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human
mirror of https://github.com/vladmandic/human
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convert to typescript

pull/70/head
Vladimir Mandic 2021-02-08 11:39:09 -05:00
parent ea9847927b
commit 6fb133b55e
69 changed files with 6640 additions and 6775 deletions
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2
README.md
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@ -46,7 +46,7 @@ Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows an
<br>
*This is a pre-release project, see [issues](https://github.com/vladmandic/human/issues) for list of known limitations and planned enhancements*
*See [issues](https://github.com/vladmandic/human/issues?q=) and [discussions](https://github.com/vladmandic/human/discussions) for list of known limitations and planned enhancements*
*Suggestions are welcome!*

9
demo/node.js
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@ -56,14 +56,19 @@ async function detect(input) {
}
async function test() {
// test with embedded face image
log.state('Processing embedded warmup image: face');
myConfig.warmup = 'face';
const resultFace = await human.warmup(myConfig);
log.data(resultFace);
log.data('Face: ', resultFace.face);
// test with embedded full body image
log.state('Processing embedded warmup image: full');
myConfig.warmup = 'full';
const resultFull = await human.warmup(myConfig);
log.data(resultFull);
log.data('Body:', resultFull.body);
log.data('Hand:', resultFull.hand);
log.data('Gesture:', resultFull.gesture);
}
async function main() {

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dist/demo-browser-index.json vendored
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@ -1,7 +1,7 @@
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@ -43,14 +43,14 @@
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@ -65,7 +65,7 @@
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@ -1,18 +1,18 @@
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@ -341,53 +320,49 @@
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@ -395,32 +370,32 @@
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@ -437,19 +412,19 @@
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@ -457,51 +432,51 @@
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{
"path": "src/emotion/emotion.js",
"path": "src/emotion/emotion.ts",
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{
"path": "src/embedding/embedding.js",
"path": "src/embedding/embedding.ts",
"kind": "import-statement"
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{
"path": "src/posenet/posenet.js",
"path": "src/posenet/posenet.ts",
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{
"path": "src/handpose/handpose.js",
"path": "src/handpose/handpose.ts",
"kind": "import-statement"
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{
"path": "src/gesture/gesture.js",
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{
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{
"path": "src/profile.js",
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"kind": "import-statement"
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{
@ -509,7 +484,7 @@
"kind": "import-statement"
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{
"path": "src/sample.js",
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{
@ -520,135 +495,132 @@
}
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}

234
dist/tfjs.esm.js vendored
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File diff suppressed because one or more lines are too long

4
dist/tfjs.esm.js.map vendored
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File diff suppressed because one or more lines are too long

6
dist/tfjs.esm.json vendored
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@ -25407,7 +25407,7 @@
}
]
},
"src/tfjs/tf-browser.js": {
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"bytes": 1784,
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{
@ -28613,7 +28613,7 @@
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},
"src/tfjs/tf-browser.js": {
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"node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/abs.js": {
@ -29739,7 +29739,7 @@
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}
},
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"bytes": 1071825
}
}
}

24
package-lock.json generated
View File

@ -821,9 +821,9 @@
}
},
"esbuild": {
"version": "0.8.42",
"resolved": "https://registry.npmjs.org/esbuild/-/esbuild-0.8.42.tgz",
"integrity": "sha512-zUtj5RMqROCCCH0vV/a7cd8YQg8I0GWBhV3A3PklWRT+oM/YwVbnrtFnITzE1otGdnXplWHWdZ4OcYiV0PN+JQ==",
"version": "0.8.43",
"resolved": "https://registry.npmjs.org/esbuild/-/esbuild-0.8.43.tgz",
"integrity": "sha512-ZVE2CpootS4jtnfV0bbtJdgRsHEXcMP0P7ZXGfTmNzzhBr2e5ag7Vp3ry0jmw8zduJz4iHzxg4m5jtPxWERz1w==",
"dev": true
},
"escalade": {
@ -2285,9 +2285,9 @@
"dev": true
},
"simple-git": {
"version": "2.32.0",
"resolved": "https://registry.npmjs.org/simple-git/-/simple-git-2.32.0.tgz",
"integrity": "sha512-swz7avV2JADYgTmvs+j/eDBt+gPx3SAyh2MxlDVvxqHzHLkKr6kLr4N62qZCv5LBxc9Wx8TIXVeJKmTTY8UdSQ==",
"version": "2.34.2",
"resolved": "https://registry.npmjs.org/simple-git/-/simple-git-2.34.2.tgz",
"integrity": "sha512-/EX4FtcpAj5L/Bs5zgaBGYDrnkrKflFVNppNLH9VXpIjZBLHx5cZ6/mOYJCoKXKlLRuk3iTvzrIsHo7v42zWHg==",
"dev": true,
"requires": {
"@kwsites/file-exists": "^1.1.1",
@ -2505,6 +2505,12 @@
"strip-bom": "^3.0.0"
}
},
"tslib": {
"version": "2.1.0",
"resolved": "https://registry.npmjs.org/tslib/-/tslib-2.1.0.tgz",
"integrity": "sha512-hcVC3wYEziELGGmEEXue7D75zbwIIVUMWAVbHItGPx0ziyXxrOMQx4rQEVEV45Ut/1IotuEvwqPopzIOkDMf0A==",
"dev": true
},
"type-check": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/type-check/-/type-check-0.4.0.tgz",
@ -2520,6 +2526,12 @@
"integrity": "sha512-4dbzIzqvjtgiM5rw1k5rEHtBANKmdudhGyBEajN01fEyhaAIhsoKNy6y7+IN93IfpFtwY9iqi7kD+xwKhQsNJA==",
"dev": true
},
"typescript": {
"version": "4.1.3",
"resolved": "https://registry.npmjs.org/typescript/-/typescript-4.1.3.tgz",
"integrity": "sha512-B3ZIOf1IKeH2ixgHhj6la6xdwR9QrLC5d1VKeCSY4tvkqhF2eqd9O7txNlS0PO3GrBAFIdr3L1ndNwteUbZLYg==",
"dev": true
},
"uri-js": {
"version": "4.4.1",
"resolved": "https://registry.npmjs.org/uri-js/-/uri-js-4.4.1.tgz",

6
package.json
View File

@ -35,7 +35,7 @@
"@vladmandic/pilogger": "^0.2.14",
"chokidar": "^3.5.1",
"dayjs": "^1.10.4",
"esbuild": "^0.8.42",
"esbuild": "^0.8.43",
"eslint": "^7.19.0",
"eslint-config-airbnb-base": "^14.2.1",
"eslint-plugin-import": "^2.22.1",
@ -44,7 +44,9 @@
"eslint-plugin-promise": "^4.2.1",
"rimraf": "^3.0.2",
"seedrandom": "^3.0.5",
"simple-git": "^2.32.0"
"simple-git": "^2.34.2",
"tslib": "^2.1.0",
"typescript": "^4.1.3"
},
"scripts": {
"start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",

