typed op• Data kinds: points → points
• Call: fullseye.apply(img, "tb_elastic_deform", 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_elastic_deform: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_elastic_deform: other inputs (docs site)
Elastic deformation via a smooth random displacement field (correlation length sigma, RMS amplitude alpha).
An independent Gaussian random vector is placed on each point and smoothed with the spatial Gaussian weight exp(-d²/2σ²) to generate a displacement field (nearby points move coherently). The field is normalised to RMS 1 and then multiplied by alpha, so the RMS norm of the displacement is exactly alpha (for σ→∞ the field is constant = rigid-body translation, for σ→0 each point is independent). For non-rigid object deformation / training on flexible objects.
Caution (honest): the neighbour search is cKDTree.query_pairs(r=3σ). The closer σ gets to the diameter of the cloud, the closer the number of pairs approaches O(N²), so for large clouds keep σ at a local scale.
sigma < 0 raises ValueError. With sigma == 0 or a cloud of only 1 point no smoothing is done and each point gets an independent displacement. alpha is not validated (0 gives no displacement; a negative value just inverts the field). Deterministic via seed. Returns float64 (N,3) with point count and order preserved (since the correspondence before and after deformation is known by index, the error of non-rigid registration can be measured directly). Empty input returns empty.
The 3d op elastic_deform 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_elastic_deform 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op elastic_deform. 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).
• sensor_seg — py -3.11 examples_3d/sensor_seg.py
points as input)identity · 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
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.