typed op• Data kinds: points → feature
• Call: fullseye.apply(img, "tb_estimate_alpha", 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_estimate_alpha: stages (docs site)
Returns a recommended alpha based on the scale of the point cloud (based on the median nearest-neighbor distance).
Finds the median m of each point's nearest-neighbour distance and returns alpha = 1/(2m) so that the radius threshold is 1/alpha ≈ 2m (allowing up to about 2 times the neighbour spacing). This keeps the well-behaved tetrahedra near the surface while cutting off greatly stretched tetrahedra (= concavities, outside). Duplicate points have nearest-neighbour distance 0, so only positive distances are used.
points : array_like (N,3)
alpha : float
A positive finite value.
The 3d op estimate_alpha 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 tuning points; 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_estimate_alpha 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op estimate_alpha. 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).
• alpha_shape_topology — py -3.11 examples_3d/alpha_shape_topology.py
• sfm_recon — py -3.11 examples_3d/sfm_recon.py
feature as input)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.