xcv3_sift_count — 2D features op

• Data kinds: image → feature

• Call: fullseye.apply(img, "xcv3_sift_count", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

> This operator's description has not been translated yet. The original text follows as it is.

SIFT 特徴点数(OpenCV `cv2.SIFT_create().detect`)。画像から検出されたスケール不変特徴点(SIFT keypoints)の個数を feature として返す —— テクスチャの複雑さ/マッチングに使える特徴点の豊富さの指標になる。

`a は検出上限数 nfeatures(int(50+450*a) で 50〜500)を振る —— 上限に達するまでは実際の検出数がそのまま返るので、上限に張り付いていないか確認が要る。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).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.