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])

xcv3_agast_count: 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

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.

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.

xcv3_agast_count 0.50 0.50

▸ Load this pipeline · Load & run

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