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
The tool's defaults already exclude `vendor`, which covers the submodule at
scripts/vendor/jray-project. Setting the key explicitly is a trap worth
documenting: it REPLACES the defaults rather than extending them, and matching
is on path components rather than prefixes — so ["scripts/vendor"] matches
nothing while silently dropping __pycache__, node_modules, build and the rest.
Verified: the submodule's source is not scanned, and the only vendored path in
the report is the system spec it reads for PR/SR orphan checking.
Coverage after the merges: 5/63, 0 orphans. Every tag names a real requirement,
and nothing claims a requirement that is still Planned.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
GR-004 — a gallery built with one embedding model is meaningless with another.
Cosine similarities across models are garbage but look entirely plausible, so
this fails silently and expensively; every measurement taken against a
mismatched pair would have been quietly wrong.
The stamp is the model basename plus a SHA-256 of its bytes, with embed_dim as
a cheap extra guard. The hash decides and the name explains, because neither
works alone: a name is a promise rather than a fact — models get re-exported in
place under an unchanged filename, which is exactly the case where the weights
differ and nothing else does — while a bare hash mismatch tells an operator
nothing actionable.
Mismatch is fatal in every mode with no bypass. Unstamped only warns, because
unstamped is unknown rather than known-bad, and an error firing on every legacy
gallery trains people to reach for the bypass reflexively. scripts/stamp_gallery.py
binds an existing gallery in place with no re-embedding, so the warning is a
migration step rather than a permanent state; --require-gallery-stamp promotes
it to an error once a site has migrated.
Two gaps found that would have defeated the requirement outright:
- Embedding dumps carried no stamp, so a replay — which has no live embedder —
had nothing to check the gallery against. Dumps now carry embedder_model and
embedder_sha256 as root attributes. Additive; schema_version stays 1. This is
the same gap the dump audit identified independently.
- --merge produced one file holding two embedding spaces, which no later check
can untangle. Merge paths now verify before writing.
The stamp also survives identity_matcher's calibration write-back, which would
otherwise have stripped it on the first analysis run — the check would have
worked exactly once.
Conflicts resolved additively: both branches appended a source to sae_gallery
and to the test target, and both edited the GR-004 register row.
Merged suite: 64 cases, 3199 assertions, passing on CPU with no GPU.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
TRACES: GR-004, VR-001 | SR-001
Committed rather than ignored, matching house precedent: coverage becomes
visible to anyone browsing the repo, and its movement over time is real history
worth having in the log.
Stamp is model basename + SHA-256 + embed_dim: the hash decides, the name
explains. A name alone is a promise rather than a fact — models get re-exported
in place under an unchanged filename, which is exactly the case where weights
differ and nothing else does. A hash alone is unactionable in an error message.
Mismatch is fatal in every mode with no bypass. Unstamped only warns, because
unstamped is unknown rather than known-bad, and an error that fires on every
legacy gallery trains people to reach for the bypass. A migration script binds
existing galleries in place with no re-embedding, so warn is not permanent.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
TRACES: GR-004 | SR-001
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>
Adds the build/deploy story that was missing: containerised builder images for
cpu / cuda / rocm, and release jobs producing prebuilt binaries so a first
install need not compile.
States explicitly that this does not reverse DP-005. That requirement rejects
Docker as a *runtime* — GPU passthrough is fragile and exists only because of
the container. Using it as a *build* environment is the opposite case, and lets
one machine produce binaries for backends it cannot itself run. Build in a
container, run natively.
Two things deliberately cannot ship, and the installer must not imply otherwise:
TensorRT engines are GPU-architecture and TRT-version specific, so
build_trt_engines.sh still runs on the target; and models are ~725 MB in LFS,
orthogonal to the binary.
The base image is chosen by the OLDEST glibc to be supported, not by
convenience — a binary built in a container runs against the host's glibc, and
getting this wrong fails at load with GLIBC_2.xx not found. Accelerator runtimes
have the same shape of problem, so each image documents its compatible
CUDA/ROCm range and the installer checks it rather than discovering a mismatch
at first inference.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
TRACES: DP-005, DP-007, DP-008 | PR-004
Corrections from the dump audit and the completed agent work:
- AR-010 is not started, not in progress: is_scene_boundary has no producer
anywhere. SceneDetectorFunc is a terminal sink writing scenes.json and never
annotates the frame, so the field is permanently false and the dump column a
constant 0. A replay test of the frame-dependent track_alpha would pass
vacuously — the worst failure mode for a verification gate.
