Merge remote-tracking branch 'origin/master' into online-lag

common/params_keys.h

@@ -8,6 +8,7 @@ inline static std::unordered_map<std::string, uint32_t> keys = {
     {"AdbEnabled", PERSISTENT},
     {"AlwaysOnDM", PERSISTENT},
     {"ApiCache_Device", PERSISTENT},
+    {"ApiCache_FirehoseStats", PERSISTENT},
     {"AssistNowToken", PERSISTENT},
     {"AthenadPid", PERSISTENT},
     {"AthenadUploadQueue", PERSISTENT},
@@ -36,7 +37,6 @@ inline static std::unordered_map<std::string, uint32_t> keys = {
     {"ExperimentalLongitudinalEnabled", PERSISTENT | DEVELOPMENT_ONLY},
     {"ExperimentalMode", PERSISTENT},
     {"ExperimentalModeConfirmed", PERSISTENT},
-    {"FirehoseMode", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
     {"FirmwareQueryDone", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
     {"ForcePowerDown", PERSISTENT},
     {"GitBranch", PERSISTENT},

conftest.py

@@ -77,8 +77,10 @@ def openpilot_class_fixture():
 
 
 @pytest.fixture(scope="function")
-def tici_setup_fixture(openpilot_function_fixture):
+def tici_setup_fixture(request, openpilot_function_fixture):
   """Ensure a consistent state for tests on-device. Needs the openpilot function fixture to run first."""
+  if 'skip_tici_setup' in request.keywords:
+    return
   HARDWARE.initialize_hardware()
   HARDWARE.set_power_save(False)
   os.system("pkill -9 -f athena")

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="11.9"
+  export AGNOS_VERSION="11.10"
 fi
 
 export STAGING_ROOT="/data/safe_staging"

msgq_repo

@@ -1 +1 @@
-Subproject commit 095f1e23613d47031a9b23e3f9ed5dd3fe01a06e
+Subproject commit ad9020c430362d17c0edf97747d344389234be4d

opendbc_repo

@@ -1 +1 @@
-Subproject commit bc839875bd0ca476be71dea2cbebc92a4544c40c
+Subproject commit e7d08ac4794c859e604d260da010d4685c164e5b

panda

@@ -1 +1 @@
-Subproject commit 2c802449fd51d9904ca265d06b7a5f9969057ae3
+Subproject commit 3bf1f8e871f3c577fccba07f57958f30508a2187

pyproject.toml

@@ -143,6 +143,7 @@ asyncio_default_fixture_loop_scope = "function"
 markers = [
   "slow: tests that take awhile to run and can be skipped with -m 'not slow'",
   "tici: tests that are only meant to run on the C3/C3X",
+  "skip_tici_setup: mark test to skip tici setup fixture"
 ]
 testpaths = [
   "common",
@@ -215,7 +216,7 @@ lint.select = [
   "E", "F", "W", "PIE", "C4", "ISC", "A", "B",
   "NPY", # numpy
   "UP",  # pyupgrade
-  "TRY302", "TRY400", "TRY401", # try/excepts
+  "TRY203", "TRY400", "TRY401", # try/excepts
   "RUF008", "RUF100",
   "TID251",
   "PLR1704",

selfdrive/controls/controlsd.py

@@ -40,7 +40,7 @@ class Controls:
                                    'driverMonitoringState', 'onroadEvents', 'driverAssistance'], poll='selfdriveState')
     self.pm = messaging.PubMaster(['carControl', 'controlsState'])
 
-    self.steer_limited = False
+    self.steer_limited_by_controls = False
     self.desired_curvature = 0.0
 
     self.pose_calibrator = PoseCalibrator()
@@ -109,11 +109,11 @@ class Controls:
     actuators.accel = float(self.LoC.update(CC.longActive, CS, long_plan.aTarget, long_plan.shouldStop, pid_accel_limits))
 
     # Steering PID loop and lateral MPC
-    self.desired_curvature = clip_curvature(CS.vEgo, self.desired_curvature, model_v2.action.desiredCurvature)
+    self.desired_curvature, curvature_limited = clip_curvature(CS.vEgo, self.desired_curvature, model_v2.action.desiredCurvature, lp.roll)
-    actuators.curvature = float(self.desired_curvature)
+    actuators.curvature = self.desired_curvature
     steer, steeringAngleDeg, lac_log = self.LaC.update(CC.latActive, CS, self.VM, lp,
-                                                       self.steer_limited, self.desired_curvature,
+                                                       self.steer_limited_by_controls, self.desired_curvature,
-                                                       self.calibrated_pose)  # TODO what if not available
+                                                       self.calibrated_pose, curvature_limited)  # TODO what if not available
     actuators.torque = float(steer)
     actuators.steeringAngleDeg = float(steeringAngleDeg)
     # Ensure no NaNs/Infs
@@ -161,10 +161,10 @@ class Controls:
     if self.sm['selfdriveState'].active:
       CO = self.sm['carOutput']
       if self.CP.steerControlType == car.CarParams.SteerControlType.angle:
-        self.steer_limited = abs(CC.actuators.steeringAngleDeg - CO.actuatorsOutput.steeringAngleDeg) > \
+        self.steer_limited_by_controls = abs(CC.actuators.steeringAngleDeg - CO.actuatorsOutput.steeringAngleDeg) > \
                                               STEER_ANGLE_SATURATION_THRESHOLD
       else:
-        self.steer_limited = abs(CC.actuators.torque - CO.actuatorsOutput.torque) > 1e-2
+        self.steer_limited_by_controls = abs(CC.actuators.torque - CO.actuatorsOutput.torque) > 1e-2
 
     # TODO: both controlsState and carControl valids should be set by
     #       sm.all_checks(), but this creates a circular dependency
@@ -180,7 +180,7 @@ class Controls:
 
     cs.longitudinalPlanMonoTime = self.sm.logMonoTime['longitudinalPlan']
     cs.lateralPlanMonoTime = self.sm.logMonoTime['modelV2']
-    cs.desiredCurvature = float(self.desired_curvature)
+    cs.desiredCurvature = self.desired_curvature
     cs.longControlState = self.LoC.long_control_state
     cs.upAccelCmd = float(self.LoC.pid.p)
     cs.uiAccelCmd = float(self.LoC.pid.i)

selfdrive/controls/lib/drive_helpers.py

@@ -1,5 +1,6 @@
 import numpy as np
 from cereal import log
+from opendbc.car.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
 from openpilot.common.realtime import DT_CTRL
 
 MIN_SPEED = 1.0
@@ -7,20 +8,33 @@ CONTROL_N = 17
 CAR_ROTATION_RADIUS = 0.0
 # This is a turn radius smaller than most cars can achieve
 MAX_CURVATURE = 0.2
+MAX_VEL_ERR = 5.0  # m/s
 
 # EU guidelines
-MAX_LATERAL_JERK = 5.0
+MAX_LATERAL_JERK = 5.0  # m/s^3
-MAX_VEL_ERR = 5.0
+MAX_LATERAL_ACCEL_NO_ROLL = 3.0  # m/s^2
 
-def clip_curvature(v_ego, prev_curvature, new_curvature):
+
-  new_curvature = np.clip(new_curvature, -MAX_CURVATURE, MAX_CURVATURE)
+def clamp(val, min_val, max_val):
-  v_ego = max(MIN_SPEED, v_ego)
+  clamped_val = float(np.clip(val, min_val, max_val))
+  return clamped_val, clamped_val != val
+
+
+def clip_curvature(v_ego, prev_curvature, new_curvature, roll):
+  # This function respects ISO lateral jerk and acceleration limits + a max curvature
+  v_ego = max(v_ego, MIN_SPEED)
   max_curvature_rate = MAX_LATERAL_JERK / (v_ego ** 2)  # inexact calculation, check https://github.com/commaai/openpilot/pull/24755
-  safe_desired_curvature = np.clip(new_curvature,
+  new_curvature = np.clip(new_curvature,
                           prev_curvature - max_curvature_rate * DT_CTRL,
                           prev_curvature + max_curvature_rate * DT_CTRL)
 
-  return safe_desired_curvature
+  roll_compensation = roll * ACCELERATION_DUE_TO_GRAVITY
+  max_lat_accel = MAX_LATERAL_ACCEL_NO_ROLL + roll_compensation
+  min_lat_accel = -MAX_LATERAL_ACCEL_NO_ROLL + roll_compensation
+  new_curvature, limited_accel = clamp(new_curvature, min_lat_accel / v_ego ** 2, max_lat_accel / v_ego ** 2)
+
+  new_curvature, limited_max_curv = clamp(new_curvature, -MAX_CURVATURE, MAX_CURVATURE)
+  return float(new_curvature), limited_accel or limited_max_curv
 
 
 def get_speed_error(modelV2: log.ModelDataV2, v_ego: float) -> float:

selfdrive/controls/lib/latcontrol.py

@@ -17,14 +17,15 @@ class LatControl(ABC):
     self.steer_max = 1.0
 
   @abstractmethod
-  def update(self, active, CS, VM, params, steer_limited, desired_curvature, calibrated_pose):
+  def update(self, active, CS, VM, params, steer_limited_by_controls, desired_curvature, calibrated_pose, curvature_limited):
     pass
 
   def reset(self):
     self.sat_count = 0.
 
-  def _check_saturation(self, saturated, CS, steer_limited):
+  def _check_saturation(self, saturated, CS, steer_limited_by_controls, curvature_limited):
-    if saturated and CS.vEgo > self.sat_check_min_speed and not steer_limited and not CS.steeringPressed:
+    # Saturated only if control output is not being limited by car torque/angle rate limits
+    if (saturated or curvature_limited) and CS.vEgo > self.sat_check_min_speed and not steer_limited_by_controls and not CS.steeringPressed:
       self.sat_count += self.sat_count_rate
     else:
       self.sat_count -= self.sat_count_rate

selfdrive/controls/lib/latcontrol_angle.py

@@ -11,7 +11,7 @@ class LatControlAngle(LatControl):
     super().__init__(CP, CI)
     self.sat_check_min_speed = 5.
 