30
server/build.js
View File

@ -6,6 +6,7 @@ const log = require('@vladmandic/pilogger');
// keeps esbuild service instance cached
let es;
let busy = false;
const banner = `
/*
Human library
@ -33,7 +34,7 @@ const targets = {
platform: 'node',
format: 'cjs',
metafile: 'dist/tfjs.esm.json',
entryPoints: ['src/tfjs/tf-node.js'],
entryPoints: ['src/tfjs/tf-node.ts'],
outfile: 'dist/tfjs.esm.js',
external: ['@tensorflow'],
},
@ -41,7 +42,7 @@ const targets = {
platform: 'node',
format: 'cjs',
metafile: 'dist/human.node.json',
entryPoints: ['src/human.js'],
entryPoints: ['src/human.ts'],
outfile: 'dist/human.node.js',
external: ['@tensorflow'],
},
@ -51,7 +52,7 @@ const targets = {
platform: 'node',
format: 'cjs',
metafile: 'dist/tfjs.esm.json',
entryPoints: ['src/tfjs/tf-node-gpu.js'],
entryPoints: ['src/tfjs/tf-node-gpu.ts'],
outfile: 'dist/tfjs.esm.js',
external: ['@tensorflow'],
},
@ -59,7 +60,7 @@ const targets = {
platform: 'node',
format: 'cjs',
metafile: 'dist/human.node.json',
entryPoints: ['src/human.js'],
entryPoints: ['src/human.ts'],
outfile: 'dist/human.node-gpu.js',
external: ['@tensorflow'],
},
@ -69,7 +70,7 @@ const targets = {
platform: 'browser',
format: 'esm',
metafile: 'dist/tfjs.esm.json',
entryPoints: ['src/tfjs/tf-browser.js'],
entryPoints: ['src/tfjs/tf-browser.ts'],
outfile: 'dist/tfjs.esm.js',
external: ['fs', 'buffer', 'util', '@tensorflow'],
},
@ -77,7 +78,7 @@ const targets = {
platform: 'browser',
format: 'esm',
metafile: 'dist/human.esm.json',
entryPoints: ['src/human.js'],
entryPoints: ['src/human.ts'],
outfile: 'dist/human.esm-nobundle.js',
external: ['fs', 'buffer', 'util', '@tensorflow'],
},
@ -87,7 +88,7 @@ const targets = {
platform: 'browser',
format: 'esm',
metafile: 'dist/tfjs.esm.json',
entryPoints: ['src/tfjs/tf-browser.js'],
entryPoints: ['src/tfjs/tf-browser.ts'],
outfile: 'dist/tfjs.esm.js',
external: ['fs', 'buffer', 'util'],
},
@ -95,16 +96,16 @@ const targets = {
platform: 'browser',
format: 'iife',
globalName: 'Human',
metafile: 'dist/human.json',
entryPoints: ['src/human.js'],
outfile: 'dist/human.js',
metafile: 'dist/human.tson',
entryPoints: ['src/human.ts'],
outfile: 'dist/human.ts',
external: ['fs', 'buffer', 'util'],
},
esm: {
platform: 'browser',
format: 'esm',
metafile: 'dist/human.esm.json',
entryPoints: ['src/human.js'],
entryPoints: ['src/human.ts'],
outfile: 'dist/human.esm.js',
external: ['fs', 'buffer', 'util'],
},
@ -148,6 +149,12 @@ async function getStats(metafile) {
// rebuild on file change
async function build(f, msg) {
if (busy) {
log.state('Build: busy...');
setTimeout(() => build(f, msg), 500);
return;
}
busy = true;
log.info('Build: file', msg, f, 'target:', common.target);
if (!es) es = await esbuild.startService();
// common build options
@ -168,6 +175,7 @@ async function build(f, msg) {
log.error('Build error', JSON.stringify(err.errors || err, null, 2));
if (require.main === module) process.exit(1);
}
busy = false;
}
if (require.main === module) {

4
server/changelog.js
View File

@ -21,9 +21,9 @@ Repository: **<${app.repository.url}>**
`;
async function update(f) {
const all = await git.log();
const gitLog = await git.log();
// @ts-ignore
const log = all.all.sort((a, b) => (new Date(b.date).getTime() - new Date(a.date).getTime()));
const log = gitLog.all.sort((a, b) => (new Date(b.date).getTime() - new Date(a.date).getTime()));
let previous = '';
for (const l of log) {

14
server/dev.js
View File

@ -52,6 +52,14 @@ const mime = {
'.wasm': 'application/wasm',
};
let last = Date.now();
async function buildAll(evt, msg) {
const now = Date.now();
if ((now - last) > 2) build.build(evt, msg);
else log.state('Build: merge event file', msg, evt);
last = now;
}
// watch filesystem for any changes and notify build when needed
async function watch() {
const watcher = chokidar.watch(options.monitor, {
@ -66,9 +74,9 @@ async function watch() {
});
// single event handler for file add/change/delete
watcher
.on('add', (evt) => build.build(evt, 'add'))
.on('change', (evt) => build.build(evt, 'modify'))
.on('unlink', (evt) => build.build(evt, 'remove'))
.on('add', (evt) => buildAll(evt, 'add'))
.on('change', (evt) => buildAll(evt, 'modify'))
.on('unlink', (evt) => buildAll(evt, 'remove'))
.on('error', (err) => log.error(`Client watcher error: ${err}`))
.on('ready', () => log.state('Monitoring:', options.monitor));
}

48
src/age/age.js → src/age/age.ts
View File

@ -1,12 +1,12 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
import * as profile from '../profile.js';
const models = {};
const models = { age: null };
let last = { age: 0 };
let skipped = Number.MAX_SAFE_INTEGER;
async function load(config) {
export async function load(config) {
if (!models.age) {
models.age = await tf.loadGraphModel(config.face.age.modelPath);
log(`load model: ${config.face.age.modelPath.match(/\/(.*)\./)[1]}`);
@ -14,7 +14,7 @@ async function load(config) {
return models.age;
}
async function predict(image, config) {
export async function predict(image, config) {
if (!models.age) return null;
if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {
skipped++;
@ -38,29 +38,27 @@ async function predict(image, config) {
tf.dispose(resize);
let ageT;
const obj = {};
const obj = { age: undefined };
if (!config.profile) {
if (config.face.age.enabled) ageT = await models.age.predict(enhance);
} else {
const profileAge = config.face.age.enabled ? await tf.profile(() => models.age.predict(enhance)) : {};
ageT = profileAge.result.clone();
profileAge.result.dispose();
// @ts-ignore
profile.run('age', profileAge);
if (models.age) {
if (!config.profile) {
if (config.face.age.enabled) ageT = await models.age.predict(enhance);
} else {
const profileAge = config.face.age.enabled ? await tf.profile(() => models.age.predict(enhance)) : {};
ageT = profileAge.result.clone();
profileAge.result.dispose();
profile.run('age', profileAge);
}
enhance.dispose();
if (ageT) {
const data = ageT.dataSync();
obj.age = Math.trunc(10 * data[0]) / 10;
}
ageT.dispose();
last = obj;
}
enhance.dispose();
if (ageT) {
const data = ageT.dataSync();
obj.age = Math.trunc(10 * data[0]) / 10;
}
ageT.dispose();
last = obj;
resolve(obj);
});
}
exports.predict = predict;
exports.load = load;

53
src/blazeface/blazeface.js → src/blazeface/blazeface.ts
View File

@ -1,4 +1,4 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
const NUM_LANDMARKS = 6;
@ -24,7 +24,7 @@ function generateAnchors(inputSize) {
return anchors;
}
const disposeBox = (box) => {
export const disposeBox = (box) => {
box.startEndTensor.dispose();
box.startPoint.dispose();
box.endPoint.dispose();
@ -65,7 +65,16 @@ function scaleBoxFromPrediction(face, scaleFactor) {
});
}
class BlazeFaceModel {
export class BlazeFaceModel {
blazeFaceModel: any;
width: number;
height: number;
anchorsData: any;
anchors: any;
inputSize: number;
config: any;
scaleFaces: number;
constructor(model, config) {
this.blazeFaceModel = model;
this.width = config.face.detector.inputSize;
@ -132,47 +141,11 @@ class BlazeFaceModel {
scaleFactor: [inputImage.shape[2] / this.width, inputImage.shape[1] / this.height],
};
}
async estimateFaces(input) {
// @ts-ignore
const { boxes, scaleFactor } = await this.getBoundingBoxes(input);
const faces = [];
for (const face of boxes) {
const landmarkData = face.landmarks.arraySync();
const scaledBox = scaleBoxFromPrediction(face, scaleFactor);
// @ts-ignore
const boxData = scaleBox.arraySync();
const probabilityData = face.probability.arraySync();
const anchor = face.anchor;
const [scaleFactorX, scaleFactorY] = scaleFactor;
const scaledLandmarks = landmarkData
.map((landmark) => ([
(landmark[0] + anchor[0]) * scaleFactorX,
(landmark[1] + anchor[1]) * scaleFactorY,
]));
const normalizedFace = {
topLeft: boxData.slice(0, 2),
bottomRight: boxData.slice(2),
landmarks: scaledLandmarks,
probability: probabilityData,
};
disposeBox(face.box);
face.landmarks.dispose();
face.probability.dispose();
scaledBox.dispose();
faces.push(normalizedFace);
}
return faces;
}
}
async function load(config) {
export async function load(config) {
const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });
const model = new BlazeFaceModel(blazeface, config);
log(`load model: ${config.face.detector.modelPath.match(/\/(.*)\./)[1]}`);
return model;
}
exports.load = load;
exports.BlazeFaceModel = BlazeFaceModel;
exports.disposeBox = disposeBox;