- T1 (functor-level) becomes the primary verification tier, not T2. KPN node
functors are plain callables constructed outside the network, so a node is
tested by calling operator() with hand-built inputs. That removes four
hazards at once: fixture provenance, replay-from-frame-0, cross-test state
leakage, and replay-harness nondeterminism. It also means a dead upstream
producer no longer blocks testing its consumer.
- VR-010 (dump provenance) and VR-011 (replay harness rewrite) added. A dump
made with LVFace is currently byte-indistinguishable from one made with
w600k-R50 — the GR-004 problem again, in the dump.
- Four requirements had no verification tier at all; the traceability gate
found them.
- DP-007: CI builder image, CPU-only, pinned by tag in the Gitea container
registry. Corpus fixtures go to the package registry rather than LFS: LFS is
pulled on clone and would tax every developer for data only CI reads.
- IR-004/005/007/008 marked done; the v1 DSP parameters they had to pin are
now normative in the server spec.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
TRACES: AR-010, DP-007, IR-004, IR-005, IR-007, IR-008, VR-001, VR-010, VR-011 | SR-002, SR-003
The phase structure encoded ordering assumptions that stopped being true as the
design changed, and its Phase 2 still described retuning constants that are now
withdrawn. Ordering is now derived from per-requirement dependencies instead:
anything with no unmet dependency is startable.
Carries over the TrackRegistry design (now keyed to AR-012/AR-013) and records
what was withdrawn from the old plan, including the --presence-mode flag —
comparison against old behaviour uses recorded reference output rather than a
second live code path.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Adds the requirements baseline for the pipeline redesign:
- SPEC.md — software requirements with Current/Gap deltas per item, so the
document doubles as a work list.
- requirements.md — stable flat IDs (AR/DP/IR/GR/VR) with parent traces,
priorities, statuses, and a per-requirement verification plan. Replaces the
thematic A1..E8 scheme, which had already produced an A1a and an out-of-order
E6; IDs are now permanent and never reused.
- IMPLEMENTATION-PLAN.md — phased work.
The central change is AR-012: presence follows track extent rather than
per-frame recognition, so a window starts when an actor appears rather than
when the recogniser first succeeded. anneal_sec and extinction_sec are
withdrawn rather than retuned — a track that survives its own gaps leaves them
nothing to do.
Verification is shaped by CI running on an N100 with no dGPU: the existing
HDF5 dump makes everything downstream of embedding replayable on CPU, which
covers the bulk of the redesign.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Her bbox is frozen at identical coordinates for t=2450 and t=2451; the
dump's own per-frame detections show only one real face at t=2451, and
it matches the Chloë Sevigny box (IoU 1.0), not hers. The frame is one
ghost overlapping one fresh misidentification, not two competing fresh
identities as previously written.
Replaces narrative claims with verified numbers across all report pages:
- Cross-model held-out validation (LVFace/mbf/r18, all 5 held-out
films): LVFace wins every film outright, not just "consistent with"
the training-set pick. r50 dropped from the detailed comparison
(gallery has ~30% fewer reference images per actor than the other
three models on identical source photos).
- Per-film training breakdown: LVFace does not win every training
film (mbf beats it on Lord of War); the 75.3% macro figure hides a
10.7pp spread.
- Gallery coverage computed per film (20.3%-78.6%) instead of one
flat 67%-missing average.
- Found and fixed a real scoring bug in optimize.py: a candidate
whose hardest film's replay timed out was averaged over survivors
instead of penalized, silently rewarding partial coverage. Affected
3 of 16 training combos; corrected throughout, and optimize.py now
scores an incomplete evaluation f1=0.0 instead of averaging over
whichever films happened to finish.
- Every FPI frame in the deep dive now comes from the proper montage
renderer (Onscreen/Offscreen panel, ghosts never drawn as boxes),
never the bare-box debug overlay used earlier.
- Every distinct out-of-cast name across all 9 films gets its own
frame at its first appearance (9 names, 4 films), not a
single-example spot check: 2 ground-truth gaps, 1 photograph
misread as a person, 6 genuine lookalike confusions.
- New methodology.md: the scene-level-vs-per-second scoring mismatch
that the rest of the report assumes, written out once.
- Cut the deadlock/gdb debugging narrative from the experiment log;
kept the one fact that matters (KPN's node/network split lets the
expensive GPU stage run once and the cheap stage replay against
cached embeddings).
- Plain declarative style throughout, no em dashes, no blog voice.
- switch report frames to the scene best/worst montage renderer
(Onscreen/Offscreen panels + TPI/FPI/FN legend): perfect-second hero,
wedding couple, funeral 19-of-20, polygraph bridging, crew-scene FN
ceiling, Robert Patrick ground-truth gap, rapid-cut double label,
Herbie Hancock on an in-fiction screen
- deep dive restructured: extinction bridging framed as designed
behavior with a measurable cost (debug overlay draws the boxes; the
shipped output is presence windows), plus the face-vs-presence
ceiling and two X-Ray-is-wrong exhibits
- Material polish: light/dark palette toggle, landing-page grid cards,
figure/caption CSS, how-to-read admonition; site_url set so 404 links
resolve under the Pages subpath
- README: perfect-second and screen-call frames committed (gitignore
exceptions), readme_example.jpg retired
- build_site.sh: stage_frame helper downscales montage frames to 1920px
and pulls any missing montage-frames packages
- experiment_charts.py generates 4 figures from experiments/ artifacts:
held-out per-film F1, 16-combo ranking, DE search landscape, and the
Downton detector-vs-tracker ghost timeline (replaces the blank
title-card screenshot)
- new frames: 19-correct wedding shot (success case), Many Saints
ghost-vs-unknown frame (three error classes in one image)
- rename rep4-optimizer-results.md -> model-bakeoff.md; rep4 kept only
as the on-disk artifact prefix, explained once
- repo file references are now links via https://REPOLINK/<path>
placeholders; build_site.sh pins them to the HEAD commit's raw URLs
and fails the build if a linked path doesn't exist at HEAD
- drop references to removed scripts (scene_score.py, score_config.py)
and to session-memory names; mark artifact-registry paths with their
pull commands
- commit readme_example.jpg + pipeline_topology.svg so README renders
on the plain Gitea repo view
- deploy_pages.sh: push built site/ to the gitea-pages branch
Splits the rep4 write-up's key findings into their own linkable pages:
- best-model.md: calibration curves first (discriminative power, independent
of any threshold), then F1 on the benchmark — LVFace-B Glint360K wins both.
- gallery-scope.md: whole vs. cast-restricted gallery, isolated from model and
expansion choice — restriction wins on every axis, but isn't a shipped
runtime feature yet.
- pose-expansion.md: the training-set expand_gallery effect, and the held-out
replication attempt that found it doesn't reproduce (5 films, 2 models,
after catching and fixing a replay-timeout truncation bug and a bbox
first-match-instead-of-best-match bug in the comparison harness itself). An
honest null result, with the methodology errors documented since they're
exactly the kind that manufacture a false "it works!" finding.
- lvface-deep-dive.md: the winning model's held-out generalization gap, its
two failure modes (frozen-bbox ghost tracks), and a verified case (cross-
checked against Jellyfin's independent cast metadata) where LVFace
correctly identified an actor that X-Ray's ground truth failed to credit.
Adds a "report-highlights" artifact-registry package (scripts/artifacts/
push_artifacts.sh, pull_artifacts.sh) for hand-picked illustrative frames that
aren't reproducible via the automated best/worst montage selection, and wires
pulling it into scripts/docs/build_site.sh.
docs/rep4-optimizer-results.md is the main deliverable: the model bake-off +
threshold re-tune experiment log, including the ROCm teardown deadlock root
cause and fix, DE concurrency tuning, the 16-combo results table, held-out
validation against 5 films never seen by the optimizer (macro F1 67.4% vs.
75.3% training — a real generalization gap), the frozen-bbox "ghost track"
failure mode found via annotated frame evidence, calibration curves per model,
and an isolated-effects breakdown of gallery scope vs. pose expansion.
MkDocs site (mkdocs.yml, docs/index.md) renders docs/*.md; scripts/docs/
pulls referenced images from the artifact registry and generates the
calibration chart at build time (see the tooling commit) rather than
committing images to the repo.
experiments/ now keeps only scripts + README + SESSION_STATE.md in git — every
data artifact (galleries, dumps, X-Ray corpus, montage frames, trajectories,
manifests, results) moved to the Gitea package registry. film-lut.template.json
is the committed placeholder for the gitignored file-lut.json (real local
movie paths, never shared — some source filenames carry scene-release tags).
Adds models/transnetv2.onnx (via Git LFS, matching the other ONNX models) for
the new scene-detection path.
dtourolleandClaude Opus 5