mirror of https://github.com/vladmandic/human
switched face embedding to mobileface
Vladimir Mandic
parent
162ace9fc3
commit
12b0058a1b
10
CHANGELOG.md
10
CHANGELOG.md
|
|
@ -1,6 +1,6 @@
|
|||
# @vladmandic/human
|
||||
|
||||
Version: **1.0.3**
|
||||
Version: **1.1.0**
|
||||
Description: **Human: AI-powered 3D Face Detection, Face Embedding & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition**
|
||||
|
||||
Author: **Vladimir Mandic <mandic00@live.com>**
|
||||
|
|
@ -11,14 +11,16 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
|
|||
|
||||
### **HEAD -> main** 2021/03/11 mandic00@live.com
|
||||
|
||||
|
||||
### **1.0.4** 2021/03/11 mandic00@live.com
|
||||
|
||||
- add face return tensor
|
||||
- add test for face descriptors
|
||||
- wip on embedding
|
||||
- simplify face box coordinate calculations
|
||||
- annotated models and removed gender-ssrnet
|
||||
- autodetect inputsizes
|
||||
|
||||
### **origin/main** 2021/03/10 mandic00@live.com
|
||||
|
||||
|
||||
### **1.0.3** 2021/03/10 mandic00@live.com
|
||||
|
||||
- strong typing for public classes and hide private classes
|
||||
|
|
|
|||
|
|
@ -69,7 +69,7 @@ Default models in Human library are:
|
|||
- **Gender Detection**: Oarriaga Gender
|
||||
- **Age Detection**: SSR-Net Age IMDB
|
||||
- **Body Analysis**: PoseNet
|
||||
- **Face Embedding**: Sirius-AI MobileFaceNet Embedding
|
||||
- **Face Embedding**: BecauseofAI MobileFace Embedding
|
||||
|
||||
Note that alternative models are provided and can be enabled via configuration
|
||||
For example, `PoseNet` model can be switched for `BlazePose` model depending on the use case
|
||||
|
|
|
|||
10
TODO.md
10
TODO.md
|
|
@ -8,3 +8,13 @@
|
|||
- Explore EfficientPose
|
||||
<https://github.com/daniegr/EfficientPose>
|
||||
<https://github.com/PINTO0309/PINTO_model_zoo/tree/main/084_EfficientPose>
|
||||
|
||||
## WiP: Embedding
|
||||
|
||||
- Implement offsetRaw
|
||||
|
||||
full with and without rotation
|
||||
full with and without embedding
|
||||
full with any without mesh
|
||||
embedding with and without mesh
|
||||
boxRaw and meshRaw with and without mesh
|
||||
|
|
|
|||
|
|
@ -121,9 +121,9 @@ export default {
|
|||
},
|
||||
|
||||
embedding: {
|
||||
enabled: false, // to improve accuracy of face embedding extraction it is recommended
|
||||
// to enable detector.rotation and mesh.enabled
|
||||
modelPath: '../models/mobilefacenet.json',
|
||||
enabled: false, // to improve accuracy of face embedding extraction it is
|
||||
// highly recommended to enable detector.rotation and mesh.enabled
|
||||
modelPath: '../models/mobileface.json',
|
||||
},
|
||||
},
|
||||
|
||||
|
|
|
|||
|
|
@ -84,10 +84,21 @@ let original;
|
|||
async function calcSimmilariry(result) {
|
||||
document.getElementById('compare-container').style.display = human.config.face.embedding.enabled ? 'block' : 'none';
|
||||
if (!human.config.face.embedding.enabled) return;
|
||||
if (!(result?.face?.length > 0) || (result?.face[0]?.embedding?.length !== 192)) return;
|
||||
if (!(result?.face?.length > 0) || (result?.face[0]?.embedding?.length !== 256)) return;
|
||||
if (!original) {
|
||||
original = result;
|
||||
document.getElementById('compare-canvas').getContext('2d').drawImage(original.canvas, 0, 0, 200, 200);
|
||||
if (result.face[0].tensor) {
|
||||
const enhanced = human.enhance(result.face[0]);
|
||||
if (enhanced) {
|
||||
const c = document.getElementById('orig');
|
||||
const squeeze = enhanced.squeeze();
