distance_peaks — SEGMENTATION `watershed3d` op

• Data kinds: voxel → labels

• Call: import fullseye as fs; fs.ledger.distance_peaks(binary, min_distance: 'float' = 1.0) -> 'np.ndarray' (to call the implementation directly, import watershed3d; watershed3d.distance_peaks(binary, min_distance: 'float' = 1.0) -> 'np.ndarray'; from the registry, opssegmentation.get("distance_peaks"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

前景距離変換の局所極大を `min_distance` NMS で間引いた int マーカ配列を返す。

:func:volops.vol_distance_transform + :func:volops.vol_local_maxima の薄い合成に、

「極大座標→ラベル配列(1 物体 1 シード)」の後処理を足したもの(`watershed_vol` が

内部で使うシード生成を単体で公開=可視化・検証用)。

Parameters

----------

binary : array_like

bool または 0/1 の 3D 前景ボリューム。

min_distance : float

採用シード間の最小ユークリッド距離(voxel)。物体間隔より小さく、物体内ノイズ極大の

間隔より大きく取る。

Returns

-------

markers : ndarray(int32)

binary と同形状。0=シード無し、1..k=各シードラベル。

Detailed usage guide

• halcon_segmentation family guide

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.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• watershed3d_tour — py -3.11 examples/watershed3d_tour.py

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

—

Same category (`watershed3d`)

watershed_vol · separate_touching

*Provenance: watershed3d.py — SEGMENTATION operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

distance_peaks — SEGMENTATION watershed3d op