tb_project_spherical — 2D `typed` op

• Data kinds: points → image

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

Usage

Project onto a spherical range image for rotating LiDAR (v_res, h_res). Empty cells = 0, nearest point wins (minimum range).

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

各点を方位角(列)× 仰角(行)ビンへ落とし、センサ原点からの range(slant distance)を書く。

v_fov=(v_min,v_max)[度] の仰角帯の外側、原点上(r=0)、非有限座標の点は落とす(honest drop)。

空/全 drop の場合は全ゼロ画像を返す(=何も見えていない、honest)。

2-D 進化レジストリへ橋渡しした 3d の op `project_spherical。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。a が h_res(既定 1024)、b が v_res`(既定 64)を振る。

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 `image` as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

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_project_spherical — 2D typed op