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breakpilot-lehrer/admin-lehrer/components/ocr-overlay/useSlideWordPositions.ts
Benjamin Admin d6f51e4418
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fix: deduplicate overlapping OCR words and use per-word Y positions in overlay
Backend: Add spatial overlap check (>=50% horizontal IoU) to Kombi merge
so words at the same position are deduplicated even when OCR text differs.

Frontend: Add yPct/hPct to WordPosition so each word renders at its actual
vertical position instead of all words collapsing to the cell center Y.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-13 20:27:08 +01:00

232 lines
7.2 KiB
TypeScript

import { useEffect, useState } from 'react'
import type { GridCell } from '@/app/(admin)/ai/ocr-overlay/types'
export interface WordPosition {
xPct: number
wPct: number
yPct: number
hPct: number
text: string
fontRatio: number
}
/**
* "Slide from left" positioning using OCR word bounding boxes.
*
* TEXT comes from cell.text (cleaned, IPA-corrected).
* POSITIONS come from word_boxes (exact OCR coordinates).
*
* Tokens from cell.text are matched 1:1 (in order) to word_boxes
* sorted left-to-right. This guarantees:
* - ALL words from cell.text appear (no dropping)
* - Words preserve their reading order
* - Each word lands on its correct black-text position
* - No red words overlap each other
*
* If token count != box count, extra tokens get estimated positions
* (spread across remaining space).
*
* Fallback: pixel-projection slide if no word_boxes available.
*/
export function useSlideWordPositions(
imageUrl: string,
cells: GridCell[],
active: boolean,
rotation: 0 | 180 = 0,
): Map<string, WordPosition[]> {
const [result, setResult] = useState<Map<string, WordPosition[]>>(new Map())
useEffect(() => {
if (!active || cells.length === 0 || !imageUrl) return
const img = new Image()
img.crossOrigin = 'anonymous'
img.onload = () => {
const imgW = img.naturalWidth
const imgH = img.naturalHeight
const hasWordBoxes = cells.some(c => c.word_boxes && c.word_boxes.length > 0)
if (hasWordBoxes) {
// --- WORD-BOX PATH: use OCR positions directly ---
// Each word_box already has exact coordinates from OCR.
// Use them as-is — no fuzzy matching needed.
const positions = new Map<string, WordPosition[]>()
for (const cell of cells) {
if (!cell.bbox_pct || !cell.text) continue
const boxes = (cell.word_boxes || [])
.filter(wb => wb.text.trim())
.sort((a, b) => a.left - b.left)
if (boxes.length === 0) {
// No word_boxes — spread tokens evenly across cell
const tokens = cell.text.split(/\s+/).filter(Boolean)
if (tokens.length === 0) continue
const fallbackW = cell.bbox_pct.w / tokens.length
const wordPos = tokens.map((t, i) => ({
xPct: cell.bbox_pct.x + i * fallbackW,
wPct: fallbackW,
yPct: cell.bbox_pct.y,
hPct: cell.bbox_pct.h,
text: t,
fontRatio: 1.0,
}))
positions.set(cell.cell_id, wordPos)
continue
}
// Use each word_box directly with its OCR coordinates
const wordPos: WordPosition[] = boxes.map(box => ({
xPct: (box.left / imgW) * 100,
wPct: (box.width / imgW) * 100,
yPct: (box.top / imgH) * 100,
hPct: (box.height / imgH) * 100,
text: box.text,
fontRatio: 1.0,
}))
if (wordPos.length > 0) {
positions.set(cell.cell_id, wordPos)
}
}
setResult(positions)
