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refactor draw and models namespaces

pull/356/head
Vladimir Mandic 2022-11-17 14:39:02 -05:00
parent 8fe34fd723
commit 8d9190a773
31 changed files with 1510 additions and 1462 deletions
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5
CHANGELOG.md
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@ -9,7 +9,10 @@
## Changelog
### **HEAD -> main** 2022/11/16 mandic00@live.com
### **HEAD -> main** 2022/11/17 mandic00@live.com
### **origin/main** 2022/11/16 mandic00@live.com
- added webcam id specification
- include external typedefs

12
README.md
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@ -68,7 +68,7 @@
- **Full** [[*Live*]](https://vladmandic.github.io/human/demo/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo): Main browser demo app that showcases all Human capabilities
- **Simple** [[*Live*]](https://vladmandic.github.io/human/demo/typescript/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/typescript): Simple demo in WebCam processing demo in TypeScript
- **Embedded** [[*Live*]](https://vladmandic.github.io/human/demo/video/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/video/index.html): Even simpler demo with tiny code embedded in HTML file
- **Face Match** [[*Live*]](https://vladmandic.github.io/human/demo/facematch/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/facematch): Extract faces from images, calculates face descriptors and simmilarities and matches them to known database
- **Face Match** [[*Live*]](https://vladmandic.github.io/human/demo/facematch/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/facematch): Extract faces from images, calculates face descriptors and similarities and matches them to known database
- **Face ID** [[*Live*]](https://vladmandic.github.io/human/demo/faceid/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/faceid): Runs multiple checks to validate webcam input before performing face match to faces in IndexDB
- **Multi-thread** [[*Live*]](https://vladmandic.github.io/human/demo/multithread/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/multithread): Runs each Human module in a separate web worker for highest possible performance
- **NextJS** [[*Live*]](https://vladmandic.github.io/human-next/out/index.html) [[*Details*]](https://github.com/vladmandic/human-next): Use Human with TypeScript, NextJS and ReactJS
@ -377,6 +377,16 @@ drawResults(); // start draw loop
And for even better results, you can run detection in a separate web worker thread
<br><hr><br>
## Detailed Usage
- [**Wiki Home**](https://github.com/vladmandic/human/wiki)
- [**List of all available methods, properies and namespaces**](https://github.com/vladmandic/human/wiki/Usage)
- [**TypeDoc API Specification - Main class**](https://vladmandic.github.io/human/typedoc/classes/Human.html)
- [**TypeDoc API Specification - Full**](https://vladmandic.github.io/human/typedoc/)
<br><hr><br>
## TypeDefs

11
TODO.md
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@ -80,6 +80,15 @@ Architecture:
- Upgrade to **TFJS 4.0** with **strong typing**
see [notes](https://github.com/vladmandic/human#typedefs) on how to use
- `TypeDef` refactoring
- Re-architect `human.models` namespace for better dynamic model handling
Added additional methods `load`, `list`, `loaded`, `reset`
- Add named export for improved bundler support when using non-default imports
- Support for `NodeJS` v19
- Support for **NodeJS v19**
- Upgrade to **TypeScript 4.9**
Breaking changes:
- Replaced `result.face[n].iris` with `result.face[n].distance`
- Replaced `human.getModelStats()` with `human.models.stats()`
- Moved `human.similarity`, `human.distance` and `human.match` to namespace `human.match.*`
- Obsolete `human.enhance()`
- Obsolete `human.gl`

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demo/faceid/index.js
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demo/faceid/index.js.map
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2
demo/faceid/index.ts
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@ -250,7 +250,7 @@ async function detectFace() {
}
const db = await indexDb.load();
const descriptors = db.map((rec) => rec.descriptor).filter((desc) => desc.length > 0);
const res = human.match(current.face.embedding, descriptors, matchOptions);
const res = human.match.find(current.face.embedding, descriptors, matchOptions);
current.record = db[res.index] || null;
if (current.record) {
log(`best match: ${current.record.name} | id: ${current.record.id} | similarity: ${Math.round(1000 * res.similarity) / 10}%`);

2
demo/facematch/README.md
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@ -11,7 +11,7 @@
## Browser Face Recognition Demo
- `demo/facematch`: Demo for Browsers that uses all face description and embedding features to
detect, extract and identify all faces plus calculate simmilarity between them
detect, extract and identify all faces plus calculate similarity between them
It highlights functionality such as:

16
demo/facematch/facematch.js
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@ -1,7 +1,7 @@
/**
* Human demo for browsers
*
* Demo for face descriptor analysis and face simmilarity analysis
* Demo for face descriptor analysis and face similarity analysis
*/
/** @type {Human} */
@ -70,6 +70,9 @@ async function SelectFaceCanvas(face) {
document.getElementById('orig').style.filter = 'blur(16px)';
if (face.tensor) {
title('Sorting Faces by Similarity');
const c = document.getElementById('orig');
await human.tf.browser.toPixels(face.tensor, c);
/*
const enhanced = human.enhance(face);
if (enhanced) {
const c = document.getElementById('orig');
@ -81,8 +84,9 @@ async function SelectFaceCanvas(face) {
ctx.font = 'small-caps 0.4rem "Lato"';
ctx.fillStyle = 'rgba(255, 255, 255, 1)';
}
*/
const arr = db.map((rec) => rec.embedding);
const res = await human.match(face.embedding, arr);
const res = await human.match.find(face.embedding, arr);
log('Match:', db[res.index].name);
const emotion = face.emotion[0] ? `${Math.round(100 * face.emotion[0].score)}% ${face.emotion[0].emotion}` : 'N/A';
document.getElementById('desc').innerHTML = `
@ -103,7 +107,7 @@ async function SelectFaceCanvas(face) {
for (const canvas of canvases) {
// calculate similarity from selected face to current one in the loop
const current = all[canvas.tag.sample][canvas.tag.face];
const similarity = human.similarity(face.embedding, current.embedding);
const similarity = human.match.similarity(face.embedding, current.embedding);
canvas.tag.similarity = similarity;
// get best match
// draw the canvas
@ -120,7 +124,7 @@ async function SelectFaceCanvas(face) {
ctx.font = 'small-caps 1rem "Lato"';
const start = human.now();
const arr = db.map((rec) => rec.embedding);
const res = await human.match(current.embedding, arr);
const res = await human.match.find(current.embedding, arr);
time += (human.now() - start);
if (res.similarity > minScore) ctx.fillText(`DB: ${(100 * res.similarity).toFixed(1)}% ${db[res.index].name}`, 4, canvas.height - 30);
}
@ -161,7 +165,7 @@ async function AddFaceCanvas(index, res, fileName) {
ctx.fillStyle = 'rgba(255, 255, 255, 1)';
ctx.fillText(`${res.face[i].age}y ${(100 * (res.face[i].genderScore || 0)).toFixed(1)}% ${res.face[i].gender}`, 4, canvas.height - 6);
const arr = db.map((rec) => rec.embedding);
const result = human.match(res.face[i].embedding, arr);
const result = human.match.find(res.face[i].embedding, arr);
ctx.font = 'small-caps 1rem "Lato"';
if (result.similarity && res.similarity > minScore) ctx.fillText(`${(100 * result.similarity).toFixed(1)}% ${db[result.index].name}`, 4, canvas.height - 30);
document.getElementById('faces').appendChild(canvas);
@ -256,7 +260,7 @@ async function main() {
title('');
log('Ready');
human.validate(userConfig);
human.similarity([], []);
human.match.similarity([], []);
}
window.onload = main;

14
demo/index.js
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@ -222,21 +222,13 @@ async function calcSimmilarity(result) {
compare.original = result;
log('setting face compare baseline:', result.face[0]);
if (result.face[0].tensor) {
const enhanced = human.enhance(result.face[0]);
if (enhanced) {
const c = document.getElementById('orig');
const squeeze = human.tf.squeeze(enhanced);
const norm = human.tf.div(squeeze, 255);
human.tf.browser.toPixels(norm, c);
human.tf.dispose(enhanced);
human.tf.dispose(squeeze);
human.tf.dispose(norm);
}
const c = document.getElementById('orig');
human.tf.browser.toPixels(result.face[0].tensor, c);
} else {
document.getElementById('compare-canvas').getContext('2d').drawImage(compare.original.canvas, 0, 0, 200, 200);
}
}
const similarity = human.similarity(compare.original.face[0].embedding, result.face[0].embedding);
const similarity = human.match.similarity(compare.original.face[0].embedding, result.face[0].embedding);
document.getElementById('similarity').innerText = `similarity: ${Math.trunc(1000 * similarity) / 10}%`;
}

