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])

xcv_stylization: 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

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.

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.

xcv_stylization 0.50 0.50

▸ Load this pipeline · Load & run

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