Translate manga from Japanese/Chinese to English using Gemini, or optionally with a Python server (YOLO+MangaOCR+mBART+Colorization)/in-browser CTD/Google.
// ==UserScript== // @name Jp Manga Translator // @author moony // @license MIT // @version 2.6 // @description Translate manga from Japanese/Chinese to English using Gemini, or optionally with a Python server (YOLO+MangaOCR+mBART+Colorization)/in-browser CTD/Google. // @namespace JpMangaTranslator // @match *.mangadex.org/* // @match *.mangapark.net/* // @match *.weebcentral.com/* // @match *.mangahere.cc/* // @match *.mangafox.fun/* // @match *.fanfox.net/* // @match *.webtoons.com/* // @match *.bato.to.*/* // @match *.asuracomic.net/* // @match *.tapas.io/* // @match *.dynasty-scans.com/* // @match *.comic-walker.com/* // @match *.pixiv.net/*/artworks/* // @match *.8muses.com/* // @match *.hentai2read.com/* // @match *.e-hentai.org/* // @match *.exhentai.* // @match *.nhentai.net/* // @match *.hitomi.la/* // @match *.raw.senmanga.com/* // @exclude *.mangaplus.shueisha.co.jp/* // @exclude *.battwo.com/* // @exclude *.natomanga.com/* // @exclude *.mangakakalot.gg/* // @icon https://i.imgur.com/9Oym4Cp.png // @grant GM_xmlhttpRequest // @grant GM_registerMenuCommand // @grant GM_getValue // @grant GM_setValue // @connect localhost // @connect ocrt.iwanhae.kr // @connect generativelanguage.googleapis.com // @connect translate.googleapis.com // @connect api.mymemory.translated.net // @connect huggingface.co // @connect cdn.jsdelivr.net // @connect fonts.googleapis.com // @connect fonts.gstatic.com // @connect * // @require https://cdn.jsdelivr.net/npm/[email protected]/dist/ort.all.min.js // @run-at document-idle // ==/UserScript== (function () { 'use strict'; const log = (...a) => console.log('[MT]', ...a); const API_BASE = GM_getValue('server_url', 'http://localhost:8000'); const DETECT_MIN_IMAGE_SIZE = 600; const CTD_INPUT_SIZE = 1024, CTD_CONF_THR = 0.25, CTD_IOU_THR = 0.50; const OCR_BASE_PADDING = 8, OCR_MAX_BATCH = 24; const fontStyle = document.createElement('style'); fontStyle.textContent = `@import url('https://fonts.googleapis.com/css2?family=Comic+Neue:wght@700&display=swap');`; document.head.appendChild(fontStyle); const ORT_BASE = 'https://cdn.jsdelivr.net/npm/[email protected]/dist/'; try { if (typeof ort !== 'undefined' && ort.env) { if (typeof ort.setWasmPaths === 'function') ort.setWasmPaths(ORT_BASE); else if (ort.env.wasm) ort.env.wasm.wasmPaths = ORT_BASE; if (ort.env.wasm) { ort.env.wasm.simd = true; ort.env.wasm.numThreads = 1; // Force single thread to avoid issues } if (ort.env.webgpu) { ort.env.webgpu.preferredLayout = 'NCHW'; ort.env.webgpu.powerPreference = 'high-performance'; } } } catch (e) { log('ORT env warn:', e.message); } // === FIX: Persistent state across soft navigations === if (!window._MT) window._MT = { ctdSession: null, ctdBytes: null, dbSession: null, dbBytes: null, mangaOCR: null, queue: [], processing: false, processed: new Set() }; const MT = window._MT; // === FIX: WebGPU-first session creation === async function createSession(bytes, name) { if (navigator.gpu) { try { const adapter = await navigator.gpu.requestAdapter(); if (adapter) { const sess = await ort.InferenceSession.create(bytes, { executionProviders: ['webgpu'], graphOptimizationLevel: 'all' }); log(`${name}: WebGPU ready`); return sess; } } catch (e) { log(`${name}: WebGPU failed, trying WASM:`, e.message); } } const sess = await ort.InferenceSession.create(bytes, { executionProviders: ['wasm'], graphOptimizationLevel: 'all' }); log(`${name}: WASM ready`); return sess; } if (!GM_getValue('_init')) { GM_setValue('mode', 'browser'); // Pipeline mode: 'gemini' (API-Key) | 'external' (iwanhae.kr) by Default | 'server' (local) | 'browser' (WebGPU) GM_setValue('aio', false); // All-In-One: single API call for detect+OCR+translate vs modular pipeline GM_setValue('colorize', false); // Server-only: colorize B&W manga GM_setValue('detector', 'ctd'); // Bubble detector: 'yolo' (server) | 'ctd' (WebGPU, bubble-focused) | 'db' (WIP text-focused) | 'none' GM_setValue('ocr', 'manga2025'); // OCR jp/zh engine: 'server' | 'manga2025' (WebGPU) | 'none' GM_setValue('translator', 'google'); // Translator: 'mbart' (server) | 'google' (free API) | 'mymemory' | 'none' GM_setValue('target_lang', 'English'); // Gemini-only: target language GM_setValue('_init', 1); } GM_registerMenuCommand('Preset: Gemini API (All-in-One)', async () => { let key = GM_getValue('gemini_key'); if (!key) { key = prompt('Enter GEMINI_API_KEY from https://aistudio.google.com/app/apikey:'); if (key) GM_setValue('gemini_key', key); } setPreset('Gemini', { mode: 'gemini', aio: true, detector: 'none', ocr: 'none', translator: 'none', colorize: false }); }); GM_registerMenuCommand('Preset: iwanhae.kr (All-in-One, free)', () => setPreset('iwanhae', { mode: 'external', aio: true, detector: 'none', ocr: 'none', translator: 'none', colorize: false })); GM_registerMenuCommand('Preset: Server (YOLO+MangaOCR+mBART+Colorize)', () => setPreset('Server', { mode: 'server', aio: false, detector: 'yolo', ocr: 'server', translator: 'mbart', colorize: true })); GM_registerMenuCommand('Preset: Browser (CTD+MangaOCR-2025+Google)', () => setPreset('Browser', { mode: 'browser', aio: false, detector: 'ctd', ocr: 'manga2025', translator: 'google', colorize: false })); GM_registerMenuCommand('Process visible image', processVisibleImage); function setPreset(name, flags) { Object.entries(flags).forEach(([k, v]) => GM_setValue(k, v)); log('✓ Preset:', name); setTimeout(() => location.reload(), 100); } function resolveUrl(img) { if (!img) return null; if (img.toDataURL) return img.toDataURL('image/png'); let u = img.currentSrc || img.src || img.getAttribute('data-src') || img.getAttribute('data-original'); if (!u) return null; if (u.startsWith('//')) u = location.protocol + u; return u; } function getVisibleMangaImage() { let best = null, bestArea = 0; for (const el of document.querySelectorAll('img, canvas')) { const r = el.getBoundingClientRect(); if (r.top >= window.innerHeight || r.bottom <= 0) continue; const w = el.naturalWidth || el.width, h = el.naturalHeight || el.height; if (w < DETECT_MIN_IMAGE_SIZE && h < DETECT_MIN_IMAGE_SIZE) continue; const u = resolveUrl(el); if (!u || (u.startsWith('data:') && !el.getContext)) continue; const area = w * h; if (area > bestArea) { best = el; bestArea = area; } } return best; } function gmFetch(url, opts = {}) { return new Promise((ok, err) => GM_xmlhttpRequest({ method: opts.method || 'GET', url, headers: opts.headers || {}, data: opts.body, responseType: opts.responseType || 'json', timeout: opts.timeout || 120000, onload: r => (r.status >= 200 && r.status < 300) ? ok(r.response) : err(new Error(`HTTP ${r.status}`)), onerror: () => err(new Error('Network error')), ontimeout: () => err(new Error('Timeout')) })); } function fetchBlob(url) { if (url.startsWith('data:')) return fetch(url).then(r => r.blob()); return new Promise((ok, err) => GM_xmlhttpRequest({ method: 'GET', url, responseType: 'blob', headers: { 'Referer': window.location.origin }, timeout: 60000, onload: r => ok(r.response), onerror: () => err(new Error('Blob error')), ontimeout: () => err(new Error('Blob timeout')) })); } function fetchBase64(url) { return new Promise((ok, err) => GM_xmlhttpRequest({ method: 'GET', url, responseType: 'blob', headers: { 'Referer': window.location.origin }, timeout: 60000, onload: r => { const rd = new FileReader(); rd.onloadend = () => ok(rd.result.split(',')[1]); rd.onerror = () => err(new Error('FileReader failed')); rd.readAsDataURL(r.response); }, onerror: () => err(new Error('Image error')), ontimeout: () => err(new Error('Image timeout')) })); } const bitmapCache = new Map(); async function getBitmap(url) { if (bitmapCache.has(url)) return bitmapCache.get(url); const bl = await fetchBlob(url), bm = await createImageBitmap(bl); bitmapCache.set(url, bm); return bm; } const iou = (a, b) => { const x1 = Math.max(a[0], b[0]), y1 = Math.max(a[1], b[1]); const x2 = Math.min(a[2], b[2]), y2 = Math.min(a[3], b[3]); const inter = Math.max(0, x2 - x1) * Math.max(0, y2 - y1); const A = (a[2] - a[0]) * (a[3] - a[1]), B = (b[2] - b[0]) * (b[3] - b[1]); return inter / Math.max(A + B - inter, 1); }; const nms = (boxes, scores, thr) => { const idx = boxes.map((_, i) => i).sort((a, b) => scores[b] - scores[a]); const kept = []; for (const i of idx) { let keep = true; for (const j of kept) if (iou(boxes[i], boxes[j]) > thr) { keep = false; break; } if (keep) kept.push(i); } return kept; }; function sortReadingOrder(boxes, rtl = true) { const items = boxes.map(b => ({ b, cy: (b[1] + b[3]) / 2, h: (b[3] - b[1]) })).sort((a, b) => a.cy - b.cy); const rows = []; for (const it of items) { const r = rows.find(x => Math.abs(x.cy - it.cy) < Math.min(x.h, it.h) * 0.6); if (r) { r.items.push(it); r.cy = (r.cy * r.items.length + it.cy) / (r.items.length + 1); r.h = (r.h + it.h) / 2; } else rows.push({ cy: it.cy, h: it.h, items: [it] }); } rows.forEach(r => r.items.sort((a, b) => rtl ? b.b[0] - a.b[0] : a.b[0] - b.b[0])); return rows.flatMap(r => r.items.map(i => i.b)); } function findNearbyBoxIndices(boxes) { const nearby = new Set(); for (let i = 0; i < boxes.length; i++) { for (let j = i + 1; j < boxes.length; j++) { const [x1a, y1a, x2a, y2a] = boxes[i], [x1b, y1b, x2b, y2b] = boxes[j]; const gapX = Math.max(0, Math.max(x1a, x1b) - Math.min(x2a, x2b)); const gapY = Math.max(0, Math.max(y1a, y1b) - Math.min(y2a, y2b)); if (gapX < OCR_BASE_PADDING * 2 && gapY < OCR_BASE_PADDING * 2) { nearby.add(i); nearby.add(j); } } } return nearby; } async function createCanvasFromBlob(blob, width, height) { return new Promise((ok, err) => { const url = URL.createObjectURL(blob), img = new Image(); img.onload = () => { const c = document.createElement('canvas'); c.width = width; c.height = height; c.getContext('2d').drawImage(img, 0, 0); URL.revokeObjectURL(url); ok(c); }; img.onerror = () => { URL.revokeObjectURL(url); err(new Error('img load')); }; img.src = url; }); } const CJK_RE = /[\u3000-\u303F\u3040-\u30FF\u3400-\u4DBF\u4E00-\u9FFF]/; function wrapCJK(ctx, text, maxWidth) { const out = []; let line = ''; for (const ch of text) { const t = line + ch; if (ctx.measureText(t).width > maxWidth && line) { out.push(line); line = ch; } else line = t; } if (line) out.push(line); return out; } function wrapLatin(ctx, text, maxWidth) { const words = text.split(/\s+/); const out = []; let line = ''; for (const w of words) { const t = line ? (line + ' ' + w) : w; if (ctx.measureText(t).width > maxWidth && line) { out.push(line); line = w; } else line = t; } if (line) out.push(line); return out; } function drawTextOnCanvas(canvas, region) { const ctx = canvas.getContext('2d'); const [x1, y1, x2, y2] = region.box; const rw = Math.max(1, x2 - x1), rh = Math.max(1, y2 - y1); const pad = 4; ctx.save(); ctx.fillStyle = '#fff'; ctx.fillRect(x1 - pad, y1 - pad, rw + 2 * pad, rh + 2 * pad); const fs = Math.min(28, Math.max(12, Math.floor(rh * 0.35))); ctx.font = `bold ${fs}px "Comic Neue","Bangers","Impact","Arial Black",sans-serif`; // Wait for font to load before applying ctx.textBaseline = 'middle'; ctx.fillStyle = '#000'; const text = String(region.text || ''); if (!text.trim()) { ctx.restore(); return; } const isCJK = CJK_RE.test(text), tall = rh > rw * 1.25; if (isCJK && tall) { const chars = [...text]; const maxPerCol = Math.max(1, Math.floor(rh / (fs * 1.1))); const cols = Math.ceil(chars.length / maxPerCol); const colW = Math.min(fs * 1.05, rw / cols); for (let c = 0; c < cols; c++) { const colX = x2 - (c + 0.5) * colW; for (let i = 0; i < maxPerCol; i++) { const idx = c * maxPerCol + i; if (idx >= chars.length) break; ctx.fillText(chars[idx], colX, y1 + (i + 0.5) * (fs * 1.1)); } } } else { const lines = (isCJK ? wrapCJK(ctx, text, rw - 12) : wrapLatin(ctx, text, rw - 12)); ctx.textAlign = 'center'; const lh = fs * 1.2; const total = lines.length * lh; let yy = y1 + (rh - total) / 2 + lh / 2; for (const L of lines) { ctx.fillText(L, x1 + rw / 2, Math.round(yy)); yy += lh; } } ctx.restore(); } function deviceId() { let id = GM_getValue('device_id'); if (!id) { id = 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, c => ((c === 'x' ? Math.random() * 16 : (Math.random() * 16 & 3) | 8) | 0).toString(16)); GM_setValue('device_id', id); } return id; } async function externalAPI(url, lang = 'English') { const blob = await fetchBlob(url); const resp = await new Promise((ok, err) => GM_xmlhttpRequest({ method: 'POST', url: `https://ocrt.iwanhae.kr/ocrv1?lang=${lang}`, headers: { 'X-DEVICE-ID': deviceId(), 'X-REFERER': location.hostname, 'X-REFERER-PATH': location.pathname, 'Content-Type': blob.type || 'image/webp' }, data: blob, timeout: 120000, onload: r => ok(r.responseText || ''), onerror: () => err(new Error('external net')), ontimeout: () => err(new Error('external timeout')) })); const segments = []; for (const line of resp.split(/\r?\n/)) { const match = line.match(/^data:\s*(\{.