4
demo/nodejs/README.md
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@ -82,7 +82,7 @@ node demo/nodejs/node.js
detector: { modelPath: 'handdetect.json' },
skeleton: { modelPath: 'handskeleton.json' }
},
object: { enabled: true, modelPath: 'mb3-centernet.json', minConfidence: 0.2, iouThreshold: 0.4, maxDetected: 10, skipFrames: 19 }
object: { enabled: true, modelPath: 'centernet.json', minConfidence: 0.2, iouThreshold: 0.4, maxDetected: 10, skipFrames: 19 }
}
08:52:15.673 Human: version: 2.0.0
08:52:15.674 Human: tfjs version: 3.6.0
@ -96,7 +96,7 @@ node demo/nodejs/node.js
08:52:15.847 Human: load model: file://models/handdetect.json
08:52:15.847 Human: load model: file://models/handskeleton.json
08:52:15.914 Human: load model: file://models/movenet-lightning.json
08:52:15.957 Human: load model: file://models/mb3-centernet.json
08:52:15.957 Human: load model: file://models/centernet.json
08:52:16.015 Human: load model: file://models/faceres.json
08:52:16.015 Human: tf engine state: 50796152 bytes 1318 tensors
2021-06-01 08:52:16 INFO: Loaded: [ 'face', 'movenet', 'handpose', 'emotion', 'centernet', 'faceres', [length]: 6 ]

2
demo/nodejs/node-similarity.js
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@ -57,7 +57,7 @@ async function main() {
if (!res1 || !res1.face || res1.face.length === 0 || !res2 || !res2.face || res2.face.length === 0) {
throw new Error('Could not detect face descriptors');
}
const similarity = human.similarity(res1.face[0].embedding, res2.face[0].embedding, { order: 2 });
const similarity = human.match.similarity(res1.face[0].embedding, res2.face[0].embedding, { order: 2 });
log.data('Similarity: ', similarity);
}

2
demo/segmentation/index.js
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@ -52,7 +52,7 @@ async function main() {
log('platform:', human.env.platform, '| agent:', human.env.agent);
await human.load(); // preload all models
log('backend:', human.tf.getBackend(), '| available:', human.env.backends);
log('models stats:', human.getModelStats());
log('models stats:', human.models.stats());
log('models loaded:', Object.values(human.models).filter((model) => model !== null).length);
await human.warmup(); // warmup function to initialize backend for future faster detection
const numTensors = human.tf.engine().state.numTensors;

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demo/typescript/index.js
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@ -4,100 +4,6 @@
author: <https://github.com/vladmandic>'
*/
// demo/typescript/index.ts
import * as H from "../../dist/human.esm.js";
var width = 1920;
var humanConfig = {
modelBasePath: "../../models",
filter: { enabled: true, equalization: false, flip: false, width },
face: { enabled: true, detector: { rotation: true }, mesh: { enabled: true }, attention: { enabled: false }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true }, antispoof: { enabled: true }, liveness: { enabled: true } },
body: { enabled: true },
hand: { enabled: false },
object: { enabled: false },
segmentation: { enabled: false },
gesture: { enabled: true }
};
var human = new H.Human(humanConfig);
human.env.perfadd = false;
human.draw.options.font = 'small-caps 18px "Lato"';
human.draw.options.lineHeight = 20;
var dom = {
video: document.getElementById("video"),
canvas: document.getElementById("canvas"),
log: document.getElementById("log"),
fps: document.getElementById("status"),
perf: document.getElementById("performance")
};
var timestamp = { detect: 0, draw: 0, tensors: 0, start: 0 };
var fps = { detectFPS: 0, drawFPS: 0, frames: 0, averageMs: 0 };
var log = (...msg) => {
dom.log.innerText += msg.join(" ") + "\n";
console.log(...msg);
};
var status = (msg) => dom.fps.innerText = msg;
var perf = (msg) => dom.perf.innerText = "tensors:" + human.tf.memory().numTensors.toString() + " | performance: " + JSON.stringify(msg).replace(/"|{|}/g, "").replace(/,/g, " | ");
async function detectionLoop() {
if (!dom.video.paused) {
if (timestamp.start === 0)
timestamp.start = human.now();
await human.detect(dom.video);
const tensors = human.tf.memory().numTensors;
if (tensors - timestamp.tensors !== 0)
log("allocated tensors:", tensors - timestamp.tensors);
timestamp.tensors = tensors;
fps.detectFPS = Math.round(1e3 * 1e3 / (human.now() - timestamp.detect)) / 1e3;
fps.frames++;
fps.averageMs = Math.round(1e3 * (human.now() - timestamp.start) / fps.frames) / 1e3;
if (fps.frames % 100 === 0 && !dom.video.paused)
log("performance", { ...fps, tensors: timestamp.tensors });
}
timestamp.detect = human.now();
requestAnimationFrame(detectionLoop);
}
async function drawLoop() {
var _a, _b, _c;
if (!dom.video.paused) {
const interpolated = human.next(human.result);
const processed = await human.image(dom.video);
human.draw.canvas(processed.canvas, dom.canvas);
const opt = { bodyLabels: `person confidence [score] and ${(_c = (_b = (_a = human.result) == null ? void 0 : _a.body) == null ? void 0 : _b[0]) == null ? void 0 : _c.keypoints.length} keypoints` };
await human.draw.all(dom.canvas, interpolated, opt);
perf(interpolated.performance);
}
const now = human.now();
fps.drawFPS = Math.round(1e3 * 1e3 / (now - timestamp.draw)) / 1e3;
timestamp.draw = now;
status(dom.video.paused ? "paused" : `fps: ${fps.detectFPS.toFixed(1).padStart(5, " ")} detect | ${fps.drawFPS.toFixed(1).padStart(5, " ")} draw`);
setTimeout(drawLoop, 30);
}
async function webCam() {
const devices = await human.webcam.enumerate();
const id = devices[0].deviceId;
await human.webcam.start({ element: dom.video, crop: true, width, id });
dom.canvas.width = human.webcam.width;
dom.canvas.height = human.webcam.height;
dom.canvas.onclick = async () => {
if (human.webcam.paused)
await human.webcam.play();
else
human.webcam.pause();
};
}
async function main() {
log("human version:", human.version, "| tfjs version:", human.tf.version["tfjs-core"]);
log("platform:", human.env.platform, "| agent:", human.env.agent);
status("loading...");
await human.load();
log("backend:", human.tf.getBackend(), "| available:", human.env.backends);
log("models stats:", human.getModelStats());
log("models loaded:", Object.values(human.models).filter((model) => model !== null).length);
log("environment", human.env);
status("initializing...");
await human.warmup();
await webCam();
await detectionLoop();
await drawLoop();
}
window.onload = main;
import*as m from"../../dist/human.esm.js";var f=1920,b={modelBasePath:"../../models",filter:{enabled:!0,equalization:!1,flip:!1,width:f},face:{enabled:!0,detector:{rotation:!0},mesh:{enabled:!0},attention:{enabled:!1},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0},antispoof:{enabled:!0},liveness:{enabled:!0}},body:{enabled:!0},hand:{enabled:!1},object:{enabled:!1},segmentation:{enabled:!1},gesture:{enabled:!0}},e=new m.Human(b);e.env.perfadd=!1;e.draw.options.font='small-caps 18px "Lato"';e.draw.options.lineHeight=20;var a={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},n={detect:0,draw:0,tensors:0,start:0},s={detectFPS:0,drawFPS:0,frames:0,averageMs:0},o=(...t)=>{a.log.innerText+=t.join(" ")+`
`,console.log(...t)},r=t=>a.fps.innerText=t,g=t=>a.perf.innerText="tensors:"+e.tf.memory().numTensors.toString()+" | performance: "+JSON.stringify(t).replace(/"|{|}/g,"").replace(/,/g," | ");async function u(){if(!a.video.paused){n.start===0&&(n.start=e.now()),await e.detect(a.video);let t=e.tf.memory().numTensors;t-n.tensors!==0&&o("allocated tensors:",t-n.tensors),n.tensors=t,s.detectFPS=Math.round(1e3*1e3/(e.now()-n.detect))/1e3,s.frames++,s.averageMs=Math.round(1e3*(e.now()-n.start)/s.frames)/1e3,s.frames%100===0&&!a.video.paused&&o("performance",{...s,tensors:n.tensors})}n.detect=e.now(),requestAnimationFrame(u)}async function p(){var d,i,c;if(!a.video.paused){let l=e.next(e.result),w=await e.image(a.video);e.draw.canvas(w.canvas,a.canvas);let v={bodyLabels:`person confidence [score] and ${(c=(i=(d=e.result)==null?void 0:d.body)==null?void 0:i[0])==null?void 0:c.keypoints.length} keypoints`};await e.draw.all(a.canvas,l,v),g(l.performance)}let t=e.now();s.drawFPS=Math.round(1e3*1e3/(t-n.draw))/1e3,n.draw=t,r(a.video.paused?"paused":`fps: ${s.detectFPS.toFixed(1).padStart(5," ")} detect | ${s.drawFPS.toFixed(1).padStart(5," ")} draw`),setTimeout(p,30)}async function h(){let d=(await e.webcam.enumerate())[0].deviceId;await e.webcam.start({element:a.video,crop:!0,width:f,id:d}),a.canvas.width=e.webcam.width,a.canvas.height=e.webcam.height,a.canvas.onclick=async()=>{e.webcam.paused?await e.webcam.play():e.webcam.pause()}}async function y(){o("human version:",e.version,"| tfjs version:",e.tf.version["tfjs-core"]),o("platform:",e.env.platform,"| agent:",e.env.agent),r("loading..."),await e.load(),o("backend:",e.tf.getBackend(),"| available:",e.env.backends),o("models stats:",e.models.stats()),o("models loaded:",Object.values(e.models).filter(t=>t!==null).length),o("environment",e.env),r("initializing..."),await e.warmup(),await h(),await u(),await p()}window.onload=y;
//# sourceMappingURL=index.js.map

