Add watershed clustering: hierarchical watershed frontend

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.

docs/design/architecture.md

@@ -111,9 +111,10 @@ Driver flow:
 
 ## Built-in implementations
 
-- **Frontends**
+- **Frontends** (selected by `Config::clustering`)
   - `ColorClusterFrontend` — wraps `visioncortex::color_clusters::Runner`, including the transparency-keying logic that currently lives in `converter.rs` (find unused key color, key fully-transparent pixels, `KeyingAction`).
   - `BinaryFrontend` — threshold → `BinaryImage::to_clusters`.
+  - `WatershedFrontend` — hierarchical watershed by volume on the 4-adjacency pixel graph (Cousty et al. TPAMI 2009; Najman, Cousty & Perret ISMM 2013), cut at `watershed_detail`. Emits a flat partition with a solid full-canvas background layer so stacked overdraw stays seam-free.
   - Third parties implement `Frontend` to feed external label maps or ML segmentation.
 - **ColorFitters**
   - `Identity` (today's behavior: mean cluster color)
@@ -141,7 +142,7 @@ Output size is a tracked metric: the test suite asserts a byte-size budget again
 
 ## CLI
 
-clap 4 derive, in the `vtracer` crate. Kept flags (mapping naturally): `-i/--input`, `-o/--output`, `--preset bw|poster|photo`, `--colormode color|bw`, `--filter_speckle`, `--color_precision`, `--gradient_step`, `--mode pixel|polygon|spline`, `--corner_threshold`, `--segment_length`, `--splice_threshold`, `--path_precision`.
+clap 4 derive, in the `vtracer` crate. Kept flags (mapping naturally): `-i/--input`, `-o/--output`, `--preset bw|poster|photo`, `--clustering color-cluster|bw|watershed` (formerly `--colormode`), `--filter_speckle`, `--color_precision`, `--gradient_step`, `--mode pixel|polygon|spline`, `--corner_threshold`, `--segment_length`, `--splice_threshold`, `--path_precision`.
 
 New: