sunnypilot v2026.002.000

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

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)