mirror of https://github.com/vladmandic/human
complete model refactoring
Vladimir Mandic
parent
0f5ccda33c
commit
2b5901ff55
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@ -355,7 +355,6 @@ config = {
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enlargeFactor: 1.65, // empiric tuning as skeleton prediction prefers hand box with some whitespace
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maxHands: 10, // maximum number of hands detected in the input, should be set to the minimum number for performance
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detector: {
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anchors: '../models/handdetect/anchors.json',
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modelPath: '../models/handdetect/model.json',
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},
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skeleton: {
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After Width: | Height: | Size: 121 KiB |
19
config.js
19
config.js
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@ -46,7 +46,7 @@ export default {
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// face.enabled is required for all face models: detector, mesh, iris, age, gender, emotion
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// (note: module is not loaded until it is required)
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detector: {
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modelPath: '../models/blazeface/back/model.json', // can be 'front' or 'back'.
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modelPath: '../models/blazeface-back.json', // can be 'front' or 'back'.
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// 'front' is optimized for large faces such as front-facing camera and 'back' is optimized for distanct faces.
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inputSize: 256, // fixed value: 128 for front and 256 for 'back'
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maxFaces: 10, // maximum number of faces detected in the input, should be set to the minimum number for performance
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@ -59,18 +59,18 @@ export default {
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},
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mesh: {
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enabled: true,
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modelPath: '../models/facemesh/model.json',
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modelPath: '../models/facemesh.json',
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inputSize: 192, // fixed value
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},
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iris: {
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enabled: true,
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modelPath: '../models/iris/model.json',
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modelPath: '../models/iris.json',
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enlargeFactor: 2.3, // empiric tuning
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inputSize: 64, // fixed value
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},
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age: {
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enabled: true,
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modelPath: '../models/ssrnet-age/imdb/model.json', // can be 'imdb' or 'wiki'
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modelPath: '../models/ssrnet-age-imdb.json', // can be 'imdb' or 'wiki'
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// which determines training set for model
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inputSize: 64, // fixed value
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skipFrames: 10, // how many frames to go without re-running the detector, only used for video inputs
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@ -78,19 +78,19 @@ export default {
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gender: {
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enabled: true,
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minConfidence: 0.8, // threshold for discarding a prediction
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modelPath: '../models/ssrnet-gender/imdb/model.json',
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modelPath: '../models/ssrnet-gender-imdb.json',
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},
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emotion: {
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enabled: true,
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inputSize: 64, // fixed value
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minConfidence: 0.5, // threshold for discarding a prediction
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skipFrames: 10, // how many frames to go without re-running the detector
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modelPath: '../models/emotion/model.json',
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modelPath: '../models/emotion.json',
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},
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},
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body: {
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enabled: true,
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modelPath: '../models/posenet/model.json',
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modelPath: '../models/posenet.json',
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inputResolution: 257, // fixed value
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outputStride: 16, // fixed value
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maxDetections: 10, // maximum number of people detected in the input, should be set to the minimum number for performance
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@ -109,11 +109,10 @@ export default {
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enlargeFactor: 1.65, // empiric tuning as skeleton prediction prefers hand box with some whitespace