return
}
// --- FALLBACK: pixel-projection slide (no word_boxes) ---
const canvas = document.createElement('canvas')
canvas.width = imgW
canvas.height = imgH
const ctx = canvas.getContext('2d')
if (!ctx) return
if (rotation === 180) {
ctx.translate(imgW, imgH)
ctx.rotate(Math.PI)
ctx.drawImage(img, 0, 0)
ctx.setTransform(1, 0, 0, 1, 0, 0)
} else {
ctx.drawImage(img, 0, 0)
}
const refFontSize = 40
const fontFam = "'Liberation Sans', Arial, sans-serif"
ctx.font = `${refFontSize}px ${fontFam}`
const cellHeights = cells
.filter(c => c.bbox_pct && c.bbox_pct.h > 0)
.map(c => Math.round(c.bbox_pct.h / 100 * imgH))
.sort((a, b) => a - b)
const medianCh = cellHeights.length > 0
? cellHeights[Math.floor(cellHeights.length / 2)]
: 30
const renderedFontImgPx = medianCh * 0.7
const measureScale = renderedFontImgPx / refFontSize
const spaceWidthPx = Math.max(2, Math.round(ctx.measureText(' ').width * measureScale))
const positions = new Map<string, WordPosition[]>()
for (const cell of cells) {
if (!cell.bbox_pct || !cell.text) continue
let cx: number, cy: number
const cw = Math.round(cell.bbox_pct.w / 100 * imgW)
const ch = Math.round(cell.bbox_pct.h / 100 * imgH)
if (rotation === 180) {
cx = Math.round((100 - cell.bbox_pct.x - cell.bbox_pct.w) / 100 * imgW)
cy = Math.round((100 - cell.bbox_pct.y - cell.bbox_pct.h) / 100 * imgH)
} else {
cx = Math.round(cell.bbox_pct.x / 100 * imgW)
cy = Math.round(cell.bbox_pct.y / 100 * imgH)
}
if (cw <= 0 || ch <= 0) continue
if (cx < 0) cx = 0
if (cy < 0) cy = 0
if (cx + cw > imgW || cy + ch > imgH) continue
const imageData = ctx.getImageData(cx, cy, cw, ch)
const proj = new Float32Array(cw)
for (let y = 0; y < ch; y++) {
for (let x = 0; x < cw; x++) {
const idx = (y * cw + x) * 4
const lum = 0.299 * imageData.data[idx] + 0.587 * imageData.data[idx + 1] + 0.114 * imageData.data[idx + 2]
if (lum < 128) proj[x]++
}
}
const threshold = Math.max(1, ch * 0.03)
const ink = new Uint8Array(cw)
for (let x = 0; x < cw; x++) {
ink[x] = proj[x] >= threshold ? 1 : 0
}
if (rotation === 180) {
ink.reverse()
}
const tokens = cell.text.split(/\s+/).filter(Boolean)
if (tokens.length === 0) continue
const tokenWidthsPx = tokens.map(t =>
Math.max(4, Math.round(ctx.measureText(t).width * measureScale))
)
const wordPos: WordPosition[] = []
let cursor = 0
for (let ti = 0; ti < tokens.length; ti++) {
const tokenW = tokenWidthsPx[ti]
const coverageNeeded = Math.max(1, Math.round(tokenW * 0.15))
let bestX = cursor
const searchLimit = Math.max(cursor, cw - tokenW)
for (let x = cursor; x <= searchLimit; x++) {
let inkCount = 0
const spanEnd = Math.min(x + tokenW, cw)
for (let dx = 0; dx < spanEnd - x; dx++) {
inkCount += ink[x + dx]
}
if (inkCount >= coverageNeeded) {
bestX = x
break
}
if (x > cursor + cw * 0.3 && ti > 0) {
bestX = cursor
break
}
}
if (bestX + tokenW > cw) {
bestX = Math.max(0, cw - tokenW)
}
wordPos.push({
xPct: cell.bbox_pct.x + (bestX / cw) * cell.bbox_pct.w,
wPct: (tokenW / cw) * cell.bbox_pct.w,
yPct: cell.bbox_pct.y,
hPct: cell.bbox_pct.h,
text: tokens[ti],
fontRatio: 1.0,
})
cursor = bestX + tokenW + spaceWidthPx
}
if (wordPos.length > 0) {
positions.set(cell.cell_id, wordPos)
}
}
setResult(positions)
}
img.src = imageUrl
}, [active, cells, imageUrl, rotation])
return result
}