6ed69a3d48
Major changes: - Organized Python v1 implementation into v1/ subdirectory - Created Rust workspace with 9 modular crates: - wifi-densepose-core: Core types, traits, errors - wifi-densepose-signal: CSI processing, phase sanitization, FFT - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch) - wifi-densepose-api: Axum-based REST/WebSocket API - wifi-densepose-db: SQLx database layer - wifi-densepose-config: Configuration management - wifi-densepose-hardware: Hardware abstraction - wifi-densepose-wasm: WebAssembly bindings - wifi-densepose-cli: Command-line interface Documentation: - ADR-001: Workspace structure - ADR-002: Signal processing library selection - ADR-003: Neural network inference strategy - DDD domain model with bounded contexts Testing: - 69 tests passing across all crates - Signal processing: 45 tests - Neural networks: 21 tests - Core: 3 doc tests Performance targets: - 10x faster CSI processing (~0.5ms vs ~5ms) - 5x lower memory usage (~100MB vs ~500MB) - WASM support for browser deployment
61 lines
1.4 KiB
TOML
61 lines
1.4 KiB
TOML
[package]
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name = "wifi-densepose-nn"
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version.workspace = true
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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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[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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once_cell = "1.19"
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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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