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human
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complete model refactoring

pull/280/head
Vladimir Mandic 2020-11-03 09:34:36 -05:00
parent 0f5ccda33c
commit 2b5901ff55
20 changed files with 18788 additions and 73 deletions
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1
README.md
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@ -355,7 +355,6 @@ config = {
enlargeFactor: 1.65, // empiric tuning as skeleton prediction prefers hand box with some whitespace enlargeFactor: 1.65, // empiric tuning as skeleton prediction prefers hand box with some whitespace
maxHands: 10, // maximum number of hands detected in the input, should be set to the minimum number for performance maxHands: 10, // maximum number of hands detected in the input, should be set to the minimum number for performance
detector: { detector: {
anchors: '../models/handdetect/anchors.json',
modelPath: '../models/handdetect/model.json', modelPath: '../models/handdetect/model.json',
}, },
skeleton: { skeleton: {

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19
config.js
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@ -46,7 +46,7 @@ export default {
// face.enabled is required for all face models: detector, mesh, iris, age, gender, emotion // face.enabled is required for all face models: detector, mesh, iris, age, gender, emotion
// (note: module is not loaded until it is required) // (note: module is not loaded until it is required)
detector: { detector: {
modelPath: '../models/blazeface/back/model.json', // can be 'front' or 'back'. modelPath: '../models/blazeface-back.json', // can be 'front' or 'back'.
// 'front' is optimized for large faces such as front-facing camera and 'back' is optimized for distanct faces. // 'front' is optimized for large faces such as front-facing camera and 'back' is optimized for distanct faces.
inputSize: 256, // fixed value: 128 for front and 256 for 'back' inputSize: 256, // fixed value: 128 for front and 256 for 'back'
maxFaces: 10, // maximum number of faces detected in the input, should be set to the minimum number for performance maxFaces: 10, // maximum number of faces detected in the input, should be set to the minimum number for performance
@ -59,18 +59,18 @@ export default {
}, },
mesh: { mesh: {
enabled: true, enabled: true,
modelPath: '../models/facemesh/model.json', modelPath: '../models/facemesh.json',
inputSize: 192, // fixed value inputSize: 192, // fixed value
}, },
iris: { iris: {
enabled: true, enabled: true,
modelPath: '../models/iris/model.json', modelPath: '../models/iris.json',
enlargeFactor: 2.3, // empiric tuning enlargeFactor: 2.3, // empiric tuning
inputSize: 64, // fixed value inputSize: 64, // fixed value
}, },
age: { age: {
enabled: true, enabled: true,
modelPath: '../models/ssrnet-age/imdb/model.json', // can be 'imdb' or 'wiki' modelPath: '../models/ssrnet-age-imdb.json', // can be 'imdb' or 'wiki'
// which determines training set for model // which determines training set for model
inputSize: 64, // fixed value inputSize: 64, // fixed value
skipFrames: 10, // how many frames to go without re-running the detector, only used for video inputs skipFrames: 10, // how many frames to go without re-running the detector, only used for video inputs
@ -78,19 +78,19 @@ export default {
gender: { gender: {
enabled: true, enabled: true,
minConfidence: 0.8, // threshold for discarding a prediction minConfidence: 0.8, // threshold for discarding a prediction
modelPath: '../models/ssrnet-gender/imdb/model.json', modelPath: '../models/ssrnet-gender-imdb.json',
}, },
emotion: { emotion: {
enabled: true, enabled: true,
inputSize: 64, // fixed value inputSize: 64, // fixed value
minConfidence: 0.5, // threshold for discarding a prediction minConfidence: 0.5, // threshold for discarding a prediction
skipFrames: 10, // how many frames to go without re-running the detector skipFrames: 10, // how many frames to go without re-running the detector
modelPath: '../models/emotion/model.json', modelPath: '../models/emotion.json',
}, },
}, },
body: { body: {
enabled: true, enabled: true,
modelPath: '../models/posenet/model.json', modelPath: '../models/posenet.json',
inputResolution: 257, // fixed value inputResolution: 257, // fixed value
outputStride: 16, // fixed value outputStride: 16, // fixed value
maxDetections: 10, // maximum number of people detected in the input, should be set to the minimum number for performance maxDetections: 10, // maximum number of people detected in the input, should be set to the minimum number for performance
@ -109,11 +109,10 @@ export default {
enlargeFactor: 1.65, // empiric tuning as skeleton prediction prefers hand box with some whitespace enlargeFactor: 1.65, // empiric tuning as skeleton prediction prefers hand box with some whitespace
maxHands: 10, // maximum number of hands detected in the input, should be set to the minimum number for performance maxHands: 10, // maximum number of hands detected in the input, should be set to the minimum number for performance
detector: { detector: {
anchors: '../models/handdetect/anchors.json', modelPath: '../models/handdetect.json',
modelPath: '../models/handdetect/model.json',
}, },
skeleton: { skeleton: {
modelPath: '../models/handskeleton/model.json', modelPath: '../models/handskeleton.json',
}, },
}, },
}; };

