dtourolle
0da8271836
Local masking needs to know where an image's regions are. The watershed spike (S15 arm A) found the boundaries but had no idea what any of them enclosed; its coarse levels were geometric accidents. This adds the other half and the thing that joins them. `core/dr-segment` is where region reasoning now lives — the hierarchy moves out of `dr-gpu`, which keeps only the pixel passes that are genuinely shaders. The new crate is device-free and, without its default features, model-free too: 20 of its tests need neither an adapter nor 11 MB of weights. Arm B runs YOLO26n-seg through `ort`. D13 framed inference as a choice between `ort`'s C++ runtime and the pure-Rust dependency policy; that was a false choice. `ort`'s `alternative-backend` feature unlinks the C entirely and `ort-tract` supplies the API from tract, which is pure Rust. Measured before committing to it: zero unsupported operators, 420 ms for 640x640, and correct masks on bus.jpg. No NDK problem to solve, so D13's largest tolerated exception is not needed. Arm C is `prior.rs`, and it ships because the two arms fail in opposite directions. Instance membership re-weights the merge saddles, so region pairs the model believes share an object merge early and pairs straddling its edge merge late. No boundary moves — only the order in which they dissolve — which is how the result stays pixel-accurate at every level while its coarse levels become named things. Two things the spec assumed that turned out to be false, both recorded in models/LICENCE.md: there is no usable ADE20K-trained YOLO, so the shipped vocabulary is COCO's 80 subjects and *stuff* like sky and foliage must come from arm A; and tract cannot parse a dynamic-shape export, so the graph's input is fixed and tiling is the only route to more semantic resolution. Weights are AGPL-3.0, which GPLv3 §13 permits and which makes the combined work effectively AGPL. Deliberate, not accidental. They live in Git LFS, and a build script fails with an instruction rather than embedding a pointer file when the clone lacks them.
47 lines
1.7 KiB
TOML
47 lines
1.7 KiB
TOML
[package]
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name = "dr-segment"
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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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# Guards against a Git LFS pointer being embedded in place of the weights.
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build = "build.rs"
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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 for why the C++ ONNX Runtime is not linked here.
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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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# The example reads an ordinary JPEG, because the thing worth looking at is
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# whether detections land on a real photograph. Pure Rust, and already in the
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# tree for embedded previews.
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zune-jpeg.workspace = true
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env_logger.workspace = true
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[features]
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# On by default: a local adjustment that cannot select a subject is half the
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# feature, and the whole point of the tract backend is that enabling this costs
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# no C dependency on any platform.
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default = ["semantic", "embedded-model"]
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# Arm B — the ONNX runtime and the instance decoder.
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#
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# Separable because the watershed half is genuinely independent of it: with
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# this off, `dr-segment` is a pure-CPU graph algorithm crate with no model to
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# carry, which is what the headless hierarchy tests want.
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semantic = ["dep:ort", "dep:ort-tract", "dep:ndarray"]
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# Compile the weights into the binary.
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#
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# Separate from `semantic` because the two answer different questions. Android
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# hands the app no filesystem path to read a model from (ARCH §6.9), so there
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# it must be embedded; a desktop packager pointing at a system model directory,
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# or a test that only needs the decoder, wants the runtime without the 11 MB.
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embedded-model = ["semantic"]
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