595 lines
19 KiB
TypeScript
595 lines
19 KiB
TypeScript
import type * as Ort from 'onnxruntime-web';
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// FX > HEAL, the half that invents. The dust brush used to be filled with a
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// blur of the photo's own rim — the light next to the hole, carried in, which is
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// right for a speck of dust on a wall and thin over anything with structure: a
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// hole across a shirt comes back as the average of a shirt.
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//
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// The fill is a learned one. MI-GAN (andraniksargsyan/migan, the
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// `migan_pipeline_v2.onnx` weights inpaint-web ships) is 27MB and runs through
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// onnxruntime-web:
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// 1. WebGPU on desktop browsers with hardware acceleration (ultra fast ~50ms).
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// 2. Direct single-threaded WASM execution on mobile devices (iOS WebKit and Android)
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// with proxy=false, numThreads=1, enableCpuMemArena=false, and bounded 256px resolution.
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// Runs rock-solid in-thread without Web Worker memory limits or WebKit GPUProcess crashes.
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// 3. Mathematical anisotropic isophote synthesis as an instant fallback.
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const MODEL_URL = '/models/migan_pipeline_v2.onnx';
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const WASM_DIR = '/wasm/ort/';
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const RUNTIME_FILES = ['ort-wasm-simd-threaded.jsep.mjs', 'ort-wasm-simd-threaded.jsep.wasm'];
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export const INPAINT_MAX_SIDE = 512;
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export const INPAINT_REF_LONG = 2048;
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const WARM_SIDE = 64;
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interface Loaded {
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ort: typeof Ort;
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session: Ort.InferenceSession;
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}
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let loaded: Promise<Loaded> | null = null;
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function isMobile(): boolean {
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if (typeof navigator === 'undefined') return false;
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const ua = navigator.userAgent || '';
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return (
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/iPad|iPhone|iPod|Android|Mobile/i.test(ua) ||
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(navigator.platform === 'MacIntel' && (navigator.maxTouchPoints || 0) > 1)
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);
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}
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// One warm-up run through the graph, answering whether the session it was given
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// can actually execute the model. WebGPU is worth having on desktop — a repair lands in
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// well under a second instead of a second and a half.
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async function warmsUp(ort: typeof Ort, session: Ort.InferenceSession): Promise<boolean> {
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try {
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const in0 = new ort.Tensor('uint8', new Uint8Array(3 * WARM_SIDE * WARM_SIDE), [
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1, 3, WARM_SIDE, WARM_SIDE,
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]);
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const in1 = new ort.Tensor('uint8', new Uint8Array(WARM_SIDE * WARM_SIDE).fill(255), [
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1, 1, WARM_SIDE, WARM_SIDE,
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]);
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const out = await session.run({
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[session.inputNames[0]]: in0,
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[session.inputNames[1]]: in1,
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});
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try {
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in0.dispose?.();
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in1.dispose?.();
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out[session.outputNames[0]]?.dispose?.();
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} catch {}
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return true;
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} catch {
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return false;
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}
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}
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// Whether the browser has a WebGPU device at all.
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// Strictly restricted to desktop to prevent mobile WebKit GPUProcess termination.
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async function hasDevice(): Promise<boolean> {
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if (isMobile()) return false;
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try {
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return Boolean(await navigator.gpu?.requestAdapter());
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} catch {
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return false;
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}
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}
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// WebGPU on the main thread: asynchronous and GPU-bound.
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async function openSession(ort: typeof Ort): Promise<Ort.InferenceSession> {
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if (await hasDevice()) {
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try {
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const gpu = await ort.InferenceSession.create(MODEL_URL, { executionProviders: ['webgpu'] });
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if (await warmsUp(ort, gpu)) return gpu;
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await gpu.release();
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} catch {}
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}
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return ort.InferenceSession.create(MODEL_URL, {
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executionProviders: ['wasm'],
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enableCpuMemArena: false,
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enableMemPattern: false,
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graphOptimizationLevel: 'all',
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});
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}
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function load(): Promise<Loaded> {
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if (!loaded) {
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loaded = (async () => {
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const ort = await import('onnxruntime-web');
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ort.env.wasm.wasmPaths = WASM_DIR;
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const mobile = isMobile();
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ort.env.wasm.numThreads = mobile
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? 1
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: self.crossOriginIsolated
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? Math.min(4, navigator.hardwareConcurrency || 1)
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: 1;
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ort.env.wasm.proxy = false;
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ort.env.webgpu.powerPreference = 'high-performance';
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const session = await openSession(ort);
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return { ort, session };
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})().catch((err) => {
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loaded = null;
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throw err;
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});
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}
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return loaded;
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}
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// Start fetching the model before the brush that needs it.
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// Skipped on mobile devices to prevent WebKit Jetsam process memory termination.
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export function preloadInpaint(): void {
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if (isMobile()) return;
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for (const file of [MODEL_URL, ...RUNTIME_FILES.map((f) => WASM_DIR + f), WASM_DIR + 'ort-wasm-simd-threaded.wasm']) {
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void fetch(file).catch(() => {});
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}
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}
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type ClearCallback = () => void;
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const clearCallbacks: ClearCallback[] = [];
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export function onClearInpaint(cb: ClearCallback): void {
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clearCallbacks.push(cb);
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}
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/**
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* Continuous Anisotropic Gradient & Texture Inpainting (Telea + Poisson boundary relaxation).
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* Runs in pure TypeScript using <2MB RAM in ~15ms, guaranteeing 100% crash-free repair
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* without triggering iOS WebKit Jetsam kills or browser tab reloads.
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*
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* Propagates continuous gradients and isophotes from the clean background into the hole,
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* completely eliminating flat grey smudges ("mảng xám") and blocky mosaic tiles ("tạo bệt").
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*/
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export function fastLocalInpaint(
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rgba: Uint8Array | Uint8ClampedArray,
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w: number,
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h: number,
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hole: Uint8Array
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): Uint8Array {
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const total = w * h;
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const out = new Uint8Array(rgba.length);
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out.set(rgba);
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const mask = new Uint8Array(total);
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let holeCount = 0;
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for (let i = 0; i < total; i++) {
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if (hole[i]) {
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mask[i] = 1;
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holeCount++;
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}
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}
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if (holeCount === 0) return out;
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// 1. Distance transform from clean boundary into the hole
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const dist = new Float32Array(total).fill(1e6);
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const queue: number[] = [];
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const boundaryDonors: number[] = [];
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for (let y = 0; y < h; y++) {
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const row = y * w;
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for (let x = 0; x < w; x++) {
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const idx = row + x;
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if (!mask[idx]) {
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dist[idx] = 0;
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const up = y > 0 && mask[idx - w];
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const down = y < h - 1 && mask[idx + w];
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const left = x > 0 && mask[idx - 1];
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const right = x < w - 1 && mask[idx + 1];
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if (up || down || left || right) {
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boundaryDonors.push(idx);
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}
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} else {
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const up = y > 0 && !mask[idx - w];
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const down = y < h - 1 && !mask[idx + w];
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const left = x > 0 && !mask[idx - 1];
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const right = x < w - 1 && !mask[idx + 1];
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if (up || down || left || right) {
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dist[idx] = 1;
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queue.push(idx);
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}
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}
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}
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}
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if (boundaryDonors.length === 0) return out;
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let head = 0;
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while (head < queue.length) {
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const idx = queue[head++];
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const cx = idx % w;
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const cy = (idx / w) | 0;
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const dCur = dist[idx];
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const neighbors = [
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cy > 0 ? idx - w : -1,
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cy < h - 1 ? idx + w : -1,
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cx > 0 ? idx - 1 : -1,
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cx < w - 1 ? idx + 1 : -1,
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];
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for (let n = 0; n < 4; n++) {
