dtourolleandClaude Opus 5
19981c1033
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>
48 lines
1.6 KiB
TOML
48 lines
1.6 KiB
TOML
[package]
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name = "dr-face"
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version.workspace = true
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edition.workspace = true
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rust-version.workspace = true
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license.workspace = true
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[dependencies]
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thiserror.workspace = true
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log.workspace = true
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# Inference. `ort` is the API; **tract is the engine** — see the workspace
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# manifest, and docs/faces.md §3, for why the C++ ONNX Runtime is not linked.
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ort = { workspace = true, optional = true }
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ort-tract = { workspace = true, optional = true }
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ndarray = { workspace = true, optional = true }
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[dev-dependencies]
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zune-jpeg.workspace = true
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env_logger.workspace = true
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# The M1 probe drives `ort` directly so it can print the raw load error.
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ort = { workspace = true }
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ort-tract = { workspace = true }
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[[example]]
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name = "probe"
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required-features = ["inference"]
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[[example]]
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name = "faces"
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required-features = ["inference"]
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[features]
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# Nothing on by default, and in particular **no `embedded-model`**: the weights
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# are not a build input and never become one (docs/faces.md §2.2). A feature
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# flag that *could* embed them is a flag someone eventually sets in a packaging
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# script, and the InsightFace grant does not survive that.
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default = []
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# The ONNX runtime, and the two stages that need it.
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#
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# Separable because the accuracy of this subsystem lives in `calibrate` and
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# `cluster`, which are arithmetic over embeddings with no model in them. They
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# must be testable against synthetic embeddings on a machine with no weights on
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# it — a test suite that needs a research-licensed download is a test suite
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# that does not run in CI.
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inference = ["dep:ort", "dep:ort-tract", "dep:ndarray"]
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