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demo/typescript/index.js.map
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2
demo/typescript/index.ts
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@ -100,7 +100,7 @@ async function main() { // main entry point
status('loading...');
await human.load(); // preload all models
log('backend:', human.tf.getBackend(), '| available:', human.env.backends);
log('models stats:', human.getModelStats());
log('models stats:', human.models.stats());
log('models loaded:', Object.values(human.models).filter((model) => model !== null).length);
log('environment', human.env);
status('initializing...');

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models/centernet.bin Normal file
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models/centernet.json Normal file
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2
models/models.json
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@ -1,6 +1,7 @@
{
"antispoof": 853098,
"blazeface": 538928,
"centernet": 4030290,
"emotion": 820516,
"facemesh": 1477958,
"faceres": 6978814,
@ -8,7 +9,6 @@
"handtrack": 2964837,
"iris": 2599092,
"liveness": 592976,
"mb3-centernet": 4030290,
"models": 0,
"movenet-lightning": 4650216,
"age": 161240,

2
src/config.ts
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@ -449,7 +449,7 @@ const config: Config = {
},
object: {
enabled: false,
modelPath: 'mb3-centernet.json',
modelPath: 'centernet.json',
minConfidence: 0.2,
iouThreshold: 0.4,
maxDetected: 10,

2
src/face/faceres.ts
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@ -2,7 +2,7 @@
* FaceRes model implementation
*
* Returns Age, Gender, Descriptor
* Implements Face simmilarity function
* Implements Face similarity function
*
* Based on: [**HSE-FaceRes**](https://github.com/HSE-asavchenko/HSE_FaceRec_tf)
*/

62
src/human.ts
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@ -22,11 +22,9 @@ import * as centernet from './object/centernet';
import * as efficientpose from './body/efficientpose';
import * as face from './face/face';
import * as facemesh from './face/facemesh';
import * as faceres from './face/faceres';
import * as gesture from './gesture/gesture';
import * as handpose from './hand/handpose';
import * as handtrack from './hand/handtrack';
import * as humangl from './tfjs/humangl';
import * as image from './image/image';
import * as interpolate from './util/interpolate';
import * as meet from './segmentation/meet';
@ -41,7 +39,7 @@ import * as selfie from './segmentation/selfie';
import * as warmups from './warmup';
// type definitions
import { Input, DrawOptions, Config, Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, PersonResult, AnyCanvas, emptyResult } from './exports';
import { Input, DrawOptions, Config, Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, AnyCanvas, emptyResult } from './exports';
import type { Tensor, Tensor4D } from './tfjs/types';
// type exports
export * from './exports';
@ -94,7 +92,15 @@ export class Human {
* - options: are global settings for all draw operations, can be overriden for each draw method {@link DrawOptions}
* - face, body, hand, gesture, object, person: draws detected results as overlays on canvas
*/
draw: { canvas: typeof draw.canvas, face: typeof draw.face, body: typeof draw.body, hand: typeof draw.hand, gesture: typeof draw.gesture, object: typeof draw.object, person: typeof draw.person, all: typeof draw.all, options: DrawOptions };
// draw: { canvas: typeof draw.canvas, face: typeof draw.face, body: typeof draw.body, hand: typeof draw.hand, gesture: typeof draw.gesture, object: typeof draw.object, person: typeof draw.person, all: typeof draw.all, options: DrawOptions };
draw: typeof draw = draw;
/** Face Matching
* - similarity: compare two face descriptors and return similarity index
* - distance: compare two face descriptors and return raw calculated differences
* - find: compare face descriptor to array of face descriptors and return best match
*/
match: typeof match = match;
/** Currently loaded models
* @internal
@ -121,8 +127,6 @@ export class Human {
#numTensors: number;
#analyzeMemoryLeaks: boolean;
#checkSanity: boolean;
/** WebGL debug info */
gl: Record<string, unknown>;
// definition end
/** Constructor for **Human** library that is futher used for all operations
@ -153,28 +157,15 @@ export class Human {
this.performance = {};
this.events = (typeof EventTarget !== 'undefined') ? new EventTarget() : undefined;
// object that contains all initialized models
this.models = new models.Models();
this.models = new models.Models(this);
// reexport draw methods
draw.init();
this.draw = {
options: draw.options,
canvas: (input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) => draw.canvas(input, output),
face: (output: AnyCanvas, result: FaceResult[], options?: Partial<DrawOptions>) => draw.face(output, result, options),
body: (output: AnyCanvas, result: BodyResult[], options?: Partial<DrawOptions>) => draw.body(output, result, options),
hand: (output: AnyCanvas, result: HandResult[], options?: Partial<DrawOptions>) => draw.hand(output, result, options),
gesture: (output: AnyCanvas, result: GestureResult[], options?: Partial<DrawOptions>) => draw.gesture(output, result, options),
object: (output: AnyCanvas, result: ObjectResult[], options?: Partial<DrawOptions>) => draw.object(output, result, options),
person: (output: AnyCanvas, result: PersonResult[], options?: Partial<DrawOptions>) => draw.person(output, result, options),
all: (output: AnyCanvas, result: Result, options?: Partial<DrawOptions>) => draw.all(output, result, options),
};
this.result = emptyResult();
// export access to image processing
this.process = { tensor: null, canvas: null };
// export raw access to underlying models
this.faceTriangulation = facemesh.triangulation;
this.faceUVMap = facemesh.uvmap;
// set gl info
this.gl = humangl.config;
// init model validation
models.validateModel(this, null, '');
// include platform info
@ -227,18 +218,6 @@ export class Human {
return msgs;
}
/** Check model for invalid kernel ops for current backend */
check() {
return models.validate(this);
}
/** Exports face matching methods {@link match#similarity} */
public similarity = match.similarity;
/** Exports face matching methods {@link match#distance} */
public distance = match.distance;
/** Exports face matching methods {@link match#match} */
public match = match.match;
/** Utility wrapper for performance.now() */
now(): number { // eslint-disable-line class-methods-use-this
return now();
@ -273,16 +252,7 @@ export class Human {
return tensor;
}
/** Enhance method performs additional enhacements to face image previously detected for futher processing
*
* @param input - Tensor as provided in human.result.face[n].tensor
* @returns Tensor
*/
enhance(input: Tensor): Tensor | null { // eslint-disable-line class-methods-use-this
return faceres.enhance(input);
}
/** Compare two input tensors for pixel simmilarity
/** Compare two input tensors for pixel similarity
* - use `human.image` to process any valid input and get a tensor that can be used for compare
* - when passing manually generated tensors:
* - both input tensors must be in format [1, height, width, 3]
@ -325,18 +295,17 @@ export class Human {
await tf.ready();
if (this.env.browser) {
if (this.config.debug) log('configuration:', this.config);
// @ts-ignore private property
if (this.config.debug) log('tf flags:', this.tf.ENV.flags);
}
}
await models.load(this); // actually loads models
await this.models.load(); // actually loads models
if (this.env.initial && this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors'); // print memory stats on first run
this.env.initial = false;
const loaded = Object.values(this.models).filter((model) => model).length;
if (loaded !== count) { // number of loaded models changed
models.validate(this); // validate kernel ops used by model against current backend
this.models.validate(); // validate kernel ops used by model against current backend
this.emit('load');
}
@ -359,9 +328,6 @@ export class Human {
return interpolate.calc(result, this.config);
}
/** get model loading/loaded stats */
getModelStats(): models.ModelStats { return models.getModelStats(this); }
/** Warmup method pre-initializes all configured models for faster inference
* - can take significant time on startup
* - only used for `webgl` and `humangl` backends

259
src/models.ts
View File

@ -31,136 +31,10 @@ import { modelStats, ModelInfo } from './tfjs/load';
import type { GraphModel } from './tfjs/types';
import type { Human } from './human';
/** Instances of all possible TFJS Graph Models used by Human
* - loaded as needed based on configuration
* - initialized explictly with `human.load()` method
* - initialized implicity on first call to `human.detect()`
* - each model can be `null` if not loaded, instance of `GraphModel` if loaded or `Promise` if loading
*/
export class Models {
ssrnetage: null | GraphModel | Promise<GraphModel> = null;
gear: null | GraphModel | Promise<GraphModel> = null;
blazeposedetect: null | GraphModel | Promise<GraphModel> = null;
blazepose: null | GraphModel | Promise<GraphModel> = null;
centernet: null | GraphModel | Promise<GraphModel> = null;
efficientpose: null | GraphModel | Promise<GraphModel> = null;
mobilefacenet: null | GraphModel | Promise<GraphModel> = null;
insightface: null | GraphModel | Promise<GraphModel> = null;
emotion: null | GraphModel | Promise<GraphModel> = null;
facedetect: null | GraphModel | Promise<GraphModel> = null;
faceiris: null | GraphModel | Promise<GraphModel> = null;
facemesh: null | GraphModel | Promise<GraphModel> = null;
faceres: null | GraphModel | Promise<GraphModel> = null;
ssrnetgender: null | GraphModel | Promise<GraphModel> = null;
handpose: null | GraphModel | Promise<GraphModel> = null;
handskeleton: null | GraphModel | Promise<GraphModel> = null;
handtrack: null | GraphModel | Promise<GraphModel> = null;
liveness: null | GraphModel | Promise<GraphModel> = null;
meet: null | GraphModel | Promise<GraphModel> = null;
movenet: null | GraphModel | Promise<GraphModel> = null;
nanodet: null | GraphModel | Promise<GraphModel> = null;
posenet: null | GraphModel | Promise<GraphModel> = null;
selfie: null | GraphModel | Promise<GraphModel> = null;
rvm: null | GraphModel | Promise<GraphModel> = null;
antispoof: null | GraphModel | Promise<GraphModel> = null;
}
/** structure that holds global stats for currently loaded models */
export interface ModelStats {
numLoadedModels: number,
numDefinedModels: number,
percentageLoaded: number,
totalSizeFromManifest: number,
totalSizeWeights: number,
totalSizeLoading: number,
totalSizeEnabled: undefined,
modelStats: ModelInfo[],
}
let instance: Human;
export const getModelStats = (currentInstance: Human): ModelStats => {
if (currentInstance) instance = currentInstance;
if (!instance) log('instance not registred');
let totalSizeFromManifest = 0;
let totalSizeWeights = 0;
let totalSizeLoading = 0;
for (const m of Object.values(modelStats)) {
totalSizeFromManifest += m.sizeFromManifest;
totalSizeWeights += m.sizeLoadedWeights;
totalSizeLoading += m.sizeDesired;
}
const percentageLoaded = totalSizeLoading > 0 ? totalSizeWeights / totalSizeLoading : 0;
return {
numLoadedModels: Object.values(modelStats).length,
numDefinedModels: Object.keys(instance.models).length,
percentageLoaded,
totalSizeFromManifest,
totalSizeWeights,
totalSizeLoading,
totalSizeEnabled: undefined,
modelStats: Object.values(modelStats),
};
};
export function reset(currentInstance: Human): void {
if (currentInstance) instance = currentInstance;
// if (instance.config.debug) log('resetting loaded models');
for (const model of Object.keys(instance.models)) instance.models[model as keyof Models] = null;
}
/** Load method preloads all instance.configured models on-demand */
export async function load(currentInstance: Human): Promise<void> {
if (currentInstance) instance = currentInstance;
if (!instance) log('instance not registred');
if (env.initial) reset(instance);
if (instance.config.hand.enabled) { // handpose model is a combo that must be loaded as a whole
if (!instance.models.handpose && instance.config.hand.detector?.modelPath?.includes('handdetect')) {
[instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);
}
if (!instance.models.handskeleton && instance.config.hand.landmarks && instance.config.hand.detector?.modelPath?.includes('handdetect')) {
[instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);
}
}
if (instance.config.body.enabled && !instance.models.blazepose && instance.config.body.modelPath?.includes('blazepose')) instance.models.blazepose = blazepose.loadPose(instance.config);
if (instance.config.body.enabled && !instance.models.blazeposedetect && instance.config.body['detector'] && instance.config.body['detector'].modelPath) instance.models.blazeposedetect = blazepose.loadDetect(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && instance.config.body.modelPath?.includes('efficientpose')) instance.models.efficientpose = efficientpose.load(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && instance.config.body.modelPath?.includes('movenet')) instance.models.movenet = movenet.load(instance.config);
if (instance.config.body.enabled && !instance.models.posenet && instance.config.body.modelPath?.includes('posenet')) instance.models.posenet = posenet.load(instance.config);
if (instance.config.face.enabled && !instance.models.facedetect) instance.models.facedetect = blazeface.load(instance.config);
if (instance.config.face.enabled && instance.config.face.antispoof?.enabled && !instance.models.antispoof) instance.models.antispoof = antispoof.load(instance.config);
if (instance.config.face.enabled && instance.config.face.liveness?.enabled && !instance.models.liveness) instance.models.liveness = liveness.load(instance.config);
if (instance.config.face.enabled && instance.config.face.description?.enabled && !instance.models.faceres) instance.models.faceres = faceres.load(instance.config);
if (instance.config.face.enabled && instance.config.face.emotion?.enabled && !instance.models.emotion) instance.models.emotion = emotion.load(instance.config);
if (instance.config.face.enabled && instance.config.face.iris?.enabled && !instance.config.face.attention?.enabled && !instance.models.faceiris) instance.models.faceiris = iris.load(instance.config);
if (instance.config.face.enabled && instance.config.face.mesh?.enabled && (!instance.models.facemesh)) instance.models.facemesh = facemesh.load(instance.config);
if (instance.config.face.enabled && instance.config.face['gear']?.enabled && !instance.models.gear) instance.models.gear = gear.load(instance.config);
if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetage) instance.models.ssrnetage = ssrnetAge.load(instance.config);
if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetgender) instance.models.ssrnetgender = ssrnetGender.load(instance.config);
if (instance.config.face.enabled && instance.config.face['mobilefacenet']?.enabled && !instance.models.mobilefacenet) instance.models.mobilefacenet = mobilefacenet.load(instance.config);
if (instance.config.face.enabled && instance.config.face['insightface']?.enabled && !instance.models.insightface) instance.models.insightface = insightface.load(instance.config);
if (instance.config.hand.enabled && !instance.models.handtrack && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handtrack = handtrack.loadDetect(instance.config);
if (instance.config.hand.enabled && instance.config.hand.landmarks && !instance.models.handskeleton && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handskeleton = handtrack.loadSkeleton(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && instance.config.object.modelPath?.includes('centernet')) instance.models.centernet = centernet.load(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && instance.config.object.modelPath?.includes('nanodet')) instance.models.nanodet = nanodet.load(instance.config);
if (instance.config.segmentation.enabled && !instance.models.selfie && instance.config.segmentation.modelPath?.includes('selfie')) instance.models.selfie = selfie.load(instance.config);
if (instance.config.segmentation.enabled && !instance.models.meet && instance.config.segmentation.modelPath?.includes('meet')) instance.models.meet = meet.load(instance.config);
if (instance.config.segmentation.enabled && !instance.models.rvm && instance.config.segmentation.modelPath?.includes('rvm')) instance.models.rvm = rvm.load(instance.config);
// models are loaded in parallel asynchronously so lets wait until they are actually loaded
for await (const model of Object.keys(instance.models)) {
if (instance.models[model as keyof Models] && typeof instance.models[model as keyof Models] !== 'undefined') {
instance.models[model as keyof Models] = await instance.models[model as keyof Models];
}
}
}
export interface KernelOps { name: string, url: string, missing: string[], ops: string[] }
export function validateModel(currentInstance: Human | null, model: GraphModel | null, name: string): KernelOps | null {