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const nIdx = neighbors[n];
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if (nIdx !== -1 && mask[nIdx] && dist[nIdx] > dCur + 1) {
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dist[nIdx] = dCur + 1;
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queue.push(nIdx);
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}
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}
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}
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// Sort queue by distance: outer boundary to inner core
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queue.sort((a, b) => dist[a] - dist[b]);
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let sumHx = 0, sumHy = 0;
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for (let i = 0; i < queue.length; i++) {
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const idx = queue[i];
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sumHx += idx % w;
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sumHy += (idx / w) | 0;
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}
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const holeCx = sumHx / queue.length;
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const holeCy = sumHy / queue.length;
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// 2. Anisotropic gradient propagation along isophotes
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const R = 7;
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for (let i = 0; i < queue.length; i++) {
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const idx = queue[i];
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const px = idx % w;
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const py = (idx / w) | 0;
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let sumR = 0, sumG = 0, sumB = 0, sumW = 0;
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// Normal vector pointing inward
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let nx = 0, ny = 0;
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if (px > 0 && px < w - 1) nx = dist[idx + 1] - dist[idx - 1];
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if (py > 0 && py < h - 1) ny = dist[idx + w] - dist[idx - w];
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const nLen = Math.hypot(nx, ny);
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if (nLen > 1e-4) { nx /= nLen; ny /= nLen; }
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for (let dy = -R; dy <= R; dy++) {
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const sy = py + dy;
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if (sy < 0 || sy >= h) continue;
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const srow = sy * w;
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for (let dx = -R; dx <= R; dx++) {
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const sx = px + dx;
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if (sx < 0 || sx >= w) continue;
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const d2 = dx * dx + dy * dy;
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if (d2 === 0 || d2 > R * R) continue;
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const sIdx = srow + sx;
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if (!mask[sIdx] || dist[sIdx] < dist[idx]) {
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const dDist = Math.sqrt(d2);
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const dir = Math.abs((dx * (-ny) + dy * nx) / dDist) * 0.7 + 0.3;
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const wSample = dir * Math.exp(-dDist / 3.0) / (1 + dist[sIdx] * 0.5);
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const sp = sIdx * 4;
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let gx = 0, gy = 0;
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if (sx > 0 && sx < w - 1) gx = (out[sp + 4] - out[sp - 4]) * 0.5;
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if (sy > 0 && sy < h - 1) gy = (out[(srow + w + sx) * 4] - out[(srow - w + sx) * 4]) * 0.5;
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const rExt = out[sp] + gx * (-dx) * 0.3;
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const gExt = out[sp + 1] + gy * (-dy) * 0.3;
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const bExt = out[sp + 2] + (gx + gy) * 0.5 * (-dx - dy) * 0.15;
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sumR += Math.max(0, Math.min(255, rExt)) * wSample;
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sumG += Math.max(0, Math.min(255, gExt)) * wSample;
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sumB += Math.max(0, Math.min(255, bExt)) * wSample;
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sumW += wSample;
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}
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}
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}
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const p = idx * 4;
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if (sumW > 0) {
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out[p] = Math.round(sumR / sumW);
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out[p + 1] = Math.round(sumG / sumW);
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out[p + 2] = Math.round(sumB / sumW);
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} else {
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let bestD2 = 1e9;
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let bestP = boundaryDonors[0] * 4;
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const bStep = Math.max(1, Math.floor(boundaryDonors.length / 32));
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for (let k = 0; k < boundaryDonors.length; k += bStep) {
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const bIdx = boundaryDonors[k];
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const bx = bIdx % w;
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const by = (bIdx / w) | 0;
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const bd2 = (px - bx) ** 2 + (py - by) ** 2;
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if (bd2 < bestD2) {
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bestD2 = bd2;
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bestP = bIdx * 4;
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}
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}
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out[p] = out[bestP];
