feat: Complete Rust port of WiFi-DensePose with modular crates

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

rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/Cargo.toml

@@ -0,0 +1,60 @@
+[package]
+name = "wifi-densepose-nn"
+version.workspace = true
+edition.workspace = true
+authors.workspace = true
+license.workspace = true
+repository.workspace = true
+documentation.workspace = true
+keywords = ["neural-network", "onnx", "inference", "densepose", "deep-learning"]
+categories = ["science", "computer-vision"]
+description = "Neural network inference for WiFi-DensePose pose estimation"
+
+[features]
+default = ["onnx"]
+onnx = ["ort"]
+tch-backend = ["tch"]
+candle-backend = ["candle-core", "candle-nn"]
+cuda = ["onnx"]
+tensorrt = ["onnx"]
+all-backends = ["onnx", "tch-backend", "candle-backend"]
+
+[dependencies]
+# Core utilities
+thiserror.workspace = true
+anyhow.workspace = true
+serde.workspace = true
+serde_json.workspace = true
+tracing.workspace = true
+
+# Tensor operations
+ndarray.workspace = true
+num-traits.workspace = true
+
+# ONNX Runtime (default)
+ort = { workspace = true, optional = true }
+
+# PyTorch backend (optional)
+tch = { workspace = true, optional = true }
+
+# Candle backend (optional)
+candle-core = { workspace = true, optional = true }
+candle-nn = { workspace = true, optional = true }
+
+# Async runtime
+tokio = { workspace = true, features = ["sync", "rt"] }
+
+# Additional utilities
+parking_lot = "0.12"
+once_cell = "1.19"
+memmap2 = "0.9"
+
+[dev-dependencies]
+criterion.workspace = true
+proptest.workspace = true
+tokio = { workspace = true, features = ["rt-multi-thread", "macros"] }
+tempfile = "3.10"
+
+[[bench]]
+name = "inference_bench"
+harness = false