jiti-meet/react/features/stream-effects/virtual-background/index.js

65 lines
1.9 KiB
JavaScript

// @flow
import * as wasmCheck from 'wasm-check';
import JitsiStreamBackgroundEffect from './JitsiStreamBackgroundEffect';
import createTFLiteModule from './vendor/tflite/tflite';
import createTFLiteSIMDModule from './vendor/tflite/tflite-simd';
const models = {
model96: 'libs/segm_lite_v681.tflite',
model144: 'libs/segm_full_v679.tflite'
};
const segmentationDimensions = {
model96: {
height: 96,
width: 160
},
model144: {
height: 144,
width: 256
}
};
/**
* Creates a new instance of JitsiStreamBackgroundEffect. This loads the Meet background model that is used to
* extract person segmentation.
*
* @param {Object} virtualBackground - The virtual object that contains the background image source and
* the isVirtualBackground flag that indicates if virtual image is activated.
* @returns {Promise<JitsiStreamBackgroundEffect>}
*/
export async function createVirtualBackgroundEffect(virtualBackground: Object) {
if (!MediaStreamTrack.prototype.getSettings && !MediaStreamTrack.prototype.getConstraints) {
throw new Error('JitsiStreamBackgroundEffect not supported!');
}
let tflite;
if (wasmCheck.feature.simd) {
tflite = await createTFLiteSIMDModule();
} else {
tflite = await createTFLiteModule();
}
const modelBufferOffset = tflite._getModelBufferMemoryOffset();
const modelResponse = await fetch(wasmCheck.feature.simd ? models.model144 : models.model96);
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 ? segmentationDimensions.model144 : segmentationDimensions.model96,
virtualBackground
};
return new JitsiStreamBackgroundEffect(tflite, options);
}