project_spherical — 3D `lidar_projection` op

• Data kinds: points → image2d

• Call: import spherical_proj; spherical_proj.project_spherical(points, h_res: 'int' = 1024, v_res: 'int' = 64, v_fov=(-25.0, 15.0)) -> 'np.ndarray' (or ops3d.get("project_spherical"))

Usage

Project into the spherical range image of a spinning LiDAR (v_res, h_res). Empty cells are 0; nearer points win (minimum range).

Background guides (the physics and conventions behind this op)

• depth_sensors — 深度センサの知識 — 測距原理・実機の値・欠測の出方

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)

• lidar_projection — py -3.11 examples_3d/lidar_projection.py

Ops the type connects to (they accept `image2d` as input)

fuse_to_voxel · fit_poly_surface · eval_poly_surface · surface_form_error · background_flatten · polar_unwrap · fit_zernike · matcap_shade

Same category (`lidar_projection`)

unproject_spherical · project_cylindrical

*Provenance: spherical_proj.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

project_spherical — 3D lidar_projection op