*\})\s*$/); if (!match) continue; try { const obj = JSON.parse(match[1]); if (obj?.type === 'segment' && obj.segment?.box_2d) segments.push({ text: obj.segment.text || '', translation: obj.segment.translation || '', box: obj.segment.box_2d }); } catch {} } return segments; } async function geminiAPI(url, W, H) { const key = GM_getValue('gemini_key'); if (!key) throw new Error('Set Gemini key via preset'); const targetLang = GM_getValue('target_lang', 'English'); const b64 = await fetchBase64(url); const body = { contents: [{ parts: [ // prompt complexity: percentages > pixel { text: `Detect ALL text in manga image (include partial edges). Extract original text and translate to ${targetLang}. Return JSON: {"regions":[{"text":"original text","translation":"translated text","position":{"x":20.5,"y":30.2,"width":15.3,"height":10.1}}]} Position values are percentages (0-100).` }, { inline_data: { mime_type: 'image/jpeg', data: b64 } } ]}]}; const text = await new Promise((ok, err) => GM_xmlhttpRequest({ method: 'POST', url: `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite-preview-09-2025:generateContent?key=${key}`, headers: { 'Content-Type': 'application/json' }, data: JSON.stringify(body), timeout: 60000, onload: r => { if (r.status >= 200 && r.status < 300) { try { const j = JSON.parse(r.responseText); ok(j.candidates?.[0]?.content?.parts?.[0]?.text || ''); } catch { err(new Error('Gemini parse')); } } else err(new Error('Gemini HTTP ' + r.status)); }, onerror: () => err(new Error('Gemini net')), ontimeout: () => err(new Error('Gemini timeout')) })); const m = text.match(/\{[\s\S]*\}/); if (!m) throw new Error('Gemini JSON missing'); const res = JSON.parse(m[0]), out = []; for (const r of (res?.regions || [])) { const p = r.position || { x: 0, y: 0, width: 0, height: 0 }; const x1 = Math.round(p.x / 100 * W), y1 = Math.round(p.y / 100 * H); const x2 = Math.round(x1 + p.width / 100 * W), y2 = Math.round(y1 + p.height / 100 * H); out.push({ text: r.text || '', translation: r.translation || '', box: [x1, y1, x2, y2] }); } return out; } async function serverDetect(url) { const b64 = await fetchBase64(url); const r = await gmFetch(`${API_BASE}/detect`, { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ image: b64 }) }); if (r?.status !== 'ok') throw new Error('detect failed'); return r.boxes || []; } async function serverOCR(url, boxes) { const b64 = await fetchBase64(url); const r = await gmFetch(`${API_BASE}/ocr`, { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ image: b64, boxes }) }); if (r?.status !== 'ok') throw new Error('ocr failed'); return r.texts || []; } async function serverTranslateMBART(texts) { const r = await gmFetch(`${API_BASE}/translate_mbart`, { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ texts }) }); if (r?.status !== 'ok') throw new Error('mbart failed'); return r.translations; } async function serverColorize(url, sigma = 15) { const b64 = await fetchBase64(url); const r = await gmFetch(`${API_BASE}/colorize`, { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ image: b64, denoise_sigma: sigma }), timeout: 180000 }); if (r?.status !== 'ok') throw new Error('colorize failed'); return 'data:image/png;base64,' + r.image; } const CTD_URL = 'https://huggingface.co/mayocream/comic-text-detector-onnx/resolve/main/comic-text-detector.onnx'; let ctdInputName = 'images'; // === FIX: Use MT state for CTD session === async function ensureCTD() { if (MT.ctdSession) return; if (!MT.ctdBytes) { log('CTD: downloading...'); MT.ctdBytes = await gmFetch(CTD_URL, { responseType: 'arraybuffer' }); log(`CTD: ${(MT.ctdBytes.byteLength / 1e6).toFixed(1)}MB`); } MT.ctdSession = await createSession(MT.ctdBytes, 'CTD'); ctdInputName = MT.ctdSession.inputNames?.[0] || 'images'; } function chwFromBitmap(bitmap, size) { const c = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas'); c.width = size; c.height = size; const g = c.getContext('2d'); g.drawImage(bitmap, 0, 0, size, size); const d = g.getImageData(0, 0, size, size).data; const plane = size * size, out = new Float32Array(3 * plane); for (let i = 0; i < plane; i++) { out[i] = d[i * 4] / 255; out[plane + i] = d[i * 4 + 1] / 255; out[2 * plane + i] = d[i * 4 + 2] / 255; } return out; } function decodeCTD(tensor, inSize, natW, natH) { const dims = tensor.dims, data = tensor.data; const N = dims[1], D = dims[2]; const sx = natW / inSize, sy = natH / inSize; let boxes = [], scores = []; for (let i = 0; i < N; i++) { const off = i * D; const cx = data[off], cy = data[off + 1], ww = data[off + 2], hh = data[off + 3]; const norm = Math.max(cx, cy, ww, hh) <= 1.5; const scaleX = norm ? inSize : 1, scaleY = norm ? inSize : 1; let obj = 0.5, cls = 1.0; if (D >= 5) obj = data[off + 4]; if (D >= 6) { let mx = -1e9; for (let k = 5; k < D; k++) if (data[off + k] > mx) mx = data[off + k]; cls = mx; } const conf = obj * cls; if (conf < CTD_CONF_THR) continue; const x = cx * scaleX, y = cy * scaleY, w = ww * scaleX, h = hh * scaleY; const x1 = Math.round(Math.max(0, Math.min(inSize, x - w / 2)) * sx); const y1 = Math.round(Math.max(0, Math.min(inSize, y - h / 2)) * sy); const x2 = Math.round(Math.max(0, Math.min(inSize, x + w / 2)) * sx); const y2 = Math.round(Math.max(0, Math.min(inSize, y + h / 2)) * sy); if ((x2 - x1) >= 6 && (y2 - y1) >= 6) { boxes.push([x1, y1, x2, y2]); scores.push(conf); } } if (!boxes.length) return []; const keep = nms(boxes, scores, CTD_IOU_THR); return keep.map(i => boxes[i]); } async function detectCTD(url, W, H) { await ensureCTD(); const bm = await getBitmap(url); const chw = chwFromBitmap(bm, CTD_INPUT_SIZE); const out = await MT.ctdSession.run({ [ctdInputName]: new ort.Tensor('float32', chw, [1, 3, CTD_INPUT_SIZE, CTD_INPUT_SIZE]) }); const outName = MT.ctdSession.outputNames?.[0] || Object.keys(out)[0]; const tensor = out[outName]; return (!tensor || tensor.dims.length !== 3 || tensor.dims[2] < 6) ? [] : decodeCTD(tensor, CTD_INPUT_SIZE, W, H); } // DB text detector (PP-OCRv3): self-contained with hardcoded thresholds const DB_URL = 'https://cdn.jsdelivr.net/npm/[email protected]/models/en_PP-OCRv3_det_infer.onnx'; const DB_SIZE = 640; let dbInputName = 'x'; // === FIX: Use MT state for DB session === async function ensureDB() { if (MT.dbSession) return; if (!MT.dbBytes) { log('DB: downloading...'); MT.dbBytes = await gmFetch(DB_URL, { responseType: 'arraybuffer' }); } MT.dbSession = await createSession(MT.dbBytes, 'DB'); dbInputName = MT.dbSession.inputNames?.[0] || 'x'; } function dbPreprocess(bmp) { const W = bmp.width, H = bmp.height; const scale = Math.min(DB_SIZE / W, DB_SIZE / H); const newW = Math.round(W * scale), newH = Math.round(H * scale); const padX = Math.floor((DB_SIZE - newW) / 2), padY = Math.floor((DB_SIZE - newH) / 2); const oc = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(DB_SIZE, DB_SIZE) : document.createElement('canvas'); oc.width = DB_SIZE; oc.height = DB_SIZE; const ctx = oc.getContext('2d'); ctx.fillStyle = '#000'; ctx.fillRect(0, 0, DB_SIZE, DB_SIZE); ctx.drawImage(bmp, 0, 0, W, H, padX, padY, newW, newH); const d = ctx.getImageData(0, 0, DB_SIZE, DB_SIZE).data; const plane = DB_SIZE * DB_SIZE, chw = new Float32Array(plane * 3); for (let i = 0, j = 0; j < plane; j++, i += 4) { chw[j] = d[i] / 255; chw[plane + j] = d[i + 1] / 255; chw[2 * plane + j] = d[i + 2] / 255; } return { tensorData: chw, padX, padY, scale }; } function dbPostprocess(prob, W, H, thr, meanKeep, unclipRatio, nmsIou) { const bins = new Uint8Array(W * H); for (let i = 0; i < W * H; i++) bins[i] = prob[i] >= thr ? 1 : 0; const visited = new Uint8Array(W * H); const id = (x, y) => y * W + x; const dirs = [[1,0],[-1,0],[0,1],[0,-1],[1,1],[1,-1],[-1,1],[-1,-1]]; const comps = []; const qx = new Int32Array(W * H), qy = new Int32Array(W * H); const MIN_W = Math.max(6, Math.floor(W * 0.01)), MIN_H = Math.max(6, Math.floor(H * 0.01)); for (let y = 0; y < H; y++) { for (let x = 0; x < W; x++) { const p = id(x, y); if (!bins[p] || visited[p]) continue; let qh = 0, qt = 0; qx[qt] = x; qy[qt] = y; qt++; visited[p] = 1; let minx = x, miny = y, maxx = x, maxy = y, sum = 0, cnt = 0; while (qh < qt) { const cx = qx[qh], cy = qy[qh]; qh++; const ip = id(cx, cy); sum += prob[ip]; cnt++; if (cx < minx) minx = cx; if (cy < miny) miny = cy; if (cx > maxx) maxx = cx; if (cy > maxy) maxy = cy; for (const [dx, dy] of dirs) { const nx = cx + dx, ny = cy + dy; if (nx < 0 || ny < 0 || nx >= W || ny >= H) continue; const np = id(nx, ny); if (!bins[np] || visited[np]) continue; visited[np] = 1; qx[qt] = nx; qy[qt] = ny; qt++; } } const mean = sum / Math.max(1, cnt); if (mean < meanKeep) continue; const bw = maxx - minx + 1, bh = maxy - miny + 1; if (bw < MIN_W || bh < MIN_H) continue; const cx = minx + bw / 2, cy = miny + bh / 2; const sx = bw * unclipRatio, sy = bh * unclipRatio; const x1 = Math.max(0, Math.round(cx - sx / 2)), y1 = Math.max(0, Math.round(cy - sy / 2)); const x2 = Math.min(W, Math.round(cx + sx / 2)), y2 = Math.min(H, Math.round(cy + sy / 2)); comps.push({ xyxy: [x1, y1, x2, y2], score: mean }); } } comps.sort((a, b) => b.score - a.score); const kept = []; for (const c of comps) { let ok = true; for (const k of kept) if (iou(c.xyxy, k.xyxy) > nmsIou) { ok = false; break; } if (ok) kept.push(c); } return kept.map(c => c.xyxy); } function mergeDbBoxes(boxes) { if (boxes.length <= 