Make Best one network, and retire Medium and the mixture

Best was a mixture of two experts and a gate, 110 GMAC a megapixel;
Medium a single network at 48 that was softer on real edges. fb-combo
(darkroom-denoise, 20 000 steps from fb-edges2, taught by the mixture
with a quarter of its crops from the edge-rich parts of the frames) is
Medium's shape and holds the mixture's edges on real photographs:
edge PSNR within 0.04-0.06 dB at ISO 1600/6400/25600, more sharpness
kept at all three, the chart's edge 0.89 photosites wide against 0.82.
It is 0.27 dB short on smooth areas at ISO 25600. It becomes Best, and
the methods are Bilinear, Fast and Best.

Saved edits keep their numbers: 2, which was Medium, is now Best, and
3, which was Best, is past the end and reads as the default, Best.
The network ships as mosaic-hq, a new name: the result cache keys a
model by name and size, and this one is byte for byte the old Medium's
size. Its tablet form (A16W16) lost 0.00 dB in simulated QDQ at every
ISO and at most 0.09 dB across the noise bracket.

models/LICENCE.md

@@ -134,10 +134,9 @@ declined, and the InsightFace grant of D13).
 
 | File | Source | Trained on | Used by |
 |---|---|---|---|
-| `denoise/mosaic-best-1408.onnx` | trained in the `darkroom-denoise` repository (2026-10-04, run `final`, 30 000 steps, from the experts of runs `m2` and `edges-100`) | 1,701 of the maintainer's own base-ISO raws and 6,000 synthetic scenes the repository draws itself, with the Canon EOS 6D's measured noise added | the learned demosaic and denoise, Best (FR-DEV-3g) |
-| `denoise/mosaic-medium-1408.onnx` | distilled from `final` in the same repository (2026-10-04, run `student-m`, 20 000 steps, from `m2`) | the same | Medium |
+| `denoise/mosaic-hq-1408.onnx` | trained in the `darkroom-denoise` repository (2026-10-07, run `fb-combo`, 20 000 steps, from `fb-edges2` ← `student-m`), taught by the mixture of experts that was Best until 0.24 (run `final`) at a half share, with 10 % drawn scenes and 25 % crops from the edge-rich parts of the training frames | 1,701 of the maintainer's own base-ISO raws and 6,000 synthetic scenes the repository draws itself, with the Canon EOS 6D's measured noise added | the learned demosaic and denoise, Best (FR-DEV-3g) |
 | `denoise/mosaic-fast-1408.onnx` | distilled from `final` (2026-10-04, run `student-s`, 30 000 steps, from scratch) | the same | Fast |
-| `denoise/mosaic-{best,medium,fast}.onnx` | the three networks above, re-exported with any height and width by `tools/export_whole.py` in the same repository (2026-10-06) from the same checkpoints; identical to the 1408 files at 1408² | the same | the same methods, a whole frame at a time on a GPU (denoise.md §14) |
+| `denoise/mosaic-{hq,fast}.onnx` | the two networks above with any height and width, by `tools/export_whole.py` in the same repository from the same checkpoints; identical to the 1408 files at 1408² | the same | the same methods, a whole frame at a time on a GPU (denoise.md §14) |
 
 U-Nets of plain 3×3 convolutions, ReLU, strided and transposed
 convolutions and additive skips — no third-party architecture code or