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human
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release candidate

pull/134/head
Vladimir Mandic 2021-05-30 12:03:34 -04:00
parent 261ecda985
commit 3cf15ff629
26 changed files with 635 additions and 577 deletions
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5
CHANGELOG.md
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@ -1,6 +1,6 @@
# @vladmandic/human
Version: **1.9.4**
Version: **2.0.0**
Description: **Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gesture Recognition**
Author: **Vladimir Mandic <mandic00@live.com>**
@ -9,8 +9,9 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
## Changelog
### **HEAD -> main** 2021/05/29 mandic00@live.com
### **HEAD -> main** 2021/05/30 mandic00@live.com
- quantize handdetect model
- added experimental movenet-lightning and removed blazepose from default dist
- added experimental face.rotation.gaze
- fix and optimize for mobile platform

12
README.md
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@ -66,6 +66,7 @@ Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) fo
- [**Platform Support**](https://github.com/vladmandic/human/wiki/Platforms)
- [**List of Models & Credits**](https://github.com/vladmandic/human/wiki/Models)
- [**Security & Privacy Policy**](https://github.com/vladmandic/human/blob/main/SECURITY.md)
- [**License & Usage Restrictions**](https://github.com/vladmandic/human/blob/main/LICENSE)
<br>
@ -77,8 +78,8 @@ Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) fo
## Options
As presented in the demo application...
> [demo/index.html](demo/index.html)
All options as presented in the demo application...
> [demo/index.html](demo/index.html)
![Options visible in demo](assets/screenshot-menu.png)
@ -88,7 +89,7 @@ As presented in the demo application...
<br>
**Training image:**
**Validation image:**
> [demo/index.html](demo/index.html?image=%22../assets/human-sample-upper.jpg%22)
![Example Training Image](assets/screenshot-sample.png)
@ -104,7 +105,10 @@ As presented in the demo application...
![Example Using WebCam](assets/screenshot-webcam.jpg)
**Face Similarity Matching:**
> [demo/facematch.html](demo/facematch.html)
Extracts all faces from provided input images,
sorts them by similarity to selected face
and optionally matches detected face with database of known people to guess their names
> [demo/facematch.html](demo/facematch.html)
![Face Matching](assets/screenshot-facematch.jpg)

14
TODO.md
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@ -7,7 +7,7 @@ N/A
## Exploring Features
- Implement demo as installable PWA with model caching
- Implement results interpolation on library level
- Implement results interpolation on library level instead inside draw functions
- Switch to TypeScript 4.3
## Explore Models
@ -16,6 +16,14 @@ N/A
## In Progress
- Face interpolation
- Gaze interpolation
- Face rotation interpolation
- Object detection interpolation
- Unify score/confidence variables
## Issues
- CenterNet WebGL: <https://github.com/tensorflow/tfjs/issues/5145>
- CenterNet WASM: <https://github.com/tensorflow/tfjs/issues/5110>
- NanoDet WASM: <https://github.com/tensorflow/tfjs/issues/4824>
- BlazeFace and HandPose rotation in NodeJS: <https://github.com/tensorflow/tfjs/issues/4066>
- TypeDoc with TS 4.3: <https://github.com/TypeStrong/typedoc/issues/1589>

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1
demo/index-worker.js
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@ -13,6 +13,7 @@ function log(...msg) {
onmessage = async (msg) => {
if (busy) return;
busy = true;
// received from index.js using:
// worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, config }, [image.data.buffer]);
const image = new ImageData(new Uint8ClampedArray(msg.data.image), msg.data.width, msg.data.height);
let result = {};

89
demo/index.js
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@ -1,13 +1,26 @@
// @ts-nocheck // typescript checks disabled as this is pure javascript
/**
* Human demo for browsers
*
* Main demo app that exposes all Human functionality
* @description Main demo app that exposes all Human functionality
*
* @params Optional URL parameters:
* image=<imagePath:string>: perform detection on specific image and finish
* worker=<true|false>: use WebWorkers
* backend=<webgl|wasm|cpu>: use specific TF backend for operations
* preload=<true|false>: pre-load all configured models
* warmup=<true|false>: warmup all configured models
*
* @example <https://wyse:10031/?backend=wasm&worker=true&image="/assets/sample-me.jpg">
*
* @configuration
* userConfig={}: contains all model configuration used by human
* drawOptions={}: contains all draw variables used by human.draw
* ui={}: contains all variables exposed in the UI
*/
// @ts-nocheck // typescript checks disabled as this is pure javascript
import Human from '../dist/human.esm.js'; // equivalent of @vladmandic/human
// import Human from '../dist/human.esm-nobundle.js'; // this requires that tf is loaded manually and bundled before human can be used
import Menu from './helpers/menu.js';
import GLBench from './helpers/gl-bench.js';
import webRTC from './helpers/webrtc.js';
@ -15,8 +28,7 @@ import webRTC from './helpers/webrtc.js';
let human;
const userConfig = {
warmup: 'full',
/*
warmup: 'none',
backend: 'webgl',
async: false,
cacheSensitivity: 0,
@ -34,10 +46,9 @@ const userConfig = {
hand: { enabled: false },
// body: { enabled: true, modelPath: 'posenet.json' },
// body: { enabled: true, modelPath: 'blazepose.json' },
body: { enabled: true, modelPath: 'movenet-lightning.json' },
object: { enabled: false },
body: { enabled: false, modelPath: 'movenet-lightning.json' },
object: { enabled: true },
gesture: { enabled: true },
*/
};
const drawOptions = {
@ -53,7 +64,7 @@ const ui = {
facing: true, // camera facing front or back
baseBackground: 'rgba(50, 50, 50, 1)', // 'grey'
columns: 2, // when processing sample images create this many columns
useWorker: false, // use web workers for processing
useWorker: true, // use web workers for processing
worker: 'index-worker.js',
maxFPSframes: 10, // keep fps history for how many frames
modelsPreload: true, // preload human models on startup
@ -84,6 +95,7 @@ const ui = {
// sample images
compare: '../assets/sample-me.jpg', // base image for face compare
/*
samples: [
'../assets/sample6.jpg',
'../assets/sample1.jpg',
@ -92,45 +104,10 @@ const ui = {
'../assets/sample3.jpg',
'../assets/sample2.jpg',
],
/*
ui.samples = [
'../private/daz3d/daz3d-brianna.jpg',
'../private/daz3d/daz3d-chiyo.jpg',
'../private/daz3d/daz3d-cody.jpg',
'../private/daz3d/daz3d-drew-01.jpg',
'../private/daz3d/daz3d-drew-02.jpg',
'../private/daz3d/daz3d-ella-01.jpg',
'../private/daz3d/daz3d-ella-02.jpg',
'../private/daz3d/daz3d-_emotions01.jpg',
'../private/daz3d/daz3d-_emotions02.jpg',
'../private/daz3d/daz3d-_emotions03.jpg',
'../private/daz3d/daz3d-_emotions04.jpg',
'../private/daz3d/daz3d-_emotions05.jpg',
'../private/daz3d/daz3d-gillian.jpg',
'../private/daz3d/daz3d-ginnifer.jpg',
'../private/daz3d/daz3d-hye-01.jpg',
'../private/daz3d/daz3d-hye-02.jpg',
'../private/daz3d/daz3d-kaia.jpg',
'../private/daz3d/daz3d-karen.jpg',
'../private/daz3d/daz3d-kiaria-01.jpg',
'../private/daz3d/daz3d-kiaria-02.jpg',
'../private/daz3d/daz3d-lilah-01.jpg',
'../private/daz3d/daz3d-lilah-02.jpg',
'../private/daz3d/daz3d-lilah-03.jpg',
'../private/daz3d/daz3d-lila.jpg',
'../private/daz3d/daz3d-lindsey.jpg',
'../private/daz3d/daz3d-megah.jpg',
'../private/daz3d/daz3d-selina-01.jpg',
'../private/daz3d/daz3d-selina-02.jpg',
'../private/daz3d/daz3d-snow.jpg',
'../private/daz3d/daz3d-sunshine.jpg',
'../private/daz3d/daz3d-taia.jpg',
'../private/daz3d/daz3d-tuesday-01.jpg',
'../private/daz3d/daz3d-tuesday-02.jpg',
'../private/daz3d/daz3d-tuesday-03.jpg',
'../private/daz3d/daz3d-zoe.jpg',
];
*/
samples: [
'../private/daz3d/daz3d-kiaria-02.jpg',
],
};
// global variables
@ -267,9 +244,9 @@ async function drawResults(input) {
// if buffered, immediate loop but limit frame rate although it's going to run slower as JS is singlethreaded
if (ui.buffered) {
ui.drawThread = requestAnimationFrame(() => drawResults(input, canvas));
} else if (!ui.buffered && ui.drawThread) {
} else {
log('stopping buffered refresh');
cancelAnimationFrame(ui.drawThread);
if (ui.drawThread) cancelAnimationFrame(ui.drawThread);
ui.drawThread = null;
}
}
@ -435,7 +412,7 @@ function runHumanDetect(input, canvas, timestamp) {
offscreen.width = canvas.width;
offscreen.height = canvas.height;
const ctx = offscreen.getContext('2d');
ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);
ctx.drawImage(input, 0, 0, canvas.width, canvas.height);
const data = ctx.getImageData(0, 0, canvas.width, canvas.height);
// perform detection in worker
webWorker(input, data, canvas, userConfig, timestamp);
@ -522,6 +499,7 @@ async function detectVideo() {
// just initialize everything and call main function
async function detectSampleImages() {
document.getElementById('play').style.display = 'none';
document.getElementById('canvas').style.display = 'none';
document.getElementById('samples-container').style.display = 'block';
log('running detection of sample images');
@ -530,6 +508,9 @@ async function detectSampleImages() {
for (const m of Object.values(menu)) m.hide();
for (const image of ui.samples) await processImage(image);
status();
document.getElementById('play').style.display = 'none';
document.getElementById('loader').style.display = 'none';
if (ui.detectThread) cancelAnimationFrame(ui.detectThread);
}
function setupMenu() {
@ -692,6 +673,12 @@ async function main() {
document.documentElement.style.setProperty('--icon-size', ui.iconSize);
// sanity check for webworker compatibility
if (typeof Worker === 'undefined' || typeof OffscreenCanvas === 'undefined') {
ui.useWorker = false;
log('workers are disabled due to missing browser functionality');
}
// parse url search params
const params = new URLSearchParams(location.search);
log('url options:', params.toString());