|
||||
human.tf.browser.toPixels(squeeze, c);
|
||||
enhanced.dispose();
|
||||
squeeze.dispose();
|
||||
}
|
||||
} else {
|
||||
document.getElementById('compare-canvas').getContext('2d').drawImage(original.canvas, 0, 0, 200, 200);
|
||||
}
|
||||
}
|
||||
const simmilarity = human.simmilarity(original?.face[0]?.embedding, result?.face[0]?.embedding);
|
||||
document.getElementById('simmilarity').innerText = `simmilarity: ${Math.trunc(1000 * simmilarity) / 10}%`;
|
||||
|
|
|
|||
|
|
@ -26,9 +26,9 @@
|
|||
<body>
|
||||
<br>Sample Images:
|
||||
<div id="images"></div>
|
||||
<br>Selected Face<br>
|
||||
<br>Selected Face (Enhanced)<br>
|
||||
<canvas id="orig" style="width: 200px; height: 200px;"></canvas>
|
||||
<br>Extracted Faces - click on a face to sort by simmilarity:<br>
|
||||
<br><br>Extracted Faces - click on a face to sort by simmilarity:<br>
|
||||
<div id="faces"></div>
|
||||
</body>
|
||||
</html>
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@ const userConfig = {
|
|||
enabled: true,
|
||||
detector: { rotation: true, return: true },
|
||||
mesh: { enabled: true },
|
||||
embedding: { enabled: true, modelPath: '../models/mobilefacenet.json' },
|
||||
embedding: { enabled: true },
|
||||
iris: { enabled: false },
|
||||
age: { enabled: false },
|
||||
gender: { enabled: false },
|
||||
|
|
@ -21,12 +21,15 @@ const userConfig = {
|
|||
gesture: { enabled: false },
|
||||
body: { enabled: false },
|
||||
};
|
||||
const human = new Human(userConfig);
|
||||
|
||||
const human = new Human(userConfig); // new instance of human
|
||||
|
||||
const samples = ['../assets/sample-me.jpg', '../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg'];
|
||||
// const samples = ['../assets/sample-me.jpg', '../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg',
|
||||
// '../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',
|
||||
// '../private/me (9).jpg', '../private/me (10).jpg', '../private/me (11).jpg', '../private/me (12).jpg', '../private/me (13).jpg'];
|
||||
const all = [];
|
||||
// '../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',
|
||||
// '../private/me (9).jpg', '../private/me (10).jpg', '../private/me (11).jpg', '../private/me (12).jpg', '../private/me (13).jpg'];
|
||||
|
||||
const all = []; // array that will hold all detected faces
|
||||
|
||||
function log(...msg) {
|
||||
const dt = new Date();
|
||||
|
|
@ -38,14 +41,24 @@ function log(...msg) {
|
|||
async function analyze(face) {
|
||||
log('Face:', face);
|
||||
|
||||
const box = [[0.05, 0.15, 0.90, 0.85]]; // top, left, bottom, right
|
||||
const crop = human.tf.image.cropAndResize(face.tensor.expandDims(0), box, [0], [200, 200]); // optionally do a tight box crop
|
||||
const c = document.getElementById('orig');
|
||||
human.tf.browser.toPixels(crop.squeeze(), c);
|
||||
// if we have face image tensor, enhance it and display it
|
||||
if (face.tensor) {
|
||||
const enhanced = human.enhance(face);
|
||||
if (enhanced) {
|
||||
const c = document.getElementById('orig');
|
||||
const squeeze = enhanced.squeeze();
|
||||
human.tf.browser.toPixels(squeeze, c);
|
||||
enhanced.dispose();
|
||||
squeeze.dispose();
|
||||
}
|
||||
}
|
||||
|
||||
// loop through all canvases that contain faces
|
||||
const canvases = document.getElementsByClassName('face');
|
||||
for (const canvas of canvases) {
|
||||
// calculate simmilarity from selected face to current one in the loop
|
||||
