mirror of
https://github.com/ruvnet/RuView
synced 2026-08-10 20:31:42 +00:00
ruv
b2f9c8d28d
Bumped each crate to its next patch version above whatever was already
live on crates.io (several had drifted ahead of what this checkout's
Cargo.toml showed) and published:
wifi-densepose-core 0.3.2, -vitals 0.3.2, -wifiscan 0.3.2,
-hardware 0.3.2, -signal 0.3.6, -nn 0.3.2, -ruvector 0.3.3,
-train 0.3.3, -mat 0.3.2, -wasm 0.3.1 (workspace.package version).
wifi-densepose-signal's default `eigenvalue` feature pulls in
ndarray-linalg -> openblas-src, which needs vcpkg on native Windows;
verified+published with --no-default-features instead (the crate
already builds clean without it; nothing about the published tarball
changes based on the local verify build's feature flags).
wifi-densepose-sensing-server and wifi-densepose-cli were bumped
(0.3.5, 0.3.2) but NOT published: both path-depend on ruview-auth,
which is `publish = false` and not on crates.io, so `cargo publish`
correctly refuses them ("all dependencies must have a version
requirement"). Left as-is pending a decision on whether ruview-auth
should become publishable.
Co-Authored-By: claude-flow <ruv@ruv.net>
70 lines
1.6 KiB
TOML
70 lines
1.6 KiB
TOML
[package]
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name = "wifi-densepose-nn"
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version = "0.3.2"
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edition.workspace = true
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authors.workspace = true
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license.workspace = true
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repository.workspace = true
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documentation.workspace = true
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keywords = ["neural-network", "onnx", "inference", "densepose", "deep-learning"]
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categories = ["science", "computer-vision"]
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description = "Neural network inference for WiFi-DensePose pose estimation"
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readme = "README.md"
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[features]
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default = ["onnx"]
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onnx = ["ort"]
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tch-backend = ["tch"]
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candle-backend = ["candle-core", "candle-nn"]
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cuda = ["onnx"]
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tensorrt = ["onnx"]
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all-backends = ["onnx", "tch-backend", "candle-backend"]
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[dependencies]
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# Core utilities
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thiserror.workspace = true
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anyhow.workspace = true
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serde.workspace = true
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serde_json.workspace = true
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tracing.workspace = true
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# Tensor operations
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ndarray.workspace = true
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num-traits.workspace = true
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# ONNX Runtime (default)
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ort = { workspace = true, optional = true }
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# PyTorch backend (optional)
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tch = { workspace = true, optional = true }
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# Candle backend (optional)
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candle-core = { workspace = true, optional = true }
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candle-nn = { workspace = true, optional = true }
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# Async runtime
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tokio = { workspace = true, features = ["sync", "rt"] }
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# Additional utilities
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parking_lot = "0.12"
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memmap2 = "0.9"
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[dev-dependencies]
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criterion.workspace = true
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proptest.workspace = true
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tokio = { workspace = true, features = ["rt-multi-thread", "macros"] }
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tempfile = "3.10"
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[[bench]]
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name = "inference_bench"
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harness = false
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[[bench]]
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name = "onnx_bench"
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harness = false
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required-features = ["onnx"]
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[[bench]]
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name = "native_conv_bench"
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harness = false
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