23
demo/browser.js
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@ -223,7 +223,7 @@ function runHumanDetect(input, canvas) {
async function processImage(input) { async function processImage(input) {
timeStamp = performance.now(); timeStamp = performance.now();
return new Promise((resolve) => { return new Promise((resolve) => {
const image = document.getElementById('image'); const image = new Image();
image.onload = async () => { image.onload = async () => {
log('Processing image:', image.src); log('Processing image:', image.src);
const canvas = document.getElementById('canvas'); const canvas = document.getElementById('canvas');
@ -234,13 +234,12 @@ async function processImage(input) {
const result = await human.detect(image, config); const result = await human.detect(image, config);
drawResults(image, result, canvas); drawResults(image, result, canvas);
const thumb = document.createElement('canvas'); const thumb = document.createElement('canvas');
thumb.className = 'thumbnail';
thumb.width = window.innerWidth / (ui.columns + 0.1); thumb.width = window.innerWidth / (ui.columns + 0.1);
thumb.height = canvas.height / (window.innerWidth / thumb.width); thumb.height = canvas.height / (window.innerWidth / thumb.width);
thumb.style.margin = '8px';
thumb.style.boxShadow = '4px 4px 4px 0 dimgrey';
const ctx = thumb.getContext('2d'); const ctx = thumb.getContext('2d');
ctx.drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, thumb.width, thumb.height); ctx.drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, thumb.width, thumb.height);
document.getElementById('samples').appendChild(thumb); document.getElementById('samples-container').appendChild(thumb);
image.src = ''; image.src = '';
resolve(true); resolve(true);
}; };
@ -251,7 +250,7 @@ async function processImage(input) {
// just initialize everything and call main function // just initialize everything and call main function
async function detectVideo() { async function detectVideo() {
config.videoOptimized = true; config.videoOptimized = true;
document.getElementById('samples').style.display = 'none'; document.getElementById('samples-container').style.display = 'none';
document.getElementById('canvas').style.display = 'block'; document.getElementById('canvas').style.display = 'block';
const video = document.getElementById('video'); const video = document.getElementById('video');
const canvas = document.getElementById('canvas'); const canvas = document.getElementById('canvas');
@ -277,9 +276,12 @@ async function detectSampleImages() {
ui.baseFont = ui.baseFontProto.replace(/{size}/, `${1.2 * ui.columns}rem`); ui.baseFont = ui.baseFontProto.replace(/{size}/, `${1.2 * ui.columns}rem`);
ui.baseLineHeight = ui.baseLineHeightProto * ui.columns; ui.baseLineHeight = ui.baseLineHeightProto * ui.columns;
document.getElementById('canvas').style.display = 'none'; document.getElementById('canvas').style.display = 'none';
document.getElementById('samples').style.display = 'block'; document.getElementById('samples-container').style.display = 'block';
log('Running detection of sample images'); log('Running detection of sample images');
status('processing images');
document.getElementById('samples-container').innerHTML = '';
for (const sample of ui.samples) await processImage(sample); for (const sample of ui.samples) await processImage(sample);
status('');
} }
function setupMenu() { function setupMenu() {
@ -364,17 +366,18 @@ function setupMenu() {
} }
async function main() { async function main() {
log('Human demo starting ...'); log('Human: demo starting ...');
setupMenu(); setupMenu();
const msg = `Human Library: version: ${human.version} TensorFlow/JS version: ${human.tf.version_core}`; document.getElementById('log').innerText = `Human: version: ${human.version} TensorFlow/JS version: ${human.tf.version_core}`;
document.getElementById('log').innerText = msg; // this is not required, just pre-warms the library
status('loading'); status('loading');
log(msg);
await human.load(); await human.load();
status('initializing'); status('initializing');
const warmup = new ImageData(50, 50); const warmup = new ImageData(50, 50);
await human.detect(warmup); await human.detect(warmup);
status('human: ready'); status('human: ready');
document.getElementById('loader').style.display = 'none';
document.getElementById('play').style.display = 'block';
} }
window.onload = main; window.onload = main;

