mirror of
https://github.com/ruvnet/RuView
synced 2026-08-06 19:51:43 +00:00
fix: WebSocket race condition, data source indicators, auto-start pose detection (#96)
* feat: RVF training pipeline & UI integration (ADR-036) Implement full model training, management, and inference pipeline: Backend (Rust): - recording.rs: CSI recording API (start/stop/list/download/delete) - model_manager.rs: RVF model loading, LoRA profile switching, model library - training_api.rs: Training API with WebSocket progress streaming, simulated training mode with realistic loss curves, auto-RVF export on completion - main.rs: Wire new modules, recording hooks in all CSI paths, data dirs UI (new components): - ModelPanel.js: Dark-mode model library with load/unload, LoRA dropdown - TrainingPanel.js: Recording controls, training config, live Canvas charts - model.service.js: Model REST API client with events - training.service.js: Training + recording API client with WebSocket progress UI (enhancements): - LiveDemoTab: Model selector, LoRA profile switcher, A/B split view toggle, training quick-panel with 60s recording shortcut - SettingsPanel: Full dark mode conversion (issue #92), model configuration (device, threads, auto-load), training configuration (epochs, LR, patience) - PoseDetectionCanvas: 10-frame pose trail with ghost keypoints and motion trajectory lines, cyan trail toggle button - pose.service.js: Model-inference confidence thresholds UI (plumbing): - index.html: Training tab (8th tab) - app.js: Panel initialization and tab routing - style.css: ~250 lines of training/model panel dark-mode styles 191 Rust tests pass, 0 failures. Closes #92. Refs: ADR-036, #93 Co-Authored-By: claude-flow <ruv@ruv.net> * fix: real RuVector training pipeline + UI service fixes Training pipeline (training_api.rs): - Replace simulated training with real signal-based training loop - Load actual CSI data from .csi.jsonl recordings or live frame history - Extract 180 features per frame: subcarrier amplitudes, temporal variance, Goertzel frequency analysis (9 bands), motion gradients, global stats - Train calibrated linear CSI-to-pose mapping via mini-batch gradient descent with L2 regularization (ridge regression), Xavier init, cosine LR decay - Self-supervised: teacher targets from derive_pose_from_sensing() heuristics - Real validation metrics: MSE and PCK@0.2 on 80/20 train/val split - Export trained .rvf with real weights, feature normalization stats, witness - Add infer_pose_from_model() for live inference from trained model - 16 new tests covering features, training, inference, serialization UI fixes: - Fix double-URL bug in model.service.js and training.service.js (buildApiUrl was called twice — once in service, once in apiService) - Fix route paths to match Rust backend (/api/v1/train/*, /api/v1/recording/*) - Fix request body formats (session_name, nested config object) - Fix top-level await in LiveDemoTab.js blocking module graph - Dynamic imports for ModelPanel/TrainingPanel in app.js - Center nav tabs with flex-wrap for 8-tab layout Co-Authored-By: claude-flow <ruv@ruv.net> * fix: WebSocket onOpen race condition, data source indicators, auto-start pose detection - Fix WebSocket onOpen race condition in websocket.service.js where setupEventHandlers replaced onopen after socket was already open, preventing pose service from receiving connection signal - Add 4-state data source indicator (LIVE/SIMULATED/RECONNECTING/OFFLINE) across Dashboard, Sensing, and Live Demo tabs via sensing.service.js - Add hot-plug ESP32 auto-detection in sensing server (auto mode runs both UDP listener and simulation, switches on ESP32_TIMEOUT) - Auto-start pose detection when backend is reachable - Hide duplicate PoseDetectionCanvas controls when enableControls=false - Add standalone Demo button in LiveDemoTab for offline animated demo - Add data source banner and status styling Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
rUv
+799
-10
@@ -4,6 +4,11 @@ import { PoseDetectionCanvas } from './PoseDetectionCanvas.js';
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import { poseService } from '../services/pose.service.js';
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import { streamService } from '../services/stream.service.js';
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import { wsService } from '../services/websocket.service.js';
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import { sensingService } from '../services/sensing.service.js';
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// Optional services - loaded lazily in init() to avoid blocking module graph
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let modelService = null;
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let trainingService = null;
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export class LiveDemoTab {
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constructor(containerElement) {
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@@ -32,6 +37,27 @@ export class LiveDemoTab {
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connectionAttempts: 0
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};
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// Model control state
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this.modelState = {
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models: [],
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activeModelId: null,
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activeModelInfo: null,
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loraProfiles: [],
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selectedLoraProfile: null,
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loading: false
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};
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// Training state
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this.trainingState = {
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status: 'idle', // 'idle' | 'training' | 'recording'
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epoch: 0,
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totalEpochs: 0,
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showTrainingPanel: false
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};
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// A/B split view state
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this.splitViewActive = false;
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this.subscriptions = [];
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this.logger = this.createLogger();
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@@ -58,7 +84,17 @@ export class LiveDemoTab {
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async init() {
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try {
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this.logger.info('Initializing LiveDemoTab component');
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// Load optional services (non-blocking)
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try {
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const mod = await import('../services/model.service.js');
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modelService = mod.modelService;
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} catch (e) { /* model features disabled */ }
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try {
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const mod = await import('../services/training.service.js');
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trainingService = mod.trainingService;
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} catch (e) { /* training features disabled */ }
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// Create enhanced DOM structure
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this.createEnhancedStructure();
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@@ -71,9 +107,31 @@ export class LiveDemoTab {
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// Set up monitoring and health checks
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this.setupMonitoring();
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// Fetch available models on init
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this.fetchModels();
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// Set up model/training event listeners
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this.setupServiceListeners();
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// Initialize state
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this.updateUI();
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// Auto-start pose detection when a backend is reachable.
