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])

grad_dir: 入力 → 出力

*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).*

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.

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.

grad_dir 0.40 0.50

▸ Load this pipeline · Load & run

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