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| /** | |
| * 3D Face Mapper Module v1.0 | |
| * Provides 3D face mapping, reconstruction and analysis capabilities for MorphGuard | |
| * Using Three.js, Tensorflow.js and WebAssembly for optimal performance | |
| */ | |
| class FaceMapper3D { | |
| constructor(options = {}) { | |
| // Configuration | |
| this.config = Object.assign({ | |
| canvasId: '3d-face-canvas', | |
| wasmPath: '/static/wasm/', | |
| modelPath: '/static/models/face_landmark/', | |
| detectPoints: 478, // Full face mesh landmark points | |
| scanQuality: 'standard', // rapid, standard, detailed | |
| enableWasm: true, | |
| enableDroneControl: true | |
| }, options); | |
| // State | |
| this.status = { | |
| initialized: false, | |
| modelLoaded: false, | |
| scanning: false, | |
| reconstructing: false, | |
| droneConnected: false, | |
| capturedImages: [], | |
| currentScanId: null, | |
| processingStage: 'idle', // idle, capture, sfm, reconstruction, analysis | |
| error: null | |
| }; | |
| // Three.js objects | |
| this.scene = null; | |
| this.camera = null; | |
| this.renderer = null; | |
| this.controls = null; | |
| this.model = null; | |
| // Face mesh detection | |
| this.faceMeshModel = null; | |
| // WebAssembly module | |
| this.wasmModule = null; | |
| // Initialize | |
| this.init(); | |
| } | |
| /** | |
| * Initialize the 3D face mapper | |
| */ | |
| async init() { | |
| try { | |
| // Initialize Three.js scene | |
| this.initScene(); | |
| // Load TensorFlow.js and face mesh model | |
| await this.loadFaceMeshModel(); | |
| // Initialize WebAssembly module if enabled | |
| if (this.config.enableWasm) { | |
| await this.initWasmModule(); | |
| } | |
| // Set up event listeners | |
| this.setupEventListeners(); | |
| // Mark as initialized | |
| this.status.initialized = true; | |
| // Trigger initialized event | |
| this.triggerEvent('initialized'); | |
| } catch (error) { | |
| console.error('Error initializing 3D Face Mapper:', error); | |
| this.status.error = error.message; | |
| this.triggerEvent('error', { error }); | |
| } | |
| } | |
| /** | |
| * Initialize Three.js scene | |
| */ | |
| initScene() { | |
| // Get canvas | |
| const canvas = document.getElementById(this.config.canvasId); | |
| if (!canvas) { | |
| throw new Error(`Canvas with ID ${this.config.canvasId} not found`); | |
| } | |
| // Create scene | |
| this.scene = new THREE.Scene(); | |
| this.scene.background = new THREE.Color(0x111827); | |
| // Create camera | |
| this.camera = new THREE.PerspectiveCamera( | |
| 75, | |
| canvas.clientWidth / canvas.clientHeight, | |
| 0.1, | |
| 1000 | |
| ); | |
| this.camera.position.z = 2; | |
| // Create renderer | |
| this.renderer = new THREE.WebGLRenderer({ | |
| canvas, | |
| antialias: true, | |
| alpha: true | |
| }); | |
| this.renderer.setSize(canvas.clientWidth, canvas.clientHeight); | |
| this.renderer.setPixelRatio(window.devicePixelRatio); | |
| // Create orbit controls | |
| this.controls = new THREE.OrbitControls(this.camera, this.renderer.domElement); | |
| this.controls.enableDamping = true; | |
| this.controls.dampingFactor = 0.05; | |
| // Add lighting | |
| const ambientLight = new THREE.AmbientLight(0xffffff, 0.5); | |
| this.scene.add(ambientLight); | |
| const directionalLight = new THREE.DirectionalLight(0xffffff, 1); | |
| directionalLight.position.set(0, 1, 1); | |
| this.scene.add(directionalLight); | |
| // Add grid helper for reference | |
| const gridHelper = new THREE.GridHelper(10, 10, 0x444444, 0x222222); | |
| gridHelper.rotation.x = Math.PI / 2; | |
| this.scene.add(gridHelper); | |
| // Handle window resize | |
| window.addEventListener('resize', () => this.handleResize()); | |
| // Start animation loop | |
| this.animate(); | |
| } | |
| /** | |
| * Handle window resize | |
| */ | |
| handleResize() { | |
| const canvas = this.renderer.domElement; | |
| const width = canvas.clientWidth; | |
| const height = canvas.clientHeight; | |
| if (this.camera && this.renderer) { | |
| this.camera.aspect = width / height; | |
| this.camera.updateProjectionMatrix(); | |
| this.renderer.setSize(width, height, false); | |
| } | |
| } | |
| /** | |
| * Animation loop | |
| */ | |
| animate() { | |
| requestAnimationFrame(() => this.animate()); | |
| // Update controls | |
| if (this.controls) { | |
| this.controls.update(); | |
| } | |
| // Render scene | |
| if (this.scene && this.camera) { | |
| this.renderer.render(this.scene, this.camera); | |
| } | |
| } | |
| /** | |
| * Load TensorFlow.js and face mesh model | |
| */ | |
| async loadFaceMeshModel() { | |
| try { | |
| // Check if TensorFlow.js is loaded | |
| if (typeof tf === 'undefined') { | |
| await this.loadScript('https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@3.19.0/dist/tf.min.js'); | |
| } | |
| // Check if face-landmarks-detection is loaded | |
| if (typeof faceLandmarksDetection === 'undefined') { | |
| await this.loadScript('https://cdn.jsdelivr.net/npm/@tensorflow-models/face-landmarks-detection@1.0.2/dist/face-landmarks-detection.min.js'); | |
| } | |
| // Load face mesh model | |
| this.faceMeshModel = await faceLandmarksDetection.load( | |
| faceLandmarksDetection.SupportedPackages.mediapipeFacemesh, | |
| { maxFaces: 1 } | |
| ); | |
| this.status.modelLoaded = true; | |
| this.triggerEvent('modelLoaded'); | |
| return this.faceMeshModel; | |
| } catch (error) { | |
| console.error('Error loading face mesh model:', error); | |
| this.status.error = 'Failed to load face mesh model'; | |
| this.triggerEvent('error', { error }); | |
| throw error; | |
| } | |
| } | |
| /** | |
| * Initialize WebAssembly module | |
| */ | |
| async initWasmModule() { | |
| try { | |
| // Load WebAssembly module | |
| const response = await fetch(`${this.config.wasmPath}/face_reconstruction.wasm`); | |
| const wasmBinary = await response.arrayBuffer(); | |
| // Initialize module | |
| this.wasmModule = await WebAssembly.instantiate(wasmBinary, { | |
| env: { | |
| memory: new WebAssembly.Memory({ initial: 256, maximum: 512 }), | |
| abort: (_, __, ___, ____) => console.error('WASM abort called') | |
| }, | |
| wasi_snapshot_preview1: { | |
| proc_exit: () => {}, | |
| fd_close: () => {}, | |
| fd_write: () => {}, | |
| fd_seek: () => {}, | |
| fd_read: () => {} | |
| } | |
| }); | |
| // Export functions | |
| this.wasmFunctions = { | |
| reconstructFace: this.wasmModule.instance.exports.reconstructFace, | |
| analyzeMorphing: this.wasmModule.instance.exports.analyzeMorphing, | |
| getMemoryBuffer: () => new Uint8Array(this.wasmModule.instance.exports.memory.buffer) | |
| }; | |
| this.triggerEvent('wasmLoaded'); | |
| return this.wasmModule; | |
| } catch (error) { | |
| console.error('Error initializing WebAssembly module:', error); | |
| // Fall back to JavaScript implementation | |
| this.config.enableWasm = false; | |
| this.triggerEvent('wasmFailed', { error }); | |
| } | |
| } | |
| /** | |
| * Connect to drone | |
| */ | |
| async connectDrone(deviceId) { | |
| if (!this.config.enableDroneControl) { | |
| throw new Error('Drone control is disabled'); | |
| } | |
| try { | |
| // Simulate drone connection | |
| this.triggerEvent('droneConnecting'); | |
| // In a real implementation, this would connect to the drone | |
| await new Promise(resolve => setTimeout(resolve, 2000)); | |
| // Update drone status | |
| this.status.droneConnected = true; | |
| this.triggerEvent('droneConnected', { | |
| battery: '92%', | |
| signal: 'Excellent', | |
| gps: '12 Satellites', | |
| camera: 'Ready' | |
| }); | |
| return true; | |
| } catch (error) { | |
| console.error('Error connecting to drone:', error); | |
| this.status.error = 'Failed to connect to drone'; | |
| this.triggerEvent('error', { error }); | |
| return false; | |
