Adds TRACES tags to code that already satisfies a Done requirement, so coverage
reflects what exists rather than starting from zero:
AR-001 face detection, AR-005 ArcFace alignment, AR-023 calibration fit,
DP-001/DP-002 the single analysis core behind the CLI, IR-001 truth-file
emission, IR-006 the Jellyfin round trip, GR-001/GR-002 gallery build and
incremental merge, VR-001 the embedding dump, VR-002 replay through the real
nodes, VR-003 per-second scoring.
Only Done requirements are tagged. A tag on Planned work would inflate coverage
with fiction that looks plausible — the same failure family as a gate that
cannot fail, and harder to spot.
GR-005 (gallery never leaves the instance) stays untagged deliberately: it is a
prohibition satisfied by the absence of an egress path, so there is no unit that
decides it. Same shape as PR-005 in the system spec, which has no software row
for the same reason. A goal held only by prohibitions cannot be verified by
pointing at code.
Coverage 5/63 to 14/63. The three VR tags are reported as tagged-but-unexecuted
and excluded from the numerator, since their tier cannot run on the CI host —
tagging deliberately cannot raise the number on its own.
Suite still 64 cases, 3199 assertions.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
TRACES: AR-001, AR-005, AR-023, DP-001, DP-002, IR-001, IR-006, GR-001, GR-002, VR-001, VR-002, VR-003
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>
New C++ sources:
- kpn_bindings.cpp (sae_kpn): assembles the real face_tracker/identity_matcher/
scene_tracker nodes inside a Python-driven KPN network via nanobind, for
offline threshold-sweep replay against dumped embeddings (scripts/optimizer/).
- track_gallery.hpp: per-film gallery expansion — promotes a confidently-
identified track's novel-pose reference views into an in-memory annex so
later frames/tracks of that actor at similar poses are recognised, without
touching the baked gallery.
- dump_embeddings.cpp: standalone exe that runs detect→embed only (no gallery,
no matching) and dumps per-frame face embeddings + metadata to HDF5, so a
parameter sweep can replay the expensive half once and vary tracking/matching
config freely downstream.
- scene_detector.hpp / scene_detector_node.hpp: TransNetV2-based shot-boundary
detection, opt-in alongside the always-on histogram cut detector.
- camera_position_change_detector_node.hpp, embedding_dump_node.hpp: supporting
nodes for the above.
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