A track recognised on 318 of 385 frames was owned on none, so the truth file
named nobody while the matcher was accepting almost continuously.
The correlation discount was an annihilator rather than an attenuator. Weight
was 1 - P(same view), so once a track had one stored view every later frame of
that same face scored ~0.01 and the belief stopped moving. One observation just
over the accept threshold is logit(0.78) ~ 1.27, under the ownership bar — hence
recognised always, owned never.
Two changes, in the order they were found.
Correlated evidence is now attenuated by effective sample size,
n_eff = n / (1 + (n-1)·rho), each frame contributing the marginal gain. That has
the right shape at both ends: uncorrelated evidence accumulates linearly, and a
held pose converges on 1/rho rather than growing without bound. A constant floor
was tried first and rejected — it grows linearly forever, so a long shot could
out-argue genuinely varied evidence purely by lasting longer.
Combination is now weighted lazy-OR: P = 1 - (1-P_old)·(1-p)^w, stored as
log(1-P) so the update is additive and precision stays where it matters as P
approaches 1. Each frame is new evidence that this track is that actor, and the
belief is the probability that at least one sighting was right. It converges
faster than summing log-odds at the same effective count — 2.98 vs 2.53 after
two observations at p=0.78 — which is what a real clip needs.
Note that summing log-odds was already a correct sequential Bayesian update:
the matcher fits with prior 0.5, so logit(p) IS the per-frame log-likelihood
ratio and the running sum carries the prior forward. It was not wrong, it was
slow. What blocked ownership was the discount, not the combination rule.
Also fixes a real correctness bug: the observation count lived on the
discounter, which is shared by every track, so tracks pooled into one effective
sample and each was discounted by how many others happened to be on screen. It
is now a per-track parameter.
The registry's frame scope holds its lock for its lifetime and the mutex is not
recursive, so calling observe() inside a scope self-deadlocks. The pipeline
never does — separate nodes — but the test did, and hung rather than failing.
Documented at the call site.
Verified end to end: the same clip that produced zero actors now identifies
Bing Crosby and Dorothy Lamour with belief 0.97.
Suite: 96 cases, 6142 assertions.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
TRACES: AR-025 | SR-002
A gallery is only valid for the embedder that produced its vectors. Cosine
similarities across models are meaningless but *look* plausible, so the mistake
is silent and every measurement taken afterwards is suspect. Stamp the embedder
identity into the gallery at build; verify it at every load.
The stamp is the model file's basename plus the SHA-256 of its bytes (plus
embed_dim). The hash decides, the name explains. A name alone is a promise
rather than a fact — models get re-exported and overwritten in place under an
unchanged filename, which is exactly the case where the weights differ and
nothing else does. A hash alone is correct but unactionable in an error message.
SHA-256 is derived from the artefact, needs no registry kept current, and costs
~0.1s for a 250MB ONNX, memoised per process.
Mismatch is a hard error in every mode, with no bypass, naming both sides.
Unstamped legacy galleries warn loudly and proceed: unknown is not known-bad,
and hard-failing every pre-existing gallery would turn the check into something
people disable rather than trust. --require-gallery-stamp (or
SAE_REQUIRE_GALLERY_STAMP=1, which propagates to subprocesses) promotes that to
a hard error — the mode measurement work should run in. scripts/stamp_gallery.py
re-binds an existing gallery with no re-embedding, so "warn" is a cheap state to
leave rather than a permanent one.
Embedding dumps carry the same stamp: a replay has no live embedder, so the dump
is the embedder as far as the gallery is concerned. Derived galleries inherit
their source's stamp; --merge and the JSON gallery merge check before writing,
since one file holding two embedding spaces cannot be untangled afterwards.
Verified in: scene_analyze, scene_preview, the sae_kpn matcher binding,
replay.py, optimize.py (once per film at startup, before the first evaluation),
movienet_eval.py and both merge paths.
Stamp logic lives in src/gallery/embedder_stamp.{hpp,cpp} and its Python twin
scripts/sae_stamp.py, kept dependency-light so replay subprocesses do not pay
sae_gallery's requests/Pillow import to ask whether two models match.
Tests: 12 new cases in test_gallery_store.cpp covering the comparison logic,
both round trips, and the SHA-256 vectors that guarantee the C++ and hashlib
stamps agree. No ONNX or GPU required.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Gallery format switches from JSON to HDF5 exclusively (JSON read-only kept for
back-compat): save_gallery always writes HDF5, and the fitted Platt-sigmoid
calibration (a, b, valid, hash) is now embedded directly in the gallery file
instead of a sidecar .calib_cache.json — identity_matcher reads it from the
loaded gallery and writes back only when the embeddings actually changed
(hash mismatch), skipping the O(n^2) refit otherwise.
Also includes: TensorRT inference backend support (ort_backend.cpp,
trt_backend.cpp), gemm_backend improvements, TransNetV2-based scene-boundary
detection wired through frame_source/face_tracker/main, and CMake build
target updates for the new sources.
Bumps the KPN submodule to feature/persistent-pipeline-reuse (push_blocking
backpressure, node_ptr/node_stats introspection, ObjectVariantNodeWrapper for
stateful functors) — needed by the optimizer's sae_kpn Python bindings.
dtourolleandClaude Opus 5