Optimize get_cluster_candidates with numpy#13
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Resolves the TODO item in `frigate/util/object.py` line 402. - Early exit if the list of boxes is empty. - Converts the loop-based nested iteration into a vectorized `np.where` query for improved efficiency and readability. - Replaces the list lookup for used indices with an O(1) set. - Vectorizes the proportional area size logic to determine cluster feasibility. Co-authored-by: manupawickramasinghe <73810867+manupawickramasinghe@users.noreply.github.com>
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This PR refactors
get_cluster_candidateswithinfrigate/util/object.pyto utilizenumpyoperations. The optimization significantly limits the number of Python-side loop operations for inner list comprehensions, effectively completing theTODO: see if we can do this with numpy.compare_boxlooping bounded box comparisons with a vectorized conditioninside_maskapplied to aboxes_arr.used_boxesfrom a list to aset()to grant O(1) checks.np.any(box_areas / region_area < 0.05)rather than manually looping and recalculating area ratios over potential cluster candidates iteratively.PR created automatically by Jules for task 10958264842689069209 started by @manupawickramasinghe