typed op• Data kinds: points → signal
• Call: fullseye.apply(img, "tb_gaussian_curvature", 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.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ tb_gaussian_curvature: knob a sweep (docs site)
*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_gaussian_curvature: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_gaussian_curvature: other inputs (docs site)
Gaussian curvature K=k1·k2 (invariant to normal flipping). → (N,).
> The detailed description below is the original text — the summary and the headings are translated.
補足:
• `principal_curvatures と同じ局所二次曲面フィットで k1 * k2 を返す。符号は法線の向きに依らないため normals` 引数を持たない(向き付けは常に近傍重心ヒューリスティクス)。
• 単位は 1/長さ²。半径 R の球なら `1/R²`、円柱・平面は 0、鞍点は負(k1 と k2 が異符号)。
• `k` は近傍点数(既定 25、N-1 に切り詰め)。近傍が 5 点未満の点は 0。
• 楕円点(K>0)/放物点(K=0)/双曲点(K<0)の分類に使う。凸凹の区別は `mean_curvature か shape_index に normals` を渡して行う。
• 入力は (N,3) の点群。決定論的。
2-D 進化レジストリへ橋渡しした 3d の op `gaussian_curvature。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。a が k(既定 25)を振る。b` は未使用。
• 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_gaussian_curvature 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op gaussian_curvature. 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).
• curvature_grasp — py -3.11 examples_3d/curvature_grasp.py
• curvature_shape_index — py -3.11 examples_3d/curvature_shape_index.py
signal as input)identity · tb_create_funct_1d_array · tb_smooth_funct_1d_gauss · tb_smooth_funct_1d_mean · tb_derivate_funct_1d · tb_integrate_funct_1d · tb_zero_crossings_funct_1d · tb_abs_funct_1d
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.