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maxHands: 10, // maximum number of hands detected in the input, should be set to the minimum number for performance
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detector: {
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anchors: '../models/handdetect/anchors.json',
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modelPath: '../models/handdetect/model.json',
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modelPath: '../models/handdetect.json',
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},
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skeleton: {
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modelPath: '../models/handskeleton/model.json',
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modelPath: '../models/handskeleton.json',
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},
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},
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};
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@ -223,7 +223,7 @@ function runHumanDetect(input, canvas) {
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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 = document.getElementById('image');
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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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@ -234,13 +234,12 @@ async function processImage(input) {
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const result = await human.detect(image, config);
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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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thumb.style.margin = '8px';
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thumb.style.boxShadow = '4px 4px 4px 0 dimgrey';
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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').appendChild(thumb);
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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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@ -251,7 +250,7 @@ async function processImage(input) {
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// just initialize everything and call main function
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async function detectVideo() {
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config.videoOptimized = true;
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document.getElementById('samples').style.display = 'none';
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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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@ -277,9 +276,12 @@ async function detectSampleImages() {
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ui.baseFont = ui.baseFontProto.replace(/{size}/, `${1.2 * ui.columns}rem`);
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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').style.display = 'block';
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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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@ -364,17 +366,18 @@ function setupMenu() {
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}
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async function main() {
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log('Human demo starting ...');
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log('Human: demo starting ...');
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setupMenu();
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const msg = `Human Library: version: ${human.version} TensorFlow/JS version: ${human.tf.version_core}`;
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document.getElementById('log').innerText = msg;
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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-warms the library
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status('loading');
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log(msg);
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await human.load();
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status('initializing');
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const warmup = new ImageData(50, 50);
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await human.detect(warmup);
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status('human: ready');
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document.getElementById('loader').style.display = 'none';
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document.getElementById('play').style.display = 'block';
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}
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window.onload = main;
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@ -17,19 +17,42 @@
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<!-- <script src="../assets/tf-backend-webgpu.js"></script> -->
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<!-- <script src='../assets/tfjs-vis.min.js'></script> -->
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<script src="./browser.js" type="module"></script>
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<style>
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body { margin: 0; background: black; color: white; font-family: 'Segoe UI'; font-size: 16px; font-variant: small-caps; overflow-x: hidden; scrollbar-width: none; }
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body::-webkit-scrollbar { display: none; }
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.play { position: absolute; width: 300px; height: 300px; z-index: 25; top: 30%; left: 50%; margin-left: -150px; display: none; }
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.play-background { fill:darkslategray; cursor:pointer; opacity: 0.6; }
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.play-foreground { fill:white; cursor:pointer; opacity: 0.8; }
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.play-foreground:hover { opacity: 1; }
