sunnypilot v2026.002.000

version: sunnypilot v2026.002.000 (staging)
date: 2026-07-21T07:44:02
master commit: 2c334ede443d7391d27575af8c854a095ba702a8

openpilot/system/camerad/test/.gitignore

@@ -0,0 +1,2 @@
+jpegs/
+test_ae_gray

openpilot/system/camerad/test/debug.sh

@@ -0,0 +1,16 @@
+#!/usr/bin/env bash
+set -e
+
+#echo 4294967295 | sudo tee /sys/module/cam_debug_util/parameters/debug_mdl
+
+# no CCI and UTIL, very spammy
+echo 0xfffdbfff | sudo tee /sys/module/cam_debug_util/parameters/debug_mdl
+#echo 0 | sudo tee /sys/module/cam_debug_util/parameters/debug_mdl
+
+sudo dmesg -C
+scons -u --minimal .
+export DEBUG_FRAMES=1
+export DISABLE_ROAD=1 DISABLE_WIDE_ROAD=1
+#export DISABLE_DRIVER=1
+export LOGPRINT=debug
+./camerad

openpilot/system/camerad/test/icp_debug.sh

@@ -0,0 +1,13 @@
+#!/usr/bin/env bash
+set -e
+
+cd /sys/kernel/debug/tracing
+echo "" > trace
+echo 1 > tracing_on
+#echo Y > /sys/kernel/debug/camera_icp/a5_debug_q
+echo 0x1 > /sys/kernel/debug/camera_icp/a5_debug_type
+echo 1 > /sys/kernel/debug/tracing/events/camera/enable
+echo 0xffffffff > /sys/kernel/debug/camera_icp/a5_debug_lvl
+echo 1 > /sys/kernel/debug/tracing/events/camera/cam_icp_fw_dbg/enable
+
+cat /sys/kernel/debug/tracing/trace_pipe

openpilot/system/camerad/test/intercept.sh

@@ -0,0 +1,2 @@
+#!/usr/bin/env bash
+DISABLE_ROAD=1 DISABLE_WIDE_ROAD=1 DEBUG_FRAMES=1 LOGPRINT=debug LD_PRELOAD=/data/tici_test_scripts/isp/interceptor/tmpioctl.so ./camerad

openpilot/system/camerad/test/stress_restart.sh

@@ -0,0 +1,9 @@
+#!/bin/sh
+cd ..
+while :; do
+  ./camerad &
+  pid="$!"
+  sleep 2
+  kill -2 $pid
+  wait $pid
+done

openpilot/system/camerad/test/test_ae_gray.cc

@@ -0,0 +1,84 @@
+#define CATCH_CONFIG_MAIN
+#include "catch2/catch.hpp"
+
+#include <cassert>
+
+#include <cmath>
+#include <cstring>
+
+#include "common/util.h"
+#include "system/camerad/cameras/camera_common.h"
+
+#define W 240
+#define H 160
+
+
+#define TONE_SPLITS 3
+
+float gts[TONE_SPLITS * TONE_SPLITS * TONE_SPLITS * TONE_SPLITS] = {
+  0.917969, 0.917969, 0.375000, 0.917969, 0.375000, 0.375000, 0.187500, 0.187500, 0.187500, 0.917969,
+  0.375000, 0.375000, 0.187500, 0.187500, 0.187500, 0.187500, 0.187500, 0.187500, 0.093750, 0.093750,
+  0.093750, 0.093750, 0.093750, 0.093750, 0.093750, 0.093750, 0.093750, 0.917969, 0.375000, 0.375000,
+  0.187500, 0.187500, 0.187500, 0.187500, 0.187500, 0.187500, 0.093750, 0.093750, 0.093750, 0.093750,
+  0.093750, 0.093750, 0.093750, 0.093750, 0.093750, 0.093750, 0.093750, 0.093750, 0.093750, 0.093750,
+  0.093750, 0.093750, 0.093750, 0.093750, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
+  0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
+  0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
+  0.000000};
+
+
+TEST_CASE("camera.test_calculate_exposure_value") {
+  // set up fake camerabuf
+  CameraBuf cb = {};
+  VisionBuf vb = {};
+  uint8_t * fb_y = new uint8_t[W*H];
+  vb.y = fb_y;
+  cb.cur_yuv_buf = &vb;
+  cb.out_img_width = W;
+  cb.out_img_height = H;
+  Rect rect = {0, 0, W-1, H-1};
+
+  printf("AE test patterns %dx%d\n", cb.out_img_width, cb.out_img_height);
+
+  // mix of 5 tones
+  uint8_t l[5] = {0, 24, 48, 96, 235}; // 235 is yuv max
+
+  bool passed = true;
+  float rtol = 0.05;
+  // generate pattern and calculate EV
+  int cnt = 0;
+  for (int i_0=0; i_0<TONE_SPLITS; i_0++) {
+    for (int i_1=0; i_1<TONE_SPLITS; i_1++) {
+      for (int i_2=0; i_2<TONE_SPLITS; i_2++) {
+        for (int i_3=0; i_3<TONE_SPLITS; i_3++) {
+          int h_0 = i_0 * H / TONE_SPLITS;
+          int h_1 = i_1 * (H - h_0) / TONE_SPLITS;
+          int h_2 = i_2 * (H - h_0 - h_1) / TONE_SPLITS;
+          int h_3 = i_3 * (H - h_0 - h_1 - h_2) / TONE_SPLITS;
+          int h_4 = H - h_0 - h_1 - h_2 - h_3;
+          memset(&fb_y[0], l[0], h_0*W);
+          memset(&fb_y[h_0*W], l[1], h_1*W);
+          memset(&fb_y[h_0*W+h_1*W], l[2], h_2*W);
+          memset(&fb_y[h_0*W+h_1*W+h_2*W], l[3], h_3*W);
+          memset(&fb_y[h_0*W+h_1*W+h_2*W+h_3*W], l[4], h_4*W);
+          float ev = calculate_exposure_value((const CameraBuf*) &cb, rect, 1, 1);
+          // printf("%d/%d/%d/%d/%d ev is %f\n", h_0, h_1, h_2, h_3, h_4, ev);
+          // printf("%f\n", ev);
+
+          // compare to gt
+          float evgt = gts[cnt];
+          if (fabs(ev - evgt) > rtol*evgt) {
+            passed = false;
+          }
+
+          // report
+          printf("%d/%d/%d/%d/%d: ev %f, gt %f, err %f\n", h_0, h_1, h_2, h_3, h_4, ev, evgt, fabs(ev - evgt) / (evgt != 0 ? evgt : 0.00001f));
+          cnt++;
+        }
+      }
+    }
+  }
+  assert(passed);
+
+  delete[] fb_y;
+}

