video/detect.py runs these for every frame:
- get_cluster_candidates: used_boxes was a list with `in` membership tests
inside the nested loop (O(n) per check). It is only ever membership-tested,
so switching it to a set (O(1)) leaves output unchanged.
- get_consolidated_object_detections: area(current_box) was recomputed on
every inner-loop iteration though it is loop-invariant; hoist it to one
call per outer detection.
Both are bit-identical (verified against the previous implementations over
randomized inputs). Measured in the release image, get_cluster_candidates on
a frame of 30 detection boxes: 59.2 us -> 42.1 us (1.4x); the gain scales
with the number of boxes per frame.
Adds a partition-invariant test (every box index lands in exactly one
cluster).
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Smarter Regions
* Formatting
* Cleanup
* Fix motion region checking logic
* Add database table and migration for regions
* Update region grid on startup
* Revert init delay change
* Fix mypy
* Move object related functions to util
* Remove unused
* Fix tests
* Remove log
* Update the region daily at 2
* Fix logic
* Formatting
* Initialize grid before starting processing frames
* Move back to creating grid in main process
* Formatting
* Fixes
* Formating
* Fix region check
* Accept all but true
* Use regions grid for startup scan
* Add clarifying comment
* Fix new grid requests
* Add tests
* Delete stale region grids from DB
* refactor existing motion detector
* implement and use cnt bgsub
* pass fps to motion detector
* create a simplified motion detector
* lightning detection
* update default motion config
* lint imports
* use estimated boxes for regions
* use improved motion detector
* update test
* use a different strategy for clustering motion and object boxes
* increase alpha during calibration
* simplify object consolidation
* add some reasonable constraints to the estimated box
* adjust cluster boundary to 10%
* refactor
* add disabled debug code
* fix variable scope
