Reputation: 1055
Context
I've been working on building a virtual-backgrounds feature for web environments, and as part of that I'm taking in a webcam feed (MediaStreamTrack), doing some image-processing in WebGL and outputting the processed video frames to a canvas.
Problem
As soon as you call captureStream() on the canvas (or, any canvas it seems), the CPU usage starts to spike (on my Linux device, from 20% to 60%).
I've re-created a simplified version of this problem here, with a simple animation and a call to canvas.captureStream():
const canvas = document.querySelector('#canvas-target');
const animation = new CanvasAnimation(canvas.getContext('2d'));
animation.start();
// Starts an animation on canvas
function captureStream(){
let stream = canvas.captureStream();
const video = document.querySelector('#stream-output');
// Create canvas stream, feed it to video
video.srcObject = stream;
// CPU starts to go up here
video.play();
}
See Codepen for the full example: https://codepen.io/sb2702/pen/MWogaeo
The main factors that seem to affect CPU usage are frame-rate and resolution - so,
I assume that the browser is just doing a lot of work under the hood to re-encode the video stream into a media stream.
The "quick" answer is to just restrict the framerate and/or resolution
My primary question is - am I missing something else fundamental about canvas, captureStream - etc.., and is there some much more CPU efficient way of generating a MediaStreamTrack with output from a Canvas?
Upvotes: 2
Views: 370