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Chris Tsang
46a1b90ccd
An alternative region-forming frontend selected by --clustering watershed (the color_mode field is replaced by clustering: color-cluster | bw | watershed across CLI, Rust, Python, and Node — it selects the algorithm, not a color space). The algorithm is the watershed hierarchy by volume on the 4-adjacency pixel graph, implemented from the papers: Cousty, Bertrand, Najman, Couprie, "Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle", IEEE TPAMI 31(8), 2009. Najman, Cousty, Perret, "Playing with Kruskal", ISMM 2013. Edge weights are the max per-channel color difference between adjacent pixels (no gradient image); a counting-sorted Kruskal pass builds the binary partition tree as a flat parents array; a leaves-to-root pass computes subtree area and volume; each merge's persistence (the volume of the smaller side, plateau-corrected) becomes its MST edge's saliency; and cutting the hierarchy is single-linkage over MST edges below the cut level. Watershed cuts label every pixel — no watershed-line pixel class — so the output is a strict, gapless partition that drops straight into both stacked and cutout modes. Integer arithmetic and flat u32 arrays throughout; deterministic across platforms; ~66 ms on a 1400x775 photo. The one dial, --watershed-detail (0..=255), maps exponentially to a target region count (each +25.5 doubles it) since the persistence distribution is far too skewed for a linear threshold. filter_speckle absorbs undersized basins into their most color-similar neighbour rather than dropping them, preserving the partition. The largest region is emitted first as a solid full-canvas background layer so stacked mode keeps its seam-free overdraw; the mosaic flatten is unaffected. Tests: partition invariant (disjoint masks tiling the canvas), detail monotonicity, min-area absorption, determinism, watershed cases in the pipeline/golden suites, stacked-vs-cutout interior equivalence, a watershed seam test, and SegmentKey coverage for the new params.