21
demo/node.js
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@ -4,6 +4,7 @@
const log = require('@vladmandic/pilogger');
const fs = require('fs');
const path = require('path');
const process = require('process');
const fetch = require('node-fetch').default;
@ -142,6 +143,7 @@ async function detect(input) {
log.data(' Object: N/A');
}
fs.writeFileSync('result.json', JSON.stringify(result, null, 2));
// print data to console
if (result) {
log.data('Persons:');
@ -182,13 +184,26 @@ async function main() {
log.header();
log.info('Current folder:', process.env.PWD);
await init();
const f = process.argv[2];
if (process.argv.length !== 3) {
log.warn('Parameters: <input image> missing');
log.warn('Parameters: <input image | folder> missing');
await test();
} else if (!fs.existsSync(process.argv[2]) && !process.argv[2].startsWith('http')) {
} else if (!fs.existsSync(f) && !f.startsWith('http')) {
log.error(`File not found: ${process.argv[2]}`);
} else {
await detect(process.argv[2]);
if (fs.existsSync(f)) {
const stat = fs.statSync(f);
if (stat.isDirectory()) {
const dir = fs.readdirSync(f);
for (const file of dir) {
await detect(path.join(f, file));
}
} else {
await detect(f);
}
} else {
await detect(f);
}
}
}

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dist/human.js vendored
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42
dist/human.node-gpu.js vendored
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@ -17598,6 +17598,8 @@ async function load11(config3) {
return model8;
}
async function process3(res, inputSize, outputShape, config3) {
if (!res)
return [];
const results = [];
const detections = res.arraySync();
const squeezeT = tf17.squeeze(res);
@ -17617,7 +17619,7 @@ async function process3(res, inputSize, outputShape, config3) {
nmsT.dispose();
let i = 0;
for (const id of nms) {
const score3 = detections[0][id][4];
const score3 = Math.trunc(100 * detections[0][id][4]) / 100;
const classVal = detections[0][id][5];
const label = labels[classVal].label;
const boxRaw3 = [
@ -17636,18 +17638,16 @@ async function process3(res, inputSize, outputShape, config3) {
}
return results;
}
async function predict10(image15, config3) {
async function predict10(input, config3) {
if (skipped6 < config3.object.skipFrames && config3.skipFrame && last4.length > 0) {
skipped6++;
return last4;
}
skipped6 = 0;
return new Promise(async (resolve) => {
const outputSize = [image15.shape[2], image15.shape[1]];
const resize = tf17.image.resizeBilinear(image15, [model8.inputSize, model8.inputSize], false);
let objectT;
if (config3.object.enabled)
objectT = model8.execute(resize, "tower_0/detections");
const outputSize = [input.shape[2], input.shape[1]];
const resize = tf17.image.resizeBilinear(input, [model8.inputSize, model8.inputSize]);
const objectT = config3.object.enabled ? model8.execute(resize, ["tower_0/detections"]) : null;
resize.dispose();
const obj = await process3(objectT, model8.inputSize, outputSize, config3);
last4 = obj;
@ -19105,9 +19105,9 @@ function calcBuffered(newResult, localOptions) {
if (!bufferedResult.body || newResult.body.length !== bufferedResult.body.length)
bufferedResult.body = JSON.parse(JSON.stringify(newResult.body));
for (let i = 0; i < newResult.body.length; i++) {
bufferedResult.body[i].box = newResult.body[i].box.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].box[j] + box6) / localOptions.bufferedFactor);
bufferedResult.body[i].boxRaw = newResult.body[i].boxRaw.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + box6) / localOptions.bufferedFactor);
bufferedResult.body[i].keypoints = newResult.body[i].keypoints.map((keypoint, j) => ({
const box6 = newResult.body[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.body[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + b) / localOptions.bufferedFactor);
const keypoints3 = newResult.body[i].keypoints.map((keypoint, j) => ({
score: keypoint.score,
part: keypoint.part,
position: {
@ -19115,17 +19115,27 @@ function calcBuffered(newResult, localOptions) {
y: bufferedResult.body[i].keypoints[j] ? ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].keypoints[j].position.y + keypoint.position.y) / localOptions.bufferedFactor : keypoint.position.y
}
}));
bufferedResult.body[i] = { ...newResult.body[i], box: box6, boxRaw: boxRaw3, keypoints: keypoints3 };
}
if (!bufferedResult.hand || newResult.hand.length !== bufferedResult.hand.length)
bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand));
for (let i = 0; i < newResult.hand.length; i++) {
bufferedResult.hand[i].box = newResult.hand[i].box.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].box[j] + box6) / localOptions.bufferedFactor);
bufferedResult.hand[i].boxRaw = newResult.hand[i].boxRaw.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + box6) / localOptions.bufferedFactor);
bufferedResult.hand[i].landmarks = newResult.hand[i].landmarks.map((landmark, j) => landmark.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].landmarks[j][k] + coord) / localOptions.bufferedFactor));
const box6 = newResult.hand[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.hand[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / localOptions.bufferedFactor);
const landmarks = newResult.hand[i].landmarks.map((landmark, j) => landmark.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].landmarks[j][k] + coord) / localOptions.bufferedFactor));
const keys = Object.keys(newResult.hand[i].annotations);
const annotations3 = [];
for (const key of keys) {
bufferedResult.hand[i].annotations[key] = newResult.hand[i].annotations[key].map((val, j) => val.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / localOptions.bufferedFactor));
annotations3[key] = newResult.hand[i].annotations[key].map((val, j) => val.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / localOptions.bufferedFactor));
}
bufferedResult.hand[i] = { ...newResult.hand[i], box: box6, boxRaw: boxRaw3, landmarks, annotations: annotations3 };
}
if (!bufferedResult.face || newResult.face.length !== bufferedResult.face.length)
bufferedResult.face = JSON.parse(JSON.stringify(newResult.face));
for (let i = 0; i < newResult.face.length; i++) {
const box6 = newResult.face[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.face[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / localOptions.bufferedFactor);
bufferedResult.face[i] = { ...newResult.face[i], box: box6, boxRaw: boxRaw3 };
}
const newPersons = newResult.persons;
if (!bufferedResult.persons || newPersons.length !== bufferedResult.persons.length)
@ -19152,7 +19162,7 @@ async function all(inCanvas2, result, drawOptions) {
calcBuffered(result, localOptions);
else
bufferedResult = result;
face2(inCanvas2, result.face, localOptions);
face2(inCanvas2, bufferedResult.face, localOptions);
body2(inCanvas2, bufferedResult.body, localOptions);
hand2(inCanvas2, bufferedResult.hand, localOptions);
gesture(inCanvas2, result.gesture, localOptions);
@ -19941,7 +19951,7 @@ lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
2Q==`;
// package.json
var version = "1.9.4";
var version = "2.0.0";
// src/human.ts
var _numTensors, _analyzeMemoryLeaks, _checkSanity, _firstRun, _lastInputSum, _lastCacheDiff, _sanity, _checkBackend, _skipFrame, _warmupBitmap, _warmupCanvas, _warmupNode;

