- Add Python WebSocket sensing server (ws_server.py) with ESP32 UDP CSI and Windows RSSI auto-detect collectors on port 8765 - Add Three.js Gaussian splat renderer with custom GLSL shaders for real-time WiFi signal field visualization (blue→green→red gradient) - Add SensingTab component with RSSI sparkline, feature meters, and motion classification badge - Add sensing.service.js WebSocket client with reconnect and simulation fallback - Implement sensing-only mode: suppress all DensePose API calls when FastAPI backend (port 8000) is not running, clean console output - ADR-019: Document sensing-only UI architecture and data flow - ADR-020: Migrate AI/model inference to Rust with RuVector ONNX Runtime, replacing ~2.7GB Python stack with ~50MB static binary - Add ruvnet/ruvector as upstream remote for RuVector crate ecosystem Co-Authored-By: claude-flow <ruv@ruv.net>
WiFi-DensePose v1 (Python Implementation)
This directory contains the original Python implementation of WiFi-DensePose.
Structure
v1/
├── src/ # Python source code
│ ├── api/ # REST API endpoints
│ ├── config/ # Configuration management
│ ├── core/ # Core processing logic
│ ├── database/ # Database models and migrations
│ ├── hardware/ # Hardware interfaces
│ ├── middleware/ # API middleware
│ ├── models/ # Neural network models
│ ├── services/ # Business logic services
│ └── tasks/ # Background tasks
├── tests/ # Test suite
├── docs/ # Documentation
├── scripts/ # Utility scripts
├── data/ # Data files
├── setup.py # Package setup
├── test_application.py # Application tests
└── test_auth_rate_limit.py # Auth/rate limit tests
Requirements
- Python 3.10+
- PyTorch 2.0+
- FastAPI
- PostgreSQL/SQLite
Installation
cd v1
pip install -e .
Usage
# Start API server
python -m src.main
# Run tests
pytest tests/
Note
This is the legacy Python implementation. For the new Rust implementation with improved performance, see /rust-port/wifi-densepose-rs/.