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.status { position: absolute; width: 100vw; top: 100px; text-align: center; font-size: 4rem; font-weight: 100; text-shadow: 2px 2px darkslategrey; }
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.thumbnail { margin: 8px; box-shadow: 0 0 4px 4px dimgrey; }
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.thumbnail:hover { box-shadow: 0 0 8px 8px dimgrey; filter: grayscale(1); }
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.log { position: fixed; bottom: 0; }
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.samples-container { display: flex; flex-wrap: wrap; }
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.video { display: none; }
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.canvas { margin: 0 auto; width: 100%; }
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.loader { width: 300px; height: 300px; border: 3px solid transparent; border-radius: 50%; border-top: 4px solid #f15e41; animation: spin 4s linear infinite; position: absolute; top: 30%; left: 50%; margin-left: -150px; }
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.loader::before, .loader::after { content: ""; position: absolute; top: 6px; bottom: 6px; left: 6px; right: 6px; border-radius: 50%; border: 4px solid transparent; }
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.loader::before { border-top-color: #bad375; animation: 3s spin linear infinite; }
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.loader::after { border-top-color: #26a9e0; animation: spin 1.5s linear infinite; }
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@keyframes spin {
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from { transform: rotate(0deg); }
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to { transform: rotate(360deg); }
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}
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</style>
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</head>
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<body style="margin: 0; background: black; color: white; font-family: 'Segoe UI'; font-size: 16px; font-variant: small-caps; overflow: hidden">
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<div id="play" style="position: absolute; width: 250px; height: 250px; z-index: 25; top: 30%; left: 50%; margin-left: -125px">
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<body>
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<div id="play" class="play">
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512">
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<path d="M256 8C119 8 8 119 8 256s111 248 248 248 248-111 248-248S393 8 256 8zm115.7 272l-176 101c-15.8 8.8-35.7-2.5-35.7-21V152c0-18.4 19.8-29.8 35.7-21l176 107c16.4 9.2 16.4 32.9 0 42z" style="fill:darkslategray; cursor:pointer; opacity: 0.6"/>
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<path d="M371.7 280l-176 101c-15.8 8.8-35.7-2.5-35.7-21V152c0-18.4 19.8-29.8 35.7-21l176 107c16.4 9.2 16.4 32.9 0 42z" style="fill:white; cursor:pointer"/>
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<path d="M256 8C119 8 8 119 8 256s111 248 248 248 248-111 248-248S393 8 256 8zm115.7 272l-176 101c-15.8 8.8-35.7-2.5-35.7-21V152c0-18.4 19.8-29.8 35.7-21l176 107c16.4 9.2 16.4 32.9 0 42z" class="play-background"/>
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<path d="M371.7 280l-176 101c-15.8 8.8-35.7-2.5-35.7-21V152c0-18.4 19.8-29.8 35.7-21l176 107c16.4 9.2 16.4 32.9 0 42z" class="play-foreground"/>
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</svg>
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</div>
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<div id="status" style="position: absolute; width: 100vw; top: 100px; text-align: center; font-size: 4rem; font-weight: 100; text-shadow: 2px 2px darkslategrey;"></div>
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<video id="video" playsinline style="display: none"></video>
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<image id="image" src="" style="display: none"></video>
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<canvas id="canvas" style="margin: 0 auto; width: 100%"></canvas>
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<div id="samples" style="display: flex; flex-wrap: wrap"></div>
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<div id="log" style="position: fixed; bottom: 0"></div>
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<div id="loader" class="loader"></div>
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<div id="status" class="status"></div>
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<video id="video" playsinline class="video"></video>
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<canvas id="canvas" class="canvas"></canvas>
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<div id="samples-container" class="samples-container"></div>
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<div id="log" class="log"></div>
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</body>
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</html>
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18
demo/node.js
18
demo/node.js
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@ -28,17 +28,17 @@ const config = {
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console: true,
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videoOptimized: false,
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face: {
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detector: { modelPath: 'file://models/blazeface/back/model.json' },
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mesh: { modelPath: 'file://models/facemesh/model.json' },
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iris: { modelPath: 'file://models/iris/model.json' },
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age: { modelPath: 'file://models/ssrnet-age/imdb/model.json' },
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gender: { modelPath: 'file://models/ssrnet-gender/imdb/model.json' },
