xcv3_agast_count — 2D `features` op

• Data kinds: image → feature

• Call: fullseye.apply(img, "xcv3_agast_count", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

AGAST keypoint count (OpenCV AGAST detector, an adaptive tree-structure version of FAST). Returns the number of detected keypoints as a feature.

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

`a は検出閾値(int(5+40*a) で 5〜45。高いほど検出数が減る)を振る。b は未使用。実装注記: cv2 5.0.0 で AgastFeatureDetector_create が cv2.xfeatures2d に移動したため、両方の場所を getattr` で試す互換コードになっている(xcv3_brisk_count と同じ事情)。

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).*

xcv3_agast_count — 2D features op