI.update(can_capnp_to_list((can.as_builder().to_bytes(), )))
-      for msg in filter(lambda m: m.src in range(64), can.can):
+      self.CI.update(can)
+      for msg in filter(lambda m: m.src < 64, can[1]):
         to_send = libsafety_py.make_CANPacket(msg.address, msg.src % 4, msg.dat)
         self.safety.safety_rx_hook(to_send)
 
@@ -396,8 +397,8 @@ class TestCarModelBase(unittest.TestCase):
     checks = defaultdict(int)
     vehicle_speed_seen = self.CP.steerControlType == SteerControlType.angle and not self.CP.notCar
     for idx, can in enumerate(self.can_msgs):
-      CS = self.CI.update(can_capnp_to_list((can.as_builder().to_bytes(), ))).as_reader()
-      for msg in filter(lambda m: m.src in range(64), can.can):
+      CS = self.CI.update(can).as_reader()
+      for msg in filter(lambda m: m.src < 64, can[1]):
         to_send = libsafety_py.make_CANPacket(msg.address, msg.src % 4, msg.dat)
         ret = self.safety.safety_rx_hook(to_send)
         self.assertEqual(1, ret, f"safety rx failed ({ret=}): {(msg.address, msg.src % 4)}")

selfdrive/controls/controlsd.py

@@ -9,7 +9,7 @@ from openpilot.common.params import Params
 from openpilot.common.realtime import config_realtime_process, Priority, Ratekeeper
 from openpilot.common.swaglog import cloudlog
 
-from opendbc.car.car_helpers import get_car_interface
+from opendbc.car.car_helpers import interfaces
 from opendbc.car.vehicle_model import VehicleModel
 from openpilot.selfdrive.controls.lib.drive_helpers import clip_curvature
 from openpilot.selfdrive.controls.lib.latcontrol import LatControl, MIN_LATERAL_CONTROL_SPEED
@@ -33,7 +33,7 @@ class Controls:
     self.CP = messaging.log_from_bytes(self.params.get("CarParams", block=True), car.CarParams)
     cloudlog.info("controlsd got CarParams")
 
-    self.CI = get_car_interface(self.CP)
+    self.CI = interfaces[self.CP.carFingerprint](self.CP)
 
     self.sm = messaging.SubMaster(['liveParameters', 'liveTorqueParameters', 'modelV2', 'selfdriveState',
                                    'liveCalibration', 'livePose', 'longitudinalPlan', 'carState', 'carOutput',

selfdrive/controls/lib/tests/test_latcontrol.py

@@ -17,9 +17,9 @@ class TestLatControl:
 
   @parameterized.expand([(HONDA.HONDA_CIVIC, LatControlPID), (TOYOTA.TOYOTA_RAV4, LatControlTorque),  (NISSAN.NISSAN_LEAF, LatControlAngle)])
   def test_saturation(self, car_name, controller):
-    CarInterface, CarController, CarState, RadarInterface = interfaces[car_name]
+    CarInterface = interfaces[car_name]
     CP = CarInterface.get_non_essential_params(car_name)
-    CI = CarInterface(CP, CarController, CarState)
+    CI = CarInterface(CP)
     VM = VehicleModel(CP)
 
     controller = controller(CP.as_reader(), CI)

selfdrive/controls/plannerd.py

@@ -20,7 +20,7 @@ def main():
   longitudinal_planner = LongitudinalPlanner(CP)
   pm = messaging.PubMaster(['longitudinalPlan', 'driverAssistance'])
   sm = messaging.SubMaster(['carControl', 'carState', 'controlsState', 'liveParameters', 'radarState', 'modelV2', 'selfdriveState'],
-                           poll='modelV2', ignore_avg_freq=['radarState'])
+                           poll='modelV2')
 
   while True:
     sm.update()

selfdrive/controls/radard.py

@@ -6,6 +6,7 @@ from typing import Any
 
 import capnp
 from cereal import messaging, log, car
+from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.params import Params
 from openpilot.common.realtime import DT_MDL, Priority, config_realtime_process
 from openpilot.common.swaglog import cloudlog
@@ -51,7 +52,7 @@ class Track:
   def __init__(self, identifier: int, v_lead: float, kalman_params: KalmanParams):
     self.identifier = identifier
     self.cnt = 0
-    self.aLeadTau = _LEAD_ACCEL_TAU
+    self.aLeadTau = FirstOrderFilter(_LEAD_ACCEL_TAU, 0.45, DT_MDL)
     self.K_A = kalman_params.A
     self.K_C = kalman_params.C
     self.K_K = kalman_params.K
@@ -74,17 +75,12 @@ class Track:
 
     # Learn if constant acceleration
     if abs(self.aLeadK) < 0.5:
-      self.aLeadTau = _LEAD_ACCEL_TAU
+      self.aLeadTau.x = _LEAD_ACCEL_TAU
     else:
-      self.aLeadTau *= 0.9
+      self.aLeadTau.update(0.0)
 
     self.cnt += 1
 
-  def reset_a_lead(self, aLeadK: float, aLeadTau: float):
-    self.kf = KF1D([[self.vLead], [aLeadK]], self.K_A, self.K_C, self.K_K)
-    self.aLeadK = aLeadK
-    self.aLeadTau = aLeadTau
-
   def get_RadarState(self, model_prob: float = 0.0):
     return {
       "dRel": float(self.dRel),
@@ -93,7 +89,7 @@ class Track:
       "vLead": float(self.vLead),
       "vLeadK": float(self.vLeadK),
       "aLeadK": float(self.aLeadK),
-      "aLeadTau": float(self.aLeadTau),
+      "aLeadTau": float(self.aLeadTau.x),
       "status": True,
       "fcw": self.is_potential_fcw(model_prob),
       "modelProb": model_prob,
@@ -211,9 +207,7 @@ class RadarD:
       self.v_ego_hist.append(self.v_ego)
       self.last_v_ego_frame = sm.recv_frame['carState']
 
-    ar_pts = {}
-    for pt in rr.points:
-      ar_pts[pt.trackId] = [pt.dRel, pt.yRel, pt.vRel, pt.measured]
+    ar_pts = {pt.trackId: [pt.dRel, pt.yRel, pt.vRel, pt.measured] for pt in rr.points}
 
     # *** remove missing points from meta data ***
     for ids in list(self.tracks.keys()):
@@ -233,10 +227,10 @@ class RadarD:
       self.tracks[ids].update(rpt[0], rpt[1], rpt[2], v_lead, rpt[3])
 
     # *** publish radarState ***
-    self.radar_state_valid = sm.all_checks() and len(rr.errors) == 0
+    self.radar_state_valid = sm.all_checks()
     self.radar_state = log.RadarState.new_message()
     self.radar_state.mdMonoTime = sm.logMonoTime['modelV2']
-    self.radar_state.radarErrors = list(rr.errors)
+    self.radar_state.radarErrors = rr.errors
     self.radar_state.carStateMonoTime = sm.logMonoTime['carState']
 
     if len(sm['modelV2'].velocity.x):

selfdrive/controls/tests/test_leads.py

@@ -26,6 +26,6 @@ class TestLeads:
     msgs = [m for _ in range(3) for m in single_iter_pkg()]
     out = replay_process_with_name("card", msgs, fingerprint=TOYOTA.TOYOTA_COROLLA_TSS2)
     states = [m for m in out if m.which() == "liveTracks"]
-    failures = [not state.valid and len(state.liveTracks.errors) for state in states]
+    failures = [not state.valid for state in states]
 
     assert len(states) == 0 or all(failures)

selfdrive/debug/check_can_parser_performance.py

@@ -6,7 +6,6 @@ from tqdm import tqdm
 from cereal import car
 from opendbc.car.tests.routes import CarTestRoute
 from openpilot.selfdrive.car.tests.test_models import TestCarModelBase
-from openpilot.selfdrive.pandad import can_capnp_to_list
 from openpilot.tools.plotjuggler.juggle import DEMO_ROUTE
 
 N_RUNS = 10
@@ -25,13 +24,11 @@ if __name__ == '__main__':
   CC = car.CarControl.new_message()
   ets = []
   for _ in tqdm(range(N_RUNS)):
-    msgs = [m.as_builder().to_bytes() for m in tm.can_msgs]
     start_t = time.process_time_ns()
-    for msg in msgs:
-      can_list = can_capnp_to_list([msg])
+    for msg in tm.can_msgs:
       for cp in tm.CI.can_parsers.values():
         if cp is not None:
-          cp.update_strings(can_list)
+          cp.update_strings(msg)
     ets.append((time.process_time_ns() - start_t) * 1e-6)
 
   print(f'{len(tm.can_msgs)} CAN packets, {N_RUNS} runs')

selfdrive/debug/run_process_on_route.py

@@ -10,21 +10,21 @@ if __name__ == "__main__":
                                    formatter_class=argparse.ArgumentDefaultsHelpFormatter)
   parser.add_argument("--fingerprint", help="The fingerprint to use")
   parser.add_argument("route", help="The route name to use")
-  parser.add_argument("process", help="The process to run")
+  parser.add_argument("process", nargs='+', help="The process(s) to run")
   args = parser.parse_args()
 
-  cfg = [c for c in CONFIGS if c.proc_name == args.process][0]
+  cfgs = [c for c in CONFIGS if c.proc_name in args.process]
 
   lr = LogReader(args.route)
   inputs = list(lr)
 
-  outputs = replay_process(cfg, inputs, fingerprint=args.fingerprint)
+  outputs = replay_process(cfgs, inputs, fingerprint=args.fingerprint)
 
   # Remove message generated by the process under test and merge in the new messages
   produces = {o.which() for o in outputs}
   inputs = [i for i in inputs if i.which() not in produces]
   outputs = sorted(inputs + outputs, key=lambda x: x.logMonoTime)
 
-  fn = f"{args.route.replace('/', '_')}_{args.process}.zst"
+  fn = f"{args.route.replace('/', '_')}_{'_'.join(args.process)}.zst"
   print(f"Saving log to {fn}")
   save_log(fn, outputs)

selfdrive/debug/test_fw_query_on_routes.py

@@ -65,8 +65,7 @@ if __name__ == "__main__":
           CP = msg.carParams
           car_fw = [fw for fw in CP.carFw if not fw.logging]
           if len(car_fw) == 0:
-            print("no fw")
-            break
+            print("WARNING: no fw")
 
           live_fingerprint = CP.carFingerprint
           live_fingerprint = MIGRATION.get(live_fingerprint, live_fingerprint)
@@ -98,7 +97,7 @@ if __name__ == "__main__":
           print("New style (exact):", exact_matches)
           print("New style (fuzzy):", fuzzy_matches)
 
-          padding = max([len(fw.brand or UNKNOWN_BRAND) for fw in car_fw])
+          padding = max([len(fw.brand or UNKNOWN_BRAND) for fw in car_fw] + [0])
           for version in sorted(car_fw, key=lambda fw: fw.brand):
             subaddr = None if version.subAddress == 0 else hex(version.subAddress)
             print(f"  Brand: {version.brand or UNKNOWN_BRAND:{padding}}, bus: {version.bus} - " +

selfdrive/locationd/locationd.py

@@ -147,13 +147,13 @@ class LocationEstimator:
       self.car_speed = abs(msg.vEgo)
 
     elif which == "liveCalibration":
+      # Note that we use this message during calibration
       if len(msg.rpyCalib) > 0:
         calib = np.array(msg.rpyCalib)
         if calib.min() < -CALIB_RPY_SANITY_CHECK or calib.max() > CALIB_RPY_SANITY_CHECK:
           return HandleLogResult.INPUT_INVALID
 
         self.device_from_calib = rot_from_euler(calib)
-        self.calibrated = msg.calStatus == log.LiveCalibrationData.Status.calibrated
 
     elif which == "cameraOdometry":
       if not self._validate_timestamp(t):

selfdrive/locationd/paramsd.py

@@ -46,18 +46,25 @@ class ParamsLearner:
     self.yaw_rate_std = 0.0
     self.roll = 0.0
     self.steering_angle = 0.0
-    self.roll_valid = False
 
   def handle_log(self, t, which, msg):
     if which == 'livePose':
       device_pose = Pose.from_live_pose(msg)
       calibrated_pose = self.calibrator.build_calibrated_pose(device_pose)
-      self.yaw_rate, self.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:
+        # 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)
 
       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
-      self.roll_valid = (localizer_roll_std < ROLL_STD_MAX) and (ROLL_MIN < localizer_roll < ROLL_MAX) and msg.sensorsOK
-      if self.roll_valid:
+      roll_valid = (localizer_roll_std < ROLL_STD_MAX) and (ROLL_MIN < localizer_roll < ROLL_MAX) and msg.sensorsOK
+      if roll_valid:
         roll = localizer_roll
         # Experimentally found multiplier of 2 to be best trade-off between stability and accuracy or similar?
         roll_std = 2 * localizer_roll_std
@@ -67,18 +74,12 @@ class ParamsLearner:
         roll_std = np.radians(10.0)
       self.roll = np.clip(roll, self.roll - ROLL_MAX_DELTA, self.roll + ROLL_MAX_DELTA)
 