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// Check after a brief delay (sensing WS may still be connecting).
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this._autoStartOnce = false;
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const tryAutoStart = () => {
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if (this._autoStartOnce || this.state.isActive) return;
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const ds = sensingService.dataSource;
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if (ds === 'live' || ds === 'server-simulated') {
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this._autoStartOnce = true;
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this.logger.info('Auto-starting pose detection (data source: ' + ds + ')');
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this.startDemo();
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}
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};
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setTimeout(tryAutoStart, 2000);
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// Also listen for sensing state changes in case server connects later
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this._autoStartUnsub = sensingService.onStateChange(tryAutoStart);
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this.logger.info('LiveDemoTab component initialized successfully');
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} catch (error) {
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this.logger.error('Failed to initialize LiveDemoTab', { error: error.message });
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@@ -88,6 +146,11 @@ export class LiveDemoTab {
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// Create enhanced structure if it doesn't exist
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const enhancedHTML = `
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<div class="live-demo-enhanced">
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<!-- Data source banner — prominent indicator for live vs simulated -->
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<div id="demo-source-banner" class="demo-source-banner demo-source-unknown" role="status" aria-live="polite">
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Detecting data source...
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</div>
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<div class="demo-header">
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<div class="demo-title">
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<h2>Live Human Pose Detection</h2>
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@@ -99,6 +162,7 @@ export class LiveDemoTab {
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<div class="demo-controls">
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<button class="btn btn--primary" id="start-enhanced-demo">Start Detection</button>
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<button class="btn btn--secondary" id="stop-enhanced-demo" disabled>Stop Detection</button>
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<button class="btn btn--accent" id="run-offline-demo">Demo</button>
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<button class="btn btn--primary" id="toggle-debug">Debug Mode</button>
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<select class="zone-select" id="zone-selector">
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<option value="zone_1">Zone 1</option>
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@@ -148,6 +212,49 @@ export class LiveDemoTab {
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</div>
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</div>
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<div class="model-control-panel" id="model-control-panel">
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<h4>Model Control</h4>
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<div class="setting-row-ld">
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<label class="ld-label">Model:</label>
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<select class="ld-select" id="model-selector">
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<option value="">Signal-Derived (no model)</option>
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</select>
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</div>
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<div class="model-info-row" id="model-active-info" style="display: none;">
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<span class="ld-label" id="model-active-name"></span>
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<span class="model-pck-badge" id="model-active-pck"></span>
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</div>
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<div class="setting-row-ld" id="lora-profile-row" style="display: none;">
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<label class="ld-label">LoRA Profile:</label>
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<select class="ld-select" id="lora-profile-selector">
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<option value="">None</option>
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</select>
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</div>
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<div class="model-actions">
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<button class="btn-ld btn-ld-accent" id="load-model-btn">Load Model</button>
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<button class="btn-ld btn-ld-muted" id="unload-model-btn" disabled>Unload</button>
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</div>
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<div class="model-status-text" id="model-status-text">No model loaded</div>
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</div>
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<div class="split-view-panel">
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<div class="setting-row-ld">
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<label class="ld-label">Compare: Signal vs Model</label>
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<button class="btn-ld btn-ld-toggle" id="split-view-toggle" disabled>Off</button>