-  def update(self, active, CS, VM, params, steer_limited, desired_curvature, calibrated_pose):
+  def update(self, active, CS, VM, params, steer_limited_by_controls, desired_curvature, calibrated_pose, curvature_limited):
     angle_log = log.ControlsState.LateralAngleState.new_message()
 
     if not active:
@@ -23,7 +23,7 @@ class LatControlAngle(LatControl):
       angle_steers_des += params.angleOffsetDeg
 
     angle_control_saturated = abs(angle_steers_des - CS.steeringAngleDeg) > STEER_ANGLE_SATURATION_THRESHOLD
-    angle_log.saturated = bool(self._check_saturation(angle_control_saturated, CS, False))
+    angle_log.saturated = bool(self._check_saturation(angle_control_saturated, CS, False, curvature_limited))
     angle_log.steeringAngleDeg = float(CS.steeringAngleDeg)
     angle_log.steeringAngleDesiredDeg = angle_steers_des
     return 0, float(angle_steers_des), angle_log

selfdrive/controls/lib/latcontrol_pid.py

@@ -17,7 +17,7 @@ class LatControlPID(LatControl):
     super().reset()
     self.pid.reset()
 
-  def update(self, active, CS, VM, params, steer_limited, desired_curvature, calibrated_pose):
+  def update(self, active, CS, VM, params, steer_limited_by_controls, desired_curvature, calibrated_pose, curvature_limited):
     pid_log = log.ControlsState.LateralPIDState.new_message()
     pid_log.steeringAngleDeg = float(CS.steeringAngleDeg)
     pid_log.steeringRateDeg = float(CS.steeringRateDeg)
@@ -43,6 +43,6 @@ class LatControlPID(LatControl):
       pid_log.i = float(self.pid.i)
       pid_log.f = float(self.pid.f)
       pid_log.output = float(output_steer)
-      pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_steer) < 1e-3, CS, steer_limited))
+      pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_steer) < 1e-3, CS, steer_limited_by_controls, curvature_limited))
 
     return output_steer, angle_steers_des, pid_log

selfdrive/controls/lib/latcontrol_torque.py

@@ -37,7 +37,7 @@ class LatControlTorque(LatControl):
     self.torque_params.latAccelOffset = latAccelOffset
     self.torque_params.friction = friction
 
-  def update(self, active, CS, VM, params, steer_limited, desired_curvature, calibrated_pose):
+  def update(self, active, CS, VM, params, steer_limited_by_controls, desired_curvature, calibrated_pose, curvature_limited):
     pid_log = log.ControlsState.LateralTorqueState.new_message()
     if not active:
       output_torque = 0.0
@@ -73,7 +73,7 @@ class LatControlTorque(LatControl):
                                           desired_lateral_accel - actual_lateral_accel, lateral_accel_deadzone, friction_compensation=True,
                                           gravity_adjusted=True)
 
-      freeze_integrator = steer_limited or CS.steeringPressed or CS.vEgo < 5
+      freeze_integrator = steer_limited_by_controls or CS.steeringPressed or CS.vEgo < 5
       output_torque = self.pid.update(pid_log.error,
                                       feedforward=ff,
                                       speed=CS.vEgo,
@@ -87,7 +87,7 @@ class LatControlTorque(LatControl):
       pid_log.output = float(-output_torque)
       pid_log.actualLateralAccel = float(actual_lateral_accel)
       pid_log.desiredLateralAccel = float(desired_lateral_accel)
-      pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited))
+      pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_controls, curvature_limited))
 
     # TODO left is positive in this convention
     return -output_torque, 0.0, pid_log

selfdrive/controls/lib/tests/test_latcontrol.py

@@ -33,7 +33,15 @@ class TestLatControl:
     lp = generate_livePose()
     pose = Pose.from_live_pose(lp.livePose)
 
+    # Saturate for curvature limited and controller limited
     for _ in range(1000):
-      _, _, lac_log = controller.update(True, CS, VM, params, False, 1, pose)
+      _, _, lac_log = controller.update(True, CS, VM, params, False, 0, pose, True)
+    assert lac_log.saturated
+
+    for _ in range(1000):
+      _, _, lac_log = controller.update(True, CS, VM, params, False, 0, pose, False)
+    assert not lac_log.saturated
 
+    for _ in range(1000):
+      _, _, lac_log = controller.update(True, CS, VM, params, False, 1, pose, False)
     assert lac_log.saturated

selfdrive/selfdrived/selfdrived.py

@@ -328,11 +328,11 @@ class SelfdriveD:
     if lac.active and not recent_steer_pressed and not self.CP.notCar:
       clipped_speed = max(CS.vEgo, MIN_LATERAL_CONTROL_SPEED)
       actual_lateral_accel = controlstate.curvature * (clipped_speed**2)
-      desired_lateral_accel = controlstate.desiredCurvature * (clipped_speed**2)
+      desired_lateral_accel = self.sm['modelV2'].action.desiredCurvature * (clipped_speed**2)
       undershooting = abs(desired_lateral_accel) / abs(1e-3 + actual_lateral_accel) > 1.2
       turning = abs(desired_lateral_accel) > 1.0
-      good_speed = CS.vEgo > 5
+      # TODO: lac.saturated includes speed and other checks, should be pulled out
-      if undershooting and turning and good_speed and lac.saturated:
+      if undershooting and turning and lac.saturated:
         self.events.add(EventName.steerSaturated)
 
     # Check for FCW

selfdrive/test/process_replay/migration.py

@@ -358,6 +358,7 @@ def migrate_cameraStates(msgs):
 
     new_msg = messaging.new_message(msg.which())
     new_camera_state = getattr(new_msg, new_msg.which())
+    new_camera_state.sensor = camera_state.sensor
     new_camera_state.frameId = encode_id
     new_camera_state.encodeId = encode_id
     # timestampSof was added later so it might be missing on some old segments

selfdrive/test/process_replay/model_replay.py

@@ -19,8 +19,8 @@ from openpilot.tools.lib.framereader import FrameReader, NumpyFrameReader
 from openpilot.tools.lib.logreader import LogReader, save_log
 from openpilot.tools.lib.github_utils import GithubUtils
 
-TEST_ROUTE = "2f4452b03ccb98f0|2022-12-03--13-45-30"
+TEST_ROUTE = "8494c69d3c710e81|000001d4--2648a9a404"
-SEGMENT = 6
+SEGMENT = 4
 MAX_FRAMES = 100 if PC else 400
 
 NO_MODEL = "NO_MODEL" in os.environ
@@ -66,6 +66,8 @@ def generate_report(proposed, master, tmp, commit):
                      (lambda x: get_idx_if_non_empty(x.action.desiredCurvature), "desiredCurvature"),
                      (lambda x: get_idx_if_non_empty(x.leadsV3[0].x, 0), "leadsV3.x"),
                      (lambda x: get_idx_if_non_empty(x.laneLines[1].y, 0), "laneLines.y"),
+                     (lambda x: get_idx_if_non_empty(x.meta.desireState, 3), "desireState.laneChangeLeft"),
+                     (lambda x: get_idx_if_non_empty(x.meta.desireState, 4), "desireState.laneChangeRight"),
                      (lambda x: get_idx_if_non_empty(x.meta.disengagePredictions.gasPressProbs, 1), "gasPressProbs")
                     ], "modelV2")
   DriverStateV2_Plots = zl([
@@ -143,7 +145,8 @@ def trim_logs_to_max_frames(logs, max_frames, frs_types, include_all_types):
 
 def model_replay(lr, frs):
   # modeld is using frame pairs
-  modeld_logs = trim_logs_to_max_frames(lr, MAX_FRAMES, {"roadCameraState", "wideRoadCameraState"}, {"roadEncodeIdx", "wideRoadEncodeIdx", "carParams"})
+  modeld_logs = trim_logs_to_max_frames(lr, MAX_FRAMES, {"roadCameraState", "wideRoadCameraState"},
+                                                                         {"roadEncodeIdx", "wideRoadEncodeIdx", "carParams", "carState", "carControl"})
   dmodeld_logs = trim_logs_to_max_frames(lr, MAX_FRAMES, {"driverCameraState"}, {"driverEncodeIdx", "carParams"})
 
   if not SEND_EXTRA_INPUTS:

selfdrive/test/process_replay/process_replay.py

@@ -580,7 +580,7 @@ CONFIGS = [
   ),
   ProcessConfig(
     proc_name="modeld",
-    pubs=["deviceState", "roadCameraState", "wideRoadCameraState", "liveCalibration", "driverMonitoringState", "carState"],
+    pubs=["deviceState", "roadCameraState", "wideRoadCameraState", "liveCalibration", "driverMonitoringState", "carState", "carControl"],
     subs=["modelV2", "drivingModelData", "cameraOdometry"],
     ignore=["logMonoTime", "modelV2.frameDropPerc", "modelV2.modelExecutionTime", "drivingModelData.frameDropPerc", "drivingModelData.modelExecutionTime"],
     should_recv_callback=ModeldCameraSyncRcvCallback(),

selfdrive/test/process_replay/ref_commit

@@ -1 +1 @@
-d343af55506b14a4011bfe43b2a49c7e3c387d75
+a9487c6a5c2f0bb83c9d629ff64c8f64a4e4ca13

selfdrive/test/process_replay/regen.py

@@ -12,10 +12,9 @@ from openpilot.selfdrive.test.process_replay.process_replay import CONFIGS, FAKE
                                                                    check_openpilot_enabled, check_most_messages_valid, get_custom_params_from_lr
 from openpilot.selfdrive.test.process_replay.vision_meta import DRIVER_CAMERA_FRAME_SIZES
 from openpilot.selfdrive.test.update_ci_routes import upload_route
-from openpilot.tools.lib.route import Route
 from openpilot.tools.lib.framereader import FrameReader, BaseFrameReader, FrameType
 from openpilot.tools.lib.logreader import LogReader, LogIterable, save_log
-
+from openpilot.tools.lib.openpilotci import get_url
 
 class DummyFrameReader(BaseFrameReader):
   def __init__(self, w: int, h: int, frame_count: int, pix_val: int):
@@ -55,45 +54,28 @@ def regen_segment(
 
 
 def setup_data_readers(
-    route: str, sidx: int, use_route_meta: bool,
+    route: str, sidx: int, needs_driver_cam: bool = True, needs_road_cam: bool = True, dummy_driver_cam: bool = False
-    needs_driver_cam: bool = True, needs_road_cam: bool = True, dummy_driver_cam: bool = False
 ) -> tuple[LogReader, dict[str, Any]]:
-  if use_route_meta:
-    r = Route(route)
-    lr = LogReader(r.log_paths()[sidx])
-    frs = {}
-    if needs_road_cam and len(r.camera_paths()) > sidx and r.camera_paths()[sidx] is not None:
-      frs['roadCameraState'] = FrameReader(r.camera_paths()[sidx])
-    if needs_road_cam and  len(r.ecamera_paths()) > sidx and r.ecamera_paths()[sidx] is not None:
-      frs['wideRoadCameraState'] = FrameReader(r.ecamera_paths()[sidx])
-    if needs_driver_cam:
-      if dummy_driver_cam:
-        frs['driverCameraState'] = DummyFrameReader.zero_dcamera()
-      elif len(r.dcamera_paths()) > sidx and r.dcamera_paths()[sidx] is not None:
-        device_type = next(str(msg.initData.deviceType) for msg in lr if msg.which() == "initData")
-        assert device_type != "neo", "Driver camera not supported on neo segments. Use dummy dcamera."
-        frs['driverCameraState'] = FrameReader(r.dcamera_paths()[sidx])
-  else:
   lr = LogReader(f"{route}/{sidx}/r")
   frs = {}
   if needs_road_cam:
-      frs['roadCameraState'] = FrameReader(f"cd:/{route.replace('|', '/')}/{sidx}/fcamera.hevc")
+    frs['roadCameraState'] = FrameReader(get_url(route, str(sidx), "fcamera.hevc"))
     if next((True for m in lr if m.which() == "wideRoadCameraState"), False):
-        frs['wideRoadCameraState'] = FrameReader(f"cd:/{route.replace('|', '/')}/{sidx}/ecamera.hevc")
+      frs['wideRoadCameraState'] = FrameReader(get_url(route, str(sidx), "ecamera.hevc"))
   if needs_driver_cam:
     if dummy_driver_cam:
       frs['driverCameraState'] = DummyFrameReader.zero_dcamera()
     else:
       device_type = next(str(msg.initData.deviceType) for msg in lr if msg.which() == "initData")
       assert device_type != "neo", "Driver camera not supported on neo segments. Use dummy dcamera."
-        frs['driverCameraState'] = FrameReader(f"cd:/{route.replace('|', '/')}/{sidx}/dcamera.hevc")
+      frs['driverCameraState'] = FrameReader(get_url(route, str(sidx), "dcamera.hevc"))
 