-      yaw_rate_valid = msg.angularVelocityDevice.valid and self.calibrator.calib_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 self.active:
         if msg.posenetOK:
-
-          if yaw_rate_valid:
-            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)]))
+          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)]))
 
           self.kf.predict_and_observe(t,
                                       ObservationKind.ROAD_ROLL,
@@ -224,13 +225,13 @@ def main():
       liveParameters.posenetValid = True
       liveParameters.sensorValid = sensors_valid
       liveParameters.steerRatio = float(x[States.STEER_RATIO].item())
-      liveParameters.steerRatioValid = min_sr <= liveParameters.steerRatio <= max_sr
       liveParameters.stiffnessFactor = float(x[States.STIFFNESS].item())
-      liveParameters.stiffnessFactorValid = 0.2 <= liveParameters.stiffnessFactor <= 5.0
       liveParameters.roll = float(roll)
       liveParameters.angleOffsetAverageDeg = float(angle_offset_average)
-      liveParameters.angleOffsetAverageValid = bool(avg_offset_valid)
       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,

selfdrive/modeld/constants.py

@@ -14,8 +14,14 @@ class ModelConstants:
 
   # model inputs constants
   MODEL_FREQ = 20
+  HISTORY_FREQ = 5
+  HISTORY_LEN_SECONDS = 5
+  TEMPORAL_SKIP = MODEL_FREQ // HISTORY_FREQ
+  FULL_HISTORY_BUFFER_LEN = MODEL_FREQ * HISTORY_LEN_SECONDS
+  INPUT_HISTORY_BUFFER_LEN = HISTORY_FREQ * HISTORY_LEN_SECONDS
+
   FEATURE_LEN = 512
-  FULL_HISTORY_BUFFER_LEN = 100
+
   DESIRE_LEN = 8
   TRAFFIC_CONVENTION_LEN = 2
   LAT_PLANNER_STATE_LEN = 4

selfdrive/modeld/modeld.py

@@ -56,16 +56,24 @@ class ModelState:
   prev_desire: np.ndarray  # for tracking the rising edge of the pulse
 
   def __init__(self, context: CLContext):
-    self.frames = {'input_imgs': DrivingModelFrame(context), 'big_input_imgs': DrivingModelFrame(context)}
+    self.frames = {
+      'input_imgs': DrivingModelFrame(context, ModelConstants.TEMPORAL_SKIP),
+      'big_input_imgs': DrivingModelFrame(context, ModelConstants.TEMPORAL_SKIP)
+    }
     self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32)
 
+    self.full_features_buffer = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN,  ModelConstants.FEATURE_LEN), dtype=np.float32)
+    self.full_desire = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32)
+    self.full_prev_desired_curv = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32)
+    self.temporal_idxs = slice(-1-(ModelConstants.TEMPORAL_SKIP*(ModelConstants.INPUT_HISTORY_BUFFER_LEN-1)), None, ModelConstants.TEMPORAL_SKIP)
+
     # policy inputs
     self.numpy_inputs = {
-      'desire': np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32),
+      'desire': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32),
       'traffic_convention': np.zeros((1, ModelConstants.TRAFFIC_CONVENTION_LEN), dtype=np.float32),
       'lateral_control_params': np.zeros((1, ModelConstants.LATERAL_CONTROL_PARAMS_LEN), dtype=np.float32),
-      'prev_desired_curv': np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32),
-      'features_buffer': np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN,  ModelConstants.FEATURE_LEN), dtype=np.float32),
+      'prev_desired_curv': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32),
+      'features_buffer': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN,  ModelConstants.FEATURE_LEN), dtype=np.float32),
     }
 
     with open(VISION_METADATA_PATH, 'rb') as f:
@@ -104,8 +112,9 @@ class ModelState:
     new_desire = np.where(inputs['desire'] - self.prev_desire > .99, inputs['desire'], 0)
     self.prev_desire[:] = inputs['desire']
 
-    self.numpy_inputs['desire'][0,:-1] = self.numpy_inputs['desire'][0,1:]
-    self.numpy_inputs['desire'][0,-1] = new_desire
+    self.full_desire[0,:-1] = self.full_desire[0,1:]
+    self.full_desire[0,-1] = new_desire
+    self.numpy_inputs['desire'][:] = self.full_desire.reshape((1,ModelConstants.INPUT_HISTORY_BUFFER_LEN,ModelConstants.TEMPORAL_SKIP,-1)).max(axis=2)
 
     self.numpy_inputs['traffic_convention'][:] = inputs['traffic_convention']
     self.numpy_inputs['lateral_control_params'][:] = inputs['lateral_control_params']
@@ -128,15 +137,17 @@ class ModelState:
     self.vision_output = self.vision_run(**self.vision_inputs).numpy().flatten()
     vision_outputs_dict = self.parser.parse_vision_outputs(self.slice_outputs(self.vision_output, self.vision_output_slices))
 
-    self.numpy_inputs['features_buffer'][0,:-1] = self.numpy_inputs['features_buffer'][0,1:]
-    self.numpy_inputs['features_buffer'][0,-1] = vision_outputs_dict['hidden_state'][0, :]
+    self.full_features_buffer[0,:-1] = self.full_features_buffer[0,1:]
+    self.full_features_buffer[0,-1] = vision_outputs_dict['hidden_state'][0, :]
+    self.numpy_inputs['features_buffer'][:] = self.full_features_buffer[0, self.temporal_idxs]
 
     self.policy_output = self.policy_run(**self.policy_inputs).numpy().flatten()
     policy_outputs_dict = self.parser.parse_policy_outputs(self.slice_outputs(self.policy_output, self.policy_output_slices))
 
     # TODO model only uses last value now
-    self.numpy_inputs['prev_desired_curv'][0,:-1] = self.numpy_inputs['prev_desired_curv'][0,1:]
-    self.numpy_inputs['prev_desired_curv'][0,-1,:] = policy_outputs_dict['desired_curvature'][0, :]
+    self.full_prev_desired_curv[0,:-1] = self.full_prev_desired_curv[0,1:]
+    self.full_prev_desired_curv[0,-1,:] = policy_outputs_dict['desired_curvature'][0, :]
+    self.numpy_inputs['prev_desired_curv'][:] = self.full_prev_desired_curv[0, self.temporal_idxs]
 
     combined_outputs_dict = {**vision_outputs_dict, **policy_outputs_dict}
     if SEND_RAW_PRED:

selfdrive/modeld/models/commonmodel.cc

@@ -5,11 +5,12 @@
 
 #include "common/clutil.h"
 
-DrivingModelFrame::DrivingModelFrame(cl_device_id device_id, cl_context context) : ModelFrame(device_id, context) {
+DrivingModelFrame::DrivingModelFrame(cl_device_id device_id, cl_context context, int _temporal_skip) : ModelFrame(device_id, context) {
   input_frames = std::make_unique<uint8_t[]>(buf_size);
+  temporal_skip = _temporal_skip;
   input_frames_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, buf_size, NULL, &err));
-  img_buffer_20hz_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, 2*frame_size_bytes, NULL, &err));
-  region.origin = 1 * frame_size_bytes;
+  img_buffer_20hz_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, (temporal_skip+1)*frame_size_bytes, NULL, &err));
+  region.origin = temporal_skip * frame_size_bytes;
   region.size = frame_size_bytes;
   last_img_cl = CL_CHECK_ERR(clCreateSubBuffer(img_buffer_20hz_cl, CL_MEM_READ_WRITE, CL_BUFFER_CREATE_TYPE_REGION, &region, &err));
 
@@ -20,7 +21,7 @@ DrivingModelFrame::DrivingModelFrame(cl_device_id device_id, cl_context context)
 cl_mem* DrivingModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) {
   run_transform(yuv_cl, MODEL_WIDTH, MODEL_HEIGHT, frame_width, frame_height, frame_stride, frame_uv_offset, projection);
 
-  for (int i = 0; i < 1; i++) {
+  for (int i = 0; i < temporal_skip; i++) {
     CL_CHECK(clEnqueueCopyBuffer(q, img_buffer_20hz_cl, img_buffer_20hz_cl, (i+1)*frame_size_bytes, i*frame_size_bytes, frame_size_bytes, 0, nullptr, nullptr));
   }
   loadyuv_queue(&loadyuv, q, y_cl, u_cl, v_cl, last_img_cl);
@@ -36,6 +37,7 @@ cl_mem* DrivingModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_hei
 DrivingModelFrame::~DrivingModelFrame() {
   deinit_transform();
   loadyuv_destroy(&loadyuv);
+  CL_CHECK(clReleaseMemObject(input_frames_cl));
   CL_CHECK(clReleaseMemObject(img_buffer_20hz_cl));
   CL_CHECK(clReleaseMemObject(last_img_cl));
   CL_CHECK(clReleaseCommandQueue(q));
@@ -57,5 +59,6 @@ cl_mem* MonitoringModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_
 
 MonitoringModelFrame::~MonitoringModelFrame() {
   deinit_transform();
+  CL_CHECK(clReleaseMemObject(input_frame_cl));
   CL_CHECK(clReleaseCommandQueue(q));
 }

selfdrive/modeld/models/commonmodel.h

@@ -64,20 +64,21 @@ protected:
 
 class DrivingModelFrame : public ModelFrame {
 public:
-  DrivingModelFrame(cl_device_id device_id, cl_context context);
+  DrivingModelFrame(cl_device_id device_id, cl_context context, int _temporal_skip);
   ~DrivingModelFrame();
   cl_mem* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection);
 
   const int MODEL_WIDTH = 512;
   const int MODEL_HEIGHT = 256;
   const int MODEL_FRAME_SIZE = MODEL_WIDTH * MODEL_HEIGHT * 3 / 2;
-  const int buf_size = MODEL_FRAME_SIZE * 2;
+  const int buf_size = MODEL_FRAME_SIZE * 2; // 2 frames are temporal_skip frames apart
   const size_t frame_size_bytes = MODEL_FRAME_SIZE * sizeof(uint8_t);
 
 private:
   LoadYUVState loadyuv;
   cl_mem img_buffer_20hz_cl, last_img_cl, input_frames_cl;
   cl_buffer_region region;
+  int temporal_skip;
 };
 
 class MonitoringModelFrame : public ModelFrame {

selfdrive/modeld/models/commonmodel.pxd

@@ -20,7 +20,7 @@ cdef extern from "selfdrive/modeld/models/commonmodel.h":
 
   cppclass DrivingModelFrame:
     int buf_size
-    DrivingModelFrame(cl_device_id, cl_context)
+    DrivingModelFrame(cl_device_id, cl_context, int)
 
   cppclass MonitoringModelFrame:
     int buf_size

selfdrive/modeld/models/commonmodel_pyx.pyx

@@ -59,8 +59,8 @@ cdef class ModelFrame:
 cdef class DrivingModelFrame(ModelFrame):
   cdef cppDrivingModelFrame * _frame
 
-  def __cinit__(self, CLContext context):
-    self._frame = new cppDrivingModelFrame(context.device_id, context.context)
+  def __cinit__(self, CLContext context, int temporal_skip):
+    self._frame = new cppDrivingModelFrame(context.device_id, context.context, temporal_skip)
     self.frame = <cppModelFrame*>(self._frame)
     self.buf_size = self._frame.buf_size
 

selfdrive/modeld/models/driving_policy.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5cae3285c876804e649b14adadcfb8be79a9bd5a1b928113e37f1f08e25e9688
-size 16581121
+oid sha256:98f0121ccb6f850077b04cc91bd33d370fc6cbdc2bd35f1ab55628a15a813f36
+size 15966721

selfdrive/modeld/models/driving_vision.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:29bbf79f9dfd7048c0013bb81e86d9b2979275b95ea1ed8a86d1a86a88695240
+oid sha256:897f80d0388250f99bba69b6a8434560cc0fd83157cbeb0bc134c67fe4e64624
 size 34882971

selfdrive/pandad/panda.cc

@@ -66,6 +66,25 @@ void Panda::set_alternative_experience(uint16_t alternative_experience) {
   handle->control_write(0xdf, alternative_experience, 0);
 }
 
