One crate names the runtime, the providers and the devices; dr-face and
dr-segment ask it for a session by role. It hands ort an API table once
per process — from a libonnxruntime it dlopens when the app names a
directory holding one, otherwise from tract — so the Rust build stays
free of C on every target and a package can install the runtime as a
file (docs/inference.md §3).
Sessions live in a registry behind a Model handle that holds the bytes,
not the session: every use refreshes a timestamp and a reaper unloads
whatever sat idle past the decay. A scan that runs the detector on each
image never lets it go idle; a click in the develop view lets the
segmenter go after thirty seconds; a handle used after that reloads,
and reloads on a higher rung if a compiled engine has landed meanwhile.
The probe walks the platform's ladder by building strict sessions and
timing them against the CPU provider, caches the choice against a
fingerprint of the runtime, driver, hardware and models, and compiles
engines for the selected rung in the background, smallest model first.
Nothing in this commit turns the native path on: the apps still run on
tract until they call init with a runtime directory.
Two MIT classifiers from the same author as the reference pipeline's
whole-body detector: OCEC answers P(open) for one 40×24 eye, SGC
P(sunglasses) for a 48×48 head. Both load in tract once their batch
dimension is pinned by tools/fix-face-model-shapes.sh, like the embedder.
The crops come through the same fitted similarity the aligned face does,
so an eye window is a constant in template units rather than a second
warp, and a tilted head yields an upright eye. Measured on 60 proxies
from the reference library: the eye window plateaus at 22×11, the S
variant beats M and L (which overfit their own domain), and for
sunglasses the aligned face beats a head framing but the higher of the
two catches 11 of 12 pairs against 9 for either alone.
The reading keeps both eyes and the sunglasses number apart, because a
wink averages to the least informative value and a lens of dark glass
draws a confident answer from the eye classifier — over a woman in
sunglasses it read the right eye 0.97 open. Sunglasses take precedence,
and a face behind them is neither open nor a blink.
Ports the pipeline from the C++ reference in ../scene-actor-extraction
(MIT, same author). End to end on real portraits it separates identities
the way the reference's fitted calibration says it should: 0.596 between
distinct photographs of one person, 0.05 between different people, either
side of MBF's 0.267 boundary.
Three things are structural rather than incidental:
Aligned112 can only be built by align::warp, so Embedder::embed cannot be
handed an unaligned bounding-box crop. That mistake yields 512 plausible
unit-norm numbers and no error, so the type system refuses it instead.
Embedding carries its ModelId and cosine() returns None across models,
because a cross-model similarity is the one mistake that produces
plausible garbage rather than a failure.
The model-free half -- alignment, embedding arithmetic, f16 storage --
sits outside the inference feature and is covered by 11 tests that need
no weights on the machine.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Neither InsightFace export parses as shipped -- SCRFD fails at its input
node, ArcFace at the first Conv -- which is the same wall dr-segment hit
on YOLO's dynamic export. Both load cleanly with the input dims frozen,
so the pure-Rust runtime holds for the face pipeline too.
tools/fix-face-model-shapes.sh does the freezing, and exists so the
artefact is reproducible rather than a binary someone once produced. It
takes two forms because the two graphs need different ones: ArcFace's
batch is a named dim_param, SCRFD's H and W are dynamic but unnamed.
Also notes YuNet loading with no intervention, which matters for the
licence question in faces.md 2.3.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
dtourolle