export function validateModel(instance: Human | null, model: GraphModel | null, name: string): KernelOps | null {
if (!model) return null;
if (currentInstance) instance = currentInstance;
if (!instance) log('instance not registred');
if (!instance?.config?.validateModels) return null;
const simpleOps = ['const', 'placeholder', 'noop', 'pad', 'squeeze', 'add', 'sub', 'mul', 'div'];
const ignoreOps = ['biasadd', 'fusedbatchnormv3', 'matmul', 'switch', 'shape', 'merge', 'split', 'broadcastto'];
@ -193,15 +67,124 @@ export function validateModel(currentInstance: Human | null, model: GraphModel |
return missing.length > 0 ? { name, missing, ops, url } : null;
}
export function validate(currentInstance: Human): { name: string, missing: string[] }[] {
if (currentInstance) instance = currentInstance;
if (!instance) log('instance not registred');
const missing: KernelOps[] = [];
for (const defined of Object.keys(currentInstance.models)) {
const model: GraphModel | null = currentInstance.models[defined as keyof Models] as GraphModel | null;
if (!model) continue;
const res = validateModel(currentInstance, model, defined);
if (res) missing.push(res);
}
return missing;
/** structure that holds global stats for currently loaded models */
export interface ModelStats {
numLoadedModels: number,
numDefinedModels: number,
percentageLoaded: number,
totalSizeFromManifest: number,
totalSizeWeights: number,
totalSizeLoading: number,
modelStats: ModelInfo[],
}
/** Models class used by Human
* - models: record of all GraphModels
* - list: returns list of configured models with their stats
* - loaded: returns array of loaded models
* - reset: unloads all models
* - validate: checks loaded models for valid kernel ops vs current backend
* - stats: live detailed model stats that can be checked during model load phase
*/
export class Models {
instance: Human;
models: Record<string, null | GraphModel>;
constructor(currentInstance: Human) {
this.models = {};
this.instance = currentInstance;
}
stats(): ModelStats {
let totalSizeFromManifest = 0;
let totalSizeWeights = 0;
let totalSizeLoading = 0;
for (const m of Object.values(modelStats)) {
totalSizeFromManifest += m.sizeFromManifest;
totalSizeWeights += m.sizeLoadedWeights;
totalSizeLoading += m.sizeDesired;
}
const percentageLoaded = totalSizeLoading > 0 ? totalSizeWeights / totalSizeLoading : 0;
return {
numLoadedModels: Object.values(modelStats).length,
numDefinedModels: Object.keys(this.models).length,
percentageLoaded,
totalSizeFromManifest,
totalSizeWeights,
totalSizeLoading,
modelStats: Object.values(modelStats),
};
}
reset(): void {
for (const model of Object.keys(this.models)) this.models[model] = null;
}
async load(): Promise<void> {
if (env.initial) this.reset();
const m: Record<string, null | GraphModel | Promise<GraphModel>> = {};
// face main models
m.blazeface = (this.instance.config.face.enabled && !this.models.blazeface) ? blazeface.load(this.instance.config) : null;
m.antispoof = (this.instance.config.face.enabled && this.instance.config.face.antispoof?.enabled && !this.models.antispoof) ? antispoof.load(this.instance.config) : null;
m.liveness = (this.instance.config.face.enabled && this.instance.config.face.liveness?.enabled && !this.models.liveness) ? liveness.load(this.instance.config) : null;
m.faceres = (this.instance.config.face.enabled && this.instance.config.face.description?.enabled && !this.models.faceres) ? faceres.load(this.instance.config) : null;
m.emotion = (this.instance.config.face.enabled && this.instance.config.face.emotion?.enabled && !this.models.emotion) ? emotion.load(this.instance.config) : null;
m.iris = (this.instance.config.face.enabled && this.instance.config.face.iris?.enabled && !this.instance.config.face.attention?.enabled && !this.models.iris) ? iris.load(this.instance.config) : null;
m.facemesh = (this.instance.config.face.enabled && this.instance.config.face.mesh?.enabled && (!this.models.facemesh)) ? facemesh.load(this.instance.config) : null;
// face alternatives
m.gear = (this.instance.config.face.enabled && this.instance.config.face['gear']?.enabled && !this.models.gear) ? gear.load(this.instance.config) : null;
m.ssrnetage = (this.instance.config.face.enabled && this.instance.config.face['ssrnet']?.enabled && !this.models.ssrnetage) ? ssrnetAge.load(this.instance.config) : null;
m.ssrnetgender = (this.instance.config.face.enabled && this.instance.config.face['ssrnet']?.enabled && !this.models.ssrnetgender) ? ssrnetGender.load(this.instance.config) : null;
m.mobilefacenet = (this.instance.config.face.enabled && this.instance.config.face['mobilefacenet']?.enabled && !this.models.mobilefacenet) ? mobilefacenet.load(this.instance.config) : null;
m.insightface = (this.instance.config.face.enabled && this.instance.config.face['insightface']?.enabled && !this.models.insightface) ? insightface.load(this.instance.config) : null;
// body alterinatives
m.blazepose = (this.instance.config.body.enabled && !this.models.blazepose && this.instance.config.body.modelPath?.includes('blazepose')) ? blazepose.loadPose(this.instance.config) : null;
m.blazeposedetect = (this.instance.config.body.enabled && !this.models.blazeposedetect && this.instance.config.body['detector'] && this.instance.config.body['detector'].modelPath) ? blazepose.loadDetect(this.instance.config) : null;
m.efficientpose = (this.instance.config.body.enabled && !this.models.efficientpose && this.instance.config.body.modelPath?.includes('efficientpose')) ? efficientpose.load(this.instance.config) : null;
m.movenet = (this.instance.config.body.enabled && !this.models.movenet && this.instance.config.body.modelPath?.includes('movenet')) ? movenet.load(this.instance.config) : null;
m.posenet = (this.instance.config.body.enabled && !this.models.posenet && this.instance.config.body.modelPath?.includes('posenet')) ? posenet.load(this.instance.config) : null;
// hand alternatives
m.handtrack = (this.instance.config.hand.enabled && !this.models.handtrack && this.instance.config.hand.detector?.modelPath?.includes('handtrack')) ? handtrack.loadDetect(this.instance.config) : null;
m.handskeleton = (this.instance.config.hand.enabled && this.instance.config.hand.landmarks && !this.models.handskeleton && this.instance.config.hand.detector?.modelPath?.includes('handtrack')) ? handtrack.loadSkeleton(this.instance.config) : null;
if (this.instance.config.hand.detector?.modelPath?.includes('handdetect')) [m.handpose, m.handskeleton] = (!this.models.handpose) ? await handpose.load(this.instance.config) : [null, null];
// object detection alternatives
m.centernet = (this.instance.config.object.enabled && !this.models.centernet && this.instance.config.object.modelPath?.includes('centernet')) ? centernet.load(this.instance.config) : null;
m.nanodet = (this.instance.config.object.enabled && !this.models.nanodet && this.instance.config.object.modelPath?.includes('nanodet')) ? nanodet.load(this.instance.config) : null;
// segmentation alternatives
m.selfie = (this.instance.config.segmentation.enabled && !this.models.selfie && this.instance.config.segmentation.modelPath?.includes('selfie')) ? selfie.load(this.instance.config) : null;
m.meet = (this.instance.config.segmentation.enabled && !this.models.meet && this.instance.config.segmentation.modelPath?.includes('meet')) ? meet.load(this.instance.config) : null;
m.rvm = (this.instance.config.segmentation.enabled && !this.models.rvm && this.instance.config.segmentation.modelPath?.includes('rvm')) ? rvm.load(this.instance.config) : null;
// models are loaded in parallel asynchronously so lets wait until they are actually loaded
await Promise.all([...Object.values(m)]);
for (const model of Object.keys(m)) this.models[model] = m[model] as GraphModel || this.models[model] || null; // only update actually loaded models
}
list() {
const models = Object.keys(this.models).map((model) => ({ name: model, loaded: (this.models[model] !== null), size: 0, url: this.models[model] ? this.models[model]?.['modelUrl'] : null }));
for (const m of models) {
const stats = Object.keys(modelStats).find((s) => s.startsWith(m.name));
if (!stats) continue;
m.size = modelStats[stats].sizeLoadedWeights;
m.url = modelStats[stats].url;
}
return models;
}
loaded() {
const list = this.list();
const loaded = list.filter((model) => model.loaded).map((model) => model.name);
return loaded;
}
validate(): { name: string, missing: string[] }[] {
const missing: KernelOps[] = [];
for (const defined of Object.keys(this.models)) {
const model: GraphModel | null = this.models[defined as keyof Models];
if (!model) continue;
const res = validateModel(this.instance, model, defined);
if (res) missing.push(res);
}
return missing;
}
}

