* feat: Adds an example to convert a deployment to use jaas.

* squash: Generates the daily asap token with expiration of 1 day.

The default is 1 hour.

* squash: Use local deployment UI with jaas, not 8x8.vc one.

- We load config.js from 8x8.vc with the tenant, to allow release pinning to work.

- We sed the vpass_cookie in the custom nginx conf as variables are not allowed in location matching.

- The jaas-vars need to be global as it will overwrite config.js location and index html.

* squash: Enables e2ee for the meetings.

* squash: Bump node version check.

* squash: Fix filename.

* squash: Updates the readme.

* squash: Checks whether node is installed.

* squash: Fixes initial configuration.

The jaas-vars is required to reload nginx, done by update-asap-daily script.

* squash: More fixes of misspelled config file.

* squash: Fixes serving the pub key.

It now lives here https://github.com/jitsi/jitsi-meet-load-test

* language(typescript) first ts component, added ts configurations, actionTypes.js are now ts files

* ref(face-landmarks) refactor namings

* code review

* Initial implementation; Happy flow

* Maybe revert this

* Functional prototype

* feat(facial-expressions): get stream when changing background effect and use presenter effect with camera

* add(facial-expressions): array that stores the expressions durin the meeting

* refactor(facial-expressions): capture imagebitmap from stream with imagecapture api

* add(speaker-stats): expression label

* fix(facial-expression): expression store

* revert: expression leabel on speaker stats

* add(facial-expressions): broadcast of expression when it changes

* feat: facial expression handling on prosody

* fix(facial-expressions): get the right track when opening and closing camera

* add(speaker-stats): facial expression column

* fix(facial-expressions): allow to start facial recognition only after joining conference

* fix(mod_speakerstats_component): storing last emotion in speaker stats component and sending it

* chore(facial-expressions): change detection from 2000ms to 1000ms

* add(facial-expressions): send expression to server when there is only one participant

* feat(facial-expressions): store expresions as a timeline

* feat(mod_speakerstats_component): store facial expresions as a timeline

* fix(facial-expressions): stop facial recognition only when muting video track

* fix(facial-expressions): presenter mode get right track to detect face

* add: polyfils for image capture for firefox and safari

* refactor(facial-expressions): store expressions by counting them in a map

* chore(facial-expressions): remove manually assigning the backend for tenserflowjs

* feat(facial-expressions): move face-api from main thread to web worker

* fix(facial-expressions): make feature work on firefox and safari

* feat(facial-expressions): camera time tracker

* feat(facial-expressions): camera time tracker in prosody

* add(facial-expressions): expressions time as TimeElapsed object in speaker stats

* fix(facial-expresions): lower the frequency of detection when tf uses cpu backend

* add(facial-expressions): duration to the expression and send it with durantion when it is done

* fix(facial-expressions): prosody speaker stats covert fro string to number and bool values set by xmpp

* refactor(facial-expressions): change expressions labels from text to emoji

* refactor(facial-expressions): remove camera time tracker

* add(facial-expressions): detection time interval

* chore(facial-expressions): add docs and minor refactor of the code

* refactor(facial-expressions): put timeout in worker and remove set interval in main thread

* feat(facial-expressions): disable feature in the config

* add(facial-expressions): tooltips of labels in speaker stats

* refactor(facial-expressions): send facial expressions function and remove some unused functions and console logs

* refactor(facial-expressions): rename action type when a change is done to the track by the virtual backgrounds to be used in facial expressions middleware

* chore(facial-expressions): order imports and format some code

* fix(facial-expressions): rebase issues with newer master

* fix(facial-expressions): package-lock.json

* fix(facial-expression): add commented default value of disableFacialRecognition flag and short description

* fix(facial-expressions): change disableFacialRecognition to enableFacialRecognition flag in config

* fix: resources load-test package-lock.json

* fix(facial-expressions): set and get facial expressions only if facial recognition enabled

* add: facial recognition resources folder in .eslintignore

* chore: package-lock update

* fix: package-lock.json

* fix(facial-expressions): gpu memory leak in the web worker

* fix(facial-expressions): set cpu time interval for detection to 6000ms

* chore(speaker-stats): fix indentation

* chore(facial-expressions): remove empty lines between comments and type declarations

* fix(facial-expressions): remove camera timetracker

* fix(facial-expressions): remove facialRecognitionAllowed flag

* fix(facial-expressions): remove sending interval time to worker

* refactor(facial-expression): middleware

* fix(facial-expression): end tensor scope after setting backend

* fix(facial-expressions): sending info back to worker only on facial expression message

* fix: lint errors

* refactor(facial-expressions): bundle web worker using webpack

* fix: deploy-facial-expressions command in makefile

* chore: fix load test package-lock.json and package.json

* chore: sync package-lock.json

Co-authored-by: Mihai-Andrei Uscat <mihai.uscat@8x8.com>

Use the Google Meet model and SIMD optimized WASM.

Enable ESLint on jitsi-meet with the same configuration and the same
goals as in lib-jitsi-meet.