bigbluebutton-Github/bigbluebutton-html5/imports/ui/services/virtual-background/index.js
2021-12-09 15:51:20 +03:00

358 lines
12 KiB
JavaScript

/* NOTICE: This file is a Derivative Work of the original component in Jitsi Meet
* See https://github.com/jitsi/jitsi-meet/tree/master/react/features/stream-effects/virtual-background/vendor.
* It is partially copied under the Apache Public License 2.0 (see https://www.apache.org/licenses/LICENSE-2.0).
*/
import * as wasmcheck from 'wasm-check';
import {
CLEAR_TIMEOUT,
TIMEOUT_TICK,
SET_TIMEOUT,
timerWorkerScript
} from './TimeWorker';
import {
BASE_PATH,
MODELS,
getVirtualBgImagePath,
} from '/imports/ui/services/virtual-background/service'
const blurValue = '25px';
function drawImageProp(ctx, img, x, y, w, h, offsetX, offsetY) {
if (arguments.length === 2) {
x = y = 0;
w = ctx.canvas.width;
h = ctx.canvas.height;
}
// Default offset is center
offsetX = typeof offsetX === 'number' ? offsetX : 0.5;
offsetY = typeof offsetY === 'number' ? offsetY : 0.5;
// Keep bounds [0.0, 1.0]
if (offsetX < 0) offsetX = 0;
if (offsetY < 0) offsetY = 0;
if (offsetX > 1) offsetX = 1;
if (offsetY > 1) offsetY = 1;
const iw = img.width,
ih = img.height,
r = Math.min(w / iw, h / ih);
let nw = iw * r,
nh = ih * r,
cx, cy, cw, ch, ar = 1;
// Decide which gap to fill
if (nw < w) ar = w / nw;
if (Math.abs(ar - 1) < 1e-14 && nh < h) ar = h / nh;
nw *= ar;
nh *= ar;
// Calc source rectangle
cw = iw / (nw / w);
ch = ih / (nh / h);
cx = (iw - cw) * offsetX;
cy = (ih - ch) * offsetY;
// Make sure source rectangle is valid
if (cx < 0) cx = 0;
if (cy < 0) cy = 0;
if (cw > iw) cw = iw;
if (ch > ih) ch = ih;
ctx.drawImage(img, cx, cy, cw, ch, x, y, w, h);
}
class VirtualBackgroundService {
_model;
_options;
_segmentationMask;
_inputVideoElement;
_outputCanvasElement;
_segmentationMask;
_segmentationPixelCount;
_segmentationMaskCanvas;
_segmentationMaskCtx;
_virtualImage;
_maskFrameTimerWorker;
constructor(model, options) {
this._model = model;
this._options = options;
if (this._options.virtualBackground.backgroundType === 'image') {
this._virtualImage = document.createElement('img');
this._virtualImage.crossOrigin = 'anonymous';
this._virtualImage.src = this._options.virtualBackground.virtualSource;
}
this._segmentationPixelCount = this._options.width * this._options.height;
// Bind event handler so it is only bound once for every instance.
this._onMaskFrameTimer = this._onMaskFrameTimer.bind(this);
this._outputCanvasElement = document.createElement('canvas');
this._outputCanvasElement.getContext('2d');
this._inputVideoElement = document.createElement('video');
}
/**
* EventHandler onmessage for the maskFrameTimerWorker WebWorker.
* @param {EventHandler} response - The onmessage EventHandler parameter.
* @returns {void}
*/
_onMaskFrameTimer(response) {
if (response.data.id === TIMEOUT_TICK) {
this._renderMask();
}
}
/**
* Represents the run post processing.
*
* @returns {void}
*/
runPostProcessing() {
this._outputCanvasCtx.globalCompositeOperation = 'copy';
// Draw segmentation mask.
//
// Smooth out the edges.
if (this._options.virtualBackground.isVirtualBackground) {
this._outputCanvasCtx.filter = 'blur(4px)';
} else {
this._outputCanvasCtx.filter = 'blur(8px)';
}
this._outputCanvasCtx.drawImage(
this._segmentationMaskCanvas,
0,
0,
this._options.width,
this._options.height,
0,
0,
this._inputVideoElement.width,
this._inputVideoElement.height
);
this._outputCanvasCtx.globalCompositeOperation = 'source-in';
this._outputCanvasCtx.filter = 'none';
// Draw the foreground video.
//
this._outputCanvasCtx.drawImage(this._inputVideoElement, 0, 0);
// Draw the background.
//
this._outputCanvasCtx.globalCompositeOperation = 'destination-over';
if (this._options.virtualBackground.isVirtualBackground) {
drawImageProp(
this._outputCanvasCtx,
this._virtualImage,
0,
0,
this._inputVideoElement.width,
this._inputVideoElement.height,
0.5,
0.5,
);
} else {
this._outputCanvasCtx.filter = `blur(${blurValue})`;
this._outputCanvasCtx.drawImage(this._inputVideoElement, 0, 0);
}
}
/**
* Represents the run Tensorflow Interference.
*
* @returns {void}
*/
runInference() {
this._model._runInference();
const outputMemoryOffset = this._model._getOutputMemoryOffset() / 4;
for (let i = 0; i < this._segmentationPixelCount; i++) {
const background = this._model.HEAPF32[outputMemoryOffset + (i * 2)];
const person = this._model.HEAPF32[outputMemoryOffset + (i * 2) + 1];
const shift = Math.max(background, person);
const backgroundExp = Math.exp(background - shift);
const personExp = Math.exp(person - shift);
// Sets only the alpha component of each pixel.
this._segmentationMask.data[(i * 4) + 3] = (255 * personExp) / (backgroundExp + personExp);
}
this._segmentationMaskCtx.putImageData(this._segmentationMask, 0, 0);
}
/**
* Loop function to render the background mask.
