feat(quality): score every face on sharpness and alignment before it is evidence

Every embedding now carries the quality of the input it came from. Both
axes fall out of the AR-005 warp for free: crop_sharpness() is the
normalised Laplacian variance over the aligned 112x112, so contrast and
size cannot leak into it, and the alignment residual is the part of the
landmark deformation a similarity transform cannot explain, so in-plane
roll reads as zero and foreshortening does not.

Carried, not consumed. Nothing discounts or thresholds on either number
yet -- that is AR-030 and VR-012, and the knee has to be located against
recorded data before a gate is chosen. What this change buys is that the
data exists to locate it with.

No face is admitted unscored: the -1 sentinel is preserved rather than
clamped, and a degenerate landmark fit is counted rather than silently
dropped.

Takes the VR-001 dump to schema_version 2. The bump is not for readers,
which check for the datasets by name and replay a v1 dump unchanged; it
is so a consumer can tell "never scored" from "scored zero", which is
not recoverable from the arrays afterwards.

TRACES: AR-028, AR-029, AR-030 | VR-001 | SR-002

scripts/optimizer/replay.py

@@ -63,6 +63,14 @@ def load_frames(dump_path: str, min_conf: float = 0.0):
         bbox = f["faces/bbox"][:]
         lmk  = f["faces/landmarks"][:]
         conf = f["faces/confidence"][:]
+        # TRACES: AR-028 | SR-002
+        # The quality vector, present from schema v2. A v1 dump predates AR-028
+        # and simply has no such dataset — read as absent, never as a default,
+        # so a face from an old dump stays at the C++ -1 "unscored" sentinel
+        # rather than acquiring a fabricated sharpness of 0 (which is a real
+        # value on this axis, meaning a featureless crop).
+        qual = {k: f[f"faces/{k}"][:] for k in ("sharpness", "alignment_residual")
+                if f"faces/{k}" in f}
         movie = f.attrs.get("movie", "")
         fps   = float(f.attrs.get("sample_fps", 1.0))
 
@@ -81,6 +89,8 @@ def load_frames(dump_path: str, min_conf: float = 0.0):
                 "landmarks":  np.ascontiguousarray(lmk[keep][sel],  dtype=np.float32),
                 "confidence": np.ascontiguousarray(c[sel],          dtype=np.float32),
                 "embeddings": np.ascontiguousarray(emb[keep][sel],  dtype=np.float32),
+                **{k: np.ascontiguousarray(v[keep][sel], dtype=np.float32)
+                   for k, v in qual.items()},
             })
         else:
             frames.append({
@@ -90,6 +100,8 @@ def load_frames(dump_path: str, min_conf: float = 0.0):
                 "landmarks":  np.ascontiguousarray(lmk[keep],  dtype=np.float32),
                 "confidence": c,
                 "embeddings": np.ascontiguousarray(emb[keep],  dtype=np.float32),
+                **{k: np.ascontiguousarray(v[keep], dtype=np.float32)
+                   for k, v in qual.items()},
             })
     last_ts = float(ts[-1]) if len(ts) else 0.0
     frames.append({"timestamp_sec": last_ts, "eof": True})