perf(track): avoid per-frame allocations and list lookups in tracker

Two small per-object-per-frame improvements in the tracker hot path
(match_and_update), both bit-identical:

- get_stationary_threshold returned a freshly constructed StationaryThresholds
  (a dataclass plus a list) on every call for any label not in the three
  known lists - i.e. for common labels like person/dog. The default thresholds
  are constant and never mutated, so return a shared module-level singleton,
  as the other three cases already do.
- untracked_object_boxes membership used `box not in [list of boxes]` (O(n));
  build a set of box tuples for O(1) membership. Boxes are hashable as tuples
  and output is unchanged.

get_stationary_threshold appeared in a live py-spy --gil profile of a camera
process_frames worker. Adds tests for the threshold lookups.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Daniel-dev22 2026-06-20 09:42:22 -04:00
parent 5003ab895c
commit 21c792c22b
3 changed files with 47 additions and 3 deletions

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@ -0,0 +1,39 @@
"""Tests for stationary object classification thresholds."""
import unittest
from frigate.track.stationary_classifier import (
DEFAULT_OBJECT_THRESHOLDS,
DYNAMIC_OBJECT_THRESHOLDS,
NON_STATIONARY_OBJECT_THRESHOLDS,
STATIONARY_OBJECT_THRESHOLDS,
StationaryThresholds,
get_stationary_threshold,
)
class TestStationaryThresholds(unittest.TestCase):
def test_known_labels_return_expected_singletons(self) -> None:
self.assertIs(get_stationary_threshold("package"), STATIONARY_OBJECT_THRESHOLDS)
self.assertIs(get_stationary_threshold("car"), DYNAMIC_OBJECT_THRESHOLDS)
self.assertIs(
get_stationary_threshold("license_plate"),
NON_STATIONARY_OBJECT_THRESHOLDS,
)
def test_unknown_label_returns_shared_default(self) -> None:
# an unknown label must reuse the shared default instance, not allocate
# a fresh one on every call (this runs per object per frame)
first = get_stationary_threshold("person")
second = get_stationary_threshold("dog")
self.assertIs(first, DEFAULT_OBJECT_THRESHOLDS)
self.assertIs(second, DEFAULT_OBJECT_THRESHOLDS)
def test_default_matches_a_fresh_instance(self) -> None:
# the shared default must be value-equivalent to the previous
# per-call StationaryThresholds()
self.assertEqual(DEFAULT_OBJECT_THRESHOLDS, StationaryThresholds())
if __name__ == "__main__":
unittest.main()

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@ -641,9 +641,11 @@ class NorfairTracker(ObjectTracker):
self.deregister(self.track_id_map[e_id], e_id)
# update list of object boxes that don't have a tracked object yet
tracked_object_boxes = [obj["box"] for obj in self.tracked_objects.values()]
tracked_object_boxes = {
tuple(obj["box"]) for obj in self.tracked_objects.values()
}
self.untracked_object_boxes = [
o[2] for o in detections if o[2] not in tracked_object_boxes
o[2] for o in detections if tuple(o[2]) not in tracked_object_boxes
]
def print_objects_as_table(self, tracked_objects: Sequence) -> None:

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@ -63,6 +63,9 @@ NON_STATIONARY_OBJECT_THRESHOLDS = StationaryThresholds(
max_stationary_history=4,
)
# Default thresholds for any other object label
DEFAULT_OBJECT_THRESHOLDS = StationaryThresholds()
def get_stationary_threshold(label: str) -> StationaryThresholds:
"""Get the stationary thresholds for a given object label."""
@ -76,7 +79,7 @@ def get_stationary_threshold(label: str) -> StationaryThresholds:
if label in NON_STATIONARY_OBJECT_THRESHOLDS.objects:
return NON_STATIONARY_OBJECT_THRESHOLDS
return StationaryThresholds()
return DEFAULT_OBJECT_THRESHOLDS
class StationaryMotionClassifier: