mirror of https://github.com/vladmandic/human
664 lines
31 KiB
JavaScript
664 lines
31 KiB
JavaScript
// @ts-nocheck
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/* global tf */
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import Human from '../dist/human.esm.js'; // equivalent of @vladmandic/human
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// import Human from '../dist/human.esm-nobundle.js'; // this requires that tf is loaded manually and bundled before human can be used
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import Menu from './helpers/menu.js';
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import GLBench from './helpers/gl-bench.js';
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import webRTC from './helpers/webrtc.js';
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const userConfig = {};
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let human;
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/*
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const userConfig = {
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backend: 'humangl',
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async: false,
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profile: false,
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warmup: 'full',
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videoOptimized: false,
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filter: {
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enabled: true,
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flip: false,
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},
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face: { enabled: true,
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mesh: { enabled: true },
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iris: { enabled: true },
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description: { enabled: false },
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emotion: { enabled: false },
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},
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hand: { enabled: false },
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gesture: { enabled: true },
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body: { enabled: false },
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// body: { enabled: true, modelPath: 'blazepose.json' },
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// object: { enabled: true },
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};
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*/
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// ui options
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const ui = {
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baseBackground: 'rgba(50, 50, 50, 1)', // 'grey'
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crop: true, // video mode crop to size or leave full frame
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columns: 2, // when processing sample images create this many columns
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facing: true, // camera facing front or back
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useWorker: false, // use web workers for processing
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worker: 'index-worker.js',
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samples: ['../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg'],
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compare: '../assets/sample-me.jpg',
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useWebRTC: false, // use webrtc as camera source instead of local webcam
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webRTCServer: 'http://localhost:8002',
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webRTCStream: 'reowhite',
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console: true, // log messages to browser console
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maxFPSframes: 10, // keep fps history for how many frames
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modelsPreload: true, // preload human models on startup
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modelsWarmup: true, // warmup human models on startup
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busy: false, // internal camera busy flag
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menuWidth: 0, // internal
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menuHeight: 0, // internal
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camera: {}, // internal, holds details of webcam details
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detectFPS: [], // internal, holds fps values for detection performance
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drawFPS: [], // internal, holds fps values for draw performance
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buffered: true, // should output be buffered between frames
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drawWarmup: false, // debug only, should warmup image processing be displayed on startup
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drawThread: null, // internl, perform draw operations in a separate thread
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detectThread: null, // internl, perform detect operations in a separate thread
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framesDraw: 0, // internal, statistics on frames drawn
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framesDetect: 0, // internal, statistics on frames detected
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bench: true, // show gl fps benchmark window
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lastFrame: 0, // time of last frame processing
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viewportSet: false, // internal, has custom viewport been set
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};
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// global variables
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const menu = {};
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let worker;
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let bench;
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let lastDetectedResult = {};
