mirror of https://github.com/vladmandic/human
add face return tensor
Vladimir Mandic
parent
435030056a
commit
9aa53df307
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@ -9,7 +9,14 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
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## Changelog
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### **HEAD -> main** 2021/03/10 mandic00@live.com
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### **HEAD -> main** 2021/03/11 mandic00@live.com
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- wip on embedding
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- simplify face box coordinate calculations
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- annotated models and removed gender-ssrnet
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- autodetect inputsizes
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### **origin/main** 2021/03/10 mandic00@live.com
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### **1.0.3** 2021/03/10 mandic00@live.com
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1
TODO.md
1
TODO.md
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@ -4,7 +4,6 @@
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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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- Explore EfficientPose
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<https://github.com/daniegr/EfficientPose>
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@ -67,7 +67,7 @@ export default {
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// (note: module is not loaded until it is required)
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detector: {
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modelPath: '../models/blazeface-back.json',
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rotation: true, // use best-guess rotated face image or just box with rotation as-is
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rotation: false, // use best-guess rotated face image or just box with rotation as-is
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// false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees
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// this parameter is not valid in nodejs
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maxFaces: 10, // maximum number of faces detected in the input
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@ -85,7 +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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return: false, // return extracted face as tensor
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},
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mesh: {
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@ -121,7 +121,8 @@ export default {
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},
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embedding: {
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enabled: false,
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enabled: false, // to improve accuracy of face embedding extraction it is recommended
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// to enable detector.rotation and mesh.enabled
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modelPath: '../models/mobilefacenet.json',
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},
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},
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@ -3,18 +3,20 @@ import Human from '../src/human';
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import Menu from './menu.js';
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import GLBench from './gl-bench.js';
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// const userConfig = { backend: 'webgl' }; // add any user configuration overrides
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const userConfig = { backend: 'webgl' }; // add any user configuration overrides
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/*
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const userConfig = {
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backend: 'wasm',
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async: false,
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warmup: 'face',
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videoOptimized: false,
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face: { enabled: true, mesh: { enabled: true }, iris: { enabled: false }, age: { enabled: false }, gender: { enabled: false }, emotion: { enabled: false }, embedding: { enabled: true } },
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face: { enabled: true, mesh: { enabled: true }, iris: { enabled: false }, age: { enabled: false }, gender: { enabled: false }, emotion: { enabled: false }, embedding: { enabled: false } },
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hand: { enabled: false },
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gesture: { enabled: false },
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body: { enabled: false, modelPath: '../models/blazepose.json' },
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};
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*/
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const human = new Human(userConfig);
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@ -20,12 +20,14 @@
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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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.face { width: 150px; height: 150px; }
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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>Selected Face<br>
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<canvas id="orig" style="width: 200px; height: 200px;"></canvas>
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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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@ -9,7 +9,7 @@ const userConfig = {
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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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detector: { rotation: true, return: 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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@ -22,9 +22,10 @@ const userConfig = {
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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 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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// 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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@ -36,6 +37,12 @@ function log(...msg) {
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async function analyze(face) {
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log('Face:', face);
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const box = [[0.05, 0.15, 0.90, 0.85]]; // top, left, bottom, right
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const crop = human.tf.image.cropAndResize(face.tensor.expandDims(0), box, [0], [200, 200]); // optionally do a tight box crop
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const c = document.getElementById('orig');
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human.tf.browser.toPixels(crop.squeeze(), c);
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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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@ -64,7 +71,7 @@ async function faces(index, res) {
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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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log('Select:', 'Image:', evt.target.tag.sample, 'Face:', 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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@ -73,7 +80,7 @@ async function faces(index, res) {
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}
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async function add(index) {
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log('Add:', samples[index]);
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log('Add image:', 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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@ -89,6 +96,7 @@ async function add(index) {
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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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log('Ready');
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}
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window.onload = main;
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2
wiki
2
wiki
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@ -1 +1 @@
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Subproject commit fa7ac1f695547aa0fd25845e6cac7ed5ee0adcae
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Subproject commit a6a1fb7149d8a25da4874ce469f66977d517420d
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