+std::string Panda::serial_read(int port_number) {
+  std::string ret;
+  char buffer[USBPACKET_MAX_SIZE] = {};
+
+  while (true) {
+    int bytes_read = handle->control_read(0xe0, port_number, 0, (unsigned char *)buffer, USBPACKET_MAX_SIZE);
+    if (bytes_read <= 0) {
+      break;
+    }
+    ret.append(buffer, bytes_read);
+  }
+
+  return ret;
+}
+
+void Panda::set_uart_baud(int uart, int rate) {
+  handle->control_write(0xe4, uart, int(rate / 300));
+}
+
 cereal::PandaState::PandaType Panda::get_hw_type() {
   unsigned char hw_query[1] = {0};
 

selfdrive/pandad/panda.h

@@ -64,6 +64,8 @@ public:
   cereal::PandaState::PandaType get_hw_type();
   void set_safety_model(cereal::CarParams::SafetyModel safety_model, uint16_t safety_param=0U);
   void set_alternative_experience(uint16_t alternative_experience);
+  std::string serial_read(int port_number = 0);
+  void set_uart_baud(int uart, int rate);
   void set_fan_speed(uint16_t fan_speed);
   uint16_t get_fan_speed();
   void set_ir_pwr(uint16_t ir_pwr);

selfdrive/pandad/pandad.cc

@@ -452,6 +452,14 @@ void pandad_run(std::vector<Panda *> &pandas) {
       send_peripheral_state(peripheral_panda, &pm);
     }
 
+    // Forward logs from pandas to cloudlog if available
+    for (auto *panda : pandas) {
+      std::string log = panda->serial_read();
+      if (!log.empty()) {
+        LOGD("%s", log.c_str());
+      }
+    }
+
     rk.keepTime();
   }
 

selfdrive/pandad/pandad_api_impl.pyx

@@ -17,14 +17,17 @@ cdef extern from "opendbc/can/common.h":
     vector[CanFrame] frames
 
 cdef extern from "can_list_to_can_capnp.cc":
-  void can_list_to_can_capnp_cpp(const vector[CanFrame] &can_list, string &out, bool sendcan, bool valid)
+  void can_list_to_can_capnp_cpp(const vector[CanFrame] &can_list, string &out, bool sendcan, bool valid) nogil
   void can_capnp_to_can_list_cpp(const vector[string] &strings, vector[CanData] &can_data, bool sendcan)
 
 def can_list_to_can_capnp(can_msgs, msgtype='can', valid=True):
   cdef CanFrame *f
   cdef vector[CanFrame] can_list
+  cdef uint32_t cpp_can_msgs_len = len(can_msgs)
+
+  with nogil:
+    can_list.reserve(cpp_can_msgs_len)
 
-  can_list.reserve(len(can_msgs))
   for can_msg in can_msgs:
     f = &(can_list.emplace_back())
     f.address = can_msg[0]
@@ -32,7 +35,10 @@ def can_list_to_can_capnp(can_msgs, msgtype='can', valid=True):
     f.src = can_msg[2]
 
   cdef string out
-  can_list_to_can_capnp_cpp(can_list, out, msgtype == 'sendcan', valid)
+  cdef bool is_sendcan = (msgtype == 'sendcan')
+  cdef bool is_valid = valid
+  with nogil:
+    can_list_to_can_capnp_cpp(can_list, out, is_sendcan, is_valid)
   return out
 
 def can_capnp_to_list(strings, msgtype='can'):

selfdrive/selfdrived/events.py

@@ -832,6 +832,11 @@ EVENTS: dict[int, dict[str, Alert | AlertCallbackType]] = {
     ET.NO_ENTRY: NoEntryAlert("Radar Error: Restart the Car"),
   },
 
+  EventName.radarTempUnavailable: {
+    ET.SOFT_DISABLE: soft_disable_alert("Radar Temporarily Unavailable"),
+    ET.NO_ENTRY: NoEntryAlert("Radar Temporarily Unavailable"),
+  },
+
   # Every frame from the camera should be processed by the model. If modeld
   # is not processing frames fast enough they have to be dropped. This alert is
   # thrown when over 20% of frames are dropped.

selfdrive/selfdrived/selfdrived.py

@@ -80,7 +80,7 @@ class SelfdriveD:
                                    'managerState', 'liveParameters', 'radarState', 'liveTorqueParameters',
                                    'controlsState', 'carControl', 'driverAssistance', 'alertDebug'] + \
                                    self.camera_packets + self.sensor_packets + self.gps_packets,
-                                  ignore_alive=ignore, ignore_avg_freq=ignore+['radarState',],
+                                  ignore_alive=ignore, ignore_avg_freq=ignore,
                                   ignore_valid=ignore, frequency=int(1/DT_CTRL))
 
     # read params
@@ -269,7 +269,13 @@ class SelfdriveD:
           self.events.add(EventName.cameraFrameRate)
     if not REPLAY and self.rk.lagging:
       self.events.add(EventName.selfdrivedLagging)
-    if len(self.sm['radarState'].radarErrors) or ((not self.rk.lagging or REPLAY) and not self.sm.all_checks(['radarState'])):
+    if not self.sm.valid['radarState']:
+      if self.sm['radarState'].radarErrors.canError:
+        self.events.add(EventName.canError)
+      elif self.sm['radarState'].radarErrors.radarUnavailableTemporary:
+        self.events.add(EventName.radarTempUnavailable)
+      else:
+        self.events.add(EventName.radarFault)
       self.events.add(EventName.radarFault)
     if not self.sm.valid['pandaStates']:
       self.events.add(EventName.usbError)
@@ -305,7 +311,7 @@ class SelfdriveD:
         self.events.add(EventName.posenetInvalid)
       if not self.sm['livePose'].inputsOK:
         self.events.add(EventName.locationdTemporaryError)
-      if not self.sm['liveParameters'].valid and not TESTING_CLOSET and (not SIMULATION or REPLAY):
+      if not self.sm['liveParameters'].valid and cal_status == log.LiveCalibrationData.Status.calibrated and not TESTING_CLOSET and (not SIMULATION or REPLAY):
         self.events.add(EventName.paramsdTemporaryError)
 
     # conservative HW alert. if the data or frequency are off, locationd will throw an error

selfdrive/test/process_replay/migration.py

@@ -241,14 +241,16 @@ def migrate_gpsLocation(msgs):
 
 @migration(inputs=["deviceState", "initData"])
 def migrate_deviceState(msgs):
+  init_data = next((m.initData for _, m in msgs if m.which() == 'initData'), None)
+  device_state = next((m.deviceState for _, m in msgs if m.which() == 'deviceState'), None)
+  if init_data is None or device_state is None:
+    return [], [], []
+
   ops = []
-  dt = None
   for i, msg in msgs:
-    if msg.which() == 'initData':
-      dt = msg.initData.deviceType
     if msg.which() == 'deviceState':
       n = msg.as_builder()
-      n.deviceState.deviceType = dt
+      n.deviceState.deviceType = init_data.deviceType
       ops.append((i, n.as_reader()))
   return ops, [], []
 
@@ -274,7 +276,7 @@ def migrate_pandaStates(msgs):
     "KIA_EV6": HyundaiSafetyFlags.EV_GAS | HyundaiSafetyFlags.CANFD_LKA_STEERING,
   }
   # TODO: get new Ford route
-  safety_param_migration |= {car: FordSafetyFlags.LONG_CONTROL for car in (set(FORD) - FORD.with_flags(FordFlags.CANFD))}
+  safety_param_migration |= dict.fromkeys((set(FORD) - FORD.with_flags(FordFlags.CANFD)), FordSafetyFlags.LONG_CONTROL)
 
   # Migrate safety param base on carParams
   CP = next((m.carParams for _, m in msgs if m.which() == 'carParams'), None)

selfdrive/test/process_replay/process_replay.py

@@ -342,7 +342,7 @@ def card_fingerprint_callback(rc, pm, msgs, fingerprint):
 def get_car_params_callback(rc, pm, msgs, fingerprint):
   params = Params()
   if fingerprint:
-    CarInterface, _, _, _ = interfaces[fingerprint]
+    CarInterface = interfaces[fingerprint]
     CP = CarInterface.get_non_essential_params(fingerprint)
   else:
     can = DummySocket()

selfdrive/test/process_replay/ref_commit

@@ -1 +1 @@
-87088a3540ddfc26356d9b71a3a4f40efcbc9b3b
+e9d57157494480637a8ffb52257d2b660a48be67

selfdrive/test/test_onroad.py

@@ -187,7 +187,7 @@ class TestOnroad:
 
   def test_manager_starting_time(self):
     st = self.ts['managerState']['t'][0]
-    assert (st - self.manager_st) < 10, f"manager.py took {st - self.manager_st}s to publish the first 'managerState' msg"
+    assert (st - self.manager_st) < 12.5, f"manager.py took {st - self.manager_st}s to publish the first 'managerState' msg"
 
   def test_cloudlog_size(self):
     msgs = self.msgs['logMessage']
@@ -391,7 +391,7 @@ class TestOnroad:
     result += "----------------- Model Timing -----------------\n"
     result += "------------------------------------------------\n"
     cfgs = [
-      ("modelV2", 0.045, 0.035),
+      ("modelV2", 0.045, 0.040),  # TODO: this should be stricter but it's hard to measure exactly
       ("driverStateV2", 0.045, 0.035),
     ]
     for (s, instant_max, avg_max) in cfgs:

selfdrive/ui/qt/offroad/firehose.cc

@@ -69,6 +69,7 @@ FirehosePanel::FirehosePanel(SettingsWindow *parent) : QWidget((QWidget*)parent)
     "<br><br>"
     "<b>Frequently Asked Questions</b><br><br>"
     "<i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br>"
+    "<i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br>"
     "<i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br>"
     "<i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training."
   ));
@@ -87,7 +88,7 @@ FirehosePanel::FirehosePanel(SettingsWindow *parent) : QWidget((QWidget*)parent)
       QJsonDocument doc = QJsonDocument::fromJson(response.toUtf8());
       QJsonObject json = doc.object();
       int count = json["firehose"].toInt();
-      contribution_label->setText(tr("<b>%1 %2</b> of your driving are in the training dataset so far.").arg(count).arg(count == 1 ? "segment" : "segments"));
+      contribution_label->setText(tr("<b>%n segment(s)</b> of your driving is in the training dataset so far.", "", count));
       contribution_label->show();
     }
   });

selfdrive/ui/qt/setup/setup.cc

@@ -48,7 +48,8 @@ void Setup::download(QString url) {
   auto version = util::read_file("/VERSION");
 
   struct curl_slist *list = NULL;
-  list = curl_slist_append(list, ("X-openpilot-serial: " + Hardware::get_serial()).c_str());
+  std::string header = "X-openpilot-serial: " + Hardware::get_serial();
+  list = curl_slist_append(list, header.c_str());
 
   char tmpfile[] = "/tmp/installer_XXXXXX";
   FILE *fp = fdopen(mkstemp(tmpfile), "wb");

selfdrive/ui/soundd.py

@@ -69,14 +69,13 @@ class Soundd:
     for sound in sound_list:
       filename, play_count, volume = sound_list[sound]
 
-      wavefile = wave.open(BASEDIR + "/selfdrive/assets/sounds/" + filename, 'r')
+      with wave.open(BASEDIR + "/selfdrive/assets/sounds/" + filename, 'r') as wavefile:
+        assert wavefile.getnchannels() == 1
+        assert wavefile.getsampwidth() == 2
+        assert wavefile.getframerate() == SAMPLE_RATE
 
