contour_point_num_xld — 2D `contour` op

• Data kinds: contour → feature

• Call: fullseye.apply(img, "contour_point_num_xld", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

• HALCON equivalent: contour_point_num_xld (the HALCON reference is a useful guide to its meaning and parameters)

Usage

> This operator's description has not been translated yet. The original text follows as it is.

XLD 輪郭群のうち最も点数の多い輪郭を選び、その頂点数を 500 点で正規化して [0,1] で返す（500 点以上は 1.0 に飽和）。a, b は未使用。輪郭が無ければ 0 を返す。

HALCON の `contour_point_num_xld`（XLD 輪郭に含まれる点の実数をそのまま返す演算）とは異なり、この実装は点数そのものではなく 500 点でスケーリングした比率を返す近似（feature sort が [0,1] 想定の値を運ぶ契約のため）。

Detailed usage guide

• gallery2d_contour_measure family guide

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• gallery2d_contour_measure — py -3.11 examples/gallery2d_contour_measure.py

Ops the type connects to (they accept `feature` as input)

identity

Same category (`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).*

contour_point_num_xld — 2D contour op