Picks up the KPN fix: node data outputs block on a full channel rather than
dropping. Sentinels stay out-of-band, so EOF can always overtake a stalled data
path and the hold-and-wait deadlock that comment warns about is not reachable.
Verified on a 77s clip at 5 fps, which should yield 385 sampled frames:
before 65 written, 320 dropped, 29s, two runs differ
after 385 written, 0 dropped, 17s, two runs byte-identical
The determinism is the part that matters. Golden fixtures were impossible while
what got dropped depended on timing; VR-001 fixture generation is unblocked by
this, and so is the CI replay strategy that depends on it.
Faster rather than slower, which is worth recording because the intuition runs
the other way: a dropped frame has already cost its decode, and the overflow
exception cost more still.
AR-004 is not fully closed. Channel capacity remains a count of items, while a
face carries a 112x112 crop and a 512-float embedding — so a crowded frame
occupies far more memory per slot than a sparse one. Bounding by bytes in
flight is the remaining half, and it matters once max_faces is removed (AR-003).
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
TRACES: AR-004, VR-001 | SR-002
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.
Register a KPN event handler in both scene_analyze and scene_preview:
- Overflow events accumulate per-node dropped-frame counts, printed on exit.
- A Closed event from any node other than result_sink at EOF means a stage
died; trip an atomic so the main loop bails out instead of hanging on
'done' forever, and exit non-zero.
Bumps external/KPN to the commit that exposes set_event_handler / NodeEvent.
dtourolleandClaude Opus 5