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</div>
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</div>
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<div class="training-quick-panel" id="training-quick-panel">
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<h4>Training</h4>
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<div class="training-status-row">
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<span class="training-status-badge" id="training-status-badge">Idle</span>
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</div>
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<div class="training-actions">
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<button class="btn-ld btn-ld-accent" id="open-training-panel-btn">Open Training Panel</button>
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<button class="btn-ld btn-ld-muted" id="quick-record-btn">Record 60s</button>
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</div>
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</div>
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<div class="setup-guide-panel">
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<h4>Setup Guide</h4>
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<div class="setup-levels">
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@@ -606,6 +713,270 @@ export class LiveDemoTab {
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border-radius: 3px;
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font-size: 10px;
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}
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/* Model Control Panel */
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.model-control-panel,
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.split-view-panel,
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.training-quick-panel {
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background: rgba(17, 24, 39, 0.9);
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border: 1px solid rgba(56, 68, 89, 0.6);
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border-radius: 12px;
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padding: 16px;
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}
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.model-control-panel h4,
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.training-quick-panel h4 {
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margin: 0 0 12px 0;
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color: #e0e0e0;
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font-size: 14px;
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font-weight: 600;
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}
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.setting-row-ld {
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display: flex;
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justify-content: space-between;
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align-items: center;
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margin-bottom: 10px;
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gap: 8px;
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}
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.ld-label {
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color: #8899aa;
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font-size: 11px;
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flex-shrink: 0;
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}
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.ld-select {
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flex: 1;
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padding: 6px 10px;
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border: 1px solid rgba(56, 68, 89, 0.6);
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border-radius: 6px;
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background: rgba(15, 20, 35, 0.8);
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color: #b0b8c8;
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font-size: 12px;
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cursor: pointer;
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min-width: 0;
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}
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.ld-select:focus {
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outline: none;
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border-color: #667eea;
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box-shadow: 0 0 0 2px rgba(102, 126, 234, 0.15);
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}
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.ld-select option {
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background: #1a2234;
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color: #c8d0dc;
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}
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.model-info-row {
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display: flex;
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justify-content: space-between;
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align-items: center;
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margin-bottom: 10px;
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padding: 6px 8px;
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background: rgba(30, 40, 60, 0.6);
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border-radius: 6px;
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}
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.model-pck-badge {
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font-size: 11px;
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font-weight: 600;
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padding: 2px 8px;
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border-radius: 8px;
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background: rgba(102, 126, 234, 0.15);
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color: #8ea4f0;
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}
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.model-actions,
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.training-actions {