-      assert wavefile.getnchannels() == 1
-      assert wavefile.getsampwidth() == 2
-      assert wavefile.getframerate() == SAMPLE_RATE
-
-      length = wavefile.getnframes()
-      self.loaded_sounds[sound] = np.frombuffer(wavefile.readframes(length), dtype=np.int16).astype(np.float32) / (2**16/2)
+        length = wavefile.getnframes()
+        self.loaded_sounds[sound] = np.frombuffer(wavefile.readframes(length), dtype=np.int16).astype(np.float32) / (2**16/2)
 
   def get_sound_data(self, frames): # get "frames" worth of data from the current alert sound, looping when required
 

selfdrive/ui/translations/main_ar.ts

@@ -309,33 +309,42 @@
     <name>FirehosePanel</name>
     <message>
         <source>🔥 Firehose Mode 🔥</source>
-        <translation type="unfinished"></translation>
+        <translation>🔥 وضع خرطوم الحريق 🔥</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>يتعلم تطبيق openpilot كيفية القيادة من خلال مشاهدة البشر، مثلك، أثناء القيادة.
+
+يتيح لك وضع خرطوم الحريق زيادة تحميلات بيانات التدريب لتحسين نماذج القيادة في OpenPilot. كلما زادت البيانات، زادت النماذج، مما يعني وضعًا تجريبيًا أفضل.</translation>
     </message>
     <message>
         <source>Firehose Mode: ACTIVE</source>
-        <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
+        <translation>وضع خرطوم الحريق: نشط</translation>
     </message>
     <message>
         <source>ACTIVE</source>
-        <translation type="unfinished"></translation>
+        <translation>نشط</translation>
     </message>
     <message>
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
-        <translation type="unfinished"></translation>
+        <translation>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;غير نشط&lt;/span&gt;: اتصل بشبكة غير محسوبة</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>للحصول على أقصى فعالية، أحضر جهازك إلى الداخل واتصل بمحول USB-C جيد وشبكة Wi-Fi أسبوعياً.&lt;br&gt;&lt;br&gt;يمكن أن يعمل وضع خرطوم الحريق أيضاً أثناء القيادة إذا كنت متصلاً بنقطة اتصال أو ببطاقة SIM غير محدودة.&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;b&gt;الأسئلة المتكررة&lt;/b&gt;&lt;br&gt;&lt;br&gt;&lt;i&gt;هل يهم كيف أو أين أقود؟&lt;/i&gt; لا، فقط قد كما تفعل عادة.&lt;br&gt;&lt;br&gt;&lt;i&gt;هل يتم سحب كل مقاطع رحلاتي في وضع خرطوم الحريق؟&lt;/i&gt; لا، نقوم بسحب مجموعة مختارة من مقاطع رحلاتك.&lt;br&gt;&lt;br&gt;&lt;i&gt;ما هو محول USB-C الجيد؟&lt;/i&gt; أي شاحن سريع للهاتف أو اللابتوب يجب أن يكون مناسباً.&lt;br&gt;&lt;br&gt;&lt;i&gt;هل يهم أي برنامج أستخدم؟&lt;/i&gt; نعم، فقط النسخة الأصلية من openpilot (وأفرع معينة) يمكن استخدامها للتدريب.</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>
+            <numerusform>حتى الآن، يوجد &lt;/b&gt;%n مقطع&lt;b&gt;%n من قيادتك في مجموعة بيانات التدريب.</numerusform>
+            <numerusform>حتى الآن، يوجد &lt;/b&gt;%n مقطع&lt;b&gt;%n من قيادتك في مجموعة بيانات التدريب.</numerusform>
+            <numerusform>حتى الآن، يوجد &lt;/b&gt;%n مقطع&lt;b&gt;%n من قيادتك في مجموعة بيانات التدريب.</numerusform>
+            <numerusform>حتى الآن، يوجد &lt;/b&gt;%n مقطع&lt;b&gt;%n من قيادتك في مجموعة بيانات التدريب.</numerusform>
+            <numerusform>حتى الآن، يوجد &lt;/b&gt;%n مقطع&lt;b&gt;%n من قيادتك في مجموعة بيانات التدريب.</numerusform>
+            <numerusform>حتى الآن، يوجد &lt;/b&gt;%n مقطع&lt;b&gt;%n من قيادتك في مجموعة بيانات التدريب.</numerusform>
+        </translation>
     </message>
 </context>
 <context>
@@ -692,7 +701,7 @@ This may take up to a minute.</source>
     </message>
     <message>
         <source>Firehose</source>
-        <translation type="unfinished"></translation>
+        <translation>خرطوم الحريق</translation>
     </message>
 </context>
 <context>
@@ -1003,22 +1012,22 @@ This may take up to a minute.</source>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>الشروط والأحكام</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>رفض</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>قم بالتمرير للقبول</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>أوافق</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation>مرحباً بكم في 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>يجب عليك قبول الشروط والأحكام لاستخدام openpilot. اقرأ أحدث الشروط على &lt;span style=&apos;color: #465BEA;&apos;&gt;https://comma.ai/terms&lt;/span&gt; قبل الاستمرار.</translation>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>
@@ -1170,15 +1179,15 @@ This may take up to a minute.</source>
     <name>WiFiPromptWidget</name>
     <message>
         <source>Open</source>
-        <translation type="unfinished"></translation>
+        <translation>انفتح</translation>
     </message>
     <message>
         <source>Maximize your training data uploads to improve openpilot&apos;s driving models.</source>
-        <translation type="unfinished"></translation>
+        <translation>قم بزيادة تحميلات بيانات التدريب الخاصة بك لتحسين نماذج القيادة الخاصة بـ 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; وضع خرطوم الحريق &lt;span style=&apos;font-family: Noto Color Emoji;&apos;&gt;🔥&lt;/span&gt;</translation>
     </message>
 </context>
 <context>

selfdrive/ui/translations/main_de.ts

@@ -321,14 +321,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>Firehose Mode: ACTIVE</source>
         <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
-    </message>
     <message>
         <source>ACTIVE</source>
         <translation type="unfinished"></translation>
@@ -337,6 +329,17 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
         <translation type="unfinished"></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>
+    </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>
+            <numerusform></numerusform>
+        </translation>
+    </message>
 </context>
 <context>
     <name>HudRenderer</name>
@@ -987,22 +990,22 @@ This may take up to a minute.</source>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>Benutzungsbedingungen</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>Ablehnen</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>Scrolle herunter um zu akzeptieren</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>Zustimmen</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation type="unfinished"></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>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>

selfdrive/ui/translations/main_en.ts

@@ -1,6 +1,16 @@
 <?xml version="1.0" encoding="utf-8"?>
 <!DOCTYPE TS>
 <TS version="2.1" language="en_US">
+<context>
+    <name>FirehosePanel</name>
+    <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>
+            <numerusform>&lt;b&gt;%n segment&lt;/b&gt; of your driving is in the training dataset so far.</numerusform>
+            <numerusform>&lt;b&gt;%n segments&lt;/b&gt; of your driving are in the training dataset so far.</numerusform>
+        </translation>
+    </message>
+</context>
 <context>
     <name>InputDialog</name>
     <message numerus="yes">

selfdrive/ui/translations/main_es.ts

@@ -321,14 +321,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>Firehose Mode: ACTIVE</source>
         <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
-    </message>
     <message>
         <source>ACTIVE</source>
         <translation type="unfinished"></translation>
@@ -337,6 +329,17 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
         <translation type="unfinished"></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>
+    </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>
+            <numerusform></numerusform>
+        </translation>
+    </message>
 </context>
 <context>
     <name>HudRenderer</name>
@@ -987,22 +990,22 @@ Esto puede tardar un minuto.</translation>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>Términos &amp; Condiciones</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>Rechazar</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>Desliza para aceptar</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>Aceptar</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation type="unfinished"></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>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>

selfdrive/ui/translations/main_fr.ts

@@ -321,14 +321,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>Firehose Mode: ACTIVE</source>
         <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
-    </message>
     <message>
         <source>ACTIVE</source>
         <translation type="unfinished"></translation>
@@ -337,6 +329,17 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
         <translation type="unfinished"></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>
+    </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>
+            <numerusform></numerusform>
+        </translation>
+    </message>
 </context>
 <context>
     <name>HudRenderer</name>
@@ -987,22 +990,22 @@ Cela peut prendre jusqu&apos;à une minute.</translation>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>Termes &amp; Conditions</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>Refuser</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>Faire défiler pour accepter</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>Accepter</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation type="unfinished"></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>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>

selfdrive/ui/translations/main_ja.ts

@@ -321,14 +321,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>Firehose Mode: ACTIVE</source>
         <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
-    </message>
     <message>
         <source>ACTIVE</source>
         <translation type="unfinished"></translation>
@@ -337,6 +329,16 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
         <translation type="unfinished"></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>
+    </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>
+    </message>
 </context>
 <context>
     <name>HudRenderer</name>
@@ -983,22 +985,22 @@ This may take up to a minute.</source>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>利用規約</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>拒否</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>スクロールして同意</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>同意</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation type="unfinished"></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>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>

selfdrive/ui/translations/main_ko.ts

@@ -129,11 +129,11 @@
     </message>
     <message>
         <source>WARNING: openpilot longitudinal control is in alpha for this car and will disable Automatic Emergency Braking (AEB).</source>
-        <translation>경고: openpilot 가감속 제어 알파 기능으로 차량의 자동긴급제동(AEB)을 비활성화합니다.</translation>
+        <translation>경고: openpilot 가감속 제어는 알파 기능으로 차량의 자동긴급제동(AEB)기능이 작동하지 않습니다.</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>이 차량은 openpilot 가감속 제어 대신 기본적으로 차량의 ACC로 가감속을 제어합니다. openpilot의 가감속 제어로 전환하려면 이 기능을 활성화하세요. openpilot 가감속 제어 알파를 활성화하는 경우 실험 모드 활성화를 권장합니다.</translation>
+        <translation>이 차량에서 openpilot은 openpilot 가감속 제어 대신 기본적으로 차량의 ACC로 가감속을 제어합니다. openpilot 가감속 제어로 전환하려면 이 기능을 활성화하세요. openpilot 가감속 제어 알파 기능을 활성화하는 경우 실험 모드 활성화를 권장합니다.</translation>
     </message>
     <message>
         <source>Enable ADB</source>
@@ -315,27 +315,31 @@
         <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>오픈파일럿은 여러분과 같은 사람이 운전하는 모습을 보면서 운전하는 법을 배웁니다.
+
+파이어호스 모드를 사용하면 훈련 데이터 업로드를 최대화하여 오픈파일럿의 주행 모델을 개선할 수 있습니다. 더 많은 데이터는 더 큰 모델을 의미하며, 이는 더 나은 실험 모드를 의미합니다.</translation>
     </message>
     <message>
         <source>Firehose Mode: ACTIVE</source>
-        <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
+        <translation>파이어호스 모드: 활성화</translation>
     </message>
     <message>
         <source>ACTIVE</source>
-        <translation type="unfinished"></translation>
+        <translation>활성화</translation>
     </message>
     <message>
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
-        <translation type="unfinished"></translation>
+        <translation>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;비활성&lt;/span&gt;: 무제한 네트워크에 연결</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>최대한의 효과를 얻으려면 매주 장치를 실내로 가져와 좋은 USB-C 케이블에 연결하고 Wi-Fi에 연결하세요.&lt;br&gt;&lt;br&gt;파이어호스 모드는 핫스팟 또는 무제한 SIM 카드에 연결된 경우에는 운전 중에도 작동할 수 있습니다.&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;b&gt;자주 묻는 질문&lt;/b&gt;&lt;br&gt;&lt;br&gt;&lt;i&gt;운전 방법이나 장소가 중요한가요?&lt;/i&gt; 아니요, 평소처럼 운전하시면 됩니다.&lt;br&gt;&lt;br&gt;&lt;i&gt;파이어호스 모드에서 제 모든 구간을 가져오나요?.&lt;br&gt;&lt;br&gt;&lt;i&gt; 아니요, 저희는 여러분의 구간 중 일부를 선별적으로 가져옵니다.&lt;br&gt;&lt;br&gt;&lt;i&gt;좋은 USB-C 케이블은 무엇인가요?&lt;/i&gt; 휴대폰이나 노트북 고속 충전기가 있으면 됩니다.&lt;br&gt;&lt;br&gt;&lt;i&gt;어떤 소프트웨어를 실행하는지가 중요한가요?&lt;/i&gt; 예, 오직 공식 openpilot의 특정 포크만 트레이닝에 사용할 수 있습니다.</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>
     </message>
 </context>
 <context>
@@ -441,7 +445,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
     </message>
     <message>
         <source>openpilot was unable to identify your car. Your car is either unsupported or its ECUs are not recognized. Please submit a pull request to add the firmware versions to the proper vehicle. Need help? Join discord.comma.ai.</source>
-        <translation>openpilot이 차량을 식별할 수 없었습니다. 지원되지 않는 차량이거나 ECU가 인식되지 않습니다. 해당 차량에 맞는 펌웨어 버전을 추가하려면 PR을 제출하세요. 도움이 필요하시면 discord.comma.ai에 가입하세요.</translation>
+        <translation>openpilot이 차량을 식별할 수 없습니다. 지원되지 않는 차량이거나 ECU가 인식되지 않습니다. 해당 차량에 맞는 펌웨어 버전을 추가하려면 PR을 제출하세요. 도움이 필요하시면 discord.comma.ai에 가입하세요.</translation>
     </message>
     <message>
         <source>openpilot detected a change in the device&apos;s mounting position. Ensure the device is fully seated in the mount and the mount is firmly secured to the windshield.</source>
@@ -449,7 +453,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
     </message>
     <message>
         <source>Device temperature too high. System cooling down before starting. Current internal component temperature: %1</source>
-        <translation>장치 온도가 너무 높습니다. 시작하기 전에 온도를 낮춰주세요. 현재 내부 부품 온도: %1</translation>
+        <translation>장치의 온도가 너무 높습니다. 시작 전에 온도를 낮춰주세요. 현재 내부 구성 요소 온도: %1</translation>
     </message>
 </context>
 <context>
@@ -983,22 +987,22 @@ This may take up to a minute.</source>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>이용약관</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>거절</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>동의하려면 아래로 스크롤하세요</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>동의</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation>오픈 파일럿에 오신 것을 환영합니다.</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>오픈파일럿을 사용하려면 이용약관에 동의해야 합니다. 최신 약관은 &lt;span style=&apos;color: #465BEA;&apos;&gt;https://comma.ai/terms&lt;/span&gt; 에서 최신 약관을 읽은 후 계속하세요.</translation>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>
@@ -1100,7 +1104,7 @@ This may take up to a minute.</source>
     </message>
     <message>
         <source>The driving visualization will transition to the road-facing wide-angle camera at low speeds to better show some turns. The Experimental mode logo will also be shown in the top right corner.</source>
-        <translation>운전 시각화는 일부 회전을 더 잘 보여주기 위해 저속에서 도로를 향한 광각 카메라로 전환됩니다. 실험 모드 로고도 우측 상단에 표시됩니다.</translation>
+        <translation>운전 시각화는 일부 회전을 더 잘 보여주기 위해 저속에서 도로를 향한 광각 카메라로 전환됩니다. 우측 상단에 실험 모드 로고가 표시됩니다.</translation>
     </message>
     <message>
         <source>Always-On Driver Monitoring</source>
@@ -1108,7 +1112,7 @@ This may take up to a minute.</source>
     </message>
     <message>
         <source>Enable driver monitoring even when openpilot is not engaged.</source>
-        <translation>Openpilot이 활성화되지 않은 경우에도 드라이버 모니터링을 활성화합니다.</translation>
+        <translation>openpilot이 활성화되지 않은 경우에도 드라이버 모니터링을 활성화합니다.</translation>
     </message>
 </context>
 <context>

