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* simplify onvif and autotracking code Removes about 230 lines from the ONVIF controller and autotracker without changing how PTZ moves are calculated. `OnvifController` no longer keeps its own `camera_configs` copy of the camera config, the cached `GetStatus`, `GetServiceCapabilities`, and `AbsoluteMove` request objects are gone in favor of plain dicts at the call site, and `PtzAutoTrackerThread` is merged into `PtzAutoTracker`. Repeated blocks in the autotracker (waiting for the motor to stop, disabling autotracking on a failed setup step) are now single helpers. * use camera config for autotracking enabled state Camera processes read autotracking state from a shared `autotracker_enabled` value that the dispatcher and autotracker had to keep in sync with the config by hand. Camera processes now subscribe to the `autotracking` and `onvif` config updates and read `onvif.autotracking.enabled` directly, so the shared value and the autotracker's mirroring method are gone. `_disable` now publishes its change so the camera process hears about it. Also removes `tracking_active`, which was set and cleared but never read. * compute max target box from live zoom factor * fix autotracking debug overlay max target box lookup * make max target box a function of zoom factor
120 lines
4.4 KiB
Python
120 lines
4.4 KiB
Python
import unittest
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import numpy as np
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from frigate.config.camera.motion import MotionConfig
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from frigate.motion.improved_motion import ImprovedMotionDetector
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class TestImprovedMotionDetector(unittest.TestCase):
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def setUp(self):
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# small frame for testing; actual frames are grayscale
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self.frame_shape = (100, 100) # height, width
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self.config = MotionConfig()
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# motion detector assumes a rasterized_mask attribute exists on config
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# when update_mask() is called; add one manually by bypassing pydantic.
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object.__setattr__(
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self.config,
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"rasterized_mask",
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np.ones((self.frame_shape[0], self.frame_shape[1]), dtype=np.uint8),
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)
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# create minimal PTZ metrics stub to satisfy detector checks
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class _Stub:
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def __init__(self, value=False):
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self.value = value
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def is_set(self):
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return bool(self.value)
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class DummyPTZ:
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def __init__(self):
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self.motor_stopped = _Stub(False)
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self.stop_time = _Stub(0)
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self.detector = ImprovedMotionDetector(
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self.frame_shape, self.config, fps=30, ptz_metrics=DummyPTZ()
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)
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# establish a baseline frame (all zeros)
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base_frame = np.zeros(
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(self.frame_shape[0], self.frame_shape[1]), dtype=np.uint8
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)
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self.detector.detect(base_frame)
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def _half_change_frame(self) -> np.ndarray:
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"""Produce a frame where roughly half of the pixels are different."""
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frame = np.zeros((self.frame_shape[0], self.frame_shape[1]), dtype=np.uint8)
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# flip the top half to white
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frame[: self.frame_shape[0] // 2, :] = 255
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return frame
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def test_skip_motion_threshold_default(self):
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"""With the default (None) setting, motion should always be reported."""
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frame = self._half_change_frame()
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boxes = self.detector.detect(frame)
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self.assertTrue(
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boxes, "Expected motion boxes when skip threshold is unset (disabled)"
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)
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def test_skip_motion_threshold_applied(self):
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"""Setting a low skip threshold should prevent any boxes from being returned."""
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# change the config and update the detector reference
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self.config.skip_motion_threshold = 0.4
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self.detector.config = self.config
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self.detector.update_mask()
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frame = self._half_change_frame()
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boxes = self.detector.detect(frame)
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self.assertEqual(
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boxes,
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[],
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"Motion boxes should be empty when scene change exceeds skip threshold",
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)
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def _bright_frame(self, offset: int) -> np.ndarray:
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"""Produce a bright frame with a small dark object that moves."""
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frame = np.full((self.frame_shape[0], self.frame_shape[1]), 200, dtype=np.uint8)
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x = 10 + (offset * 5) % 60
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frame[40:60, x : x + 15] = 20
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return frame
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def test_skip_motion_threshold_recovers_after_skip(self):
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"""Skipped frames must still be blended into the background.
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A bright scene differs from the zeroed background across the whole
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frame, so the first frames are skipped. The background has to catch up
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anyway, otherwise motion detection never returns.
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"""
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self.config.skip_motion_threshold = 0.5
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self.config.improve_contrast = False
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self.detector.config = self.config
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self.detector.update_mask()
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boxes = [len(self.detector.detect(self._bright_frame(i))) for i in range(40)]
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self.assertEqual(boxes[0], 0, "First frame should exceed the skip threshold")
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self.assertGreater(
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self.detector.avg_frame.max(),
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0,
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"Background was never updated while frames were skipped",
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)
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self.assertTrue(any(boxes), "Motion detection never recovered after a skip")
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def test_skip_motion_threshold_does_not_affect_calibration(self):
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"""Even when skipping, the detector should go into calibrating state."""
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self.config.skip_motion_threshold = 0.4
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self.detector.config = self.config
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self.detector.update_mask()
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frame = self._half_change_frame()
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_ = self.detector.detect(frame)
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self.assertTrue(
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self.detector.calibrating,
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"Detector should be in calibrating state after skip event",
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)
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if __name__ == "__main__":
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unittest.main()
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