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display: flex;
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gap: 8px;
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margin-top: 10px;
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}
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.btn-ld {
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flex: 1;
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padding: 7px 12px;
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border: 1px solid rgba(255, 255, 255, 0.1);
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border-radius: 8px;
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font-size: 12px;
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font-weight: 500;
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cursor: pointer;
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transition: all 0.2s ease;
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text-align: center;
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}
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.btn-ld:disabled {
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opacity: 0.4;
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cursor: not-allowed;
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}
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.btn-ld-accent {
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background: rgba(102, 126, 234, 0.15);
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color: #8ea4f0;
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border-color: rgba(102, 126, 234, 0.3);
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}
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.btn-ld-accent:hover:not(:disabled) {
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background: rgba(102, 126, 234, 0.25);
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border-color: rgba(102, 126, 234, 0.5);
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}
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.btn-ld-muted {
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background: rgba(30, 40, 60, 0.8);
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color: #8899aa;
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border-color: rgba(255, 255, 255, 0.08);
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}
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.btn-ld-muted:hover:not(:disabled) {
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background: rgba(40, 50, 70, 0.9);
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color: #b0b8c8;
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}
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.btn-ld-toggle {
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min-width: 44px;
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flex: 0;
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padding: 4px 10px;
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background: rgba(30, 40, 60, 0.8);
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color: #8899aa;
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border-color: rgba(255, 255, 255, 0.08);
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border-radius: 12px;
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font-size: 11px;
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}
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.btn-ld-toggle.active {
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background: rgba(0, 212, 255, 0.15);
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color: #00d4ff;
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border-color: rgba(0, 212, 255, 0.4);
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}
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.model-status-text {
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margin-top: 8px;
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font-size: 11px;
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color: #6b7a8d;
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}
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.training-status-row {
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margin-bottom: 8px;
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}
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.training-status-badge {
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display: inline-block;
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padding: 3px 10px;
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border-radius: 10px;
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font-size: 11px;
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font-weight: 600;
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text-transform: uppercase;
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letter-spacing: 0.4px;
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background: rgba(108, 117, 125, 0.15);
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color: #8899aa;
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border: 1px solid rgba(108, 117, 125, 0.3);
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}
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.training-status-badge.training {
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background: rgba(251, 191, 36, 0.12);
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color: #fbbf24;
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border-color: rgba(251, 191, 36, 0.3);
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}
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.training-status-badge.recording {
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background: rgba(239, 68, 68, 0.12);
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color: #ef4444;
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border-color: rgba(239, 68, 68, 0.3);
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animation: pulse 1.5s ease-in-out infinite;
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}
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|
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/* A/B Split View Overlay */
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.split-view-divider {
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position: absolute;