   return lr, frs
 
 
 def regen_and_save(
   route: str, sidx: int, processes: str | Iterable[str] = "all", outdir: str = FAKEDATA,
-  upload: bool = False, use_route_meta: bool = False, disable_tqdm: bool = False, dummy_driver_cam: bool = False
+  upload: bool = False, disable_tqdm: bool = False, dummy_driver_cam: bool = False
 ) -> str:
   if not isinstance(processes, str) and not hasattr(processes, "__iter__"):
     raise ValueError("whitelist_proc must be a string or iterable")
@@ -110,7 +92,7 @@ def regen_and_save(
     replayed_processes = CONFIGS
 
   all_vision_pubs = {pub for cfg in replayed_processes for pub in cfg.vision_pubs}
-  lr, frs = setup_data_readers(route, sidx, use_route_meta,
+  lr, frs = setup_data_readers(route, sidx,
                                needs_driver_cam="driverCameraState" in all_vision_pubs,
                                needs_road_cam="roadCameraState" in all_vision_pubs or "wideRoadCameraState" in all_vision_pubs,
                                dummy_driver_cam=dummy_driver_cam)

selfdrive/test/process_replay/regen_all.py

@@ -17,7 +17,7 @@ def regen_job(segment, upload, disable_tqdm):
     sn = SegmentName(segment[1])
     fake_dongle_id = 'regen' + ''.join(random.choice('0123456789ABCDEF') for _ in range(11))
     try:
-      relr = regen_and_save(sn.route_name.canonical_name, sn.segment_num, upload=upload, use_route_meta=False,
+      relr = regen_and_save(sn.route_name.canonical_name, sn.segment_num, upload=upload,
                             outdir=os.path.join(FAKEDATA, fake_dongle_id), disable_tqdm=disable_tqdm, dummy_driver_cam=True)
       relr = '|'.join(relr.split('/')[-2:])
       return f'  ("{segment[0]}", "{relr}"), '

selfdrive/test/process_replay/test_processes.py

@@ -42,22 +42,22 @@ source_segments = [
 
 segments = [
   ("BODY", "regenA67A128BCD8|2024-08-30--02-36-22--0"),
-  ("HYUNDAI", "regen9CBD921E93E|2024-08-30--02-38-51--0"),
+  ("HYUNDAI", "regenCCD47FEBC0C|2025-03-04--03-21-48--0"),
   ("HYUNDAI2", "regen306779F6870|2024-10-03--04-03-23--0"),
-  ("TOYOTA", "regen1CA7A48E6F7|2024-08-30--02-45-08--0"),
+  ("TOYOTA", "regen4A5115B248D|2025-03-04--03-21-43--0"),
   ("TOYOTA2", "regen6E484EDAB96|2024-08-30--02-47-37--0"),
   ("TOYOTA3", "regen4CE950B0267|2024-08-30--02-51-30--0"),
-  ("HONDA", "regenC8F0D6ADC5C|2024-08-30--02-54-01--0"),
+  ("HONDA", "regenB8CABEC09CC|2025-03-04--03-32-55--0"),
   ("HONDA2", "regen4B38A7428CD|2024-08-30--02-56-31--0"),
   ("CHRYSLER", "regenF3DBBA9E8DF|2024-08-30--02-59-03--0"),
   ("RAM", "regenDB02684E00A|2024-08-30--03-02-54--0"),
-  ("SUBARU", "regenAA1FF48CF1F|2024-08-30--03-06-45--0"),
+  ("SUBARU", "regen5E3347D0A0F|2025-03-04--03-23-55--0"),
   ("GM", "regen720F2BA4CF6|2024-08-30--03-09-15--0"),
   ("GM2", "regen9ADBECBCD1C|2024-08-30--03-13-04--0"),
   ("NISSAN", "regen58464878D07|2024-08-30--03-15-31--0"),
   ("VOLKSWAGEN", "regenED976DEB757|2024-08-30--03-18-02--0"),
   ("MAZDA", "regenACF84CCF482|2024-08-30--03-21-55--0"),
-  ("FORD", "regen756F8230C21|2024-11-07--00-08-24--0"),
+  ("FORD", "regenA75209BD115|2025-03-04--03-23-53--0"),
   ("RIVIAN", "bc095dc92e101734|000000db--ee9fe46e57--1"),
 ]
 

selfdrive/test/test_onroad.py

@@ -1,8 +1,6 @@
 import math
 import json
 import os
-import pathlib
-import psutil
 import pytest
 import shutil
 import subprocess
@@ -12,7 +10,7 @@ from collections import Counter, defaultdict
 from pathlib import Path
 from tabulate import tabulate
 
-from cereal import car, log
+from cereal import log
 import cereal.messaging as messaging
 from cereal.services import SERVICE_LIST
 from openpilot.common.basedir import BASEDIR
@@ -23,6 +21,7 @@ from openpilot.selfdrive.test.helpers import set_params_enabled, release_only
 from openpilot.system.hardware import HARDWARE
 from openpilot.system.hardware.hw import Paths
 from openpilot.tools.lib.logreader import LogReader
+from openpilot.tools.lib.log_time_series import msgs_to_time_series
 
 """
 CPU usage budget
@@ -112,6 +111,7 @@ def cputime_total(ct):
 
 
 @pytest.mark.tici
+@pytest.mark.skip_tici_setup
 class TestOnroad:
 
   @classmethod
@@ -119,7 +119,8 @@ class TestOnroad:
     if "DEBUG" in os.environ:
       segs = filter(lambda x: os.path.exists(os.path.join(x, "rlog.zst")), Path(Paths.log_root()).iterdir())
       segs = sorted(segs, key=lambda x: x.stat().st_mtime)
-      cls.lr = list(LogReader(os.path.join(segs[-3], "rlog.zst")))
+      cls.lr = list(LogReader(os.path.join(segs[-1], "rlog.zst")))
+      cls.ts = msgs_to_time_series(cls.lr)
       return
 
     # setup env
@@ -140,44 +141,31 @@ class TestOnroad:
       proc = subprocess.Popen(["python", manager_path])
 
       sm = messaging.SubMaster(['carState'])
-      with Timeout(150, "controls didn't start"):
+      with Timeout(30, "controls didn't start"):
-        while sm.recv_frame['carState'] < 0:
+        while not sm.seen['carState']:
           sm.update(1000)
 
-      route = None
-      cls.segments = []
-      with Timeout(300, "timed out waiting for logs"):
-        while route is None:
       route = params.get("CurrentRoute", encoding="utf-8")
-          time.sleep(0.01)
+      assert route is not None
 
-        # test car params caching
+      segs = list(Path(Paths.log_root()).glob(f"{route}--*"))
-        params.put("CarParamsCache", car.CarParams().to_bytes())
+      assert len(segs) == 1
-
-        while len(cls.segments) < 1:
-          segs = set()
-          if Path(Paths.log_root()).exists():
-            segs = set(Path(Paths.log_root()).glob(f"{route}--*"))
-          cls.segments = sorted(segs, key=lambda s: int(str(s).rsplit('--')[-1]))
-          time.sleep(0.01)
 
       time.sleep(TEST_DURATION)
-
     finally:
-      cls.gpu_procs = {psutil.Process(int(f.name)).name() for f in pathlib.Path('/sys/devices/virtual/kgsl/kgsl/proc/').iterdir() if f.is_dir()}
-
       if proc is not None:
         proc.terminate()
         if proc.wait(60) is None:
           proc.kill()
 
-    cls.lrs = [list(LogReader(os.path.join(str(s), "rlog.zst"))) for s in cls.segments]
+    cls.lr = list(LogReader(os.path.join(str(segs[0]), "rlog.zst")))
-
+    st = time.monotonic()
-    cls.lr = list(LogReader(os.path.join(str(cls.segments[0]), "rlog.zst")))
+    cls.ts = msgs_to_time_series(cls.lr)
-    cls.log_path = cls.segments[0]
+    print("msgs to time series", time.monotonic() - st)
+    log_path = segs[0]
 
     cls.log_sizes = {}
-    for f in cls.log_path.iterdir():
+    for f in log_path.iterdir():
       assert f.is_file()
       cls.log_sizes[f] = f.stat().st_size / 1e6
 
@@ -198,7 +186,7 @@ class TestOnroad:
         assert len(msgs) >= math.floor(SERVICE_LIST[s].frequency*int(TEST_DURATION*0.8))
 
   def test_manager_starting_time(self):
-    st = self.msgs['managerState'][0].logMonoTime / 1e9
+    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"
 
   def test_cloudlog_size(self):
@@ -226,7 +214,7 @@ class TestOnroad:
     result += "-------------- UI Draw Timing ------------------\n"
     result += "------------------------------------------------\n"
 
-    ts = [m.uiDebug.drawTimeMillis for m in self.msgs['uiDebug']]
+    ts = self.ts['uiDebug']['drawTimeMillis']
     result += f"min  {min(ts):.2f}ms\n"
     result += f"max  {max(ts):.2f}ms\n"
     result += f"std  {np.std(ts):.2f}ms\n"
@@ -309,9 +297,6 @@ class TestOnroad:
     assert np.max(np.diff(mems)) <= 4, "Max memory increase too high"
     assert np.average(np.diff(mems)) <= 1, "Average memory increase too high"
 
