The learned demosaic was an option under Detail, off by default. It is
now how a Bayer raw is developed: on by default at full strength on
every device — which hardware runs it is the inference engine's choice
— and first in the Adjust panel, since it decides what every control
below is applied to.
Strength (0-100, default 100) replaces Keep grain: grain = 100 -
strength, the same luminance-only blend, so moving it is one GPU pass
and never a re-run. 0.21.0's sidecars stored grain; it is still read,
as the inverse, and never written.
With it on for every photograph, the result is now kept on disk
(denoise.md §7.1, §12): the network's output as half floats, keyed on
a SHA-256 of the file's bytes and the model, oldest first past a 5 GB
budget, beside the inference engine's cache. A reopened photograph and
an export of one already developed read it back instead of running the
network again; a damaged entry is a miss.
The grain blend replaces the Amount of §7.2, and why its objection to a
blend does not hold for brightness alone; the Hexagon is out (int8 -6 to
-9 dB); §11 holds the data, the noise model taken from the library, the
model, the validation table, the blind estimate's reach and the speed.
A design draft for the learned stage outstanding.md §3 lists as missing:
a joint demosaic-and-denoise network that runs on the mosaic, in the
slot architecture.md §5.2 reserves for it, with its result kept as a
cache rather than a new file in the library. It covers the model and
tiling, synthetic training pairs from the library and a per-body noise
calibration, evaluation on real pairs, the Amount control, speed on the
tablet, X-Trans, and the decisions still open. Nothing in it is built;
figures marked "estimate" wait for the measurements that replace them.
dtourolle