1) return boxes; const n = boxes.length, parent = [...Array(n).keys()]; const find = i => parent[i] === i ? i : (parent[i] = find(parent[i])); for (let i = 0; i < n; i++) { for (let j = i + 1; j < n; j++) { const [ax1, ay1, ax2, ay2] = boxes[i], [bx1, by1, bx2, by2] = boxes[j]; const gapX = Math.max(0, Math.max(ax1, bx1) - Math.min(ax2, bx2)); const gapY = Math.max(0, Math.max(ay1, by1) - Math.min(ay2, by2)); if (gapX < 10 && gapY < 10) parent[find(i)] = find(j); } } const groups = new Map(); for (let i = 0; i < n; i++) { const r = find(i), b = boxes[i]; if (!groups.has(r)) groups.set(r, [...b]); else { const g = groups.get(r); g[0] = Math.min(g[0], b[0]); g[1] = Math.min(g[1], b[1]); g[2] = Math.max(g[2], b[2]); g[3] = Math.max(g[3], b[3]); } } return [...groups.values()]; } async function detectDB(url, W, H) { await ensureDB(); const bm = await getBitmap(url); const prep = dbPreprocess(bm); const feeds = {}; feeds[dbInputName] = new ort.Tensor('float32', prep.tensorData, [1, 3, DB_SIZE, DB_SIZE]); const out = await MT.dbSession.run(feeds); let outTensor = null; for (const k of Object.keys(out)) { const t = out[k], d = t.dims || []; if ((d.length === 4 && d[0] === 1 && d[1] === 1 && d[2] === DB_SIZE && d[3] === DB_SIZE) || (d.length === 3 && d[0] === 1 && d[1] === DB_SIZE && d[2] === DB_SIZE)) { outTensor = t; break; } } if (!outTensor) outTensor = out[Object.keys(out)[0]]; let probData; try { probData = await outTensor.getData(true); } catch { probData = outTensor.data; } const prob = probData.length === DB_SIZE * DB_SIZE ? probData : probData.slice(0, DB_SIZE * DB_SIZE); const boxes640 = dbPostprocess(prob, DB_SIZE, DB_SIZE, 0.30, 0.55, 1.60, 0.2); let boxes = boxes640.map(b => { const [x1, y1, x2, y2] = b; const rx1 = Math.max(0, Math.min(W, Math.round((x1 - prep.padX) / prep.scale))); const ry1 = Math.max(0, Math.min(H, Math.round((y1 - prep.padY) / prep.scale))); const rx2 = Math.max(0, Math.min(W, Math.round((x2 - prep.padX) / prep.scale))); const ry2 = Math.max(0, Math.min(H, Math.round((y2 - prep.padY) / prep.scale))); return [rx1, ry1, rx2, ry2]; }); return mergeDbBoxes(boxes); } const MANGA_OCR = { encoder: 'https://huggingface.co/l0wgear/manga-ocr-2025-onnx/resolve/main/encoder_model.onnx', decoder: 'https://huggingface.co/l0wgear/manga-ocr-2025-onnx/resolve/main/decoder_model.onnx', tokenizer: 'https://huggingface.co/l0wgear/manga-ocr-2025-onnx/resolve/main/tokenizer.json' }; class MangaOCRWeb { constructor() { this.encoder = null; this.decoder = null; this.vocab = []; this.V = 0; this.maxLen = 50; this.encBytes = null; this.decBytes = null; } async init() { if (this.encoder && this.decoder) return; log('MangaOCR: downloading...'); const [tok, enc, dec] = await Promise.all([ this.vocab.length ? Promise.resolve(null) : gmFetch(MANGA_OCR.tokenizer, { responseType: 'json' }), this.encBytes || gmFetch(MANGA_OCR.encoder, { responseType: 'arraybuffer' }), this.decBytes || gmFetch(MANGA_OCR.decoder, { responseType: 'arraybuffer' }) ]); if (tok) { const arr = Object.entries(tok.model.vocab).sort((a, b) => a[1] - b[1]); this.vocab = arr.map(([t]) => t); this.V = this.vocab.length; } if (!this.encBytes) this.encBytes = enc; if (!this.decBytes) this.decBytes = dec; log(`MangaOCR: vocab=${this.V}, enc=${(this.encBytes.byteLength / 1e6).toFixed(1)}MB, dec=${(this.decBytes.byteLength / 1e6).toFixed(1)}MB`); this.encoder = await createSession(this.encBytes, 'OCR-Enc'); this.decoder = await createSession(this.decBytes, 'OCR-Dec'); } async ensure() { if (!this.encoder || !this.decoder) await this.init(); return this; } cropTensor(bm, box, imgW, imgH, useLowPadding = false) { const [x1, y1, x2, y2] = box; const pad = useLowPadding ? Math.floor(OCR_BASE_PADDING / 2) : OCR_BASE_PADDING; const px1 = Math.max(0, x1 - pad), py1 = Math.max(0, y1 - pad); const px2 = Math.min(imgW, x2 + pad), py2 = Math.min(imgH, y2 + pad); const c = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(256, 256) : document.createElement('canvas'); c.width = 256; c.height = 256; const g = c.getContext('2d'); g.drawImage(bm, px1, py1, px2 - px1, py2 - py1, 0, 0, 256, 256); const d = g.getImageData(16, 16, 224, 224).data; const N = 224 * 224; const R = new Float32Array(N), G = new Float32Array(N), B = new Float32Array(N); for (let i = 0, j = 0; i < d.length; i += 4, j++) { R[j] = d[i] / 255 * 2 - 1; G[j] = d[i + 1] / 255 * 2 - 1; B[j] = d[i + 2] / 255 * 2 - 1; } return { R, G, B }; } // === FIX: Process one box at a time