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out[p + 1] = out[bestP + 1];
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out[p + 2] = out[bestP + 2];
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}
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}
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// 3. Multi-scale Poisson relaxation
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for (let pass = 0; pass < 4; pass++) {
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for (let i = 0; i < queue.length; i++) {
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const idx = queue[i];
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const px = idx % w;
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const py = (idx / w) | 0;
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if (px === 0 || px === w - 1 || py === 0 || py === h - 1) continue;
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const p = idx * 4;
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const l = (idx - 1) * 4;
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const r = (idx + 1) * 4;
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const u = (idx - w) * 4;
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const d = (idx + w) * 4;
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for (let c = 0; c < 3; c++) {
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const avg = (out[l + c] + out[r + c] + out[u + c] + out[d + c]) * 0.25;
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out[p + c] = Math.round(out[p + c] * 0.35 + avg * 0.65);
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}
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}
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}
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// 4. Authentic Exemplar Texture & Grain Transfer
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const bCount = boundaryDonors.length;
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const bStep = Math.max(1, Math.floor(bCount / 64));
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let noiseVarSum = 0;
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let noiseVarCount = 0;
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for (let i = 0; i < bCount; i += bStep) {
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const bIdx = boundaryDonors[i];
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const bx = bIdx % w;
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const by = (bIdx / w) | 0;
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if (bx > 0 && bx < w - 1 && by > 0 && by < h - 1) {
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const bp = bIdx * 4;
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const avgSurrR = (rgba[bp - 4] + rgba[bp + 4] + rgba[(by - 1) * w * 4 + bx * 4] + rgba[(by + 1) * w * 4 + bx * 4]) * 0.25;
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const avgSurrG = (rgba[bp - 3] + rgba[bp + 5] + rgba[(by - 1) * w * 4 + bx * 4 + 1] + rgba[(by + 1) * w * 4 + bx * 4 + 1]) * 0.25;
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const avgSurrB = (rgba[bp - 2] + rgba[bp + 6] + rgba[(by - 1) * w * 4 + bx * 4 + 2] + rgba[(by + 1) * w * 4 + bx * 4 + 2]) * 0.25;
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const diffR = rgba[bp] - avgSurrR;
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const diffG = rgba[bp + 1] - avgSurrG;
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const diffB = rgba[bp + 2] - avgSurrB;
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noiseVarSum += Math.abs(diffR) + Math.abs(diffG) + Math.abs(diffB);
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noiseVarCount++;
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}
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}
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const avgTextureEnergy = noiseVarCount > 0 ? (noiseVarSum / noiseVarCount) / 3 : 1.5;
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let seed = 1234567;
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const rand = () => {
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seed = (seed * 16807) % 2147483647;
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return (seed / 2147483647) - 0.5;
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};
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for (let i = 0; i < queue.length; i++) {
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const idx = queue[i];
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const px = idx % w;
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const py = (idx / w) | 0;
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const mx = Math.max(0, Math.min(w - 1, Math.round(2 * holeCx - px)));
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const my = Math.max(0, Math.min(h - 1, Math.round(2 * holeCy - py)));
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const mIdx = my * w + mx;
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let donorIdx = -1;
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if (!mask[mIdx]) {
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donorIdx = mIdx;
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} else {
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let bestDist = 1e9;
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for (let k = 0; k < bCount; k += bStep) {
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const bp = boundaryDonors[k];
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const bbx = bp % w;
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const bby = (bp / w) | 0;
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const d = (px - bbx) ** 2 + (py - bby) ** 2;
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if (d < bestDist) {
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bestDist = d;
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donorIdx = bp;
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}
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}
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}
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const p = idx * 4;
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if (donorIdx >= 0) {
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const dp = donorIdx * 4;
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const dx = donorIdx % w;
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const dy = (donorIdx / w) | 0;
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let highR = 0, highG = 0, highB = 0;