selfdrive/ui/translations/main_pt-BR.ts

@@ -309,33 +309,38 @@
     <name>FirehosePanel</name>
     <message>
         <source>🔥 Firehose Mode 🔥</source>
-        <translation>🔥 Mode Firehose 🔥</translation>
+        <translation>🔥 Modo Firehose 🔥</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>O openpilot aprende a dirigir observando humanos, como você, dirigirem.
+
+O Modo Firehose permite maximizar o envio de dados de treinamento para melhorar os modelos de direção do openpilot. Mais dados significam modelos maiores, o que resulta em um Modo Experimental melhor.</translation>
     </message>
     <message>
         <source>Firehose Mode: ACTIVE</source>
-        <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
+        <translation>Modo Firehose: ATIVO</translation>
     </message>
     <message>
         <source>ACTIVE</source>
-        <translation type="unfinished"></translation>
+        <translation>ATIVO</translation>
     </message>
     <message>
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
-        <translation type="unfinished"></translation>
+        <translation>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INATIVO&lt;/span&gt;: conecte-se a uma rede sem restrição &lt;br&gt; de dados</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>Para maior eficácia, leve seu dispositivo para dentro de casa e conecte-o a um bom adaptador USB-C e Wi-Fi semanalmente.&lt;br&gt;&lt;br&gt;O Modo Firehose também pode funcionar enquanto você dirige, se estiver conectado a um hotspot ou a um chip SIM com dados ilimitados.&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;b&gt;Perguntas Frequentes&lt;/b&gt;&lt;br&gt;&lt;br&gt;&lt;i&gt;Importa como ou onde eu dirijo?&lt;/i&gt; Não, basta dirigir normalmente.&lt;br&gt;&lt;br&gt;&lt;i&gt;Todos os meus segmentos são enviados no Modo Firehose?&lt;/i&gt; Não, selecionamos apenas um subconjunto dos seus segmentos.&lt;br&gt;&lt;br&gt;&lt;i&gt;Qual é um bom adaptador USB-C?&lt;/i&gt; Qualquer carregador rápido de telefone ou laptop deve ser suficiente.&lt;br&gt;&lt;br&gt;&lt;i&gt;Importa qual software eu uso?&lt;/i&gt; Sim, apenas o openpilot oficial (e alguns forks específicos) podem ser usados para treinamento.</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>
+            <numerusform>&lt;b&gt;%n segmento&lt;/b&gt; da sua direção está no conjunto de dados de treinamento até agora.</numerusform>
+            <numerusform>&lt;b&gt;%n segmentos&lt;/b&gt; da sua direção estão no conjunto de dados de treinamento até agora.</numerusform>
+        </translation>
     </message>
 </context>
 <context>
@@ -987,22 +992,22 @@ Isso pode levar até um minuto.</translation>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>Termos &amp; Condições</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>Declinar</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>Role a tela para aceitar</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>Concordo</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation>Bem vindo ao 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>Você deve aceitar os Termos e Condições para usar o openpilot. Leia os termos mais recentes em &lt;span style=&apos;color: #465BEA;&apos;&gt;https://comma.ai/terms&lt;/span&gt; antes de continuar.</translation>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>
@@ -1162,7 +1167,7 @@ Isso pode levar até um minuto.</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>&lt;span style=&apos;font-family: &quot;Noto Color Emoji&quot;;&apos;&gt;🔥&lt;/span&gt; Mode Firehose &lt;span style=&apos;font-family: Noto Color Emoji;&apos;&gt;🔥&lt;/span&gt;</translation>
+        <translation>&lt;span style=&apos;font-family: &quot;Noto Color Emoji&quot;;&apos;&gt;🔥&lt;/span&gt; Modo Firehose &lt;span style=&apos;font-family: Noto Color Emoji;&apos;&gt;🔥&lt;/span&gt;</translation>
     </message>
 </context>
 <context>

selfdrive/ui/translations/main_th.ts

@@ -321,14 +321,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>Firehose Mode: ACTIVE</source>
         <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
-    </message>
     <message>
         <source>ACTIVE</source>
         <translation type="unfinished"></translation>
@@ -337,6 +329,16 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
         <translation type="unfinished"></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>
+    </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>
+    </message>
 </context>
 <context>
     <name>HudRenderer</name>
@@ -983,22 +985,22 @@ This may take up to a minute.</source>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>ข้อตกลงและเงื่อนไข</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>ปฏิเสธ</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>เลื่อนเพื่อตอบรับข้อตกลง</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>ยอมรับ</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation type="unfinished"></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>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>

selfdrive/ui/translations/main_tr.ts

@@ -321,14 +321,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>Firehose Mode: ACTIVE</source>
         <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
-    </message>
     <message>
         <source>ACTIVE</source>
         <translation type="unfinished"></translation>
@@ -337,6 +329,16 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
         <translation type="unfinished"></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>
+    </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>
+    </message>
 </context>
 <context>
     <name>HudRenderer</name>
@@ -981,22 +983,22 @@ This may take up to a minute.</source>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>Şartlar ve Koşullar</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>Reddet</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>Kabul etmek için kaydırın</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>Kabul et</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation type="unfinished"></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>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>

selfdrive/ui/translations/main_zh-CHS.ts

@@ -315,27 +315,31 @@
         <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 通过观察人类驾驶（包括您）来学习如何驾驶。
+
+“训练数据上传模式”允许您最大化上传训练数据，以改进 openpilot 的驾驶模型。更多数据意味着更强大的模型，也就意味着更优秀的“实验模式”。</translation>
     </message>
     <message>
         <source>Firehose Mode: ACTIVE</source>
-        <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
+        <translation>训练数据上传模式：激活中</translation>
     </message>
     <message>
         <source>ACTIVE</source>
-        <translation type="unfinished"></translation>
+        <translation>激活中</translation>
     </message>
     <message>
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
-        <translation type="unfinished"></translation>
+        <translation>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;未激活&lt;/span&gt;：请连接至不限流量的网络</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>为了达到最佳效果，请每周将您的设备带回室内，并连接到优质的 USB-C 充电器和 Wi-Fi。&lt;br&gt;&lt;br&gt;Firehose 模式在行驶时也能运行，但需连接到移动热点或使用不限流量的 SIM 卡。&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;b&gt;常见问题&lt;/b&gt;&lt;br&gt;&lt;br&gt;&lt;i&gt;我开车的方式或地点有影响吗？&lt;/i&gt;不会，请像平常一样驾驶即可。&lt;br&gt;&lt;br&gt;&lt;i&gt;Firehose 模式会上传所有的驾驶片段吗？&lt;/i&gt;不会，我们会选择性地上传部分片段。&lt;br&gt;&lt;br&gt;&lt;i&gt;什么是好的 USB-C 充电器？&lt;/i&gt;任何快速手机或笔记本电脑充电器都应该适用。&lt;br&gt;&lt;br&gt;&lt;i&gt;我使用的软件版本有影响吗？&lt;/i&gt;有的，只有官方 openpilot（以及特定的分支）可以用于训练。</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>
+            <numerusform>&lt;b&gt;目前已有 %n 段&lt;/b&gt; 您的驾驶数据被纳入训练数据集。</numerusform>
+        </translation>
     </message>
 </context>
 <context>
@@ -983,22 +987,22 @@ This may take up to a minute.</source>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>条款和条件</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>拒绝</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>滑动以接受</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>同意</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation>欢迎使用 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>您必须接受《条款与条件》才能使用 openpilot。在继续之前，请先阅读最新条款：&lt;span style=&apos;color: #465BEA;&apos;&gt;https://comma.ai/terms&lt;/span&gt;。</translation>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>

selfdrive/ui/translations/main_zh-CHT.ts

@@ -315,27 +315,31 @@
         <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 透過觀察人類駕駛（包括您）來學習如何駕駛。
+
+「訓練資料上傳模式」可讓您最大化上傳訓練數據，以改進 openpilot 的駕駛模型。更多數據代表更強大的模型，也就意味著更優秀的「實驗模式」。</translation>
     </message>
     <message>
         <source>Firehose Mode: ACTIVE</source>
-        <translation type="unfinished"></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;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>
-    </message>
-    <message>
-        <source>&lt;b&gt;%1 %2&lt;/b&gt; of your driving are in the training dataset so far.</source>
-        <translation type="unfinished"></translation>
+        <translation>訓練資料上傳模式：啟用中</translation>
     </message>
     <message>
         <source>ACTIVE</source>
-        <translation type="unfinished"></translation>
+        <translation>啟用中</translation>
     </message>
     <message>
         <source>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;INACTIVE&lt;/span&gt;: connect to unmetered network</source>
-        <translation type="unfinished"></translation>
+        <translation>&lt;span stylesheet=&apos;font-size: 60px; font-weight: bold; color: #e74c3c;&apos;&gt;未啟用&lt;/span&gt;：請連接至不限流量的網路</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>為了達到最佳效果，請每週將您的裝置帶回室內，並連接至優質的 USB-C 充電器與 Wi-Fi。&lt;br&gt;&lt;br&gt;訓練資料上傳模式在行駛時也能運作，但需連接至行動熱點或使用不限流量的 SIM 卡。&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;b&gt;常見問題&lt;/b&gt;&lt;br&gt;&lt;br&gt;&lt;i&gt;我開車的方式或地點有影響嗎？&lt;/i&gt; 不會，請像平常一樣駕駛即可。&lt;br&gt;&lt;br&gt;&lt;i&gt;訓練資料上傳模式會上傳所有的駕駛片段嗎？&lt;/i&gt;不會，我們會選擇性地上傳部分片段。&lt;br&gt;&lt;br&gt;&lt;i&gt;什麼是好的 USB-C 充電器？&lt;/i&gt;任何快速手機或筆電充電器都應該適用。&lt;br&gt;&lt;br&gt;&lt;i&gt;我使用的軟體版本有影響嗎？&lt;/i&gt;有的，只有官方 openpilot（以及特定的分支）可以用於訓練。</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>
+            <numerusform>&lt;b&gt;目前已有 %n 段&lt;/b&gt; 您的駕駛數據被納入訓練資料集。</numerusform>
+        </translation>
     </message>
 </context>
 <context>
@@ -983,22 +987,22 @@ This may take up to a minute.</source>
 </context>
 <context>
     <name>TermsPage</name>
-    <message>
-        <source>Terms &amp; Conditions</source>
-        <translation>條款和條件</translation>
-    </message>
     <message>
         <source>Decline</source>
         <translation>拒絕</translation>
     </message>
-    <message>
-        <source>Scroll to accept</source>
-        <translation>滑動至頁尾接受條款</translation>
-    </message>
     <message>
         <source>Agree</source>
         <translation>接受</translation>
     </message>
+    <message>
+        <source>Welcome to openpilot</source>
+        <translation>歡迎使用 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>您必須接受《條款與條件》才能使用 openpilot。在繼續之前，請先閱讀最新條款：&lt;span style=&apos;color: #465BEA;&apos;&gt;https://comma.ai/terms&lt;/span&gt;。</translation>
+    </message>
 </context>
 <context>
     <name>TogglesPanel</name>

system/camerad/cameras/camera_qcom2.cc

@@ -141,7 +141,8 @@ void CameraState::set_camera_exposure(float grey_frac) {
   // TODO: Lower latency to 2 frames, by using the histogram outputted by the sensor we can do AE before the debayering is complete
 
   const auto &sensor = camera.sensor;
-  const float cur_ev_ = cur_ev[camera.buf.cur_frame_data.frame_id % 3] * sensor->ev_scale;
+  // Offset idx by one to not get stuck in self loop
+  const float cur_ev_ = cur_ev[(camera.buf.cur_frame_data.frame_id - 1) % 3] * sensor->ev_scale;
 
