mirror of
https://github.com/ruvnet/RuView
synced 2026-07-31 18:51:42 +00:00
rUv
2e018f4f19
Native frame contract, universal RF encoder, RF-aware Gaussian spatial memory, physics-guided synthetic RF worlds, edge sensing control plane, BLE-CS + factorized pose. All 10 ADRs (273-282) fully implemented and tested (99 tests); ADR-278 (radar inverse rendering) honestly gated with zero code as a future research program. Deep-reviewed and hardware-tested against a live ESP32-C6 CSI node before merge: fixed a reachable panic, a silent NaN-corruption path, a cross-entity Gaussian conflation bug, and a wrong-center-frequency bug in the WiFi adapter (confirmed live: was misreporting channel 4 as 2437 MHz, now correctly reports 2427 MHz matching the hardware parser exactly). Added a standing hardware-in-the-loop test (examples/esp32_live_hardware_test.rs). Also fixed unrelated pre-existing issues surfaced during validation (wifi-densepose-core clippy warnings, a ruview-auth Windows build break, a sensing-server test flake). Full review: https://gist.github.com/ruvnet/89795f3c4b8ea166cff5ac35ae4c7651
wifi-densepose-core
Core types, traits, and utilities for the WiFi-DensePose pose estimation system.
Overview
wifi-densepose-core is the foundation crate for the WiFi-DensePose workspace. It defines the
shared data structures, error types, and trait contracts used by every other crate in the
ecosystem. The crate is no_std-compatible (with the std feature disabled) and forbids all
unsafe code.
Features
- Core data types --
CsiFrame,ProcessedSignal,PoseEstimate,PersonPose,Keypoint,KeypointType,BoundingBox,Confidence,Timestamp, and more. - Trait abstractions --
SignalProcessor,NeuralInference, andDataStoredefine the contracts for signal processing, neural network inference, and data persistence respectively. - Error hierarchy --
CoreError,SignalError,InferenceError, andStorageErrorprovide typed error handling across subsystem boundaries. no_stdsupport -- Disable the defaultstdfeature for embedded or WASM targets.- Constants --
MAX_KEYPOINTS(17, COCO format),MAX_SUBCARRIERS(256),DEFAULT_CONFIDENCE_THRESHOLD(0.5).
Feature flags
| Flag | Default | Description |
|---|---|---|
std |
yes | Enable standard library support |
serde |
no | Serialization via serde (+ ndarray serde) |
async |
no | Async trait definitions via async-trait |
Quick Start
use wifi_densepose_core::{CsiFrame, Keypoint, KeypointType, Confidence};
// Create a keypoint with high confidence
let keypoint = Keypoint::new(
KeypointType::Nose,
0.5,
0.3,
Confidence::new(0.95).unwrap(),
);
assert!(keypoint.is_visible());
Or use the prelude for convenient bulk imports:
use wifi_densepose_core::prelude::*;
Architecture
wifi-densepose-core/src/
lib.rs -- Re-exports, constants, prelude
types.rs -- CsiFrame, PoseEstimate, Keypoint, etc.
traits.rs -- SignalProcessor, NeuralInference, DataStore
error.rs -- CoreError, SignalError, InferenceError, StorageError
utils.rs -- Shared helper functions
Related Crates
| Crate | Role |
|---|---|
wifi-densepose-signal |
CSI signal processing algorithms |
wifi-densepose-nn |
Neural network inference backends |
wifi-densepose-train |
Training pipeline with ruvector |
wifi-densepose-mat |
Disaster detection (MAT) |
wifi-densepose-hardware |
Hardware sensor interfaces |
wifi-densepose-vitals |
Vital sign extraction |
wifi-densepose-wifiscan |
Multi-BSSID WiFi scanning |
License
MIT OR Apache-2.0