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examples(through-wall): ESP32 sensor auto-detection + WiFlow analysis tools

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- wiflow_browser.html: auto-detect live ESP32 nodes from the /ws/sensing stream and lock
  them as the model schema (NODE_IDS/CSI_DIM dynamic), persisted + restorable
- wiflow_ab.py: leakage-controlled A/B (chronological/random/blocked-gap/grouped-bucket,
  multi-seed) — the honest CSI→pose evaluation harness
- wiflow_capture.py / wiflow_train.py / wiflow_infer.py: camera-paired capture + train + infer
- pose.html: live WiFi-inferred skeleton viewer; serve.py: static server
- gitignore the regenerable 1.5MB model.npz artifact

Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
ruv
2026-06-16 17:00:57 -04:00
parent a784546918
commit 42c764652d
7 changed files with 747 additions and 6 deletions
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examples/through-wall/wiflow_browser.html
+104 -6
View File
@@ -112,7 +112,11 @@
<div class="label">empty-room baseline (ADR-151) — step OUT of the space</div>
<canvas id="calCv" width="420" height="300"></canvas>
<div style="margin-top:10px;display:flex;gap:8px;align-items:center;flex-wrap:wrap">
<button id="calBtn" class="btn">calibrate baseline (10 s)</button>
<button id="detBtn" class="btn">① detect ESP32 sensors</button>
<span id="detNodes" class="v">not detected</span>
</div>
<div style="margin-top:10px;display:flex;gap:8px;align-items:center;flex-wrap:wrap">
<button id="calBtn" class="btn">② calibrate baseline (10 s)</button>
<button id="recalBtn" class="ghost btn">recalibrate</button>
<label class="note" style="margin:0">get-ready countdown
<input id="calReady" type="number" value="5" min="3" max="15" style="width:64px"> s</label>
@@ -285,9 +289,15 @@
// wss when served over https (mobile/secure-context safe), else ws; ?ws= overrides
const CSI_WS = (new URLSearchParams(location.search)).get('ws')
|| `${location.protocol === 'https:' ? 'wss' : 'ws'}://${location.hostname || 'localhost'}:8765/ws/sensing`;
const NODE_IDS = [9, 13]; // per-node features in this fixed order (matches Python pipeline)
// Per-node feature schema — AUTO-DETECTED from the live stream (see detectSensors).
// [9,13] is only the fallback until detection runs. ORDER is fixed (sorted ascending)
// so the model's input layout is stable across capture / train / infer.
let NODE_IDS = [9, 13];
const FIELD_LEN = 400; // signal_field.values padded/truncated to 400
const CSI_DIM = 4 + NODE_IDS.length * 3 + FIELD_LEN; // 4 + 6 + 400 = 410
let CSI_DIM = 4 + NODE_IDS.length * 3 + FIELD_LEN; // 4 global + 3/node + 400 field
function recomputeCsiDim(){ CSI_DIM = 4 + NODE_IDS.length * 3 + FIELD_LEN; }
let sensorsDetected = false; // true once a detect (auto/manual/restored) has locked the node set
let autoDetectStarted = false; // one-shot guard for the auto-detect on first live frame
const N_KP = 17, OUT_DIM = N_KP * 2; // 17 COCO keypoints -> 34 coords
const BASELINE_SECONDS = 10; // empty-room calibration window
const EPS = 1e-6;
@@ -333,9 +343,9 @@ async function selectBackend(){
// ============================================================================
// CSI vector construction — MUST match wiflow_capture.py csi_vector() exactly.
// [mean_rssi, variance, motion_band_power, breathing_band_power] (4 global)
// + for node 9 then node 13: [mean_rssi, variance, motion_band_power] (6 per-node)
// + for each node in NODE_IDS order: [mean_rssi, variance, motion_band_power] (3 per-node)
// + signal_field.values padded/truncated to 400 (400 field)
// = 410-d (RAW — baseline-normalization applied separately, see baselineNorm)
// = CSI_DIM-d (RAW — baseline-normalization applied separately, see baselineNorm)
// ============================================================================
function csiVector(frame){
const f = frame.features || {};
@@ -368,6 +378,87 @@ function baselineNorm(vecRaw){
return out;
}
// ============================================================================
// ESP32 sensor auto-detection
// Sniff the live /ws/sensing stream, find which node_ids are actually present
// and healthy, and lock that ordered set as the per-node schema (NODE_IDS/CSI_DIM).
// The node set defines the model's input dimension, so detection must run BEFORE
// calibration + capture; changing it invalidates a baseline/dataset built on a
// different set (we confirm, then reset, on a manual re-detect).