   // Scale target grey between min and 0.4 depending on lighting conditions
   float new_target_grey = std::clamp(0.4 - 0.3 * log2(1.0 + sensor->target_grey_factor*cur_ev_) / log2(6000.0), target_grey_minimums[camera.cc.camera_num], 0.4);
@@ -268,7 +269,7 @@ void camerad_thread() {
 
   // *** per-cam init ***
   std::vector<std::unique_ptr<CameraState>> cams;
-  for (const auto &config : {WIDE_ROAD_CAMERA_CONFIG, ROAD_CAMERA_CONFIG, DRIVER_CAMERA_CONFIG}) {
+  for (const auto &config : ALL_CAMERA_CONFIGS) {
     auto cam = std::make_unique<CameraState>(&m, config);
     cam->init(&v, device_id, ctx);
     cams.emplace_back(std::move(cam));

system/camerad/cameras/spectra.cc

@@ -237,7 +237,7 @@ SpectraCamera::SpectraCamera(SpectraMaster *master, const CameraConfig &config)
   : m(master),
     enabled(config.enabled),
     cc(config) {
-  ife_buf_depth = (cc.output_type == ISP_RAW_OUTPUT) ? 4 : VIPC_BUFFER_COUNT;
+  ife_buf_depth = VIPC_BUFFER_COUNT;
   assert(ife_buf_depth < MAX_IFE_BUFS);
 }
 
@@ -266,7 +266,7 @@ int SpectraCamera::clear_req_queue() {
   req_mgr_flush_request.link_hdl = link_handle;
   req_mgr_flush_request.flush_type = CAM_REQ_MGR_FLUSH_TYPE_ALL;
   int ret = do_cam_control(m->video0_fd, CAM_REQ_MGR_FLUSH_REQ, &req_mgr_flush_request, sizeof(req_mgr_flush_request));
-  LOGD("flushed all req: %d", ret);
+  LOGD("flushed all req: %d", ret);  // returns a "time until timeout" on clearing the workq
 
   for (int i = 0; i < MAX_IFE_BUFS; ++i) {
     destroySyncObjectAt(i);
@@ -1258,6 +1258,8 @@ void SpectraCamera::camera_close() {
   LOG("-- Stop devices %d", cc.camera_num);
 
   if (enabled) {
+    clear_req_queue();
+
     // ret = device_control(sensor_fd, CAM_STOP_DEV, session_handle, sensor_dev_handle);
     // LOGD("stop sensor: %d", ret);
     int ret = device_control(m->isp_fd, CAM_STOP_DEV, session_handle, isp_dev_handle);
@@ -1328,7 +1330,16 @@ bool SpectraCamera::handle_camera_event(const cam_req_mgr_message *event_data) {
   uint64_t timestamp = event_data->u.frame_msg.timestamp;    // timestamped in the kernel's SOF IRQ callback
   //LOGD("handle cam %d ts %lu req id %lu frame id %lu", cc.camera_num, timestamp, request_id, frame_id_raw);
 
-  if (stress_test("skipping SOF event")) return false;
+  // if there's a lag, some more frames could have already come in before
+  // we cleared the queue, so we'll still get them with valid (> 0) request IDs.
+  if (timestamp < last_requeue_ts) {
+    LOGD("skipping frame: ts before requeue / cam %d ts %lu req id %lu frame id %lu", cc.camera_num, timestamp, request_id, frame_id_raw);
+    return false;
+  }
+
+  if (stress_test("skipping SOF event")) {
+    return false;
+  }
 
   if (!validateEvent(request_id, frame_id_raw)) {
     return false;
@@ -1360,7 +1371,7 @@ bool SpectraCamera::validateEvent(uint64_t request_id, uint64_t frame_id_raw) {
   // check if the request ID is even valid. this happens after queued
   // requests are cleared. unclear if it happens any other time.
   if (request_id == 0) {
-    if (invalid_request_count++ > 10) {
+    if (invalid_request_count++ > ife_buf_depth+2) {
       LOGE("camera %d reset after half second of invalid requests", cc.camera_num);
       clearAndRequeue(request_id_last + 1);
       invalid_request_count = 0;
@@ -1379,7 +1390,7 @@ bool SpectraCamera::validateEvent(uint64_t request_id, uint64_t frame_id_raw) {
 
     if (request_id != request_id_last + 1) {
       LOGE("camera %d requests skipped %ld -> %ld", cc.camera_num, request_id_last, request_id);
-      clearAndRequeue(request_id_last + 1);
+      clearAndRequeue(request_id + 1);
       return false;
     }
   }
@@ -1390,6 +1401,7 @@ void SpectraCamera::clearAndRequeue(uint64_t from_request_id) {
   // clear everything, then queue up a fresh set of frames
   LOGW("clearing and requeuing camera %d from %lu", cc.camera_num, from_request_id);
   clear_req_queue();
+  last_requeue_ts = nanos_since_boot();
   for (uint64_t id = from_request_id; id < from_request_id + ife_buf_depth; ++id) {
     enqueue_frame(id);
   }
@@ -1400,11 +1412,20 @@ bool SpectraCamera::waitForFrameReady(uint64_t request_id) {
   int buf_idx = request_id % ife_buf_depth;
   assert(sync_objs_ife[buf_idx]);
 
+  if (stress_test("sync sleep time")) {
+    util::sleep_for(350);
+    return false;
+  }
+
   auto waitForSync = [&](uint32_t sync_obj, int timeout_ms, const char *sync_type) {
+    double st = millis_since_boot();
     struct cam_sync_wait sync_wait = {};
     sync_wait.sync_obj = sync_obj;
     sync_wait.timeout_ms = stress_test(sync_type) ? 1 : timeout_ms;
-    return do_sync_control(m->cam_sync_fd, CAM_SYNC_WAIT, &sync_wait, sizeof(sync_wait)) == 0;
+    bool ret = do_sync_control(m->cam_sync_fd, CAM_SYNC_WAIT, &sync_wait, sizeof(sync_wait)) == 0;
+    double et = millis_since_boot();
+    if (!ret) LOGE("camera %d %s failed after %.2fms", cc.camera_num, sync_type, et-st);
+    return ret;
   };
 
   // wait for frame from IFE
@@ -1415,6 +1436,7 @@ bool SpectraCamera::waitForFrameReady(uint64_t request_id) {
     // BPS is typically 7ms
     success = waitForSync(sync_objs_bps[buf_idx], 50, "BPS sync");
   }
+
   return success;
 }
 

system/camerad/cameras/spectra.h

@@ -181,6 +181,7 @@ public:
   int sync_objs_ife[MAX_IFE_BUFS] = {};
   int sync_objs_bps[MAX_IFE_BUFS] = {};
   uint64_t request_id_last = 0;
+  uint64_t last_requeue_ts = 0;
   uint64_t frame_id_raw_last = 0;
   int invalid_request_count = 0;
   bool skip_expected = true;
@@ -202,11 +203,16 @@ private:
   inline static bool first_frame_synced = false;
 
   // a mode for stressing edge cases: realignment, sync failures, etc.
-  inline bool stress_test(const char* log) {
-    static double prob = std::stod(util::getenv("SPECTRA_ERROR_PROB", "-1"));;
-    bool triggered = (prob > 0) && ((static_cast<double>(rand()) / RAND_MAX) < prob);
+  inline bool stress_test(std::string log) {
+    static double last_trigger = 0;
+    static double prob = std::stod(util::getenv("SPECTRA_ERROR_PROB", "-1"));
+    static double dt = std::stod(util::getenv("SPECTRA_ERROR_DT", "1"));
+    bool triggered = (prob > 0) && \
+                     ((static_cast<double>(rand()) / RAND_MAX) < prob) && \
+                     (millis_since_boot() - last_trigger) > dt;
     if (triggered) {
-      LOGE("stress test (cam %d): %s", cc.camera_num, log);
+      last_trigger = millis_since_boot();
+      LOGE("stress test (cam %d): %s", cc.camera_num, log.c_str());
     }
     return triggered;
   }

system/camerad/main.cc

@@ -6,9 +6,8 @@
 #include "common/util.h"
 
 int main(int argc, char *argv[]) {
-  int ret = util::set_realtime_priority(53);
-  assert(ret == 0);
-  ret = util::set_core_affinity({6});
+  // doesn't need RT priority since we're using isolcpus
+  int ret = util::set_core_affinity({6});
   assert(ret == 0 || Params().getBool("IsOffroad")); // failure ok while offroad due to offlining cores
 
   camerad_thread();

system/hardware/base.h

@@ -34,8 +34,6 @@ public:
   static bool get_ssh_enabled() { return false; }
   static void set_ssh_enabled(bool enabled) {}
 
-  static void config_cpu_rendering(bool offscreen);
-
   static bool PC() { return false; }
   static bool TICI() { return false; }
   static bool AGNOS() { return false; }

system/hardware/pc/hardware.h

@@ -12,12 +12,4 @@ public:
   static bool PC() { return true; }
   static bool TICI() { return util::getenv("TICI", 0) == 1; }
   static bool AGNOS() { return util::getenv("TICI", 0) == 1; }
-
-  static void config_cpu_rendering(bool offscreen) {
-    if (offscreen) {
-      setenv("QT_QPA_PLATFORM", "offscreen", 1);
-    }
-    setenv("__GLX_VENDOR_LIBRARY_NAME", "mesa", 1);
-    setenv("LP_NUM_THREADS", "0", 1); // disable threading so we stay on our assigned CPU
-  }
 };

system/hardware/tici/agnos.json

@@ -56,28 +56,28 @@
   },
   {
     "name": "boot",
-    "url": "https://commadist.azureedge.net/agnosupdate/boot-bca7573652def58a0afc40bbdd550d63dc08ed2e925ace69032aef84bb9dc4ba.img.xz",
-    "hash": "bca7573652def58a0afc40bbdd550d63dc08ed2e925ace69032aef84bb9dc4ba",
-    "hash_raw": "bca7573652def58a0afc40bbdd550d63dc08ed2e925ace69032aef84bb9dc4ba",
-    "size": 18475008,
+    "url": "https://commadist.azureedge.net/agnosupdate/boot-0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a.img.xz",
+    "hash": "0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a",
+    "hash_raw": "0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a",
+    "size": 18479104,
     "sparse": false,
     "full_check": true,
     "has_ab": true,
-    "ondevice_hash": "8907415564e8a242548e871b534dcd53240fe4e4517700c6c85b5637e365f0b0"
+    "ondevice_hash": "47b2096995578a5078e393c33108b42756009dbb361c43c508fc93cd8bda99cc"
   },
   {
     "name": "system",
-    "url": "https://commadist.azureedge.net/agnosupdate/system-5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9.img.xz",
-    "hash": "e4872f4132111b7b28586d978dd01bb48ffa031e103d029ebede7613c1bc2aa6",
-    "hash_raw": "5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9",
+    "url": "https://commadist.azureedge.net/agnosupdate/system-ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211.img.xz",
+    "hash": "fbda983c40e75d8c4784a45c687f27dd27f97f7f0e9a71b4981ec2092ff68a72",
+    "hash_raw": "ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211",
     "size": 4404019200,
     "sparse": true,
     "full_check": false,
     "has_ab": true,
-    "ondevice_hash": "4e5e680b4ac387ddc974b32dd3d5ec1d76282511eab974866b3b72399034985e",
+    "ondevice_hash": "428c744458d5f35199aab96a0928876c9deeff3e753e95044291408ba244f0af",
     "alt": {
-      "hash": "5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9",
-      "url": "https://commadist.azureedge.net/agnosupdate/system-5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9.img",
+      "hash": "ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211",
+      "url": "https://commadist.azureedge.net/agnosupdate/system-ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211.img",
       "size": 4404019200
     }
   }

