mirror of https://github.com/vladmandic/human
67 lines
2.5 KiB
JavaScript
67 lines
2.5 KiB
JavaScript
/**
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* Human simple demo for NodeJS
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*/
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const childProcess = require('child_process'); // eslint-disable-line camelcase
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const log = require('@vladmandic/pilogger'); // eslint-disable-line node/no-unpublished-require
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const canvas = require('canvas'); // eslint-disable-line node/no-unpublished-require
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const config = {
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cacheSensitivity: 0.01,
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wasmPlatformFetch: true,
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modelBasePath: 'https://vladmandic.github.io/human-models/models/',
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};
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const count = 10;
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async function loadImage(input) {
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const inputImage = await canvas.loadImage(input);
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const inputCanvas = new canvas.Canvas(inputImage.width, inputImage.height);
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const inputCtx = inputCanvas.getContext('2d');
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inputCtx.drawImage(inputImage, 0, 0);
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const imageData = inputCtx.getImageData(0, 0, inputCanvas.width, inputCanvas.height);
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process.send({ input, resolution: [inputImage.width, inputImage.height] });
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return imageData;
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}
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async function runHuman(module, backend) {
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if (backend === 'wasm') require('@tensorflow/tfjs-backend-wasm'); // eslint-disable-line node/no-unpublished-require, global-require
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const Human = require('../../dist/' + module); // eslint-disable-line global-require, import/no-dynamic-require
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config.backend = backend;
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const human = new Human.Human(config);
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human.env.Canvas = canvas.Canvas;
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human.env.Image = canvas.Image;
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human.env.ImageData = canvas.ImageData;
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process.send({ human: human.version, module });
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await human.init();
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process.send({ desired: human.config.backend, wasm: human.env.wasm, tfjs: human.tf.version.tfjs, tensorflow: human.env.tensorflow });
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const imageData = await loadImage('samples/in/ai-body.jpg');
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const t0 = human.now();
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await human.load();
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const t1 = human.now();
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await human.warmup();
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const t2 = human.now();
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for (let i = 0; i < count; i++) await human.detect(imageData);
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const t3 = human.now();
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process.send({ backend: human.tf.getBackend(), load: Math.round(t1 - t0), warmup: Math.round(t2 - t1), detect: Math.round(t3 - t2), count, memory: human.tf.memory().numBytes });
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}
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async function executeWorker(args) {
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return new Promise((resolve) => {
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const worker = childProcess.fork(process.argv[1], args);
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worker.on('message', (msg) => log.data(msg));
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worker.on('exit', () => resolve(true));
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});
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}
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async function main() {
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if (process.argv[2]) {
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await runHuman(process.argv[2], process.argv[3]);
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} else {
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await executeWorker(['human.node.js', 'tensorflow']);
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await executeWorker(['human.node-gpu.js', 'tensorflow']);
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await executeWorker(['human.node-wasm.js', 'wasm']);
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}
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}
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main();
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