to avoid session conflicts === async ocrOneBox(bm, box, imgW, imgH, useLowPadding) { const { R, G, B } = this.cropTensor(bm, box, imgW, imgH, useLowPadding); const plane = 224 * 224, batch = new Float32Array(3 * plane); batch.set(R, 0); batch.set(G, plane); batch.set(B, 2 * plane); const encOut = await this.encoder.run({ pixel_values: new ort.Tensor('float32', batch, [1, 3, 224, 224]) }); const hs = encOut.last_hidden_state, seq = hs.dims[1], hid = hs.dims[2]; const hsTensor = new ort.Tensor('float32', hs.data, [1, seq, hid]); const ids = [2n]; for (let step = 0; step < this.maxLen; step++) { const decOut = await this.decoder.run({ input_ids: new ort.Tensor('int64', new BigInt64Array(ids), [1, ids.length]), encoder_hidden_states: hsTensor }); const logits = decOut.logits.data, off = (ids.length - 1) * this.V; let mx = -1e9, idx = 0; for (let j = 0; j < this.V; j++) if (logits[off + j] > mx) { mx = logits[off + j]; idx = j; } if (idx === 3) break; ids.push(BigInt(idx)); } return ids.slice(1).filter(n => n > 14n).map(i => this.vocab[Number(i)]).join(''); } async ocrBatchWithBitmap(bm, imgW, imgH, boxes) { const out = [], nearbyIndices = findNearbyBoxIndices(boxes); for (let i = 0; i < boxes.length; i++) { out.push(await this.ocrOneBox(bm, boxes[i], imgW, imgH, nearbyIndices.has(i))); } return out; } } // === FIX: Use MT state for MangaOCR === async function ensureMangaOCR() { if (!MT.mangaOCR) MT.mangaOCR = new MangaOCRWeb(); await MT.mangaOCR.ensure(); return MT.mangaOCR; } function deduplicateTexts(texts, boxes) { const seen = new Map(), result = []; for (let i = 0; i < texts.length; i++) { const text = texts[i], box = boxes[i]; if (seen.has(text) && text.trim()) { const prevIdx = seen.get(text); if (iou(box, boxes[prevIdx]) > 0.3) { result.push(''); continue; } } seen.set(text, i); result.push(text); } return result; } function isJapanese(text) { return CJK_RE.test(text); } // Filter out Japanese text (translation failed) async function translateGoogle(texts) { if (!texts.length) return []; const SEP = '\u241E', esc = s => s.replaceAll(SEP, ' '); const indices = [], nonEmpty = []; for (let i = 0; i < texts.length; i++) if (texts[i].trim()) { indices.push(i); nonEmpty.push(texts[i]); } if (!nonEmpty.length) return new Array(texts.length).fill(''); const q = nonEmpty.map(esc).join(SEP); const p = new URLSearchParams({ client: 'gtx', sl: 'auto', tl: 'en', dt: 't', q }); const r = await gmFetch(`https://translate.googleapis.com/translate_a/single?${p}`, { timeout: 15000, responseType: 'json' }); let out = ''; if (Array.isArray(r?.[0])) for (const seg of r[0]) if (seg?.[0]) out += seg[0]; const translated = out.split(SEP); const result = new Array(texts.length).fill(''); const minLen = Math.min(indices.length, translated.length); // mapping: handle separator split mismatches for (let i = 0; i < minLen; i++) { const tr = translated[i] || ''; // Only use translation if it's not empty and not still Japanese result[indices[i]] = (tr.trim() && !isJapanese(tr)) ? tr : ''; } return result; } async function translateMyMemory(texts) { if (!texts.length) return []; const url = 'https://api.mymemory.translated.net/get'; const params = new URLSearchParams({ q: texts.join('\n'), langpair: 'ja|en', de: '[email protected]' }); try { const r = await gmFetch(`${url}?${params}`, { timeout: 15000, responseType: 'json' }); if (r?.responseStatus === 200) { const translated = r.responseData?.translatedText || ''; if (!translated || translated.includes('MetaMask')) return translateGoogle(texts); const arr = translated.split('\n'); while (arr.length < texts.length) arr.push(''); return arr.slice(0, texts.length); } return translateGoogle(texts); } catch { return translateGoogle(texts); } } async function getSegmentsFromAIO(url, W, H) { const mode = GM_getValue('mode'), override = GM_getValue('translator', 'none'); let segs = (mode === 'gemini') ? await geminiAPI(url, W, H) : await externalAPI(url); if (override !