system/hardware/tici/all-partitions.json

@@ -339,62 +339,62 @@
   },
   {
     "name": "boot",
-    "url": "https://commadist.azureedge.net/agnosupdate/boot-bca7573652def58a0afc40bbdd550d63dc08ed2e925ace69032aef84bb9dc4ba.img.xz",
-    "hash": "bca7573652def58a0afc40bbdd550d63dc08ed2e925ace69032aef84bb9dc4ba",
-    "hash_raw": "bca7573652def58a0afc40bbdd550d63dc08ed2e925ace69032aef84bb9dc4ba",
-    "size": 18475008,
+    "url": "https://commadist.azureedge.net/agnosupdate/boot-0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a.img.xz",
+    "hash": "0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a",
+    "hash_raw": "0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a",
+    "size": 18479104,
     "sparse": false,
     "full_check": true,
     "has_ab": true,
-    "ondevice_hash": "8907415564e8a242548e871b534dcd53240fe4e4517700c6c85b5637e365f0b0"
+    "ondevice_hash": "47b2096995578a5078e393c33108b42756009dbb361c43c508fc93cd8bda99cc"
   },
   {
     "name": "system",
-    "url": "https://commadist.azureedge.net/agnosupdate/system-5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9.img.xz",
-    "hash": "e4872f4132111b7b28586d978dd01bb48ffa031e103d029ebede7613c1bc2aa6",
-    "hash_raw": "5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9",
+    "url": "https://commadist.azureedge.net/agnosupdate/system-ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211.img.xz",
+    "hash": "fbda983c40e75d8c4784a45c687f27dd27f97f7f0e9a71b4981ec2092ff68a72",
+    "hash_raw": "ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211",
     "size": 4404019200,
     "sparse": true,
     "full_check": false,
     "has_ab": true,
-    "ondevice_hash": "4e5e680b4ac387ddc974b32dd3d5ec1d76282511eab974866b3b72399034985e",
+    "ondevice_hash": "428c744458d5f35199aab96a0928876c9deeff3e753e95044291408ba244f0af",
     "alt": {
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-      "url": "https://commadist.azureedge.net/agnosupdate/system-5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9.img",
+      "hash": "ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211",
+      "url": "https://commadist.azureedge.net/agnosupdate/system-ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211.img",
       "size": 4404019200
     }
   },
   {
     "name": "userdata_90",
-    "url": "https://commadist.azureedge.net/agnosupdate/userdata_90-16c037fa42ee99bc6ec92909efc8a8075a0e8a0232a7d90e39e7d40a7bd0ee8e.img.xz",
-    "hash": "c6fb215f2b297f7ff5b8f133bc5d687772b37f2fee42a44aa730e37a84a14e52",
-    "hash_raw": "16c037fa42ee99bc6ec92909efc8a8075a0e8a0232a7d90e39e7d40a7bd0ee8e",
+    "url": "https://commadist.azureedge.net/agnosupdate/userdata_90-17f46ba0d0eec10cf14804c84d9bcf4f6fa864074f1b90ff2fb4873399d64b1a.img.xz",
+    "hash": "1442ae218daff960783bc493a32dd489fa787e4025c64fa3132f48b1e627647f",
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+    "ondevice_hash": "a64fea9c3a7bec11b850a55d50ceb30a032742c90aadf0ce35cdbef9349bebba"
   },
   {
     "name": "userdata_89",
-    "url": "https://commadist.azureedge.net/agnosupdate/userdata_89-62c2c41470282b581ec1bbbe0375fb3b6c66df2f4bc3dc6c6fdf796f1797f136.img.xz",
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-    "hash_raw": "62c2c41470282b581ec1bbbe0375fb3b6c66df2f4bc3dc6c6fdf796f1797f136",
+    "url": "https://commadist.azureedge.net/agnosupdate/userdata_89-69b2404839f87b1de5c05766550ca0217d5ed566c9f2ea41c46b5a301540a3ac.img.xz",
+    "hash": "332e6cf5c221690a01ebfd0582420e039c7796a8fb2d499e44a8b657dffe4af2",
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+    "ondevice_hash": "c560c76007fd8997e01e516ab16ff445048945a13bf830bb2a4c7f6e9d2fe5f6"
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   {
     "name": "userdata_30",
-    "url": "https://commadist.azureedge.net/agnosupdate/userdata_30-3e71d8804c90a6dff5048edb976149f9ea177efa139dea47cb585cef76b26f6e.img.xz",
-    "hash": "1b201ecbd0e1573777811bf18fa90cb080bfbccb34a6dcfd39b412632e7ca699",
-    "hash_raw": "3e71d8804c90a6dff5048edb976149f9ea177efa139dea47cb585cef76b26f6e",
+    "url": "https://commadist.azureedge.net/agnosupdate/userdata_30-ffc34d8753520e684448185db801c05bb81e23c54a499cc40a2e38b7009cdf36.img.xz",
+    "hash": "8bfb1fdec9c8f96c97bcce1efbc7d502447bdb3b481cc408b24b5feef66839fd",
+    "hash_raw": "ffc34d8753520e684448185db801c05bb81e23c54a499cc40a2e38b7009cdf36",
     "size": 32212254720,
     "sparse": true,
     "full_check": true,
     "has_ab": false,
-    "ondevice_hash": "47c28e63209556442cd9d2fd06a6c0e7fcf35c8a4e4fbcc550b9c089429ad0e0"
+    "ondevice_hash": "8f840157d73fa4469aa650d668e046c9750304af84248ab83453cbd285918859"
   }
 ]

system/hardware/tici/hardware.h

@@ -109,11 +109,4 @@ public:
 
   static bool get_ssh_enabled() { return Params().getBool("SshEnabled"); }
   static void set_ssh_enabled(bool enabled) { Params().putBool("SshEnabled", enabled); }
-
-  static void config_cpu_rendering(bool offscreen) {
-    if (offscreen) {
-      setenv("QT_QPA_PLATFORM", "eglfs", 1); // offscreen doesn't work with EGL/GLES
-    }
-    setenv("LP_NUM_THREADS", "0", 1); // disable threading so we stay on our assigned CPU
-  }
 };

system/loggerd/loggerd.cc

@@ -165,8 +165,15 @@ int handle_encoder_msg(LoggerdState *s, Message *msg, std::string &name, struct
         s->logger.segment(), offset_segment_num,
         s->ready_to_rotate.load(), s->max_waiting, name.c_str());
     }
-    // queue up all the new segment messages, they go in after the rotate
-    re.q.push_back(msg);
+
+    // TODO: define this behavior, but for now don't leak
+    if (re.q.size() > MAIN_FPS*10) {
+      LOGE_100("%s: dropping frame, queue is too large", name.c_str());
+      delete msg;
+    } else {
+      // queue up all the new segment messages, they go in after the rotate
+      re.q.push_back(msg);
+    }
   } else {
     LOGE("%s: encoderd packet has a older segment!!! idx.getSegmentNum():%d s->logger.segment():%d re.encoderd_segment_offset:%d",
       name.c_str(), idx.getSegmentNum(), s->logger.segment(), re.encoderd_segment_offset);

system/loggerd/tests/test_zstd_writer.cc

@@ -18,15 +18,21 @@ TEST_CASE("ZstdFileWriter writes and compresses data correctly in loops", "[Zstd
   // Step 1: Write compressed data to file in a loop
   {
     ZstdFileWriter writer(filename, LOG_COMPRESSION_LEVEL);
+    // Write various data sizes including edge cases
+    std::vector<size_t> testSizes = {dataSize, 1, 0, dataSize * 2};  // Normal, minimal, empty, large
     for (int i = 0; i < iterations; ++i) {
-      std::string testData = util::random_string(dataSize);
+      size_t currentSize = testSizes[i % testSizes.size()];
+      std::string testData = util::random_string(currentSize);
       totalTestData.append(testData);
+
       writer.write((void *)testData.c_str(), testData.size());
     }
   }
 
   // Step 2: Decompress the file and verify the data
   auto compressedContent = util::read_file(filename);
+  REQUIRE(compressedContent.size() > 0);
+  REQUIRE(compressedContent.size() < totalTestData.size());
   std::string decompressedData = zstd_decompress(compressedContent);
 
   // Step 3: Verify that the decompressed data matches the original accumulated data

system/manager/process.py

@@ -221,8 +221,12 @@ class PythonProcess(ManagerProcess):
     if self.proc is not None:
       return
 
+    # TODO: this is just a workaround for this tinygrad check:
+    # https://github.com/tinygrad/tinygrad/blob/ac9c96dae1656dc220ee4acc39cef4dd449aa850/tinygrad/device.py#L26
+    name = self.name if "modeld" not in self.name else "MainProcess"
+
     cloudlog.info(f"starting python {self.module}")
-    self.proc = Process(name=self.name, target=self.launcher, args=(self.module, self.name))
+    self.proc = Process(name=name, target=self.launcher, args=(self.module, self.name))
     self.proc.start()
     self.watchdog_seen = False
     self.shutting_down = False

system/manager/process_config.py

@@ -75,10 +75,8 @@ procs = [
   PythonProcess("micd", "system.micd", iscar),
   PythonProcess("timed", "system.timed", always_run, enabled=not PC),
 
-  # TODO: Make python process once TG allows opening QCOM from child pro
-  # https://github.com/tinygrad/tinygrad/blob/ac9c96dae1656dc220ee4acc39cef4dd449aa850/tinygrad/device.py#L26
-  NativeProcess("modeld", "selfdrive/modeld", ["./modeld.py"], only_onroad),
-  NativeProcess("dmonitoringmodeld", "selfdrive/modeld", ["./dmonitoringmodeld.py"], driverview, enabled=(WEBCAM or not PC)),
+  PythonProcess("modeld", "selfdrive.modeld.modeld", only_onroad),
+  PythonProcess("dmonitoringmodeld", "selfdrive.modeld.dmonitoringmodeld", driverview, enabled=(WEBCAM or not PC)),
 
   NativeProcess("sensord", "system/sensord", ["./sensord"], only_onroad, enabled=not PC),
   NativeProcess("ui", "selfdrive/ui", ["./ui"], always_run, watchdog_max_dt=(5 if not PC else None)),

system/ui/lib/application.py

@@ -15,6 +15,7 @@ DEBUG_FPS = os.getenv("DEBUG_FPS") == '1'
 STRICT_MODE = os.getenv("STRICT_MODE") == '1'
 
 DEFAULT_TEXT_SIZE = 60
+DEFAULT_TEXT_COLOR = rl.Color(200, 200, 200, 255)
 FONT_DIR = os.path.join(BASEDIR, "selfdrive/assets/fonts")
 
 
@@ -118,7 +119,7 @@ class GuiApplication:
     rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.BORDER_WIDTH, 0)
     rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.TEXT_SIZE, DEFAULT_TEXT_SIZE)
     rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.BACKGROUND_COLOR, rl.color_to_int(rl.BLACK))
-    rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.TEXT_COLOR_NORMAL, rl.color_to_int(rl.Color(200, 200, 200, 255)))
+    rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.TEXT_COLOR_NORMAL, rl.color_to_int(DEFAULT_TEXT_COLOR))
     rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.BACKGROUND_COLOR, rl.color_to_int(rl.Color(30, 30, 30, 255)))
     rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.BASE_COLOR_NORMAL, rl.color_to_int(rl.Color(50, 50, 50, 255)))
 

system/ui/lib/button.py

@@ -54,6 +54,7 @@ def gui_button(
   if button_style != ButtonStyle.TRANSPARENT:
     rl.draw_rectangle_rounded(rect, roundness, 20, bg_color)
   else:
+    rl.draw_rectangle_rounded(rect, roundness, 20, rl.BLACK)
     rl.draw_rectangle_rounded_lines_ex(rect, roundness, 20, 2, rl.WHITE)
 
   font = gui_app.font(font_weight)

system/ui/lib/label.py

@@ -1,11 +1,55 @@
 import pyray as rl
+from openpilot.system.ui.lib.application import gui_app, FontWeight, DEFAULT_TEXT_SIZE, DEFAULT_TEXT_COLOR
 from openpilot.system.ui.lib.utils import GuiStyleContext
 
-def gui_label(rect, text, font_size):
+
+def gui_label(
+  rect: rl.Rectangle,
+  text: str,
+  font_size: int = DEFAULT_TEXT_SIZE,
+  color: rl.Color = DEFAULT_TEXT_COLOR,
+  font_weight: FontWeight = FontWeight.NORMAL,
+  alignment: int = rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
+  alignment_vertical: int = rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE
+):
+  # Set font based on the provided weight
+  font = gui_app.font(font_weight)
+
+  # Measure text size
+  text_size = rl.measure_text_ex(font, text, font_size, 0)
+
+  # Calculate horizontal position based on alignment
+  text_x = rect.x + {
+    rl.GuiTextAlignment.TEXT_ALIGN_LEFT: 0,
+    rl.GuiTextAlignment.TEXT_ALIGN_CENTER: (rect.width - text_size.x) / 2,
+    rl.GuiTextAlignment.TEXT_ALIGN_RIGHT: rect.width - text_size.x,
+  }.get(alignment, 0)
+
+  # Calculate vertical position based on alignment
+  text_y = rect.y + {
+    rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP: 0,
+    rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE: (rect.height - text_size.y) / 2,
+    rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM: rect.height - text_size.y,
+  }.get(alignment_vertical, 0)
+
+  # Draw the text in the specified rectangle
+  rl.draw_text_ex(font, text, rl.Vector2(text_x, text_y), font_size, 0, color)
+
+
+def gui_text_box(
+  rect: rl.Rectangle,
+  text: str,
+  font_size: int = DEFAULT_TEXT_SIZE,
+  color: rl.Color = DEFAULT_TEXT_COLOR,
+  alignment: int = rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
+  alignment_vertical: int = rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP
+):
   styles = [
+    (rl.GuiControl.DEFAULT, rl.GuiControlProperty.TEXT_COLOR_NORMAL, rl.color_to_int(color)),
     (rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.TEXT_SIZE, font_size),
     (rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.TEXT_LINE_SPACING, font_size),
-    (rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.TEXT_ALIGNMENT_VERTICAL, rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP),
+    (rl.GuiControl.DEFAULT, rl.GuiControlProperty.TEXT_ALIGNMENT, alignment),
+    (rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.TEXT_ALIGNMENT_VERTICAL, alignment_vertical),
     (rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.TEXT_WRAP_MODE, rl.GuiTextWrapMode.TEXT_WRAP_WORD)
   ]
 

system/ui/reset.py

@@ -7,7 +7,7 @@ from enum import IntEnum
 
 from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.lib.button import gui_button, ButtonStyle
-from openpilot.system.ui.lib.label import gui_label
+from openpilot.system.ui.lib.label import gui_label, gui_text_box
 
