typed op• Data kinds: points → volume
• Call: fullseye.apply(img, "tb_capsule_sdf", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
*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.*
*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
Stages (the ops that come before → this op, left to right):
▸ tb_capsule_sdf: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_capsule_sdf: other inputs (docs site)
Motion (GIF: frames / views / slices in turn. The still figure is the complete one; the GIF is supplementary):
Exact signed distance field of a capsule formed by thickening the segment a–b by radius radius.
sdf(p) = ‖p - (a + clamp(((p-a)·(b-a))/‖b-a‖², 0, 1)·(b-a))‖ - radius. It is exactly the shortest distance to a segment, so the gradient norm is 1 in all of space (unlike a cylinder its ends are round, so it has no corners and is exact). Suited to approximating ribs, piping, bones, wires and the swept volume of a tool.
Arguments and validation (ValueError):
• grid: float array (..., 3) whose last axis is 3.
• a / b: end points of the core line (3 elements). If a == b, a sphere (matches sphere_sdf).
• radius: thickness (negative is rejected).
Return value: float64 of grid.shape[:-1].
Usage: when judging tool reachability by "does the tool's swept volume intersect the part", place the tool as a capsule and check whether the minimum of sdf_intersect is positive. Also for synthesising trabeculae, vessels and fibres.
The 3d op capsule_sdf bridged into the 2-D evolution registry. The implementation is the same; only the calling convention is adapted to op(v, a, b). This op has no tunable parameters; neither a nor b is used.
• 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.
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_capsule_sdf 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op capsule_sdf. 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).
• procedural_hand — py -3.11 examples_3d/procedural_hand.py
• sdf_csg — py -3.11 examples_3d/sdf_csg.py
volume as input)identity · vol_gaussian · vol_median · vol_erode · vol_dilate · vol_threshold · vol_reg_dilate · vol_reg_erode
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.