edges op• Data kinds: image → image
• Call: fullseye.apply(img, "xsk2_inv_gauss_grad", 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 actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ xsk2_inv_gauss_grad: knob a sweep (docs site)
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ xsk2_inv_gauss_grad: other inputs (docs site)
*No colour (H,W,3) input is shown: this op treats the colour channel as a third spatial axis (it crosses channels). Call it per channel.*
Inverse Gaussian gradient image (the edge-stopping function for Active Contour / GAC). Calls skimage.segmentation.inverse_gaussian_gradient.
a sweeps the edge sensitivity alpha (50 + 150*a, range 50–200; the larger, the more even weak edges lower the stopping-function value = the more easily it stops). b is unused. The value is small (close to 0) at edges and close to 1 in flat areas —— an output intended as the edge-stopping term in geodesic active contour style segmentation; viewed directly as an edge image, its brightness looks inverted compared with ordinary edge detection.
Border handling: replicate the edge pixel (nearest neighbour) (measured; tools/impl2/border_probe.py).
Blank frame (measured): feeding an image of uniform brightness makes every pixel foreground (1), regardless of the brightness. A frame that is blown out, occluded, or simply has no subject comes back as “100 % defective”, so test for uniformity upstream and reject such frames.
• 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.
xsk2_inv_gauss_grad 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 · edge_transition_width · grad_dir · log · corner_response
*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.