edges op• Data kinds: voxel → voxel
• Call: import fullseye as fs; fs.ledger.canny3d(vol, low: 'float', high: 'float', sigma: 'float' = 1.0) -> 'np.ndarray' (to call the implementation directly, import edges3d; edges3d.canny3d(vol, low: 'float', high: 'float', sigma: 'float' = 1.0) -> 'np.ndarray'; from the registry, ops3d.get("canny3d"))
3-D Canny edge detection (non-maximum suppression + hysteresis).
vol : (D,H,W) array
Grey voxels.
low, high : float
Lower / upper hysteresis thresholds (on the gradient magnitude). 0 <= low <= high, high > 0.
sigma : float
Standard deviation of the smoothing.
edge_mask : (D,H,W) bool
Edges thinned to 1 voxel.
(1) get the smoothed gradient with gradient3d → (2) keep local maxima by NMS along the gradient direction (trilinear interpolation)
→ (3) grow with 26-connectivity at the low threshold from high-threshold seeds. The thresholds are absolute, so giving them on the scale of gmag.max() for the target is robust.
• 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.
• edges_3d — py -3.11 examples_3d/edges_3d.py
voxel as input)voxel_to_mips · voxel_to_mesh · signed_distance_field · to_points · sobel3d · hessian3d · curvature_maps · edt_jfa
edges)gradient3d · log_zero_crossings · link_edges · edge_points
*Provenance: edges3d.py — 3D 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.