42
dist/human.node-wasm.js vendored
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@ -17599,6 +17599,8 @@ async function load11(config3) {
return model8;
}
async function process3(res, inputSize, outputShape, config3) {
if (!res)
return [];
const results = [];
const detections = res.arraySync();
const squeezeT = tf17.squeeze(res);
@ -17618,7 +17620,7 @@ async function process3(res, inputSize, outputShape, config3) {
nmsT.dispose();
let i = 0;
for (const id of nms) {
const score3 = detections[0][id][4];
const score3 = Math.trunc(100 * detections[0][id][4]) / 100;
const classVal = detections[0][id][5];
const label = labels[classVal].label;
const boxRaw3 = [
@ -17637,18 +17639,16 @@ async function process3(res, inputSize, outputShape, config3) {
}
return results;
}
async function predict10(image15, config3) {
async function predict10(input, config3) {
if (skipped6 < config3.object.skipFrames && config3.skipFrame && last4.length > 0) {
skipped6++;
return last4;
}
skipped6 = 0;
return new Promise(async (resolve) => {
const outputSize = [image15.shape[2], image15.shape[1]];
const resize = tf17.image.resizeBilinear(image15, [model8.inputSize, model8.inputSize], false);
let objectT;
if (config3.object.enabled)
objectT = model8.execute(resize, "tower_0/detections");
const outputSize = [input.shape[2], input.shape[1]];
const resize = tf17.image.resizeBilinear(input, [model8.inputSize, model8.inputSize]);
const objectT = config3.object.enabled ? model8.execute(resize, ["tower_0/detections"]) : null;
resize.dispose();
const obj = await process3(objectT, model8.inputSize, outputSize, config3);
last4 = obj;
@ -19106,9 +19106,9 @@ function calcBuffered(newResult, localOptions) {
if (!bufferedResult.body || newResult.body.length !== bufferedResult.body.length)
bufferedResult.body = JSON.parse(JSON.stringify(newResult.body));
for (let i = 0; i < newResult.body.length; i++) {
bufferedResult.body[i].box = newResult.body[i].box.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].box[j] + box6) / localOptions.bufferedFactor);
bufferedResult.body[i].boxRaw = newResult.body[i].boxRaw.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + box6) / localOptions.bufferedFactor);
bufferedResult.body[i].keypoints = newResult.body[i].keypoints.map((keypoint, j) => ({
const box6 = newResult.body[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.body[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + b) / localOptions.bufferedFactor);
const keypoints3 = newResult.body[i].keypoints.map((keypoint, j) => ({
score: keypoint.score,
part: keypoint.part,
position: {
@ -19116,17 +19116,27 @@ function calcBuffered(newResult, localOptions) {
y: bufferedResult.body[i].keypoints[j] ? ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].keypoints[j].position.y + keypoint.position.y) / localOptions.bufferedFactor : keypoint.position.y
}
}));
bufferedResult.body[i] = { ...newResult.body[i], box: box6, boxRaw: boxRaw3, keypoints: keypoints3 };
}
if (!bufferedResult.hand || newResult.hand.length !== bufferedResult.hand.length)
bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand));
for (let i = 0; i < newResult.hand.length; i++) {
bufferedResult.hand[i].box = newResult.hand[i].box.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].box[j] + box6) / localOptions.bufferedFactor);
bufferedResult.hand[i].boxRaw = newResult.hand[i].boxRaw.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + box6) / localOptions.bufferedFactor);
bufferedResult.hand[i].landmarks = newResult.hand[i].landmarks.map((landmark, j) => landmark.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].landmarks[j][k] + coord) / localOptions.bufferedFactor));
const box6 = newResult.hand[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.hand[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / localOptions.bufferedFactor);
const landmarks = newResult.hand[i].landmarks.map((landmark, j) => landmark.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].landmarks[j][k] + coord) / localOptions.bufferedFactor));
const keys = Object.keys(newResult.hand[i].annotations);
const annotations3 = [];
for (const key of keys) {
bufferedResult.hand[i].annotations[key] = newResult.hand[i].annotations[key].map((val, j) => val.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / localOptions.bufferedFactor));
annotations3[key] = newResult.hand[i].annotations[key].map((val, j) => val.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / localOptions.bufferedFactor));
}
bufferedResult.hand[i] = { ...newResult.hand[i], box: box6, boxRaw: boxRaw3, landmarks, annotations: annotations3 };
}
if (!bufferedResult.face || newResult.face.length !== bufferedResult.face.length)
bufferedResult.face = JSON.parse(JSON.stringify(newResult.face));
for (let i = 0; i < newResult.face.length; i++) {
const box6 = newResult.face[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.face[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / localOptions.bufferedFactor);
bufferedResult.face[i] = { ...newResult.face[i], box: box6, boxRaw: boxRaw3 };
}
const newPersons = newResult.persons;
if (!bufferedResult.persons || newPersons.length !== bufferedResult.persons.length)
@ -19153,7 +19163,7 @@ async function all(inCanvas2, result, drawOptions) {
calcBuffered(result, localOptions);
else
bufferedResult = result;
face2(inCanvas2, result.face, localOptions);
face2(inCanvas2, bufferedResult.face, localOptions);
body2(inCanvas2, bufferedResult.body, localOptions);
hand2(inCanvas2, bufferedResult.hand, localOptions);
gesture(inCanvas2, result.gesture, localOptions);
@ -19942,7 +19952,7 @@ lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
2Q==`;
// package.json
var version = "1.9.4";
var version = "2.0.0";
// src/human.ts
var _numTensors, _analyzeMemoryLeaks, _checkSanity, _firstRun, _lastInputSum, _lastCacheDiff, _sanity, _checkBackend, _skipFrame, _warmupBitmap, _warmupCanvas, _warmupNode;

