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6 Commits
| Author | SHA1 | Message | Date | |
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 nai
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49fb2ca9f4 |
feat(ui): UI overhaul — consolidates #305-#309 (keyboard shortcuts, perf monitor, toasts, theme, command palette, activity log, data export, mobile PWA, accessibility, i18n) (#620)
* feat(ui): add keyboard shortcuts, perf monitor, toast system, theme toggle, and WCAG accessibility - Keyboard shortcuts overlay (press ? for help, 1-8 for tabs, T for theme, P for perf) - Real-time performance monitor with FPS, memory, latency sparklines (draggable) - Enhanced toast notification system with stacking, auto-dismiss, progress bars - Dark/light theme toggle with localStorage persistence and system preference detection - WCAG accessibility: skip-to-content link, ARIA roles/attributes on tabs and panels, arrow key navigation in tab bar, focus-visible outlines - ESLint config for UI directory with security and quality rules * feat(ui): add command palette, activity log, data export, fullscreen mode, connection status - Command palette (Ctrl+K / Cmd+K) with fuzzy search across tabs and actions - Activity log panel (L key) with real-time console interception, filters, resizable - Data export utility (E key) for sensor data as JSON/CSV with dialog - Fullscreen mode (F key / F11) for visualization tabs with exit button - Connection status widget in header showing WebSocket state and reconnect * feat(ui): add mobile hamburger nav, PWA support, and 40 unit tests - Mobile hamburger navigation: slide-out drawer replacing tab bar on <768px, swipe-to-close, animated hamburger icon, auto-sync with tab manager - PWA manifest + service worker: installable dashboard, offline shell caching (cache-first for static, network-first for API), auto-cleanup of old caches - 40 unit tests for ToastManager, ThemeToggle, KeyboardShortcuts, PerfMonitor, TabManager - browser-based test runner at ui/tests/unit-tests.html - PWA meta tags: theme-color, apple-mobile-web-app-capable, manifest link - Icon generator page for creating PWA icons (ui/icons/generate.html) * feat(ui): add URL routing, onboarding tour, idle detection, notification center - Hash router: tabs are bookmarkable/shareable via URL (#demo, #sensing, etc.), syncs with TabManager, supports browser back/forward navigation - Onboarding tour: interactive 6-step first-run walkthrough with spotlight highlighting, step indicators, skip/back/next controls, localStorage persistence - Idle detection: pauses health polling and reduces CSS animations after 3 min of inactivity, resumes on user interaction, integrates with Page Visibility API - Notification center: bell icon in header with unread badge, event history panel with mark-read/clear, persists across page views via sessionStorage * feat(ui): add i18n (EN/PL), screenshot tool, settings panel, reduced motion, uptime clock - i18n: English/Polish translations with auto-detection, language selector in header, data-i18n attributes on dashboard elements, localStorage persistence - Screenshot tool (S key): captures active tab to clipboard or downloads PNG, flash effect, canvas rendering with watermark, fallback for tainted canvases - Quick settings panel (gear icon): reduced motion toggle, high contrast mode, compact layout mode, health polling toggle, clear data, reset onboarding - Uptime clock: current time + session duration in header - prefers-reduced-motion: system-level and manual toggle, disables all animations and transitions for vestibular accessibility - High contrast mode: WCAG AAA compliant colors for both light and dark themes - Compact mode: condensed layout for dense information display |
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rUv
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7c1351fd5d |
feat(demo): wire all 6 RuVector WASM attention mechanisms into pose fusion