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top: 0;
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bottom: 0;
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left: 50%;
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width: 2px;
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background: repeating-linear-gradient(
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to bottom,
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rgba(255, 255, 255, 0.4) 0px,
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rgba(255, 255, 255, 0.4) 6px,
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transparent 6px,
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transparent 12px
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);
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z-index: 15;
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pointer-events: none;
|
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}
|
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|
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.split-view-label {
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position: absolute;
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top: 8px;
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||||
z-index: 16;
|
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font-size: 10px;
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font-weight: 600;
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text-transform: uppercase;
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letter-spacing: 0.5px;
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padding: 3px 8px;
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border-radius: 4px;
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pointer-events: none;
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}
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|
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.split-view-label.left {
|
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left: 8px;
|
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background: rgba(0, 204, 136, 0.2);
|
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color: #00cc88;
|
||||
}
|
||||
|
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.split-view-label.right {
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right: 8px;
|
||||
background: rgba(102, 126, 234, 0.2);
|
||||
color: #8ea4f0;
|
||||
}
|
||||
|
||||
/* Training modal overlay */
|
||||
.training-panel-overlay {
|
||||
position: fixed;
|
||||
top: 0;
|
||||
left: 0;
|
||||
right: 0;
|
||||
bottom: 0;
|
||||
background: rgba(0, 0, 0, 0.7);
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
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||||
z-index: 1000;
|
||||
}
|
||||
|
||||
.training-panel-modal {
|
||||
background: #0d1117;
|
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border: 1px solid rgba(56, 68, 89, 0.6);
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border-radius: 12px;
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||||
padding: 24px;
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min-width: 400px;
|
||||
max-width: 600px;
|
||||
max-height: 80vh;
|
||||
overflow-y: auto;
|
||||
color: #e0e0e0;
|
||||
}
|
||||
|
||||
.training-panel-modal h3 {
|
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margin: 0 0 16px 0;
|
||||
font-size: 18px;
|
||||
color: #e0e0e0;
|
||||
}
|
||||
|
||||
.training-panel-modal .close-btn {
|
||||
float: right;
|
||||
background: rgba(30, 40, 60, 0.8);
|
||||
border: 1px solid rgba(255, 255, 255, 0.1);
|
||||
color: #8899aa;
|
||||
border-radius: 6px;
|
||||
padding: 4px 10px;
|
||||
cursor: pointer;
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
.training-panel-modal .close-btn:hover {
|
||||
background: rgba(50, 60, 80, 0.9);
|
||||
color: #c8d0dc;
|
||||
}
|
||||
`;
|
||||
|
||||
if (!document.querySelector('#live-demo-enhanced-styles')) {
|
||||
@@ -664,6 +1035,16 @@ export class LiveDemoTab {
|
||||
stopBtn.addEventListener('click', () => this.stopDemo());
|
||||
}
|
||||
|
||||
// Offline demo button — runs client-side animated demo (no server needed)
|
||||
const offlineDemoBtn = this.container.querySelector('#run-offline-demo');
|
||||
if (offlineDemoBtn) {
|
||||
offlineDemoBtn.addEventListener('click', () => {
|
||||
if (this.components.poseCanvas) {
|
||||
this.components.poseCanvas.toggleDemo();
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
if (debugBtn) {
|
||||
debugBtn.addEventListener('click', () => this.toggleDebugMode());
|
||||
}
|
||||
@@ -690,6 +1071,9 @@ export class LiveDemoTab {
|
||||
exportLogsBtn.addEventListener('click', () => this.exportLogs());
|
||||
}
|
||||
|
||||
// Model, training, and split-view controls
|
||||
this.setupModelTrainingControls();
|
||||
|
||||
this.logger.debug('Enhanced controls set up');
|
||||
}
|
||||
|
||||
@@ -706,6 +1090,23 @@ export class LiveDemoTab {
|
||||
this.updateMetricsDisplay();
|
||||
}, 1000);
|
||||
|
||||
// Subscribe to sensing service for data-source changes
|
||||
this._sensingStateUnsub = sensingService.onStateChange(() => {
|
||||
this.updateSourceBanner();
|
||||
this.updateStatusIndicator();
|
||||
});
|
||||
// Throttle data-based banner updates (frames arrive at 10Hz)
|
||||
let lastBannerUpdate = 0;
|
||||
this._sensingDataUnsub = sensingService.onData(() => {
|
||||
const now = Date.now();
|
||||
if (now - lastBannerUpdate > 2000) {
|
||||
lastBannerUpdate = now;
|
||||
this.updateSourceBanner();
|
||||
}
|
||||
});
|
||||
// Initial banner update
|
||||
this.updateSourceBanner();
|
||||
|
||||
this.logger.debug('Monitoring set up');
|
||||
}
|
||||
|
||||
@@ -901,17 +1302,40 @@ export class LiveDemoTab {
|
||||
}
|
||||
|
||||
getStatusClass() {
|
||||
if (this.state.isActive) {
|
||||
return this.state.connectionState === 'connected' ? 'active' : 'connecting';
|
||||
if (!this.state.isActive) {
|
||||
return this.state.connectionState === 'error' ? 'error' : '';
|
||||
}
|
||||
return this.state.connectionState === 'error' ? 'error' : '';
|
||||
const ds = sensingService.dataSource;
|
||||
if (ds === 'live') return 'active';
|
||||
if (ds === 'server-simulated') return 'sim';
|
||||
return 'connecting';
|
||||
}
|
||||
|
||||
getStatusText() {
|
||||
if (this.state.isActive) {
|
||||
