Ship the border filler trained against MI-GAN's own discriminator: texture in the deep bands, level with stock on LPIPS

docs/panorama.md

@@ -538,9 +538,24 @@ each loss weighting did, and the two runs abandoned (blur under L1 in
 the hole; a brick pattern under a strong adversarial term against a
 discriminator that had not learned) — is `runs/` in `darkroom-infill`.
 
-**What is still wrong.** The ground fill is softer than its context —
+**Second model, the same day.** The morning's fill was soft in the deep
-texture, not structure, is what a night on a laptop GPU could not finish.
+ground bands. The afternoon's run trained the generator against MI-GAN's
-The levers, in order: a discriminator that learns (a pretrained one —
+own pretrained discriminator (non-saturating loss, lazy R1, feature
-MI-GAN's own from the unfused checkpoint — instead of a PatchGAN from
+matching), with fresh noise inputs while training and flip/translation
-scratch), feature matching, and more steps at 512. FR-MRG-4's
+augmentation of the discriminator's input — both needed, or the generator
-*experimental* stays.
+settles into a periodic texture the discriminator cannot see. The shipped
+weights (step 4 750 of `runs/border-v6`) are level with the stock model on
+LPIPS (edge 0.125 / corner 0.187 against 0.121 / 0.183) while keeping the
+PSNR gain (edge 18.0 / corner 15.7 against 16.9 / 14.6). On the fixture
+the ground bands now carry texture at the right tone; at 1:1 a faint
+regular hatch is visible in the deepest part.
+
+**What is still wrong.** The hatch, and any deep textured void the
+generator must invent. The better answer for those is not generative:
+seed the void with the picture's own texture in hexagonal cells, let the
+discriminator rank the candidates, and let the generator heal only the
+gaps between cells — built and measured in `darkroom-infill`
+(`infill/hexfill.py`), the most convincing scree corner produced so far,
+and the next thing to port into `dr_pano::fill` (it needs the
+discriminator as a second model, ~80 MB fp16). FR-MRG-4's *experimental*
+stays.

models/LICENCE.md

@@ -104,7 +104,7 @@ the dataset licence restricts models trained on it by name.
 
 | File | Source | Trained on | Used by |
 |---|---|---|---|
-| `inpaint/migan-512.onnx` | `migan_512_places2.pt` from `https://github.com/Picsart-AI-Research/MI-GAN` (Sargsyan et al., ICCV 2023), **fine-tuned** in the `darkroom-infill` repository (2026-09-20) | Places2 by the authors, then ~7 400 of the maintainer's own photographs with border-shaped voids | the panorama border fill (FR-MRG-4) |
+| `inpaint/migan-512.onnx` | `migan_512_places2.pt` from `https://github.com/Picsart-AI-Research/MI-GAN` (Sargsyan et al., ICCV 2023), **fine-tuned** in the `darkroom-infill` repository (2026-09-20, second model that evening: trained against MI-GAN's own discriminator) | Places2 by the authors, then ~7 400 of the maintainer's own photographs with border-shaped voids | the panorama border fill (FR-MRG-4) |
 
 The bare 512 generator at a fixed `1×4×512×512`, six operator types; the
 tiling, the context and the blend are Rust (`dr_pano::fill`). Since