* feat: dual-modal WASM browser pose estimation demo (ADR-058) Live webcam video + WiFi CSI fusion for real-time pose estimation. Two parallel CNN pipelines (ruvector-cnn-wasm) with attention-weighted fusion and dynamic confidence gating. Three modes: Dual, Video-only, CSI-only. Includes pre-built WASM package (~52KB) for browser deployment. - ADR-058: Dual-modal architecture design - ui/pose-fusion.html: Main demo page with dark theme UI - 7 JS modules: video-capture, csi-simulator, cnn-embedder, fusion-engine, pose-decoder, canvas-renderer, main orchestrator - Pre-built ruvector-cnn-wasm WASM package for browser - CSI heatmap, embedding space visualization, latency metrics - WebSocket support for live ESP32 CSI data - Navigation link added to main dashboard Co-Authored-By: claude-flow <ruv@ruv.net> * fix: motion-responsive skeleton + through-wall CSI tracking - Pose decoder now uses per-cell motion grid to track actual arm/head positions — raising arms moves the skeleton's arms, head follows lateral movement - Motion grid (10x8 cells) tracks intensity per body zone: head, left/right arm upper/mid, legs - Through-wall mode: when person exits frame, CSI maintains presence with slow decay (~10s) and skeleton drifts in exit direction - CSI simulator persists sensing after video loss, ghost pose renders with decreasing confidence - Reduced temporal smoothing (0.45) for faster response to movement Co-Authored-By: claude-flow <ruv@ruv.net> * fix: video fills available space + correct WASM path resolution - Remove fixed aspect-ratio and max-height from video panel so it fills the available viewport space without scrolling - Grid uses 1fr row for content area, overflow:hidden on main grid - Fix WASM path: resolve relative to JS module file using import.meta.url instead of hardcoded ./pkg/ which resolved incorrectly on gh-pages - Responsive: mobile still gets aspect-ratio constraint Co-Authored-By: claude-flow <ruv@ruv.net> * feat: live ESP32 CSI pipeline + auto-connect WebSocket - Add auto-connect to local sensing server WebSocket (ws://localhost:8765) - Demo shows "Live ESP32" when connected to real CSI data - Add build_firmware.ps1 for native Windows ESP-IDF builds (no Docker) - Add read_serial.ps1 for ESP32 serial monitor Pipeline: ESP32 → UDP:5005 → sensing-server → WS:8765 → browser demo Co-Authored-By: claude-flow <ruv@ruv.net> * docs: add ADR-059 live ESP32 CSI pipeline + update README with demo links - ADR-059: Documents end-to-end ESP32 → sensing server → browser pipeline - README: Add dual-modal pose fusion demo link, update ADR count to 49 - References issue #245 Co-Authored-By: claude-flow <ruv@ruv.net> * feat: RSSI visualization, RuVector attention WASM, cache-bust fixes - Add animated RSSI Signal Strength panel with sparkline history - Fix RuVector WasmMultiHeadAttention retptr calling convention - Wire up RuVector Multi-Head + Flash Attention in CNN embedder - Add ambient temporal drift to CSI simulator for visible heatmap animation - Fix embedding space projection (sparse projection replaces cancelling sum) - Add auto-scaling to embedding space renderer - Add cache busters (?v=4) to all ES module imports to prevent stale caches - Add diagnostic logging for module version verification - Add RSSI tracking with quality labels and color-coded dBm display - Includes ruvector-attention-wasm v2.0.5 browser ESM wrapper Co-Authored-By: claude-flow <ruv@ruv.net> * feat: 26-keypoint dexterous pose + full RuVector attention pipeline Pose Decoder (17 → 26 keypoints): - Add finger approximations: thumb, index, pinky per hand (6 new) - Add toe tips: left/right foot index (2 new) - Add neck keypoint (1 new) - Hand openness driven by arm motion intensity - Finger positions computed from wrist-elbow axis angles CNN Embedder (full RuVector WASM pipeline): - Stage 1: Multi-Head Attention (global spatial reasoning) - Stage 2: Hyperbolic Attention (hierarchical body-part tree) - Stage 3: MoE Attention (3 experts: upper/lower/extremities, top-2) - Blended 40/30/30 weighting → final embedding projection Canvas Renderer: - Magenta finger joints with distinct glow - Cyan toe tips - White neck keypoint - Thinner limb lines for hand/foot connections - Joint count shown in overlay label CSI Simulator: - Skip synthetic person state when live ESP32 connected - Only simulate CSI data in demo mode (was already correct) Embedding