features op• Data kinds: image → feature
• Call: fullseye.apply(img, "entropy_gray", 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 Shannon entropy of grayscale levels (computed from a 64-bin histogram and normalized by its maximum value, `log2(64)=6 bits). Represents the "spread/information content" of the gray-level distribution -- the value is larger for more uniform images and approaches 0 as the image is biased toward a single gray level. HALCON's entropy_gray` (Determine the entropy and anisotropy of images.) returns a pair of entropy and anisotropy, but this stand-in implements only the entropy.
> The detailed description below is the original text — the summary and the headings are translated.
`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.
• 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.