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

*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).*
Pillow's edge detection filter. Enhances edges using the fixed kernel (Laplacian-type) of `PIL.ImageFilter.FIND_EDGES`.
> The detailed description below is the original text — the summary and the headings are translated.
a, b は未使用(固定カーネル)。`xpil_contour` と似た系統だが係数が異なり、輪郭より生のエッジ強度に近い出力になる。
• gallery2d_edges 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.
xpil_find_edges 0.40 0.50
▸ Load this pipeline · Load & run
• gallery2d_edges — py -3.11 examples/gallery2d_edges.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
edges)sobel_mag · prewitt_mag · roberts_mag · dog · grad_dir · log · corner_response · sk_scharr
*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.