feat: no fixed cap on faces per frame

AR-003 — max_faces defaults to 0, meaning no cap. A fixed cap discards the
SMALLEST faces first, which are exactly the background cast X-Ray still credits
with scene membership, so the pipeline was systematically losing the people it
is supposed to find in crowded scenes.

This is only safe now that AR-004 landed. Previously an uncapped frame would
have pushed more work into channels that dropped on overflow, trading a visible
cap for silent loss. With backpressure the producer slows instead, so per-frame
cost is contained rather than discarded.

The matcher's kMaxFaces used to throw above 32, which made it an accidental
second cap. It sizes the similarity engine's preallocated buffer, so it bounds
memory rather than face count — the frame is now scored in batches of that size.
Memory stays bounded; faces do not.

Largest-first ordering is kept even without the cap, and the comment now says
why: the Hungarian solver tie-breaks on index order, so that ordering is
load-bearing for the replay determinism test rather than a leftover of the cap.

Verified end to end on a real clip: identical output to the capped run (385
frames, 693 faces), which is expected since that footage peaks at 4 faces per
frame — the point is the absence of a regression. The committed fixtures remain
byte-identical and valid.

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

TRACES: AR-003 | SR-002

src/face_embedder_engine.hpp

@@ -112,6 +112,17 @@ public:
         return res;
     }
 
+    // ── Stage accessors ──────────────────────────────────────────────────────
+    // embed_mat() above is the whole detect→align→embed chain, which is the
+    // right entry point for embedding a gallery image. Studies that need to
+    // intervene between the stages — swapping the landmark source, degrading a
+    // crop before it reaches the embedder — drive these instead, so they still
+    // exercise the shipped detector, alignment and embedder rather than a
+    // re-implementation of them.
+    std::vector<DetectedFace> detect(const cv::Mat& img) { return detector_->detect(img); }
+
+    Embedding embed_crop(const cv::Mat& crop) { return embedder_->embed_one(crop); }
+
 private:
     std::unique_ptr<IFaceDetector>   detector_;
     std::unique_ptr<IFaceEmbedder>   embedder_;