| } | |
| } | |
| /** | |
| * Disconnect from drone | |
| */ | |
| async disconnectDrone() { | |
| if (!this.status.droneConnected) { | |
| return false; | |
| } | |
| try { | |
| // Simulate drone disconnection | |
| this.triggerEvent('droneDisconnecting'); | |
| // In a real implementation, this would disconnect from the drone | |
| await new Promise(resolve => setTimeout(resolve, 1000)); | |
| // Update drone status | |
| this.status.droneConnected = false; | |
| this.triggerEvent('droneDisconnected'); | |
| return true; | |
| } catch (error) { | |
| console.error('Error disconnecting from drone:', error); | |
| this.status.error = 'Failed to disconnect from drone'; | |
| this.triggerEvent('error', { error }); | |
| return false; | |
| } | |
| } | |
| /** | |
| * Start 3D scan using drone | |
| */ | |
| async startDroneScan(options = {}) { | |
| if (!this.status.droneConnected) { | |
| throw new Error('Drone is not connected'); | |
| } | |
| if (this.status.scanning) { | |
| throw new Error('Scan already in progress'); | |
| } | |
| // Merge options with defaults | |
| const scanOptions = Object.assign({ | |
| pattern: 'orbital', // orbital, hemispheric, spiral | |
| quality: this.config.scanQuality, | |
| subjectId: 'unknown' | |
| }, options); | |
| try { | |
| // Generate scan ID | |
| this.status.currentScanId = 'SCAN_' + Date.now().toString(); | |
| // Update status | |
| this.status.scanning = true; | |
| this.status.capturedImages = []; | |
| this.status.processingStage = 'capture'; | |
| // Clear previous data | |
| this.clearModel(); | |
| // Trigger scan started event | |
| this.triggerEvent('scanStarted', { | |
| scanId: this.status.currentScanId, | |
| options: scanOptions | |
| }); | |
| // Determine number of images based on quality | |
| const imageCount = { | |
| 'rapid': 15, | |
| 'standard': 30, | |
| 'detailed': 60 | |
| }[scanOptions.quality] || 30; | |
| // Simulate drone capturing images | |
| for (let i = 0; i < imageCount; i++) { | |
| // Update progress | |
| const progress = (i + 1) / imageCount; | |
| this.triggerEvent('scanProgress', { | |
| progress, | |
| currentImage: i + 1, | |
| totalImages: imageCount, | |
| stage: 'capture' | |
| }); | |
| // Simulate image capture | |
| await new Promise(resolve => setTimeout(resolve, 500)); | |
| // Add simulated image (in real implementation, this would be actual images) | |
| this.status.capturedImages.push({ | |
| id: `img_${i}`, | |
| position: this.simulateCameraPosition(i, imageCount, scanOptions.pattern), | |
| // In a real implementation, this would be actual image data | |
| imageData: `simulated_image_${i}.jpg` | |
| }); | |
| } | |
| // Start reconstruction process | |
| await this.reconstructFaceModel(); | |
| // Mark scan as completed | |
| this.status.scanning = false; | |
| this.status.processingStage = 'completed'; | |
| // Trigger scan completed event | |
| this.triggerEvent('scanCompleted', { | |
| scanId: this.status.currentScanId, | |
| imageCount, | |
| reconstructionSuccess: true | |
| }); | |
| return { | |
| scanId: this.status.currentScanId, | |
| imageCount, | |
| subjectId: scanOptions.subjectId, | |
| timestamp: new Date().toISOString(), | |
| success: true | |
| }; | |
| } catch (error) { | |
| console.error('Error scanning with drone:', error); | |
| // Update status | |
| this.status.scanning = false; | |
| this.status.error = error.message; | |
| this.status.processingStage = 'error'; | |
| // Trigger error event | |
| this.triggerEvent('error', { error }); | |
| return { | |
| success: false, | |
| error: error.message | |
| }; | |
| } | |
| } | |
| /** | |
| * Cancel current scan | |
| */ | |
| cancelScan() { | |
| if (!this.status.scanning) { | |
| return false; | |
| } | |
| // Update status | |
| this.status.scanning = false; | |
| this.status.processingStage = 'cancelled'; | |
| // Trigger cancel event | |
| this.triggerEvent('scanCancelled', { | |
| scanId: this.status.currentScanId | |
| }); | |
| return true; | |
| } | |
| /** | |
| * Simulate camera position for different scan patterns | |
| */ | |
| simulateCameraPosition(index, total, pattern) { | |
| const progress = index / (total - 1); | |
| switch (pattern) { | |
| case 'orbital': | |
| // Horizontal circle around subject | |
| const angle = progress * Math.PI * 2; | |
| return { | |
| x: Math.sin(angle) * 2, | |
| y: 0.2, // Slightly above eye level | |
| z: Math.cos(angle) * 2 | |
| }; | |
| case 'hemispheric': | |
| // Hemisphere above subject | |
| const azimuth = progress * Math.PI * 2; | |
| const elevation = (0.2 + progress * 0.6) * Math.PI / 2; | |
| return { | |
| x: 2 * Math.sin(azimuth) * Math.cos(elevation), | |
| y: 2 * Math.sin(elevation), | |
| z: 2 * Math.cos(azimuth) * Math.cos(elevation) | |
| }; | |
| case 'spiral': | |
| // Spiral pattern for complete coverage | |
| const spiralAngle = progress * Math.PI * 6; | |
| const spiralHeight = Math.sin(progress * Math.PI) * 1.5; | |
| const radius = 1.5 + Math.sin(progress * Math.PI * 2) * 0.5; | |
| return { | |
| x: Math.sin(spiralAngle) * radius, | |
| y: spiralHeight, | |
| z: Math.cos(spiralAngle) * radius | |
| }; | |
| default: | |
| return { x: 0, y: 0, z: 2 }; | |
| } | |
| } | |
| /** | |
| * Reconstruct 3D face model from captured images | |
| */ | |
| async reconstructFaceModel() { | |
| if (this.status.capturedImages.length === 0) { | |
| throw new Error('No images captured'); | |
| } | |
| try { | |
| // Update status | |
| this.status.reconstructing = true; | |
| this.status.processingStage = 'sfm'; | |
| // Trigger reconstruction started event | |
| this.triggerEvent('reconstructionStarted', { | |
| scanId: this.status.currentScanId, | |
| imageCount: this.status.capturedImages.length | |
| }); | |
| // Structure from Motion stage | |
| this.triggerEvent('reconstructionProgress', { | |
| stage: 'sfm', | |
| progress: 0.0, | |
| message: 'Extracting features...' | |
| }); | |
| // Simulate feature extraction | |
| await new Promise(resolve => setTimeout(resolve, 3000)); | |
| this.triggerEvent('reconstructionProgress', { | |
| stage: 'sfm', | |
| progress: 0.5, | |
| message: 'Matching features...' | |
| }); | |
| // Simulate feature matching | |
| await new Promise(resolve => setTimeout(resolve, 2000)); | |
| // Simulate sparse reconstruction | |
| this.triggerEvent('reconstructionProgress', { | |
| stage: 'reconstruction', | |
| progress: 0.0, | |
| message: 'Building sparse point cloud...' | |
| }); | |
| await new Promise(resolve => setTimeout(resolve, 3000)); | |
| // Simulate dense reconstruction | |
| this.triggerEvent('reconstructionProgress', { | |
| stage: 'reconstruction', | |
| progress: 0.5, | |
| message: 'Building dense model...' | |
| }); | |
| await new Promise(resolve => setTimeout(resolve, 5000)); | |
| // Create actual 3D model | |
| await this.createFaceModel(); | |
| // Analyze the reconstructed model | |
| this.triggerEvent('reconstructionProgress', { | |
| stage: 'analysis', | |
| progress: 0.0, | |
| message: 'Analyzing model for morphing...' | |
| }); | |
| // Perform morphing analysis | |
| const analysisResult = await this.analyzeMorphing(); | |
| // Update status | |
| this.status.reconstructing = false; | |
| this.status.processingStage = 'completed'; | |
| // Trigger reconstruction completed event | |
| this.triggerEvent('reconstructionCompleted', { | |
| scanId: this.status.currentScanId, | |
| analysisResult | |
| }); | |
| return analysisResult; | |
| } catch (error) { | |
| console.error('Error reconstructing face model:', error); | |
| // Update status | |
| this.status.reconstructing = false; | |
| this.status.error = error.message; | |
| this.status.processingStage = 'error'; | |
| // Trigger error event | |
| this.triggerEvent('error', { error }); | |
| throw error; | |
| } | |
| } | |
| /** | |
| * Create 3D face model | |
| */ | |
| async createFaceModel() { | |
| // Clear any existing model | |
| this.clearModel(); | |
| // Create new model (in a real implementation, this would use actual reconstruction data) | |
| // For demo purposes, create a simple face mesh | |
| return new Promise(resolve => { | |
| // Create geometry (simplified face shape) | |
| const geometry = new THREE.SphereGeometry(1, 32, 32); | |
| // Create material with face texture | |
| const material = new THREE.MeshStandardMaterial({ | |
| color: 0xf5f5f5, | |
| roughness: 0.7, | |
| metalness: 0.1, | |
| wireframe: false | |
| }); | |
| // Create mesh | |
| this.model = new THREE.Mesh(geometry, material); | |
| this.scene.add(this.model); | |
| // Move camera to front view | |
| this.camera.position.set(0, 0, 3); | |
| this.controls.update(); | |
| // Resolve after brief delay | |
| setTimeout(resolve, 500); | |
| }); | |
| } | |
| /** | |
| * Analyze the 3D model for morphing artifacts | |
| */ | |
| async analyzeMorphing() { | |
| // Check if model exists | |
| if (!this.model) { | |
| throw new Error('No model to analyze'); | |
| } | |
| try { | |
| // If WebAssembly is enabled, use that for analysis | |
| if (this.config.enableWasm && this.wasmModule) { | |
| return this.analyzeWithWasm(); | |
| } else { | |
| return this.analyzeWithJS(); | |
| } | |
| } catch (error) { | |
| console.error('Error analyzing morphing:', error); | |
| throw error; | |
| } | |
| } | |
| /** | |
| * Analyze morphing using WebAssembly | |
| */ | |
| analyzeWithWasm() { | |
| // In a real implementation, this would: | |
| // 1. Extract model data | |
| // 2. Pass to WebAssembly module | |
| // 3. Get analysis results | |
| // Simulate analysis with random result | |
| const isMorphed = Math.random() > 0.5; | |
| const confidence = isMorphed ? | |
| 0.7 + (Math.random() * 0.3) : // Higher confidence for morphed (70-100%) | |
| 0.8 + (Math.random() * 0.2); // Very high confidence for authentic (80-100%) | |
| return { | |
| isMorphed, | |
| confidence, | |
| regions: this.generateRegions(isMorphed), | |
| metrics: { | |
| asymmetry: isMorphed ? Math.random() * 0.5 + 0.5 : Math.random() * 0.3, | |
| textureConsistency: isMorphed ? Math.random() * 0.5 : Math.random() * 0.5 + 0.5, | |
| depthCoherence: isMorphed ? Math.random() * 0.4 : Math.random() * 0.3 + 0.7, | |
| featureAlignment: isMorphed ? Math.random() * 0.6 : Math.random() * 0.2 + 0.8 | |
| } | |
| }; | |
| } | |
| /** | |
| * Analyze morphing using JavaScript (fallback) | |
| */ | |
| analyzeWithJS() { | |
| // Same as WebAssembly but pure JS implementation | |
| // Simulate analysis with random result | |
| const isMorphed = Math.random() > 0.5; | |
| const confidence = isMorphed ? | |
| 0.7 + (Math.random() * 0.25) : // Slightly lower confidence (70-95%) | |
| 0.8 + (Math.random() * 0.15); // Still high confidence (80-95%) | |
| return { | |
| isMorphed, | |
| confidence, | |
| regions: this.generateRegions(isMorphed), | |
| metrics: { | |
| asymmetry: isMorphed ? Math.random() * 0.5 + 0.5 : Math.random() * 0.3, | |
| textureConsistency: isMorphed ? Math.random() * 0.5 : Math.random() * 0.5 + 0.5, | |
| depthCoherence: isMorphed ? Math.random() * 0.4 : Math.random() * 0.3 + 0.7, | |
| featureAlignment: isMorphed ? Math.random() * 0.6 : Math.random() * 0.2 + 0.8 | |
| } | |
| }; | |
| } | |
| /** | |
| * Generate regions data | |
| */ | |
| generateRegions(isMorphed) { | |
| if (!isMorphed) { | |
| return [{ | |
| name: 'Overall Assessment', | |
| confidence: Math.random() * 0.1, | |
| description: 'No suspicious regions detected. All facial features show normal 3D structure and texture consistency.' | |
| }]; | |
| } | |
| // Generate suspicious regions for morphed face | |
| return [ | |
| { | |
| name: 'Left Eye Region', | |
| confidence: 0.8 + Math.random() * 0.2, | |
| description: 'Abnormal depth transitions and texture inconsistencies around the eye socket.' | |
| }, | |
| { | |
| name: 'Mouth Area', | |
| confidence: 0.7 + Math.random() * 0.2, | |
| description: 'Blending artifacts detected in lip contour and surrounding areas.' | |
| }, | |
| { | |
| name: 'Nose Bridge', | |
| confidence: 0.6 + Math.random() * 0.3, | |
| description: 'Structural anomalies in the bridge and sides of the nose.' | |
| } | |
| ]; | |
| } | |
| /** | |
| * Clear the current 3D model | |
| */ | |
| clearModel() { | |
| if (this.model) { | |
| this.scene.remove(this.model); | |
| this.model = null; | |
| } | |
| } | |
| /** | |
| * Load model from stored scan | |
| */ | |
| async loadSavedModel(scanId) { | |
| try { | |
| // Clear current model | |
| this.clearModel(); | |
| // Update status | |
| this.status.processingStage = 'loading'; | |
| // Trigger loading event | |
| this.triggerEvent('modelLoading', { scanId }); | |
| // Simulate loading model from server | |
| await new Promise(resolve => setTimeout(resolve, 2000)); | |
| // Create face model (in a real implementation, this would load actual model data) | |
| await this.createFaceModel(); | |
| // Set current scan ID | |
| this.status.currentScanId = scanId; | |
| // Generate analysis data | |
| const analysisResult = await this.analyzeMorphing(); | |
| // Update status | |
| this.status.processingStage = 'loaded'; | |
| // Trigger loaded event | |
| this.triggerEvent('modelLoaded', { | |
| scanId, | |
| analysisResult | |
| }); | |
| return analysisResult; | |
| } catch (error) { | |
| console.error('Error loading saved model:', error); | |
| // Update status | |
| this.status.error = error.message; | |
| this.status.processingStage = 'error'; | |
| // Trigger error event | |
| this.triggerEvent('error', { error }); | |
| throw error; | |
| } | |
| } | |
| /** | |
| * Change visualization mode | |
| */ | |
| setVisualizationMode(mode, options = {}) { | |
| if (!this.model) { | |
| throw new Error('No model loaded'); | |
| } | |
| switch (mode) { | |
| case 'standard': | |
| this.model.material.wireframe = false; | |
| this.model.material.color.set(0xf5f5f5); | |
| break; | |
| case 'confidence': | |
| // Apply confidence heatmap visualization | |
| this.createHeatmapVisualization(options.threshold || 0.5); | |
| break; | |
| case 'wireframe': | |
| this.model.material.wireframe = true; | |
| this.model.material.color.set(0x3b82f6); | |
| break; | |
| case 'points': | |
| // Convert mesh to point cloud | |
| this.convertToPointCloud(); | |
| break; | |
| default: | |
| throw new Error(`Unknown visualization mode: ${mode}`); | |
| } | |
| // Trigger visualization change event | |
| this.triggerEvent('visualizationChanged', { mode, options }); | |
| return true; | |
| } | |
| /** | |
| * Create heatmap visualization for morphing confidence | |
| */ | |
| createHeatmapVisualization(threshold) { | |
| if (!this.model) return; | |
| // Create gradient material | |
| const material = new THREE.MeshStandardMaterial({ | |
| vertexColors: true, | |
| roughness: 0.7, | |
| metalness: 0.2 | |
| }); | |
| // Get geometry | |
| const geometry = this.model.geometry.clone(); | |
| // Create colors array | |
| const colors = []; | |
| const positions = geometry.attributes.position.array; | |
| // For each vertex, assign color based on position | |
| for (let i = 0; i < positions.length; i += 3) { | |
| const x = positions[i]; | |
| const y = positions[i + 1]; | |
| const z = positions[i + 2]; | |
| // Generate a confidence value based on position | |
| // In a real implementation, this would use actual confidence values | |
| const distance = Math.sqrt(x * x + y * y + z * z); | |
| const normalizedDistance = Math.min(1, distance / 1.2); | |
| // Calculate confidence (higher values for points further from center) | |
| let confidence = Math.abs(normalizedDistance - 0.5) * 2; | |
| // Apply threshold | |
| confidence = confidence < threshold ? 0 : confidence; | |
| // Create color (green to yellow to red) | |
| if (confidence < 0.3) { | |
| // Green (low confidence) | |
| colors.push(0.0, 1.0, 0.0); | |
| } else if (confidence < 0.7) { | |
| // Yellow (medium confidence) | |
| colors.push(1.0, 1.0, 0.0); | |
| } else { | |
| // Red (high confidence) | |
| colors.push(1.0, 0.0, 0.0); | |
| } | |
| } | |
| // Add colors to geometry | |
| geometry.setAttribute('color', new THREE.Float32BufferAttribute(colors, 3)); | |
| // Create new mesh with colored material | |
| this.scene.remove(this.model); | |
| this.model = new THREE.Mesh(geometry, material); | |
| this.scene.add(this.model); | |
| } | |
| /** | |
| * Convert mesh to point cloud | |
| */ | |
| convertToPointCloud() { | |
| if (!this.model) return; | |
| // Get geometry | |
| const geometry = this.model.geometry.clone(); | |
| // Create point cloud material | |
| const material = new THREE.PointsMaterial({ | |
| color: 0x3b82f6, | |
| size: 0.01, | |
| sizeAttenuation: true | |
| }); | |
| // Create point cloud | |
| this.scene.remove(this.model); | |
| this.model = new THREE.Points(geometry, material); | |
| this.scene.add(this.model); | |
| } | |
| /** | |
| * Reset camera view | |
| */ | |
| resetView() { | |
| this.camera.position.set(0, 0, 3); | |
| this.camera.lookAt(0, 0, 0); | |
| this.controls.reset(); | |
| } | |
| /** | |
| * Rotate view to preset position | |
| */ | |
| rotateView(position) { | |
| switch (position) { | |
| case 'front': | |
| this.camera.position.set(0, 0, 3); | |
| break; | |
| case 'side': | |
| this.camera.position.set(3, 0, 0); | |
| break; | |
| case 'top': | |
| this.camera.position.set(0, 3, 0); | |
| break; | |
| default: | |
| return; | |
| } | |
| this.camera.lookAt(0, 0, 0); | |
| this.controls.update(); | |
| } | |
| /** | |
| * Export 3D model as OBJ | |
| */ | |
| exportModel(format = 'obj') { | |
| if (!this.model) { | |
| throw new Error('No model to export'); | |
| } | |
| try { | |
| let result; | |
| switch (format.toLowerCase()) { | |
| case 'obj': | |
| // In real implementation, this would use OBJExporter | |
| result = 'Simulated OBJ export data'; | |
| break; | |
| case 'stl': | |
| // In real implementation, this would use STLExporter | |
| result = 'Simulated STL export data'; | |
| break; | |
| case 'ply': | |
| // In real implementation, this would use PLYExporter | |
| result = 'Simulated PLY export data'; | |
| break; | |
| default: | |
| throw new Error(`Unsupported export format: ${format}`); | |
| } | |
| // In real implementation, this would return a Blob | |
| return new Blob([result], { type: 'application/octet-stream' }); | |
| } catch (error) { | |
| console.error('Error exporting model:', error); | |
| throw error; | |
| } | |
| } | |
| /** | |
| * Load external script | |
| */ | |
| loadScript(src) { | |
| return new Promise((resolve, reject) => { | |
| const script = document.createElement('script'); | |
| script.src = src; | |
| script.onload = resolve; | |
| script.onerror = reject; | |
| document.head.appendChild(script); | |
| }); | |
| } | |
| /** | |
| * Set up event listeners | |
| */ | |
| setupEventListeners() { | |
| // In a real implementation, this would set up various event listeners | |
| } | |
| /** | |
| * Trigger custom event | |
| */ | |
| triggerEvent(eventName, data = {}) { | |
| // Create and dispatch custom event | |
| const event = new CustomEvent(`facemapper:${eventName}`, { | |
| detail: { ...data, source: this } | |
| }); | |
| document.dispatchEvent(event); | |
| // Call callback if defined | |
| const callbackName = `on${eventName.charAt(0).toUpperCase() + eventName.slice(1)}`; | |
| if (typeof this.config[callbackName] === 'function') { | |
| this.config[callbackName](data); | |
| } | |
| } | |
| } | |
| // Export for use in main script | |
| window.FaceMapper3D = FaceMapper3D; |