-  def test_gpu_usage(self):
-    assert self.gpu_procs == {"weston", "ui", "camerad", "selfdrive.modeld.modeld", "selfdrive.modeld.dmonitoringmodeld"}
-
   def test_camera_frame_timings(self, subtests):
     # test timing within a single camera
     result = "\n"
@@ -319,7 +304,7 @@ class TestOnroad:
     result += "-----------------  SOF Timing ------------------\n"
     result += "------------------------------------------------\n"
     for name in ['roadCameraState', 'wideRoadCameraState', 'driverCameraState']:
-      ts = [getattr(m, m.which()).timestampSof for m in self.lr if name in m.which()]
+      ts = self.ts[name]['timestampSof']
       d_ms = np.diff(ts) / 1e6
       d50 = np.abs(d_ms-50)
       result += f"{name} sof delta vs 50ms: min  {min(d50):.2f}ms\n"
@@ -338,35 +323,51 @@ class TestOnroad:
         # sanity checks within a single cam
         for cam in cams:
           with subtests.test(test="frame_skips", camera=cam):
-            cam_log = [getattr(x, x.which()) for x in self.msgs[cam]]
+            assert set(np.diff(self.ts[cam]['frameId'])) == {1, }, "Frame ID skips"
-            assert set(np.diff([x.frameId for x in cam_log])) == {1, }, "Frame ID skips"
 
             # EOF > SOF
-            eof_sof_diff = np.array([x.timestampEof - x.timestampSof for x in cam_log])
+            eof_sof_diff = self.ts[cam]['timestampEof'] - self.ts[cam]['timestampSof']
             assert np.all(eof_sof_diff > 0)
             assert np.all(eof_sof_diff < 50*1e6)
 
-        fid = {c: [getattr(m, m.which()).frameId for m in self.msgs[c]] for c in cams}
+        first_fid = {c: min(self.ts[c]['frameId']) for c in cams}
-        first_fid = [min(x) for x in fid.values()]
         if cam.endswith('CameraState'):
           # camerad guarantees that all cams start on frame ID 0
           # (note loggerd also needs to start up fast enough to catch it)
-          assert set(first_fid) == {0, }, "Cameras don't start on frame ID 0"
+          assert set(first_fid.values()) == {0, }, "Cameras don't start on frame ID 0"
         else:
           # encoder guarantees all cams start on the same frame ID
-          assert len(set(first_fid)) == 1, "Cameras don't start on same frame ID"
+          assert len(set(first_fid.values())) == 1, "Cameras don't start on same frame ID"
 
         # we don't do a full segment rotation, so these might not match exactly
-        last_fid = [max(x) for x in fid.values()]
+        last_fid = {c: max(self.ts[c]['frameId']) for c in cams}
-        assert max(last_fid) - min(last_fid) < 10
+        assert max(last_fid.values()) - min(last_fid.values()) < 10
 
-        start, end = min(first_fid), min(last_fid)
+        start, end = min(first_fid.values()), min(last_fid.values())
-        all_ts = [[getattr(m, m.which()).timestampSof for m in self.msgs[c]] for c in cams]
         for i in range(end-start):
-          ts = [round(x[i]/1e6, 1) for x in all_ts]
+          ts = {c: round(self.ts[c]['timestampSof'][i]/1e6, 1) for c in cams}
-          diff = max(ts) - min(ts)
+          diff = (max(ts.values()) - min(ts.values()))
           assert diff < 2, f"Cameras not synced properly: frame_id={start+i}, {diff=:.1f}ms, {ts=}"
 
+  def test_camera_encoder_matches(self, subtests):
+    # sanity check that the frame metadata is consistent with the encoded frames
+    pairs = [('roadCameraState', 'roadEncodeIdx'),
+             ('wideRoadCameraState', 'wideRoadEncodeIdx'),
+             ('driverCameraState', 'driverEncodeIdx')]
+    for cam, enc in pairs:
+      with subtests.test(camera=cam, encoder=enc):
+        cam_frames = {fid: (sof, eof) for fid, sof, eof in zip(
+          self.ts[cam]['frameId'],
+          self.ts[cam]['timestampSof'],
+          self.ts[cam]['timestampEof'],
+          strict=True,
+        )}
+        for i, fid in enumerate(self.ts[enc]['frameId']):
+          cam_sof, cam_eof = cam_frames[fid]
+          enc_sof, enc_eof = self.ts[enc]['timestampSof'][i], self.ts[enc]['timestampEof'][i]
+          assert enc_sof == cam_sof, f"SOF mismatch: frameId={fid}, enc_sof={enc_sof}, cam_sof={cam_sof}"
+          assert enc_eof == cam_eof, f"EOF mismatch: frameId={fid}, enc_eof={enc_eof}, cam_eof={cam_eof}"
+
   def test_mpc_execution_timings(self):
     result = "\n"
     result += "------------------------------------------------\n"
@@ -438,12 +439,7 @@ class TestOnroad:
 
   @release_only
   def test_startup(self):
-    startup_alert = None
+    startup_alert = self.ts['selfdriveState']['alertText1'][0]
-    for msg in self.lrs[0]:
-      # can't use onroadEvents because the first msg can be dropped while loggerd is starting up
-      if msg.which() == "selfdriveState":
-        startup_alert = msg.selfdriveState.alertText1
-        break
     expected = EVENTS[log.OnroadEvent.EventName.startup][ET.PERMANENT].alert_text_1
     assert startup_alert == expected, "wrong startup alert"
 

selfdrive/ui/qt/offroad/firehose.cc

@@ -10,6 +10,9 @@
 #include <QScrollArea>
 #include <QStackedLayout>
 #include <QProgressBar>
+#include <QJsonDocument>
+#include <QJsonObject>
+#include <QTimer>
 
 FirehosePanel::FirehosePanel(SettingsWindow *parent) : QWidget((QWidget*)parent) {
   layout = new QVBoxLayout(this);
@@ -28,7 +31,7 @@ FirehosePanel::FirehosePanel(SettingsWindow *parent) : QWidget((QWidget*)parent)
   content_layout->setSpacing(20);
 
   // Top description
-  QLabel *description = new QLabel(tr("openpilot learns to drive by watching humans, like you, drive.\n\nFirehose Mode allows you to maximize your training data uploads to improve openpilot's driving models. More data means bigger models with better Experimental Mode."));
+  QLabel *description = new QLabel(tr("openpilot learns to drive by watching humans, like you, drive.\n\nFirehose Mode allows you to maximize your training data uploads to improve openpilot's driving models. More data means bigger models, which means better Experimental Mode."));
   description->setStyleSheet("font-size: 45px; padding-bottom: 20px;");
   description->setWordWrap(true);
   content_layout->addWidget(description);
@@ -40,41 +43,16 @@ FirehosePanel::FirehosePanel(SettingsWindow *parent) : QWidget((QWidget*)parent)
   line->setStyleSheet("background-color: #444444; margin-top: 5px; margin-bottom: 5px;");
   content_layout->addWidget(line);
 
-  enable_firehose = new ParamControl("FirehoseMode", tr("Enable Firehose Mode"), "", "");
+  toggle_label = new QLabel(tr("Firehose Mode: ACTIVE"));
+  toggle_label->setStyleSheet("font-size: 60px; font-weight: bold; color: white;");
+  content_layout->addWidget(toggle_label);
 
-  content_layout->addWidget(enable_firehose);
+  // Add contribution label
-
+  contribution_label = new QLabel();
-  // Create progress bar container
+  contribution_label->setStyleSheet("font-size: 52px; margin-top: 10px; margin-bottom: 10px;");
-  progress_container = new QFrame();
+  contribution_label->setWordWrap(true);
-  progress_container->hide();
+  contribution_label->hide();
-  QHBoxLayout *progress_layout = new QHBoxLayout(progress_container);
+  content_layout->addWidget(contribution_label);
-  progress_layout->setContentsMargins(10, 0, 10, 10);
-  progress_layout->setSpacing(20);
-
-  progress_bar = new QProgressBar();
-  progress_bar->setRange(0, 100);
-  progress_bar->setValue(0);
-  progress_bar->setTextVisible(false);
-  progress_bar->setStyleSheet(R"(
-    QProgressBar {
-      background-color: #444444;
-      border-radius: 10px;
-      height: 20px;
-    }
-    QProgressBar::chunk {
-      background-color: #3498db;
-      border-radius: 10px;
-    }
-  )");
-  progress_bar->setFixedHeight(40);
-
-  // Progress text
-  progress_text = new QLabel(tr("0%"));
-  progress_text->setStyleSheet("font-size: 40px; font-weight: bold; color: white;");
-
-  progress_layout->addWidget(progress_text);
-
-  content_layout->addWidget(progress_container);
 
   // Add a separator before detailed instructions
   QFrame *line2 = new QFrame();
@@ -85,22 +63,49 @@ FirehosePanel::FirehosePanel(SettingsWindow *parent) : QWidget((QWidget*)parent)
 
   // Detailed instructions at the bottom
   detailed_instructions = new QLabel(tr(
-    "Follow these steps to get your device ready:<br>"
+    "For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br>"
-    "\t1. Bring your device inside and connect to a good USB-C adapter<br>"
-    "\t2. Connect to Wi-Fi<br>"
-    "\t3. Enable the toggle<br>"
-    "\t4. Leave it connected for at least 30 minutes<br>"
     "<br>"
-    "The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness."
+    "Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br>"
-    "<br><br><b>FAQ</b><br>"
+    "<br><br>"
-    "<i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br>"
+    "<b>Frequently Asked Questions</b><br><br>"
-    "<i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br>"
+    "<i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br>"
-    "<i>Do I need to be on Wi-Fi?</i> Yes.<br>"
+    "<i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br>"
-    "<i>Do I need to bring the device inside?</i> No, you can enable once you're parked, however your uploads will be limited by your car's battery.<br>"
+    "<i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training."
   ));
-  detailed_instructions->setStyleSheet("font-size: 40px; padding: 20px; color: #E4E4E4;");
+  detailed_instructions->setStyleSheet("font-size: 40px; color: #E4E4E4;");
   detailed_instructions->setWordWrap(true);
   content_layout->addWidget(detailed_instructions);
 
   layout->addWidget(content, 1);
+
+  // Set up the API request for firehose stats
+  const QString dongle_id = QString::fromStdString(Params().get("DongleId"));
+  firehose_stats = new RequestRepeater(this, CommaApi::BASE_URL + "/v1/devices/" + dongle_id + "/firehose_stats",
+                                       "ApiCache_FirehoseStats", 30, true);
+  QObject::connect(firehose_stats, &RequestRepeater::requestDone, [=](const QString &response, bool success) {
+    if (success) {
+      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->show();
+    }
+  });
+
+  QObject::connect(uiState(), &UIState::uiUpdate, this, &FirehosePanel::refresh);
+}
+
+void FirehosePanel::refresh() {
+  auto deviceState = (*uiState()->sm)["deviceState"].getDeviceState();
+  auto networkType = deviceState.getNetworkType();
+  bool networkMetered = deviceState.getNetworkMetered();
+
+  bool is_active = !networkMetered && (networkType != cereal::DeviceState::NetworkType::NONE);
+  if (is_active) {
+    toggle_label->setText(tr("ACTIVE"));
+    toggle_label->setStyleSheet("font-size: 60px; font-weight: bold; color: #2ecc71;");
+  } else {
+    toggle_label->setText(tr("<span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network"));
+    toggle_label->setStyleSheet("font-size: 60px;");
+  }
 }

selfdrive/ui/qt/offroad/firehose.h

@@ -2,10 +2,8 @@
 
 #include <QWidget>
 #include <QVBoxLayout>
-#include <QProgressBar>
 #include <QLabel>
-#include "selfdrive/ui/qt/widgets/controls.h"
+#include "selfdrive/ui/qt/request_repeater.h"
-#include "common/params.h"
 