return this.state.connectionState === 'connected' ? 'Active' : 'Connecting...';
|
||||
if (!this.state.isActive) {
|
||||
return this.state.connectionState === 'error' ? 'Error' : 'Ready';
|
||||
}
|
||||
return this.state.connectionState === 'error' ? 'Error' : 'Ready';
|
||||
const ds = sensingService.dataSource;
|
||||
if (ds === 'live') return 'Active \u2014 ESP32 Live';
|
||||
if (ds === 'server-simulated') return 'Active \u2014 Simulated Data';
|
||||
if (ds === 'simulated') return 'Active \u2014 Offline Simulation';
|
||||
return 'Connecting...';
|
||||
}
|
||||
|
||||
/** Update the prominent data-source banner at the top of Live Demo. */
|
||||
updateSourceBanner() {
|
||||
const banner = this.container.querySelector('#demo-source-banner');
|
||||
if (!banner) return;
|
||||
const ds = sensingService.dataSource;
|
||||
const config = {
|
||||
'live': { text: 'LIVE \u2014 ESP32 Hardware Connected', cls: 'demo-source-live' },
|
||||
'server-simulated': { text: 'SIMULATED DATA \u2014 No Hardware Detected', cls: 'demo-source-sim' },
|
||||
'reconnecting': { text: 'RECONNECTING TO SERVER...', cls: 'demo-source-reconnecting' },
|
||||
'simulated': { text: 'OFFLINE \u2014 Server Unreachable, Local Sim', cls: 'demo-source-offline' },
|
||||
};
|
||||
const cfg = config[ds] || config['reconnecting'];
|
||||
banner.textContent = cfg.text;
|
||||
banner.className = 'demo-source-banner ' + cfg.cls;
|
||||
}
|
||||
|
||||
updateControls() {
|
||||
@@ -942,8 +1366,20 @@ export class LiveDemoTab {
|
||||
};
|
||||
|
||||
if (elements.connectionStatus) {
|
||||
elements.connectionStatus.textContent = this.state.connectionState;
|
||||
elements.connectionStatus.className = `health-${this.getHealthClass(this.state.connectionState)}`;
|
||||
const ds = sensingService.dataSource;
|
||||
const dsLabels = {
|
||||
'live': 'Connected \u2014 ESP32',
|
||||
'server-simulated': 'Connected \u2014 Simulated',
|
||||
'reconnecting': 'Reconnecting...',
|
||||
'simulated': 'Offline \u2014 Simulated',
|
||||
};
|
||||
const label = dsLabels[ds] || this.state.connectionState;
|
||||
elements.connectionStatus.textContent = label;
|
||||
const cls = ds === 'live' ? 'good'
|
||||
: ds === 'server-simulated' ? 'sim'
|
||||
: ds === 'simulated' ? 'bad'
|
||||
: this.getHealthClass(this.state.connectionState);
|
||||
elements.connectionStatus.className = `health-${cls}`;
|
||||
}
|
||||
|
||||
if (elements.frameCount) {
|
||||
@@ -1061,6 +1497,356 @@ export class LiveDemoTab {
|
||||
}
|
||||
}
|
||||
|
||||
// --- Model Control Methods ---
|
||||
|
||||
async fetchModels() {
|
||||
if (!modelService) return;
|
||||
try {
|
||||
const data = await modelService.listModels();
|
||||
this.modelState.models = data?.models || [];
|
||||
this.populateModelSelector();
|
||||
// Check if a model is already active
|
||||
const active = await modelService.getActiveModel();
|
||||
if (active && active.model_id) {
|
||||
this.modelState.activeModelId = active.model_id;
|
||||
this.modelState.activeModelInfo = active;
|
||||
this.updateModelUI();
|
||||
}
|
||||
} catch (error) {
|
||||
this.logger.warn('Could not fetch models', { error: error.message });
|
||||
}
|
||||
}
|
||||
|
||||
populateModelSelector() {
|
||||
const selector = this.container.querySelector('#model-selector');
|
||||
if (!selector) return;
|
||||
// Keep the first "Signal-Derived" option
|
||||
selector.innerHTML = '<option value="">Signal-Derived (no model)</option>';
|
||||
this.modelState.models.forEach(model => {
|
||||
const opt = document.createElement('option');
|
||||
opt.value = model.id || model.model_id || model.name;
|
||||
opt.textContent = model.name || model.id || 'Unknown Model';
|
||||
selector.appendChild(opt);
|
||||
});
|
||||
if (this.modelState.activeModelId) {
|
||||
selector.value = this.modelState.activeModelId;
|
||||
}
|
||||
}
|
||||
|
||||
async handleLoadModel() {
|
||||
if (!modelService) return;
|
||||
const selector = this.container.querySelector('#model-selector');
|
||||
const modelId = selector?.value;
|
||||
if (!modelId) {
|
||||
this.setModelStatus('Select a model first');
|
||||
return;
|
||||
}
|
||||
try {
|
||||
this.modelState.loading = true;
|
||||
this.setModelStatus('Loading...');
|
||||
const loadBtn = this.container.querySelector('#load-model-btn');
|
||||
if (loadBtn) loadBtn.disabled = true;
|
||||
|
||||
await modelService.loadModel(modelId);
|
||||
this.modelState.activeModelId = modelId;
|
||||
|
||||
// Try to fetch full info
|
||||
try {
|
||||
const info = await modelService.getModel(modelId);
|
||||
this.modelState.activeModelInfo = info;
|
||||
} catch (e) {
|
||||
this.modelState.activeModelInfo = { model_id: modelId };
|
||||
}
|
||||
|
||||
// Fetch LoRA profiles
|
||||
try {
|
||||
const profiles = await modelService.getLoraProfiles();
|
||||
this.modelState.loraProfiles = profiles || [];
|
||||
} catch (e) {
|
||||
this.modelState.loraProfiles = [];
|
||||
}
|
||||
|
||||
this.modelState.loading = false;
|
||||
this.updateModelUI();
|
||||
this.updateSplitViewAvailability();
|
||||
|
||||
// Update pose source badge to model inference
|
||||
this.setState({ poseSource: 'model_inference' });
|
||||
|
||||
} catch (error) {
|
||||
this.modelState.loading = false;
|
||||
this.setModelStatus(`Error: ${error.message}`);
|
||||
const loadBtn = this.container.querySelector('#load-model-btn');
|
||||
if (loadBtn) loadBtn.disabled = false;
|
||||
this.logger.error('Failed to load model', { error: error.message });
|
||||
}
|
||||
}
|
||||
|
||||
async handleUnloadModel() {
|
||||
if (!modelService) return;
|
||||
try {
|
||||
await modelService.unloadModel();
|
||||
this.modelState.activeModelId = null;
|
||||
this.modelState.activeModelInfo = null;
|
||||
this.modelState.loraProfiles = [];
|
||||
this.modelState.selectedLoraProfile = null;
|
||||
this.updateModelUI();
|
||||
this.updateSplitViewAvailability();
|
||||
this.disableSplitView();
|
||||
this.setState({ poseSource: 'signal_derived' });
|
||||
} catch (error) {
|
||||
this.setModelStatus(`Error: ${error.message}`);
|
||||
this.logger.error('Failed to unload model', { error: error.message });
|
||||
}
|
||||
}
|
||||
|
||||
async handleLoraProfileChange(profileName) {
|
||||
if (!modelService || !this.modelState.activeModelId) return;
|
||||
if (!profileName) return;
|
||||
try {
|
||||
await modelService.activateLoraProfile(this.modelState.activeModelId, profileName);
|
||||