3
src/tfjs/humangl.ts
View File

@ -4,7 +4,6 @@ import * as tf from 'dist/tfjs.esm.js';
import type { Human } from '../human';
import { log } from '../util/util';
import * as image from '../image/image';
import * as models from '../models';
import type { AnyCanvas } from '../exports';
export const config = {
@ -46,7 +45,7 @@ export function register(instance: Human): void {
if (instance.config.backend !== 'humangl') return;
if ((config.name in tf.engine().registry) && !config?.gl?.getParameter(config.gl.VERSION)) {
log('humangl error: backend invalid context');
models.reset(instance);
instance.models.reset();
/*
log('resetting humangl backend');
await tf.removeBackend(config.name);

5
src/tfjs/load.ts
View File

@ -18,6 +18,7 @@ export interface ModelInfo {
sizeDesired: number,
sizeFromManifest: number,
sizeLoadedWeights: number,
url: string,
}
export const modelStats: Record<string, ModelInfo> = {};
@ -45,6 +46,7 @@ export async function loadModel(modelPath: string | undefined): Promise<GraphMod
sizeLoadedWeights: 0,
sizeDesired: modelsDefs[shortModelName],
inCache: false,
url: '',
};
options.cacheSupported = (typeof indexedDB !== 'undefined'); // check if localStorage and indexedb are available
let cachedModels = {};
@ -54,8 +56,9 @@ export async function loadModel(modelPath: string | undefined): Promise<GraphMod
options.cacheSupported = false;
}
modelStats[shortModelName].inCache = (options.cacheSupported && options.cacheModels) && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache
modelStats[shortModelName].url = modelStats[shortModelName].inCache ? cachedModelName : modelUrl;
const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url: string, init?: RequestInit) => httpHandler(url, init) };
let model: GraphModel = new tf.GraphModel(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl
let model: GraphModel = new tf.GraphModel(modelStats[shortModelName].url, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl
let loaded = false;
try {
// @ts-ignore private function

6
src/warmup.ts
View File

@ -8,9 +8,9 @@ import * as sample from './sample';
import * as image from './image/image';
import * as backend from './tfjs/backend';
import { env } from './util/env';
import type { Config } from './config';
import { emptyResult, Result } from './result';
import { Human, models } from './human';
import type { Config } from './config';
import type { Human } from './human';
import type { Tensor, DataType } from './tfjs/types';
async function warmupBitmap(instance: Human): Promise<Result | undefined> {
@ -161,7 +161,7 @@ export async function warmup(instance: Human, userConfig?: Partial<Config>): Pro
return emptyResult();
}
return new Promise(async (resolve) => {
await models.load(instance);
await instance.models.load();
await runCompile(instance);
const res = await runInference(instance);
const t1 = now();