 // Forward declarations
 class SettingsWindow;
@@ -18,11 +16,12 @@ public:
 private:
   QVBoxLayout *layout;
 
-  ParamControl *enable_firehose;
-  QFrame *progress_container;
-  QProgressBar *progress_bar;
-  QLabel *progress_text;
   QLabel *detailed_instructions;
+  QLabel *contribution_label;
+  QLabel *toggle_label;
 
-  void updateFirehoseState(bool enabled);
+  RequestRepeater *firehose_stats;
+
+private slots:
+  void refresh();
 };

selfdrive/ui/translations/main_ar.ts

@@ -312,21 +312,29 @@
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Enable Firehose Mode</source>
+        <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>
     </message>
     <message>
-        <source>openpilot learns to drive by watching humans, like you, drive.
+        <source>Firehose Mode: ACTIVE</source>
-
-Firehose Mode allows you to maximize your training data uploads to improve openpilot&apos;s driving models. More data means bigger models with better Experimental Mode.</source>
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>0%</source>
+        <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">5G {0%?}</translation>
+        <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>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>
 </context>

selfdrive/ui/translations/main_de.ts

@@ -312,21 +312,29 @@
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Enable Firehose Mode</source>
+        <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>
     </message>
     <message>
-        <source>openpilot learns to drive by watching humans, like you, drive.
+        <source>Firehose Mode: ACTIVE</source>
-
-Firehose Mode allows you to maximize your training data uploads to improve openpilot&apos;s driving models. More data means bigger models with better Experimental Mode.</source>
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>0%</source>
+        <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">5G {0%?}</translation>
+        <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>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>
 </context>

selfdrive/ui/translations/main_es.ts

@@ -312,21 +312,29 @@
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Enable Firehose Mode</source>
+        <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>
     </message>
     <message>
-        <source>openpilot learns to drive by watching humans, like you, drive.
+        <source>Firehose Mode: ACTIVE</source>
-
-Firehose Mode allows you to maximize your training data uploads to improve openpilot&apos;s driving models. More data means bigger models with better Experimental Mode.</source>
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>0%</source>
+        <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">5G {0%?}</translation>
+        <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>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>
 </context>

selfdrive/ui/translations/main_fr.ts

@@ -312,21 +312,29 @@
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Enable Firehose Mode</source>
+        <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>
     </message>
     <message>
-        <source>openpilot learns to drive by watching humans, like you, drive.
+        <source>Firehose Mode: ACTIVE</source>
-
-Firehose Mode allows you to maximize your training data uploads to improve openpilot&apos;s driving models. More data means bigger models with better Experimental Mode.</source>
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>0%</source>
+        <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">5G {0%?}</translation>
+        <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>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>
 </context>

selfdrive/ui/translations/main_ja.ts

@@ -311,25 +311,31 @@
         <source>🔥 Firehose Mode 🔥</source>
         <translation>🔥 Firehoseモード 🔥</translation>
     </message>
-    <message>
-        <source>Enable Firehose Mode</source>
-        <translation>Firehoseを有効にする</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 with better Experimental Mode.</source>
+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>openpilotは人間であるあなたの運転から学び、AI学習します。
+        <translation type="unfinished"></translation>
-
+    </message>
-Firehoseモードを有効にすると、学習データを最大限アップロードし、openpilotの運転モデルを向上させることができます。より多くのデータはより大きなモデルを生み出し、Experimentalモードの精度向上につながります。</translation>
+    <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>
     </message>
     <message>
-        <source>0%</source>
+        <source>ACTIVE</source>
-        <translation type="unfinished">5G {0%?}</translation>
+        <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>以下の手順に従ってデバイスを準備してください:&lt;br&gt;	1. デバイスを室内に持ち込み、高速なUSB-C電源に接続してください&lt;br&gt;	2. Wi-Fiに接続してください&lt;br&gt;	3. 機能を有効にしてください&lt;br&gt;	4. 少なくとも30分間接続したままにしてください&lt;br&gt;&lt;br&gt;デバイスを再起動すると、この機能はオフになります。最大の効果を得るために、少なくとも週に1回は繰り返してください。&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&gt;&lt;br&gt;&lt;i&gt;どのように運転するか、どこで運転するかは重要ですか？&lt;/i&gt; いいえ、普段通りに運転してください。&lt;br&gt;&lt;i&gt;高速なUSB-C電源とは何ですか？&lt;/i&gt; スマフォやノートPC用のワット数の大きい充電器を使って下さい。&lt;br&gt;&lt;i&gt;Wi-Fiに接続する必要がありますか？&lt;/i&gt; その通りです。&lt;br&gt;&lt;i&gt;デバイスを屋内に持ち込む必要がありますか？&lt;/i&gt; いいえ、駐車後に有効にすることができますが、アップロードは車のバッテリーによって制限されます。&lt;br&gt;</translation>
+        <translation type="unfinished"></translation>
     </message>
 </context>
 <context>

selfdrive/ui/translations/main_ko.ts

@@ -311,25 +311,31 @@
         <source>🔥 Firehose Mode 🔥</source>
         <translation>🔥 파이어호스 모드 🔥</translation>
     </message>
-    <message>
-        <source>Enable Firehose Mode</source>
-        <translation>파이어호스 모드 활성화</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 with better Experimental Mode.</source>
+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>오픈파일럿은 여러분과 같은 사람이 운전하는 모습을 보면서 운전하는 법을 배웁니다.
+        <translation type="unfinished"></translation>
-
+    </message>
-파이어호스 모드를 사용하면 훈련 데이터 업로드를 최대화하여 오픈파일럿의 주행 모델을 개선할 수 있습니다. 더 많은 데이터는 더 나은 실험 모드를 갖춘 더 큰 모델을 의미합니다.</translation>
+    <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>
     </message>
     <message>
-        <source>0%</source>
+        <source>ACTIVE</source>
-        <translation>0%</translation>
+        <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>다음 단계에 따라 장치를 준비하세요.:&lt;br&gt;	1. 장치를 내부로 가져와 올바른 USB-C 어댑터에 연결하세요.&lt;br&gt; 2. Wi-Fi에 연결하세요.&lt;br&gt; 3. 토글을 활성화하세요.&lt;br&gt;	4. 최소 30분 동안 연결 상태로 두세요.&lt;br&gt;&lt;br&gt; 장치를 다시 시작하면 토글이 꺼집니다. 효과를 극대화하려면 적어도 일주일에 한 번씩 반복하세요.&lt;br&gt;&lt;br&gt;&lt;b&gt;자주 묻는 질문&lt;/b&gt;&lt;br&gt;&lt;i&gt;운전 방법이나 장소가 중요한가요?&lt;/i&gt; 아니요, 평소처럼 운전하세요.&lt;br&gt;&lt;i&gt;올바른 USB-C 어댑터란 무엇인가요?&lt;/i&gt; 휴대폰이나 노트북 고속 충전기라면 어떤 것이든 괜찮습니다.&lt;br&gt;&lt;i&gt;Wi-Fi에 연결되어 있어야 하나요?&lt;/i&gt; 예.&lt;br&gt;&lt;i&gt;장치를 차 안으로 가져와야 하나요?&lt;/i&gt; 아니요, 주차한 후에는 활성화할 수 있지만 차량의 배터리에 따라 업로드가 제한됩니다.&lt;br&gt;</translation>
+        <translation type="unfinished"></translation>
     </message>
 </context>
 <context>

selfdrive/ui/translations/main_pt-BR.ts

@@ -309,24 +309,32 @@
     <name>FirehosePanel</name>
     <message>
         <source>🔥 Firehose Mode 🔥</source>
+        <translation>🔥 Mode 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>
     </message>
     <message>
-        <source>Enable Firehose Mode</source>
+        <source>Firehose Mode: ACTIVE</source>
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>openpilot learns to drive by watching humans, like you, drive.
+        <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>
-Firehose Mode allows you to maximize your training data uploads to improve openpilot&apos;s driving models. More data means bigger models with better Experimental Mode.</source>
+    </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>0%</source>
+        <source>ACTIVE</source>
-        <translation type="unfinished">5G {0%?}</translation>
+        <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>
 </context>
@@ -668,7 +676,7 @@ Isso pode levar até um minuto.</translation>
     </message>
     <message>
         <source>Firehose</source>
-        <translation type="unfinished"></translation>
+        <translation>Firehose</translation>
     </message>
 </context>
 <context>
@@ -1146,15 +1154,15 @@ Isso pode levar até um minuto.</translation>
     <name>WiFiPromptWidget</name>
     <message>
         <source>Open</source>
-        <translation type="unfinished"></translation>
+        <translation>Abrir</translation>
     </message>
     <message>
         <source>Maximize your training data uploads to improve openpilot&apos;s driving models.</source>
-        <translation type="unfinished"></translation>
+        <translation>Maximize seus envios de dados de treinamento para melhorar os modelos de direção do 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; Mode 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

@@ -312,21 +312,29 @@
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Enable Firehose Mode</source>
+        <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>
     </message>
     <message>
-        <source>openpilot learns to drive by watching humans, like you, drive.
+        <source>Firehose Mode: ACTIVE</source>
-
-Firehose Mode allows you to maximize your training data uploads to improve openpilot&apos;s driving models. More data means bigger models with better Experimental Mode.</source>
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>0%</source>
+        <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">5G {0%?}</translation>
+        <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>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>
 </context>

selfdrive/ui/translations/main_tr.ts

@@ -312,21 +312,29 @@
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Enable Firehose Mode</source>
+        <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>
     </message>
     <message>
-        <source>openpilot learns to drive by watching humans, like you, drive.
+        <source>Firehose Mode: ACTIVE</source>
-
-Firehose Mode allows you to maximize your training data uploads to improve openpilot&apos;s driving models. More data means bigger models with better Experimental Mode.</source>
         <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>0%</source>
+        <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">5G {0%?}</translation>
+        <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>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>
 </context>

selfdrive/ui/translations/main_zh-CHS.ts

@@ -311,25 +311,31 @@
         <source>🔥 Firehose Mode 🔥</source>
         <translation>🔥 训练数据上传模式 🔥</translation>
     </message>
-    <message>
-        <source>Enable Firehose Mode</source>
-        <translation>启用训练数据上传模式</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 with better Experimental Mode.</source>
+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>openpilot 通过观察人类（像你一样的驾驶）来学习驾驶。
+        <translation type="unfinished"></translation>
-
+    </message>
-训练数据上传模式可让你最大化上传训练数据，以改进 openpilot 的驾驶模型。更多数据意味着更大的模型，并带来更优秀的实验模式。</translation>
+    <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>
     </message>
     <message>
-        <source>0%</source>
+        <source>ACTIVE</source>
-        <translation>0%</translation>
+        <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>按照以下步骤准备您的设备：&lt;br&gt;	1. 将设备带到室内并连接到良好的 USB-C 充电器&lt;br&gt;	2. 连接 Wi-Fi&lt;br&gt;	3. 启用开关&lt;br&gt;	4. 保持连接至少 30 分钟&lt;br&gt;&lt;br&gt;开关会在设备重新启动后自动关闭。请至少每周重复一次，以获得最佳效果。&lt;br&gt;&lt;br&gt;&lt;b&gt;常见问题&lt;/b&gt;&lt;br&gt;&lt;i&gt;驾驶方式或地点重要吗？&lt;/i&gt; 不，按照平常的方式驾驶即可。&lt;br&gt;&lt;i&gt;什么是良好的 USB-C 充电器？&lt;/i&gt; 任何快速手机或笔记本电脑充电器都可以。&lt;br&gt;&lt;i&gt;我需要连接 Wi-Fi 吗？&lt;/i&gt; 是的。&lt;br&gt;&lt;i&gt;我需要把设备带到室内吗？&lt;/i&gt; 不，您可以在停车后启用，但您的上传速度将受限于车辆的电池。&lt;br&gt;</translation>
+        <translation type="unfinished"></translation>
     </message>
 </context>
 <context>

selfdrive/ui/translations/main_zh-CHT.ts

@@ -311,25 +311,31 @@
         <source>🔥 Firehose Mode 🔥</source>
         <translation>🔥 訓練資料上傳模式 🔥</translation>
     </message>
-    <message>
-        <source>Enable Firehose Mode</source>
-        <translation>啟用訓練資料上傳模式</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 with better Experimental Mode.</source>
+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>openpilot 透過觀察人類（像你一樣的駕駛）來學習駕駛。
+        <translation type="unfinished"></translation>
-
+    </message>
-訓練資料上傳模式可讓你最大化上傳訓練數據，以改進 openpilot 的駕駛模型。更多數據意味著更大的模型，並帶來更優秀的實驗模式。</translation>
+    <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>
     </message>
     <message>
-        <source>0%</source>
+        <source>ACTIVE</source>
-        <translation>0%</translation>
+        <translation type="unfinished"></translation>
     </message>
     <message>
-        <source>Follow these steps to get your device ready:&lt;br&gt;	1. Bring your device inside and connect to a good USB-C adapter&lt;br&gt;	2. Connect to Wi-Fi&lt;br&gt;	3. Enable the toggle&lt;br&gt;	4. Leave it connected for at least 30 minutes&lt;br&gt;&lt;br&gt;The toggle turns off once you restart your device. Repeat at least once a week for maximum effectiveness.&lt;br&gt;&lt;br&gt;&lt;b&gt;FAQ&lt;/b&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;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;i&gt;Do I need to be on Wi-Fi?&lt;/i&gt; Yes.&lt;br&gt;&lt;i&gt;Do I need to bring the device inside?&lt;/i&gt; No, you can enable once you&apos;re parked, however your uploads will be limited by your car&apos;s battery.&lt;br&gt;</source>
+        <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>按照以下步驟準備您的裝置：&lt;br&gt;	1. 將裝置帶到室內並連接到良好的 USB-C 充電器&lt;br&gt;	2. 連接 Wi-Fi&lt;br&gt;	3. 啟用開關&lt;br&gt;	4. 保持連接至少 30 分鐘&lt;br&gt;&lt;br&gt;開關會在裝置重新啟動後自動關閉。請至少每週重複一次，以獲得最佳效果。&lt;br&gt;&lt;br&gt;&lt;b&gt;常見問題&lt;/b&gt;&lt;br&gt;&lt;i&gt;駕駛方式或地點重要嗎？&lt;/i&gt; 不，按照平常的方式駕駛即可。&lt;br&gt;&lt;i&gt;什麼是良好的 USB-C 充電器？&lt;/i&gt; 任何快速手機或筆記本電腦充電器都可以。&lt;br&gt;&lt;i&gt;我需要連接 Wi-Fi 嗎？&lt;/i&gt; 是的。&lt;br&gt;&lt;i&gt;我需要把裝置帶到室內嗎？&lt;/i&gt; 不，您可以在停車後啟用，但您的上傳速度將受限於車輛的電池。&lt;br&gt;</translation>
+        <translation type="unfinished"></translation>
     </message>
 </context>
 <context>

system/athena/athenad.py

@@ -508,10 +508,6 @@ def getSshAuthorizedKeys() -> str:
 def getGithubUsername() -> str:
   return Params().get("GithubUsername", encoding='utf8') or ''
 
-@dispatcher.add_method
-def getFirehoseMode() -> bool:
-  return Params().get_bool("FirehoseMode") or False
-
 @dispatcher.add_method
 def getSimInfo():
   return HARDWARE.get_sim_info()

system/hardware/tici/agnos.json

@@ -67,17 +67,17 @@
   },
   {
     "name": "system",
-    "url": "https://commadist.azureedge.net/agnosupdate/system-061783c4826369c7aa711266e8e1d9eecfd0a6d6c8afc6042e4045617512be75.img.xz",
+    "url": "https://commadist.azureedge.net/agnosupdate/system-5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9.img.xz",
-    "hash": "affcc08700026f1726ef16337e031fffc5556435b2b0facea81c7ffb0b66560c",
+    "hash": "e4872f4132111b7b28586d978dd01bb48ffa031e103d029ebede7613c1bc2aa6",
-    "hash_raw": "061783c4826369c7aa711266e8e1d9eecfd0a6d6c8afc6042e4045617512be75",
+    "hash_raw": "5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9",
     "size": 4404019200,
     "sparse": true,
     "full_check": false,
     "has_ab": true,
-    "ondevice_hash": "cc86836c6fc1c54f24dd0395e57e0b1ac6efe44d3ece833ab3ed456fe46a55cf",
+    "ondevice_hash": "4e5e680b4ac387ddc974b32dd3d5ec1d76282511eab974866b3b72399034985e",
     "alt": {
-      "hash": "061783c4826369c7aa711266e8e1d9eecfd0a6d6c8afc6042e4045617512be75",
+      "hash": "5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9",
-      "url": "https://commadist.azureedge.net/agnosupdate/system-061783c4826369c7aa711266e8e1d9eecfd0a6d6c8afc6042e4045617512be75.img",
+      "url": "https://commadist.azureedge.net/agnosupdate/system-5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9.img",
       "size": 4404019200
     }
   }

system/hardware/tici/all-partitions.json

@@ -350,51 +350,51 @@
   },
   {
     "name": "system",
-    "url": "https://commadist.azureedge.net/agnosupdate/system-061783c4826369c7aa711266e8e1d9eecfd0a6d6c8afc6042e4045617512be75.img.xz",
+    "url": "https://commadist.azureedge.net/agnosupdate/system-5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9.img.xz",
-    "hash": "affcc08700026f1726ef16337e031fffc5556435b2b0facea81c7ffb0b66560c",
+    "hash": "e4872f4132111b7b28586d978dd01bb48ffa031e103d029ebede7613c1bc2aa6",
-    "hash_raw": "061783c4826369c7aa711266e8e1d9eecfd0a6d6c8afc6042e4045617512be75",
+    "hash_raw": "5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9",
     "size": 4404019200,
     "sparse": true,
     "full_check": false,
     "has_ab": true,
-    "ondevice_hash": "cc86836c6fc1c54f24dd0395e57e0b1ac6efe44d3ece833ab3ed456fe46a55cf",
+    "ondevice_hash": "4e5e680b4ac387ddc974b32dd3d5ec1d76282511eab974866b3b72399034985e",
     "alt": {
-      "hash": "061783c4826369c7aa711266e8e1d9eecfd0a6d6c8afc6042e4045617512be75",
+      "hash": "5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9",
-      "url": "https://commadist.azureedge.net/agnosupdate/system-061783c4826369c7aa711266e8e1d9eecfd0a6d6c8afc6042e4045617512be75.img",
+      "url": "https://commadist.azureedge.net/agnosupdate/system-5612484e7f255659c0845de620e7c733afd2e1b939f9464f5ef039721bb7cba9.img",
       "size": 4404019200
     }
   },
   {
     "name": "userdata_90",
-    "url": "https://commadist.azureedge.net/agnosupdate/userdata_90-fd9d27a3ef5c1f63b85721798ba4ea10f2a4c71d0c8d9b59362a99f24dfff54a.img.xz",
+    "url": "https://commadist.azureedge.net/agnosupdate/userdata_90-16c037fa42ee99bc6ec92909efc8a8075a0e8a0232a7d90e39e7d40a7bd0ee8e.img.xz",
-    "hash": "b77b66ae8178519dbd72443ff7bdd21b97d0d4d76425472bedc7d369958de37b",
+    "hash": "c6fb215f2b297f7ff5b8f133bc5d687772b37f2fee42a44aa730e37a84a14e52",
-    "hash_raw": "fd9d27a3ef5c1f63b85721798ba4ea10f2a4c71d0c8d9b59362a99f24dfff54a",
+    "hash_raw": "16c037fa42ee99bc6ec92909efc8a8075a0e8a0232a7d90e39e7d40a7bd0ee8e",
     "size": 96636764160,
     "sparse": true,
     "full_check": true,
     "has_ab": false,
-    "ondevice_hash": "52d2b8e2486e7fa0cdeb2a6512a8058db43544c905367a2e1b81a5ad4636d4b7"
+    "ondevice_hash": "7199262f209abbb07be5eece505ac4d4c7ba8957f2d9ff7b1ac1ef2063461665"
   },
   {
     "name": "userdata_89",
-    "url": "https://commadist.azureedge.net/agnosupdate/userdata_89-1042711c5f69146ff7680f09eab1b2eb6fe9da0411318e9ff913c27168cb0307.img.xz",
+    "url": "https://commadist.azureedge.net/agnosupdate/userdata_89-62c2c41470282b581ec1bbbe0375fb3b6c66df2f4bc3dc6c6fdf796f1797f136.img.xz",
-    "hash": "cc24b1c78234f92cd8ef66541f3fb8924719fc4b7f42c26e26eb71ec21cd2e93",
+    "hash": "d66f894436fa11d4ff00f8a84e54d9e23a6492b0087f69bb958d2ab0bdc6dfba",
-    "hash_raw": "1042711c5f69146ff7680f09eab1b2eb6fe9da0411318e9ff913c27168cb0307",
+    "hash_raw": "62c2c41470282b581ec1bbbe0375fb3b6c66df2f4bc3dc6c6fdf796f1797f136",
     "size": 95563022336,
     "sparse": true,
     "full_check": true,
     "has_ab": false,
-    "ondevice_hash": "80bf38b8b60ea1ef1fc0849af4e18bf114761f98f5371476e2f762d0f8463204"
+    "ondevice_hash": "f1d3685618f6d1bde24ce6109284c5d30ece2f4fd015be67e8b52ef7e06067a4"
   },
   {
     "name": "userdata_30",
-    "url": "https://commadist.azureedge.net/agnosupdate/userdata_30-6d429550c42616e3f252034305f238ce0e90926762992ff3f92322f226caa5b6.img.xz",
+    "url": "https://commadist.azureedge.net/agnosupdate/userdata_30-3e71d8804c90a6dff5048edb976149f9ea177efa139dea47cb585cef76b26f6e.img.xz",
-    "hash": "657b052cf6434ef19ff73bdeaf5b2511e5c42f64594ae37bac467a12b4cd673f",
+    "hash": "1b201ecbd0e1573777811bf18fa90cb080bfbccb34a6dcfd39b412632e7ca699",
-    "hash_raw": "6d429550c42616e3f252034305f238ce0e90926762992ff3f92322f226caa5b6",
+    "hash_raw": "3e71d8804c90a6dff5048edb976149f9ea177efa139dea47cb585cef76b26f6e",
     "size": 32212254720,
     "sparse": true,
     "full_check": true,
     "has_ab": false,
-    "ondevice_hash": "6437e5a5b7144103952950f2f59f8e70b98cd26ee5bfb06cbd0a13b2e2f343b7"
+    "ondevice_hash": "47c28e63209556442cd9d2fd06a6c0e7fcf35c8a4e4fbcc550b9c089429ad0e0"
   }
 ]

