mirror of https://github.com/vladmandic/human
407 lines
18 KiB
JavaScript
407 lines
18 KiB
JavaScript
import Human from '../dist/human.esm.js';
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import draw from './draw.js';
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import Menu from './menu.js';
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const userConfig = {}; // add any user configuration overrides
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const human = new Human(userConfig);
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// ui options
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const ui = {
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baseColor: 'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel
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baseBackground: 'rgba(50, 50, 50, 1)', // 'grey'
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baseLabel: 'rgba(173, 216, 230, 0.9)', // 'lightblue' with dark alpha channel
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baseFontProto: 'small-caps {size} "Segoe UI"',
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baseLineWidth: 12,
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baseLineHeightProto: 2,
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crop: true,
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columns: 2,
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busy: false,
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facing: true,
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useWorker: false,
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worker: 'demo/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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drawBoxes: true,
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drawPoints: false,
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drawPolygons: true,
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fillPolygons: false,
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useDepth: true,
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console: true,
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maxFrames: 10,
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modelsPreload: true,
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modelsWarmup: true,
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menuWidth: 0,
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menuHeight: 0,
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camera: {},
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fps: [],
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};
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// global variables
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let menu;
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let menuFX;
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let worker;
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let timeStamp;
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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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const log = (...msg) => {
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// eslint-disable-next-line no-console
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if (ui.console) console.log(...msg);
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};
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const status = (msg) => {
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// eslint-disable-next-line no-console
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document.getElementById('status').innerText = msg;
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};
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// draws processed results and starts processing of a next frame
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function drawResults(input, result, canvas) {
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// update fps data
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const elapsed = performance.now() - timeStamp;
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ui.fps.push(1000 / elapsed);
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if (ui.fps.length > ui.maxFrames) ui.fps.shift();
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// enable for continous performance monitoring
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// console.log(result.performance);
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// immediate loop before we even draw results, but limit frame rate to 30
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if (input.srcObject) {
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// eslint-disable-next-line no-use-before-define
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if (elapsed > 33) requestAnimationFrame(() => runHumanDetect(input, canvas));
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// eslint-disable-next-line no-use-before-define
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else setTimeout(() => runHumanDetect(input, canvas), 33 - elapsed);
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}
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// draw fps chart
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menu.updateChart('FPS', ui.fps);
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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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draw.face(result.face, canvas, ui, human.facemesh.triangulation);
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draw.body(result.body, canvas, ui);
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draw.hand(result.hand, canvas, ui);
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draw.gesture(result.gesture, canvas, ui);
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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 avg = Math.trunc(10 * ui.fps.reduce((a, b) => a + b) / ui.fps.length) / 10;
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const warning = (ui.fps.length > 5) && (avg < 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} | resolution: ${ui.camera.width} x ${ui.camera.height} ${processing}<br>
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backend: ${human.tf.getBackend()} | ${memory}<br>
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performance: ${str(result.performance)} FPS:${avg}<br>
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${warning}
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`;
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}
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// setup webcam
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async function setupCamera() {
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if (ui.busy) return null;
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ui.busy = true;
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const video = document.getElementById('video');
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const canvas = document.getElementById('canvas');
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const output = document.getElementById('log');
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const live = video.srcObject ? ((video.srcObject.getVideoTracks()[0].readyState === 'live') && (video.readyState > 2) && (!video.paused)) : false;
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let msg = '';
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status('setting up camera');
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// setup webcam. note that navigator.mediaDevices requires that page is accessed via https
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if (!navigator.mediaDevices) {
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msg = 'camera access not supported';
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output.innerText += `\n${msg}`;
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log(msg);
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status(msg);
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return null;
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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: {
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facingMode: ui.facing ? 'user' : 'environment',
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resizeMode: ui.crop ? 'crop-and-scale' : 'none',
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width: { ideal: window.innerWidth },
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height: { ideal: window.innerHeight },
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},
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};
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try {
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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 };
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stream = await navigator.mediaDevices.getUserMedia(constraints);
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} catch (err) {
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if (err.name === 'PermissionDeniedError') 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';
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output.innerText += `\n${msg}`;
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status(msg);
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log(err);
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}
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if (stream) video.srcObject = stream;
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else return null;
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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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const size = 14 + (6 * canvas.width / window.innerWidth);
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ui.baseFont = ui.baseFontProto.replace(/{size}/, `${size}px`);
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if (live) video.play();
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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(video);
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};
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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) {
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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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worker.warned = false;
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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 (!worker.warned) {
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log('warning: cannot transfer canvas from worked thread');
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log('warning: image will not show filter effects');
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worker.warned = true;
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}
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drawResults(input, msg.data.result, canvas);
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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 }, [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) {
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timeStamp = performance.now();
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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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// 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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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 = new OffscreenCanvas(canvas.width, 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);
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} else {
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human.detect(input, userConfig).then((result) => {
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if (result.error) log(result.error);
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else drawResults(input, result, canvas);
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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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timeStamp = performance.now();
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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:', 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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drawResults(image, result, canvas);
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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 = canvas.height / (window.innerWidth / thumb.width);
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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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human.config.videoOptimized = true;
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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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ui.baseLineHeight = ui.baseLineHeightProto;
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if ((video.srcObject !== null) && !video.paused) {
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document.getElementById('play').style.display = 'block';
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status('paused');
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video.pause();
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} else {
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await setupCamera();
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document.getElementById('play').style.display = 'none';
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status('');
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video.play();
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}
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runHumanDetect(video, canvas);
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}
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// just initialize everything and call main function
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async function detectSampleImages() {
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document.getElementById('play').style.display = 'none';
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human.config.videoOptimized = false;
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const size = 12 + Math.trunc(12 * ui.columns * window.innerWidth / document.body.clientWidth);
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ui.baseFont = ui.baseFontProto.replace(/{size}/, `${size}px`);
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ui.baseLineHeight = ui.baseLineHeightProto * ui.columns;
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document.getElementById('canvas').style.display = 'none';
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document.getElementById('samples-container').style.display = 'block';
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log('Running detection of sample images');
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status('processing images');
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document.getElementById('samples-container').innerHTML = '';
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for (const sample of ui.samples) await processImage(sample);
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status('');
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}
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function setupMenu() {
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menu = new Menu(document.body, '', { top: '1rem', right: '1rem' });
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const btn = menu.addButton('start video', 'pause video', () => detectVideo());
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menu.addButton('process images', 'process images', () => detectSampleImages());
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document.getElementById('play').addEventListener('click', () => btn.click());
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menu.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menu.addList('backend', ['cpu', 'webgl', 'wasm'], human.config.backend, (val) => human.config.backend = val);
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menu.addBool('async operations', human.config, 'async', (val) => human.config.async = val);
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menu.addBool('enable profiler', human.config, 'profile', (val) => human.config.profile = val);
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menu.addBool('memory shield', human.config, 'deallocate', (val) => human.config.deallocate = val);
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menu.addBool('use web worker', ui, 'useWorker');
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menu.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menu.addLabel('enabled models');
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menu.addBool('face detect', human.config.face, 'enabled');
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menu.addBool('face mesh', human.config.face.mesh, 'enabled');
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menu.addBool('face iris', human.config.face.iris, 'enabled');
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menu.addBool('face age', human.config.face.age, 'enabled');
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menu.addBool('face gender', human.config.face.gender, 'enabled');
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menu.addBool('face emotion', human.config.face.emotion, 'enabled');
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menu.addBool('body pose', human.config.body, 'enabled');
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menu.addBool('hand pose', human.config.hand, 'enabled');
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menu.addBool('gesture analysis', human.config.gesture, 'enabled');
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menu.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menu.addLabel('model parameters');
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menu.addRange('max objects', human.config.face.detector, 'maxFaces', 1, 50, 1, (val) => {
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human.config.face.detector.maxFaces = parseInt(val);
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human.config.body.maxDetections = parseInt(val);
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human.config.hand.maxHands = parseInt(val);
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});
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menu.addRange('skip frames', human.config.face.detector, 'skipFrames', 0, 50, 1, (val) => {
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human.config.face.detector.skipFrames = parseInt(val);
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human.config.face.emotion.skipFrames = parseInt(val);
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human.config.face.age.skipFrames = parseInt(val);
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human.config.hand.skipFrames = parseInt(val);
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});
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menu.addRange('min confidence', human.config.face.detector, 'minConfidence', 0.0, 1.0, 0.05, (val) => {
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human.config.face.detector.minConfidence = parseFloat(val);
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human.config.face.gender.minConfidence = parseFloat(val);
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human.config.face.emotion.minConfidence = parseFloat(val);
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human.config.hand.minConfidence = parseFloat(val);
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});
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menu.addRange('score threshold', human.config.face.detector, 'scoreThreshold', 0.1, 1.0, 0.05, (val) => {
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human.config.face.detector.scoreThreshold = parseFloat(val);
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human.config.hand.scoreThreshold = parseFloat(val);
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human.config.body.scoreThreshold = parseFloat(val);
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});
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menu.addRange('overlap', human.config.face.detector, 'iouThreshold', 0.1, 1.0, 0.05, (val) => {
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human.config.face.detector.iouThreshold = parseFloat(val);
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human.config.hand.iouThreshold = parseFloat(val);
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});
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menu.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menu.addChart('FPS', 'FPS');
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menuFX = new Menu(document.body, '', { top: '1rem', right: '18rem' });
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menuFX.addLabel('ui options');
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menuFX.addBool('crop & scale', ui, 'crop', () => setupCamera());
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menuFX.addBool('camera front/back', ui, 'facing', () => setupCamera());
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menuFX.addBool('use 3D depth', ui, 'useDepth');
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menuFX.addBool('draw boxes', ui, 'drawBoxes');
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menuFX.addBool('draw polygons', ui, 'drawPolygons');
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menuFX.addBool('Fill Polygons', ui, 'fillPolygons');
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menuFX.addBool('draw points', ui, 'drawPoints');
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menuFX.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menuFX.addLabel('image processing');
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menuFX.addBool('enabled', human.config.filter, 'enabled');
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ui.menuWidth = menuFX.addRange('image width', human.config.filter, 'width', 0, 3840, 10, (val) => human.config.filter.width = parseInt(val));
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ui.menuHeight = menuFX.addRange('image height', human.config.filter, 'height', 0, 2160, 10, (val) => human.config.filter.height = parseInt(val));
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menuFX.addRange('brightness', human.config.filter, 'brightness', -1.0, 1.0, 0.05, (val) => human.config.filter.brightness = parseFloat(val));
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menuFX.addRange('contrast', human.config.filter, 'contrast', -1.0, 1.0, 0.05, (val) => human.config.filter.contrast = parseFloat(val));
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menuFX.addRange('sharpness', human.config.filter, 'sharpness', 0, 1.0, 0.05, (val) => human.config.filter.sharpness = parseFloat(val));
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menuFX.addRange('blur', human.config.filter, 'blur', 0, 20, 1, (val) => human.config.filter.blur = parseInt(val));
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menuFX.addRange('saturation', human.config.filter, 'saturation', -1.0, 1.0, 0.05, (val) => human.config.filter.saturation = parseFloat(val));
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menuFX.addRange('hue', human.config.filter, 'hue', 0, 360, 5, (val) => human.config.filter.hue = parseInt(val));
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menuFX.addRange('pixelate', human.config.filter, 'pixelate', 0, 32, 1, (val) => human.config.filter.pixelate = parseInt(val));
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menuFX.addBool('negative', human.config.filter, 'negative');
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menuFX.addBool('sepia', human.config.filter, 'sepia');
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menuFX.addBool('vintage', human.config.filter, 'vintage');
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menuFX.addBool('kodachrome', human.config.filter, 'kodachrome');
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menuFX.addBool('technicolor', human.config.filter, 'technicolor');
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menuFX.addBool('polaroid', human.config.filter, 'polaroid');
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}
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async function main() {
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log('Human: demo starting ...');
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setupMenu();
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document.getElementById('log').innerText = `Human: version ${human.version} TensorFlow/JS: version ${human.tf.version_core}`;
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// this is not required, just pre-loads all models
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if (ui.modelsPreload) {
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status('loading');
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await human.load(userConfig);
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}
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// this is not required, just pre-warms all models for faster initial inference
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if (ui.modelsWarmup) {
|
|
status('initializing');
|
|
await human.warmup(userConfig);
|
|
}
|
|
status('human: ready');
|
|
document.getElementById('loader').style.display = 'none';
|
|
document.getElementById('play').style.display = 'block';
|
|
}
|
|
|
|
window.onload = main;
|
|
window.onresize = setupCamera;
|