161
test/build.log
View File

@ -1,105 +1,56 @@
2022-11-17 10:11:23 DATA:  Build {"name":"@vladmandic/human","version":"3.0.0"}
2022-11-17 10:11:23 INFO:  Application: {"name":"@vladmandic/human","version":"3.0.0"}
2022-11-17 10:11:23 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true}
2022-11-17 10:11:23 INFO:  Toolchain: {"build":"0.7.14","esbuild":"0.15.14","typescript":"4.9.3","typedoc":"0.23.21","eslint":"8.27.0"}
2022-11-17 10:11:23 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]}
2022-11-17 10:11:23 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]}
2022-11-17 10:11:23 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1289,"outputBytes":361}
2022-11-17 10:11:23 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":569,"outputBytes":924}
2022-11-17 10:11:23 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":80,"inputBytes":673583,"outputBytes":317615}
2022-11-17 10:11:23 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":577,"outputBytes":928}
2022-11-17 10:11:23 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":80,"inputBytes":673587,"outputBytes":317619}
2022-11-17 10:11:23 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":665,"outputBytes":1876}
2022-11-17 10:11:23 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":80,"inputBytes":674535,"outputBytes":317730}
2022-11-17 10:11:23 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1375,"outputBytes":670}
2022-11-17 10:11:23 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":80,"inputBytes":673329,"outputBytes":316181}
2022-11-17 10:11:23 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":10,"inputBytes":1375,"outputBytes":1144900}
2022-11-17 10:11:23 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":80,"inputBytes":1817559,"outputBytes":1457643}
2022-11-17 10:11:23 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":80,"inputBytes":1817559,"outputBytes":1917209}
2022-11-17 10:11:27 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":15}
2022-11-17 10:11:29 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":77,"generated":true}
2022-11-17 10:11:29 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6136,"outputBytes":2914}
2022-11-17 10:11:29 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":17174,"outputBytes":9251}
2022-11-17 10:11:37 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":114,"errors":0,"warnings":0}
2022-11-17 10:11:37 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"}
2022-11-17 10:11:37 STATE: Copy: {"input":"node_modules/@vladmandic/tfjs/types/tfjs-core.d.ts","output":"types/tfjs-core.d.ts"}
2022-11-17 10:11:37 INFO:  Done...
2022-11-17 10:11:37 STATE: Copy: {"input":"node_modules/@vladmandic/tfjs/types/tfjs.d.ts","output":"types/tfjs.esm.d.ts"}
2022-11-17 10:11:37 STATE: Copy: {"input":"src/types/tsconfig.json","output":"types/tsconfig.json"}
2022-11-17 10:11:37 STATE: Copy: {"input":"src/types/eslint.json","output":"types/.eslintrc.json"}
2022-11-17 10:11:37 STATE: Copy: {"input":"src/types/tfjs.esm.d.ts","output":"dist/tfjs.esm.d.ts"}
2022-11-17 10:11:37 STATE: Filter: {"input":"types/tfjs-core.d.ts"}
2022-11-17 10:11:38 STATE: API-Extractor: {"succeeeded":true,"errors":0,"warnings":195}
2022-11-17 10:11:38 STATE: Filter: {"input":"types/human.d.ts"}
2022-11-17 10:11:38 STATE: Write: {"output":"dist/human.esm-nobundle.d.ts"}
2022-11-17 10:11:38 STATE: Write: {"output":"dist/human.esm.d.ts"}
2022-11-17 10:11:38 STATE: Write: {"output":"dist/human.d.ts"}
2022-11-17 10:11:38 STATE: Write: {"output":"dist/human.node-gpu.d.ts"}
2022-11-17 10:11:38 STATE: Write: {"output":"dist/human.node.d.ts"}
2022-11-17 10:11:38 STATE: Write: {"output":"dist/human.node-wasm.d.ts"}
2022-11-17 10:11:38 INFO:  Analyze models: {"folders":8,"result":"models/models.json"}
2022-11-17 10:11:38 STATE: Models {"folder":"./models","models":12}
2022-11-17 10:11:38 STATE: Models {"folder":"../human-models/models","models":43}
2022-11-17 10:11:38 STATE: Models {"folder":"../blazepose/model/","models":4}
2022-11-17 10:11:38 STATE: Models {"folder":"../anti-spoofing/model","models":1}
2022-11-17 10:11:38 STATE: Models {"folder":"../efficientpose/models","models":3}
2022-11-17 10:11:38 STATE: Models {"folder":"../insightface/models","models":5}
2022-11-17 10:11:38 STATE: Models {"folder":"../movenet/models","models":3}
2022-11-17 10:11:38 STATE: Models {"folder":"../nanodet/models","models":4}
2022-11-17 10:11:39 STATE: Models: {"count":58,"totalSize":386543911}
2022-11-17 10:11:39 INFO:  Human Build complete... {"logFile":"test/build.log"}
2022-11-17 10:16:08 INFO:  @vladmandic/human version 3.0.0
2022-11-17 10:16:08 INFO:  User: vlado Platform: linux Arch: x64 Node: v19.1.0
2022-11-17 10:16:08 INFO:  Application: {"name":"@vladmandic/human","version":"3.0.0"}
2022-11-17 10:16:08 INFO:  Environment: {"profile":"development","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true}
2022-11-17 10:16:08 INFO:  Toolchain: {"build":"0.7.14","esbuild":"0.15.14","typescript":"4.9.3","typedoc":"0.23.21","eslint":"8.27.0"}
2022-11-17 10:16:08 INFO:  Build: {"profile":"development","steps":["serve","watch","compile"]}
2022-11-17 10:16:08 STATE: WebServer: {"ssl":false,"port":8000,"root":"."}
2022-11-17 10:16:08 STATE: WebServer: {"ssl":true,"port":8001,"root":".","sslKey":"node_modules/@vladmandic/build/cert/https.key","sslCrt":"node_modules/@vladmandic/build/cert/https.crt"}
2022-11-17 10:16:08 STATE: Watch: {"locations":["src/**/*","tfjs/**/*","demo/**/*.ts"]}
2022-11-17 10:16:08 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1289,"outputBytes":1357}
2022-11-17 10:16:08 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1565,"outputBytes":1786}
2022-11-17 10:16:08 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":80,"inputBytes":674445,"outputBytes":507569}
2022-11-17 10:16:08 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1573,"outputBytes":1810}
2022-11-17 10:16:08 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":80,"inputBytes":674469,"outputBytes":507589}
2022-11-17 10:16:08 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1661,"outputBytes":1992}
2022-11-17 10:16:08 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":80,"inputBytes":674651,"outputBytes":507780}
2022-11-17 10:16:08 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2371,"outputBytes":923}
2022-11-17 10:16:08 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":80,"inputBytes":673582,"outputBytes":510177}
2022-11-17 10:16:09 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":10,"inputBytes":2371,"outputBytes":1144900}
2022-11-17 10:16:09 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":80,"inputBytes":1817559,"outputBytes":1457643}
2022-11-17 10:16:09 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":80,"inputBytes":1817559,"outputBytes":1917209}
2022-11-17 10:16:09 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6136,"outputBytes":4208}
2022-11-17 10:16:09 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":17567,"outputBytes":13914}
2022-11-17 10:16:09 INFO:  Listening...
2022-11-17 10:16:20 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":301,"url":"/demo/typescript","redirect":"/demo/typescript/index.html","remote":"::1"}
2022-11-17 10:16:20 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/html","size":1953,"url":"/demo/typescript/index.html","remote":"::1"}
2022-11-17 10:16:20 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/javascript","size":4208,"url":"/demo/typescript/index.js","remote":"::1"}
2022-11-17 10:16:22 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":301,"url":"/demo/faceid","redirect":"/demo/faceid/index.html","remote":"::1"}
2022-11-17 10:16:22 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/html","size":3415,"url":"/demo/faceid/index.html","remote":"::1"}
2022-11-17 10:16:22 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/javascript","size":13914,"url":"/demo/faceid/index.js","remote":"::1"}
2022-11-17 10:16:22 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/javascript","size":1917209,"url":"/dist/human.esm.js","remote":"::1"}
2022-11-17 10:16:22 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"font/woff2","size":181500,"url":"/assets/lato-light.woff2","remote":"::1"}
2022-11-17 10:16:22 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/manifest+json","size":304,"url":"/demo/manifest.webmanifest","remote":"::1"}
2022-11-17 10:16:22 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"image/png","size":142790,"url":"/assets/icon.png","remote":"::1"}
2022-11-17 10:16:23 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/manifest+json","size":304,"url":"/demo/manifest.webmanifest","remote":"::1"}
2022-11-17 10:16:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/octet-stream","size":28470,"url":"/demo/faceid/index.js.map","remote":"::1"}
2022-11-17 10:16:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/octet-stream","size":3385692,"url":"/dist/human.esm.js.map","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/html","size":3415,"url":"/demo/faceid/index.html","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/javascript","size":13914,"url":"/demo/faceid/index.js","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"font/woff2","size":181500,"url":"/assets/lato-light.woff2","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/javascript","size":1917209,"url":"/dist/human.esm.js","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/octet-stream","size":28470,"url":"/demo/faceid/index.js.map","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/octet-stream","size":3385692,"url":"/dist/human.esm.js.map","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"image/x-icon","size":261950,"url":"/favicon.ico","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/manifest+json","size":304,"url":"/demo/manifest.webmanifest","remote":"::1"}
2022-11-17 10:16:39 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"image/png","size":142790,"url":"/assets/icon.png","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":301,"url":"/demo/typescript","redirect":"/demo/typescript/index.html","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/html","size":1953,"url":"/demo/typescript/index.html","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/javascript","size":4208,"url":"/demo/typescript/index.js","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"font/woff2","size":181500,"url":"/assets/lato-light.woff2","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"text/javascript","size":1917209,"url":"/dist/human.esm.js","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/octet-stream","size":9470,"url":"/demo/typescript/index.js.map","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/octet-stream","size":3385692,"url":"/dist/human.esm.js.map","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"application/manifest+json","size":304,"url":"/demo/manifest.webmanifest","remote":"::1"}
2022-11-17 10:17:25 DATA:  HTTPS: {"method":"GET","ver":"2.0","status":200,"mime":"image/png","size":142790,"url":"/assets/icon.png","remote":"::1"}
2022-11-17 14:37:08 DATA:  Build {"name":"@vladmandic/human","version":"3.0.0"}
2022-11-17 14:37:08 INFO:  Application: {"name":"@vladmandic/human","version":"3.0.0"}
2022-11-17 14:37:08 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true}
2022-11-17 14:37:08 INFO:  Toolchain: {"build":"0.7.14","esbuild":"0.15.14","typescript":"4.9.3","typedoc":"0.23.21","eslint":"8.27.0"}
2022-11-17 14:37:08 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]}
2022-11-17 14:37:08 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]}
2022-11-17 14:37:08 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1289,"outputBytes":361}
2022-11-17 14:37:08 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":569,"outputBytes":924}
2022-11-17 14:37:08 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":80,"inputBytes":670179,"outputBytes":317460}
2022-11-17 14:37:08 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":577,"outputBytes":928}
2022-11-17 14:37:08 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":80,"inputBytes":670183,"outputBytes":317464}
2022-11-17 14:37:08 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":665,"outputBytes":1876}
2022-11-17 14:37:08 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":80,"inputBytes":671131,"outputBytes":317575}
2022-11-17 14:37:08 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1375,"outputBytes":670}
2022-11-17 14:37:08 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":80,"inputBytes":669925,"outputBytes":316039}
2022-11-17 14:37:08 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":10,"inputBytes":1375,"outputBytes":1144900}
2022-11-17 14:37:08 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":80,"inputBytes":1814155,"outputBytes":1457353}
2022-11-17 14:37:09 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":80,"inputBytes":1814155,"outputBytes":1914737}
2022-11-17 14:37:12 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":15}
2022-11-17 14:37:14 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":77,"generated":true}
2022-11-17 14:37:14 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6135,"outputBytes":2913}
2022-11-17 14:37:14 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":17572,"outputBytes":9456}
2022-11-17 14:37:22 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":114,"errors":0,"warnings":1}
2022-11-17 14:37:22 WARN: 
/home/vlado/dev/human/src/human.ts
42:17 warning 'DrawOptions' is defined but never used @typescript-eslint/no-unused-vars
✖ 1 problem (0 errors, 1 warning)
2022-11-17 14:37:22 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"}
2022-11-17 14:37:22 STATE: Copy: {"input":"node_modules/@vladmandic/tfjs/types/tfjs-core.d.ts","output":"types/tfjs-core.d.ts"}
2022-11-17 14:37:22 INFO:  Done...
2022-11-17 14:37:22 STATE: Copy: {"input":"node_modules/@vladmandic/tfjs/types/tfjs.d.ts","output":"types/tfjs.esm.d.ts"}
2022-11-17 14:37:22 STATE: Copy: {"input":"src/types/tsconfig.json","output":"types/tsconfig.json"}
2022-11-17 14:37:22 STATE: Copy: {"input":"src/types/eslint.json","output":"types/.eslintrc.json"}
2022-11-17 14:37:22 STATE: Copy: {"input":"src/types/tfjs.esm.d.ts","output":"dist/tfjs.esm.d.ts"}
2022-11-17 14:37:22 STATE: Filter: {"input":"types/tfjs-core.d.ts"}
2022-11-17 14:37:23 STATE: API-Extractor: {"succeeeded":true,"errors":0,"warnings":195}
2022-11-17 14:37:23 STATE: Filter: {"input":"types/human.d.ts"}
2022-11-17 14:37:23 STATE: Write: {"output":"dist/human.esm-nobundle.d.ts"}
2022-11-17 14:37:23 STATE: Write: {"output":"dist/human.esm.d.ts"}
2022-11-17 14:37:23 STATE: Write: {"output":"dist/human.d.ts"}
2022-11-17 14:37:23 STATE: Write: {"output":"dist/human.node-gpu.d.ts"}
2022-11-17 14:37:23 STATE: Write: {"output":"dist/human.node.d.ts"}
2022-11-17 14:37:23 STATE: Write: {"output":"dist/human.node-wasm.d.ts"}
2022-11-17 14:37:23 INFO:  Analyze models: {"folders":8,"result":"models/models.json"}
2022-11-17 14:37:23 STATE: Models {"folder":"./models","models":12}
2022-11-17 14:37:23 STATE: Models {"folder":"../human-models/models","models":43}
2022-11-17 14:37:23 STATE: Models {"folder":"../blazepose/model/","models":4}
2022-11-17 14:37:23 STATE: Models {"folder":"../anti-spoofing/model","models":1}
2022-11-17 14:37:23 STATE: Models {"folder":"../efficientpose/models","models":3}
2022-11-17 14:37:23 STATE: Models {"folder":"../insightface/models","models":5}
2022-11-17 14:37:23 STATE: Models {"folder":"../movenet/models","models":3}
2022-11-17 14:37:23 STATE: Models {"folder":"../nanodet/models","models":4}
2022-11-17 14:37:24 STATE: Models: {"count":58,"totalSize":386543911}
2022-11-17 14:37:24 INFO:  Human Build complete... {"logFile":"test/build.log"}

4
test/test-browser-esm.js
View File

@ -75,7 +75,7 @@ async function testDefault(title, testConfig = {}) {
await human.load();
const models = Object.keys(human.models).map((model) => ({ name: model, loaded: (human.models[model] !== null) }));
log(' models', models);
const ops = await human.check();
const ops = await human.models.validate();
if (ops && ops.length > 0) log(' missing ops', ops);
const img = await image('../../samples/in/ai-body.jpg');
const input = await human.image(img); // process image
@ -108,7 +108,7 @@ async function testMatch() {
const similarity = await human.similarity(desc1, desc2);
const descArray = [];
for (let i = 0; i < 100; i++) descArray.push(desc2);
const match = await human.match(desc1, descArray);
const match = await human.match.find(desc1, descArray);
log(`test similarity/${human.tf.getBackend()}`, match, similarity);
}

9
test/test-node-load.js
View File

@ -9,22 +9,21 @@ const log = (status, ...data) => {
async function main() {
const human = new Human.Human(); // create instance of human using default configuration
const startTime = new Date();
log('info', 'load start', { human: human.version, tf: tf.version_core, progress: human.getModelStats().percentageLoaded });
log('info', 'load start', { human: human.version, tf: tf.version_core, progress: human.models.stats().percentageLoaded });
async function monitor() {
const progress = human.getModelStats().percentageLoaded;
const progress = human.models.stats().percentageLoaded;
log('data', 'load interval', { elapsed: new Date() - startTime, progress });
if (progress < 1) setTimeout(monitor, 10);
}
monitor();
// setInterval(() => log('interval', { elapsed: new Date() - startTime, progress: human.getModelStats().percentageLoaded }));
const loadPromise = human.load();
loadPromise
.then(() => log('state', 'passed', { progress: human.getModelStats().percentageLoaded }))
.then(() => log('state', 'passed', { progress: human.models.stats().percentageLoaded }))
.catch(() => log('error', 'load promise'));
await loadPromise;
log('info', 'load final', { progress: human.getModelStats().percentageLoaded });
log('info', 'load final', { progress: human.models.stats().percentageLoaded });
await human.warmup(); // optional as model warmup is performed on-demand first time its executed
}

24
test/test-node-main.js
View File

@ -138,7 +138,7 @@ async function testDetect(human, input, title, checkLeak = true) {
lastOp = `testDetect ${title}`;
log('state', 'start', title);
await human.load(config);
const missing = human.check();
const missing = human.models.validate();
for (const op of missing) log('warn', 'missing kernel ops', { title, model: op.name, url: op.url, missing: op.missing, backkend: human.tf.getBackend() });
const tensors = human.tf.engine().state.numTensors;
const image = input ? await getImage(human, input) : human.tf.randomNormal([1, 1024, 1024, 3]);
@ -189,7 +189,7 @@ async function verifyDetails(human) {
verify(res.face.length === 1, 'details face length', res.face.length);
for (const face of res.face) {
verify(face.score > 0.9 && face.boxScore > 0.9 && face.faceScore > 0.9, 'details face score', face.score, face.boxScore, face.faceScore);
verify(face.age > 23 && face.age < 30 && face.gender === 'female' && face.genderScore > 0.9 && face.iris > 0.5 && face.distance < 2.5, 'details face age/gender', face.age, face.gender, face.genderScore, face.distance);
verify(face.age > 23 && face.age < 30 && face.gender === 'female' && face.genderScore > 0.9 && face.distance > 0.5 && face.distance < 2.5, 'details face age/gender', face.age, face.gender, face.genderScore, face.distance);
verify(face.box.length === 4 && face.boxRaw.length === 4 && face.mesh.length === 478 && face.meshRaw.length === 478 && face.embedding.length === 1024, 'details face arrays', face.box.length, face.mesh.length, face.embedding.length);
verify(face.emotion.length >= 2 && face.emotion[0].score > 0.30 && face.emotion[0].emotion === 'angry', 'details face emotion', face.emotion.length, face.emotion[0]);
verify(face.real > 0.55, 'details face anti-spoofing', face.real);
@ -293,9 +293,9 @@ async function test(Human, inputConfig) {
// test model loading
log('info', 'test: model load');
await human.load();
const models = Object.keys(human.models).map((model) => ({ name: model, loaded: (human.models[model] !== null), url: human.models[model] ? human.models[model]['modelUrl'] : null }));
const loaded = models.filter((model) => model.loaded);
if (models.length === 25 && loaded.length === 11) log('state', 'passed: models loaded', models.length, loaded.length, models);
const models = human.models.list();
const loaded = human.models.loaded();
if (models.length === 24 && loaded.length === 11) log('state', 'passed: models loaded', models.length, loaded.length, models);
else log('error', 'failed: models loaded', models.length, loaded.length, models);
log('info', 'memory:', { memory: human.tf.memory() });
log('info', 'state:', { state: human.tf.engine().state });
@ -380,15 +380,15 @@ async function test(Human, inputConfig) {
const desc3 = res3 && res3.face && res3.face[0] && res3.face[0].embedding ? [...res3.face[0].embedding] : null;
if (!desc1 || !desc2 || !desc3 || desc1.length !== 1024 || desc2.length !== 1024 || desc3.length !== 1024) log('error', 'failed: face descriptor', desc1?.length, desc2?.length, desc3?.length);
else log('state', 'passed: face descriptor');
res1 = human.similarity(desc1, desc1);
res2 = human.similarity(desc1, desc2);
res3 = human.similarity(desc1, desc3);
res1 = human.match.similarity(desc1, desc1);
res2 = human.match.similarity(desc1, desc2);
res3 = human.match.similarity(desc1, desc3);
if (res1 < 1 || res2 < 0.40 || res3 < 0.40 || res2 > 0.75 || res3 > 0.75) log('error', 'failed: face similarity', { similarity: [res1, res2, res3], descriptors: [desc1?.length, desc2?.length, desc3?.length] });
else log('state', 'passed: face similarity', { similarity: [res1, res2, res3], descriptors: [desc1?.length, desc2?.length, desc3?.length] });
// test object detection
log('info', 'test object');
config.object = { enabled: true, modelPath: 'mb3-centernet.json' };
config.object = { enabled: true, modelPath: 'centernet.json' };
res = await testDetect(human, 'samples/in/ai-body.jpg', 'object');
if (!res || res.object?.length < 1 || res.object[0]?.label !== 'person') log('error', 'failed: centernet', res.object);
else log('state', 'passed: centernet');
@ -461,9 +461,9 @@ async function test(Human, inputConfig) {
const arr = db.map((rec) => rec.embedding);
if (db.length < 20) log('error', 'failed: face database ', db.length);
else log('state', 'passed: face database', db.length);
res1 = human.match(desc1, arr);
res2 = human.match(desc2, arr);
res3 = human.match(desc3, arr);
res1 = human.match.find(desc1, arr);
res2 = human.match.find(desc2, arr);
res3 = human.match.find(desc3, arr);
if (res1.index !== 4 || res2.index !== 4 || res3.index !== 4) log('error', 'failed: face match', res1, res2, res3);
else log('state', 'passed: face match', { first: { index: res1.index, similarity: res1.similarity } }, { second: { index: res2.index, similarity: res2.similarity } }, { third: { index: res3.index, similarity: res3.similarity } });

1315
test/test.log
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2
wiki

@ -1 +1 @@
Subproject commit 93e58e16b579922e2f19bc91c8ead0af0f326f5a
Subproject commit 6ea5ea911dcf7ad598c8ee3777b103d7e531fec5