features op• Data kinds: image → feature
• Call: fullseye.apply(img, "cv_hough_lines", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: hough_lines (the HALCON reference is a useful guide to its meaning and parameters)
Line (line-segment) detection via the probabilistic Hough transform (a single scalar feature, OpenCV implementation). First creates an edge image with Canny, then uses a voting scheme to find sets of edge pixels arranged in a line and detects them as segments - here, only the number of detected segments is returned (0 if none).
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の hough_lines(Detect lines in edge images with the help of the Hough transform and returns it in HNF.)に相当(近似。線のパラメータではなく本数のみ)。実装は `cv2.HoughLinesP(Canny(_u8(v),50,150), 1, pi/180, threshold=int(20+40*a), minLineLength=int(10+20*b), maxLineGap=5)` —— a は投票数のしきい値(直線と認める最低票数)を 20〜60 に、b は最小線分長を 10〜30 に振る。Canny の内部しきい値(50, 150)と maxLineGap(5)は固定。
• gallery2d_features family guide
• 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.
• gallery2d_features — py -3.11 examples/gallery2d_features.py
feature as input)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.