// ============================================================================
async function detectSensors(ms = 3000){
const tally = {}; // node_id -> { seen, fps, rssi }
let frames = 0;
const t0 = performance.now();
const el = $('detNodes'); if (el){ el.textContent = 'scanning…'; el.className = 'v'; }
while (performance.now() - t0 < ms){
if (latestCSI.frame && latestCSI.source === 'esp32'){
frames++;
for (const nf of (latestCSI.frame.node_features || [])){
const id = nf.node_id; if (id == null) continue;
const f = nf.features || {};
const t = (tally[id] || (tally[id] = { seen:0, fps:0, rssi:0 }));
t.seen++; t.fps += (+nf.frame_rate_hz || 0);
t.rssi += (+f.mean_rssi || +nf.rssi_dbm || 0);
}
}
await new Promise(r => setTimeout(r, 100));
}
// healthy = seen in >40% of sampled frames (filters transient / duplicate ids)
const healthy = Object.keys(tally).map(k => ({
id:+k, seen:tally[k].seen, fps:tally[k].fps/tally[k].seen, rssi:tally[k].rssi/tally[k].seen }))
.filter(n => n.seen >= Math.max(2, frames * 0.4))
.sort((a,b)=> a.id - b.id);
return { healthy, frames };
}
function renderDetectedSensors(list){
const el = $('detNodes'); if (!el) return;
el.textContent = list.length
? list.map(n => `#${n.id} (${Math.round(n.fps)}fps, ${Math.round(n.rssi)}dB)`).join(' · ')
: 'none found';
el.className = list.length ? 'v green' : 'v red';
}
async function runDetect(manual){
const { healthy, frames } = await detectSensors(manual ? 4000 : 3000);
if (!healthy.length){
const el = $('detNodes');
if (el){ el.textContent = frames ? 'no healthy nodes' : 'no live CSI (start sensing-server / esp32)';
el.className = 'v red'; }
return;
}
const ids = healthy.map(n => n.id);
const changed = ids.length !== NODE_IDS.length || ids.some((v,i)=> v !== NODE_IDS[i]);
if (changed && (baseline || SAMPLES.length)){
const ok = confirm(
`Detected sensors [${ids.join(', ')}] differ from the current set [${NODE_IDS.join(', ')}].\n\n` +
`The node set defines the model input, so switching invalidates the existing baseline` +
(SAMPLES.length ? ` and ${SAMPLES.length} captured samples` : ``) +
`. Reset and use the detected set?`);
if (!ok){ renderDetectedSensors(healthy); return; }
if (baseline){ baseline = null; stageDone.calibrate = false; idbDel('baseline');
$('calStatus').textContent = 'NOT CALIBRATED'; $('calStatus').className = 'v'; $('calBar').style.width = '0%'; }
if (SAMPLES.length){ SAMPLES = []; covCounts = new Array(BUCKETS.length).fill(0);
idbPut('samples', []); $('capN').textContent = '0'; $('trN').textContent = '0'; renderCoverage(); }
}
NODE_IDS = ids; recomputeCsiDim(); sensorsDetected = true;
idbPut('nodeIds', NODE_IDS);
renderDetectedSensors(healthy);
refreshGates();
}
async function restoreNodeIds(){
try{
const ids = await idbGet('nodeIds');
if (Array.isArray(ids) && ids.length){
NODE_IDS = ids.slice(); recomputeCsiDim(); sensorsDetected = true;
const el = $('detNodes');
if (el){ el.textContent = 'restored: ' + NODE_IDS.map(i => '#' + i).join(' '); el.className = 'v'; }
}
}catch(e){ /* ignore */ }
}
// ============================================================================
// CSI WebSocket
// ============================================================================
@@ -388,6 +479,11 @@ function connectCSI(){
source: src,
nodes: (d.nodes || []).map(n => n.node_id).filter(x => x != null).sort((a,b)=>a-b)
};
// auto-detect the sensor set once, on the first live frame, only when starting fresh
// (no baseline / no samples) so we never silently change a schema work is built on.
if (src === 'esp32' && !sensorsDetected && !autoDetectStarted && !baseline && SAMPLES.length === 0){
autoDetectStarted = true; runDetect(false);
}
if (src === 'esp32') banner('live','LIVE — real ESP32 CSI');
else banner('sim',`SIMULATED — not real (source=${src})`);
};
@@ -599,6 +695,7 @@ function finishCalibration(){
refreshGates();
}
$('calBtn').addEventListener('click', startCalibration);
$('detBtn').addEventListener('click', ()=> runDetect(true));
$('recalBtn').addEventListener('click', ()=>{ baseline = null; stageDone.calibrate = false;
$('calStatus').textContent = 'NOT CALIBRATED'; $('calStatus').className = 'v';
$('calBar').style.width = '0%'; $('calN').textContent = '0'; idbDel('baseline'); refreshGates(); startCalibration(); });
@@ -736,7 +833,7 @@ $('clrBtn').addEventListener('click', async ()=>{
$('expBtn').addEventListener('click', ()=>{
const out = {
format: 'wiflow-browser-dataset', version: 1, exported: new Date().toISOString(),
csi_dim: CSI_DIM, out_dim: OUT_DIM, buckets: BUCKETS,
csi_dim: CSI_DIM, out_dim: OUT_DIM, buckets: BUCKETS, nodes: NODE_IDS.slice(),
note: 'csi is baseline-normalized (ADR-151 deviation-from-baseline); kps are 17 COCO keypoints in [0,1] image coords',
samples: SAMPLES.map((s,i)=>({ csi: Array.from(s.csi), kps: Array.from(s.kps), bucket: s.bucket, t: (s.t!=null?s.t:i) }))
};
@@ -1152,6 +1249,7 @@ function inferLoop(){
(async function boot(){
connectCSI();
await selectBackend();
await restoreNodeIds(); // restore a previously-detected sensor set (fixes CSI_DIM before baseline)
await loadBaseline();
await idbLoad();
await loadModel();