 NVME = "/dev/nvme0n1"
 USERDATA = "/dev/disk/by-partlabel/userdata"
@@ -51,13 +51,11 @@ class Reset:
     threading.Timer(0.1, self.do_reset).start()
 
   def render(self, rect: rl.Rectangle):
-    rl.gui_set_font(gui_app.font(FontWeight.BOLD))
-    label_rect = rl.Rectangle(rect.x + 140, rect.y, rect.width - 280, rect.height)
-    gui_label(label_rect, "System Reset", 90)
-    rl.gui_set_font(gui_app.font(FontWeight.NORMAL))
+    label_rect = rl.Rectangle(rect.x + 140, rect.y, rect.width - 280, 100)
+    gui_label(label_rect, "System Reset", 100, font_weight=FontWeight.BOLD)
 
-    label_rect.y += 150
-    gui_label(label_rect, self.get_body_text(), 80)
+    text_rect = rl.Rectangle(rect.x + 140, rect.y + 140, rect.width - 280, rect.height - 90 - 100)
+    gui_text_box(text_rect, self.get_body_text(), 90)
 
     button_height = 160
     button_spacing = 50

system/ui/text.py

@@ -39,7 +39,7 @@ def main():
 
   text_content = sys.argv[1] if len(sys.argv) > 1 else DEMO_TEXT
 
-  textarea_rect = rl.Rectangle(MARGIN, MARGIN, gui_app.width - MARGIN * 2, gui_app.height - MARGIN * 2 - BUTTON_SIZE.y - SPACING)
+  textarea_rect = rl.Rectangle(MARGIN, MARGIN, gui_app.width - MARGIN * 2, gui_app.height - MARGIN * 2)
   wrapped_lines = wrap_text(text_content, FONT_SIZE, textarea_rect.width - 20)
   content_rect = rl.Rectangle(0, 0, textarea_rect.width - 20, len(wrapped_lines) * LINE_HEIGHT)
   scroll_panel = GuiScrollPanel(show_vertical_scroll_bar=True)

system/ui/widgets/confirm_dialog.py

@@ -0,0 +1,62 @@
+import pyray as rl
+from openpilot.system.ui.lib.button import gui_button, ButtonStyle
+from openpilot.system.ui.lib.label import gui_text_box
+
+# Constants for dialog dimensions and styling
+DIALOG_WIDTH = 1520
+DIALOG_HEIGHT = 600
+BUTTON_HEIGHT = 160
+MARGIN = 50
+TEXT_AREA_HEIGHT_REDUCTION = 200
+BACKGROUND_COLOR = rl.Color(27, 27, 27, 255)
+
+
+def confirm_dialog(rect: rl.Rectangle, message: str, confirm_text: str, cancel_text: str = "Cancel") -> int:
+  # Calculate dialog position and size, centered within the parent rectangle
+  dialog_x = rect.x + (rect.width - DIALOG_WIDTH) / 2
+  dialog_y = rect.y + (rect.height - DIALOG_HEIGHT) / 2
+  dialog_rect = rl.Rectangle(dialog_x, dialog_y, DIALOG_WIDTH, DIALOG_HEIGHT)
+
+  # Calculate button positions at the bottom of the dialog
+  bottom = dialog_rect.y + dialog_rect.height
+  button_width = (dialog_rect.width - 3 * MARGIN) // 2
+  no_button_x = dialog_rect.x + MARGIN
+  yes_button_x = dialog_rect.x + dialog_rect.width - button_width - MARGIN
+  button_y = bottom - BUTTON_HEIGHT - MARGIN
+  no_button = rl.Rectangle(no_button_x, button_y, button_width, BUTTON_HEIGHT)
+  yes_button = rl.Rectangle(yes_button_x, button_y, button_width, BUTTON_HEIGHT)
+
+  # Draw the dialog background
+  rl.draw_rectangle(
+    int(dialog_rect.x),
+    int(dialog_rect.y),
+    int(dialog_rect.width),
+    int(dialog_rect.height),
+    BACKGROUND_COLOR,
+  )
+
+  # Draw the message in the dialog, centered
+  text_rect = rl.Rectangle(dialog_rect.x, dialog_rect.y, dialog_rect.width, dialog_rect.height - TEXT_AREA_HEIGHT_REDUCTION)
+  gui_text_box(
+    text_rect,
+    message,
+    alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+    alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE,
+  )
+
+  # Initialize result; -1 means no action taken yet
+  result = -1
+
+  # Check for keyboard input for accessibility
+  if rl.is_key_pressed(rl.KeyboardKey.KEY_ENTER):
+    result = 1  # Confirm
+  elif rl.is_key_pressed(rl.KeyboardKey.KEY_ESCAPE):
+    result = 0  # Cancel
+
+  # Check for button clicks
+  if gui_button(yes_button, confirm_text, button_style=ButtonStyle.PRIMARY):
+    result = 1  # Confirm
+  if gui_button(no_button, cancel_text):
+    result = 0  # Cancel
+
+  return result

system/ui/widgets/keyboard.py

@@ -0,0 +1,104 @@
+import pyray as rl
+from openpilot.system.ui.lib.button import gui_button
+from openpilot.system.ui.lib.label import gui_label
+
+# Constants for special keys
+BACKSPACE_KEY = "<-"
+ENTER_KEY = "Enter"
+SPACE_KEY = "  "
+SHIFT_KEY = "↑"
+SHIFT_DOWN_KEY = "↓"
+NUMERIC_KEY = "123"
+SYMBOL_KEY = "#+="
+ABC_KEY = "ABC"
+
+# Define keyboard layouts as a dictionary for easier access
+keyboard_layouts = {
+  "lowercase": [
+    ["q", "w", "e", "r", "t", "y", "u", "i", "o", "p"],
+    ["a", "s", "d", "f", "g", "h", "j", "k", "l"],
+    [SHIFT_KEY, "z", "x", "c", "v", "b", "n", "m", BACKSPACE_KEY],
+    [NUMERIC_KEY, "/", "-", SPACE_KEY, ".", ENTER_KEY],
+  ],
+  "uppercase": [
+    ["Q", "W", "E", "R", "T", "Y", "U", "I", "O", "P"],
+    ["A", "S", "D", "F", "G", "H", "J", "K", "L"],
+    [SHIFT_DOWN_KEY, "Z", "X", "C", "V", "B", "N", "M", BACKSPACE_KEY],
+    [NUMERIC_KEY, "/", "-", SPACE_KEY, ".", ENTER_KEY],
+  ],
+  "numbers": [
+    ["1", "2", "3", "4", "5", "6", "7", "8", "9", "0"],
+    ["-", "/", ":", ";", "(", ")", "$", "&", "@", "\""],
+    [SYMBOL_KEY, ".", ",", "?", "!", "`", BACKSPACE_KEY],
+    [ABC_KEY, SPACE_KEY, ".", ENTER_KEY],
+  ],
+  "specials": [
+    ["[", "]", "{", "}", "#", "%", "^", "*", "+", "="],
+    ["_", "\\", "|", "~", "<", ">", "€", "£", "¥", "•"],
+    [NUMERIC_KEY, ".", ",", "?", "!", "'", BACKSPACE_KEY],
+    [ABC_KEY, SPACE_KEY, ".", ENTER_KEY],
+  ],
+}
+
+
+class Keyboard:
+  def __init__(self, max_text_size: int = 255):
+    self._layout = keyboard_layouts["lowercase"]
+    self._input_text = ""
+    self._max_text_size = max_text_size
+
+  @property
+  def text(self) -> str:
+    return self._input_text
+
+  def clear(self):
+    self._input_text = ""
+
+  def render(self, rect, title, sub_title):
+    gui_label(rl.Rectangle(rect.x, rect.y, rect.width, 95), title, 90)
+    gui_label(rl.Rectangle(rect.x, rect.y + 95, rect.width, 60), sub_title, 55, rl.GRAY)
+    if gui_button(rl.Rectangle(rect.x + rect.width - 300, rect.y, 300, 100), "Cancel"):
+      return -1
+
+    # Text box for input
+    rl.gui_text_box(rl.Rectangle(rect.x, rect.y + 160, rect.width, 100), self._input_text, self._max_text_size, True)
+
+    h_space, v_space = 15, 15
+    row_y_start = rect.y + 300  # Starting Y position for the first row
+    key_height = (rect.height - 300 - 3 * v_space) / 4
+    key_max_width = (rect.width - (len(self._layout[2]) - 1) * h_space) / len(self._layout[2])
+
+    # Iterate over the rows of keys in the current layout
+    for row, keys in enumerate(self._layout):
+      key_width = min((rect.width - (180 if row == 1 else 0) - h_space * (len(keys) - 1)) / len(keys), key_max_width)
+      start_x = rect.x + (90 if row == 1 else 0)
+
+      for i, key in enumerate(keys):
+        if i > 0:
+          start_x += h_space
+
+        new_width = (key_width * 3 + h_space * 2) if key == SPACE_KEY else (key_width * 2 + h_space if key == ENTER_KEY else key_width)
+        key_rect = rl.Rectangle(start_x, row_y_start + row * (key_height + v_space), new_width, key_height)
+        start_x += new_width
+
+        if gui_button(key_rect, key):
+          if key == ENTER_KEY:
+            return 1
+          else:
+            self.handle_key_press(key)
+
+    return 0
+
+  def handle_key_press(self, key):
+    if key in (SHIFT_DOWN_KEY, ABC_KEY):
+      self._layout = keyboard_layouts["lowercase"]
+    elif key == SHIFT_KEY:
+      self._layout = keyboard_layouts["uppercase"]
+    elif key == NUMERIC_KEY:
+      self._layout = keyboard_layouts["numbers"]
+    elif key == SYMBOL_KEY:
+      self._layout = keyboard_layouts["specials"]
+    elif key == BACKSPACE_KEY and len(self._input_text) > 0:
+      self._input_text = self._input_text[:-1]
+    elif key != BACKSPACE_KEY and len(self._input_text) < self._max_text_size:
+      self._input_text += key

tools/joystick/joystick_control.py

@@ -28,7 +28,7 @@ class Keyboard:
     key = self.kb.getch().lower()
     self.cancel = False
     if key == 'r':
-      self.axes_values = {ax: 0. for ax in self.axes_values}
+      self.axes_values = dict.fromkeys(self.axes_values, 0.)
     elif key == 'c':
       self.cancel = True
     elif key in self.axes_map:
@@ -65,7 +65,7 @@ class Joystick:
     try:
       joystick_event = get_gamepad()[0]
     except (OSError, UnpluggedError):
-      self.axes_values = {ax: 0. for ax in self.axes_values}
+      self.axes_values = dict.fromkeys(self.axes_values, 0.)
       return False
 
     event = (joystick_event.code, joystick_event.state)

tools/lib/url_file.py

@@ -16,8 +16,7 @@ CHUNK_SIZE = 1000 * K
 logging.getLogger("urllib3").setLevel(logging.WARNING)
 
 def hash_256(link: str) -> str:
-  hsh = str(sha256((link.split("?")[0]).encode('utf-8')).hexdigest())
-  return hsh
+  return sha256((link.split("?")[0]).encode('utf-8')).hexdigest()
 
 
 class URLFileException(Exception):

uv.lock

@@ -12,16 +12,16 @@ resolution-markers = [
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.8"
+version = "2.6.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/de/7c/79a15272e88d2563c9d63599fa59f05778975f35b255bf8f90c8b12b4ada/aiohappyeyeballs-2.4.8.tar.gz", hash = "sha256:19728772cb12263077982d2f55453babd8bec6a052a926cd5c0c42796da8bf62", size = 22337 }
+sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/52/0e/b187e2bb3eeb2644515109657c4474d65a84e7123de249bf1e8467d04a65/aiohappyeyeballs-2.4.8-py3-none-any.whl", hash = "sha256:6cac4f5dd6e34a9644e69cf9021ef679e4394f54e58a183056d12009e42ea9e3", size = 15005 },
+    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265 },
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.11.13"
+version = "3.11.14"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -32,40 +32,40 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
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