graph op• Data kinds: image2d → table
• Call: import fullseye as fs; fs.ledger.hierarchical_watershed(image, *, threshold: 'float' = 0.0, n_regions: 'Optional[int]' = None, mask=None, connectivity: 'int' = 4) -> 'Dict[str, object]' (to call the implementation directly, import seggraph; seggraph.hierarchical_watershed(image, *, threshold: 'float' = 0.0, n_regions: 'Optional[int]' = None, mask=None, connectivity: 'int' = 4) -> 'Dict[str, object]'; from the registry, opssegmentation.get("hierarchical_watershed"))
Hierarchical watershed by dynamics: attaches the dynamics saliency to the edges of the minimum spanning forest of the relief image (low places are basins) and returns the components joined by edges with saliency ≤ threshold (if n_regions is given, the smallest threshold that yields that many regions is used) (hierarchical_watershed).
Giving mask restricts it to the inside (0 outside). Returns: labels (1..k), n_regions, basins (the partition at threshold 0 = the watershed basins), n_basins, dynamics (per basin; the deepest basin of each connected component is inf), levels (heights at which basins vanish, ascending), threshold (the value actually used). Number of basins = number of basins with dynamics > threshold (n_expected, counted and returned by this function).
• halcon_segmentation family guide
• graph_hierarchy_and_thresholds — Segmentation from graph, hierarchy and threshold theorems — what is exact, and where the partition breaks down
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• poc_graph_hierarchy_segmentation — py -3.11 examples/poc_graph_hierarchy_segmentation.py
table as input)graph)graph_cut_binary · alpha_expansion · statistical_region_merging · max_tree · area_opening_attr · quasi_flat_zones · alpha_tree · ultrametric_contour_map
*Provenance: seggraph.py — SEGMENTATION operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.