43
demo/index.html
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@ -17,19 +17,42 @@
<!-- <script src="../assets/tf-backend-webgpu.js"></script> --> <!-- <script src="../assets/tf-backend-webgpu.js"></script> -->
<!-- <script src='../assets/tfjs-vis.min.js'></script> --> <!-- <script src='../assets/tfjs-vis.min.js'></script> -->
<script src="./browser.js" type="module"></script> <script src="./browser.js" type="module"></script>
<style>
body { margin: 0; background: black; color: white; font-family: 'Segoe UI'; font-size: 16px; font-variant: small-caps; overflow-x: hidden; scrollbar-width: none; }
body::-webkit-scrollbar { display: none; }
.play { position: absolute; width: 300px; height: 300px; z-index: 25; top: 30%; left: 50%; margin-left: -150px; display: none; }
.play-background { fill:darkslategray; cursor:pointer; opacity: 0.6; }
.play-foreground { fill:white; cursor:pointer; opacity: 0.8; }
.play-foreground:hover { opacity: 1; }
.status { position: absolute; width: 100vw; top: 100px; text-align: center; font-size: 4rem; font-weight: 100; text-shadow: 2px 2px darkslategrey; }
.thumbnail { margin: 8px; box-shadow: 0 0 4px 4px dimgrey; }
.thumbnail:hover { box-shadow: 0 0 8px 8px dimgrey; filter: grayscale(1); }
.log { position: fixed; bottom: 0; }
.samples-container { display: flex; flex-wrap: wrap; }
.video { display: none; }
.canvas { margin: 0 auto; width: 100%; }
.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; }
.loader::before, .loader::after { content: ""; position: absolute; top: 6px; bottom: 6px; left: 6px; right: 6px; border-radius: 50%; border: 4px solid transparent; }
.loader::before { border-top-color: #bad375; animation: 3s spin linear infinite; }
.loader::after { border-top-color: #26a9e0; animation: spin 1.5s linear infinite; }
@keyframes spin {
from { transform: rotate(0deg); }
to { transform: rotate(360deg); }
}
</style>
</head> </head>
<body style="margin: 0; background: black; color: white; font-family: 'Segoe UI'; font-size: 16px; font-variant: small-caps; overflow: hidden"> <body>
<div id="play" style="position: absolute; width: 250px; height: 250px; z-index: 25; top: 30%; left: 50%; margin-left: -125px"> <div id="play" class="play">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512">
<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"/> <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"/>
<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"/> <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"/>
</svg> </svg>
</div> </div>
<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> <div id="loader" class="loader"></div>
<video id="video" playsinline style="display: none"></video> <div id="status" class="status"></div>
<image id="image" src="" style="display: none"></video> <video id="video" playsinline class="video"></video>
<canvas id="canvas" style="margin: 0 auto; width: 100%"></canvas> <canvas id="canvas" class="canvas"></canvas>
<div id="samples" style="display: flex; flex-wrap: wrap"></div> <div id="samples-container" class="samples-container"></div>
<div id="log" style="position: fixed; bottom: 0"></div> <div id="log" class="log"></div>
</body> </body>
</html> </html>