const res = human.simmilarity(face.embedding, all[canvas.tag.sample][canvas.tag.face].embedding);
|
||||
// draw the canvas and simmilarity score
|
||||
canvas.title = res;
|
||||
await human.tf.browser.toPixels(all[canvas.tag.sample][canvas.tag.face].tensor, canvas);
|
||||
const ctx = canvas.getContext('2d');
|
||||
|
|
@ -55,6 +68,8 @@ async function analyze(face) {
|
|||
ctx.fillStyle = 'rgba(255, 255, 255, 1)';
|
||||
ctx.fillText(`${(100 * res).toFixed(1)}%`, 4, 20);
|
||||
}
|
||||
|
||||
// sort all faces by simmilarity
|
||||
const sorted = document.getElementById('faces');
|
||||
[...sorted.children]
|
||||
.sort((a, b) => parseFloat(b.title) - parseFloat(a.title))
|
||||
|
|
@ -70,12 +85,16 @@ async function faces(index, res) {
|
|||
canvas.width = 200;
|
||||
canvas.height = 200;
|
||||
canvas.className = 'face';
|
||||
// mouse click on any face canvas triggers analysis
|
||||
canvas.addEventListener('click', (evt) => {
|
||||
log('Select:', 'Image:', evt.target.tag.sample, 'Face:', evt.target.tag.face);
|
||||
analyze(all[evt.target.tag.sample][evt.target.tag.face]);
|
||||
});
|
||||
human.tf.browser.toPixels(res.face[i].tensor, canvas);
|
||||
document.getElementById('faces').appendChild(canvas);
|
||||
// if we actually got face image tensor, draw canvas with that face
|
||||
if (res.face[i].tensor) {
|
||||
human.tf.browser.toPixels(res.face[i].tensor, canvas);
|
||||
document.getElementById('faces').appendChild(canvas);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -83,9 +102,9 @@ async function add(index) {
|
|||
log('Add image:', samples[index]);
|
||||
return new Promise((resolve) => {
|
||||
const img = new Image(100, 100);
|
||||
img.onload = () => {
|
||||
human.detect(img).then((res) => faces(index, res));
|
||||
document.getElementById('images').appendChild(img);
|
||||
img.onload = () => { // must wait until image is loaded
|
||||
human.detect(img).then((res) => faces(index, res)); // then wait until image is analyzed
|
||||
document.getElementById('images').appendChild(img); // and finally we can add it
|
||||
resolve(true);
|
||||
};
|
||||
img.title = samples[index];
|
||||
|
|
@ -95,7 +114,7 @@ async function add(index) {
|
|||
|
||||
async function main() {
|
||||
await human.load();
|
||||
for (const i in samples) await add(i);
|
||||
for (const i in samples) await add(i); // download and analyze all images
|
||||
log('Ready');
|
||||
}
|
||||
|
||||
|
|
|
|||
11
demo/node.js
11
demo/node.js
|
|
@ -1,8 +1,10 @@
|
|||
const log = require('@vladmandic/pilogger');
|
||||
const fs = require('fs');
|
||||
const process = require('process');
|
||||
// for Node, `tfjs-node` or `tfjs-node-gpu` should be loaded before using Human
|
||||
|
||||
// for NodeJS, `tfjs-node` or `tfjs-node-gpu` should be loaded before using Human
|
||||
const tf = require('@tensorflow/tfjs-node'); // or const tf = require('@tensorflow/tfjs-node-gpu');
|
||||
|
||||
// load specific version of Human library that matches TensorFlow mode
|
||||
const Human = require('../dist/human.node.js').default; // or const Human = require('../dist/human.node-gpu.js').default;
|
||||
|
||||
|
|
@ -15,15 +17,16 @@ const myConfig = {
|
|||
async: false,
|
||||
face: {
|
||||
enabled: true,
|
||||
detector: { modelPath: 'file://models/blazeface-back.json', enabled: true },
|
||||
detector: { modelPath: 'file://models/blazeface-back.json', enabled: true, rotation: false },
|
||||
mesh: { modelPath: 'file://models/facemesh.json', enabled: true },