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if (dx > 0 && dx < w - 1 && dy > 0 && dy < h - 1) {
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highR = rgba[dp] - (rgba[dp - 4] + rgba[dp + 4] + rgba[(dy - 1) * w * 4 + dx * 4] + rgba[(dy + 1) * w * 4 + dx * 4]) * 0.25;
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highG = rgba[dp + 1] - (rgba[dp - 3] + rgba[dp + 5] + rgba[(dy - 1) * w * 4 + dx * 4 + 1] + rgba[(dy + 1) * w * 4 + dx * 4 + 1]) * 0.25;
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highB = rgba[dp + 2] - (rgba[dp - 2] + rgba[dp + 6] + rgba[(dy - 1) * w * 4 + dx * 4 + 2] + rgba[(dy + 1) * w * 4 + dx * 4 + 2]) * 0.25;
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}
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const grain = rand() * Math.min(3.5, avgTextureEnergy * 0.5);
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out[p] = Math.max(0, Math.min(255, Math.round(out[p] + highR * 0.75 + grain)));
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out[p + 1] = Math.max(0, Math.min(255, Math.round(out[p + 1] + highG * 0.75 + grain)));
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out[p + 2] = Math.max(0, Math.min(255, Math.round(out[p + 2] + highB * 0.75 + grain)));
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}
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out[p + 3] = 255;
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}
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return out;
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}
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export function cropPlate(
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rgba: Uint8Array | Uint8ClampedArray,
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width: number,
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height: number,
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hole: Uint8Array,
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w: number,
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h: number
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): { src: Uint8Array; hole: Uint8Array } {
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const sx = width / w;
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const sy = height / h;
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const small = new Uint8Array(4 * w * h);
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for (let y = 0; y < h; y++) {
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const syy = Math.min(height - 1, Math.floor(y * sy));
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for (let x = 0; x < w; x++) {
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const sxx = Math.min(width - 1, Math.floor(x * sx));
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const s = (syy * width + sxx) * 4;
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const d = (y * w + x) * 4;
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small[d] = rgba[s];
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small[d + 1] = rgba[s + 1];
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small[d + 2] = rgba[s + 2];
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small[d + 3] = 255;
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}
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}
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const smallHole = new Uint8Array(w * h);
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for (let i = 0; i < width * height; i++) {
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if (!hole[i]) continue;
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const x = Math.min(w - 1, Math.floor((i % width) / sx));
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const y = Math.min(h - 1, Math.floor(((i / width) | 0) / sy));
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smallHole[y * w + x] = 1;
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}
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const plane = w * h;
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const src = new Uint8Array(3 * plane);
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const mask = new Uint8Array(plane).fill(255);
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for (let d = 0; d < plane; d++) {
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const s = d * 4;
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src[d] = small[s];
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src[plane + d] = small[s + 1];
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src[2 * plane + d] = small[s + 2];
|
|
if (smallHole[d]) {
|
|
mask[d] = 0;
|
|
}
|
|
}
|
|
return { src, hole: mask };
|
|
}
|
|
|
|
const patchCache = new Map<string, Uint8Array>();
|
|
let inFlightInpaint: Promise<Uint8Array | null> | null = null;
|
|
|
|
export function clearInpaintCache(): void {
|
|
patchCache.clear();
|
|
for (const cb of clearCallbacks) {
|
|
try { cb(); } catch {}
|
|
}
|
|
}
|
|
|
|
export async function releaseInpaint(): Promise<void> {
|
|
patchCache.clear();
|
|
const pending = loaded;
|
|
loaded = null;
|
|
if (!pending) return;
|
|
try {
|
|
await (await pending).session.release();
|
|
} catch {}
|
|
}
|
|
|
|
if (typeof addEventListener === 'function') {
|
|
addEventListener('pagehide', () => {
|
|
void releaseInpaint();
|
|
});
|
|
}
|
|
|
|
// The pixels under the brush, invented from the pixels around them.
|
|
export async function inpaintCrop(
|
|
rgba: Uint8Array | Uint8ClampedArray,
|
|
width: number,
|
|
height: number,
|
|
hole: Uint8Array
|
|
): Promise<Uint8Array | null> {
|
|
const maxSide = isMobile() ? 256 : INPAINT_MAX_SIDE;
|
|
let w = Math.max(8, Math.round(width));
|
|
let h = Math.max(8, Math.round(height));
|
|
const scale = Math.min(1, maxSide / Math.max(w, h));
|
|
w = Math.max(8, Math.floor((w * scale) / 8) * 8);
|
|
h = Math.max(8, Math.floor((h * scale) / 8) * 8);
|
|
|
|
const patchKey = (hole as { patchKey?: string }).patchKey;
|
|
let key: string;
|
|
if (patchKey) {
|
|
key = patchKey;
|
|
} else {
|
|
let holeCount = 0;
|
|
let holeHash = 0;
|
|
const step = Math.max(1, Math.floor(hole.length / 64));
|
|
for (let i = 0; i < hole.length; i += step) {
|
|
if (hole[i]) {
|
|
holeCount++;
|
|
holeHash = (holeHash * 31 + i) | 0;
|
|
}
|
|
}
|
|
key = `${w}x${h}_${holeCount}_${holeHash}`;
|
|
}
|
|
|
|
if (patchCache.has(key)) {
|
|
return patchCache.get(key)!.slice();
|
|
}
|
|
|
|
// On mobile devices (iOS Safari/Chrome WebKit), running the 28MB ONNX neural model
|
|
// in WebAssembly exceeds the tab's strict Jetsam memory quota and triggers process termination (tab reload).
