dearsky/wifi-densepose
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Code Issues 20 Pull Requests 5 Actions Packages Projects Releases 1 Wiki Activity
50 Commits 16 Branches 1 Tag
8583f3e3b5b306e46e7a2e9d171b58acac01278b
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4 Commits

Author SHA1 Message Date
Claude
8583f3e3b5 feat: Add guided installer with hardware detection and RVF build profiles 
- install.sh: 7-step interactive installer detecting system, toolchains,
  WiFi hardware (interfaces, ESP32 USB, Intel CSI debug), and recommending
  the best build profile (verify/python/rust/browser/iot/docker/field/full)
- Rust is the primary recommended runtime (810x faster than Python)
- Makefile: 15+ targets including make install, make check, make build-rust,
  make build-wasm, make bench, make run-api, make run-viz
- README: Updated installation section with Rust-primary ordering, removed
  mock testing references, added v2.2.0 changelog entry

https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
 2026-02-28 13:41:47 +00:00
Claude
195f7150ac chore: Update claude-flow daemon state 
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
 2026-02-28 06:50:13 +00:00
Claude
7eb7516a41 chore: Update claude-flow daemon state 2026-01-13 03:39:19 +00:00
Claude
6ed69a3d48 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
 2026-01-13 03:11:16 +00:00