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emotion: { modelPath: 'file://models/emotion/model.json' },
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detector: { modelPath: 'file://models/blazeface-back.json' },
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mesh: { modelPath: 'file://models/facemesh.json' },
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iris: { modelPath: 'file://models/iris.json' },
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age: { modelPath: 'file://models/ssrnet-age-imdb.json' },
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gender: { modelPath: 'file://models/ssrnet-gender-imdb.json' },
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emotion: { modelPath: 'file://models/emotion.json' },
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},
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body: { modelPath: 'file://models/posenet/model.json' },
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body: { modelPath: 'file://models/posenet.json' },
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hand: {
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detector: { anchors: 'file://models/handdetect/anchors.json', modelPath: 'file://models/handdetect/model.json' },
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skeleton: { modelPath: 'file://models/handskeleton/model.json' },
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detector: { modelPath: 'file://models/handdetect.json' },
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skeleton: { modelPath: 'file://models/handskeleton.json' },
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},
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};
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@ -0,0 +1,12 @@
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{
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"name": "Human Library",
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"short_name": "Human",
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"icons": [
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{ "src": "/assets/icon.png", "sizes": "853x853", "type": "image/png", "purpose": "any maskable" }
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],
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"start_url": "/",
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"scope": "/",
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"display": "standalone",
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"background_color": "#000000",
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"theme_color": "#000000"
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}
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@ -0,0 +1,105 @@
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{
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"format": "graph-model",
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"generatedBy": "2.3.1",
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"convertedBy": "TensorFlow.js Converter v2.4.0",
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"userDefinedMetadata":
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{
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"signature":
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{
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"inputs": {"input_1:0":{"name":"input_1:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"-1"},{"size":"64"},{"size":"64"},{"size":"1"}]}}},
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"outputs": {"Identity:0":{"name":"Identity:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"-1"},{"size":"7"}]}}}
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}
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},
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"modelTopology":
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{
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"node":
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[
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{"name":"unknown_60","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"64"},{"size":"1"}]}}}}},
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{"name":"unknown_66","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"128"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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{"name":"unknown_43","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"32"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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{"name":"unknown_49","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"64"},{"size":"1"}]}}}}},
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{"name":"unknown_26","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"16"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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{"name":"unknown_32","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"32"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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{"name":"unknown_9","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"8"},{"size":"1"}]}}}}},
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{"name":"unknown_15","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"16"},{"size":"1"}]}}}}},
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{"name":"unknown_77","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"128"},{"size":"7"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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{"name":"unknown_78","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"7"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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{"name":"StatefulPartitionedCall/model_1/global_average_pooling2d_1/Mean/reduction_indices","op":"Const","attr":{"dtype":{"type":"DT_INT32"},"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"2"}]}}}}},
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{"name":"input_1","op":"Placeholder","attr":{"dtype":{"type":"DT_FLOAT"},"shape":{"shape":{"dim":[{"size":"-1"},{"size":"64"},{"size":"64"},{"size":"1"}]}}}},