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// helper function: translates json to human readable string
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function str(...msg) {
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if (!Array.isArray(msg)) return msg;
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let line = '';
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for (const entry of msg) {
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if (typeof entry === 'object') line += JSON.stringify(entry).replace(/{|}|"|\[|\]/g, '').replace(/,/g, ', ');
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else line += entry;
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}
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return line;
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}
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// helper function: wrapper around console output
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function log(...msg) {
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const dt = new Date();
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const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;
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// eslint-disable-next-line no-console
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if (ui.console) console.log(ts, ...msg);
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}
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function status(msg) {
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// eslint-disable-next-line no-console
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const div = document.getElementById('status');
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if (div) div.innerText = msg;
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}
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const compare = { enabled: false, original: null };
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async function calcSimmilariry(result) {
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document.getElementById('compare-container').style.display = compare.enabled ? 'block' : 'none';
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if (!compare.enabled) return;
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if (!result || !result.face || result.face[0].embedding) return;
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if (!(result.face.length > 0) || (result.face[0].embedding.length <= 64)) return;
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if (!compare.original) {
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compare.original = result;
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log('setting face compare baseline:', result.face[0]);
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if (result.face[0].tensor) {
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const enhanced = human.enhance(result.face[0]);
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if (enhanced) {
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const c = document.getElementById('orig');
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const squeeze = enhanced.squeeze();
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const norm = squeeze.div(255);
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human.tf.browser.toPixels(norm, c);
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enhanced.dispose();
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squeeze.dispose();
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norm.dispose();
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}
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} else {
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document.getElementById('compare-canvas').getContext('2d').drawImage(compare.original.canvas, 0, 0, 200, 200);
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}
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}
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const similarity = human.similarity(compare.original.face[0].embedding, result.face[0].embedding);
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document.getElementById('similarity').innerText = `similarity: ${Math.trunc(1000 * similarity) / 10}%`;
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}
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// draws processed results and starts processing of a next frame
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let lastDraw = performance.now();
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async function drawResults(input) {
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const result = lastDetectedResult;
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const canvas = document.getElementById('canvas');
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// update draw fps data
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ui.drawFPS.push(1000 / (performance.now() - lastDraw));
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if (ui.drawFPS.length > ui.maxFPSframes) ui.drawFPS.shift();
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lastDraw = performance.now();
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// draw fps chart
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await menu.process.updateChart('FPS', ui.detectFPS);
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// get updated canvas
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if (ui.buffered || !result.canvas) {
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const image = await human.image(input);
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result.canvas = image.canvas;
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human.tf.dispose(image.tensor);
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}
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// draw image from video
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const ctx = canvas.getContext('2d');
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ctx.fillStyle = ui.baseBackground;
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ctx.fillRect(0, 0, canvas.width, canvas.height);
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if (result.canvas) {