tinygrad_repo

@@ -1 +1 @@
-Subproject commit 6f39c4d653737c056540194605dc18a7273df280
+Subproject commit 70266e9f94d5a247ccbb2f3a46e72a2fbdaf7a8e

tools/cabana/dbc/generate_dbc_json.py

@@ -7,7 +7,7 @@ from opendbc.car.fingerprints import MIGRATION
 from opendbc.car.values import PLATFORMS
 
 
-def generate_dbc_json() -> str:
+def generate_dbc_dict() -> dict[str, str]:
   dbc_map = {}
   for platform in PLATFORMS.values():
     if platform != "MOCK":
@@ -24,7 +24,7 @@ def generate_dbc_json() -> str:
     if MIGRATION[m] in dbc_map:
       dbc_map[m] = dbc_map[MIGRATION[m]]
 
-  return json.dumps(dict(sorted(dbc_map.items())), indent=2)
+  return dbc_map
 
 
 if __name__ == "__main__":
@@ -35,5 +35,5 @@ if __name__ == "__main__":
   args = parser.parse_args()
 
   with open(args.out, 'w') as f:
-    f.write(generate_dbc_json())
+    f.write(json.dumps(dict(sorted(generate_dbc_dict().items())), indent=2))
   print(f"Generated and written to {args.out}")

tools/car_porting/README.md

@@ -57,7 +57,21 @@ Traceback (most recent call last):
 AssertionError: 1 is not false : panda safety doesn't agree with openpilot: {'gasPressed': 116}
 ```
 
-### [tools/car_porting/examples/subaru_steer_temp_fault.ipynb](/tools/car_porting/examples/subaru_steer_temp_fault.ipynb)
+## Jupyter notebooks
+
+To use these notebooks, install Jupyter within your [openpilot virtual environment](/tools/README.md).
+
+```bash
+uv pip install jupyter ipykernel
+```
+
+Launching:
+
+```bash
+jupyter notebook
+```
+
+### [examples/subaru_steer_temp_fault.ipynb](/tools/car_porting/examples/subaru_steer_temp_fault.ipynb)
 
 An example of searching through a database of segments for a specific condition, and plotting the results.
 
@@ -65,7 +79,7 @@ An example of searching through a database of segments for a specific condition,
 
 *a plot of the steer_warning vs steering angle, where we can see it is clearly caused by a large steering angle change*
 
-### [tools/car_porting/examples/subaru_long_accel.ipynb](/tools/car_porting/examples/subaru_long_accel.ipynb)
+### [examples/subaru_long_accel.ipynb](/tools/car_porting/examples/subaru_long_accel.ipynb)
 
 An example of plotting the response of an actuator when it is active.
 
@@ -73,7 +87,7 @@ An example of plotting the response of an actuator when it is active.
 
 *a plot of the brake_pressure vs acceleration, where we can see it is a fairly linear response.*
 
-### [tools/car_porting/examples/ford_vin_fingerprint.ipynb](/tools/car_porting/examples/ford_vin_fingerprint.ipynb)
+### [examples/ford_vin_fingerprint.ipynb](/tools/car_porting/examples/ford_vin_fingerprint.ipynb)
 
 In this example, we use the public comma car segments database to check if vin fingerprinting is feasible for ford.
 
@@ -94,3 +108,22 @@ vin: 5LM5J7XC8MGXXXXXX real platform: FORD EXPLORER 6TH GEN              determi
 vin: 3FTTW8E31PRXXXXXX real platform: FORD MAVERICK 1ST GEN              determined platform: mock                              correct: False
 vin: 3FTTW8E99NRXXXXXX real platform: FORD MAVERICK 1ST GEN              determined platform: mock                              correct: False
 ```
+
+### [examples/find_segments_with_message.ipynb](/tools/car_porting/examples/find_segments_with_message.ipynb)
+
+Searches for segments where a set of given CAN message IDs are present. In the example, we search for all messages
+used for CAN-based ignition detection.
+
+```
+Match found: 46b21f1c5f7aa885/2024-01-23--15-19-34/20/s    JEEP GRAND CHEROKEE V6 2018            ['VW CAN Ign']
+Match found: a63a23c3e628f288/2023-11-05--18-36-20/8/s     JEEP GRAND CHEROKEE V6 2018            ['VW CAN Ign']
+Match found: ce31b7a998781ba8/2024-01-19--07-05-29/23/s    JEEP GRAND CHEROKEE 2019               ['VW CAN Ign']
+Match found: e1dfba62a4e33f7b/2023-12-25--19-31-00/4/s     JEEP GRAND CHEROKEE 2019               ['VW CAN Ign']
+Match found: e1dfba62a4e33f7b/2024-01-10--14-33-57/2/s     JEEP GRAND CHEROKEE 2019               ['VW CAN Ign']
+Match found: ae679616266f4096/2023-12-05--15-43-46/4/s     RAM HD 5TH GEN                         ['Tesla 3/Y CAN Ign']
+Match found: ae679616266f4096/2023-11-18--17-49-42/3/s     RAM HD 5TH GEN                         ['Tesla 3/Y CAN Ign']
+Match found: ae679616266f4096/2024-01-03--21-57-09/25/s    RAM HD 5TH GEN                         ['Tesla 3/Y CAN Ign']
+Match found: 6dae2984cc53cd7f/2023-12-10--11-53-15/17/s    FORD BRONCO SPORT 1ST GEN              ['Rivian CAN Ign']
+Match found: 6dae2984cc53cd7f/2023-12-03--17-31-17/29/s    FORD BRONCO SPORT 1ST GEN              ['Rivian CAN Ign']
+Match found: 6dae2984cc53cd7f/2023-11-27--23-29-07/1/s     FORD BRONCO SPORT 1ST GEN              ['Rivian CAN Ign']
+```

