region op• Data kinds: region → feature
• Call: fullseye.apply(img, "r2_runlength_features", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: runlength_features (the HALCON reference is a useful guide to its meaning and parameters)
*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.*
*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
Stages (the ops that come before → this op, left to right):
▸ r2_runlength_features: stages (docs site)
Region -> feature: mean length of horizontal foreground runs.
Scans each row of the foreground mask (> 0.5) from the left, collects the lengths of all runs of consecutive foreground pixels (horizontal runs), and returns their mean (in pixels) as 1 scalar. Run starts/ends are detected from the differences of each row zero-padded per row. a, b are unused.
The return value is a numpy.float64. 0.0 if there is no foreground. The unit is pixels, and it is not normalised by the image size (for the same shape at 2 times the resolution, the value is also 2 times). Vertical runs are not counted (an orientation-dependent feature whose value changes greatly between vertical and horizontal stripes). Regions with many thin horizontal lines give large values, and lots of dot-like noise brings it close to 1. For the variance and entropy of run lengths see r3_runlength_distribution; for removing short runs, r3_eliminate_runs. Since it is a feature, no image op should follow it.
• gallery2d_region 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.
threshold 0.50 0.50 r2_runlength_features 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_region — py -3.11 examples/gallery2d_region.py
feature as input)region)reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small · invert_region
*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.