illusion op• Data kinds: none → table (an op determined by its arguments alone — it takes no image or data input)
• Call: import fullseye as fs; fs.ledger.illusion_ground_truth(name: 'str' = '') -> 'dict' (to call the implementation directly, import illusion; illusion.illusion_ground_truth(name: 'str' = '') -> 'dict'; from the registry, opsgenerative.get("illusion_ground_truth"))
Returns, as a table, the exact invariants that the illusions preserve (empty name gives all of them).
★This is the core of the family. Hand out just the figure and it ends with "how pretty", but when the ground truth comes out together with the figure, you can score the side that measures. Every value in the return value is "the value it should be", not a measured value (measuring is the caller's job).
• 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.
• poc_calipers_under_illusion — py -3.11 examples/poc_calipers_under_illusion.py
table as input)perpetual_step · perpetual_render
illusion)illusion_cafe_wall · illusion_muller_lyer · illusion_ponzo · illusion_zollner · illusion_poggendorff · illusion_fraser_spiral · illusion_ebbinghaus · illusion_kanizsa
*Provenance: illusion.py — GENERATIVE 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.