122 lines
2.9 KiB
JavaScript
122 lines
2.9 KiB
JavaScript
// @flow
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import './faceApiPatch';
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import * as faceapi from '@vladmandic/face-api';
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import {
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CLEAR_TIMEOUT,
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CPU_TIME_INTERVAL,
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FACIAL_EXPRESSION_MESSAGE,
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INIT_WORKER,
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SET_TIMEOUT,
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INTERVAL_MESSAGE,
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WEBGL_TIME_INTERVAL
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} from './constants';
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/**
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* A flag that indicates whether the tensorflow models were loaded or not.
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*/
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let modelsLoaded = false;
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/**
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* The url where the models for the facial detection of expressions are located.
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*/
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let modelsURL;
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/**
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* A flag that indicates whether the tensorflow backend is set or not.
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*/
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let backendSet = false;
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/**
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* A timer variable for set interval.
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*/
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let timer;
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/**
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* The duration of the set timeout.
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*/
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let timeoutDuration = -1;
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/**
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* A patch for having window object in the worker.
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*/
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const window = {
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screen: {
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width: 1280,
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height: 720
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}
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};
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onmessage = async function(message) {
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switch (message.data.type) {
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case INIT_WORKER : {
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modelsURL = message.data.url;
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if (message.data.windowScreenSize) {
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window.screen = message.data.windowScreenSize;
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}
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break;
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}
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case SET_TIMEOUT : {
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if (!message.data.imageData || !modelsURL) {
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self.postMessage({
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type: FACIAL_EXPRESSION_MESSAGE,
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value: null
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});
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}
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// the models are loaded
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if (!modelsLoaded) {
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await faceapi.loadTinyFaceDetectorModel(modelsURL);
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await faceapi.loadFaceExpressionModel(modelsURL);
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modelsLoaded = true;
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}
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faceapi.tf.engine().startScope();
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const tensor = faceapi.tf.browser.fromPixels(message.data.imageData);
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const detections = await faceapi.detectSingleFace(
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tensor,
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new faceapi.TinyFaceDetectorOptions()
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).withFaceExpressions();
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// The backend is set
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if (!backendSet) {
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const backend = faceapi.tf.getBackend();
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if (backend) {
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if (backend === 'webgl') {
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timeoutDuration = WEBGL_TIME_INTERVAL;
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} else if (backend === 'cpu') {
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timeoutDuration = CPU_TIME_INTERVAL;
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}
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self.postMessage({
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type: INTERVAL_MESSAGE,
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value: timeoutDuration
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});
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backendSet = true;
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}
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}
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faceapi.tf.engine().endScope();
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let facialExpression;
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if (detections) {
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facialExpression = detections.expressions.asSortedArray()[0].expression;
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}
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timer = setTimeout(() => {
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self.postMessage({
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type: FACIAL_EXPRESSION_MESSAGE,
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value: facialExpression
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});
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}, timeoutDuration);
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break;
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}
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case CLEAR_TIMEOUT: {
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if (timer) {
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clearTimeout(timer);
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timer = null;
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}
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break;
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}
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}
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};
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