mirror of https://github.com/vladmandic/human
50 lines
1.5 KiB
JavaScript
50 lines
1.5 KiB
JavaScript
import Human from '../../dist/human.custom.esm.js';
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const loop = 20;
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// eslint-disable-next-line no-console
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const log = (...msg) => console.log(...msg);
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const myConfig = {
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backend: 'humangl',
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modelBasePath: 'https://vladmandic.github.io/human/models',
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wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.9.0/dist/',
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debug: true,
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async: true,
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cacheSensitivity: 0,
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filter: { enabled: false },
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face: {
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enabled: true,
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detector: { enabled: true, rotation: false },
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mesh: { enabled: true },
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iris: { enabled: true },
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description: { enabled: true },
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emotion: { enabled: false },
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},
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hand: { enabled: true, rotation: false },
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body: { enabled: true },
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object: { enabled: false },
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};
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async function main() {
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const human = new Human(myConfig);
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await human.tf.ready();
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log('Human:', human.version);
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await human.load();
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const loaded = Object.keys(human.models).filter((a) => human.models[a]);
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log('Loaded:', loaded);
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log('Memory state:', human.tf.engine().memory());
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const element = document.getElementById('image');
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const processed = await human.image(element);
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const t0 = human.now();
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await human.detect(processed.tensor, myConfig);
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const t1 = human.now();
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log('Backend:', human.tf.getBackend());
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log('Warmup:', Math.round(t1 - t0));
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for (let i = 0; i < loop; i++) await human.detect(processed.tensor, myConfig);
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const t2 = human.now();
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log('Average:', Math.round((t2 - t1) / loop));
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}
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main();
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