18
src/blazeface/box.js → src/blazeface/box.ts
View File

@ -1,29 +1,26 @@
import * as tf from '../../dist/tfjs.esm.js';
function scaleBoxCoordinates(box, factor) {
export function scaleBoxCoordinates(box, factor) {
const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];
const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];
return { startPoint, endPoint };
}
exports.scaleBoxCoordinates = scaleBoxCoordinates;
function getBoxSize(box) {
export function getBoxSize(box) {
return [
Math.abs(box.endPoint[0] - box.startPoint[0]),
Math.abs(box.endPoint[1] - box.startPoint[1]),
];
}
exports.getBoxSize = getBoxSize;
function getBoxCenter(box) {
export function getBoxCenter(box) {
return [
box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,
box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,
];
}
exports.getBoxCenter = getBoxCenter;
function cutBoxFromImageAndResize(box, image, cropSize) {
export function cutBoxFromImageAndResize(box, image, cropSize) {
const h = image.shape[1];
const w = image.shape[2];
const boxes = [[
@ -32,9 +29,8 @@ function cutBoxFromImageAndResize(box, image, cropSize) {
]];
return tf.image.cropAndResize(image, boxes, [0], cropSize);
}
exports.cutBoxFromImageAndResize = cutBoxFromImageAndResize;
function enlargeBox(box, factor = 1.5) {
export function enlargeBox(box, factor = 1.5) {
const center = getBoxCenter(box);
const size = getBoxSize(box);
const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];
@ -42,9 +38,8 @@ function enlargeBox(box, factor = 1.5) {
const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];
return { startPoint, endPoint, landmarks: box.landmarks };
}
exports.enlargeBox = enlargeBox;
function squarifyBox(box) {
export function squarifyBox(box) {
const centers = getBoxCenter(box);
const size = getBoxSize(box);
const maxEdge = Math.max(...size);
@ -53,4 +48,3 @@ function squarifyBox(box) {
const endPoint = [centers[0] + halfSize, centers[1] + halfSize];
return { startPoint, endPoint, landmarks: box.landmarks };
}
exports.squarifyBox = squarifyBox;

37
src/blazeface/coords.js → src/blazeface/coords.ts
View File

@ -1,4 +1,4 @@
const MESH_ANNOTATIONS = {
export const MESH_ANNOTATIONS = {
silhouette: [
10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,
397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,
@ -37,7 +37,7 @@ const MESH_ANNOTATIONS = {
leftCheek: [425],
};
const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.
export const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.
{ key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },
{ key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },
{ key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },
@ -49,7 +49,7 @@ const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to
// { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },
];
const UV468 = [
export const UV468 = [
[0.499976992607117, 0.652534008026123],
[0.500025987625122, 0.547487020492554],
[0.499974012374878, 0.602371990680695],
@ -520,7 +520,7 @@ const UV468 = [
[0.723330020904541, 0.363372981548309],
];
const TRI468 = [
export const TRI468 = [
127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,
151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,
157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,
@ -606,7 +606,7 @@ const TRI468 = [
259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,
453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];
const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,
export const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,
8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,
45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,
23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,
@ -614,7 +614,8 @@ const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3,
35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,
48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,
66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];
const TRI33 = [
export const TRI33 = [
/* eyes */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,
/* brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,
/* 4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,
@ -624,9 +625,10 @@ const TRI33 = [
/* chin */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,
/* cont */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,
];
const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];
const VTX68 = [
export const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];
export const VTX68 = [
/* cont */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,
/* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,
/* nose */ 168, 6, 195, 4, 98, 97, 2, 326, 327,
@ -634,18 +636,13 @@ const VTX68 = [
/* lip */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,
/* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,
];
const VTX33 = [33, 133, 362, 263, 1, 62, 308, 159, 145, 386, 374, 6, 102, 331, 2, 13, 14, 70, 105, 107, 336, 334, 300, 54, 10, 284, 50, 280, 234, 454, 58, 288, 152];
const VTX7 = [33, 133, 362, 263, 1, 78, 308];
exports.MESH_ANNOTATIONS = MESH_ANNOTATIONS;
exports.MESH_TO_IRIS_INDICES_MAP = MESH_TO_IRIS_INDICES_MAP;
export const VTX33 = [33, 133, 362, 263, 1, 62, 308, 159, 145, 386, 374, 6, 102, 331, 2, 13, 14, 70, 105, 107, 336, 334, 300, 54, 10, 284, 50, 280, 234, 454, 58, 288, 152];
exports.TRI468 = TRI468;
exports.TRI68 = TRI68;
exports.TRI33 = TRI33;
exports.TRI7 = TRI7;
export const VTX7 = [33, 133, 362, 263, 1, 78, 308];
exports.UV468 = UV468;
exports.UV68 = VTX68.map((x) => UV468[x]);
exports.UV33 = VTX33.map((x) => UV468[x]);
exports.UV7 = VTX7.map((x) => UV468[x]);
export const UV68 = VTX68.map((x) => UV468[x]);
export const UV33 = VTX33.map((x) => UV468[x]);
export const UV7 = VTX7.map((x) => UV468[x]);

12
src/blazeface/facemesh.js → src/blazeface/facemesh.ts
View File

@ -1,12 +1,14 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
import * as blazeface from './blazeface.js';
import * as facepipeline from './facepipeline.js';
import * as coords from './coords.js';
class MediaPipeFaceMesh {
export class MediaPipeFaceMesh {
facePipeline: any;
config: any;
constructor(blazeFace, blazeMeshModel, irisModel, config) {
// @ts-ignore
this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel, config);
this.config = config;
}
@ -48,7 +50,7 @@ class MediaPipeFaceMesh {
}
let faceModels = [null, null, null];
async function load(config) {
export async function load(config) {
faceModels = await Promise.all([
(!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,
(!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,
@ -60,6 +62,4 @@ async function load(config) {
return faceMesh;
}
exports.load = load;
exports.MediaPipeFaceMesh = MediaPipeFaceMesh;
exports.triangulation = coords.TRI468;

44
src/blazeface/facepipeline.js → src/blazeface/facepipeline.ts
View File

@ -4,7 +4,7 @@ import * as bounding from './box';
import * as util from './util';
import * as coords from './coords.js';
// eslint-disable-next-line no-unused-vars
import { log } from '../log.js';
import { log } from '../log';
const LANDMARKS_COUNT = 468;
const MESH_MOUTH_INDEX = 13;
@ -22,11 +22,11 @@ const IRIS_IRIS_INDEX = 71;
const IRIS_NUM_COORDINATES = 76;
// Replace the raw coordinates returned by facemesh with refined iris model coordinates. Update the z coordinate to be an average of the original and the new. This produces the best visual effect.
function replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {
function replaceRawCoordinates(rawCoords, newCoords, prefix, keys = null) {
for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {
const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];
const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];
const shouldReplaceAllKeys = keys == null;
const shouldReplaceAllKeys = keys === null;
if (shouldReplaceAllKeys || keys.includes(key)) {
for (let j = 0; j < indices.length; j++) {
const index = indices[j];
@ -39,7 +39,19 @@ function replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {
}
}
// The Pipeline coordinates between the bounding box and skeleton models.
class Pipeline {
export class Pipeline {
storedBoxes: any;
runsWithoutFaceDetector: number;
boundingBoxDetector: any;
meshDetector: any;
irisModel: any;
meshWidth: number;
meshHeight: number;
irisSize: number;
irisEnlarge: number;
skipped: number;
detectedFaces: number;
constructor(boundingBoxDetector, meshDetector, irisModel, config) {
// An array of facial bounding boxes.
this.storedBoxes = [];
@ -56,7 +68,6 @@ class Pipeline {
}
transformRawCoords(rawCoords, box, angle, rotationMatrix) {
// @ts-ignore
const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });
const scaleFactor = [boxSize[0] / this.meshWidth, boxSize[1] / this.meshHeight];
const coordsScaled = rawCoords.map((coord) => ([
@ -66,7 +77,6 @@ class Pipeline {
const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;
const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;
const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;
// @ts-ignore
const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];
return coordsRotated.map((coord) => ([
coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),
@ -83,9 +93,7 @@ class Pipeline {
// Returns a box describing a cropped region around the eye fit for passing to the iris model.
getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {
// @ts-ignore
const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));
// @ts-ignore
const boxSize = bounding.getBoxSize(box);
let crop = tf.image.cropAndResize(face, [[
box.startPoint[1] / this.meshHeight,
@ -159,11 +167,8 @@ class Pipeline {
return null;
}
for (let i = 0; i < this.storedBoxes.length; i++) {
// @ts-ignore
const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);
// @ts-ignore
const enlargedBox = bounding.enlargeBox(scaledBox);
// @ts-ignore
const squarifiedBox = bounding.squarifyBox(enlargedBox);
const landmarks = this.storedBoxes[i].landmarks.arraySync();
const confidence = this.storedBoxes[i].confidence;
@ -188,17 +193,14 @@ class Pipeline {
if (config.face.detector.rotation) {
const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= LANDMARKS_COUNT) ? MESH_KEYPOINTS_LINE_OF_SYMMETRY_INDICES : BLAZEFACE_KEYPOINTS_LINE_OF_SYMMETRY_INDICES;
angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);
// @ts-ignore
const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });
const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];
const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized);
rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);
// @ts-ignore
face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshHeight, this.meshWidth]).div(255);
} else {
rotationMatrix = util.IDENTITY_MATRIX;
const cloned = input.clone();
// @ts-ignore
face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, cloned, [this.meshHeight, this.meshWidth]).div(255);
}
@ -215,8 +217,8 @@ class Pipeline {
}
const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours, which are included in the coordinates.
const confidenceVal = confidence.dataSync()[0];
if (confidenceVal < config.face.detector.minConfidence) return null; // if below confidence just exit
const faceConfidence = confidence.dataSync()[0];
if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit
const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);
let rawCoords = coordsReshaped.arraySync();
@ -245,20 +247,19 @@ class Pipeline {
}
const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);
// @ts-ignore
const landmarksBox = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData));
// @ts-ignore
const squarifiedLandmarksBox = bounding.squarifyBox(landmarksBox);
const transformedCoords = tf.tensor2d(transformedCoordsData);
const prediction = {
coords: transformedCoords,
box: landmarksBox,
faceConfidence: confidenceVal,
faceConfidence,
confidence: box.confidence,
image: face,
rawCoords,
};
if (config.face.mesh.returnRawData) prediction.rawCoords = rawCoords;
this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoords.arraySync(), confidence: box.confidence, faceConfidence: confidenceVal };
if (!config.face.mesh.returnRawData) delete prediction.rawCoords;
this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoords.arraySync(), confidence: box.confidence, faceConfidence };
return prediction;
}));
@ -275,4 +276,3 @@ class Pipeline {
return { startPoint, endPoint, landmarks };
}
}
exports.Pipeline = Pipeline;

34
src/blazeface/util.js → src/blazeface/util.ts
View File

@ -1,52 +1,47 @@
exports.IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];
export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];
/**
* Normalizes the provided angle to the range -pi to pi.
* @param angle The angle in radians to be normalized.
*/
function normalizeRadians(angle) {
export function normalizeRadians(angle) {
return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));
}
exports.normalizeRadians = normalizeRadians;
/**
* Computes the angle of rotation between two anchor points.
* @param point1 First anchor point
* @param point2 Second anchor point
*/
function computeRotation(point1, point2) {
export function computeRotation(point1, point2) {
const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);
return normalizeRadians(radians);
}
exports.computeRotation = computeRotation;
function radToDegrees(rad) {
export function radToDegrees(rad) {
return rad * 180 / Math.PI;
}
exports.radToDegrees = radToDegrees;
function buildTranslationMatrix(x, y) {
export function buildTranslationMatrix(x, y) {
return [[1, 0, x], [0, 1, y], [0, 0, 1]];
}
function dot(v1, v2) {
export function dot(v1, v2) {
let product = 0;
for (let i = 0; i < v1.length; i++) {
product += v1[i] * v2[i];
}
return product;
}
exports.dot = dot;
function getColumnFrom2DArr(arr, columnIndex) {
export function getColumnFrom2DArr(arr, columnIndex) {
const column = [];
for (let i = 0; i < arr.length; i++) {
column.push(arr[i][columnIndex]);
}
return column;
}
exports.getColumnFrom2DArr = getColumnFrom2DArr;
function multiplyTransformMatrices(mat1, mat2) {
export function multiplyTransformMatrices(mat1, mat2) {
const product = [];
const size = mat1.length;
for (let row = 0; row < size; row++) {
@ -57,7 +52,8 @@ function multiplyTransformMatrices(mat1, mat2) {
}
return product;
}
function buildRotationMatrix(rotation, center) {
export function buildRotationMatrix(rotation, center) {
const cosA = Math.cos(rotation);
const sinA = Math.sin(rotation);
const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];
@ -66,9 +62,8 @@ function buildRotationMatrix(rotation, center) {
const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);
return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);
}
exports.buildRotationMatrix = buildRotationMatrix;
function invertTransformMatrix(matrix) {
export function invertTransformMatrix(matrix) {
const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];
const translationComponent = [matrix[0][2], matrix[1][2]];
const invertedTranslation = [
@ -81,17 +76,14 @@ function invertTransformMatrix(matrix) {
[0, 0, 1],
];
}
exports.invertTransformMatrix = invertTransformMatrix;
function rotatePoint(homogeneousCoordinate, rotationMatrix) {
export function rotatePoint(homogeneousCoordinate, rotationMatrix) {
return [
dot(homogeneousCoordinate, rotationMatrix[0]),
dot(homogeneousCoordinate, rotationMatrix[1]),
];
}
exports.rotatePoint = rotatePoint;
function xyDistanceBetweenPoints(a, b) {
export function xyDistanceBetweenPoints(a, b) {
return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));
}
exports.xyDistanceBetweenPoints = xyDistanceBetweenPoints;

15
src/embedding/embedding.js → src/embedding/embedding.ts
View File

@ -1,13 +1,13 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
import * as profile from '../profile.js';
// based on https://github.com/sirius-ai/MobileFaceNet_TF
// model converted from https://github.com/sirius-ai/MobileFaceNet_TF/files/3551493/FaceMobileNet192_train_false.zip
const models = {};
const models = { embedding: null };
async function load(config) {
export async function load(config) {
if (!models.embedding) {
models.embedding = await tf.loadGraphModel(config.face.embedding.modelPath);
log(`load model: ${config.face.embedding.modelPath.match(/\/(.*)\./)[1]}`);
@ -15,7 +15,7 @@ async function load(config) {
return models.embedding;
}
function simmilarity(embedding1, embedding2) {
export function simmilarity(embedding1, embedding2) {
if (embedding1?.length !== embedding2?.length) return 0;
// general minkowski distance
// euclidean distance is limited case where order is 2
@ -24,7 +24,7 @@ function simmilarity(embedding1, embedding2) {
return (Math.trunc(1000 * (1 - distance)) / 1000);
}
async function predict(image, config) {
export async function predict(image, config) {
if (!models.embedding) return null;
return new Promise(async (resolve) => {
const resize = tf.image.resizeBilinear(image, [config.face.embedding.inputSize, config.face.embedding.inputSize], false);
@ -39,7 +39,6 @@ async function predict(image, config) {
const profileData = await tf.profile(() => models.embedding.predict({ img_inputs: resize }));
data = [...profileData.result.dataSync()];
profileData.result.dispose();
// @ts-ignore
profile.run('emotion', profileData);
}
}
@ -48,7 +47,3 @@ async function predict(image, config) {
resolve(data);
});
}
exports.predict = predict;
exports.simmilarity = simmilarity;
exports.load = load;

11
src/emotion/emotion.js → src/emotion/emotion.ts
View File

@ -1,9 +1,9 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
import * as profile from '../profile.js';
const annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];
const models = {};
const models = { emotion: null };
let last = [];
let skipped = Number.MAX_SAFE_INTEGER;
@ -11,7 +11,7 @@ let skipped = Number.MAX_SAFE_INTEGER;
const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale
const scale = 1; // score multiplication factor
async function load(config) {
export async function load(config) {
if (!models.emotion) {
models.emotion = await tf.loadGraphModel(config.face.emotion.modelPath);
log(`load model: ${config.face.emotion.modelPath.match(/\/(.*)\./)[1]}`);
@ -19,7 +19,7 @@ async function load(config) {
return models.emotion;
}
async function predict(image, config) {
export async function predict(image, config) {
if (!models.emotion) return null;
if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {
skipped++;
@ -77,6 +77,3 @@ async function predict(image, config) {
resolve(obj);
});
}
exports.predict = predict;
exports.load = load;

