gradient3d — 3D `edges` op

• Data kinds: voxel → gradient

• Call: import fullseye as fs; fs.ledger.gradient3d(vol, sigma: 'float' = 1.0) (to call the implementation directly, import edges3d; edges3d.gradient3d(vol, sigma: 'float' = 1.0); from the registry, ops3d.get("gradient3d"))

Usage

Compute the central-difference gradient after Gaussian smoothing.

> The detailed description below is the original text — the summary and the headings are translated.

Parameters

----------

vol : (D,H,W) array

グレー voxel。

sigma : float

ガウス平滑の標準偏差(voxel 単位)。0 で平滑なし(生の中心差分)。

Returns

-------

gmag : (D,H,W) float64

勾配の大きさ ||∇I||。

gvec : (D,H,W,3) float64

勾配ベクトル。成分は (∂/∂axis0, ∂/∂axis1, ∂/∂axis2) = (depth, height, width)。

Notes

-----

平滑には scipy.ndimage.gaussian_filter(mode="nearest")、微分には np.gradient(spacing=1)

を用いる。np.gradient は内部が中心差分、境界のみ片側差分。

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• edges_3d — py -3.11 examples_3d/edges_3d.py

Ops the type connects to (they accept `gradient` as input)

fuse_to_voxel

Same category (`edges`)

canny3d · 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).*

gradient3d — 3D edges op