mirror of
https://github.com/ruvnet/RuView
synced 2026-08-01 19:01:42 +00:00
rUv
004a63e82d
- Upgrade openssl to 0.10.78 (CVE-2026-41676), jsonwebtoken to 9.4 - Suppress unmaintained-only/no-CVE advisories in .cargo/audit.toml with per-entry rationale - Fix all `cargo clippy --all-targets -- -D warnings` errors across 35 crates: derivable_impls, needless_range_loop, map_or→is_some_and/ is_none_or, await_holding_lock (drop MutexGuard before .await), ptr_arg (&mut Vec→&mut [T]), useless_conversion, approximate_constant (2.718→E, 3.14→PI), field_reassign_with_default, manual_inspect, useless_vec, lines_filter_map_ok, print_literal, dead_code - Apply `cargo fmt --all` - Pre-existing test failure in wifi-densepose-signal (test_estimate_occupancy_noise_only) is not introduced by this PR
80 lines
2.9 KiB
Rust
80 lines
2.9 KiB
Rust
//! Long-running inference loop. Polls the appliance's sensing-server,
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//! slides a CSI window, runs the count head, and emits `person.count`
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//! events. Same shape as `cog-pose-estimation::runtime`.
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//!
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//! Multi-node fusion is single-node only in v0.0.1 — the appliance's
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//! `/api/v1/sensing/latest` endpoint already aggregates across nodes
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//! before serving, so per-cog fusion is deferred until each node ships
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//! raw frames separately (ADR-103 §"Multi-node fusion" v0.2.0).
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use crate::inference::{CsiWindow, InferenceEngine, INPUT_SUBCARRIERS, INPUT_TIMESTEPS};
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use crate::publisher;
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use std::time::Duration;
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use tokio::time::sleep;
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pub struct RunConfig {
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pub sensing_url: String,
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pub poll_ms: u64,
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}
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pub async fn run_loop(
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cfg: RunConfig,
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engine: InferenceEngine,
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) -> Result<(), Box<dyn std::error::Error>> {
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let mut buffer: Vec<f32> = Vec::with_capacity(INPUT_SUBCARRIERS * INPUT_TIMESTEPS);
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let cap = INPUT_SUBCARRIERS * INPUT_TIMESTEPS;
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let mut tick: u64 = 0;
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loop {
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match fetch_frame(&cfg.sensing_url).await {
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Ok(amplitudes) => {
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tick += 1;
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buffer.extend(amplitudes);
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while buffer.len() > 2 * cap {
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let extra = buffer.len() - cap;
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buffer.drain(0..extra);
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}
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if buffer.len() >= cap {
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let window = CsiWindow {
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data: buffer[buffer.len() - cap..].to_vec(),
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};
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if let Ok(pred) = engine.infer(&window) {
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// v0.0.1 ships single-node — fusion is a no-op for
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// N=1. v0.2.0 will append additional per-node
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// predictions to a vec and call
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// `fusion::fuse_confidence_weighted` before emit.
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publisher::person_count(tick, &pred, 1);
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}
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}
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}
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Err(e) => {
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tracing::warn!(error = %e, "sensing-server fetch failed");
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}
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}
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sleep(Duration::from_millis(cfg.poll_ms)).await;
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}
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}
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async fn fetch_frame(url: &str) -> Result<Vec<f32>, Box<dyn std::error::Error>> {
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let url = url.to_string();
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let body = tokio::task::spawn_blocking(move || -> Result<String, ureq::Error> {
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Ok(ureq::get(&url).call()?.into_string()?)
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})
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.await??;
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let json: serde_json::Value = serde_json::from_str(&body)?;
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let snapshot = json.get("snapshot").unwrap_or(&json);
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let nodes = snapshot
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.get("nodes")
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.and_then(|v| v.as_array())
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.ok_or("missing nodes[]")?;
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let amplitude = nodes
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.first()
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.and_then(|n| n.get("amplitude"))
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.and_then(|v| v.as_array())
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.ok_or("missing nodes[0].amplitude[]")?;
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Ok(amplitude
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.iter()
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.filter_map(|v| v.as_f64().map(|f| f as f32))
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.collect())
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}
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