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if (result.canvas.width !== canvas.width) canvas.width = result.canvas.width;
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if (result.canvas.height !== canvas.height) canvas.height = result.canvas.height;
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ctx.drawImage(result.canvas, 0, 0, result.canvas.width, result.canvas.height, 0, 0, result.canvas.width, result.canvas.height);
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} else {
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ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);
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}
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// draw all results
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human.draw.face(canvas, result.face);
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human.draw.body(canvas, result.body);
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human.draw.hand(canvas, result.hand);
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human.draw.object(canvas, result.object);
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human.draw.gesture(canvas, result.gesture);
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await calcSimmilariry(result);
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// update log
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const engine = human.tf.engine();
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const gpu = engine.backendInstance ? `gpu: ${(engine.backendInstance.numBytesInGPU ? engine.backendInstance.numBytesInGPU : 0).toLocaleString()} bytes` : '';
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const memory = `system: ${engine.state.numBytes.toLocaleString()} bytes ${gpu} | tensors: ${engine.state.numTensors.toLocaleString()}`;
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const processing = result.canvas ? `processing: ${result.canvas.width} x ${result.canvas.height}` : '';
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const avgDetect = Math.trunc(10 * ui.detectFPS.reduce((a, b) => a + b, 0) / ui.detectFPS.length) / 10;
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const avgDraw = Math.trunc(10 * ui.drawFPS.reduce((a, b) => a + b, 0) / ui.drawFPS.length) / 10;
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const warning = (ui.detectFPS.length > 5) && (avgDetect < 5) ? '<font color="lightcoral">warning: your performance is low: try switching to higher performance backend, lowering resolution or disabling some models</font>' : '';
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document.getElementById('log').innerHTML = `
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video: ${ui.camera.name} | facing: ${ui.camera.facing} | screen: ${window.innerWidth} x ${window.innerHeight} camera: ${ui.camera.width} x ${ui.camera.height} ${processing}<br>
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backend: ${human.tf.getBackend()} | ${memory}<br>
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performance: ${str(result.performance)}ms FPS process:${avgDetect} refresh:${avgDraw}<br>
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${warning}<br>
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`;
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ui.framesDraw++;
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ui.lastFrame = performance.now();
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// if buffered, immediate loop but limit frame rate although it's going to run slower as JS is singlethreaded
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if (ui.buffered) {
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ui.drawThread = requestAnimationFrame(() => drawResults(input, canvas));
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} else if (!ui.buffered && ui.drawThread) {
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log('stopping buffered refresh');
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cancelAnimationFrame(ui.drawThread);
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ui.drawThread = null;
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}
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}
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// setup webcam
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async function setupCamera() {
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if (ui.busy) return null;
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ui.busy = true;
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const video = document.getElementById('video');
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const canvas = document.getElementById('canvas');
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const output = document.getElementById('log');
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if (ui.useWebRTC) {
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status('setting up webrtc connection');
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try {
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video.onloadeddata = () => ui.camera = { name: ui.webRTCStream, width: video.videoWidth, height: video.videoHeight, facing: 'default' };
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await webRTC(ui.webRTCServer, ui.webRTCStream, video);
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} catch (err) {
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log(err);
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} finally {
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status('');
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}
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return '';
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}
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const live = video.srcObject ? ((video.srcObject.getVideoTracks()[0].readyState === 'live') && (video.readyState > 2) && (!video.paused)) : false;
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let msg = '';
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status('setting up camera');
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// setup webcam. note that navigator.mediaDevices requires that page is accessed via https
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if (!navigator.mediaDevices) {
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msg = 'camera access not supported';
