grad_dir — 2D `edges` op

• Data kinds: image → image

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

Usage

Returns the gradient direction (edge orientation) as an image. No corresponding HALCON op has been specified (unique to fullseye).

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

`a, b は未使用。Sobel 応答から atan2(Gy, Gx) で角度（-π〜π）を求め、[0,1] へ線形に写す。0 と 1 はどちらも同じ角度（-π≡π`）に対応する周期量である点に注意——連続的に変化する向きでも出力が 0 と 1 の間で不連続にジャンプし得る。平坦な領域では勾配がほぼ 0 で方向が不定になり、ノイズの影響を受けやすい。

Detailed usage guide

• gallery2d_edges 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_edges — py -3.11 examples/gallery2d_edges.py

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

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (`edges`)

sobel_mag · prewitt_mag · roberts_mag · dog · log · corner_response · sk_scharr · sk_farid

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

grad_dir — 2D edges op