mirror of https://github.com/vladmandic/human
add test for face descriptors
Vladimir Mandic
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622de45e50
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@ -1,2 +1,2 @@
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node_modules
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alternative
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private
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1
TODO.md
1
TODO.md
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@ -2,6 +2,7 @@
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- Strong typing
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- Automated testing
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- Guard against corrupt input
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- Improve face embedding
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- Build Face embedding database
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- Dynamic sample processing
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@ -85,6 +85,7 @@ export default {
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scoreThreshold: 0.2, // threshold for deciding when to remove boxes based on score
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// in non-maximum suppression,
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// this is applied on detection objects only and before minConfidence
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return: true, // return extracted face as tensor
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},
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mesh: {
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@ -0,0 +1,32 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<title>Human</title>
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<meta charset="utf-8">
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<meta http-equiv="content-type">
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<meta content="text/html">
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<meta name="description" content="Human: 3D Face Detection, Body Pose, Hand & Finger Tracking, Iris Tracking, Age & Gender Prediction, Emotion Prediction & Gesture Recognition; Author: Vladimir Mandic <https://github.com/vladmandic>">
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<meta name="viewport" content="width=device-width, initial-scale=0.6, minimum-scale=0.3, maximum-scale=3.0, shrink-to-fit=yes, user-scalable=yes">
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<meta name="theme-color" content="#000000"/>
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<meta name="application-name" content="Human">
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<meta name="msapplication-tooltip" content="Human: AI-powered 3D Human Detection">
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<link rel="manifest" href="./manifest.webmanifest">
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<link rel="shortcut icon" href="../favicon.ico" type="image/x-icon">
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<link rel="apple-touch-icon" href="../assets/icon.png">
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<script src="./embedding.js" type="module"></script>
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<style>
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@font-face { font-family: 'Lato'; font-display: swap; font-style: normal; font-weight: 100; src: local('Lato'), url('../assets/lato-light.woff2') }
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html { font-family: 'Lato', 'Segoe UI'; font-size: 20px; font-variant: small-caps; }
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body { margin: 0; background: black; color: white; overflow-x: hidden; scrollbar-width: none; }
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body::-webkit-scrollbar { display: none; }
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img { object-fit: contain; }
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.face { width: 200px; height: 200px; }
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</style>
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</head>
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<body>
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<br>Sample Images:
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<div id="images"></div>
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<br>Extracted Faces - click on a face to sort by simmilarity:<br>
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<div id="faces"></div>
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</body>
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</html>
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@ -0,0 +1,94 @@
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import Human from '../dist/human.esm.js';
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const userConfig = {
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backend: 'wasm',
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async: false,
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warmup: 'none',
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debug: true,
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filter: false,
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videoOptimized: false,
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face: {
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enabled: true,
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detector: { rotation: true },
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mesh: { enabled: true },
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embedding: { enabled: true, modelPath: '../models/mobilefacenet.json' },
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iris: { enabled: false },
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age: { enabled: false },
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gender: { enabled: false },
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emotion: { enabled: false },
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},
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hand: { enabled: false },
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gesture: { enabled: false },
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body: { enabled: false },
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};
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const human = new Human(userConfig);
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const samples = ['../assets/sample-me.jpg', '../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg',
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'../private/me (1).jpg', '../private/me (2).jpg', '../private/me (3).jpg', '../private/me (4).jpg', '../private/me (5).jpg', '../private/me (6).jpg', '../private/me (7).jpg', '../private/me (8).jpg',
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'../private/me (9).jpg', '../private/me (10).jpg', '../private/me (11).jpg', '../private/me (12).jpg', '../private/me (13).jpg'];
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const all = [];
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function log(...msg) {
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const dt = new Date();
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const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;
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// eslint-disable-next-line no-console
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console.log(ts, ...msg);
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}
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async function analyze(face) {
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log('Face:', face);
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const canvases = document.getElementsByClassName('face');
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for (const canvas of canvases) {
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const res = human.simmilarity(face.embedding, all[canvas.tag.sample][canvas.tag.face].embedding);
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canvas.title = res;
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await human.tf.browser.toPixels(all[canvas.tag.sample][canvas.tag.face].tensor, canvas);
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const ctx = canvas.getContext('2d');
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ctx.font = 'small-caps 1rem "Lato"';
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ctx.fillStyle = 'rgba(0, 0, 0, 1)';
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ctx.fillText(`${(100 * res).toFixed(1)}%`, 3, 19);
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ctx.fillStyle = 'rgba(255, 255, 255, 1)';
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ctx.fillText(`${(100 * res).toFixed(1)}%`, 4, 20);
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}
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const sorted = document.getElementById('faces');
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[...sorted.children]
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.sort((a, b) => parseFloat(b.title) - parseFloat(a.title))
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.forEach((canvas) => sorted.appendChild(canvas));
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}
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async function faces(index, res) {
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all[index] = res.face;
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for (const i in res.face) {
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// log(res.face[i]);
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const canvas = document.createElement('canvas');
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canvas.tag = { sample: index, face: i };
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canvas.width = 200;
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canvas.height = 200;
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canvas.className = 'face';
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canvas.addEventListener('click', (evt) => {
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log('Select:', evt.target.tag.sample, evt.target.tag.face);
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analyze(all[evt.target.tag.sample][evt.target.tag.face]);
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});
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human.tf.browser.toPixels(res.face[i].tensor, canvas);
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document.getElementById('faces').appendChild(canvas);
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}
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}
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async function add(index) {
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log('Add:', samples[index]);
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return new Promise((resolve) => {
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const img = new Image(100, 100);
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img.onload = () => {
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human.detect(img).then((res) => faces(index, res));
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document.getElementById('images').appendChild(img);
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resolve(true);
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};
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img.title = samples[index];
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img.src = samples[index];
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});
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}
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async function main() {
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await human.load();
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for (const i in samples) await add(i);
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}
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window.onload = main;
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@ -303,7 +303,8 @@ class Human {
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emotion: string,
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embedding: any,
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iris: number,
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angle: any
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angle: any,
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tensor: any,
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}> = [];
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this.state = 'run:face';
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@ -402,7 +403,7 @@ class Human {
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embedding: embeddingRes,
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iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,
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angle,
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// image: face.image.toInt().squeeze(),
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tensor: this.config.face.detector.return ? face.image.squeeze() : null,
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});
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// dont need face anymore
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2
wiki
2
wiki
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@ -1 +1 @@
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Subproject commit 69294f7a0a99bd996286f8f5bb655c7ea8bfc10d
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Subproject commit fa7ac1f695547aa0fd25845e6cac7ed5ee0adcae
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