xcv_stylization — 2D `artistic` op

• Data kinds: image → image

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

Usage

OpenCV's stylization (painterly/cartoon-like non-photorealistic rendering).

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

エッジ保存平滑化を使って細部を均しつつ主要な輪郭を残し、平坦な色面と

目立つ輪郭からなるイラスト調の画像を作る(内部で 3ch に変換して処理し、

結果をグレースケールへ戻す)。

`a が空間方向の平滑化範囲 sigma_s` を 20〜120 で振る(大きいほど

広い範囲を均す)。`b が色(輝度)差の許容範囲 sigma_r` を 0.1〜0.5

で振る(大きいほどエッジをまたいで均しやすくなり、平坦化が強まる)。

Detailed usage guide

• gallery2d_color_artistic 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_color_artistic — py -3.11 examples/gallery2d_color_artistic.py

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

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

Same category (`artistic`)

xcv_pencil_sketch · xpil_emboss

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

xcv_stylization — 2D artistic op