unproject_spherical — 3D lidar_projection op

• Data kinds: image2d → points

• Call: import spherical_proj; spherical_proj.unproject_spherical(range_img, v_fov=(-25.0, 15.0)) -> 'np.ndarray' (or ops3d.get("unproject_spherical"))

Usage

Spherical range image → 3-D points (M, 3). Only the cells with range > 0 are back-projected, at their bin-centre angles.

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 points as input)

points_to_voxel · gaussians_to_voxel · estimate_point_normals · to_points · match_points_ncc · match_pca · moment_axes · icp_point2point_3d

Same category (lidar_projection)

project_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).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.