macro_binarize — 2D macro op

• Data kinds: image → image

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

macro_binarize: input → output

*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).*

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

▸ macro_binarize: 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.*

Usage

A fixed pipeline discovered by evolutionary search: bilateral(a=0.06,b=0.89) → unsharp(a=0.51,b=0.34) → bilateral(a=0.04,b=0.24) → lowpass(a=0.75,b=0.59) → gopen(a=0.38,b=1.00) → unsharp(a=0.78,b=0.68) (6 stages that alternate smoothing and unsharp masking, clean up with a lowpass and grayscale opening, then sharpen once more).

a, b are frozen and unused. On the binarize task (IoU) it reaches 0.75 on the locked holdout, beating the hand-made baseline of 0.62, but while train is 0.91 / holdout 0.95, locked_holdout drops to 0.75 -- the per-split differences are stated without hiding them (feedback_benchmark_honest_disclosure). There is no single HALCON operator corresponding to it.

Knobs (measured): sweeping a from 0 to 1 does not change the output (measured on five different inputs).

Detailed usage guide

• gallery2d_physics_alife_3d family guide

References (sample data, literature)

• 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.

Try it in Studio

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.

macro_binarize 0.50 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_physics_alife_3d — py -3.11 examples/gallery2d_physics_alife_3d.py

Ops the type connects to (they accept image as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (macro)

macro_denoise · macro_edge · macro_vol_denoise


*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.