contour op• Data kinds: image → contour
• Call: fullseye.apply(img, "lines_facet", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: lines_facet (the HALCON reference is a useful guide to its meaning and parameters)

*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*
Detects line-like structures (ridges) and returns them as a contour (XLD contour). The implementation computes 'line-ness' using a Frangi filter (`skimage.filters.frangi, multiscale sigma=1..3 ridge enhancement), and outputs the pixel coordinates of connected components exceeding the threshold 0.1+0.4a` directly as a contour point sequence. b is unused.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の `lines_facet`(局所多項式近似=ファセットモデルで線を検出する演算)とは検出原理が異なる近似 —— facet モデルによるサブピクセル位置推定は行わず、Frangi 応答の二値化領域を輪郭化しているだけなので、座標はサブピクセル精度を持たない。
• gallery2d_contour_measure 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.
lines_facet 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_contour_measure — py -3.11 examples/gallery2d_contour_measure.py
contour as input)identity · select_contours · smooth_contours · fit_line_contours · contours_to_region · count_contours · total_length · select_contours_xld
contour)select_contours · smooth_contours · fit_line_contours · contours_to_region · sk_find_contours · edges_sub_pix · lines_gauss · select_contours_xld
*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.