typed op• Data kinds: points → volume
• Call: fullseye.apply(img, "tb_plane_segmentation", 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_plane_segmentation: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ tb_plane_segmentation: knob b sweep (docs site)
Stages (the ops that come before → this op, left to right):
▸ tb_plane_segmentation: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_plane_segmentation: other inputs (docs site)
Motion (GIF: frames / views / slices in turn. The still figure is the complete one; the GIF is supplementary):
Iteratively extracts up to max_planes planes via repeated RANSAC (remaining residual points are -1).
> The detailed description below is the original text — the summary and the headings are translated.
残り点集合に :func:ransac_fit.ransac_plane を掛け、その最大 consensus 平面の
inlier 数が `min_inliers` 以上なら新ラベルを与えて除去 → 残りで再検出、を繰り返す。
複数の床/壁/階段状の面を一度に分離する(単一平面適合の pcseg との差)。inlier が
`min_inliers` に満たなくなった時点で停止し、以降の点は残差 -1(球や複雑物体はここに残る)。
Args:
points: (N,3) 点群。
thresh: 点-平面距離の inlier しきい値(距離、要 > 0)。
min_inliers: 平面として採用する最小 inlier 数(要 >= 3)。
max_planes: 抽出する平面の最大枚数(要 >= 1)。
iters: 各 RANSAC 反復数。
seed: 乱数シード(決定論。各平面で seed+平面index を使う)。
Returns:
labels: (N,) int。検出順(=consensus 大きい順に近い)に 0,1,2,... を平面へ付与、
どの平面にも属さない残差点は -1。空入力は shape (0,)。
2-D 進化レジストリへ橋渡しした 3d の op `plane_segmentation。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 max_planes(既定 5)、b が iters`(既定 300)を振る。
• 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_plane_segmentation 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op plane_segmentation. 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).
• object_segmentation — py -3.11 examples_3d/object_segmentation.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.