29
src/faceboxes/faceboxes.js → src/faceboxes/faceboxes.ts
View File

@ -1,9 +1,14 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
import * as profile from '../profile.js';
class FaceBoxes {
export class FaceBoxes {
enlarge: number;
model: any;
config: any;
constructor(model, config) {
this.enlarge = 1.1;
this.model = model;
this.config = config;
}
@ -36,15 +41,20 @@ class FaceBoxes {
resizeT.dispose();
for (const i in boxes) {
if (scores[i] && scores[i] > this.config.face.detector.minConfidence) {
const enlarge = 1.05;
const crop = [boxes[i][0] / enlarge, boxes[i][1] / enlarge, boxes[i][2] * enlarge, boxes[i][3] * enlarge];
const crop = [boxes[i][0] / this.enlarge, boxes[i][1] / this.enlarge, boxes[i][2] * this.enlarge, boxes[i][3] * this.enlarge];
const boxRaw = [crop[1], crop[0], (crop[3]) - (crop[1]), (crop[2]) - (crop[0])];
const box = [parseInt(boxRaw[0] * input.shape[2]), parseInt(boxRaw[1] * input.shape[1]), parseInt(boxRaw[2] * input.shape[2]), parseInt(boxRaw[3] * input.shape[1])];
const image = tf.image.cropAndResize(input, [crop], [0], [this.config.face.detector.inputSize, this.config.face.detector.inputSize]);
const box = [
parseInt((boxRaw[0] * input.shape[2]).toString()),
parseInt((boxRaw[1] * input.shape[1]).toString()),
parseInt((boxRaw[2] * input.shape[2]).toString()),
parseInt((boxRaw[3] * input.shape[1]).toString())];
const resized = tf.image.cropAndResize(input, [crop], [0], [this.config.face.detector.inputSize, this.config.face.detector.inputSize]);
const image = resized.div([255]);
resized.dispose();
results.push({
confidence: scores[i],
box,
boxRaw,
boxRaw: this.config.face.mesh.returnRawData ? boxRaw : null,
image,
// mesh,
// meshRaw,
@ -56,7 +66,7 @@ class FaceBoxes {
}
}
async function load(config) {
export async function load(config) {
const model = await tf.loadGraphModel(config.face.detector.modelPath);
log(`load model: ${config.face.detector.modelPath.match(/\/(.*)\./)[1]}`);
const faceboxes = new FaceBoxes(model, config);
@ -64,6 +74,3 @@ async function load(config) {
if (config.face.iris.enabled) log(`load model: ${config.face.iris.modelPath.match(/\/(.*)\./)[1]}`);
return faceboxes;
}
exports.load = load;
exports.FaceBoxes = FaceBoxes;

14
src/gender/gender.js → src/gender/gender.ts
View File

@ -1,8 +1,8 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
import * as profile from '../profile.js';
const models = {};
const models = { gender: null };
let last = { gender: '' };
let skipped = Number.MAX_SAFE_INTEGER;
let alternative = false;
@ -10,7 +10,7 @@ let alternative = false;
// tuning values
const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale
async function load(config) {
export async function load(config) {
if (!models.gender) {
models.gender = await tf.loadGraphModel(config.face.gender.modelPath);
alternative = models.gender.inputs[0].shape[3] === 1;
@ -19,7 +19,7 @@ async function load(config) {
return models.gender;
}
async function predict(image, config) {
export async function predict(image, config) {
if (!models.gender) return null;
if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {
skipped++;
@ -45,7 +45,7 @@ async function predict(image, config) {
tf.dispose(resize);
let genderT;
const obj = {};
const obj = { gender: undefined, confidence: undefined };
if (!config.profile) {
if (config.face.gender.enabled) genderT = await models.gender.predict(enhance);
@ -53,7 +53,6 @@ async function predict(image, config) {
const profileGender = config.face.gender.enabled ? await tf.profile(() => models.gender.predict(enhance)) : {};
genderT = profileGender.result.clone();
profileGender.result.dispose();
// @ts-ignore
profile.run('gender', profileGender);
}
enhance.dispose();
@ -82,6 +81,3 @@ async function predict(image, config) {
resolve(obj);
});
}
exports.predict = predict;
exports.load = load;

8
src/gesture/gesture.js → src/gesture/gesture.ts
View File

@ -1,4 +1,4 @@
exports.body = (res) => {
export const body = (res) => {
if (!res) return [];
const gestures = [];
for (let i = 0; i < res.length; i++) {
@ -18,7 +18,7 @@ exports.body = (res) => {
return gestures;
};
exports.face = (res) => {
export const face = (res) => {
if (!res) return [];
const gestures = [];
for (let i = 0; i < res.length; i++) {
@ -39,7 +39,7 @@ exports.face = (res) => {
return gestures;
};
exports.iris = (res) => {
export const iris = (res) => {
if (!res) return [];
const gestures = [];
for (let i = 0; i < res.length; i++) {
@ -58,7 +58,7 @@ exports.iris = (res) => {
return gestures;
};
exports.hand = (res) => {
export const hand = (res) => {
if (!res) return [];
const gestures = [];
for (let i = 0; i < res.length; i++) {

2
src/handpose/anchors.js → src/handpose/anchors.ts
View File

@ -1,4 +1,4 @@
exports.anchors = [
export const anchors = [
{
w: 1,
h: 1,

29
src/handpose/box.js → src/handpose/box.ts
View File

@ -1,18 +1,20 @@
import * as tf from '../../dist/tfjs.esm.js';
function getBoxSize(box) {
export function getBoxSize(box) {
return [
Math.abs(box.endPoint[0] - box.startPoint[0]),
Math.abs(box.endPoint[1] - box.startPoint[1]),
];
}
function getBoxCenter(box) {
export function getBoxCenter(box) {
return [
box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,
box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,
];
}
function cutBoxFromImageAndResize(box, image, cropSize) {
export function cutBoxFromImageAndResize(box, image, cropSize) {
const h = image.shape[1];
const w = image.shape[2];
const boxes = [[
@ -23,7 +25,8 @@ function cutBoxFromImageAndResize(box, image, cropSize) {
]];
return tf.image.cropAndResize(image, boxes, [0], cropSize);
}
function scaleBoxCoordinates(box, factor) {
export function scaleBoxCoordinates(box, factor) {
const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];
const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];
const palmLandmarks = box.palmLandmarks.map((coord) => {
@ -32,7 +35,8 @@ function scaleBoxCoordinates(box, factor) {
});
return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };
}
function enlargeBox(box, factor = 1.5) {
export function enlargeBox(box, factor = 1.5) {
const center = getBoxCenter(box);
const size = getBoxSize(box);
const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];
@ -40,7 +44,8 @@ function enlargeBox(box, factor = 1.5) {
const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];
return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };
}
function squarifyBox(box) {
export function squarifyBox(box) {
const centers = getBoxCenter(box);
const size = getBoxSize(box);
const maxEdge = Math.max(...size);
@ -49,7 +54,8 @@ function squarifyBox(box) {
const endPoint = [centers[0] + halfSize, centers[1] + halfSize];
return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };
}
function shiftBox(box, shiftFactor) {
export function shiftBox(box, shiftFactor) {
const boxSize = [
box.endPoint[0] - box.startPoint[0],
box.endPoint[1] - box.startPoint[1],
@ -59,12 +65,3 @@ function shiftBox(box, shiftFactor) {
const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];
return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };
}
export {
cutBoxFromImageAndResize,
enlargeBox,
getBoxCenter,
getBoxSize,
scaleBoxCoordinates,
shiftBox,
squarifyBox,
};

9
src/handpose/handdetector.js → src/handpose/handdetector.ts
View File

@ -1,7 +1,13 @@
import * as tf from '../../dist/tfjs.esm.js';
import * as box from './box';
class HandDetector {
export class HandDetector {
model: any;
anchors: any;
anchorsTensor: any;
inputSizeTensor: any;
doubleInputSizeTensor: any;
constructor(model, inputSize, anchorsAnnotated) {
this.model = model;
this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);
@ -78,4 +84,3 @@ class HandDetector {
return hands;
}
}
exports.HandDetector = HandDetector;

13
src/handpose/handpipeline.js → src/handpose/handpipeline.ts
View File

@ -2,7 +2,7 @@ import * as tf from '../../dist/tfjs.esm.js';
import * as box from './box';
import * as util from './util';
// eslint-disable-next-line no-unused-vars
import { log } from '../log.js';
import { log } from '../log';
// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];
const PALM_BOX_ENLARGE_FACTOR = 5; // default 3
@ -12,7 +12,14 @@ const PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];
const PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;
const PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;
class HandPipeline {
export class HandPipeline {
handDetector: any;
landmarkDetector: any;
inputSize: number;
storedBoxes: any;
skipped: number;
detectedHands: number;
constructor(handDetector, landmarkDetector, inputSize) {
this.handDetector = handDetector;
this.landmarkDetector = landmarkDetector;
@ -154,5 +161,3 @@ class HandPipeline {
return { startPoint, endPoint };
}
}
exports.HandPipeline = HandPipeline;

12
src/handpose/handpose.js → src/handpose/handpose.ts
View File

@ -1,6 +1,6 @@
// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
import * as handdetector from './handdetector';
import * as handpipeline from './handpipeline';
@ -15,7 +15,9 @@ const MESH_ANNOTATIONS = {
palmBase: [0],
};
class HandPose {
export class HandPose {
handPipeline: any;
constructor(handPipeline) {
this.handPipeline = handPipeline;
}
@ -51,20 +53,16 @@ class HandPose {
return hands;
}
}
exports.HandPose = HandPose;
async function load(config) {
export async function load(config) {
const [handDetectorModel, handPoseModel] = await Promise.all([
config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,
config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,
]);
// @ts-ignore
const handDetector = new handdetector.HandDetector(handDetectorModel, config.hand.inputSize, anchors.anchors);
// @ts-ignore
const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, config.hand.inputSize);
const handPose = new HandPose(handPipeline);
if (config.hand.enabled) log(`load model: ${config.hand.detector.modelPath.match(/\/(.*)\./)[1]}`);
if (config.hand.landmarks) log(`load model: ${config.hand.skeleton.modelPath.match(/\/(.*)\./)[1]}`);
return handPose;
}
exports.load = load;

