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https://github.com/ruvnet/RuView
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4700764a3a
Add a divergence report (count + fraction outside tolerance, per-feature breakdown, worst offenders) so we can tell a few branch-flip elements from a pervasive regression. The CI tolerance gate failed with max|d|=0.85 / maxrel=345 — far beyond FP rounding — so we need to see WHICH feature elements diverge structurally on the Azure runner.
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 /v2/.