42
dist/human.node.js vendored
View File

@ -17598,6 +17598,8 @@ async function load11(config3) {
return model8;
}
async function process3(res, inputSize, outputShape, config3) {
if (!res)
return [];
const results = [];
const detections = res.arraySync();
const squeezeT = tf17.squeeze(res);
@ -17617,7 +17619,7 @@ async function process3(res, inputSize, outputShape, config3) {
nmsT.dispose();
let i = 0;
for (const id of nms) {
const score3 = detections[0][id][4];
const score3 = Math.trunc(100 * detections[0][id][4]) / 100;
const classVal = detections[0][id][5];
const label = labels[classVal].label;
const boxRaw3 = [
@ -17636,18 +17638,16 @@ async function process3(res, inputSize, outputShape, config3) {
}
return results;
}
async function predict10(image15, config3) {
async function predict10(input, config3) {
if (skipped6 < config3.object.skipFrames && config3.skipFrame && last4.length > 0) {
skipped6++;
return last4;
}
skipped6 = 0;
return new Promise(async (resolve) => {
const outputSize = [image15.shape[2], image15.shape[1]];
const resize = tf17.image.resizeBilinear(image15, [model8.inputSize, model8.inputSize], false);
let objectT;
if (config3.object.enabled)
objectT = model8.execute(resize, "tower_0/detections");
const outputSize = [input.shape[2], input.shape[1]];
const resize = tf17.image.resizeBilinear(input, [model8.inputSize, model8.inputSize]);
const objectT = config3.object.enabled ? model8.execute(resize, ["tower_0/detections"]) : null;
resize.dispose();
const obj = await process3(objectT, model8.inputSize, outputSize, config3);
last4 = obj;
@ -19105,9 +19105,9 @@ function calcBuffered(newResult, localOptions) {
if (!bufferedResult.body || newResult.body.length !== bufferedResult.body.length)
bufferedResult.body = JSON.parse(JSON.stringify(newResult.body));
for (let i = 0; i < newResult.body.length; i++) {
bufferedResult.body[i].box = newResult.body[i].box.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].box[j] + box6) / localOptions.bufferedFactor);
bufferedResult.body[i].boxRaw = newResult.body[i].boxRaw.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + box6) / localOptions.bufferedFactor);
bufferedResult.body[i].keypoints = newResult.body[i].keypoints.map((keypoint, j) => ({
const box6 = newResult.body[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.body[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + b) / localOptions.bufferedFactor);
const keypoints3 = newResult.body[i].keypoints.map((keypoint, j) => ({
score: keypoint.score,
part: keypoint.part,
position: {
@ -19115,17 +19115,27 @@ function calcBuffered(newResult, localOptions) {
y: bufferedResult.body[i].keypoints[j] ? ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].keypoints[j].position.y + keypoint.position.y) / localOptions.bufferedFactor : keypoint.position.y
}
}));
bufferedResult.body[i] = { ...newResult.body[i], box: box6, boxRaw: boxRaw3, keypoints: keypoints3 };
}
if (!bufferedResult.hand || newResult.hand.length !== bufferedResult.hand.length)
bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand));
for (let i = 0; i < newResult.hand.length; i++) {
bufferedResult.hand[i].box = newResult.hand[i].box.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].box[j] + box6) / localOptions.bufferedFactor);
bufferedResult.hand[i].boxRaw = newResult.hand[i].boxRaw.map((box6, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + box6) / localOptions.bufferedFactor);
bufferedResult.hand[i].landmarks = newResult.hand[i].landmarks.map((landmark, j) => landmark.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].landmarks[j][k] + coord) / localOptions.bufferedFactor));
const box6 = newResult.hand[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.hand[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / localOptions.bufferedFactor);
const landmarks = newResult.hand[i].landmarks.map((landmark, j) => landmark.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].landmarks[j][k] + coord) / localOptions.bufferedFactor));
const keys = Object.keys(newResult.hand[i].annotations);
const annotations3 = [];
for (const key of keys) {
bufferedResult.hand[i].annotations[key] = newResult.hand[i].annotations[key].map((val, j) => val.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / localOptions.bufferedFactor));
annotations3[key] = newResult.hand[i].annotations[key].map((val, j) => val.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / localOptions.bufferedFactor));
}
bufferedResult.hand[i] = { ...newResult.hand[i], box: box6, boxRaw: boxRaw3, landmarks, annotations: annotations3 };
}
if (!bufferedResult.face || newResult.face.length !== bufferedResult.face.length)
bufferedResult.face = JSON.parse(JSON.stringify(newResult.face));
for (let i = 0; i < newResult.face.length; i++) {
const box6 = newResult.face[i].box.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw3 = newResult.face[i].boxRaw.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / localOptions.bufferedFactor);
bufferedResult.face[i] = { ...newResult.face[i], box: box6, boxRaw: boxRaw3 };
}
const newPersons = newResult.persons;
if (!bufferedResult.persons || newPersons.length !== bufferedResult.persons.length)
@ -19152,7 +19162,7 @@ async function all(inCanvas2, result, drawOptions) {
calcBuffered(result, localOptions);
else
bufferedResult = result;
face2(inCanvas2, result.face, localOptions);
face2(inCanvas2, bufferedResult.face, localOptions);
body2(inCanvas2, bufferedResult.body, localOptions);
hand2(inCanvas2, bufferedResult.hand, localOptions);
gesture(inCanvas2, result.gesture, localOptions);
@ -19941,7 +19951,7 @@ lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
2Q==`;
// package.json
var version = "1.9.4";
var version = "2.0.0";
// src/human.ts
var _numTensors, _analyzeMemoryLeaks, _checkSanity, _firstRun, _lastInputSum, _lastCacheDiff, _sanity, _checkBackend, _skipFrame, _warmupBitmap, _warmupCanvas, _warmupNode;

2
dist/tfjs.esm.js vendored
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2
dist/tfjs.esm.js.map vendored
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BIN
models/mb3-centernet.bin
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552
models/mb3-centernet.json
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6
package.json
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@ -1,6 +1,6 @@
{
"name": "@vladmandic/human",
"version": "1.9.4",
"version": "2.0.0",
"description": "Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gesture Recognition",
"sideEffects": false,
"main": "dist/human.node.js",
@ -68,10 +68,10 @@
"canvas": "^2.8.0",
"chokidar": "^3.5.1",
"dayjs": "^1.10.5",
"esbuild": "^0.12.4",
"esbuild": "^0.12.5",
"eslint": "^7.27.0",
"eslint-config-airbnb-base": "^14.2.1",
"eslint-plugin-import": "^2.23.3",
"eslint-plugin-import": "^2.23.4",
"eslint-plugin-json": "^3.0.0",
"eslint-plugin-node": "^11.1.0",
"eslint-plugin-promise": "^5.1.0",

34
server/build.log
View File

@ -1,17 +1,17 @@
2021-05-29 18:28:57 INFO:  @vladmandic/human version 1.9.4
2021-05-29 18:28:57 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.0.0
2021-05-29 18:28:57 INFO:  Build: file startup all type: production config: {"minifyWhitespace":true,"minifyIdentifiers":true,"minifySyntax":true}
2021-05-29 18:28:57 STATE: Build for: node type: tfjs: {"imports":1,"importBytes":102,"outputBytes":1292,"outputFiles":"dist/tfjs.esm.js"}
2021-05-29 18:28:57 STATE: Build for: node type: node: {"imports":39,"importBytes":443782,"outputBytes":396032,"outputFiles":"dist/human.node.js"}
2021-05-29 18:28:57 STATE: Build for: nodeGPU type: tfjs: {"imports":1,"importBytes":110,"outputBytes":1300,"outputFiles":"dist/tfjs.esm.js"}
2021-05-29 18:28:57 STATE: Build for: nodeGPU type: node: {"imports":39,"importBytes":443790,"outputBytes":396036,"outputFiles":"dist/human.node-gpu.js"}
2021-05-29 18:28:57 STATE: Build for: nodeWASM type: tfjs: {"imports":1,"importBytes":149,"outputBytes":1367,"outputFiles":"dist/tfjs.esm.js"}
2021-05-29 18:28:57 STATE: Build for: nodeWASM type: node: {"imports":39,"importBytes":443857,"outputBytes":396108,"outputFiles":"dist/human.node-wasm.js"}
2021-05-29 18:28:57 STATE: Build for: browserNoBundle type: tfjs: {"imports":1,"importBytes":2478,"outputBytes":1394,"outputFiles":"dist/tfjs.esm.js"}
2021-05-29 18:28:57 STATE: Build for: browserNoBundle type: esm: {"imports":39,"importBytes":443884,"outputBytes":242161,"outputFiles":"dist/human.esm-nobundle.js"}
2021-05-29 18:28:58 STATE: Build for: browserBundle type: tfjs: {"modules":1274,"moduleBytes":4114813,"imports":7,"importBytes":2478,"outputBytes":1111414,"outputFiles":"dist/tfjs.esm.js"}
2021-05-29 18:28:59 STATE: Build for: browserBundle type: iife: {"imports":39,"importBytes":1553904,"outputBytes":1349968,"outputFiles":"dist/human.js"}
2021-05-29 18:28:59 STATE: Build for: browserBundle type: esm: {"imports":39,"importBytes":1553904,"outputBytes":1349960,"outputFiles":"dist/human.esm.js"}
2021-05-29 18:28:59 INFO:  Generate types: ["src/human.ts"]
2021-05-29 18:29:05 INFO:  Update Change log: ["/home/vlado/dev/human/CHANGELOG.md"]
2021-05-29 18:29:05 INFO:  Generate TypeDocs: ["src/human.ts"]
2021-05-30 12:02:00 INFO:  @vladmandic/human version 2.0.0
2021-05-30 12:02:00 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.0.0
2021-05-30 12:02:00 INFO:  Build: file startup all type: production config: {"minifyWhitespace":true,"minifyIdentifiers":true,"minifySyntax":true}
2021-05-30 12:02:00 STATE: Build for: node type: tfjs: {"imports":1,"importBytes":102,"outputBytes":1292,"outputFiles":"dist/tfjs.esm.js"}
2021-05-30 12:02:00 STATE: Build for: node type: node: {"imports":39,"importBytes":444757,"outputBytes":396794,"outputFiles":"dist/human.node.js"}
2021-05-30 12:02:00 STATE: Build for: nodeGPU type: tfjs: {"imports":1,"importBytes":110,"outputBytes":1300,"outputFiles":"dist/tfjs.esm.js"}
2021-05-30 12:02:00 STATE: Build for: nodeGPU type: node: {"imports":39,"importBytes":444765,"outputBytes":396798,"outputFiles":"dist/human.node-gpu.js"}
2021-05-30 12:02:00 STATE: Build for: nodeWASM type: tfjs: {"imports":1,"importBytes":149,"outputBytes":1367,"outputFiles":"dist/tfjs.esm.js"}
2021-05-30 12:02:01 STATE: Build for: nodeWASM type: node: {"imports":39,"importBytes":444832,"outputBytes":396870,"outputFiles":"dist/human.node-wasm.js"}
2021-05-30 12:02:01 STATE: Build for: browserNoBundle type: tfjs: {"imports":1,"importBytes":2478,"outputBytes":1394,"outputFiles":"dist/tfjs.esm.js"}
2021-05-30 12:02:01 STATE: Build for: browserNoBundle type: esm: {"imports":39,"importBytes":444859,"outputBytes":242556,"outputFiles":"dist/human.esm-nobundle.js"}
2021-05-30 12:02:01 STATE: Build for: browserBundle type: tfjs: {"modules":1274,"moduleBytes":4114813,"imports":7,"importBytes":2478,"outputBytes":1111418,"outputFiles":"dist/tfjs.esm.js"}
2021-05-30 12:02:02 STATE: Build for: browserBundle type: iife: {"imports":39,"importBytes":1554883,"outputBytes":1350365,"outputFiles":"dist/human.js"}
2021-05-30 12:02:02 STATE: Build for: browserBundle type: esm: {"imports":39,"importBytes":1554883,"outputBytes":1350357,"outputFiles":"dist/human.esm.js"}
2021-05-30 12:02:02 INFO:  Generate types: ["src/human.ts"]
2021-05-30 12:02:07 INFO:  Update Change log: ["/home/vlado/dev/human/CHANGELOG.md"]
2021-05-30 12:02:07 INFO:  Generate TypeDocs: ["src/human.ts"]

