feat: a store's fine-tuned head, and the two-stage gate it needs

The head is now part of a store rather than a script: `finetune_identity.py --stock
stock-lopia` trains on that store's enrolled views (27 views over 7 products, 12
augmented copies each) and writes `<stock>/identity_head.pt`, which ProductGallery
loads automatically.

The first attempt exposed a trap worth recording. A discriminative head has no "none
of the above": trained with an angular margin to separate seven products, it maps
everything confidently onto those seven, including cartons it has never seen.

  raw features, threshold 0.55   home shelf 78% accepted   foreign shelves  5% accepted
  trained head, threshold 0.40   home shelf 58% accepted   foreign shelves 44% accepted

Rejection - the gallery's whole point - disappears. The fix needs no retraining: the
two mechanisms fail in opposite directions, so raw features decide *whether* to answer
(they generalise) and the head decides *what* to answer (it discriminates). Measured:
47% accepted on the home shelf, 5% on foreign ones. Lower coverage than raw-only,
which is the honest trade.

The head also needs its own threshold (0.40 against the raw 0.55): a trained head's
similarity scale is its own, and reusing the raw line rejected almost everything it
said.

175 tests pass.

Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>

recognization/code/engine.py

@@ -93,6 +93,7 @@ class EngineSettings:
     # Cosine similarity below which the gallery calls a facing unknown. Measured:
     # same-product pairs sit above 0.6, different products below 0.5.
     gallery_threshold: float = 0.55
+    gallery_head_threshold: float = 0.40
     gallery_image_size: int = 518
     imgsz: int = 640
     # 0 -> max(2, cpu_count - 2). Measured default below (see build_default_engine).
@@ -430,6 +431,7 @@ class RecognitionEngine:
             self.settings.stock_dir,
             [product["sku_id"] for product in self.catalog()],
             threshold=self.settings.gallery_threshold,
+            head_threshold=self.settings.gallery_head_threshold,
             image_size=self.settings.gallery_image_size,
         )
         try: