Commit Graph
15 Commits
Author SHA1 Message Date
dtourolle e5204a831a feat(scene-detector): run the learned boundary detector live in the C++ pipeline
Wire the XGBoost scene-boundary detector into scene_analyze as a post-EOF step in
the result sink (like flood-fill itself — the per-film knee threshold needs the
whole film, so it cannot stream). With --scene-xgb-model set, the camera-position
node stamps a per-frame RGB histogram onto the Frame, it rides through to the
sink, and at EOF the sink runs XGBSceneBoundary over the collected histograms +
the movie's per-second audio log-PSD to produce the flood-fill boundaries. Falls
back to is_scene_boundary / is_cut when no model is configured or inference fails.

Inference is real XGBoost via CMake FetchContent (v2.1.1, static), C API in
src/inference/xgb_scene_boundary.hpp; audio log-PSD in src/inference/
audio_logpsd.hpp (FFTW + ffmpeg full-file 16kHz decode). Feature extraction
matches training exactly — video features verified row-identical to numpy, and to
avoid chasing numpy's every rounding the shipped model is TRAINED on the
C++-extracted features (scene_features_dump exe → train_xgb_cpp.py). The
C++/Python peak-finders differ slightly so boundary counts differ, but what
matters is downstream: flood + C++ detector = 75.8% macro presence F1 vs 64.0%
for the histogram-cut flood and 62.5% for track_extent, and it fixes the Scarface
flood collapse (41 -> 70). All nine films improve.

Guarded by the SAE_SCENE_XGB CMake option (on by default; heavy first build).
xgb_boundary_parity is a diff harness; scene_features_dump writes the C++ feature
matrix so training and inference share one feature implementation.

Verified end to end: scene_analyze --scene-xgb-model on a real movie stamps the
histogram, runs the detector at EOF ("XGBoost scene detector: N boundaries"), and
flood-snaps presence to the learned boundaries.
2026-08-09 21:21:29 +02:00
dtourolle 48332d2041 feat(replay): the whole replay chain is C++, including the sink
The sae_kpn module has not compiled since the AR-007/AR-008 tracker redesign,
and was switched off at the build rather than patched because the fix is a
restructuring. Two failures, one cause.

It did not compile: `add_face_tracker` built FaceTrackerFunc from a Config
alone, and the tracker has required a TrackRegistry and a calibration since
association moved into probability space.

And presence was rebuilt in Python. `replay.py::build_minimal` merged
per-frame detections into windows by annealing gaps, which is what the
pipeline did before AR-012. The sink builds a window from a TrackRegistry
claim instead — the extent of a track an actor owned, starting when they
appeared rather than when recognition first succeeded. Those answer different
questions, so every sweep was tuning against a contract the shipped code had
stopped honouring.

Both follow from the seam being a factory per node. The chain has a
construction order — the matcher fits the calibration, the registry needs a
discounter built from it, the tracker needs both, and the sink needs the
registry's claims — and independent factories cannot express it, so the
tracker kept being built against a signature that no longer existed. One
`add_pipeline` mirrors main.cpp exactly and is now the only way to build the
chain, so the ordering cannot be got wrong again from Python. DP-001 is the
requirement behind it: a replay harness is a front-end, and its job is to
supply frames and read the result, not to re-derive presence.

Lifetimes needed a home. ResultSinkFunc holds `const Config&` and
`std::atomic<bool>&`, which under main() are locals in a frame outliving the
pipeline; there is no such frame when the network is built and torn down from
Python. ReplaySession owns both for the network's lifetime, keyed by network
and released explicitly — a sweep builds one network per replay and the sink
retains every annotation, so holding them forever would grow with films x
configs. Getting this wrong presented as an empty output_path: the sink
announced `[result_sink] writing ` and wrote nothing.

test_sae_kpn.py is ported rather than left behind. It called all three removed
factories and asserted on SceneAnnotations read back per frame; neither half
survives, so it now waits on pipeline_done and asserts on the file the sink
writes. Verified against gallery_lvface.h5: three frames through the real
chain, timestamps 0/1/2, truth file written. EOF is a control token the sink
flushes on and does not record, so three inputs give three frames, never four.

SAE_BUILD_KPN_BINDINGS goes back to ON.

TRACES: VR-011, VR-002 | DP-001 | PR-002
2026-08-05 19:40:25 +02:00
dtourolle 7c7d4934ae refactor(presence): execute the extinction_sec/anneal_sec withdrawal
docs/SPEC.md specified this removal, listed its parts, and ended "grep
for both names and expect no survivors". There were about forty.
docs/requirements.md meanwhile recorded both constants as Withdrawn and
"deleted rather than retained at zero", on the grounds that a field
naming a mechanism the pipeline no longer has is actively misleading.
Neither statement was true of the code: Config still carried
extinction_sec 57.4 and anneal_sec 35.5, --extinction and --anneal still
parsed, and SceneTrackerFunc still ran its keep-alive in both shipped
pipelines, announcing its timeout at every startup.

SceneTrackerFunc is replaced by FrameAnnotationFunc, which is stateless:
same ports, same output type, no keep-alive. Presence belongs to
TrackRegistry (AR-012), where a window is the extent of a track an actor
owned and ends at the last sighting (AR-013). The keep-alive answered
that question a second time and answered it worse, by re-opening exactly
the trailing cool-down AR-013 refuses.

Visible change: --verbosity standard's frames[].identified listed every
actor inside the keep-alive, including ones absent from the frame. It
now lists what was matched in that frame. Minimal and xray output is
untouched -- both were already built from registry claims and never
consulted this node. No schema bump: the published extraction block
reports track_extinction_sec, a different knob that bounds
re-association and never extends a claim.

TrackRegistry::Config::extinction_sec is renamed track_extinction_sec to
match the Config field feeding it, so the grep SPEC.md asks for now
returns nothing rather than one confusing false positive.

Two targets turned out to have been silently dead, both since the
AR-007/AR-008 tracker redesign, and both for the same reason -- they
construct FaceTrackerFunc from a Config alone, a signature that stopped
existing when association moved into probability space:

- scene_preview is fixed here. It now mirrors main.cpp's construction
  order exactly (matcher, then registry, then tracker) and wires the
  registry's claims into the sink, which it was not doing. DP-001 says
  modes are front-ends that must not fork pipeline logic; this one had
  forked it and then rotted.
- sae_kpn is not fixed. Restructuring the seam so the tracker can reach
  a calibration that only exists once the matcher is built is VR-011's
  rewrite, not a patch, and presence claims do not cross the seam at all
  today. It is now behind SAE_BUILD_KPN_BINDINGS=OFF with the reason
  recorded, so `cmake --build` succeeds and the breakage is attributed
  rather than rediscovered.

That second one is worth stating plainly: VR-002 ("replay drives the
real KPN nodes, not a reimplementation") is marked Done, and the module
that makes replay possible has not compiled for some time. The .so in a
stale build/ predates the change.

Python side: the two names are gone from optimize.py, replay.py and
run_holdout_all_models.py as Config keys. anneal_sec survives as
REPLAY_LOCAL_KEYS -- it still configures replay.py's own windowing,
which is a Python reimplementation that no longer matches the sink and
is documented as such. That divergence is VR-011's.

TRACES: AR-012, AR-013 | DP-001 | SR-002
2026-08-05 16:21:15 +02:00
dtourolleandClaude Opus 5 c1155cb607 feat(gemm): the annex is a matrix, not a list — scored by the same GEMM
The per-film annex was folded in after the gallery multiply by a host-side
cosine loop over a vector of {embedding, actor} structs, justified in-comment
by "tens of embeddings". AR-018/AR-019 retired that assumption: every owned
track promotes, so the annex grows with cast size and film length.

TrackGallery now holds it as a contiguous row-major matrix with a parallel
actor index — the flat_emb_/flat_actor_ shape the baked gallery already uses —
and hands newly promoted rows to the matcher once per frame. The matcher pushes
them into the similarity engine's resident matrix through a new
ISimilarityEngine::append_rows, so one SGEMM covers baked and promoted
references alike and best-of-N is a single pass over one similarity column.
Capacity doubles on overflow, and the GPU backends grow device-to-device, so a
promotion never re-uploads the gallery across the bus.

Absorbing promotions runs once per frame, after every face has been scored.
Appending mid-frame would invalidate the similarity pointer the chunk loop is
still reading, and it also removes an incidental dependence on face order
within a frame — a promotion helps subsequent frames, never the one that
produced it, which is the semantics the expansion store already documented.

OpenBLAS becomes a requirement of the CPU GEMM backend rather than an
opportunistic upgrade. That path is what CI and the cpu builder image run, so
falling back to the scalar loop in silence meant AR-027 could be measured — or
believed — on a kernel no release uses. The loop survives as the correctness
oracle the BLAS backends are diffed against, behind SAE_ALLOW_SCALAR_GEMM.

Call site 3, the deferred TBI pass, is untouched: it does not exist until
AR-020, so AR-026 stays In Progress.

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

TRACES: AR-026 | UT-004, UT-005 | SR-001
2026-08-04 21:20:31 +02:00
dtourolleandClaude Opus 5 2a8ee3660b feat(audio): bind the v1 signature and validate offset recovery on real content
sae_audio exposes the shipped signature to Python. It compiles
audio_signature.cpp directly against FFmpeg rather than linking
sae_gallery: the signature needs no model, no OpenCV and no HDF5, so a
module that dragged those in would make `import sae_audio` depend on a
GPU-capable build of a path that is pure CPU DSP.

The point of binding rather than porting is that a fingerprint is only
useful if every implementation agrees byte for byte. A numpy port would
be a third implementation, and the one nobody checks against the golden
vector.

VR-014 then recovers a known trim from real film audio rather than from
the synthetic tone: 40 random in-cap offsets, every one recovered to the
nearest frame, worst error 46 ms against a 500 ms budget — and 46 ms is
the quantisation floor, not a result, since offsets land on whole
92.88 ms frames.

The soft spot is tier labelling rather than accuracy. Sub-frame
misalignment drags the score down (0.94-0.99 near a frame boundary,
0.69-0.73 at half a frame), demoting 27 of 40 correct alignments to
`loose`. Allowing +/-1 frame of slack in the score fixes it: all 40 back
to `audio` at min 0.906, false matches unmoved at 0.12-0.16, for 81 ms
of the budget.

The module stops at the producer's edge. Sliding one signature against
another is the consumer's algorithm (server SPEC §3, and the jRay
plugin implements it), so a caller writing that slide in numpy is not
duplicating anything this repo owns.

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

TRACES: IR-004, IR-005 | VR-014 | UT-105, UT-106, UT-107, UT-108 | SR-003
2026-07-31 16:52:11 +02:00
dtourolleandClaude Opus 5 cc1bed92d8 perf: back the CPU similarity GEMM with OpenBLAS
The CPU path was a scalar triple loop. It is the correctness oracle for the GPU
backends, but it is also what CI runs — there is no GPU on the N100 host — and
since AR-003 removed the per-frame face cap, a crowded frame now scores many
faces against a library-scale gallery. Scoring one face against 5000 embeddings
is 2.6 MFLOP; in scalar that does not hold up (AR-027).

S(g,f) viewed as row-major [n_faces x n_gallery] is exactly query * gallery^T,
so the loop nest collapses into a single cblas_sgemm.

OpenBLAS is optional in the build: found via pkg-config, and the scalar path
remains when it is absent so no hard dependency is added and the two can be
diffed when a similarity looks wrong. The configure step warns rather than
failing, since a developer without it should still get a working tree.

The test target links it too. Without that the suite compiles the scalar
fallback while the builder image ships CBLAS, so CI would be verifying a kernel
that is not the one running in production — the same class of mistake as testing
a path the gate never executes.

Recorded as required (not optional) in the DP-007 image, for the same reason.

Suite: 92 cases, 6136 assertions, with CBLAS compiled in.

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

TRACES: AR-026, AR-027, DP-007 | SR-001
2026-07-31 15:04:29 +02:00
dtourolleandClaude Opus 5 908d166173 feat: bind galleries to the embedder that built them
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
2026-07-30 19:04:07 +02:00
Claude 7db40f430d GR-004: bind galleries to the embedder that built them
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>
2026-07-30 18:35:46 +02:00
dtourolleandClaude Opus 5 45ef7c1916 Add the v1 audio signature to the pipeline (IR-004, IR-005, IR-007, IR-008)
Implements the content-derived spectral-peak signature from
JRay-public-server/SPEC.md §3 so a truth file is self-identifying: 120 s
window centred on the media midpoint, mono at 11025 Hz, 4096/1024 Hann
STFT, 32 log-spaced bins over 300-3000 Hz, one byte per frame (5-bit peak
band + 2-bit energy class), base64, `v1:` prefix.

Audio decode is a second stream from the FFmpeg libraries the pipeline
already links for video; libswresample is added to the existing
ffmpeg_libs interface target. The FFT is written out rather than pulled
from a library for the same reason the plugin vendors one: the output has
to be bit-identical across two languages, so a dependency whose version
could change the numerics is a liability.

The server spec fixes the geometry but not enough to reproduce a byte
stream — Hann periodicity, band aggregation, the energy-class definition,
tie-breaking and the base64 alphabet are all unconstrained by it. Those
are pinned in audio_signature.hpp and mirrored in the golden fixture, so
the plugin can be implemented from the fixture alone.

IR-005: tests/fixtures/audio/ carries a deterministic 120 s tone (FLAC —
lossless, so identical PCM to the WAV make_fixture.py emits, and 3.5x
smaller in git) plus the signature it must produce, the decoded-PCM
checksum and the full parameter contract. That directory is the artefact
shared with the plugin repo; the PCM checksum is separate from the
signature so a codec-level difference is distinguishable from a DSP one.

IR-007: media under 120 s emits no signature. Same for a file with no
audio stream or one that will not open — UR-9 is an enhancement and must
never be able to break a fetch.

Verified against an independent Python reference implementation: same
bytes. All 32 bands and all 4 energy classes appear in the golden vector,
and the window-centring test wraps the fixture in 90 s of silence either
side and requires the golden value back.

Not wired into the truth-file output yet — that is the schema_version
bump under IR-002/IR-003 and is deliberately out of scope here.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-07-30 18:25:37 +02:00
dtourolle 5d2f673a81 build: support OpenCV 5 and TensorRT 10
OpenCV: distros (Arch/CachyOS) now ship OpenCV 5 as default. The config
package rejects a 5.x install when find_package requests 4, so probe for 5
first and fall back to 4. All components used here (core, imgproc, imgcodecs,
videoio, dnn, objdetect, highgui) exist in both.

TensorRT: nvinfer1::Dims5 was removed in TRT 10 (Dims2..Dims4 remain in
NvInferLegacyDims.h). Build the TransNetV2 rank-5 input shape via the generic
nvinfer1::Dims, which is valid on both 8.x and 10.x.
2026-07-30 13:07:42 +02:00
dtourolle 41a277bc19 feat(engine): HDF5-native galleries with embedded calibration; TensorRT backends; scene detection
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.
2026-07-19 19:04:03 +02:00
dtourolle 0ee131a692 Add AMD support via ort alternative to trt 2026-06-28 11:50:05 +02:00
dtourolle a3ba53ddf7 improved performance 2026-06-13 22:44:44 +02:00
dtourolle a1d6759abc faster calibration curve generation
jellyfin intergration
2026-06-12 17:54:23 +02:00
dtourolle d753062c6c Initial commit: scene-actor-extraction pipeline
Source (KPN++ pipeline nodes, ArcFace embedders, SCRFD/YuNet detectors,
gallery builder), build scripts, and eval artifacts.

- external/KPN as a git submodule (gitea.tourolle.paris/dtourolle/KPN)
- ONNX models tracked via Git LFS (models/*.onnx)
- generated outputs, TensorRT engines, reference repos, and media ignored
2026-06-12 15:29:01 +02:00