36
src/handpose/util.js → src/handpose/util.ts
View File

@ -1,38 +1,43 @@
function normalizeRadians(angle) {
export function normalizeRadians(angle) {
return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));
}
function computeRotation(point1, point2) {
export function computeRotation(point1, point2) {
const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);
return normalizeRadians(radians);
}
const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];
function dot(v1, v2) {
export const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];
export function dot(v1, v2) {
let product = 0;
for (let i = 0; i < v1.length; i++) {
product += v1[i] * v2[i];
}
return product;
}
function getColumnFrom2DArr(arr, columnIndex) {
export function getColumnFrom2DArr(arr, columnIndex) {
const column = [];
for (let i = 0; i < arr.length; i++) {
column.push(arr[i][columnIndex]);
}
return column;
}
function multiplyTransformMatrices(mat1, mat2) {
export function multiplyTransformMatrices(mat1, mat2) {
const product = [];
const size = mat1.length;
for (let row = 0; row < size; row++) {
product.push([]);
for (let col = 0; col < size; col++) {
// @ts-ignore
product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));
}
}
return product;
}
function buildRotationMatrix(rotation, center) {
export function buildRotationMatrix(rotation, center) {
const cosA = Math.cos(rotation);
const sinA = Math.sin(rotation);
const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];
@ -41,7 +46,8 @@ function buildRotationMatrix(rotation, center) {
const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);
return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);
}
function invertTransformMatrix(matrix) {
export function invertTransformMatrix(matrix) {
const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];
const translationComponent = [matrix[0][2], matrix[1][2]];
const invertedTranslation = [
@ -54,18 +60,10 @@ function invertTransformMatrix(matrix) {
[0, 0, 1],
];
}
function rotatePoint(homogeneousCoordinate, rotationMatrix) {
export function rotatePoint(homogeneousCoordinate, rotationMatrix) {
return [
dot(homogeneousCoordinate, rotationMatrix[0]),
dot(homogeneousCoordinate, rotationMatrix[1]),
];
}
export {
buildRotationMatrix,
computeRotation,
dot,
getColumnFrom2DArr,
invertTransformMatrix,
normalizeRadians,
rotatePoint,
};

61
src/human.js → src/human.ts
View File

@ -1,25 +1,26 @@
import { log } from './log.js';
import { log } from './log';
import * as tf from '../dist/tfjs.esm.js';
import * as backend from './tfjs/backend.js';
import * as facemesh from './blazeface/facemesh.js';
import * as faceboxes from './faceboxes/faceboxes.js';
import * as age from './age/age.js';
import * as gender from './gender/gender.js';
import * as emotion from './emotion/emotion.js';
import * as embedding from './embedding/embedding.js';
import * as posenet from './posenet/posenet.js';
import * as handpose from './handpose/handpose.js';
import * as gesture from './gesture/gesture.js';
import * as image from './image.js';
import * as profile from './profile.js';
import * as config from '../config.js';
import * as sample from './sample.js';
import * as backend from './tfjs/backend';
import * as facemesh from './blazeface/facemesh';
import * as faceboxes from './faceboxes/faceboxes';
import * as age from './age/age';
import * as gender from './gender/gender';
import * as emotion from './emotion/emotion';
import * as embedding from './embedding/embedding';
import * as posenet from './posenet/posenet';
import * as handpose from './handpose/handpose';
import * as gesture from './gesture/gesture';
import * as image from './image';
import * as profile from './profile';
import * as config from '../config';
import * as sample from './sample';
import * as app from '../package.json';
import { NodeFileSystem } from '@tensorflow/tfjs-node/dist/io/file_system';
// helper function: gets elapsed time on both browser and nodejs
const now = () => {
if (typeof performance !== 'undefined') return performance.now();
return parseInt(Number(process.hrtime.bigint()) / 1000 / 1000);
return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());
};
// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides
@ -42,6 +43,25 @@ function mergeDeep(...objects) {
}
class Human {
tf: any;
version: string;
config: any;
fx: any;
state: string;
numTensors: number;
analyzeMemoryLeaks: boolean;
checkSanity: boolean;
firstRun: boolean;
perf: any;
models: any;
// models
facemesh: any;
age: any;
gender: any;
emotion: any;
body: any;
hand: any;
constructor(userConfig = {}) {
this.tf = tf;
this.version = app.version;
@ -108,7 +128,7 @@ class Human {
}
// preload models, not explicitly required as it's done automatically on first use
async load(userConfig) {
async load(userConfig = null) {
this.state = 'load';
const timeStamp = now();
if (userConfig) this.config = mergeDeep(this.config, userConfig);
@ -160,7 +180,7 @@ class Human {
}
// check if backend needs initialization if it changed
async checkBackend(force) {
async checkBackend(force = false) {
if (this.config.backend && (this.config.backend !== '') && force || (tf.getBackend() !== this.config.backend)) {
const timeStamp = now();
this.state = 'backend';
@ -308,7 +328,7 @@ class Human {
emotion: emotionRes,
embedding: embeddingRes,
iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,
image: face.image.toInt().squeeze(),
// image: face.image.toInt().squeeze(),
});
// dont need face anymore
@ -487,7 +507,8 @@ class Human {
async warmupNode() {
const atob = (str) => Buffer.from(str, 'base64');
const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);
const data = tf.node.decodeJpeg(img);
// @ts-ignore
const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs
const expanded = data.expandDims(0);
tf.dispose(data);
// log('Input:', expanded);

10
src/image.js → src/image.ts
View File

@ -1,6 +1,6 @@
import { log } from './log.js';
import { log } from './log';
import * as tf from '../dist/tfjs.esm.js';
import * as fxImage from './imagefx.js';
import * as fxImage from './imagefx';
// internal temp canvases
let inCanvas = null;
@ -9,7 +9,7 @@ let outCanvas = null;
// process input image and return tensor
// input can be tensor, imagedata, htmlimageelement, htmlvideoelement
// input is resized and run through imagefx filter
function process(input, config) {
export function process(input, config) {
let tensor;
if (input instanceof tf.Tensor) {
tensor = tf.clone(input);
@ -39,7 +39,7 @@ function process(input, config) {
outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');
if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;
if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;
this.fx = tf.ENV.flags.IS_BROWSER ? new fxImage.Canvas({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')
this.fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')
}
if (!this.fx) return inCanvas;
this.fx.reset();
@ -106,5 +106,3 @@ function process(input, config) {
}
return { tensor, canvas: config.filter.return ? outCanvas : null };
}
exports.process = process;

10
src/imagefx.js
View File

@ -5,7 +5,7 @@ WebGLImageFilter - MIT Licensed
<https://github.com/phoboslab/WebGLImageFilter>
*/
const WebGLProgram = function (gl, vertexSource, fragmentSource) {
const GLProgram = function (gl, vertexSource, fragmentSource) {
const _collect = function (source, prefix, collection) {
const r = new RegExp('\\b' + prefix + ' \\w+ (\\w+)', 'ig');
source.replace(r, (match, name) => {
@ -58,7 +58,7 @@ const WebGLProgram = function (gl, vertexSource, fragmentSource) {
}
};
const WebGLImageFilter = function (params) {
const GLImageFilter = function (params) {
if (!params) params = { };
let _drawCount = 0;
let _sourceTexture = null;
@ -180,7 +180,7 @@ const WebGLImageFilter = function (params) {
return { fbo, texture };
};
const _draw = function (flags) {
const _draw = function (flags = null) {
let source = null;
let target = null;
let flipY = false;
@ -225,7 +225,7 @@ const WebGLImageFilter = function (params) {
}
// Compile shaders
_currentProgram = new WebGLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);
_currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);
const floatSize = Float32Array.BYTES_PER_ELEMENT;
const vertSize = 4 * floatSize;
@ -606,4 +606,4 @@ const WebGLImageFilter = function (params) {
].join('\n');
};
exports.Canvas = WebGLImageFilter;
exports.GLImageFilter = GLImageFilter;