Space: - Fixed projection: sparse 8-dim projection replaces cancelling sum - Auto-scaling normalizes point spread to fill canvas Cache busters bumped to v=5 on all imports. Co-Authored-By: claude-flow <ruv@ruv.net> * fix: centroid-based pose tracking for responsive limb movement Rewrites pose decoder from intensity-based to position-based tracking: - Arms now track toward motion centroid in each body zone - Elbow/wrist positions computed along shoulder→centroid vector - Legs track toward lower-body zone centroids - Smoothing reduced from 0.45 to 0.25 for responsiveness - Zone centroids blend 30% old / 70% new each frame 6 body zones with overlapping coverage: - Head (top 20%, center cols) - Left/Right Arm (rows 10-60%, outer cols) - Torso (rows 15-55%, center cols) - Left/Right Leg (rows 50-100%, half cols each) Hand openness now driven by arm spread distance + raise amount. Cache busters v=6. Co-Authored-By: claude-flow <ruv@ruv.net> * fix: remove duplicate lAnkleX/rAnkleX declarations in pose-decoder Stale code block from old intensity-based tracking was left behind, re-declaring variables already defined by centroid-based tracking. Co-Authored-By: claude-flow <ruv@ruv.net> * feat(demo): wire all 6 RuVector WASM attention mechanisms into pose fusion - Add WasmLinearAttention and WasmLocalGlobalAttention to browser ESM wrapper - Add 6 WASM utility functions (batch_normalize, pairwise_distances, etc.) - Extend CnnEmbedder to 6-stage pipeline: Flash → MHA → Hyperbolic → Linear → MoE → L+G - Use log-energy softmax blending across all 6 stages - Wire WASM cosine_similarity and normalize into FusionEngine - Add RuVector pipeline stats panel to UI (energy, refinement, pose impact) - Compute embedding-to-joint mapping stats without modifying joint positions - Center camera prompt with flexbox layout - Add cache busters v=12 Co-Authored-By: claude-flow <ruv@ruv.net> |
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ruv
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8b57a6f64c |
docs: update README with ADR-045–048, Observatory, adaptive classifier, AMOLED display
- Update ADR count from 44 to 48 - Add adaptive classifier (ADR-048) to Intelligence features - Add Observatory visualization (ADR-047) and AMOLED display (ADR-045) to Deployment features - Update screenshot to v2-screen.png - Add ADR-045 (AMOLED), ADR-046 (Android TV), ADR-047 (Observatory), DDD deployment model - Add AMOLED display firmware (display_hal, display_task, display_ui, LVGL config) - Add Observatory UI (13 Three.js modules, CSS, HTML entry point) - Add trained adaptive model JSON - Update .gitignore for managed_components, recordings, .swarm Co-Authored-By: claude-flow <ruv@ruv.net> |
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rUv
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113011e704 |
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> |
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ruv
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b7e0f07e6e |
feat: Sensing-only UI mode with Gaussian splat visualization and Rust migration ADR
- Add Python WebSocket sensing server (ws_server.py) with ESP32 UDP CSI and Windows RSSI auto-detect collectors on port 8765 - Add Three.js Gaussian splat renderer with custom GLSL shaders for real-time WiFi signal field visualization (blue→green→red gradient) - Add SensingTab component with RSSI sparkline, feature meters, and motion classification badge - Add sensing.service.js WebSocket client with reconnect and simulation fallback - Implement sensing-only mode: suppress all DensePose API calls when FastAPI backend (port 8000) is not running, clean console output - ADR-019: Document sensing-only UI architecture and data flow - ADR-020: Migrate AI/model inference to Rust with RuVector ONNX Runtime, replacing ~2.7GB Python stack with ~50MB static binary - Add ruvnet/ruvector as upstream remote for RuVector crate ecosystem Co-Authored-By: claude-flow <ruv@ruv.net> |
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rUv
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6fe0d42f90 | Add comprehensive CSS styles for UI components and dark mode support |