18
demo/node.js
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@ -28,17 +28,17 @@ const config = {
console: true, console: true,
videoOptimized: false, videoOptimized: false,
face: { face: {
detector: { modelPath: 'file://models/blazeface/back/model.json' }, detector: { modelPath: 'file://models/blazeface-back.json' },
mesh: { modelPath: 'file://models/facemesh/model.json' }, mesh: { modelPath: 'file://models/facemesh.json' },
iris: { modelPath: 'file://models/iris/model.json' }, iris: { modelPath: 'file://models/iris.json' },
age: { modelPath: 'file://models/ssrnet-age/imdb/model.json' }, age: { modelPath: 'file://models/ssrnet-age-imdb.json' },
gender: { modelPath: 'file://models/ssrnet-gender/imdb/model.json' }, gender: { modelPath: 'file://models/ssrnet-gender-imdb.json' },
emotion: { modelPath: 'file://models/emotion/model.json' }, emotion: { modelPath: 'file://models/emotion.json' },
}, },
body: { modelPath: 'file://models/posenet/model.json' }, body: { modelPath: 'file://models/posenet.json' },
hand: { hand: {
detector: { anchors: 'file://models/handdetect/anchors.json', modelPath: 'file://models/handdetect/model.json' }, detector: { modelPath: 'file://models/handdetect.json' },
skeleton: { modelPath: 'file://models/handskeleton/model.json' }, skeleton: { modelPath: 'file://models/handskeleton.json' },
}, },
}; };

12
manifest.json Normal file
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@ -0,0 +1,12 @@
{
"name": "Human Library",
"short_name": "Human",
"icons": [
{ "src": "/assets/icon.png", "sizes": "853x853", "type": "image/png", "purpose": "any maskable" }
],
"start_url": "/",
"scope": "/",
"display": "standalone",
"background_color": "#000000",
"theme_color": "#000000"
}

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models/emotion.json Normal file
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@ -0,0 +1,105 @@
{
"format": "graph-model",
"generatedBy": "2.3.1",
"convertedBy": "TensorFlow.js Converter v2.4.0",
"userDefinedMetadata":
{
"signature":
{
"inputs": {"input_1:0":{"name":"input_1:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"-1"},{"size":"64"},{"size":"64"},{"size":"1"}]}}},
"outputs": {"Identity:0":{"name":"Identity:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"-1"},{"size":"7"}]}}}
}
},
"modelTopology":
{
"node":
[
{"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"}]}}}}},
{"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"}}},
{"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"}}},
{"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"}]}}}}},
{"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"}}},
{"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"}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}}},
{"name":"unknown_78","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"7"}]}}},"dtype":{"type":"DT_FLOAT"}}},
{"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"}]}}}}},
{"name":"input_1","op":"Placeholder","attr":{"dtype":{"type":"DT_FLOAT"},"shape":{"shape":{"dim":[{"size":"-1"},{"size":"64"},{"size":"64"},{"size":"1"}]}}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}]}}}}},
{"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"}}},
{"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"}}},
{"name":"StatefulPartitionedCall/model_1/separable_conv2d_2/separable_conv2d_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"16"}]}}}}},
{"name":"StatefulPartitionedCall/model_1/conv2d_4/Conv2D_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"16"},{"size":"32"}]}}}}},
{"name":"StatefulPartitionedCall/model_1/conv2d_4/Conv2D_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"32"}]}}},"dtype":{"type":"DT_FLOAT"}}},
{"name":"StatefulPartitionedCall/model_1/separable_conv2d_3/separable_conv2d_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"16"},{"size":"32"}]}}}}},
{"name":"StatefulPartitionedCall/model_1/separable_conv2d_3/separable_conv2d_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"32"}]}}}}},
{"name":"StatefulPartitionedCall/model_1/separable_conv2d_8/separable_conv2d_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"},{"size":"128"}]}}}}},
{"name":"StatefulPartitionedCall/model_1/separable_conv2d_4/separable_conv2d_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"32"},{"size":"32"}]}}},"dtype":{"type":"DT_FLOAT"}}},
{"name":"StatefulPartitionedCall/model_1/separable_conv2d_4/separable_conv2d_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"32"}]}}}}},
{"name":"StatefulPartitionedCall/model_1/conv2d_5/Conv2D_weights","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"32"},{"size":"64"}]}}}}},
{"name":"StatefulPartitionedCall/model_1/separable_conv2d_8/separable_conv2d_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}}}},
{"name":"StatefulPartitionedCall/model_1/conv2d_5/Conv2D_bn_offset","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"64"}]}}}}},
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@ -40,11 +40,11 @@
"scripts": { "scripts": {
"start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js", "start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",
"lint": "eslint src/*.js demo/*.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-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 --platform=browser --sourcemap --target=esnext --format=esm --external:fs --metafile=dist/human.esm.json --outfile=dist/human.esm.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 --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-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 --platform=node --sourcemap --target=esnext --format=cjs --metafile=dist/human.node.json --outfile=dist/human.node.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 --platform=node --sourcemap --target=esnext --format=cjs --external:@tensorflow --metafile=dist/human.node.json --outfile=dist/human.node-nobundle.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/", "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", "update": "npm update --depth 20 --force && npm dedupe && npm prune && npm audit",
"changelog": "node changelog.js" "changelog": "node changelog.js"

