tariqsulley 69e27b4855 Fix #78916: unpredictable results with merge by distance
The previous implementation used KDTree duplicate search with
BLI_kdtree_3d_calc_duplicates_fast(). The survivor was always
one of the input vertices, not the centroid of the cluster.

This caused cases where merging a line of vertices did not
collapse to their average position, resulting in jagged loops.

Now vertices within the threshold are clustered, their centroid
is computed, and the chosen survivor is snapped to this centroid.
This ensures predictable and consistent merge results.

Ref !145851
2025-09-19 15:09:14 +10:00
2025-08-11 12:02:20 +02:00
2025-09-16 18:04:25 +02:00
2023-12-08 13:28:13 +11:00
2025-07-10 12:48:33 +10:00

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