== 'none') { const src = segs.map(s => s.text || ''); const tr = override === 'mbart' ? await serverTranslateMBART(src) : override === 'google' ? await translateGoogle(src) : override === 'mymemory' ? await translateMyMemory(src) : src; segs = segs.map((s, i) => ({ ...s, translation: tr[i] || s.translation || '' })); } return segs; } async function detectBoxes(url, W, H) { const d = GM_getValue('detector'); let raw = []; if (d === 'yolo') raw = await serverDetect(url); else if (d === 'ctd') raw = await detectCTD(url, W, H); else if (d === 'db') raw = await detectDB(url, W, H); return sortReadingOrder(raw, true); } async function ocrTexts(url, W, H, boxes) { const o = GM_getValue('ocr'); if (o === 'server') return await serverOCR(url, boxes); if (o === 'manga2025') { const m = await ensureMangaOCR(), bm = await getBitmap(url); const rawTexts = await m.ocrBatchWithBitmap(bm, W, H, boxes); return deduplicateTexts(rawTexts, boxes); } return []; } async function translateTexts(texts) { const t = GM_getValue('translator'); if (t === 'mbart') return await serverTranslateMBART(texts); if (t === 'google') return await translateGoogle(texts); if (t === 'mymemory') return await translateMyMemory(texts); return texts; } // === FIX: Main processing function with queue support === async function run(img) { const startUrl = resolveUrl(img); if (!startUrl) { log('No valid image URL'); return; } if (startUrl.startsWith('data:') && !img.getContext) return; if (MT.processed.has(startUrl)) return; MT.processed.add(startUrl); const t0 = performance.now(); if (!img.getContext && (!img.complete || !img.naturalWidth)) { img.addEventListener('load', () => queueImage(img), { once: true }); MT.processed.delete(startUrl); return; } const W = img.naturalWidth || img.width, H = img.naturalHeight || img.height; log(`Processing ${W}x${H}...`); try { let base = await fetchBlob(startUrl); if (GM_getValue('mode') === 'server' && GM_getValue('colorize', true)) { try { const b64 = await serverColorize(startUrl); base = await fetch(b64).then(r => r.blob()); } catch (e) { log('⚠️ Colorize:', e.message || e); } } const canvas = await createCanvasFromBlob(base, W, H); if (GM_getValue('aio', true)) { const segs = await getSegmentsFromAIO(startUrl, W, H); for (const s of segs) { const text = s.translation || s.text || ''; if (text.trim() && !isJapanese(text)) drawTextOnCanvas(canvas, { box: s.box, text }); } } else { const boxes = await detectBoxes(startUrl, W, H); log(`Found ${boxes.length} boxes`); if (boxes.length) { await getBitmap(startUrl); const texts = await ocrTexts(startUrl, W, H, boxes); log(`OCR: ${texts.filter(t => t).length} texts`); const trans = await translateTexts(texts); log(`Translated: ${trans.filter(t => t).length}`); const items = boxes.map((box, i) => ({ box, text: trans[i] || '', area: (box[2] - box[0]) * (box[3] - box[1]) })); items.sort((a, b) => b.area - a.area); for (const it of items) { if (it.text.trim() && !isJapanese(it.text)) drawTextOnCanvas(canvas, { box: it.box, text: it.text }); } } } const currentUrl = resolveUrl(img); if (currentUrl !== startUrl) { log('Image changed, discarding'); bitmapCache.delete(startUrl); return; } if (img.getContext) { const x = img.getContext('2d'); img.width = W; img.height = H; x.clearRect(0, 0, W, H); x.drawImage(canvas, 0, 0); } else { img.src = canvas.toDataURL('image/png'); } bitmapCache.delete(startUrl); log(`✓ Done in ${((performance.now() - t0) / 1000).toFixed(2)}s`); } catch (e) { log('ERR:', e.message || e); MT.processed.delete(startUrl); // Allow retry on error } } // === FIX: Queue processor - one image at a time === async function processQueue() { if (MT.processing || !MT.queue.length) return; MT.processing = true; while (MT.queue.length) { const img = MT.queue.shift(); if (img.isConnected) await run(img); } MT.processing = false; } function queueImage(img) { const url = resolveUrl(img); if (!url || url.startsWith('data:') || MT.processed.has(url)) return; if (!MT.queue.includes(img)) MT.queue.push(img); processQueue(); } function processVisibleImage() { const img = getVisibleMangaImage(); if (!img) return; queueImage(img); } let autoTimer = null; function tryAutoProcess() { const img = getVisibleMangaImage(); if (!img) return; const notReady = !img.getContext && (!img.complete || !img.naturalWidth); if (notReady) { img.addEventListener('load', () => tryAutoProcess(), { once: true }); return; } queueImage(img); } const observer = new MutationObserver(() => { if (autoTimer) return; autoTimer = setTimeout(() => { autoTimer = null; tryAutoProcess(); }, 150); }); setTimeout(() => { ensureCTD().catch(() => {}); ensureMangaOCR().catch(() => {}); const container = document.querySelector('.reader-images, .comic-container, .chapter-content, main, article, #content, #viewer') || document.body; observer.observe(container, { childList: true, subtree: true, attributes: true, attributeFilter: ['src', 'data-src'] }); tryAutoProcess(); log('Auto-watch active'); }, 500); })();
