features op• Data kinds: image → feature
• Call: fullseye.apply(img, "sk_entropy_feat", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: entropy_gray (the HALCON reference is a useful guide to its meaning and parameters)
*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).*
Shannon entropy of the whole image (a single scalar feature). Summarizes the spread/information content of the brightness histogram in one number -- a higher value indicates the brightness distribution is more evenly spread out (more information / richer contrast).
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の entropy_gray(Determine the entropy and anisotropy of images.)に相当(近似。異方性は計算しない)。実装は `measure.shannon_entropy(v)`(既定の底 2、単位はビット)。a, b は未使用。
• 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.
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.
sk_entropy_feat 0.50 0.50
▸ Load this pipeline · Load & run
• 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_blur_effect · cv_cc_count
*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.