sk_find_contours — 2D `contour` op

• Data kinds: image → contour

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

Usage

Contour extraction (marching squares). Traces curves that cross a specified level value on a grayscale image and returns them as a set of sub-pixel-accuracy contour coordinate sequences -- unlike binary contour extraction, this can handle continuous-valued contours, not just the outer boundary of a binary image.

> The detailed description below is the original text — the summary and the headings are translated.

HALCON に直接対応するものは無い(空欄)。実装は `measure.find_contours(v, level=0.2+0.5*a) のうち頂点数 3 未満の断片を捨てたもの —— a は等高線のレベル(しきい値)を 0.2〜0.7 に振る。b は未使用。戻り値は画像形状と輪郭座標配列のリストを持つ辞書(contour` 型)。

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 `contour` as input)

identity · select_contours · smooth_contours · fit_line_contours · contours_to_region · count_contours · total_length · select_contours_xld

Same category (`contour`)

select_contours · smooth_contours · fit_line_contours · contours_to_region · edges_sub_pix · lines_gauss · select_contours_xld · smooth_contours_xld

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

sk_find_contours — 2D contour op