0
src/log.js → src/log.ts
View File

2
src/node.js
View File

@ -1,6 +1,6 @@
const console = require('console');
const tf = require('@tensorflow/tfjs-node');
const Human = require('..').default; // this resolves to project root which is '@vladmandic/human'
const Human = require('../dist/human.node').default; // this resolves to project root which is '@vladmandic/human'
const logger = new console.Console({
stdout: process.stdout,

3
src/posenet/buildParts.js → src/posenet/buildParts.ts
View File

@ -19,7 +19,7 @@ function scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, loca
return localMaximum;
}
function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {
export function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {
const [height, width, numKeypoints] = scores.shape;
const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);
for (let heatmapY = 0; heatmapY < height; ++heatmapY) {
@ -37,4 +37,3 @@ function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {
}
return queue;
}
exports.buildPartWithScoreQueue = buildPartWithScoreQueue;

7
src/posenet/decodeMultiple.js → src/posenet/decodeMultiple.ts
View File

@ -7,7 +7,6 @@ const kLocalMaximumRadius = 1;
function withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {
return poses.some(({ keypoints }) => {
const correspondingKeypoint = keypoints[keypointId].position;
// @ts-ignore
return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;
});
}
@ -20,9 +19,8 @@ function getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {
return notOverlappedKeypointScores / instanceKeypoints.length;
}
function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config) {
export function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config) {
const poses = [];
// @ts-ignore
const queue = buildParts.buildPartWithScoreQueue(config.body.scoreThreshold, kLocalMaximumRadius, scoresBuffer);
const squaredNmsRadius = config.body.nmsRadius ^ 2;
// Generate at most maxDetections object instances per image in decreasing root part score order.
@ -30,15 +28,12 @@ function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer
// The top element in the queue is the next root candidate.
const root = queue.dequeue();
// Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.
// @ts-ignore
const rootImageCoords = vectors.getImageCoords(root.part, config.body.outputStride, offsetsBuffer);
if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;
// Else start a new detection instance at the position of the root.
// @ts-ignore
const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, config.body.outputStride, displacementsFwdBuffer, displacementsBwdBuffer);
const score = getInstanceScore(poses, squaredNmsRadius, keypoints);
if (score > config.body.scoreThreshold) poses.push({ keypoints, score });
}
return poses;
}
exports.decodeMultiplePoses = decodeMultiplePoses;

15
src/posenet/decodePose.js → src/posenet/decodePose.ts
View File

@ -14,9 +14,7 @@ function getDisplacement(edgeId, point, displacements) {
}
function getStridedIndexNearPoint(point, outputStride, height, width) {
return {
// @ts-ignore
y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),
// @ts-ignore
x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),
};
}
@ -26,14 +24,11 @@ function traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scor
// Nearest neighbor interpolation for the source->target displacements.
const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);
const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);
// @ts-ignore
const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);
let targetKeypoint = displacedPoint;
for (let i = 0; i < offsetRefineStep; i++) {
const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);
// @ts-ignore
const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);
// @ts-ignore
targetKeypoint = vectors.addVectors({
x: targetKeypointIndices.x * outputStride,
y: targetKeypointIndices.y * outputStride,
@ -44,13 +39,12 @@ function traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scor
return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };
}
function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {
export function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {
const numParts = scores.shape[2];
const numEdges = parentToChildEdges.length;
const instanceKeypoints = new Array(numParts);
// Start a new detection instance at the position of the root.
const { part: rootPart, score: rootScore } = root;
// @ts-ignore
const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);
instanceKeypoints[rootPart.id] = {
score: rootScore,
@ -75,20 +69,16 @@ function decodePose(root, scores, offsets, outputStride, displacementsFwd, displ
}
return instanceKeypoints;
}
exports.decodePose = decodePose;
async function decodeSinglePose(heatmapScores, offsets, config) {
export async function decodeSinglePose(heatmapScores, offsets, config) {
let totalScore = 0.0;
// @ts-ignore
const heatmapValues = decoders.argmax2d(heatmapScores);
const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);
const scoresBuffer = allTensorBuffers[0];
const offsetsBuffer = allTensorBuffers[1];
const heatmapValuesBuffer = allTensorBuffers[2];
// @ts-ignore
const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, config.body.outputStride, offsetsBuffer);
const offsetPointsBuffer = await offsetPoints.buffer();
// @ts-ignore
const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));
const instanceKeypoints = keypointConfidence.map((score, i) => {
totalScore += score;
@ -106,4 +96,3 @@ async function decodeSinglePose(heatmapScores, offsets, config) {
offsetPoints.dispose();
return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };
}
exports.decodeSinglePose = decodeSinglePose;

12
src/posenet/decoders.js → src/posenet/decoders.ts
View File

@ -1,7 +1,7 @@
import * as tf from '../../dist/tfjs.esm.js';
import * as kpt from './keypoints';
function getPointsConfidence(heatmapScores, heatMapCoords) {
export function getPointsConfidence(heatmapScores, heatMapCoords) {
const numKeypoints = heatMapCoords.shape[0];
const result = new Float32Array(numKeypoints);
for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {
@ -11,7 +11,6 @@ function getPointsConfidence(heatmapScores, heatMapCoords) {
}
return result;
}
exports.getPointsConfidence = getPointsConfidence;
function getOffsetPoint(y, x, keypoint, offsetsBuffer) {
return {
@ -20,7 +19,7 @@ function getOffsetPoint(y, x, keypoint, offsetsBuffer) {
};
}
function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {
export function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {
const result = [];
for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {
const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();
@ -31,12 +30,10 @@ function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {
}
return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);
}
exports.getOffsetVectors = getOffsetVectors;
function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {
export function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {
return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));
}
exports.getOffsetPoints = getOffsetPoints;
function mod(a, b) {
return tf.tidy(() => {
@ -45,7 +42,7 @@ function mod(a, b) {
});
}
function argmax2d(inputs) {
export function argmax2d(inputs) {
const [height, width, depth] = inputs.shape;
return tf.tidy(() => {
const reshaped = inputs.reshape([height * width, depth]);
@ -55,4 +52,3 @@ function argmax2d(inputs) {
return tf.concat([yCoords, xCoords], 1);
});
}
exports.argmax2d = argmax2d;

7
src/posenet/heapSort.js → src/posenet/heapSort.ts
View File

@ -2,7 +2,11 @@
function half(k) {
return Math.floor(k / 2);
}
class MaxHeap {
export class MaxHeap {
priorityQueue: any;
numberOfElements: number;
getElementValue: any;
constructor(maxSize, getElementValue) {
this.priorityQueue = new Array(maxSize);
this.numberOfElements = -1;
@ -69,4 +73,3 @@ class MaxHeap {
this.priorityQueue[j] = t;
}
}
exports.MaxHeap = MaxHeap;

12
src/posenet/keypoints.js → src/posenet/keypoints.ts
View File

@ -1,12 +1,12 @@
exports.partNames = [
export const partNames = [
'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',
'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',
'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',
];
exports.NUM_KEYPOINTS = exports.partNames.length;
export const NUM_KEYPOINTS = exports.partNames.length;
exports.partIds = exports.partNames.reduce((result, jointName, i) => {
export const partIds = exports.partNames.reduce((result, jointName, i) => {
result[jointName] = i;
return result;
}, {});
@ -19,9 +19,9 @@ const connectedPartNames = [
['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],
['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],
];
exports.connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([exports.partIds[jointNameA], exports.partIds[jointNameB]]));
export const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));
exports.poseChain = [
export const poseChain = [
['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],
['rightEye', 'rightEar'], ['nose', 'leftShoulder'],
['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],
@ -32,7 +32,7 @@ exports.poseChain = [
['rightKnee', 'rightAnkle'],
];
exports.partChannels = [
export const partChannels = [
'left_face',
'right_face',
'right_upper_leg_front',

4
src/posenet/modelBase.js → src/posenet/modelBase.ts
View File

@ -12,7 +12,8 @@ function nameOutputResultsResNet(results) {
return { offsets, heatmap, displacementFwd, displacementBwd };
}
class BaseModel {
export class BaseModel {
model: any;
constructor(model) {
this.model = model;
}
@ -37,4 +38,3 @@ class BaseModel {
this.model.dispose();
}
}
exports.BaseModel = BaseModel;

4
src/posenet/modelWeights.js → src/posenet/modelWeights.ts
View File

@ -1,4 +1,5 @@
class ModelWeights {
export class ModelWeights {
variables: any;
constructor(variables) {
this.variables = variables;
}
@ -23,4 +24,3 @@ class ModelWeights {
for (let i = 0; i < this.variables.length; i++) this.variables[i].dispose();
}
}
exports.ModelWeights = ModelWeights;

