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https://github.com/GoogleChromeLabs/squoosh.git
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Separate CLI and API
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217
api/src/index.js
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217
api/src/index.js
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import { isMainThread } from 'worker_threads';
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import { cpus } from 'os';
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import { promises as fsp } from 'fs';
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import { codecs as encoders, preprocessors as manipulations } from './codecs.js';
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import WorkerPool from './worker_pool.js';
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import { autoOptimize } from './auto-optimizer.js';
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export { ImagePool, encoders, manipulations };
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async function decodeFile({ file }) {
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const buffer = await fsp.readFile(file);
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const firstChunk = buffer.slice(0, 16);
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const firstChunkString = Array.from(firstChunk)
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.map((v) => String.fromCodePoint(v))
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.join('');
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const key = Object.entries(encoders).find(([name, { detectors }]) =>
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detectors.some((detector) => detector.exec(firstChunkString)),
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)?.[0];
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if (!key) {
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throw Error(`${file} has an unsupported format`);
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}
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const rgba = (await encoders[key].dec()).decode(
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new Uint8Array(buffer),
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);
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return {
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bitmap: rgba,
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size: buffer.length,
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};
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}
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async function manipulateImage({ manipulationType, options, image }) {
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const manipulator = await manipulations[manipulationType].instantiate();
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image.bitmap = await manipulator(
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image.bitmap.data,
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image.bitmap.width,
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image.bitmap.height,
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options,
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);
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return image;
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}
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async function encodeImage({
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bitmap: bitmapIn,
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encName,
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encConfig,
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optimizerButteraugliTarget,
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maxOptimizerRounds,
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}) {
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let binary;
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let optionsUsed = encConfig;
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const encoder = await encoders[encName].enc();
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if (encConfig === 'auto') {
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const optionToOptimize = encoders[encName].autoOptimize.option;
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const decoder = await encoders[encName].dec();
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const encode = (bitmapIn, quality) =>
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encoder.encode(
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bitmapIn.data,
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bitmapIn.width,
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bitmapIn.height,
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Object.assign({}, encoders[encName].defaultEncoderOptions, {
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[optionToOptimize]: quality,
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}),
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);
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const decode = (binary) => decoder.decode(binary);
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const { binary: optimizedBinary, quality } = await autoOptimize(
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bitmapIn,
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encode,
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decode,
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{
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min: encoders[encName].autoOptimize.min,
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max: encoders[encName].autoOptimize.max,
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butteraugliDistanceGoal: optimizerButteraugliTarget,
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maxRounds: maxOptimizerRounds,
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},
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);
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binary = optimizedBinary;
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optionsUsed = {
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// 5 significant digits is enough
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[optionToOptimize]: Math.round(quality * 10000) / 10000,
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};
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} else {
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binary = encoder.encode(
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bitmapIn.data.buffer,
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bitmapIn.width,
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bitmapIn.height,
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encConfig,
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);
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}
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return {
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optionsUsed,
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binary,
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size: binary.length,
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};
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}
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// both decoding and encoding go through the worker pool
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function handleJob(params) {
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const { operation } = params;
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switch (operation) {
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case 'encode':
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return encodeImage(params);
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case 'decode':
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return decodeFile(params);
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case 'manipulate':
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return manipulateImage(params);
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default:
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throw Error(`Invalid job "${operation}"`);
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}
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}
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/**
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* Represents an ingested image.
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*/
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class Image {
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constructor (workerPool, file) {
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this.workerPool = workerPool;
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this.decoded = workerPool.dispatchJob({operation: 'decode', file});
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this.encodedAs = {};
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}
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/**
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* Define one or several manipulations to apply to the image.
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* @param {object} manipulateOptions - An object with manipulations to apply, and their settings.
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* @returns {Promise<undefined>} - A promise that resolves when all manipulations have completed.
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*/
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async manipulate (manipulateOptions = {}) {
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for (const [type, options] of Object.entries(manipulateOptions)) {
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if (!Object.keys(manipulations).includes(type)) {
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throw Error(`Invalid manipulation type "${type}"`);
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}
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const manipulatorOptions = Object.assign(
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{},
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manipulations[type].defaultOptions,
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options,
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);
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this.decoded = this.workerPool.dispatchJob({
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operation: 'manipulate',
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manipulationType: type,
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image: await this.decoded,
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options: manipulatorOptions,
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});
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await this.decoded;
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}
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}
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/**
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* Define one or several encoders to use on the image.
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* @param {object} encodeOptions - An object with encoders to use, and their settings.
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* @returns {Promise<undefined>} - A promise that resolves when the image has been encoded with all the specified encoders.
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*/
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async encode (encodeOptions = {}){
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const { bitmap } = await this.decoded;
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for (const [encName, options] of Object.entries(encodeOptions)) {
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if (!Object.keys(encoders).includes(encName)) {
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continue;
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}
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const encRef = encoders[encName];
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const encConfig =
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typeof options === 'string'
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? options
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: Object.assign(
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{},
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encRef.defaultEncoderOptions,
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options,
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);
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this.encodedAs[encRef.extension] = this.workerPool.dispatchJob({
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operation: 'encode',
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bitmap,
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encName,
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encConfig,
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optimizerButteraugliTarget: Number(
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encodeOptions.optimizerButteraugliTarget,
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),
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maxOptimizerRounds: Number(
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encodeOptions.maxOptimizerRounds
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),
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});
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}
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await Promise.all(Object.values(this.encodedAs));
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}
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}
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/**
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* A pool where images can be ingested and squooshed.
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*/
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class ImagePool {
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/**
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* Create a new pool.
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* @param {number} [threads] - Number of concurrent image processes to run in the pool. Defaults to the number of CPU cores in the system.
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*/
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constructor (threads) {
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this.workerPool = new WorkerPool(threads || cpus().length, __filename);
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}
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/**
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* Ingest an image into the image pool.
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* @param {string | Buffer | URL | object} image - The image or path to the image that should be ingested and decoded.
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* @returns {Image} - A custom class reference to the decoded image.
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*/
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ingestImage (image) {
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return new Image(this.workerPool, image);
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}
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/**
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* Closes the underlying image processing pipeline. The already processed images will still be there, but no new processing can start.
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* @returns {Promise<undefined>} - A promise that resolves when the underlying pipeline has closed.
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*/
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async close () {
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await this.workerPool.join();
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}
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}
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if (!isMainThread) {
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WorkerPool.useThisThreadAsWorker(handleJob);
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}
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