tools/car_porting/examples/find_segments_with_message.ipynb

@@ -0,0 +1,232 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "id": "facb8edc-9924-491a-a4dd-fe6135b0c6c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import all cars from opendbc\n",
+    "\n",
+    "from opendbc.car import structs\n",
+    "from opendbc.car.values import PLATFORMS as TEST_PLATFORMS\n",
+    "\n",
+    "# Example: add additional platforms/segments to test outside of commaCarSegments\n",
+    "\n",
+    "EXTRA_SEGMENTS = {\n",
+    "  # \"81dd9e9fe256c397/0000001f--97c42cf98d\",  # Volkswagen ID.4 test route, new car port, not in public dataset\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "id": "ed1c8aec-c274-4c61-b83d-711ea194bf86",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Searching 221 platforms\n",
+      "No segments available for DODGE_DURANGO\n",
+      "No segments available for FORD_RANGER_MK2\n",
+      "No segments available for HOLDEN_ASTRA\n",
+      "No segments available for CADILLAC_ATS\n",
+      "No segments available for CHEVROLET_MALIBU\n",
+      "No segments available for CADILLAC_XT4\n",
+      "No segments available for CHEVROLET_VOLT_2019\n",
+      "No segments available for CHEVROLET_TRAVERSE\n",
+      "No segments available for GMC_YUKON\n",
+      "No segments available for HONDA_ODYSSEY_CHN\n",
+      "No segments available for HYUNDAI_KONA_2022\n",
+      "No segments available for HYUNDAI_NEXO_1ST_GEN\n",
+      "No segments available for GENESIS_GV70_ELECTRIFIED_1ST_GEN\n",
+      "No segments available for GENESIS_G80_2ND_GEN_FL\n",
+      "No segments available for RIVIAN_R1_GEN1\n",
+      "No segments available for SUBARU_FORESTER_HYBRID\n",
+      "No segments available for TESLA_MODEL_3\n",
+      "No segments available for TESLA_MODEL_Y\n",
+      "No segments available for TOYOTA_RAV4_PRIME\n",
+      "No segments available for TOYOTA_SIENNA_4TH_GEN\n",
+      "No segments available for LEXUS_LC_TSS2\n",
+      "No segments available for VOLKSWAGEN_CADDY_MK3\n",
+      "No segments available for VOLKSWAGEN_CRAFTER_MK2\n",
+      "No segments available for VOLKSWAGEN_JETTA_MK6\n",
+      "Searching 577 segments\n"
+     ]
+    }
+   ],
+   "source": [
+    "import random\n",
+    "\n",
+    "from openpilot.tools.lib.logreader import LogReader\n",
+    "from openpilot.tools.lib.comma_car_segments import get_comma_car_segments_database\n",
+    "\n",
+    "\n",
+    "MAX_SEGS_PER_PLATFORM = 3  # Increase this to search more segments\n",
+    "\n",
+    "database = get_comma_car_segments_database()\n",
+    "TEST_SEGMENTS = []\n",
+    "\n",
+    "print(f\"Searching {len(TEST_PLATFORMS)} platforms\")\n",
+    "\n",
+    "for platform in TEST_PLATFORMS:\n",
+    "  if platform not in database:\n",
+    "    print(f\"No segments available for {platform}\")\n",
+    "    continue\n",
+    "  \n",
+    "  all_segments = database[platform]\n",
+    "  NUM_SEGMENTS = min(len(all_segments), MAX_SEGS_PER_PLATFORM)\n",
+    "  TEST_SEGMENTS.extend(random.sample(all_segments, NUM_SEGMENTS))\n",
+    "\n",
+    "TEST_SEGMENTS.extend(EXTRA_SEGMENTS)\n",
+    "\n",
+    "print(f\"Searching {len(TEST_SEGMENTS)} segments\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0c75e8f2-4f5f-4f89-b8db-5223a6534a9f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "27a243c33de44498b2b946190df44b23",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "segments searched:   0%|          | 0/577 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Match found: 0f53b336851e1384/2023-11-20--09-44-03/12/s    CHRYSLER PACIFICA HYBRID 2018          ['VW CAN Ign']\n",
+      "Match found: 7620ad20d3cefc64/2023-10-28--08-14-40/3/s     CHRYSLER PACIFICA HYBRID 2018          ['VW CAN Ign']\n",
+      "Match found: 00d247a9bb1f9196/2023-11-06--13-33-17/9/s     CHRYSLER PACIFICA HYBRID 2018          ['VW CAN Ign']\n",
+      "Match found: 120a432f63cb0de2/2023-10-30--20-01-34/1/s     CHRYSLER PACIFICA HYBRID 2019          ['VW CAN Ign']\n",
+      "Match found: b70b56b76a6217f2/2023-12-19--08-30-22/35/s    CHRYSLER PACIFICA HYBRID 2019          ['VW CAN Ign']\n",
+      "Match found: 97e388680a6716ed/2024-01-17--10-15-13/9/s     CHRYSLER PACIFICA HYBRID 2019          ['VW CAN Ign']\n",
+      "Match found: 2137b01aa0ca63f9/2024-01-06--22-06-14/70/s    CHRYSLER PACIFICA 2018                 ['VW CAN Ign']\n",
+      "Match found: 8fc6a1b72c8b1357/2023-11-06--07-50-05/8/s     CHRYSLER PACIFICA 2018                 ['VW CAN Ign']\n",
+      "Match found: 7e705eb5c27a49cc/2024-01-18--16-51-20/3/s     CHRYSLER PACIFICA 2018                 ['VW CAN Ign']\n",
+      "Match found: 12208e5acdc97eb3/2024-01-20--14-46-24/12/s    CHRYSLER PACIFICA 2020                 ['VW CAN Ign']\n",
+      "Match found: 12208e5acdc97eb3/2023-11-30--12-01-09/2/s     CHRYSLER PACIFICA 2020                 ['VW CAN Ign']\n",
+      "Match found: 9cad19e0efce3650/2024-01-26--10-24-52/27/s    CHRYSLER PACIFICA 2020                 ['VW CAN Ign']\n",
+      "Match found: 9db428338427dec2/2023-11-05--18-40-09/21/s    JEEP GRAND CHEROKEE V6 2018            ['VW CAN Ign']\n",
+      "Match found: d50ada8ee55a5e74/2023-12-11--13-38-09/0/s     JEEP GRAND CHEROKEE V6 2018            ['VW CAN Ign']\n",
+      "Match found: 900dfa83b4addfe6/2023-12-30--19-20-08/28/s    JEEP GRAND CHEROKEE V6 2018            ['VW CAN Ign']\n",
+      "Match found: 20acda0eb23d7f23/2024-01-19--17-33-26/41/s    JEEP GRAND CHEROKEE 2019               ['VW CAN Ign']\n",
+      "Match found: 1cc3b46843cad2ca/2024-01-10--20-20-54/24/s    JEEP GRAND CHEROKEE 2019               ['VW CAN Ign']\n",
+      "Match found: 2d9b6425552c52c1/2023-12-07--10-31-46/22/s    JEEP GRAND CHEROKEE 2019               ['VW CAN Ign']\n",
+      "Match found: ae679616266f4096/2023-12-04--13-13-56/16/s    RAM HD 5TH GEN                         ['Tesla 3/Y CAN Ign']\n",
+      "Match found: ae679616266f4096/2024-01-08--07-58-12/65/s    RAM HD 5TH GEN                         ['Tesla 3/Y CAN Ign']\n",
+      "Match found: ae679616266f4096/2023-12-05--15-43-46/25/s    RAM HD 5TH GEN                         ['Tesla 3/Y CAN Ign']\n",
+      "Match found: 6dae2984cc53cd7f/2024-01-09--21-41-11/4/s     FORD BRONCO SPORT 1ST GEN              ['Rivian CAN Ign']\n",
+      "Match found: 440a155809ba2b6d/2023-12-30--08-51-53/2/s     FORD BRONCO SPORT 1ST GEN              ['Rivian CAN Ign']\n",
+      "Match found: 6dae2984cc53cd7f/2024-01-06--10-11-07/1/s     FORD BRONCO SPORT 1ST GEN              ['Rivian CAN Ign']\n",
+      "Match found: a4218e6416dfd978/2023-11-27--13-48-46/19/s    FORD ESCAPE 4TH GEN                    ['Rivian CAN Ign']\n",
+      "Match found: a4218e6416dfd978/2023-11-10--14-13-14/0/s     FORD ESCAPE 4TH GEN                    ['Rivian CAN Ign']\n",
+      "Match found: a4218e6416dfd978/2023-11-27--13-48-46/4/s     FORD ESCAPE 4TH GEN                    ['Rivian CAN Ign']\n",
+      "Match found: 8a732841c3a8d5ef/2023-12-10--19-02-33/3/s     FORD EXPLORER 6TH GEN                  ['Rivian CAN Ign']\n",
+      "Match found: 0b91b433b9332780/2023-12-28--14-02-49/4/s     FORD EXPLORER 6TH GEN                  ['Rivian CAN Ign']\n",
+      "Match found: 8a732841c3a8d5ef/2023-11-09--07-28-12/1/s     FORD EXPLORER 6TH GEN                  ['Rivian CAN Ign']\n",
+      "Match found: e886087f430e7fe7/2023-11-05--19-59-40/59/s    FORD FOCUS 4TH GEN                     ['Rivian CAN Ign']\n",
+      "Match found: e886087f430e7fe7/2023-11-05--19-59-40/82/s    FORD FOCUS 4TH GEN                     ['Rivian CAN Ign']\n",
+      "Match found: e886087f430e7fe7/2023-11-05--19-59-40/106/s   FORD FOCUS 4TH GEN                     ['Rivian CAN Ign']\n"
+     ]
+    }
+   ],
+   "source": [
+    "from openpilot.tools.lib.logreader import LogReader\n",
+    "from tqdm.notebook import tqdm, tnrange\n",
+    "\n",
+    "# Example search for CAN ignition messages\n",
+    "# Be careful when filtering by bus, account for odd harness arrangements on Honda/HKG\n",
+    "\n",
+    "BUSES_TO_SEARCH = [0, 1, 2]\n",
+    "\n",
+    "# Support for external Red Panda\n",
+    "EXTERNAL_PANDA_BUSES = [bus + 4 for bus in BUSES_TO_SEARCH]\n",
+    "\n",
+    "MESSAGES_TO_FIND = {\n",
+    "  0x1F1: \"GM CAN Ign\",\n",
+    "  0x152: \"Rivian CAN Ign\",\n",
+    "  0x221: \"Tesla 3/Y CAN Ign\",\n",
+    "  0x9E:  \"Mazda CAN Ign\",\n",
+    "  0x3C0: \"VW CAN Ign\",\n",
+    "}\n",
+    "\n",
+    "progress_bar = tnrange(len(TEST_SEGMENTS), desc=\"segments searched\")\n",
+    "\n",
+    "for segment in TEST_SEGMENTS:\n",
+    "  lr = LogReader(segment)\n",
+    "  CP = lr.first(\"carParams\")\n",
+    "  if CP is None:\n",
+    "    progress_bar.update()\n",
+    "    continue\n",
+    "\n",
+    "  can_packets = [msg for msg in lr if msg.which() == \"can\"]\n",
+    "  matched_messages = set()\n",
+    "\n",
+    "  for packet in can_packets:\n",
+    "    for msg in packet.can:\n",
+    "      if msg.address in MESSAGES_TO_FIND and msg.src in (BUSES_TO_SEARCH + EXTERNAL_PANDA_BUSES):\n",
+    "        # print(msg)\n",
+    "        matched_messages.add(msg.address)\n",
+    "\n",
+    "  if len(matched_messages) > 0:\n",
+    "    message_names = [MESSAGES_TO_FIND[message] for message in matched_messages]\n",
+    "    print(f\"Match found: {segment:<45} {CP.carFingerprint:<38} {message_names}\")\n",
+    "\n",
+    "  progress_bar.update()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7724dd97-f62e-4fd3-9f64-63d49be669d2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9f393e00-8efd-40fb-a41e-d312531a83e8",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

tools/plotjuggler/juggle.py

@@ -13,6 +13,7 @@ from functools import partial
 from opendbc.car.fingerprints import MIGRATION
 from openpilot.common.basedir import BASEDIR
 from openpilot.common.swaglog import cloudlog
+from openpilot.tools.cabana.dbc.generate_dbc_json import generate_dbc_dict
 from openpilot.tools.lib.logreader import LogReader, ReadMode, save_log
 from openpilot.selfdrive.test.process_replay.migration import migrate_all
 
@@ -90,11 +91,10 @@ def juggle_route(route_or_segment_name, can, layout, dbc, should_migrate):
   if dbc is None:
     try:
       CP = lr.first('carParams')
-      platform = CP.carFingerprint
+      platform = MIGRATION.get(CP.carFingerprint, CP.carFingerprint)
-      DBC = __import__(f"opendbc.car.{CP.brand}.values", fromlist=['DBC']).DBC
+      dbc = generate_dbc_dict()[platform]
-      dbc = DBC[MIGRATION.get(CP.carFingerprint, CP.carFingerprint)]['pt']
     except Exception:
-      cloudlog.error("Failed to get DBC name from logs!")
+      cloudlog.exception("Failed to get DBC name from logs!")
 
   with tempfile.NamedTemporaryFile(suffix='.rlog', dir=juggle_dir) as tmp:
     save_log(tmp.name, all_data, compress=False)

tools/tuning/measure_steering_accuracy.py

@@ -49,7 +49,7 @@ class SteeringAccuracyTool:
     active = sm['controlsState'].active
     steer = sm['carOutput'].actuatorsOutput.torque
     standstill = sm['carState'].standstill
-    steer_limited = abs(sm['carControl'].actuators.torque - sm['carControl'].actuatorsOutput.torque) > 1e-2
+    steer_limited_by_controls = abs(sm['carControl'].actuators.torque - sm['carControl'].actuatorsOutput.torque) > 1e-2
     overriding = sm['carState'].steeringPressed
     changing_lanes = sm['modelV2'].meta.laneChangeState != 0
     model_points = sm['modelV2'].position.y
@@ -77,7 +77,7 @@ class SteeringAccuracyTool:
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             if len(model_points):
               self.speed_group_stats[group][angle_abs]["dpp"] += abs(model_points[0])
-            if steer_limited:
+            if steer_limited_by_controls:
               self.speed_group_stats[group][angle_abs]["limited"] += 1
             if control_state.saturated:
               self.speed_group_stats[group][angle_abs]["saturated"] += 1

uv.lock

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