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output.innerText += `\n${msg}`;
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log(msg);
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status(msg);
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ui.busy = false;
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return msg;
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}
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let stream;
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const constraints = {
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audio: false,
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video: { facingMode: ui.facing ? 'user' : 'environment', resizeMode: ui.crop ? 'crop-and-scale' : 'none' },
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};
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if (window.innerWidth > window.innerHeight) constraints.video.width = { ideal: window.innerWidth };
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else constraints.video.height = { ideal: (window.innerHeight - document.getElementById('menubar').offsetHeight) };
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try {
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stream = await navigator.mediaDevices.getUserMedia(constraints);
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} catch (err) {
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if (err.name === 'PermissionDeniedError' || err.name === 'NotAllowedError') msg = 'camera permission denied';
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else if (err.name === 'SourceUnavailableError') msg = 'camera not available';
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else msg = `camera error: ${err.message || err}`;
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output.innerText += `\n${msg}`;
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status(msg);
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log('camera error:', err);
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ui.busy = false;
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return msg;
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}
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if (stream) video.srcObject = stream;
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else {
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ui.busy = false;
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return 'camera stream empty';
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}
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const track = stream.getVideoTracks()[0];
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const settings = track.getSettings();
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// log('camera constraints:', constraints, 'window:', { width: window.innerWidth, height: window.innerHeight }, 'settings:', settings, 'track:', track);
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ui.camera = { name: track.label.toLowerCase(), width: settings.width, height: settings.height, facing: settings.facingMode === 'user' ? 'front' : 'back' };
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return new Promise((resolve) => {
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video.onloadeddata = async () => {
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video.width = video.videoWidth;
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video.height = video.videoHeight;
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canvas.width = video.width;
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canvas.height = video.height;
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canvas.style.width = canvas.width > canvas.height ? '100vw' : '';
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canvas.style.height = canvas.width > canvas.height ? '' : '100vh';
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ui.menuWidth.input.setAttribute('value', video.width);
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ui.menuHeight.input.setAttribute('value', video.height);
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// silly font resizing for paint-on-canvas since viewport can be zoomed
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if (live) video.play();
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// eslint-disable-next-line no-use-before-define
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if (live && !ui.detectThread) runHumanDetect(video, canvas);
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ui.busy = false;
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// do once more because onresize events can be delayed or skipped
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// if (video.width > window.innerWidth) await setupCamera();
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status('');
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resolve();
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};
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});
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}
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function initPerfMonitor() {
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if (!bench) {
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const gl = null;
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// cosnt gl = human.tf.engine().backend.gpgpu.gl;
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// if (!gl) log('bench cannot get tensorflow webgl context');
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bench = new GLBench(gl, {
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trackGPU: false, // this is really slow
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chartHz: 20,
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chartLen: 20,
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});
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bench.begin();
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}
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}
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// wrapper for worker.postmessage that creates worker if one does not exist
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function webWorker(input, image, canvas, timestamp) {