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{"name":"StatefulPartitionedCall/model_1/conv2d_1/Conv2D_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"1"},{"size":"8"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/conv2d_6/Conv2D_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"64"},{"size":"128"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/conv2d_1/Conv2D_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"8"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/conv2d_2/Conv2D_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"8"},{"size":"8"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/conv2d_6/Conv2D_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/conv2d_2/Conv2D_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"8"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/conv2d_3/Conv2D_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"8"},{"size":"16"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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{"name":"StatefulPartitionedCall/model_1/separable_conv2d_7/separable_conv2d_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"64"},{"size":"128"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/conv2d_3/Conv2D_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"16"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/separable_conv2d_1/separable_conv2d_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"8"},{"size":"16"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/separable_conv2d_1/separable_conv2d_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"16"}]}}}}},
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{"name":"StatefulPartitionedCall/model_1/separable_conv2d_7/separable_conv2d_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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{"name":"StatefulPartitionedCall/model_1/separable_conv2d_2/separable_conv2d_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"16"},{"size":"16"}]}}},"dtype":{"type":"DT_FLOAT"}}},
|
||||
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|
||||
"weights": [{"name":"unknown_60","shape":[3,3,64,1],"dtype":"float32"},{"name":"unknown_66","shape":[3,3,128,1],"dtype":"float32"},{"name":"unknown_43","shape":[3,3,32,1],"dtype":"float32"},{"name":"unknown_49","shape":[3,3,64,1],"dtype":"float32"},{"name":"unknown_26","shape":[3,3,16,1],"dtype":"float32"},{"name":"unknown_32","shape":[3,3,32,1],"dtype":"float32"},{"name":"unknown_9","shape":[3,3,8,1],"dtype":"float32"},{"name":"unknown_15","shape":[3,3,16,1],"dtype":"float32"},{"name":"unknown_77","shape":[3,3,128,7],"dtype":"float32"},{"name":"unknown_78","shape":[7],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/global_average_pooling2d_1/Mean/reduction_indices","shape":[2],"dtype":"int32"},{"name":"StatefulPartitionedCall/model_1/conv2d_1/Conv2D_weights","shape":[3,3,1,8],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_6/Conv2D_weights","shape":[1,1,64,128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_1/Conv2D_bn_offset","shape":[8],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_2/Conv2D_weights","shape":[3,3,8,8],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_6/Conv2D_bn_offset","shape":[128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_2/Conv2D_bn_offset","shape":[8],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_3/Conv2D_weights","shape":[1,1,8,16],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_7/separable_conv2d_weights","shape":[1,1,64,128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_3/Conv2D_bn_offset","shape":[16],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_1/separable_conv2d_weights","shape":[1,1,8,16],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_1/separable_conv2d_bn_offset","shape":[16],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_7/separable_conv2d_bn_offset","shape":[128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_2/separable_conv2d_weights","shape":[1,1,16,16],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_2/separable_conv2d_bn_offset","shape":[16],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_4/Conv2D_weights","shape":[1,1,16,32],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_4/Conv2D_bn_offset","shape":[32],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_3/separable_conv2d_weights","shape":[1,1,16,32],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_3/separable_conv2d_bn_offset","shape":[32],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_8/separable_conv2d_weights","shape":[1,1,128,128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_4/separable_conv2d_weights","shape":[1,1,32,32],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_4/separable_conv2d_bn_offset","shape":[32],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_5/Conv2D_weights","shape":[1,1,32,64],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_8/separable_conv2d_bn_offset","shape":[128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_5/Conv2D_bn_offset","shape":[64],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_5/separable_conv2d_weights","shape":[1,1,32,64],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_5/separable_conv2d_bn_offset","shape":[64],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_6/separable_conv2d_weights","shape":[1,1,64,64],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_6/separable_conv2d_bn_offset","shape":[64],"dtype":"float32"}]
|
||||
}
|
||||
]
|
||||
}
|
||||
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10
package.json
10
package.json
|
|
@ -40,11 +40,11 @@
|
|||
"scripts": {
|
||||
"start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",
|
||||
"lint": "eslint src/*.js demo/*.js",
|
||||
"build-iife": "esbuild --bundle --platform=browser --sourcemap --target=esnext --format=iife --external:fs --global-name=Human --metafile=dist/human.json --outfile=dist/human.js src/human.js",
|
||||
"build-esm-bundle": "esbuild --bundle --platform=browser --sourcemap --target=esnext --format=esm --external:fs --metafile=dist/human.esm.json --outfile=dist/human.esm.js src/human.js",
|
||||
