tb_occupancy_grid — 2D `typed` op

• Data kinds: points → volume

• Call: fullseye.apply(img, "tb_occupancy_grid", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Point cloud (N,3) → 3-D occupancy voxel grid (res,res,res) bool (voxels that points fall into are marked occupied).

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

`bounds=((xmin,xmax),(ymin,ymax),(zmin,zmax)) が格子の張る体積、res` は各軸の

ボクセル数(立方 res³)。ボクセルは半開区間 [lo+i/res*span, lo+(i+1)/res*span) で、

上端 (frac==1) の点は最終ボクセルに含める。bounds 外の点は落とす(端セルへ

clamp すると境界に幻の障害物が積もるため)。match3d.points_to_voxel が密度(float)

を作るのに対し、これは planning 用の占有(bool)を作る点が固有。

Raises ValueError for res<=0, non-(N,3) points, or degenerate bounds.

2-D 進化レジストリへ橋渡しした 3d の op `occupancy_grid。実装は同じで、呼び出し規約だけ op(v, a, b) に合わせてある。この op に調整点は無く、a も b` も使われない。

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)

• (none yet)

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

identity · vol_gaussian · vol_median · vol_erode · vol_dilate · vol_threshold · vol_reg_dilate · vol_reg_erode

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

tb_occupancy_grid — 2D typed op