halcon_ext op• Data kinds: contour → feature
• Call: fullseye.apply(img, "hx_smallest_circle_xld", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: smallest_circle_xld (the HALCON reference is a useful guide to its meaning and parameters)
*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):
▸ hx_smallest_circle_xld: stages (docs site)
The radius of the minimum enclosing circle of all contour points (approximated with the centroid as centre), as a normalised feature.
Merges the points of all contours of a contour dict, takes the mean of the points (centroid) as the centre, finds the distance r to the farthest point, and returns r / max(H, W) as np.float64. It is not the true minimum enclosing circle (with the centre also optimised) but an approximation by an "enclosing circle centred on the centroid", and its radius is at least the true value.
• a, b are unused.
• 0.0 if there is not even 1 point (indistinguishable from a valid value of 0).
Even with multiple contours, they are enclosed by 1 circle (not per contour). The normalisation uses the image's longer side, so even the same shape gives a different value when the image size changes. To measure circularity, use hx_fit_circle_contour (residual) or circularity_xld. The exact solution for regions is r2_smallest_circle.
• gallery2d_halcon_ext 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.
threshold 0.50 0.50 sk_find_contours 0.50 0.50 hx_smallest_circle_xld 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.py
feature as input)halcon_ext)hx_gen_circle · hx_gen_ellipse · hx_gen_rectangle2 · hx_gen_checker_region · hx_gen_grid_region · hx_gabor · hx_fit_surface1 · hx_fit_surface2
*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.