"build-esm-nobundle": "esbuild --bundle --platform=browser --sourcemap --target=esnext --format=esm --external:@tensorflow --external:fs --metafile=dist/human.esm-nobundle.json --outfile=dist/human.esm-nobundle.js src/human.js",
|
||||
"build-node": "esbuild --bundle --platform=node --sourcemap --target=esnext --format=cjs --metafile=dist/human.node.json --outfile=dist/human.node.js src/human.js",
|
||||
"build-node-nobundle": "esbuild --bundle --platform=node --sourcemap --target=esnext --format=cjs --external:@tensorflow --metafile=dist/human.node.json --outfile=dist/human.node-nobundle.js src/human.js",
|
||||
"build-iife": "esbuild --bundle --minify --platform=browser --sourcemap --target=esnext --format=iife --external:fs --global-name=Human --metafile=dist/human.json --outfile=dist/human.js src/human.js",
|
||||
"build-esm-bundle": "esbuild --bundle --minify --platform=browser --sourcemap --target=esnext --format=esm --external:fs --metafile=dist/human.esm.json --outfile=dist/human.esm.js src/human.js",
|
||||
"build-esm-nobundle": "esbuild --bundle --minify --platform=browser --sourcemap --target=esnext --format=esm --external:@tensorflow --external:fs --metafile=dist/human.esm-nobundle.json --outfile=dist/human.esm-nobundle.js src/human.js",
|
||||
"build-node": "esbuild --bundle --minify --platform=node --sourcemap --target=esnext --format=cjs --metafile=dist/human.node.json --outfile=dist/human.node.js src/human.js",
|
||||
"build-node-nobundle": "esbuild --bundle --minify --platform=node --sourcemap --target=esnext --format=cjs --external:@tensorflow --metafile=dist/human.node.json --outfile=dist/human.node-nobundle.js src/human.js",
|
||||
"build": "rimraf dist/* && npm run build-iife && npm run build-esm-bundle && npm run build-esm-nobundle && npm run build-node && npm run build-node-nobundle && ls -l dist/",
|
||||
"update": "npm update --depth 20 --force && npm dedupe && npm prune && npm audit",
|
||||
"changelog": "node changelog.js"
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
|
|
@ -2,6 +2,7 @@ const tf = require('@tensorflow/tfjs');
|
|||
const hand = require('./handdetector');
|
||||
const keypoints = require('./keypoints');
|
||||
const pipe = require('./pipeline');
|
||||
const anchors = require('./anchors.js');
|
||||
|
||||
class HandPose {
|
||||
constructor(pipeline) {
|
||||
|
|
@ -33,23 +34,12 @@ class HandPose {
|
|||
}
|
||||
exports.HandPose = HandPose;
|
||||
|
||||
async function loadAnchors(url) {
|
||||
if (tf.env().features.IS_NODE) {
|
||||
// eslint-disable-next-line global-require
|
||||
const fs = require('fs');
|
||||
const data = await fs.readFileSync(url.replace('file://', ''));
|
||||
return JSON.parse(data);
|
||||
}
|
||||
return tf.util.fetch(url).then((d) => d.json());
|
||||
}
|
||||
|
||||
async function load(config) {
|
||||
const [anchors, handDetectorModel, handPoseModel] = await Promise.all([
|
||||
loadAnchors(config.detector.anchors),
|
||||
const [handDetectorModel, handPoseModel] = await Promise.all([
|
||||
tf.loadGraphModel(config.detector.modelPath, { fromTFHub: config.detector.modelPath.includes('tfhub.dev') }),
|
||||
tf.loadGraphModel(config.skeleton.modelPath, { fromTFHub: config.skeleton.modelPath.includes('tfhub.dev') }),
|
||||
]);
|
||||
const detector = new hand.HandDetector(handDetectorModel, anchors, config);
|
||||
const detector = new hand.HandDetector(handDetectorModel, anchors.anchors, config);
|
||||
const pipeline = new pipe.HandPipeline(detector, handPoseModel, config);
|
||||
const handpose = new HandPose(pipeline);
|
||||
return handpose;
|
||||
|
|
|
|||
28
src/human.js
28
src/human.js
|
|
@ -109,28 +109,36 @@ class Human {
|
|||
|
||||
async load(userConfig) {
|
||||
if (userConfig) this.config = mergeDeep(defaults, userConfig);
|
||||
|
||||
if (first) {
|
||||
this.log(`version: ${this.version} TensorFlow/JS version: ${tf.version_core}`);
|
||||
this.log('configuration:', this.config);
|
||||
this.log('flags:', tf.ENV.flags);
|
||||
first = false;
|
||||
}
|
||||
|
||||
if (this.config.face.enabled && !this.models.facemesh) {
|
||||
this.log('Load model: Face');
|
||||
this.log('load model: face');
|
||||
this.models.facemesh = await facemesh.load(this.config.face);
|
||||
}
|
||||
if (this.config.body.enabled && !this.models.posenet) {
|
||||
this.log('Load model: Body');
|
||||
this.log('load model: body');
|
||||
this.models.posenet = await posenet.load(this.config.body);
|
||||
}
|
||||
if (this.config.hand.enabled && !this.models.handpose) {
|
||||
this.log('Load model: Hand');
|
||||
this.log('load model: hand');
|
||||
this.models.handpose = await handpose.load(this.config.hand);
|
||||
}
|
||||
if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) {
|
||||
this.log('Load model: Age');
|
||||
this.log('load model: age');
|
||||
this.models.age = await ssrnet.loadAge(this.config);
|
||||
}
|
||||
if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) {
|
||||
this.log('Load model: Gender');
|
||||
this.log('load model: gender');
|
||||
this.models.gender = await ssrnet.loadGender(this.config);
|
||||
}
|
||||
if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) {
|
||||
this.log('Load model: Emotion');
|
||||
this.log('load model: emotion');
|
||||
this.models.emotion = await emotion.load(this.config);
|
||||
}
|
||||
}
|
||||
|
|
@ -260,14 +268,6 @@ class Human {
|
|||
await this.checkBackend();
|
||||
perf.backend = Math.trunc(now() - timeStamp);
|
||||
|
||||
// check number of loaded models
|
||||
if (first) {
|
||||
this.log('Starting');
|
||||
this.log('Configuration:', this.config);
|
||||
this.log('Flags:', tf.ENV.flags);
|
||||
first = false;
|
||||
}
|
||||
|
||||
// load models if enabled
|
||||
timeStamp = now();
|
||||
this.state = 'load';
|
||||
|
|
|
|||
|
|
@ -73,7 +73,7 @@ const WebGLImageFilter = function (params) {
|
|||
// key is the shader program source, value is the compiled program
|
||||
const _shaderProgramCache = { };
|
||||
|
||||
const gl = _canvas.getContext('webgl') || _canvas.getContext('experimental-webgl');
|
||||
const gl = _canvas.getContext('webgl');
|
||||
if (!gl) throw new Error('Filter: getContext() failed');
|
||||
|
||||
this.addFilter = function (name) {
|
||||
|
|
|
|||
Loading…
Reference in New Issue