148 lines
4.1 KiB
JavaScript
148 lines
4.1 KiB
JavaScript
// @flow
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import { getLocalParticipant } from '../base/participants';
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import { extractFqnFromPath } from '../dynamic-branding';
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import logger from './logger';
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/**
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* Sends the facial expression with its duration to all the other participants.
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*
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* @param {Object} conference - The current conference.
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* @param {string} facialExpression - Facial expression to be sent.
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* @param {number} duration - The duration of the facial expression in seconds.
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* @returns {void}
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*/
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export function sendFacialExpressionToParticipants(
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conference: Object,
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facialExpression: string,
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duration: number
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): void {
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try {
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conference.sendEndpointMessage('', {
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type: 'facial_expression',
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facialExpression,
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duration
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});
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} catch (err) {
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logger.warn('Could not broadcast the facial expression to the other participants', err);
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}
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}
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/**
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* Sends the facial expression with its duration to xmpp server.
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*
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* @param {Object} conference - The current conference.
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* @param {string} facialExpression - Facial expression to be sent.
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* @param {number} duration - The duration of the facial expression in seconds.
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* @returns {void}
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*/
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export function sendFacialExpressionToServer(
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conference: Object,
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facialExpression: string,
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duration: number
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): void {
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try {
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conference.sendFacialExpression({
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facialExpression,
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duration
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});
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} catch (err) {
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logger.warn('Could not send the facial expression to xmpp server', err);
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}
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}
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/**
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* Sends facial expression to backend.
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*
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* @param {Object} state - Redux state.
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* @returns {boolean} - True if sent, false otherwise.
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*/
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export async function sendFacialExpressionsWebhook(state: Object) {
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const { webhookProxyUrl: url } = state['features/base/config'];
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const { conference } = state['features/base/conference'];
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const { jwt } = state['features/base/jwt'];
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const { connection } = state['features/base/connection'];
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const jid = connection.getJid();
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const localParticipant = getLocalParticipant(state);
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const { facialExpressionsBuffer } = state['features/facial-recognition'];
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if (facialExpressionsBuffer.length === 0) {
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return false;
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}
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const headers = {
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...jwt ? { 'Authorization': `Bearer ${jwt}` } : {},
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'Content-Type': 'application/json'
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};
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const reqBody = {
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meetingFqn: extractFqnFromPath(),
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sessionId: conference.sessionId,
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submitted: Date.now(),
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emotions: facialExpressionsBuffer,
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participantId: localParticipant.jwtId,
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participantName: localParticipant.name,
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participantJid: jid
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};
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if (url) {
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try {
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const res = await fetch(`${url}/emotions`, {
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method: 'POST',
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headers,
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body: JSON.stringify(reqBody)
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});
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if (res.ok) {
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return true;
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}
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logger.error('Status error:', res.status);
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} catch (err) {
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logger.error('Could not send request', err);
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}
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}
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return false;
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}
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/**
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* Sends the image data a canvas from the track in the image capture to the facial expression worker.
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*
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* @param {Worker} worker - Facial expression worker.
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* @param {Object} imageCapture - Image capture that contains the current track.
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* @returns {Promise<void>}
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*/
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export async function sendDataToWorker(
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worker: Worker,
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imageCapture: Object
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): Promise<void> {
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if (imageCapture === null || imageCapture === undefined) {
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return;
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}
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let imageBitmap;
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try {
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imageBitmap = await imageCapture.grabFrame();
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} catch (err) {
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logger.warn(err);
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return;
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}
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const canvas = document.createElement('canvas');
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const context = canvas.getContext('2d');
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canvas.width = imageBitmap.width;
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canvas.height = imageBitmap.height;
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context.drawImage(imageBitmap, 0, 0);
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const imageData = context.getImageData(0, 0, imageBitmap.width, imageBitmap.height);
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worker.postMessage({
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id: 'SET_TIMEOUT',
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imageData
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});
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}
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