Default reuse-as-seg OFF; default expandable_segments on Linux/WSL

Two default flips for server-edition:

1. cross_check.reuse_as_seg now defaults to false (settings + default.yaml + CLI help): the dedicated segmenter keeps its own forward and the cross-check veto stays an independent second signal. The reuse remains available via --cross-check-as-seg / config; measured cost of off vs on: ~20 s/image on CPU, +0.1-0.25 s and +0.9-1.3 GB VRAM on GPU (13.3 vs 12.0 GB reserved under expandable segments -- still fits a 16 GB card).

2. bgfilter/__init__.py defaults PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True on non-Windows platforms, before torch loads (setdefault: an explicit env value wins; native Windows is excluded because torch warns and ignores it there). Measured: reserved 15.3 -> 12.0 GB and ~10% faster on the RTX 5070 Ti; no effect on CPU-only runs.

README/DEPLOY(_ZH) synced: reuse documented as opt-in, GPU profile numbers updated for both reuse states, perf table labeled with the config it was measured under.

Verified: defaults resolve off/set as intended on Windows and WSL; explicit PYTORCH_CUDA_ALLOC_CONF override wins.

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

configs/default.yaml

@@ -74,8 +74,9 @@ cross_check:
   # trimap 99.8% identical, no structural change (fingers/wisps/bowstring OK).
   # Only applies to the birefnet backend (same-family swap); anime-seg keeps
   # its own forward, with the cross-check running independently on top.
-  # Disable with --no-cross-check-as-seg. No effect when cross_check is off.
-  reuse_as_seg: true
+  # Default OFF (server-edition): the dedicated segmenter keeps its own forward
+  # and the veto stays independent; enable with --cross-check-as-seg.
+  reuse_as_seg: false
   # Cross-check forward precision, same semantics as segmentation.precision
   # (bf16 via autocast: 2048 pass ~35s -> ~26s on a native-bf16 CPU).
   precision: fp32