Calibrate the int8 detectors on library proxies, in chunks, and measure them

The first int8 files found no faces at all, and for two reasons the
tool now guards against. The calibration set was landscape photographs
with no faces in them, so the score head's ranges had never seen the
face regime; the set is now proxies from the library itself. And ONNX
Runtime's strided and moving-average calibration modes both degrade
these graphs measurably (a quarter of the faces at eight images, none
at ninety-six), while driving the calibrator in chunks by hand gives
ranges identical to a single pass — so the tool does that, four images
at a time, and feeds quantize_static through its range cache.

Measured against f32 over 400 proxies (docs/inference.md §10.1): the
10g form finds every face above 32 px the f32 form finds; 500m and
2.5g find 96%, and what they lose sits at a median confidence of 0.52
against the 0.50 threshold. Shipped with the number on record.

The Android unpack list gains the three int8 files; without that the
tablet never saw them. D13's runtime half records the reopening.

docs/architecture.md

@@ -1236,7 +1236,7 @@ Full rationale in [requirements.md §8](requirements.md). Summary:
 | D10 | Single adaptive interface | Decided |
 | D11 | Product positioning | Decided |
 | D12 | Scope versus pace | **Open** |
-| D13 | Face inference runtime and model licensing | **Runtime answered**, licensing open |
+| D13 | Face inference runtime and model licensing | **Runtime answered**, reopened for per-device backends (docs/inference.md); licensing open |
 | D14 | Segmentation source for local masking | Decided — arm C (docs/segmentation.md §14) |
 | D15 | Target devices — 12-inch tablet and desktop, no phone | Decided (requirements D15) |