openpilot/system/camerad/test/test_camerad.py

@@ -0,0 +1,162 @@
+import os
+import time
+import pytest
+import numpy as np
+
+from openpilot.cereal.services import SERVICE_LIST
+from openpilot.tools.lib.log_time_series import msgs_to_time_series
+from openpilot.system.camerad.snapshot import get_snapshots
+from openpilot.selfdrive.test.helpers import collect_logs, log_collector, processes_context
+
+TEST_TIMESPAN = 10
+CAMERAS = ('roadCameraState', 'driverCameraState', 'wideRoadCameraState')
+EXPOSURE_STABLE_COUNT = 3
+EXPOSURE_RANGE = (0.15, 0.35)
+MAX_TEST_TIME = 25
+
+
+def _numpy_rgb2gray(im):
+  return np.clip(im[:,:,2] * 0.114 + im[:,:,1] * 0.587 + im[:,:,0] * 0.299, 0, 255).astype(np.uint8)
+
+def _exposure_stats(im):
+  h, w = im.shape[:2]
+  gray = _numpy_rgb2gray(im[h//10:9*h//10, w//10:9*w//10])
+  return float(np.median(gray) / 255.), float(np.mean(gray) / 255.)
+
+def _in_range(median, mean):
+  lo, hi = EXPOSURE_RANGE
+  return lo < median < hi and lo < mean < hi
+
+def _exposure_stable(results):
+  return all(
+    len(v) >= EXPOSURE_STABLE_COUNT and all(_in_range(*s) for s in v[-EXPOSURE_STABLE_COUNT:])
+    for v in results.values()
+  )
+
+
+def run_and_log(procs, services, duration):
+  with processes_context(procs):
+    return collect_logs(services, duration)
+
+@pytest.fixture(scope="module")
+def _camera_session():
+  """Single camerad session that collects logs and exposure data.
+     Runs until exposure stabilizes (min TEST_TIMESPAN seconds for enough log data)."""
+  with processes_context(["camerad"]), log_collector(CAMERAS) as (raw_logs, lock):
+    exposure = {cam: [] for cam in CAMERAS}
+    start = time.monotonic()
+    while time.monotonic() - start < MAX_TEST_TIME:
+      rpic, dpic = get_snapshots(frame="roadCameraState", front_frame="driverCameraState")
+      wpic, _ = get_snapshots(frame="wideRoadCameraState")
+      for cam, img in zip(CAMERAS, [rpic, dpic, wpic], strict=True):
+        exposure[cam].append(_exposure_stats(img))
+
+      if time.monotonic() - start >= TEST_TIMESPAN and _exposure_stable(exposure):
+        break
+
+    elapsed = time.monotonic() - start
+
+  with lock:
+    ts = msgs_to_time_series(raw_logs)
+
+  for cam in CAMERAS:
+    expected_frames = SERVICE_LIST[cam].frequency * elapsed
+    cnt = len(ts[cam]['t'])
+    assert expected_frames*0.8 < cnt < expected_frames*1.2, f"unexpected frame count {cam}: {expected_frames=}, got {cnt}"
+
+    dts = np.abs(np.diff([ts[cam]['timestampSof']/1e6]) - 1000/SERVICE_LIST[cam].frequency)
+    assert (dts < 1.0).all(), f"{cam} dts(ms) out of spec: max diff {dts.max()}, 99 percentile {np.percentile(dts, 99)}"
+
+  return ts, exposure
+
+@pytest.fixture(scope="module")
+def logs(_camera_session):
+  return _camera_session[0]
+
+@pytest.fixture(scope="module")
+def exposure_data(_camera_session):
+  return _camera_session[1]
+
+@pytest.mark.tici
+class TestCamerad:
+  @pytest.mark.parametrize("cam", CAMERAS)
+  def test_camera_exposure(self, exposure_data, cam):
+    lo, hi = EXPOSURE_RANGE
+    checks = exposure_data[cam]
+    assert len(checks) >= EXPOSURE_STABLE_COUNT, f"{cam}: only got {len(checks)} samples"
+
+    # check that exposure converges into the valid range
+    passed = sum(_in_range(med, mean) for med, mean in checks)