*
* @private
* @returns {void}
*/
_renderMask() {
this.resizeSource();
this.runInference();
this.runPostProcessing();
this._maskFrameTimerWorker.postMessage({
id: SET_TIMEOUT,
timeMs: 1000 / 30
});
}
/**
* Represents the resize source process.
*
* @returns {void}
*/
resizeSource() {
this._segmentationMaskCtx.drawImage(
this._inputVideoElement,
0,
0,
this._inputVideoElement.width,
this._inputVideoElement.height,
0,
0,
this._options.width,
this._options.height
);
const imageData = this._segmentationMaskCtx.getImageData(
0,
0,
this._options.width,
this._options.height
);
const inputMemoryOffset = this._model._getInputMemoryOffset() / 4;
for (let i = 0; i < this._segmentationPixelCount; i++) {
this._model.HEAPF32[inputMemoryOffset + (i * 3)] = imageData.data[i * 4] / 255;
this._model.HEAPF32[inputMemoryOffset + (i * 3) + 1] = imageData.data[(i * 4) + 1] / 255;
this._model.HEAPF32[inputMemoryOffset + (i * 3) + 2] = imageData.data[(i * 4) + 2] / 255;
}
}
changeBackgroundImage(parameters = null) {
const virtualBackgroundImagePath = getVirtualBgImagePath();
let imagesrc = virtualBackgroundImagePath + '';
let type = 'blur';
if (parameters != null && Object.keys(parameters).length > 0) {
imagesrc = parameters.name;
type = parameters.type;
this._options.virtualBackground.isVirtualBackground = parameters.isVirtualBackground;
}
this._virtualImage = document.createElement('img');
this._virtualImage.crossOrigin = 'anonymous';
this._virtualImage.src = virtualBackgroundImagePath + imagesrc;
}
/**
* Starts loop to capture video frame and render the segmentation mask.
*
* @param {MediaStream} stream - Stream to be used for processing.
* @returns {MediaStream} - The stream with the applied effect.
*/
startEffect(stream) {
this._maskFrameTimerWorker = new Worker(timerWorkerScript, { name: 'Blur effect worker' });
this._maskFrameTimerWorker.onmessage = this._onMaskFrameTimer;
const firstVideoTrack = stream.getVideoTracks()[0];
const { height, frameRate, width }
= firstVideoTrack.getSettings ? firstVideoTrack.getSettings() : firstVideoTrack.getConstraints();
this._segmentationMask = new ImageData(this._options.width, this._options.height);
this._segmentationMaskCanvas = document.createElement('canvas');
this._segmentationMaskCanvas.width = this._options.width;
this._segmentationMaskCanvas.height = this._options.height;
this._segmentationMaskCtx = this._segmentationMaskCanvas.getContext('2d');
this._outputCanvasElement.width = parseInt(width, 10);
this._outputCanvasElement.height = parseInt(height, 10);
this._outputCanvasCtx = this._outputCanvasElement.getContext('2d');
this._inputVideoElement.width = parseInt(width, 10);
this._inputVideoElement.height = parseInt(height, 10);
this._inputVideoElement.autoplay = true;
this._inputVideoElement.srcObject = stream;
this._inputVideoElement.onloadeddata = () => {
this._maskFrameTimerWorker.postMessage({
id: SET_TIMEOUT,
timeMs: 1000 / 30
});
};
return this._outputCanvasElement.captureStream(parseInt(frameRate, 15));
}
/**
* Stops the capture and render loop.
*
* @returns {void}
*/
stopEffect() {
this._maskFrameTimerWorker.postMessage({
id: CLEAR_TIMEOUT
});
this._maskFrameTimerWorker.terminate();
}
}
/**
* Creates VirtualBackgroundService. If parameters are empty, the default
* effect is blur. Parameters (if given) must contain the following:
* isVirtualBackground (boolean) - false for blur, true for image
* backgroundType (string) - 'image' for image, anything else for blur
* backgroundFilename (string) - File name that is stored in /public/resources/images/virtual-backgrounds/
* @param {Object} parameters
* @returns {VirtualBackgroundService}
*/
export async function createVirtualBackgroundService(parameters = null) {
let tflite;
let modelResponse;
if (wasmcheck.feature.simd) {
tflite = await window.createTFLiteSIMDModule();
modelResponse = await fetch(BASE_PATH+MODELS.model144.path);
} else {
tflite = await window.createTFLiteModule();
modelResponse = await fetch(BASE_PATH+MODELS.model96.path);
}
const modelBufferOffset = tflite._getModelBufferMemoryOffset();
const virtualBackgroundImagePath = getVirtualBgImagePath();
if (parameters == null) {
parameters = {};
parameters.virtualSource = virtualBackgroundImagePath + '';
parameters.backgroundType = 'blur';
parameters.isVirtualBackground = false;
} else {
parameters.virtualSource = virtualBackgroundImagePath + parameters.backgroundFilename;
}
if (!modelResponse.ok) {
throw new Error('Failed to download tflite model!');
}
const model = await modelResponse.arrayBuffer();
tflite.HEAPU8.set(new Uint8Array(model), modelBufferOffset);
tflite._loadModel(model.byteLength);
const options = {
...wasmcheck.feature.simd ? MODELS.model144.segmentationDimensions : MODELS.model96.segmentationDimensions,
virtualBackground: parameters
};
return new VirtualBackgroundService(tflite, options);
}
export default VirtualBackgroundService;