deformation op• Data kinds: image → image
• Call: fullseye.apply(img, "deform_tps", 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):
▸ deform_tps: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ deform_tps: knob b sweep (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ deform_tps: other inputs (docs site)
*The 4th column is a colour (H,W,3) input. This op handles colour without crossing channels (it does not convolve the colour channel as a third spatial axis).*
Thin-plate-spline warp over a 5x5 control grid (Bookstein, TPAMI 1989).
The 3x3 interior control points are displaced by the deterministic smooth
field `d = amp * [sin(2 pi f gx), cos(2 pi f gy)]` (gy, gx = the control
point's normalised coordinates), the 16 border control points are pinned so
the frame stays anchored. The backward map is the TPS interpolant fitted
from the *displaced* control points back to the original ones -- the unique
minimum-bending-energy interpolant, i.e. the surface a thin metal plate
would take -- and it is evaluated at every destination pixel before bilinear
resampling. `a sets the amplitude amp = 0.15*a*min(H,W), b` the
spatial frequency `f = 0.5 + 1.5b. a = 0` leaves the control points
where they are, so the solved map is the identity (up to sub-pixel resampling error).
• gallery2d_geometry family guide
• 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 canonical algorithm (author, year) and its uses are named in the family usage guide above.
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.
deform_tps 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_geometry — py -3.11 examples/gallery2d_geometry.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
deformation)*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.