52
src/draw/draw.ts
View File

@ -503,17 +503,18 @@ export async function person(inCanvas: HTMLCanvasElement, result: Array<Person>,
}
function calcBuffered(newResult, localOptions) {
// if (newResult.timestamp !== bufferedResult?.timestamp) bufferedResult = JSON.parse(JSON.stringify(newResult)); // no need to force update
// each record is only updated using deep copy when number of detected record changes, otherwise it will converge by itself
// each record is only updated using deep clone when number of detected record changes, otherwise it will converge by itself
// otherwise bufferedResult is a shallow clone of result plus updated local calculated values
// thus mixing by-reference and by-value assignments to minimize memory operations
// interpolate body results
if (!bufferedResult.body || (newResult.body.length !== bufferedResult.body.length)) bufferedResult.body = JSON.parse(JSON.stringify(newResult.body));
for (let i = 0; i < newResult.body.length; i++) { // update body: box, boxRaw, keypoints
bufferedResult.body[i].box = newResult.body[i].box
.map((box, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].box[j] + box) / localOptions.bufferedFactor) as [number, number, number, number];
bufferedResult.body[i].boxRaw = newResult.body[i].boxRaw
.map((box, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + box) / localOptions.bufferedFactor) as [number, number, number, number];
bufferedResult.body[i].keypoints = newResult.body[i].keypoints
if (!bufferedResult.body || (newResult.body.length !== bufferedResult.body.length)) bufferedResult.body = JSON.parse(JSON.stringify(newResult.body)); // deep clone once
for (let i = 0; i < newResult.body.length; i++) {
const box = newResult.body[i].box // update box
.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].box[j] + b) / localOptions.bufferedFactor) as [number, number, number, number];
const boxRaw = newResult.body[i].boxRaw // update boxRaw
.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + b) / localOptions.bufferedFactor) as [number, number, number, number];
const keypoints = newResult.body[i].keypoints // update keypoints
.map((keypoint, j) => ({
score: keypoint.score,
part: keypoint.part,
@ -522,24 +523,37 @@ function calcBuffered(newResult, localOptions) {
y: bufferedResult.body[i].keypoints[j] ? ((localOptions.bufferedFactor - 1) * bufferedResult.body[i].keypoints[j].position.y + keypoint.position.y) / localOptions.bufferedFactor : keypoint.position.y,
},
}));
bufferedResult.body[i] = { ...newResult.body[i], box, boxRaw, keypoints }; // shallow clone plus updated values
}
// interpolate hand results
if (!bufferedResult.hand || (newResult.hand.length !== bufferedResult.hand.length)) bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand));
for (let i = 0; i < newResult.hand.length; i++) { // update body: box, boxRaw, landmarks, annotations
bufferedResult.hand[i].box = newResult.hand[i].box
.map((box, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].box[j] + box) / localOptions.bufferedFactor);
bufferedResult.hand[i].boxRaw = newResult.hand[i].boxRaw
.map((box, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + box) / localOptions.bufferedFactor);
bufferedResult.hand[i].landmarks = newResult.hand[i].landmarks
if (!bufferedResult.hand || (newResult.hand.length !== bufferedResult.hand.length)) bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand)); // deep clone once
for (let i = 0; i < newResult.hand.length; i++) {
const box = newResult.hand[i].box // update box
.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw = newResult.hand[i].boxRaw // update boxRaw
.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / localOptions.bufferedFactor);
const landmarks = newResult.hand[i].landmarks // update landmarks
.map((landmark, j) => landmark
.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].landmarks[j][k] + coord) / localOptions.bufferedFactor));
const keys = Object.keys(newResult.hand[i].annotations);
const keys = Object.keys(newResult.hand[i].annotations); // update annotations
const annotations = [];
for (const key of keys) {
bufferedResult.hand[i].annotations[key] = newResult.hand[i].annotations[key]
annotations[key] = newResult.hand[i].annotations[key]
.map((val, j) => val
.map((coord, k) => ((localOptions.bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / localOptions.bufferedFactor));
}
bufferedResult.hand[i] = { ...newResult.hand[i], box, boxRaw, landmarks, annotations }; // shallow clone plus updated values
}
// interpolate face results
if (!bufferedResult.face || (newResult.face.length !== bufferedResult.face.length)) bufferedResult.face = JSON.parse(JSON.stringify(newResult.face)); // deep clone once
for (let i = 0; i < newResult.face.length; i++) {
const box = newResult.face[i].box // update box
.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / localOptions.bufferedFactor);
const boxRaw = newResult.face[i].boxRaw // update boxRaw
.map((b, j) => ((localOptions.bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / localOptions.bufferedFactor);
bufferedResult.face[i] = { ...newResult.face[i], box, boxRaw }; // shallow clone plus updated values
}
// interpolate person results
@ -569,7 +583,7 @@ export async function all(inCanvas: HTMLCanvasElement, result: Result, drawOptio
if (!(inCanvas instanceof HTMLCanvasElement)) return;
if (localOptions.bufferedOutput) calcBuffered(result, localOptions); // do results interpolation
else bufferedResult = result; // just use results as-is
face(inCanvas, result.face, localOptions); // face does have buffering
face(inCanvas, bufferedResult.face, localOptions); // face does have buffering
body(inCanvas, bufferedResult.body, localOptions); // use interpolated results if available
hand(inCanvas, bufferedResult.hand, localOptions); // use interpolated results if available
// person(inCanvas, bufferedResult.persons, localOptions); // use interpolated results if available

16
src/object/centernet.ts
View File

@ -24,18 +24,18 @@ export async function load(config) {
}
async function process(res, inputSize, outputShape, config) {
if (!res) return [];
const results: Array<Item> = [];
const detections = res.arraySync();
const squeezeT = tf.squeeze(res);
res.dispose();
const arr = tf.split(squeezeT, 6, 1); // x1, y1, x2, y2, score, class
squeezeT.dispose();
const stackT = tf.stack([arr[1], arr[0], arr[3], arr[2]], 1); // tf.nms expects y, x
const stackT = tf.stack([arr[1], arr[0], arr[3], arr[2]], 1); // reorder dims as tf.nms expects y, x
const boxesT = stackT.squeeze();
const scoresT = arr[4].squeeze();
const classesT = arr[5].squeeze();
arr.forEach((t) => t.dispose());
// @ts-ignore boxesT type is not correctly inferred
const nmsT = await tf.image.nonMaxSuppressionAsync(boxesT, scoresT, config.object.maxDetected, config.object.iouThreshold, config.object.minConfidence);
boxesT.dispose();
scoresT.dispose();
@ -44,7 +44,7 @@ async function process(res, inputSize, outputShape, config) {
nmsT.dispose();
let i = 0;
for (const id of nms) {
const score = detections[0][id][4];
const score = Math.trunc(100 * detections[0][id][4]) / 100;
const classVal = detections[0][id][5];
const label = labels[classVal].label;
const boxRaw = [
@ -64,18 +64,16 @@ async function process(res, inputSize, outputShape, config) {
return results;
}
export async function predict(image, config): Promise<Item[]> {
export async function predict(input, config): Promise<Item[]> {
if ((skipped < config.object.skipFrames) && config.skipFrame && (last.length > 0)) {
skipped++;
return last;
}
skipped = 0;
return new Promise(async (resolve) => {
const outputSize = [image.shape[2], image.shape[1]];
const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);
let objectT;
if (config.object.enabled) objectT = model.execute(resize, 'tower_0/detections');
const outputSize = [input.shape[2], input.shape[1]];
const resize = tf.image.resizeBilinear(input, [model.inputSize, model.inputSize]);
const objectT = config.object.enabled ? model.execute(resize, ['tower_0/detections']) : null;
resize.dispose();
const obj = await process(objectT, model.inputSize, outputSize, config);

240
test/test.log
View File

@ -1,120 +1,120 @@
2021-05-28 15:52:57 INFO:  @vladmandic/human version 1.9.4
2021-05-28 15:52:57 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.0.0
2021-05-28 15:52:57 INFO:  tests: ["test-node.js","test-node-gpu.js","test-node-wasm.js"]
2021-05-28 15:52:57 INFO:  test-node.js start
2021-05-28 15:52:59 STATE: test-node.js passed: create human
2021-05-28 15:52:59 INFO:  test-node.js human version: 1.9.4
2021-05-28 15:52:59 INFO:  test-node.js platform: linux x64 agent: NodeJS v16.0.0
2021-05-28 15:52:59 INFO:  test-node.js tfjs version: 3.6.0
2021-05-28 15:52:59 STATE: test-node.js passed: set backend: tensorflow
2021-05-28 15:52:59 STATE: test-node.js passed: load models
2021-05-28 15:52:59 STATE: test-node.js result: defined models: 13 loaded models: 6
2021-05-28 15:52:59 STATE: test-node.js passed: warmup: none default
2021-05-28 15:53:01 STATE: test-node.js passed: warmup: face default
2021-05-28 15:53:01 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8246909379959106,"class":"person"} {"score":0.96,"keypoints":5}
2021-05-28 15:53:01 DATA:  test-node.js result: performance: load: 397 total: 1679
2021-05-28 15:53:02 STATE: test-node.js passed: warmup: body default
2021-05-28 15:53:02 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":29.5,"gender":"female"} {"score":0.7261000871658325,"class":"person"} {"score":0.92,"keypoints":17}
2021-05-28 15:53:02 DATA:  test-node.js result: performance: load: 397 total: 1462
2021-05-28 15:53:02 INFO:  test-node.js test body variants
2021-05-28 15:53:03 STATE: test-node.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-28 15:53:04 STATE: test-node.js passed: detect: assets/human-sample-body.jpg posenet
2021-05-28 15:53:04 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1} {"score":0.7261000871658325,"class":"person"} {"score":0.91,"keypoints":17}
2021-05-28 15:53:04 DATA:  test-node.js result: performance: load: 397 total: 957
2021-05-28 15:53:05 STATE: test-node.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-28 15:53:06 STATE: test-node.js passed: detect: assets/human-sample-body.jpg blazepose
2021-05-28 15:53:06 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1} {"score":0.7261000871658325,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:06 DATA:  test-node.js result: performance: load: 397 total: 523
2021-05-28 15:53:07 STATE: test-node.js passed: detect: random default
2021-05-28 15:53:07 DATA:  test-node.js result: face: 0 body: 1 hand: 0 gesture: 1 object: 0 person: 0 {} {} {"score":1,"keypoints":39}
2021-05-28 15:53:07 DATA:  test-node.js result: performance: load: 397 total: 970
2021-05-28 15:53:07 INFO:  test-node.js test: first instance
2021-05-28 15:53:07 STATE: test-node.js passed: load image: assets/sample-me.jpg [1,700,700,3]
2021-05-28 15:53:09 STATE: test-node.js passed: detect: assets/sample-me.jpg default
2021-05-28 15:53:09 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 2 person: 1 {"confidence":1,"age":39.2,"gender":"male"} {"score":0.6820425987243652,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:09 DATA:  test-node.js result: performance: load: 397 total: 1591
2021-05-28 15:53:09 INFO:  test-node.js test: second instance
2021-05-28 15:53:09 STATE: test-node.js passed: load image: assets/sample-me.jpg [1,700,700,3]
2021-05-28 15:53:11 STATE: test-node.js passed: detect: assets/sample-me.jpg default
2021-05-28 15:53:11 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 2 person: 1 {"confidence":1,"age":39.2,"gender":"male"} {"score":0.6820425987243652,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:11 DATA:  test-node.js result: performance: load: 4 total: 1475
2021-05-28 15:53:11 INFO:  test-node.js test: concurrent
2021-05-28 15:53:11 STATE: test-node.js passed: load image: assets/human-sample-face.jpg [1,256,256,3]
2021-05-28 15:53:11 STATE: test-node.js passed: load image: assets/human-sample-face.jpg [1,256,256,3]
2021-05-28 15:53:12 STATE: test-node.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-28 15:53:13 STATE: test-node.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-28 15:53:18 STATE: test-node.js passed: detect: assets/human-sample-face.jpg default
2021-05-28 15:53:18 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8257162570953369,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:18 DATA:  test-node.js result: performance: load: 397 total: 5615
2021-05-28 15:53:18 STATE: test-node.js passed: detect: assets/human-sample-face.jpg default
2021-05-28 15:53:18 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8257162570953369,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:18 DATA:  test-node.js result: performance: load: 4 total: 5615
2021-05-28 15:53:18 STATE: test-node.js passed: detect: assets/human-sample-body.jpg default
2021-05-28 15:53:18 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":28.5,"gender":"female"} {"score":0.7273815870285034,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:18 DATA:  test-node.js result: performance: load: 397 total: 5615
2021-05-28 15:53:18 STATE: test-node.js passed: detect: assets/human-sample-body.jpg default
2021-05-28 15:53:18 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":28.5,"gender":"female"} {"score":0.7273815870285034,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:18 DATA:  test-node.js result: performance: load: 4 total: 5615
2021-05-28 15:53:18 INFO:  test-node.js test complete: 19711 ms
2021-05-28 15:53:18 INFO:  test-node-gpu.js start
2021-05-28 15:53:20 WARN:  test-node-gpu.js stderr: 2021-05-28 15:53:20.148509: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2021-05-28 15:53:20 WARN:  test-node-gpu.js stderr: 2021-05-28 15:53:20.400714: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2021-05-28 15:53:20 WARN:  test-node-gpu.js stderr: 2021-05-28 15:53:20.400783: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (wyse): /proc/driver/nvidia/version does not exist
2021-05-28 15:53:20 STATE: test-node-gpu.js passed: create human
2021-05-28 15:53:20 INFO:  test-node-gpu.js human version: 1.9.4
2021-05-28 15:53:20 INFO:  test-node-gpu.js platform: linux x64 agent: NodeJS v16.0.0
2021-05-28 15:53:20 INFO:  test-node-gpu.js tfjs version: 3.6.0
2021-05-28 15:53:20 STATE: test-node-gpu.js passed: set backend: tensorflow
2021-05-28 15:53:20 STATE: test-node-gpu.js passed: load models
2021-05-28 15:53:20 STATE: test-node-gpu.js result: defined models: 13 loaded models: 6
2021-05-28 15:53:20 STATE: test-node-gpu.js passed: warmup: none default
2021-05-28 15:53:22 STATE: test-node-gpu.js passed: warmup: face default
2021-05-28 15:53:22 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8246909379959106,"class":"person"} {"score":0.96,"keypoints":5}
2021-05-28 15:53:22 DATA:  test-node-gpu.js result: performance: load: 310 total: 1956
2021-05-28 15:53:24 STATE: test-node-gpu.js passed: warmup: body default
2021-05-28 15:53:24 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":29.5,"gender":"female"} {"score":0.7261000871658325,"class":"person"} {"score":0.92,"keypoints":17}
2021-05-28 15:53:24 DATA:  test-node-gpu.js result: performance: load: 310 total: 1601
2021-05-28 15:53:24 INFO:  test-node-gpu.js test body variants
2021-05-28 15:53:25 STATE: test-node-gpu.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-28 15:53:26 STATE: test-node-gpu.js passed: detect: assets/human-sample-body.jpg posenet
2021-05-28 15:53:26 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1} {"score":0.7261000871658325,"class":"person"} {"score":0.91,"keypoints":17}
2021-05-28 15:53:26 DATA:  test-node-gpu.js result: performance: load: 310 total: 1047
2021-05-28 15:53:27 STATE: test-node-gpu.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-28 15:53:27 STATE: test-node-gpu.js passed: detect: assets/human-sample-body.jpg blazepose
2021-05-28 15:53:27 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1} {"score":0.7261000871658325,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:27 DATA:  test-node-gpu.js result: performance: load: 310 total: 436
2021-05-28 15:53:28 STATE: test-node-gpu.js passed: detect: random default
2021-05-28 15:53:28 DATA:  test-node-gpu.js result: face: 0 body: 1 hand: 0 gesture: 1 object: 1 person: 0 {} {"score":0.7261000871658325,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:28 DATA:  test-node-gpu.js result: performance: load: 310 total: 209
2021-05-28 15:53:28 INFO:  test-node-gpu.js test: first instance
2021-05-28 15:53:28 STATE: test-node-gpu.js passed: load image: assets/sample-me.jpg [1,700,700,3]
2021-05-28 15:53:28 STATE: test-node-gpu.js passed: detect: assets/sample-me.jpg default
2021-05-28 15:53:28 DATA:  test-node-gpu.js result: face: 0 body: 1 hand: 0 gesture: 1 object: 1 person: 0 {} {"score":0.7261000871658325,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:28 DATA:  test-node-gpu.js result: performance: load: 310 total: 184
2021-05-28 15:53:28 INFO:  test-node-gpu.js test: second instance
2021-05-28 15:53:29 STATE: test-node-gpu.js passed: load image: assets/sample-me.jpg [1,700,700,3]
2021-05-28 15:53:30 STATE: test-node-gpu.js passed: detect: assets/sample-me.jpg default
2021-05-28 15:53:30 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 2 person: 1 {"confidence":1,"age":39.2,"gender":"male"} {"score":0.6820425987243652,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:30 DATA:  test-node-gpu.js result: performance: load: 2 total: 1487
2021-05-28 15:53:30 INFO:  test-node-gpu.js test: concurrent
2021-05-28 15:53:30 STATE: test-node-gpu.js passed: load image: assets/human-sample-face.jpg [1,256,256,3]
2021-05-28 15:53:30 STATE: test-node-gpu.js passed: load image: assets/human-sample-face.jpg [1,256,256,3]
2021-05-28 15:53:31 STATE: test-node-gpu.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-28 15:53:32 STATE: test-node-gpu.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-28 15:53:38 STATE: test-node-gpu.js passed: detect: assets/human-sample-face.jpg default
2021-05-28 15:53:38 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8257162570953369,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:38 DATA:  test-node-gpu.js result: performance: load: 310 total: 5528
2021-05-28 15:53:38 STATE: test-node-gpu.js passed: detect: assets/human-sample-face.jpg default
2021-05-28 15:53:38 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8257162570953369,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:38 DATA:  test-node-gpu.js result: performance: load: 2 total: 5528
2021-05-28 15:53:38 STATE: test-node-gpu.js passed: detect: assets/human-sample-body.jpg default
2021-05-28 15:53:38 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":28.5,"gender":"female"} {"score":0.7273815870285034,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:38 DATA:  test-node-gpu.js result: performance: load: 310 total: 5528
2021-05-28 15:53:38 STATE: test-node-gpu.js passed: detect: assets/human-sample-body.jpg default
2021-05-28 15:53:38 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":28.5,"gender":"female"} {"score":0.7273815870285034,"class":"person"} {"score":1,"keypoints":39}
2021-05-28 15:53:38 DATA:  test-node-gpu.js result: performance: load: 2 total: 5528
2021-05-28 15:53:38 INFO:  test-node-gpu.js test complete: 17887 ms
2021-05-28 15:53:38 INFO:  test-node-wasm.js start
2021-05-28 15:53:38 ERROR: test-node-wasm.js failed: model server: request to http://localhost:10030/models/ failed, reason: connect ECONNREFUSED 127.0.0.1:10030
2021-05-28 15:53:38 ERROR: test-node-wasm.js aborting test
2021-05-28 15:53:38 INFO:  status: {"passed":46,"failed":1}
2021-05-29 18:30:17 INFO:  @vladmandic/human version 1.9.4
2021-05-29 18:30:17 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.0.0
2021-05-29 18:30:17 INFO:  tests: ["test-node.js","test-node-gpu.js","test-node-wasm.js"]
2021-05-29 18:30:17 INFO:  test-node.js start
2021-05-29 18:30:19 STATE: test-node.js passed: create human
2021-05-29 18:30:19 INFO:  test-node.js human version: 1.9.4
2021-05-29 18:30:19 INFO:  test-node.js platform: linux x64 agent: NodeJS v16.0.0
2021-05-29 18:30:19 INFO:  test-node.js tfjs version: 3.6.0
2021-05-29 18:30:19 STATE: test-node.js passed: set backend: tensorflow
2021-05-29 18:30:19 STATE: test-node.js passed: load models
2021-05-29 18:30:19 STATE: test-node.js result: defined models: 14 loaded models: 6
2021-05-29 18:30:19 STATE: test-node.js passed: warmup: none default
2021-05-29 18:30:21 STATE: test-node.js passed: warmup: face default
2021-05-29 18:30:21 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8246909379959106,"class":"person"} {"score":0.73,"keypoints":5}
2021-05-29 18:30:21 DATA:  test-node.js result: performance: load: 345 total: 1666
2021-05-29 18:30:22 STATE: test-node.js passed: warmup: body default
2021-05-29 18:30:22 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":29.5,"gender":"female"} {"score":0.7261000871658325,"class":"person"} {"score":0.93,"keypoints":17}
2021-05-29 18:30:22 DATA:  test-node.js result: performance: load: 345 total: 1523
2021-05-29 18:30:22 INFO:  test-node.js test body variants
2021-05-29 18:30:23 STATE: test-node.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-29 18:30:24 STATE: test-node.js passed: detect: assets/human-sample-body.jpg posenet
2021-05-29 18:30:24 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1} {"score":0.7261000871658325,"class":"person"} {"score":0.96,"keypoints":16}
2021-05-29 18:30:24 DATA:  test-node.js result: performance: load: 345 total: 987
2021-05-29 18:30:25 STATE: test-node.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-29 18:30:26 STATE: test-node.js passed: detect: assets/human-sample-body.jpg movenet
2021-05-29 18:30:26 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1} {"score":0.7261000871658325,"class":"person"} {"score":0.93,"keypoints":17}
2021-05-29 18:30:26 DATA:  test-node.js result: performance: load: 345 total: 318
2021-05-29 18:30:27 STATE: test-node.js passed: detect: random default
2021-05-29 18:30:27 DATA:  test-node.js result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0,"keypoints":0}
2021-05-29 18:30:27 DATA:  test-node.js result: performance: load: 345 total: 788
2021-05-29 18:30:27 INFO:  test-node.js test: first instance
2021-05-29 18:30:27 STATE: test-node.js passed: load image: assets/sample-me.jpg [1,700,700,3]
2021-05-29 18:30:28 STATE: test-node.js passed: detect: assets/sample-me.jpg default
2021-05-29 18:30:28 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 2 person: 1 {"confidence":1,"age":39.2,"gender":"male"} {"score":0.6820425987243652,"class":"person"} {"score":0.67,"keypoints":7}
2021-05-29 18:30:28 DATA:  test-node.js result: performance: load: 345 total: 1516
2021-05-29 18:30:28 INFO:  test-node.js test: second instance
2021-05-29 18:30:29 STATE: test-node.js passed: load image: assets/sample-me.jpg [1,700,700,3]
2021-05-29 18:30:30 STATE: test-node.js passed: detect: assets/sample-me.jpg default
2021-05-29 18:30:30 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 2 person: 1 {"confidence":1,"age":39.2,"gender":"male"} {"score":0.6820425987243652,"class":"person"} {"score":0.67,"keypoints":7}
2021-05-29 18:30:30 DATA:  test-node.js result: performance: load: 7 total: 1435
2021-05-29 18:30:30 INFO:  test-node.js test: concurrent
2021-05-29 18:30:30 STATE: test-node.js passed: load image: assets/human-sample-face.jpg [1,256,256,3]
2021-05-29 18:30:30 STATE: test-node.js passed: load image: assets/human-sample-face.jpg [1,256,256,3]
2021-05-29 18:30:31 STATE: test-node.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-29 18:30:32 STATE: test-node.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-29 18:30:38 STATE: test-node.js passed: detect: assets/human-sample-face.jpg default
2021-05-29 18:30:38 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8257162570953369,"class":"person"} {"score":0.73,"keypoints":17}
2021-05-29 18:30:38 DATA:  test-node.js result: performance: load: 345 total: 5657
2021-05-29 18:30:38 STATE: test-node.js passed: detect: assets/human-sample-face.jpg default
2021-05-29 18:30:38 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8257162570953369,"class":"person"} {"score":0.73,"keypoints":17}
2021-05-29 18:30:38 DATA:  test-node.js result: performance: load: 7 total: 5657
2021-05-29 18:30:38 STATE: test-node.js passed: detect: assets/human-sample-body.jpg default
2021-05-29 18:30:38 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":28.5,"gender":"female"} {"score":0.7273815870285034,"class":"person"} {"score":0.93,"keypoints":17}
2021-05-29 18:30:38 DATA:  test-node.js result: performance: load: 345 total: 5657
2021-05-29 18:30:38 STATE: test-node.js passed: detect: assets/human-sample-body.jpg default
2021-05-29 18:30:38 DATA:  test-node.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":28.5,"gender":"female"} {"score":0.7273815870285034,"class":"person"} {"score":0.93,"keypoints":17}
2021-05-29 18:30:38 DATA:  test-node.js result: performance: load: 7 total: 5657
2021-05-29 18:30:38 INFO:  test-node.js test complete: 19401 ms
2021-05-29 18:30:38 INFO:  test-node-gpu.js start
2021-05-29 18:30:39 WARN:  test-node-gpu.js stderr: 2021-05-29 18:30:39.644962: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2021-05-29 18:30:39 WARN:  test-node-gpu.js stderr: 2021-05-29 18:30:39.887957: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2021-05-29 18:30:39 WARN:  test-node-gpu.js stderr: 2021-05-29 18:30:39.888022: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (wyse): /proc/driver/nvidia/version does not exist
2021-05-29 18:30:39 STATE: test-node-gpu.js passed: create human
2021-05-29 18:30:39 INFO:  test-node-gpu.js human version: 1.9.4
2021-05-29 18:30:39 INFO:  test-node-gpu.js platform: linux x64 agent: NodeJS v16.0.0
2021-05-29 18:30:39 INFO:  test-node-gpu.js tfjs version: 3.6.0
2021-05-29 18:30:40 STATE: test-node-gpu.js passed: set backend: tensorflow
2021-05-29 18:30:40 STATE: test-node-gpu.js passed: load models
2021-05-29 18:30:40 STATE: test-node-gpu.js result: defined models: 14 loaded models: 6
2021-05-29 18:30:40 STATE: test-node-gpu.js passed: warmup: none default
2021-05-29 18:30:42 STATE: test-node-gpu.js passed: warmup: face default
2021-05-29 18:30:42 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8246909379959106,"class":"person"} {"score":0.73,"keypoints":5}
2021-05-29 18:30:42 DATA:  test-node-gpu.js result: performance: load: 348 total: 1692
2021-05-29 18:30:43 STATE: test-node-gpu.js passed: warmup: body default
2021-05-29 18:30:43 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":29.5,"gender":"female"} {"score":0.7261000871658325,"class":"person"} {"score":0.93,"keypoints":17}
2021-05-29 18:30:43 DATA:  test-node-gpu.js result: performance: load: 348 total: 1521
2021-05-29 18:30:43 INFO:  test-node-gpu.js test body variants
2021-05-29 18:30:44 STATE: test-node-gpu.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-29 18:30:45 STATE: test-node-gpu.js passed: detect: assets/human-sample-body.jpg posenet
2021-05-29 18:30:45 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1} {"score":0.7261000871658325,"class":"person"} {"score":0.96,"keypoints":16}
2021-05-29 18:30:45 DATA:  test-node-gpu.js result: performance: load: 348 total: 1028
2021-05-29 18:30:46 STATE: test-node-gpu.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-29 18:30:46 STATE: test-node-gpu.js passed: detect: assets/human-sample-body.jpg movenet
2021-05-29 18:30:46 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1} {"score":0.7261000871658325,"class":"person"} {"score":0.93,"keypoints":17}
2021-05-29 18:30:46 DATA:  test-node-gpu.js result: performance: load: 348 total: 327
2021-05-29 18:30:47 STATE: test-node-gpu.js passed: detect: random default
2021-05-29 18:30:47 DATA:  test-node-gpu.js result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0,"keypoints":0}
2021-05-29 18:30:47 DATA:  test-node-gpu.js result: performance: load: 348 total: 757
2021-05-29 18:30:47 INFO:  test-node-gpu.js test: first instance
2021-05-29 18:30:48 STATE: test-node-gpu.js passed: load image: assets/sample-me.jpg [1,700,700,3]
2021-05-29 18:30:49 STATE: test-node-gpu.js passed: detect: assets/sample-me.jpg default
2021-05-29 18:30:49 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 2 person: 1 {"confidence":1,"age":39.2,"gender":"male"} {"score":0.6820425987243652,"class":"person"} {"score":0.67,"keypoints":7}
2021-05-29 18:30:49 DATA:  test-node-gpu.js result: performance: load: 348 total: 1413
2021-05-29 18:30:49 INFO:  test-node-gpu.js test: second instance
2021-05-29 18:30:50 STATE: test-node-gpu.js passed: load image: assets/sample-me.jpg [1,700,700,3]
2021-05-29 18:30:51 STATE: test-node-gpu.js passed: detect: assets/sample-me.jpg default
2021-05-29 18:30:51 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 2 person: 1 {"confidence":1,"age":39.2,"gender":"male"} {"score":0.6820425987243652,"class":"person"} {"score":0.67,"keypoints":7}
2021-05-29 18:30:51 DATA:  test-node-gpu.js result: performance: load: 2 total: 1429
2021-05-29 18:30:51 INFO:  test-node-gpu.js test: concurrent
2021-05-29 18:30:51 STATE: test-node-gpu.js passed: load image: assets/human-sample-face.jpg [1,256,256,3]
2021-05-29 18:30:51 STATE: test-node-gpu.js passed: load image: assets/human-sample-face.jpg [1,256,256,3]
2021-05-29 18:30:52 STATE: test-node-gpu.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-29 18:30:53 STATE: test-node-gpu.js passed: load image: assets/human-sample-body.jpg [1,1200,1200,3]
2021-05-29 18:30:59 STATE: test-node-gpu.js passed: detect: assets/human-sample-face.jpg default
2021-05-29 18:30:59 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8257162570953369,"class":"person"} {"score":0.73,"keypoints":17}
2021-05-29 18:30:59 DATA:  test-node-gpu.js result: performance: load: 348 total: 5404
2021-05-29 18:30:59 STATE: test-node-gpu.js passed: detect: assets/human-sample-face.jpg default
2021-05-29 18:30:59 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"confidence":1,"age":23.6,"gender":"female"} {"score":0.8257162570953369,"class":"person"} {"score":0.73,"keypoints":17}
2021-05-29 18:30:59 DATA:  test-node-gpu.js result: performance: load: 2 total: 5404
2021-05-29 18:30:59 STATE: test-node-gpu.js passed: detect: assets/human-sample-body.jpg default
2021-05-29 18:30:59 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":28.5,"gender":"female"} {"score":0.7273815870285034,"class":"person"} {"score":0.93,"keypoints":17}
2021-05-29 18:30:59 DATA:  test-node-gpu.js result: performance: load: 348 total: 5404
2021-05-29 18:30:59 STATE: test-node-gpu.js passed: detect: assets/human-sample-body.jpg default
2021-05-29 18:30:59 DATA:  test-node-gpu.js result: face: 1 body: 1 hand: 0 gesture: 3 object: 1 person: 1 {"confidence":1,"age":28.5,"gender":"female"} {"score":0.7273815870285034,"class":"person"} {"score":0.93,"keypoints":17}
2021-05-29 18:30:59 DATA:  test-node-gpu.js result: performance: load: 2 total: 5404
2021-05-29 18:30:59 INFO:  test-node-gpu.js test complete: 19062 ms
2021-05-29 18:30:59 INFO:  test-node-wasm.js start
2021-05-29 18:30:59 ERROR: test-node-wasm.js failed: model server: request to http://localhost:10030/models/ failed, reason: connect ECONNREFUSED 127.0.0.1:10030
2021-05-29 18:30:59 ERROR: test-node-wasm.js aborting test
2021-05-29 18:30:59 INFO:  status: {"passed":46,"failed":1}

2
types/object/centernet.d.ts vendored
View File

@ -3,4 +3,4 @@
*/
import { Item } from '../result';
export declare function load(config: any): Promise<any>;
export declare function predict(image: any, config: any): Promise<Item[]>;
export declare function predict(input: any, config: any): Promise<Item[]>;

2
wiki

@ -1 +1 @@
Subproject commit 317a8fc76cd933cc38f59948ffade324fc8f1df2
Subproject commit 78e6de4516ab49f47a906ec7778073b2dbbfed3f