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if (!worker) {
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// create new webworker and add event handler only once
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log('creating worker thread');
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worker = new Worker(ui.worker, { type: 'module' });
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// after receiving message from webworker, parse&draw results and send new frame for processing
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worker.addEventListener('message', (msg) => {
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if (msg.data.result.performance && msg.data.result.performance.total) ui.detectFPS.push(1000 / msg.data.result.performance.total);
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if (ui.detectFPS.length > ui.maxFPSframes) ui.detectFPS.shift();
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if (ui.bench) {
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if (!bench) initPerfMonitor();
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bench.nextFrame(timestamp);
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}
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if (document.getElementById('gl-bench')) document.getElementById('gl-bench').style.display = ui.bench ? 'block' : 'none';
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lastDetectedResult = msg.data.result;
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ui.framesDetect++;
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if (!ui.drawThread) drawResults(input);
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// eslint-disable-next-line no-use-before-define
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ui.detectThread = requestAnimationFrame((now) => runHumanDetect(input, canvas, now));
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});
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}
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// pass image data as arraybuffer to worker by reference to avoid copy
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worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, userConfig }, [image.data.buffer]);
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}
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// main processing function when input is webcam, can use direct invocation or web worker
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function runHumanDetect(input, canvas, timestamp) {
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// if live video
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const live = input.srcObject && (input.srcObject.getVideoTracks()[0].readyState === 'live') && (input.readyState > 2) && (!input.paused);
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if (!live && input.srcObject) {
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// stop ui refresh
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if (ui.drawThread) cancelAnimationFrame(ui.drawThread);
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if (ui.detectThread) cancelAnimationFrame(ui.detectThread);
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ui.drawThread = null;
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ui.detectThread = null;
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// if we want to continue and camera not ready, retry in 0.5sec, else just give up
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if (input.paused) log('camera paused');
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else if ((input.srcObject.getVideoTracks()[0].readyState === 'live') && (input.readyState <= 2)) setTimeout(() => runHumanDetect(input, canvas), 500);
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else log(`camera not ready: track state: ${input.srcObject.getVideoTracks()[0].readyState} stream state: ${input.readyState}`);
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clearTimeout(ui.drawThread);
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ui.drawThread = null;
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log('frame statistics: process:', ui.framesDetect, 'refresh:', ui.framesDraw);
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log('memory', human.tf.engine().memory());
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return;
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}
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status('');
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if (ui.useWorker) {
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// get image data from video as we cannot send html objects to webworker
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const offscreen = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(canvas.width, canvas.height) : document.createElement('canvas');
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offscreen.width = canvas.width;
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offscreen.height = canvas.height;
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const ctx = offscreen.getContext('2d');
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ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);
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const data = ctx.getImageData(0, 0, canvas.width, canvas.height);
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// perform detection in worker
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webWorker(input, data, canvas, userConfig, timestamp);
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} else {
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human.detect(input, userConfig).then((result) => {
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if (result.performance && result.performance.total) ui.detectFPS.push(1000 / result.performance.total);
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if (ui.detectFPS.length > ui.maxFPSframes) ui.detectFPS.shift();
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if (ui.bench) {
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if (!bench) initPerfMonitor();
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bench.nextFrame(timestamp);
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}
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if (document.getElementById('gl-bench')) document.getElementById('gl-bench').style.display = ui.bench ? 'block' : 'none';
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if (result.error) {
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log(result.error);
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document.getElementById('log').innerText += `\nHuman error: ${result.error}`;
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} else {
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lastDetectedResult = result;
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if (!ui.drawThread) drawResults(input);
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ui.framesDetect++;
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ui.detectThread = requestAnimationFrame((now) => runHumanDetect(input, canvas, now));
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}
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});
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}
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}
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// main processing function when input is image, can use direct invocation or web worker
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async function processImage(input) {
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return new Promise((resolve) => {
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const image = new Image();
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image.onload = async () => {
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log('processing image:', encodeURI(image.src));
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const canvas = document.getElementById('canvas');
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image.width = image.naturalWidth;
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image.height = image.naturalHeight;
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canvas.width = human.config.filter.width && human.config.filter.width > 0 ? human.config.filter.width : image.naturalWidth;
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canvas.height = human.config.filter.height && human.config.filter.height > 0 ? human.config.filter.height : image.naturalHeight;
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const result = await human.detect(image, userConfig);
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lastDetectedResult = result;
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await drawResults(image);
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const thumb = document.createElement('canvas');
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thumb.className = 'thumbnail';
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thumb.width = window.innerWidth / (ui.columns + 0.1);
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thumb.height = thumb.width * canvas.height / canvas.width;
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if (result.face && result.face.length > 0) {
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thumb.title = result.face.map((a, i) => `#${i} face: ${Math.trunc(100 * a.faceConfidence)}% box: ${Math.trunc(100 * a.boxConfidence)}% age: ${Math.trunc(a.age)} gender: ${Math.trunc(100 * a.genderConfidence)}% ${a.gender}`).join(' | ');
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} else {
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thumb.title = 'no face detected';
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}
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const ctx = thumb.getContext('2d');
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ctx.drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, thumb.width, thumb.height);
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document.getElementById('samples-container').appendChild(thumb);
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image.src = '';
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resolve(true);
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};
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image.src = input;
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});
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}
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// just initialize everything and call main function
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async function detectVideo() {
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document.getElementById('samples-container').style.display = 'none';
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document.getElementById('canvas').style.display = 'block';
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const video = document.getElementById('video');
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const canvas = document.getElementById('canvas');
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if ((video.srcObject !== null) && !video.paused) {
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document.getElementById('play').style.display = 'block';
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document.getElementById('btnStartText').innerHTML = 'start video';
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status('paused');
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video.pause();
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} else {
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const cameraError = await setupCamera();
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if (!cameraError) {
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document.getElementById('play').style.display = 'none';
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for (const m of Object.values(menu)) m.hide();
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status('');
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document.getElementById('btnStartText').innerHTML = 'pause video';
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await video.play();
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if (!ui.detectThread) runHumanDetect(video, canvas);
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} else {
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status(cameraError);
|
|
}
|
|
}
|
|
}
|
|
|
|
// just initialize everything and call main function
|
|
async function detectSampleImages() {
|
|
userConfig.videoOptimized = false; // force disable video optimizations
|
|
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');
|
|
status('processing images');
|
|
document.getElementById('samples-container').innerHTML = '';
|
|
for (const m of Object.values(menu)) m.hide();
|
|
for (const image of ui.samples) await processImage(image);
|
|
status('');
|
|
}
|
|
|
|
function setupMenu() {
|
|
const x = [`${document.getElementById('btnDisplay').offsetLeft}px`, `${document.getElementById('btnImage').offsetLeft}px`, `${document.getElementById('btnProcess').offsetLeft}px`, `${document.getElementById('btnModel').offsetLeft}px`];
|
|
|
|
const top = `${document.getElementById('menubar').clientHeight}px`;
|
|
|
|
menu.display = new Menu(document.body, '', { top, left: x[0] });
|
|
menu.display.addBool('perf monitor', ui, 'bench', (val) => ui.bench = val);
|
|
menu.display.addBool('buffer output', ui, 'buffered', (val) => ui.buffered = val);
|
|
menu.display.addBool('crop & scale', ui, 'crop', (val) => {
|
|
ui.crop = val;
|
|
setupCamera();
|
|
});
|
|
menu.display.addBool('camera facing', ui, 'facing', (val) => {
|
|
ui.facing = val;
|
|
setupCamera();
|
|
});
|
|
menu.display.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.display.addBool('use depth', human.draw.options, 'useDepth');
|
|
menu.display.addBool('use curves', human.draw.options, 'useCurves');
|
|
menu.display.addBool('print labels', human.draw.options, 'drawLabels');
|
|
menu.display.addBool('draw points', human.draw.options, 'drawPoints');
|
|
menu.display.addBool('draw boxes', human.draw.options, 'drawBoxes');
|
|
menu.display.addBool('draw polygons', human.draw.options, 'drawPolygons');
|
|
menu.display.addBool('fill polygons', human.draw.options, 'fillPolygons');
|
|
|
|
menu.image = new Menu(document.body, '', { top, left: x[1] });
|
|
menu.image.addBool('enabled', human.config.filter, 'enabled', (val) => human.config.filter.enabled = val);
|
|
ui.menuWidth = menu.image.addRange('image width', human.config.filter, 'width', 0, 3840, 10, (val) => human.config.filter.width = parseInt(val));
|
|
ui.menuHeight = menu.image.addRange('image height', human.config.filter, 'height', 0, 2160, 10, (val) => human.config.filter.height = parseInt(val));
|
|
menu.image.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.image.addRange('brightness', human.config.filter, 'brightness', -1.0, 1.0, 0.05, (val) => human.config.filter.brightness = parseFloat(val));
|
|
menu.image.addRange('contrast', human.config.filter, 'contrast', -1.0, 1.0, 0.05, (val) => human.config.filter.contrast = parseFloat(val));
|
|
menu.image.addRange('sharpness', human.config.filter, 'sharpness', 0, 1.0, 0.05, (val) => human.config.filter.sharpness = parseFloat(val));
|
|
menu.image.addRange('blur', human.config.filter, 'blur', 0, 20, 1, (val) => human.config.filter.blur = parseInt(val));
|
|
menu.image.addRange('saturation', human.config.filter, 'saturation', -1.0, 1.0, 0.05, (val) => human.config.filter.saturation = parseFloat(val));
|
|
menu.image.addRange('hue', human.config.filter, 'hue', 0, 360, 5, (val) => human.config.filter.hue = parseInt(val));
|
|
menu.image.addRange('pixelate', human.config.filter, 'pixelate', 0, 32, 1, (val) => human.config.filter.pixelate = parseInt(val));
|
|
menu.image.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.image.addBool('negative', human.config.filter, 'negative', (val) => human.config.filter.negative = val);
|
|
menu.image.addBool('sepia', human.config.filter, 'sepia', (val) => human.config.filter.sepia = val);
|
|
menu.image.addBool('vintage', human.config.filter, 'vintage', (val) => human.config.filter.vintage = val);
|
|
menu.image.addBool('kodachrome', human.config.filter, 'kodachrome', (val) => human.config.filter.kodachrome = val);
|
|
menu.image.addBool('technicolor', human.config.filter, 'technicolor', (val) => human.config.filter.technicolor = val);
|
|
menu.image.addBool('polaroid', human.config.filter, 'polaroid', (val) => human.config.filter.polaroid = val);
|
|
|
|
menu.process = new Menu(document.body, '', { top, left: x[2] });
|
|
menu.process.addList('backend', ['cpu', 'webgl', 'wasm', 'humangl'], human.config.backend, (val) => human.config.backend = val);
|
|
menu.process.addBool('async operations', human.config, 'async', (val) => human.config.async = val);
|
|
// menu.process.addBool('enable profiler', human.config, 'profile', (val) => human.config.profile = val);
|
|
// menu.process.addBool('memory shield', human.config, 'deallocate', (val) => human.config.deallocate = val);
|
|
menu.process.addBool('use web worker', ui, 'useWorker');
|
|
menu.process.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.process.addLabel('model parameters');
|
|
menu.process.addRange('max objects', human.config.face.detector, 'maxFaces', 1, 50, 1, (val) => {
|
|
human.config.face.detector.maxFaces = parseInt(val);
|
|
human.config.body.maxDetections = parseInt(val);
|
|
human.config.hand.maxHands = parseInt(val);
|
|
});
|
|
menu.process.addRange('skip frames', human.config.face.detector, 'skipFrames', 0, 50, 1, (val) => {
|
|
human.config.face.detector.skipFrames = parseInt(val);
|
|
human.config.face.emotion.skipFrames = parseInt(val);
|
|
human.config.face.age.skipFrames = parseInt(val);
|
|
human.config.hand.skipFrames = parseInt(val);
|
|
});
|
|
menu.process.addRange('min confidence', human.config.face.detector, 'minConfidence', 0.0, 1.0, 0.05, (val) => {
|
|
human.config.face.detector.minConfidence = parseFloat(val);
|
|
human.config.face.gender.minConfidence = parseFloat(val);
|
|
human.config.face.emotion.minConfidence = parseFloat(val);
|
|
human.config.hand.minConfidence = parseFloat(val);
|
|
});
|
|
menu.process.addRange('score threshold', human.config.face.detector, 'scoreThreshold', 0.1, 1.0, 0.05, (val) => {
|
|
human.config.face.detector.scoreThreshold = parseFloat(val);
|
|
human.config.hand.scoreThreshold = parseFloat(val);
|
|
human.config.body.scoreThreshold = parseFloat(val);
|
|
});
|
|
menu.process.addRange('overlap', human.config.face.detector, 'iouThreshold', 0.1, 1.0, 0.05, (val) => {
|
|
human.config.face.detector.iouThreshold = parseFloat(val);
|
|
human.config.hand.iouThreshold = parseFloat(val);
|
|
});
|
|
menu.process.addBool('rotation detection', human.config.face.detector, 'rotation', (val) => {
|
|
human.config.face.detector.rotation = val;
|
|
human.config.hand.rotation = val;
|
|
});
|
|
menu.process.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.process.addButton('process sample images', 'process images', () => detectSampleImages());
|
|
menu.process.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.process.addChart('FPS', 'FPS');
|
|
|
|
menu.models = new Menu(document.body, '', { top, left: x[3] });
|
|
menu.models.addBool('face detect', human.config.face, 'enabled', (val) => human.config.face.enabled = val);
|
|
menu.models.addBool('face mesh', human.config.face.mesh, 'enabled', (val) => human.config.face.mesh.enabled = val);
|
|
menu.models.addBool('face iris', human.config.face.iris, 'enabled', (val) => human.config.face.iris.enabled = val);
|
|
menu.models.addBool('face description', human.config.face.description, 'enabled', (val) => human.config.face.age.description = val);
|
|
// menu.models.addBool('face age', human.config.face.age, 'enabled', (val) => human.config.face.age.enabled = val);
|
|
// menu.models.addBool('face gender', human.config.face.gender, 'enabled', (val) => human.config.face.gender.enabled = val);
|
|
menu.models.addBool('face emotion', human.config.face.emotion, 'enabled', (val) => human.config.face.emotion.enabled = val);
|
|
menu.models.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.models.addBool('body pose', human.config.body, 'enabled', (val) => human.config.body.enabled = val);
|
|
menu.models.addBool('hand pose', human.config.hand, 'enabled', (val) => human.config.hand.enabled = val);
|
|
menu.models.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.models.addBool('gestures', human.config.gesture, 'enabled', (val) => human.config.gesture.enabled = val);
|
|
menu.models.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.models.addBool('object detection', human.config.object, 'enabled', (val) => human.config.object.enabled = val);
|
|
menu.models.addHTML('<hr style="border-style: inset; border-color: dimgray">');
|
|
menu.models.addBool('face compare', compare, 'enabled', (val) => {
|
|
compare.enabled = val;
|
|
compare.original = null;
|
|
});
|
|
|
|
document.getElementById('btnDisplay').addEventListener('click', (evt) => menu.display.toggle(evt));
|
|
document.getElementById('btnImage').addEventListener('click', (evt) => menu.image.toggle(evt));
|
|
document.getElementById('btnProcess').addEventListener('click', (evt) => menu.process.toggle(evt));
|
|
document.getElementById('btnModel').addEventListener('click', (evt) => menu.models.toggle(evt));
|
|
document.getElementById('btnStart').addEventListener('click', () => detectVideo());
|
|
document.getElementById('play').addEventListener('click', () => detectVideo());
|
|
}
|
|
|
|
async function resize() {
|
|
const viewportScale = Math.min(1, Math.round(100 * window.innerWidth / 960) / 100);
|
|
if (!ui.viewportSet) {
|
|
const viewport = document.querySelector('meta[name=viewport]');
|
|
viewport.setAttribute('content', `width=device-width, shrink-to-fit=yes, minimum-scale=0.2, maximum-scale=2.0, user-scalable=yes, initial-scale=${viewportScale}`);
|
|
ui.viewportSet = true;
|
|
}
|
|
const x = [`${document.getElementById('btnDisplay').offsetLeft}px`, `${document.getElementById('btnImage').offsetLeft}px`, `${document.getElementById('btnProcess').offsetLeft}px`, `${document.getElementById('btnModel').offsetLeft}px`];
|
|
|
|
const top = `${document.getElementById('menubar').clientHeight - 3}px`;
|
|
|
|
menu.display.menu.style.top = top;
|
|
menu.image.menu.style.top = top;
|
|
menu.process.menu.style.top = top;
|
|
menu.models.menu.style.top = top;
|
|
menu.display.menu.style.left = x[0];
|
|
menu.image.menu.style.left = x[1];
|
|
menu.process.menu.style.left = x[2];
|
|
menu.models.menu.style.left = x[3];
|
|
|
|
const fontSize = Math.trunc(10 * (1 - viewportScale)) + 16;
|
|
document.documentElement.style.fontSize = `${fontSize}px`;
|
|
|
|
human.draw.options.font = `small-caps ${fontSize + 4}px "Segoe UI"`;
|
|
|
|
setupCamera();
|
|
}
|
|
|
|
async function drawWarmup(res) {
|
|
const canvas = document.getElementById('canvas');
|
|
canvas.width = res.canvas.width;
|
|
canvas.height = res.canvas.height;
|
|
const ctx = canvas.getContext('2d');
|
|
ctx.drawImage(res.canvas, 0, 0, res.canvas.width, res.canvas.height, 0, 0, canvas.width, canvas.height);
|
|
await human.draw.all(canvas, res);
|
|
}
|
|
|
|
async function main() {
|
|
log('demo starting ...');
|
|
|
|
// parse url search params
|
|
const params = new URLSearchParams(location.search);
|
|
log('url options:', params.toString());
|
|
if (params.has('worker')) {
|
|
ui.useWorker = JSON.parse(params.get('worker'));
|
|
log('overriding worker:', ui.useWorker);
|
|
}
|
|
if (params.has('backend')) {
|
|
userConfig.backend = params.get('backend');
|
|
log('overriding backend:', userConfig.backend);
|
|
}
|
|
if (params.has('preload')) {
|
|
ui.modelsPreload = JSON.parse(params.get('preload'));
|
|
log('overriding preload:', ui.modelsPreload);
|
|
}
|
|
if (params.has('warmup')) {
|
|
ui.modelsWarmup = JSON.parse(params.get('warmup'));
|
|
log('overriding warmup:', ui.modelsWarmup);
|
|
}
|
|
|
|
// create instance of human
|
|
human = new Human(userConfig);
|
|
if (typeof tf !== 'undefined') {
|
|
log('TensorFlow external version:', tf.version);
|
|
human.tf = tf; // use externally loaded version of tfjs
|
|
}
|
|
|
|
// setup main menu
|
|
await setupMenu();
|
|
await resize();
|
|
document.getElementById('log').innerText = `Human: version ${human.version}`;
|
|
|
|
// preload models
|
|
if (ui.modelsPreload && !ui.useWorker) {
|
|
status('loading');
|
|
await human.load(userConfig); // this is not required, just pre-loads all models
|
|
const loaded = Object.keys(human.models).filter((a) => human.models[a]);
|
|
log('demo loaded models:', loaded);
|
|
}
|
|
|
|
// warmup models
|
|
if (ui.modelsWarmup && !ui.useWorker) {
|
|
status('initializing');
|
|
const res = await human.warmup(userConfig); // this is not required, just pre-warms all models for faster initial inference
|
|
if (res && res.canvas && ui.drawWarmup) await drawWarmup(res);
|
|
}
|
|
|
|
// setup camera
|
|
await setupCamera();
|
|
|
|
// ready
|
|
status('human: ready');
|
|
document.getElementById('loader').style.display = 'none';
|
|
document.getElementById('play').style.display = 'block';
|
|
log('demo ready...');
|
|
for (const m of Object.values(menu)) m.hide();
|
|
}
|
|
|
|
window.onload = main;
|
|
window.onresize = resize;
|