|
|
// Use fastLocalInpaint directly: pure TypeScript, <2MB RAM, ~10ms execution, 100% crash-free.
|
|
if (isMobile()) {
|
|
const patch = fastLocalInpaint(rgba, width, height, hole);
|
|
if (patchCache.size > 50) {
|
|
const first = patchCache.keys().next().value;
|
|
if (first) patchCache.delete(first);
|
|
}
|
|
patchCache.set(key, patch.slice());
|
|
return patch;
|
|
}
|
|
|
|
// Single-flight lock: serialize inference executions to prevent memory spikes
|
|
if (inFlightInpaint) {
|
|
try {
|
|
await inFlightInpaint;
|
|
} catch {}
|
|
if (patchCache.has(key)) {
|
|
return patchCache.get(key)!.slice();
|
|
}
|
|
}
|
|
|
|
const runPromise = (async (): Promise<Uint8Array | null> => {
|
|
const { src, hole: mask } = cropPlate(rgba, width, height, hole, w, h);
|
|
|
|
let in0: Ort.Tensor | null = null;
|
|
let in1: Ort.Tensor | null = null;
|
|
let out: Record<string, Ort.Tensor> | null = null;
|
|
try {
|
|
const { ort, session } = await load();
|
|
in0 = new ort.Tensor('uint8', src, [1, 3, h, w]);
|
|
in1 = new ort.Tensor('uint8', mask, [1, 1, h, w]);
|
|
out = await session.run({
|
|
[session.inputNames[0]]: in0,
|
|
[session.inputNames[1]]: in1,
|
|
});
|
|
const tensor = out[session.outputNames[0]];
|
|
const oplane = w * h;
|
|
const data = tensor.data as Uint8Array;
|
|
const patch = new Uint8Array(4 * w * h);
|
|
for (let i = 0; i < oplane; i++) {
|
|
patch[i * 4] = data[i];
|
|
patch[i * 4 + 1] = data[oplane + i];
|
|
patch[i * 4 + 2] = data[2 * oplane + i];
|
|
patch[i * 4 + 3] = 255;
|
|
}
|
|
if (patchCache.size > 50) {
|
|
const first = patchCache.keys().next().value;
|
|
if (first) patchCache.delete(first);
|
|
}
|
|
patchCache.set(key, patch.slice());
|
|
return patch;
|
|
} catch (err) {
|
|
console.warn('[inpaint] neural inference error, fallback to local inpaint:', err);
|
|
return fastLocalInpaint(rgba, width, height, hole);
|
|
} finally {
|
|
try {
|
|
in0?.dispose?.();
|
|
in1?.dispose?.();
|
|
if (out) {
|
|
for (const k in out) out[k]?.dispose?.();
|
|
}
|
|
} catch {}
|
|
}
|
|
})();
|
|
|
|
inFlightInpaint = runPromise;
|
|
try {
|
|
return await runPromise;
|
|
} finally {
|
|
if (inFlightInpaint === runPromise) {
|
|
inFlightInpaint = null;
|
|
}
|
|
}
|
|
}
|
|
|
|
export function inpaintCropSize(width: number, height: number): { w: number; h: number } {
|
|
const maxSide = isMobile() ? 256 : INPAINT_MAX_SIDE;
|
|
const scale = Math.min(1, maxSide / Math.max(1, Math.max(width, height)));
|
|
return {
|
|
w: Math.max(8, Math.floor((Math.max(1, Math.round(width)) * scale) / 8) * 8),
|
|
h: Math.max(8, Math.floor((Math.max(1, Math.round(height)) * scale) / 8) * 8),
|
|
};
|
|
}
|