this.modelState.selectedLoraProfile = profileName;
|
||||
this.setModelStatus(`LoRA: ${profileName} active`);
|
||||
} catch (error) {
|
||||
this.setModelStatus(`LoRA error: ${error.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
updateModelUI() {
|
||||
const loadBtn = this.container.querySelector('#load-model-btn');
|
||||
const unloadBtn = this.container.querySelector('#unload-model-btn');
|
||||
const infoRow = this.container.querySelector('#model-active-info');
|
||||
const nameEl = this.container.querySelector('#model-active-name');
|
||||
const pckEl = this.container.querySelector('#model-active-pck');
|
||||
const loraRow = this.container.querySelector('#lora-profile-row');
|
||||
const loraSel = this.container.querySelector('#lora-profile-selector');
|
||||
|
||||
const isLoaded = !!this.modelState.activeModelId;
|
||||
|
||||
if (loadBtn) loadBtn.disabled = isLoaded;
|
||||
if (unloadBtn) unloadBtn.disabled = !isLoaded;
|
||||
|
||||
if (infoRow) {
|
||||
infoRow.style.display = isLoaded ? 'flex' : 'none';
|
||||
}
|
||||
|
||||
if (isLoaded && this.modelState.activeModelInfo) {
|
||||
const info = this.modelState.activeModelInfo;
|
||||
const name = info.name || info.model_id || this.modelState.activeModelId;
|
||||
const version = info.version ? ` v${info.version}` : '';
|
||||
const pck = info.pck_score != null ? info.pck_score.toFixed(2) : '--';
|
||||
if (nameEl) nameEl.textContent = `${name}${version}`;
|
||||
if (pckEl) pckEl.textContent = `PCK: ${pck}`;
|
||||
this.setModelStatus(`Model: ${name} (PCK: ${pck})`);
|
||||
} else if (!isLoaded) {
|
||||
this.setModelStatus('No model loaded');
|
||||
}
|
||||
|
||||
// LoRA profiles
|
||||
if (loraRow && loraSel) {
|
||||
if (isLoaded && this.modelState.loraProfiles.length > 0) {
|
||||
loraRow.style.display = 'flex';
|
||||
loraSel.innerHTML = '<option value="">None</option>';
|
||||
this.modelState.loraProfiles.forEach(profile => {
|
||||
const opt = document.createElement('option');
|
||||
opt.value = profile.name || profile;
|
||||
opt.textContent = profile.name || profile;
|
||||
loraSel.appendChild(opt);
|
||||
});
|
||||
} else {
|
||||
loraRow.style.display = 'none';
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
setModelStatus(text) {
|
||||
const el = this.container.querySelector('#model-status-text');
|
||||
if (el) el.textContent = text;
|
||||
}
|
||||
|
||||
// --- A/B Split View Methods ---
|
||||
|
||||
updateSplitViewAvailability() {
|
||||
const toggle = this.container.querySelector('#split-view-toggle');
|
||||
if (toggle) {
|
||||
toggle.disabled = !this.modelState.activeModelId;
|
||||
}
|
||||
}
|
||||
|
||||
toggleSplitView() {
|
||||
if (!this.modelState.activeModelId) return;
|
||||
this.splitViewActive = !this.splitViewActive;
|
||||
const toggle = this.container.querySelector('#split-view-toggle');
|
||||
if (toggle) {
|
||||
toggle.textContent = this.splitViewActive ? 'On' : 'Off';
|
||||
toggle.classList.toggle('active', this.splitViewActive);
|
||||
}
|
||||
this.updateSplitViewOverlay();
|
||||
}
|
||||
|
||||
disableSplitView() {
|
||||
this.splitViewActive = false;
|
||||
const toggle = this.container.querySelector('#split-view-toggle');
|
||||
if (toggle) {
|
||||
toggle.textContent = 'Off';
|
||||
toggle.classList.remove('active');
|
||||
}
|
||||
this.updateSplitViewOverlay();
|
||||
}
|
||||
|
||||
updateSplitViewOverlay() {
|
||||
const mainContainer = this.container.querySelector('.pose-detection-container');
|
||||
if (!mainContainer) return;
|
||||
|
||||
// Remove existing overlays
|
||||
mainContainer.querySelectorAll('.split-view-divider, .split-view-label').forEach(el => el.remove());
|
||||
|
||||
if (this.splitViewActive) {
|
||||
const divider = document.createElement('div');
|
||||
divider.className = 'split-view-divider';
|
||||
mainContainer.appendChild(divider);
|
||||
|
||||
const leftLabel = document.createElement('div');
|
||||
leftLabel.className = 'split-view-label left';
|
||||
leftLabel.textContent = 'Signal-Derived';
|
||||
mainContainer.appendChild(leftLabel);
|
||||
|
||||
const rightLabel = document.createElement('div');
|
||||
rightLabel.className = 'split-view-label right';
|
||||
rightLabel.textContent = 'Model Inference';
|
||||
mainContainer.appendChild(rightLabel);
|
||||
}
|
||||
}
|
||||
|
||||
// --- Training Quick-Panel Methods ---
|
||||
|
||||
updateTrainingStatus() {
|
||||
const badge = this.container.querySelector('#training-status-badge');
|
||||
if (!badge) return;
|
||||
|
||||
const state = this.trainingState.status;
|
||||
badge.classList.remove('training', 'recording');
|
||||
|
||||
if (state === 'training') {
|
||||
badge.classList.add('training');
|
||||
badge.textContent = `Training epoch ${this.trainingState.epoch}/${this.trainingState.totalEpochs}`;
|
||||
} else if (state === 'recording') {
|
||||
badge.classList.add('recording');
|
||||
badge.textContent = 'Recording...';
|
||||
} else {
|
||||
badge.textContent = 'Idle';
|
||||
}
|
||||
}
|
||||
|
||||
async handleQuickRecord() {
|
||||
if (!trainingService) {
|
||||
this.logger.warn('Training service not available');
|
||||
return;
|
||||
}
|
||||
try {
|
||||
await trainingService.startRecording({ session_name: `quick_${Date.now()}`, duration_secs: 60 });
|
||||
this.trainingState.status = 'recording';
|
||||
this.updateTrainingStatus();
|
||||
// Auto-reset after ~65 seconds
|
||||
setTimeout(() => {
|
||||
if (this.trainingState.status === 'recording') {
|
||||
this.trainingState.status = 'idle';
|
||||
this.updateTrainingStatus();
|
||||
}
|
||||
}, 65000);
|
||||
} catch (error) {
|
||||
this.logger.error('Quick record failed', { error: error.message });
|
||||
}
|
||||
}
|
||||
|
||||
showTrainingPanel() {
|
||||
// Create a simple modal overlay for the training panel
|
||||
const existing = document.querySelector('.training-panel-overlay');
|
||||
if (existing) existing.remove();
|
||||
|
||||
const overlay = document.createElement('div');
|
||||
overlay.className = 'training-panel-overlay';
|
||||
overlay.innerHTML = `
|
||||
<div class="training-panel-modal">
|
||||
<button class="close-btn" id="close-training-modal">Close</button>
|
||||
<h3>Training Panel</h3>
|
||||
<p style="color: #8899aa; font-size: 13px; margin-bottom: 16px;">
|
||||
Configure and start model training from here. Connect to the backend training API to manage epochs, datasets, and checkpoints.
