Cut pipeline cost: seg-reuse, unified bf16 knob, eager mimalloc purge

Three optimizations from profiling the cross-check-dominated pipeline
(9700X CPU, all pilot-validated on TestImage3/FixImage1):

- Reuse the cross-check HR-matting@2048 forward as the segmentation mask
  (cross_check.reuse_as_seg, default ON; --no-cross-check-as-seg to opt
  out). Skips the BiRefNet@1024 load+forward entirely: ~66s -> ~45s,
  one less 0.9GB model. Trimap 99.8% identical, no structural change.

- --precision bf16 now fans out to all three models: ViTMatte keeps its
  weight cast; both BiRefNets run their forward under autocast with a
  dispatcher-level AutocastCPU fp32 shim for torchvision::deform_conv2d
  (no bf16 CPU kernel, no autocast wrapper upstream). Shared hardware
  gate in bgfilter/precision.py falls back to fp32 off native-bf16
  hardware. TestImage3: 51.9s -> 33.1s; alpha diff max 0.15, none >0.25.

- MIMALLOC_PURGE_DELAY=0 (bgfilter/__init__.py, before torch loads):
  Windows torch's bundled mimalloc lazily retains ~10GB of freed
  BiRefNet activations, stacking under ViTMatte's attention peak.
  2048x2048 bf16: peak 25.2 -> 21.4GB and slightly faster (73 -> 63s).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

configs/default.yaml

@@ -8,8 +8,10 @@ model:
   device: cpu
   matting_method: vitmatte
   fallback_to_chroma_alpha: false
-  # "bf16" halves ViTMatte activation memory (visually identical alpha); needs
-  # bf16-capable hardware (modern GPU / AVX512-BF16 CPU), else falls back to fp32.
+  # "bf16" halves ViTMatte activation memory and is ~3x faster on native-bf16
+  # CPUs (visually identical alpha); needs bf16-capable hardware (modern GPU /
+  # AVX512-BF16 CPU), else falls back to fp32. --precision bf16 sets bf16 here
+  # AND on the BiRefNet models below in one go.
   precision: fp32
 
 segmentation:
@@ -20,6 +22,9 @@ segmentation:
   model_name: ZhengPeng7/BiRefNet  # matches backend; --seg-backend anime-seg auto-selects skytnt/anime-seg
   device: cpu
   input_size: 1024
+  # BiRefNet forward precision: "bf16" runs via autocast (~1.4x on native-bf16
+  # CPUs, visually identical), else falls back to fp32. anime-seg ignores this.
+  precision: fp32
 
 trimap:
   sure_bg_threshold: 0.92
@@ -59,6 +64,15 @@ cross_check:
   enabled: true
   model_name: ZhengPeng7/BiRefNet_HR-matting
   input_size: 2048
+  # Reuse the cross-check forward as the seg mask: one HR-matting inference
+  # drives both trimap topology and the veto, skipping the primary seg model
+  # (saves its ~9s forward + ~0.9 GB load; CPU pipeline ~66s -> ~45s). Pilot:
+  # trimap 99.8% identical, no structural change (fingers/wisps/bowstring OK).
+  # Disable with --no-cross-check-as-seg. No effect when cross_check is off.
+  reuse_as_seg: true
+  # Cross-check forward precision, same semantics as segmentation.precision
+  # (bf16 via autocast: 2048 pass ~35s -> ~26s on a native-bf16 CPU).
+  precision: fp32
   proj_min: 3.0        # bg-hue projection above which a pixel is suspect
   l_min: 45.0          # Lab lightness below which a pixel is exempt (dark hair)
   feather_sigma: 2.0   # zone-boundary feather, px