+    assert passed >= EXPOSURE_STABLE_COUNT, \
+      f"{cam}: only {passed}/{len(checks)} checks in range. " + \
+      " | ".join(f"#{i+1}: med={m:.4f} mean={u:.4f}" for i, (m, u) in enumerate(checks))
+
+    # check that exposure is stable once converged (no regressions)
+    in_range = False
+    for i, (median, mean) in enumerate(checks):
+      ok = _in_range(median, mean)
+      if in_range and not ok:
+        pytest.fail(f"{cam}: exposure regressed on sample {i+1} " +
+                    f"(median={median:.4f}, mean={mean:.4f}, expected: ({lo}, {hi}))")
+      in_range = ok
+
+  def test_frame_skips(self, logs):
+    for c in CAMERAS:
+      assert set(np.diff(logs[c]['frameId'])) == {1, }, f"{c} has frame skips"
+
+  def test_frame_sync(self, logs):
+    SYNCED_CAMS = ('roadCameraState', 'wideRoadCameraState')
+    n = range(len(logs['roadCameraState']['t'][:-10]))
+
+    frame_ids = {i: [logs[cam]['frameId'][i] for cam in CAMERAS] for i in n}
+    assert all(len(set(v)) == 1 for v in frame_ids.values()), "frame IDs not aligned"
+
+    # road and wide cameras should be synced within 1.1ms
+    synced_times = {i: [logs[cam]['timestampSof'][i] for cam in SYNCED_CAMS] for i in n}
+    diffs = {i: (max(ts) - min(ts))/1e6 for i, ts in synced_times.items()}
+    laggy_frames = {k: v for k, v in diffs.items() if v > 1.1}
+    assert len(laggy_frames) == 0, f"Frames not synced properly: {laggy_frames=}"
+
+    # driver camera should be staggered ~25ms from road camera
+    for i in n:
+      offset_ms = abs(logs['driverCameraState']['timestampSof'][i] - logs['roadCameraState']['timestampSof'][i]) / 1e6
+      assert 20 < offset_ms < 30, f"driver camera stagger out of range at frame {i}: {offset_ms:.1f}ms (expected ~25ms)"
+
+  def test_sanity_checks(self, logs):
+    self._sanity_checks(logs)
+
+  def _sanity_checks(self, ts):
+    for c in CAMERAS:
+      assert c in ts
+      assert len(ts[c]['t']) > 20
+
+      # not a valid request id
+      assert 0 not in ts[c]['requestId']
+
+      # should monotonically increase
+      assert np.all(np.diff(ts[c]['frameId']) >= 1)
+      assert np.all(np.diff(ts[c]['requestId']) >= 1)
+
+      # EOF > SOF
+      assert np.all((ts[c]['timestampEof'] - ts[c]['timestampSof']) > 0)
+
+      # logMonoTime > SOF
+      assert np.all((ts[c]['t'] - ts[c]['timestampSof']/1e9) > 1e-7)
+
+      # logMonoTime > EOF, needs some tolerance since EOF is (SOF + readout time) but there is noise in the SOF timestamping (done via IRQ)
+      assert np.mean((ts[c]['t'] - ts[c]['timestampEof']/1e9) > 1e-7) > 0.7  # should be mostly logMonoTime > EOF
+      assert np.all((ts[c]['t'] - ts[c]['timestampEof']/1e9) > -0.10)        # when EOF > logMonoTime, it should never be more than two frames
+
+  def test_stress_test(self):
+    os.environ['SPECTRA_ERROR_PROB'] = '0.008'
+    try:
+      logs = run_and_log(["camerad", ], CAMERAS, 10)
+    finally:
+      del os.environ['SPECTRA_ERROR_PROB']
+    ts = msgs_to_time_series(logs)
+
+    # we should see some jumps from introduced errors
+    assert np.max([ np.max(np.diff(ts[c]['frameId'])) for c in CAMERAS ]) > 1
+    assert np.max([ np.max(np.diff(ts[c]['requestId'])) for c in CAMERAS ]) > 1
+
+    self._sanity_checks(ts)