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Skip the BGR conversion when there are no detections

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Hoisting the YUV to BGR conversion out of the detection loop made it run even
on frames with an empty detection list, where the previous per-detection code
converted nothing at all. match_and_update is called with an empty list
whenever detection is disabled, and whenever motion triggered detection but
the detector returned no trackable objects, so this is the common case on a
camera that is mostly idle.

A wasted full-frame conversion costs 0.69 ms / 2.8 MB at 1280x720 and
2.89 ms / 12.3 MB at 2688x1520 - 4x to 17x more than the contrast LUT saves
per frame - which would have made this change a net regression for
autotracking cameras.
This commit is contained in:
Mika 2026-08-13 23:13:56 +02:00
parent 231c648e87
commit d93f296691
1 changed files with 7 additions and 2 deletions
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9
frigate/track/norfair_tracker.py
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@ -526,9 +526,14 @@ class NorfairTracker(ObjectTracker):
# Convert the frame to BGR once per call for histogram embeddings rather
# than once per detection; every detection histograms a region of the
# same frame.
# same frame. Skipped when there are no detections, so a frame without
# objects costs no conversion at all.
bgr_frame: np.ndarray | None = None
if yuv_frame is not None and self.ptz_metrics.autotracker_enabled.value:
if (
detections
and yuv_frame is not None
and self.ptz_metrics.autotracker_enabled.value
):
bgr_frame = cv2.cvtColor(yuv_frame, cv2.COLOR_YUV2BGR_I420)
for obj in detections: