Press n or j to go to the next uncovered block, b, p or k for the previous block.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 | 'use client' import { useCallback, useEffect, useRef, useState } from 'react' import { createQuadDetector, type DetectedQuad as ModularDetectedQuad, type QuadDetectorConfig, } from '@/lib/vision/quadDetector' import { createQuadTracker, type TrackedQuad as ModularTrackedQuad } from '@/lib/vision/quadTracker' import type { CV, CVMat } from '@/lib/vision/opencv/types' // Re-export config type for consumers export type { QuadDetectorConfig } from '@/lib/vision/quadDetector' /** * Hook for document detection using OpenCV.js directly * * Features: * - Lazy loads OpenCV.js (~8MB) only when first used * - Uses modular quadDetector and quadTracker from @/lib/vision * - Scores quads by: size, aspect ratio, and temporal stability * - Filters out small quads (likely printed on page) vs page-sized quads * - Provides highlightDocument for drawing detected quad on overlay * - Provides extractDocument for cropping/deskewing captured image */ /** Internal tracked quad type for backward compatibility */ interface TrackedQuad extends ModularTrackedQuad { /** History of corner positions for stability calculation (used by extractDocument) */ cornerHistory?: Array<Array<{ x: number; y: number }>> } export interface DocumentDetectionDebugInfo { /** Time taken to load OpenCV in ms */ loadTimeMs: number | null /** Last detection attempt time in ms */ lastDetectionMs: number | null /** Number of quads detected this frame */ quadsDetected: number /** Number of tracked quad candidates */ trackedQuads: number /** Best quad's stability score */ bestQuadStability: number /** Best quad's frame count */ bestQuadFrameCount: number /** Last error message from detection */ lastDetectionError: string | null } /** Minimum frames a quad must be seen to be considered stable */ const MIN_FRAMES_FOR_STABLE = 3 /** Minimum frames for "locked" state */ const LOCKED_FRAME_COUNT = 5 /** Minimum stability score for locked state */ const MIN_STABILITY_FOR_LOCKED = 0.5 export interface DetectQuadsInImageResult { /** Whether a document quad was detected */ detected: boolean /** Corner positions (detected or fallback to full image) */ corners: Array<{ x: number; y: number }> /** The source canvas for the image */ sourceCanvas: HTMLCanvasElement } export interface UseDocumentDetectionReturn { /** Whether OpenCV is still loading */ isLoading: boolean /** Error message if loading failed */ error: string | null /** Whether scanner is ready to use */ isReady: boolean /** * Ensure OpenCV is loaded before using detection functions. * Call this before using highlightDocument, extractDocument, or detectQuadsInImage. * Returns true if OpenCV loaded successfully, false otherwise. */ ensureOpenCVLoaded: () => Promise<boolean> /** Whether detection is currently stable (good time to capture) */ isStable: boolean /** Whether detection is locked (very stable, ideal to capture) */ isLocked: boolean /** Debug information for troubleshooting */ debugInfo: DocumentDetectionDebugInfo /** OpenCV reference for external use (e.g., DocumentAdjuster) */ cv: unknown /** * Get the current best quad's corner positions * Returns null if no quad is detected */ getBestQuadCorners: () => Array<{ x: number; y: number }> | null /** * Capture the current video frame as a canvas * Returns null if capture fails */ captureSourceFrame: (video: HTMLVideoElement) => HTMLCanvasElement | null /** * Draw detected document edges on overlay canvas * Returns true if document was detected, false otherwise */ highlightDocument: (video: HTMLVideoElement, canvas: HTMLCanvasElement) => boolean /** * Extract and deskew the detected document * Returns canvas with cropped document, or null if extraction failed */ extractDocument: (video: HTMLVideoElement) => HTMLCanvasElement | null /** * Detect quads in a static image (for file uploads and gallery edits) * Returns detected corners or fallback corners (full image) */ detectQuadsInImage: (canvas: HTMLCanvasElement) => DetectQuadsInImageResult /** * Load an image file into a canvas * Returns the canvas, or null if loading failed */ loadImageToCanvas: (file: File) => Promise<HTMLCanvasElement | null> /** * Reset all tracking state (call when returning from adjustment mode) */ resetTracking: () => void /** * Update detector configuration (recreates detector with new settings) */ updateDetectorConfig: (config: Partial<QuadDetectorConfig>) => void /** * Current detector configuration */ detectorConfig: Partial<QuadDetectorConfig> } export interface UseDocumentDetectionOptions { /** Initial detector configuration */ detectorConfig?: Partial<QuadDetectorConfig> } export function useDocumentDetection( options?: UseDocumentDetectionOptions ): UseDocumentDetectionReturn { // Start with isLoading=false since we won't load until requested const [isLoading, setIsLoading] = useState(false) const [error, setError] = useState<string | null>(null) const cvRef = useRef<CV | null>(null) const loadPromiseRef = useRef<Promise<void> | null>(null) // Detector configuration (can be updated dynamically) const [detectorConfig, setDetectorConfig] = useState<Partial<QuadDetectorConfig>>( options?.detectorConfig ?? {} ) // Modular detector and tracker (created after OpenCV loads) const detectorRef = useRef<ReturnType<typeof createQuadDetector> | null>(null) const trackerRef = useRef<ReturnType<typeof createQuadTracker> | null>(null) // Best quad tracking const bestQuadRef = useRef<TrackedQuad | null>(null) const lastStableFrameRef = useRef<HTMLCanvasElement | null>(null) // Debug info tracking const [debugInfo, setDebugInfo] = useState<DocumentDetectionDebugInfo>({ loadTimeMs: null, lastDetectionMs: null, quadsDetected: 0, trackedQuads: 0, bestQuadStability: 0, bestQuadFrameCount: 0, lastDetectionError: null, }) const loadStartTimeRef = useRef<number>(0) // Helper to check if OpenCV is fully initialized const isOpenCVReady = useCallback((): boolean => { const cv = (window as unknown as { cv?: { imread?: unknown } }).cv return !!(cv && typeof cv.imread === 'function') }, []) // Lazy load OpenCV.js - only when explicitly requested const ensureOpenCVLoaded = useCallback(async (): Promise<boolean> => { // Already loaded if (cvRef.current) return true // Already loading - wait for it if (loadPromiseRef.current) { await loadPromiseRef.current return cvRef.current !== null } // Start loading setIsLoading(true) loadStartTimeRef.current = Date.now() loadPromiseRef.current = (async () => { try { if (typeof window !== 'undefined') { if (!isOpenCVReady()) { const existingScript = document.querySelector('script[src="/opencv.js"]') if (!existingScript) { await new Promise<void>((resolve, reject) => { const script = document.createElement('script') script.src = '/opencv.js' script.async = true script.onload = () => { const checkReady = () => { if (isOpenCVReady()) { resolve() } else { const cv = ( window as unknown as { cv?: { onRuntimeInitialized?: () => void } } ).cv if (cv) { const previousCallback = cv.onRuntimeInitialized cv.onRuntimeInitialized = () => { previousCallback?.() resolve() } } else { reject(new Error('OpenCV.js loaded but cv not found')) } } } checkReady() } script.onerror = () => reject(new Error('Failed to load OpenCV.js')) document.head.appendChild(script) }) } else { await new Promise<void>((resolve, reject) => { const maxWait = 30000 const startTime = Date.now() const checkReady = () => { if (isOpenCVReady()) { resolve() } else if (Date.now() - startTime > maxWait) { reject(new Error('OpenCV.js loading timed out')) } else { const cv = ( window as unknown as { cv?: { onRuntimeInitialized?: () => void } } ).cv if (cv) { const previousCallback = cv.onRuntimeInitialized cv.onRuntimeInitialized = () => { previousCallback?.() resolve() } } else { setTimeout(checkReady, 100) } } } checkReady() }) } } } // Store OpenCV reference cvRef.current = (window as unknown as { cv: CV }).cv // Create modular detector and tracker with current config detectorRef.current = createQuadDetector(cvRef.current, detectorConfig) trackerRef.current = createQuadTracker({ minFramesForStable: MIN_FRAMES_FOR_STABLE, minFramesForLocked: LOCKED_FRAME_COUNT, minStabilityForLocked: MIN_STABILITY_FOR_LOCKED, }) const loadTime = Date.now() - loadStartTimeRef.current setDebugInfo((prev) => ({ ...prev, loadTimeMs: loadTime })) setIsLoading(false) } catch (err) { console.error('Failed to load OpenCV:', err) setError(err instanceof Error ? err.message : 'Failed to load OpenCV') setIsLoading(false) throw err } })() try { await loadPromiseRef.current return cvRef.current !== null } catch { return false } }, [isOpenCVReady, detectorConfig]) // Recreate detector when config changes (if OpenCV is already loaded) useEffect(() => { if (cvRef.current && detectorRef.current) { detectorRef.current = createQuadDetector(cvRef.current, detectorConfig) } }, [detectorConfig]) // Update detector config function const updateDetectorConfig = useCallback((newConfig: Partial<QuadDetectorConfig>) => { setDetectorConfig((prev) => ({ ...prev, ...newConfig })) }, []) // Reusable canvas for video frame capture const frameCanvasRef = useRef<HTMLCanvasElement | null>(null) // Helper to capture video frame to canvas const captureVideoFrame = useCallback((video: HTMLVideoElement): HTMLCanvasElement | null => { if (!video.videoWidth || !video.videoHeight) return null if (!frameCanvasRef.current) { frameCanvasRef.current = document.createElement('canvas') } const frameCanvas = frameCanvasRef.current if (frameCanvas.width !== video.videoWidth || frameCanvas.height !== video.videoHeight) { frameCanvas.width = video.videoWidth frameCanvas.height = video.videoHeight } const ctx = frameCanvas.getContext('2d') if (!ctx) return null ctx.drawImage(video, 0, 0) return frameCanvas }, []) // Calculate distance between two points (kept for extractDocument) const distance = useCallback( (p1: { x: number; y: number }, p2: { x: number; y: number }): number => { return Math.sqrt((p1.x - p2.x) ** 2 + (p1.y - p2.y) ** 2) }, [] ) // Draw quad on overlay canvas const drawQuad = useCallback( ( ctx: CanvasRenderingContext2D, corners: Array<{ x: number; y: number }>, color: string, lineWidth: number ) => { ctx.strokeStyle = color ctx.lineWidth = lineWidth ctx.lineCap = 'round' ctx.lineJoin = 'round' ctx.beginPath() ctx.moveTo(corners[0].x, corners[0].y) for (let i = 1; i < corners.length; i++) { ctx.lineTo(corners[i].x, corners[i].y) } ctx.closePath() ctx.stroke() // Draw corner circles ctx.fillStyle = color for (const corner of corners) { ctx.beginPath() ctx.arc(corner.x, corner.y, lineWidth * 2, 0, Math.PI * 2) ctx.fill() } }, [] ) const highlightDocument = useCallback( (video: HTMLVideoElement, overlayCanvas: HTMLCanvasElement): boolean => { const detector = detectorRef.current const tracker = trackerRef.current if (!detector || !tracker) return false const startTime = performance.now() try { const frameCanvas = captureVideoFrame(video) if (!frameCanvas) { setDebugInfo((prev) => ({ ...prev, lastDetectionError: 'Failed to capture video frame', })) return false } // Resize overlay to match video if ( overlayCanvas.width !== video.videoWidth || overlayCanvas.height !== video.videoHeight ) { overlayCanvas.width = video.videoWidth overlayCanvas.height = video.videoHeight } const overlayCtx = overlayCanvas.getContext('2d') if (!overlayCtx) return false // Clear overlay overlayCtx.clearRect(0, 0, overlayCanvas.width, overlayCanvas.height) // Use modular detector const detectedQuads = detector.detect(frameCanvas) // Use modular tracker const bestQuad = tracker.update(detectedQuads, { width: frameCanvas.width, height: frameCanvas.height, }) const stats = tracker.getStats() const detectionTime = performance.now() - startTime // Draw all detected quads (faded) for debugging for (const quad of detectedQuads) { drawQuad(overlayCtx, quad.corners, 'rgba(100, 100, 100, 0.3)', 2) } // Draw best quad with color based on stability if (bestQuad) { // Update bestQuadRef for extractDocument bestQuadRef.current = bestQuad let color: string let lineWidth: number if (bestQuad.isLocked) { color = 'rgba(0, 255, 100, 0.95)' lineWidth = 6 // Save stable frame if (!lastStableFrameRef.current) { lastStableFrameRef.current = document.createElement('canvas') } lastStableFrameRef.current.width = frameCanvas.width lastStableFrameRef.current.height = frameCanvas.height const stableCtx = lastStableFrameRef.current.getContext('2d') stableCtx?.drawImage(frameCanvas, 0, 0) } else if (bestQuad.isStable) { color = 'rgba(100, 255, 100, 0.85)' lineWidth = 5 } else { color = 'rgba(255, 200, 0, 0.8)' lineWidth = 4 } drawQuad(overlayCtx, bestQuad.corners, color, lineWidth) } else { bestQuadRef.current = null } // Update debug info setDebugInfo((prev) => ({ ...prev, lastDetectionMs: Math.round(detectionTime), quadsDetected: detectedQuads.length, trackedQuads: stats.trackedCount, bestQuadStability: bestQuad?.stabilityScore ?? 0, bestQuadFrameCount: bestQuad?.frameCount ?? 0, lastDetectionError: null, })) return !!bestQuad } catch (err) { setDebugInfo((prev) => ({ ...prev, lastDetectionError: err instanceof Error ? err.message : 'Unknown error', })) return false } }, [captureVideoFrame, drawQuad] ) /** * Analyze document orientation and return rotation needed (0, 90, 180, 270) * Uses edge detection to find dominant text line direction * and content density to detect upside-down orientation */ const analyzeOrientation = useCallback((canvas: HTMLCanvasElement): 0 | 90 | 180 | 270 => { const cv = cvRef.current if (!cv) return 0 let src: CVMat | null = null let gray: CVMat | null = null let edges: CVMat | null = null try { src = cv.imread(canvas) gray = new cv.Mat() edges = new cv.Mat() // Convert to grayscale cv.cvtColor(src, gray, cv.COLOR_RGBA2GRAY) // Apply Canny edge detection cv.Canny(gray, edges, 50, 150) const width = edges.cols const height = edges.rows // Sample horizontal and vertical edge strips to determine orientation // For text documents, horizontal lines (text) should dominate let horizontalEdges = 0 let verticalEdges = 0 // Sample middle section of the image (avoid margins) const marginX = Math.floor(width * 0.1) const marginY = Math.floor(height * 0.1) const sampleHeight = height - 2 * marginY // Count edge pixels in horizontal strips vs vertical strips // Use a simple row/column scan approach const edgeData = new Uint8Array((edges as unknown as { data: ArrayBuffer }).data) // Count horizontal edge continuity (text lines are horizontal) for (let y = marginY; y < height - marginY; y += 5) { let runLength = 0 for (let x = marginX; x < width - marginX; x++) { if (edgeData[y * width + x] > 0) { runLength++ } else { if (runLength > 10) horizontalEdges += runLength runLength = 0 } } if (runLength > 10) horizontalEdges += runLength } // Count vertical edge continuity for (let x = marginX; x < width - marginX; x += 5) { let runLength = 0 for (let y = marginY; y < height - marginY; y++) { if (edgeData[y * width + x] > 0) { runLength++ } else { if (runLength > 10) verticalEdges += runLength runLength = 0 } } if (runLength > 10) verticalEdges += runLength } // Determine if we need 90° rotation // If vertical edges significantly dominate, text is probably sideways const ratio = horizontalEdges / (verticalEdges + 1) let rotation: 0 | 90 | 180 | 270 = 0 if (ratio < 0.5) { // Vertical edges dominate - rotate 90° clockwise rotation = 90 } else if (ratio > 2) { // Horizontal edges dominate - correct orientation (or 180°) rotation = 0 } // Now check if upside down by comparing content density // Top of document usually has more content (headers, titles) const topThird = Math.floor(sampleHeight / 3) let topDensity = 0 let bottomDensity = 0 for (let y = marginY; y < marginY + topThird; y++) { for (let x = marginX; x < width - marginX; x += 3) { if (edgeData[y * width + x] > 0) topDensity++ } } for (let y = height - marginY - topThird; y < height - marginY; y++) { for (let x = marginX; x < width - marginX; x += 3) { if (edgeData[y * width + x] > 0) bottomDensity++ } } // If bottom has significantly more content, probably upside down if (bottomDensity > topDensity * 1.5) { rotation = rotation === 0 ? 180 : rotation === 90 ? 270 : rotation } return rotation } catch (err) { console.warn('Orientation analysis failed:', err) return 0 } finally { src?.delete() gray?.delete() edges?.delete() } }, []) /** * Rotate a canvas by the specified degrees (0, 90, 180, 270) */ const rotateCanvas = useCallback( (canvas: HTMLCanvasElement, degrees: 0 | 90 | 180 | 270): HTMLCanvasElement => { if (degrees === 0) return canvas const cv = cvRef.current if (!cv) return canvas let src: CVMat | null = null let dst: CVMat | null = null try { src = cv.imread(canvas) dst = new cv.Mat() const rotateCode = degrees === 90 ? cv.ROTATE_90_CLOCKWISE : degrees === 180 ? cv.ROTATE_180 : cv.ROTATE_90_COUNTERCLOCKWISE cv.rotate(src, dst, rotateCode) const outputCanvas = document.createElement('canvas') if (degrees === 90 || degrees === 270) { outputCanvas.width = canvas.height outputCanvas.height = canvas.width } else { outputCanvas.width = canvas.width outputCanvas.height = canvas.height } cv.imshow(outputCanvas, dst) return outputCanvas } catch (err) { console.warn('Canvas rotation failed:', err) return canvas } finally { src?.delete() dst?.delete() } }, [] ) const extractDocument = useCallback( (video: HTMLVideoElement): HTMLCanvasElement | null => { const cv = cvRef.current const bestQuad = bestQuadRef.current if (!cv || !bestQuad) return null try { // Use stable frame if available, otherwise capture current const sourceCanvas = lastStableFrameRef.current && bestQuad.frameCount >= LOCKED_FRAME_COUNT ? lastStableFrameRef.current : captureVideoFrame(video) if (!sourceCanvas) return null const corners = bestQuad.corners // Calculate output dimensions (maintain aspect ratio) const width1 = distance(corners[0], corners[1]) const width2 = distance(corners[3], corners[2]) const height1 = distance(corners[0], corners[3]) const height2 = distance(corners[1], corners[2]) const outputWidth = Math.round((width1 + width2) / 2) const outputHeight = Math.round((height1 + height2) / 2) // Create source points matrix const srcPts = cv.matFromArray(4, 1, cv.CV_32FC2, [ corners[0].x, corners[0].y, corners[1].x, corners[1].y, corners[2].x, corners[2].y, corners[3].x, corners[3].y, ]) // Create destination points matrix const dstPts = cv.matFromArray(4, 1, cv.CV_32FC2, [ 0, 0, outputWidth, 0, outputWidth, outputHeight, 0, outputHeight, ]) // Get perspective transform const M = cv.getPerspectiveTransform(srcPts, dstPts) // Read source image const src = cv.imread(sourceCanvas) // Create output mat const dst = new cv.Mat() // Apply perspective warp cv.warpPerspective( src, dst, M, new cv.Size(outputWidth, outputHeight), cv.INTER_LINEAR, cv.BORDER_CONSTANT, new cv.Scalar() ) // Create output canvas const outputCanvas = document.createElement('canvas') outputCanvas.width = outputWidth outputCanvas.height = outputHeight cv.imshow(outputCanvas, dst) // Clean up srcPts.delete() dstPts.delete() M.delete() src.delete() dst.delete() // Auto-rotate based on content analysis const rotation = analyzeOrientation(outputCanvas) if (rotation !== 0) { console.log(`Auto-rotating document by ${rotation}°`) return rotateCanvas(outputCanvas, rotation) } return outputCanvas } catch (err) { console.warn('Document extraction failed:', err) return null } }, [captureVideoFrame, distance, analyzeOrientation, rotateCanvas] ) // Reset tracking state (call when returning from adjustment mode) const resetTracking = useCallback(() => { trackerRef.current?.reset() bestQuadRef.current = null lastStableFrameRef.current = null setDebugInfo((prev) => ({ ...prev, quadsDetected: 0, trackedQuads: 0, bestQuadStability: 0, bestQuadFrameCount: 0, })) }, []) // Compute derived state (use isStable/isLocked from tracked quad) const bestQuad = bestQuadRef.current const isStable = bestQuad?.isStable ?? false const isLocked = bestQuad?.isLocked ?? false // Get current best quad corners const getBestQuadCorners = useCallback((): Array<{ x: number y: number }> | null => { const quad = bestQuadRef.current if (!quad) return null return [...quad.corners] }, []) // Capture source frame (expose captureVideoFrame) const captureSourceFrame = useCallback( (video: HTMLVideoElement): HTMLCanvasElement | null => { const frame = captureVideoFrame(video) if (!frame) return null // Return a copy so caller can keep it const copy = document.createElement('canvas') copy.width = frame.width copy.height = frame.height const ctx = copy.getContext('2d') ctx?.drawImage(frame, 0, 0) return copy }, [captureVideoFrame] ) /** * Load an image file into a canvas */ const loadImageToCanvas = useCallback(async (file: File): Promise<HTMLCanvasElement | null> => { return new Promise((resolve) => { const img = new Image() const url = URL.createObjectURL(file) img.onload = () => { URL.revokeObjectURL(url) const canvas = document.createElement('canvas') canvas.width = img.naturalWidth canvas.height = img.naturalHeight const ctx = canvas.getContext('2d') if (!ctx) { resolve(null) return } ctx.drawImage(img, 0, 0) resolve(canvas) } img.onerror = () => { URL.revokeObjectURL(url) resolve(null) } img.src = url }) }, []) /** * Detect quads in a static image (for file uploads and gallery edits) * Returns detected corners or fallback corners (full image) */ const detectQuadsInImage = useCallback((canvas: HTMLCanvasElement): DetectQuadsInImageResult => { // Fallback corners (full image) const fallbackCorners = [ { x: 0, y: 0 }, { x: canvas.width, y: 0 }, { x: canvas.width, y: canvas.height }, { x: 0, y: canvas.height }, ] const detector = detectorRef.current if (!detector) { return { detected: false, corners: fallbackCorners, sourceCanvas: canvas, } } try { // Use modular detector const detectedQuads = detector.detect(canvas) if (detectedQuads.length > 0) { // Return the best quad (largest area, already sorted) return { detected: true, corners: detectedQuads[0].corners, sourceCanvas: canvas, } } // No quads detected - return fallback return { detected: false, corners: fallbackCorners, sourceCanvas: canvas, } } catch (err) { console.warn('Quad detection failed:', err) return { detected: false, corners: fallbackCorners, sourceCanvas: canvas, } } }, []) return { isLoading, error, isReady: !isLoading && !error && detectorRef.current !== null, ensureOpenCVLoaded, isStable, isLocked: !!isLocked, debugInfo, cv: cvRef.current, getBestQuadCorners, captureSourceFrame, highlightDocument, extractDocument, detectQuadsInImage, loadImageToCanvas, resetTracking, updateDetectorConfig, detectorConfig, } } export default useDocumentDetection |