tb_project_spherical — 2D typed op

Data kinds: pointsimage

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])

tb_project_spherical: input → output

*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*

Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):

tb_project_spherical: knob a sweep (docs site)

Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):

tb_project_spherical: knob b sweep (docs site)

Stages (the ops that come before → this op, left to right):

tb_project_spherical: stages (docs site)

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

tb_project_spherical: other inputs (docs site)

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)。

• `points: (N,3)、センサ原点基準で x=前, y=左, z=上。非 (N,3) は ValueError`。

• `h_res / v_res: 列数(方位角 360° の等分)・行数(仰角帯の等分)。正でなければ ValueError`。

• `v_fov: (v_min, v_max) [度]。v_min < v_max でなければ ValueError`。

列は `floor((atan2(y,x) + π) / 2π · h_res) で、列 0 が真後ろ(-x)、h_res//2` が正面(+x)、

反時計回りに増える。行は `(v_res-1) - floor((θ - v_min)/(v_max - v_min) · v_res)`(θ は仰角

[度])で、行 0 が帯の上端(θ=v_max)。画素値は slant range `sqrt(x²+y²+z²)`(座標の単位)。

同じセルに複数点が落ちたら `np.minimum.at` で最小 range を残す(奥の点は失われる)。

逆変換は `unproject_spherical(同じ v_fov` を渡す)。高さで層を切る変種が

`project_cylindrical`。

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。ah_res(既定 1024)、bv_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.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

img_to_points 0.50 0.50
tb_project_spherical 0.50 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

The examples below call the underlying ledger op project_spherical. This bridge op is the same implementation adapted to the fn(v, a, b) convention, so the behaviour carries over unchanged (only the call form differs).

lidar_projectionpy -3.11 examples_3d/lidar_projection.py

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_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal · tb_voxel_grid_downsample


*Provenance: ops.py — 2D 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.