17666
src/handpose/anchors.js Normal file
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16
src/handpose/handpose.js
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@ -2,6 +2,7 @@ const tf = require('@tensorflow/tfjs');
const hand = require('./handdetector'); const hand = require('./handdetector');
const keypoints = require('./keypoints'); const keypoints = require('./keypoints');
const pipe = require('./pipeline'); const pipe = require('./pipeline');
const anchors = require('./anchors.js');
class HandPose { class HandPose {
constructor(pipeline) { constructor(pipeline) {
@ -33,23 +34,12 @@ class HandPose {
} }
exports.HandPose = 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) { async function load(config) {
const [anchors, handDetectorModel, handPoseModel] = await Promise.all([ const [handDetectorModel, handPoseModel] = await Promise.all([
loadAnchors(config.detector.anchors),
tf.loadGraphModel(config.detector.modelPath, { fromTFHub: config.detector.modelPath.includes('tfhub.dev') }), tf.loadGraphModel(config.detector.modelPath, { fromTFHub: config.detector.modelPath.includes('tfhub.dev') }),
tf.loadGraphModel(config.skeleton.modelPath, { fromTFHub: config.skeleton.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 pipeline = new pipe.HandPipeline(detector, handPoseModel, config);
const handpose = new HandPose(pipeline); const handpose = new HandPose(pipeline);
return handpose; return handpose;

28
src/human.js
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@ -109,28 +109,36 @@ class Human {
async load(userConfig) { async load(userConfig) {
if (userConfig) this.config = mergeDeep(defaults, 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) { 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); this.models.facemesh = await facemesh.load(this.config.face);
} }
if (this.config.body.enabled && !this.models.posenet) { 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); this.models.posenet = await posenet.load(this.config.body);
} }
if (this.config.hand.enabled && !this.models.handpose) { 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); this.models.handpose = await handpose.load(this.config.hand);
} }
if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) { 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); this.models.age = await ssrnet.loadAge(this.config);
} }
if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) { 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); this.models.gender = await ssrnet.loadGender(this.config);
} }
if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) { 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); this.models.emotion = await emotion.load(this.config);
} }
} }
@ -260,14 +268,6 @@ class Human {
await this.checkBackend(); await this.checkBackend();
perf.backend = Math.trunc(now() - timeStamp); 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 // load models if enabled
timeStamp = now(); timeStamp = now();
this.state = 'load'; this.state = 'load';

2
src/imagefx.js
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@ -73,7 +73,7 @@ const WebGLImageFilter = function (params) {
// key is the shader program source, value is the compiled program // key is the shader program source, value is the compiled program
const _shaderProgramCache = { }; const _shaderProgramCache = { };
const gl = _canvas.getContext('webgl') || _canvas.getContext('experimental-webgl'); const gl = _canvas.getContext('webgl');
if (!gl) throw new Error('Filter: getContext() failed'); if (!gl) throw new Error('Filter: getContext() failed');
this.addFilter = function (name) { this.addFilter = function (name) {