|
||||
iris: { modelPath: 'file://models/iris.json', enabled: true },
|
||||
age: { modelPath: 'file://models/age.json', enabled: true },
|
||||
gender: { modelPath: 'file://models/gender.json', enabled: true },
|
||||
emotion: { modelPath: 'file://models/emotion.json', enabled: true },
|
||||
embedding: { modelPath: 'file://models/mobileface.json', enabled: true },
|
||||
},
|
||||
// body: { modelPath: 'file://models/blazepose.json', modelType: 'blazepose', enabled: true },
|
||||
body: { modelPath: 'file://models/posenet.json', modelType: 'posenet', enabled: true },
|
||||
// body: { modelPath: 'file://models/blazepose.json', enabled: true },
|
||||
body: { modelPath: 'file://models/posenet.json', enabled: true },
|
||||
hand: {
|
||||
enabled: true,
|
||||
detector: { modelPath: 'file://models/handdetect.json' },
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "@vladmandic/human",
|
||||
"version": "1.0.4",
|
||||
"version": "1.1.0",
|
||||
"description": "Human: AI-powered 3D Face Detection, Face Embedding & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition",
|
||||
"sideEffects": false,
|
||||
"main": "dist/human.node.js",
|
||||
|
|
@ -54,13 +54,13 @@
|
|||
"@tensorflow/tfjs-layers": "^3.3.0",
|
||||
"@tensorflow/tfjs-node": "^3.3.0",
|
||||
"@tensorflow/tfjs-node-gpu": "^3.3.0",
|
||||
"@types/node": "^14.14.33",
|
||||
"@types/node": "^14.14.34",
|
||||
"@typescript-eslint/eslint-plugin": "^4.17.0",
|
||||
"@typescript-eslint/parser": "^4.17.0",
|
||||
"@vladmandic/pilogger": "^0.2.14",
|
||||
"chokidar": "^3.5.1",
|
||||
"dayjs": "^1.10.4",
|
||||
"esbuild": "^0.9.0",
|
||||
"esbuild": "=0.9.0",
|
||||
"eslint": "^7.21.0",
|
||||
"eslint-config-airbnb-base": "^14.2.1",
|
||||
"eslint-plugin-import": "^2.22.1",
|
||||
|
|
|
|||
13
src/human.ts
13
src/human.ts
|
|
@ -151,6 +151,11 @@ class Human {
|
|||
return 0;
|
||||
}
|
||||
|
||||
enhance(input: any): any {
|
||||
if (this.config.face.embedding.enabled) return embedding.enhance(input);
|
||||
return null;
|
||||
}
|
||||
|
||||
// preload models, not explicitly required as it's done automatically on first use
|
||||
async load(userConfig = null) {
|
||||
this.state = 'load';
|
||||
|
|
@ -359,11 +364,11 @@ class Human {
|
|||
// run emotion, inherits face from blazeface
|
||||
this.#analyze('Start Embedding:');
|
||||
if (this.config.async) {
|
||||
embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face.image, this.config) : [];
|
||||
embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];
|
||||
} else {
|
||||
this.state = 'run:embedding';
|
||||
timeStamp = now();
|
||||
embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face.image, this.config) : [];
|
||||
embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];
|
||||
this.#perf.embedding = Math.trunc(now() - timeStamp);
|
||||
}
|
||||
this.#analyze('End Emotion:');
|
||||
|
|
@ -388,6 +393,8 @@ class Human {
|
|||
|
||||
// combine results
|
||||
faceRes.push({
|
||||
...face,
|
||||
/*
|
||||
confidence: face.confidence,
|
||||
faceConfidence: face.faceConfidence,
|
||||
boxConfidence: face.boxConfidence,
|
||||
|
|
@ -395,7 +402,9 @@ class Human {
|
|||
mesh: face.mesh,
|
||||
boxRaw: face.boxRaw,
|
||||
meshRaw: face.meshRaw,
|
||||
offsetRaw: face.offsetRaw,
|
||||
annotations: face.annotations,
|
||||
*/
|
||||
age: ageRes.age,
|
||||
gender: genderRes.gender,
|
||||
genderConfidence: genderRes.confidence,
|
||||
|
|
|
|||
Loading…
Reference in New Issue