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

.claude-flow/config.yaml

@@ -0,0 +1,28 @@
+# Claude Flow V3 Runtime Configuration
+# Generated: 2026-01-13T02:28:22.177Z
+
+version: "3.0.0"
+
+swarm:
+  topology: hierarchical-mesh
+  maxAgents: 15
+  autoScale: true
+  coordinationStrategy: consensus
+
+memory:
+  backend: hybrid
+  enableHNSW: true
+  persistPath: .claude-flow/data
+  cacheSize: 100
+
+neural:
+  enabled: true
+  modelPath: .claude-flow/neural
+
+hooks:
+  enabled: true
+  autoExecute: true
+
+mcp:
+  autoStart: false
+  port: 3000