hx_clip_contours — 2D `halcon_ext` op

• Data kinds: contour → contour

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

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

hx_clip_contours: input → output

*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):

▸ hx_clip_contours: knob a sweep (docs site)

Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):

▸ hx_clip_contours: knob b sweep (docs site)

Stages (the ops that come before → this op, left to right):

▸ hx_clip_contours: stages (docs site)

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

▸ hx_clip_contours: other inputs (docs site)

Usage

Clip contours to the image domain (a rectangle keeping the central margins a/b), dropping out-of-range points.

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

contour dict の各 contour について、画像の内側に取った矩形 `my <= row <= H-1-my、mx <= col <= W-1-mx`

に入る点だけを残し、1 点も残らない contour は捨てて返す。

• `a → 上下の余白 my = a*0.4*H`(0〜高さの 40%)。

• `b → 左右の余白 mx = b*0.4*W(0〜幅の 40%)。a=b=0 なら画像範囲 [0, H-1] × [0, W-1]` でのクリップ。

点を間引くだけで contour は分割しないため、矩形外を通って戻ってくる contour は残った点どうしが直接つながった

形(ジャンプ)になる。分割が要るなら後段で `hx_split_contours`。中心からの割合で切る類似 op に

`hx_crop_contours(中心基準の幅・高さ指定)。線長で足切りする xg_clip_contours` とは別物。

Detailed usage guide

• gallery2d_halcon_ext 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.

Try it in Studio

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_clip_contours 0.50 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.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 (`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).*

hx_clip_contours — 2D halcon_ext op