xcv_orb_count — 2D `features` op

• Data kinds: image → feature

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

Usage

Number of keypoints detected by OpenCV's ORB (Oriented FAST and Rotated BRIEF).

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

`cv2.ORB_create` で検出のみ行い(記述子は計算しない)、検出できた

キーポイント数を返す(feature 出力)。`xsk_orb_count`(skimage 版)

と同じ発想の別実装で、検出器の実装が異なるため件数が一致するとは

限らない。

`a が要求する最大特徴点数 nfeatures` を 50〜500 の範囲で振る

(上限であり、実際の検出数は画像内容に依存してそれより少なくなる)。

`b` は未使用。

Detailed usage guide

• gallery2d_features 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_features — py -3.11 examples/gallery2d_features.py

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

identity

Same category (`features`)

blob_count · area_frac · count_contours · total_length · vol_count · sk_euler · sk_entropy_feat · sk_blur_effect

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

xcv_orb_count — 2D features op