jiti-meet/react/features/facial-recognition/functions.js

139 lines
3.8 KiB
JavaScript

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