23
src/posenet/posenet.js
View File

@ -1,23 +0,0 @@
import * as modelPoseNet from './modelPoseNet';
import * as keypoints from './keypoints';
import * as util from './util';
// @ts-ignore
exports.load = modelPoseNet.load;
// @ts-ignore
exports.PoseNet = modelPoseNet.PoseNet;
exports.partChannels = keypoints.partChannels;
exports.partIds = keypoints.partIds;
exports.partNames = keypoints.partNames;
exports.poseChain = keypoints.poseChain;
// @ts-ignore
exports.getAdjacentKeyPoints = util.getAdjacentKeyPoints;
// @ts-ignore
exports.getBoundingBox = util.getBoundingBox;
// @ts-ignore
exports.getBoundingBoxPoints = util.getBoundingBoxPoints;
// @ts-ignore
exports.scaleAndFlipPoses = util.scaleAndFlipPoses;
// @ts-ignore
exports.scalePose = util.scalePose;

16
src/posenet/modelPoseNet.js → src/posenet/posenet.ts
View File

@ -1,4 +1,4 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
import * as modelBase from './modelBase';
import * as decodeMultiple from './decodeMultiple';
@ -9,15 +9,12 @@ async function estimateMultiple(input, res, config) {
return new Promise(async (resolve) => {
const height = input.shape[1];
const width = input.shape[2];
// @ts-ignore
const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);
const scoresBuffer = allTensorBuffers[0];
const offsetsBuffer = allTensorBuffers[1];
const displacementsFwdBuffer = allTensorBuffers[2];
const displacementsBwdBuffer = allTensorBuffers[3];
// @ts-ignore
const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config);
// @ts-ignore
const scaled = util.scaleAndFlipPoses(poses, [height, width], [config.body.inputSize, config.body.inputSize]);
resolve(scaled);
});
@ -27,22 +24,20 @@ async function estimateSingle(input, res, config) {
return new Promise(async (resolve) => {
const height = input.shape[1];
const width = input.shape[2];
// @ts-ignore
const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config);
const poses = [pose];
// @ts-ignore
const scaled = util.scaleAndFlipPoses(poses, [height, width], [config.body.inputSize, config.body.inputSize]);
resolve(scaled);
});
}
class PoseNet {
export class PoseNet {
baseModel: any;
constructor(model) {
this.baseModel = model;
}
async estimatePoses(input, config) {
// @ts-ignore
const resized = util.resizeTo(input, [config.body.inputSize, config.body.inputSize]);
const res = this.baseModel.predict(resized, config);
@ -61,13 +56,10 @@ class PoseNet {
this.baseModel.dispose();
}
}
exports.PoseNet = PoseNet;
async function load(config) {
export async function load(config) {
const model = await tf.loadGraphModel(config.body.modelPath);
// @ts-ignore
const mobilenet = new modelBase.BaseModel(model);
log(`load model: ${config.body.modelPath.match(/\/(.*)\./)[1]}`);
return new PoseNet(mobilenet);
}
exports.load = load;

23
src/posenet/util.js → src/posenet/util.ts
View File

@ -1,10 +1,10 @@
import * as kpt from './keypoints';
function eitherPointDoesntMeetConfidence(a, b, minConfidence) {
export function eitherPointDoesntMeetConfidence(a, b, minConfidence) {
return (a < minConfidence || b < minConfidence);
}
function getAdjacentKeyPoints(keypoints, minConfidence) {
export function getAdjacentKeyPoints(keypoints, minConfidence) {
return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {
if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {
return result;
@ -13,10 +13,9 @@ function getAdjacentKeyPoints(keypoints, minConfidence) {
return result;
}, []);
}
exports.getAdjacentKeyPoints = getAdjacentKeyPoints;
const { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;
function getBoundingBox(keypoints) {
export function getBoundingBox(keypoints) {
return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({
maxX: Math.max(maxX, x),
maxY: Math.max(maxY, y),
@ -29,20 +28,17 @@ function getBoundingBox(keypoints) {
minY: POSITIVE_INFINITY,
});
}
exports.getBoundingBox = getBoundingBox;
function getBoundingBoxPoints(keypoints) {
export function getBoundingBoxPoints(keypoints) {
const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);
return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];
}
exports.getBoundingBoxPoints = getBoundingBoxPoints;
async function toTensorBuffers3D(tensors) {
export async function toTensorBuffers3D(tensors) {
return Promise.all(tensors.map((tensor) => tensor.buffer()));
}
exports.toTensorBuffers3D = toTensorBuffers3D;
function scalePose(pose, scaleY, scaleX) {
export function scalePose(pose, scaleY, scaleX) {
return {
score: pose.score,
keypoints: pose.keypoints.map(({ score, part, position }) => ({
@ -52,18 +48,15 @@ function scalePose(pose, scaleY, scaleX) {
})),
};
}
exports.scalePose = scalePose;
function resizeTo(image, [targetH, targetW]) {
export function resizeTo(image, [targetH, targetW]) {
const input = image.squeeze(0);
const resized = input.resizeBilinear([targetH, targetW]);
input.dispose();
return resized;
}
exports.resizeTo = resizeTo;
function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {
export function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {
const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));
return scaledPoses;
}
exports.scaleAndFlipPoses = scaleAndFlipPoses;

21
src/posenet/vectors.js → src/posenet/vectors.ts
View File

@ -1,14 +1,13 @@
import * as kpt from './keypoints';
function getOffsetPoint(y, x, keypoint, offsets) {
export function getOffsetPoint(y, x, keypoint, offsets) {
return {
y: offsets.get(y, x, keypoint),
x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),
};
}
exports.getOffsetPoint = getOffsetPoint;
function getImageCoords(part, outputStride, offsets) {
export function getImageCoords(part, outputStride, offsets) {
const { heatmapY, heatmapX, id: keypoint } = part;
const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);
return {
@ -16,37 +15,31 @@ function getImageCoords(part, outputStride, offsets) {
y: part.heatmapY * outputStride + y,
};
}
exports.getImageCoords = getImageCoords;
function fillArray(element, size) {
export function fillArray(element, size) {
const result = new Array(size);
for (let i = 0; i < size; i++) {
result[i] = element;
}
return result;
}
exports.fillArray = fillArray;
function clamp(a, min, max) {
export function clamp(a, min, max) {
if (a < min) return min;
if (a > max) return max;
return a;
}
exports.clamp = clamp;
function squaredDistance(y1, x1, y2, x2) {
export function squaredDistance(y1, x1, y2, x2) {
const dy = y2 - y1;
const dx = x2 - x1;
return dy * dy + dx * dx;
}
exports.squaredDistance = squaredDistance;
function addVectors(a, b) {
export function addVectors(a, b) {
return { x: a.x + b.x, y: a.y + b.y };
}
exports.addVectors = addVectors;
function clampVector(a, min, max) {
export function clampVector(a, min, max) {
return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };
}
exports.clampVector = clampVector;

20
src/profile.js → src/profile.ts
View File

@ -1,26 +1,24 @@
import { log } from './log.js';
import { log } from './log';
const profileData = {};
export const data = {};
function profile(name, data) {
if (!data || !data.kernels) return;
export function run(name, raw) {
if (!raw || !raw.kernels) return;
const maxResults = 5;
const time = data.kernels
const time = raw.kernels
.filter((a) => a.kernelTimeMs > 0)
.reduce((a, b) => a += b.kernelTimeMs, 0);
const slowest = data.kernels
const slowest = raw.kernels
.map((a, i) => { a.id = i; return a; })
.filter((a) => a.kernelTimeMs > 0)
.sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);
const largest = data.kernels
const largest = raw.kernels
.map((a, i) => { a.id = i; return a; })
.filter((a) => a.totalBytesSnapshot > 0)
.sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);
if (slowest.length > maxResults) slowest.length = maxResults;
if (largest.length > maxResults) largest.length = maxResults;
const res = { newBytes: data.newBytes, newTensors: data.newTensors, peakBytes: data.peakBytes, numKernelOps: data.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };
profileData[name] = res;
const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };
data[name] = res;
log('Human profiler', name, res);
}
exports.run = profile;

0
src/sample.js → src/sample.ts
View File

2
src/tfjs/backend.js → src/tfjs/backend.ts
View File

@ -1,4 +1,4 @@
import { log } from '../log.js';
import { log } from '../log';
import * as tf from '../../dist/tfjs.esm.js';
export const config = {

0
src/tfjs/tf-browser.js → src/tfjs/tf-browser.ts
View File

0
src/tfjs/tf-node-gpu.js → src/tfjs/tf-node-gpu.ts
View File

0
src/tfjs/tf-node.js → src/tfjs/tf-node.ts
View File