Victor KuznetsovandClaude Opus 5 4855586834 Halve decoder memory with strip processing and a raveled Haar pass ...

Each Haar pass is one flat pywt.downcoef call over a raveled strip instead of
pywt.dwt(..., axis=1)[0], and the plane is walked in strips so no full-plane
float64 intermediate exists. Exact only while the last axis is even, so
_approximation raises on an odd width rather than returning wrong bits, and
TestRaveledHaarPass pins both that raise and the downcoef/dwt equivalence a
pywt upgrade could take away.

Drops the block constructor knob: the fold chains are written for 4, nothing
ever passed another value, and a knob that silently decodes wrong is worse
than no knob.

Peak RSS 111 MB to 21 MB on a 4.3 MP image; the decoder itself 0.011s to
0.007s, which is only 0.4% of identify() now that it is under 2% of the run.
Output bits and detector verdicts over 200 sampled data/ images, two
synthesized carriers and eight degenerate shapes are byte-identical to the
pre-vectorization decoder.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

2026-08-13 13:33:34 -07:00

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remove_ai_watermarks

Halve decoder memory with strip processing and a raveled Haar pass

2026-08-13 13:33:34 -07:00