|
||||
</p>
|
||||
<div style="display: flex; flex-direction: column; gap: 10px;">
|
||||
<div class="setting-row-ld">
|
||||
<label class="ld-label" style="flex: 1;">Status:</label>
|
||||
<span style="color: #c8d0dc; font-size: 12px;">${this.trainingState.status}</span>
|
||||
</div>
|
||||
<div class="setting-row-ld">
|
||||
<label class="ld-label" style="flex: 1;">Training service:</label>
|
||||
<span style="color: ${trainingService ? '#00cc88' : '#ef4444'}; font-size: 12px;">${trainingService ? 'Connected' : 'Not available'}</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
`;
|
||||
|
||||
document.body.appendChild(overlay);
|
||||
|
||||
// Close handler
|
||||
overlay.querySelector('#close-training-modal').addEventListener('click', () => overlay.remove());
|
||||
overlay.addEventListener('click', (e) => {
|
||||
if (e.target === overlay) overlay.remove();
|
||||
});
|
||||
}
|
||||
|
||||
// --- Service Event Listeners ---
|
||||
|
||||
setupServiceListeners() {
|
||||
if (modelService) {
|
||||
const unsub1 = modelService.on('model-loaded', (data) => {
|
||||
this.logger.info('Model loaded event', data);
|
||||
});
|
||||
const unsub2 = modelService.on('model-unloaded', () => {
|
||||
this.modelState.activeModelId = null;
|
||||
this.modelState.activeModelInfo = null;
|
||||
this.updateModelUI();
|
||||
this.disableSplitView();
|
||||
});
|
||||
this.subscriptions.push(unsub1, unsub2);
|
||||
}
|
||||
|
||||
if (trainingService) {
|
||||
const unsub3 = trainingService.on('progress', (data) => {
|
||||
if (data && data.epoch != null) {
|
||||
this.trainingState.epoch = data.epoch;
|
||||
this.trainingState.totalEpochs = data.total_epochs || data.totalEpochs || this.trainingState.totalEpochs;
|
||||
this.trainingState.status = 'training';
|
||||
this.updateTrainingStatus();
|
||||
}
|
||||
});
|
||||
const unsub4 = trainingService.on('training-stopped', () => {
|
||||
this.trainingState.status = 'idle';
|
||||
this.updateTrainingStatus();
|
||||
});
|
||||
this.subscriptions.push(unsub3, unsub4);
|
||||
}
|
||||
}
|
||||
|
||||
// --- Enhanced Controls Setup ---
|
||||
|
||||
setupModelTrainingControls() {
|
||||
// Model control buttons
|
||||
const loadBtn = this.container.querySelector('#load-model-btn');
|
||||
const unloadBtn = this.container.querySelector('#unload-model-btn');
|
||||
const loraSel = this.container.querySelector('#lora-profile-selector');
|
||||
const splitToggle = this.container.querySelector('#split-view-toggle');
|
||||
const openTrainingBtn = this.container.querySelector('#open-training-panel-btn');
|
||||
const quickRecordBtn = this.container.querySelector('#quick-record-btn');
|
||||
|
||||
if (loadBtn) loadBtn.addEventListener('click', () => this.handleLoadModel());
|
||||
if (unloadBtn) unloadBtn.addEventListener('click', () => this.handleUnloadModel());
|
||||
if (loraSel) loraSel.addEventListener('change', (e) => this.handleLoraProfileChange(e.target.value));
|
||||
if (splitToggle) splitToggle.addEventListener('click', () => this.toggleSplitView());
|
||||
if (openTrainingBtn) openTrainingBtn.addEventListener('click', () => this.showTrainingPanel());
|
||||
if (quickRecordBtn) quickRecordBtn.addEventListener('click', () => this.handleQuickRecord());
|
||||
}
|
||||
|
||||
// Clean up
|
||||
dispose() {
|
||||
try {
|
||||
@@ -1088,6 +1874,9 @@ export class LiveDemoTab {
|
||||
// Unsubscribe from services
|
||||
this.subscriptions.forEach(unsubscribe => unsubscribe());
|
||||
this.subscriptions = [];
|
||||
if (this._sensingStateUnsub) this._sensingStateUnsub();
|
||||
if (this._sensingDataUnsub) this._sensingDataUnsub();
|
||||
if (this._autoStartUnsub) this._autoStartUnsub();
|
||||
|
||||
this.logger.info('LiveDemoTab component disposed successfully');
|
||||
} catch (error) {
|
||||
|
||||
Reference in New Issue
Block a user