mirror of https://github.com/vladmandic/human
stricter linting, fix face annotations
Vladimir Mandic
parent
90a121a362
commit
cdd13e9fd9
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@ -252,7 +252,6 @@ function webWorker(input, image, canvas, timestamp) {
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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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console.log('worker', worker);
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// after receiving message from webworker, parse&draw results and send new frame for processing
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worker.addEventListener('message', (msg) => {
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if (msg.data.result.performance && msg.data.result.performance.total) ui.detectFPS.push(1000 / msg.data.result.performance.total);
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@ -270,7 +269,7 @@ function webWorker(input, image, canvas, timestamp) {
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});
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}
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// pass image data as arraybuffer to worker by reference to avoid copy
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worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, userConfig }, [image.data.buffer]);
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worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, userConfig }, 'Human', [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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@ -1,3 +1,4 @@
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// @ts-nocheck
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/* eslint-disable max-len */
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// based on: https://github.com/munrocket/gl-bench
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@ -1,3 +1,5 @@
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// @ts-nocheck
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let instance = 0;
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let CSScreated = false;
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@ -24,6 +24,6 @@ onmessage = async (msg) => {
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}
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// must strip canvas from return value as it cannot be transfered from worker thread
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if (result.canvas) result.canvas = null;
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postMessage({ result });
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postMessage({ result }, 'Human');
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busy = false;
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};
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@ -1,7 +1,7 @@
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{
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"inputs": {
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"dist/human.esm.js": {
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"bytes": 1839826,
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"bytes": 1838836,
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"imports": []
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},
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"demo/draw.js": {
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@ -9,15 +9,15 @@
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"imports": []
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},
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"demo/menu.js": {
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"bytes": 13858,
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"bytes": 13874,
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"imports": []
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},
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"demo/gl-bench.js": {
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"bytes": 10782,
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"bytes": 10797,
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"imports": []
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},
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"demo/browser.js": {
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"bytes": 25480,
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"bytes": 25454,
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"imports": [
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{
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"path": "dist/human.esm.js"
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@ -38,14 +38,14 @@
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"dist/demo-browser-index.js.map": {
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"imports": [],
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"inputs": {},
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"bytes": 1870322
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"bytes": 1868174
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},
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"dist/demo-browser-index.js": {
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"imports": [],
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"exports": [],
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"inputs": {
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"dist/human.esm.js": {
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"bytesInOutput": 1832586
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"bytesInOutput": 1832304
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},
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"demo/draw.js": {
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"bytesInOutput": 7726
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@ -57,10 +57,10 @@
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"bytesInOutput": 7382
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},
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"demo/browser.js": {
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"bytesInOutput": 19563
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"bytesInOutput": 19542
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}
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},
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"bytes": 1886446
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"bytes": 1885439
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}
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}
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}
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@ -9,7 +9,7 @@
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"imports": []
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},
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"src/tfjs/backend.js": {
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"bytes": 1340,
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"bytes": 1376,
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"imports": [
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{
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"path": "dist/tfjs.esm.js"
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@ -17,7 +17,7 @@
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]
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},
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"src/face/blazeface.js": {
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"bytes": 6986,
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"bytes": 7024,
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"imports": [
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{
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"path": "src/log.js"
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@ -44,7 +44,7 @@
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"imports": []
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},
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"src/face/facepipeline.js": {
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"bytes": 14062,
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"bytes": 14306,
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"imports": [
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{
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"path": "dist/tfjs.esm.js"
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@ -64,7 +64,7 @@
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]
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},
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"src/face/facemesh.js": {
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"bytes": 3054,
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"bytes": 2991,
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"imports": [
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{
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"path": "src/log.js"
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@ -92,7 +92,7 @@
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]
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},
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"src/age/age.js": {
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"bytes": 2017,
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"bytes": 2037,
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"imports": [
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{
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"path": "src/log.js"
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@ -106,7 +106,7 @@
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]
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},
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"src/gender/gender.js": {
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"bytes": 2886,
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"bytes": 2906,
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"imports": [
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{
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"path": "src/log.js"
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@ -120,7 +120,7 @@
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]
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},
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"src/emotion/emotion.js": {
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"bytes": 3055,
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"bytes": 3077,
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"imports": [
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{
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"path": "src/log.js"
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@ -134,7 +134,7 @@
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]
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},
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"src/embedding/embedding.js": {
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"bytes": 2041,
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"bytes": 2063,
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"imports": [
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{
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"path": "src/log.js"
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@ -191,7 +191,7 @@
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]
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},
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"src/body/decodePose.js": {
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"bytes": 5216,
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"bytes": 5368,
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"imports": [
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{
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"path": "src/body/keypoints.js"
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@ -205,7 +205,7 @@
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]
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},
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"src/body/decodeMultiple.js": {
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"bytes": 2303,
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"bytes": 2373,
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"imports": [
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{
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"path": "src/body/buildParts.js"
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@ -227,7 +227,7 @@
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]
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},
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"src/body/modelPoseNet.js": {
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"bytes": 2395,
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"bytes": 2519,
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"imports": [
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{
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"path": "src/log.js"
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@ -250,7 +250,7 @@
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]
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},
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"src/body/posenet.js": {
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"bytes": 614,
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"bytes": 712,
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"imports": [
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{
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"path": "src/body/modelPoseNet.js"
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]
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},
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"src/hand/box.js": {
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"bytes": 3226,
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"bytes": 2522,
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"imports": [
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{
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"path": "dist/tfjs.esm.js"
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@ -272,7 +272,7 @@
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]
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},
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"src/hand/handdetector.js": {
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"bytes": 4253,
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"bytes": 3548,
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"imports": [
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{
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"path": "dist/tfjs.esm.js"
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]
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},
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"src/hand/util.js": {
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"bytes": 3030,
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"bytes": 2346,
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"imports": []
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},
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"src/hand/handpipeline.js": {
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"bytes": 7951,
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"imports": [
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{
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"path": "dist/tfjs.esm.js"
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"imports": []
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},
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"src/hand/handpose.js": {
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"bytes": 3250,
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"bytes": 2578,
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"imports": [
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{
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"path": "src/log.js"
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"imports": []
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},
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"src/imagefx.js": {
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"bytes": 19352,
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"bytes": 19445,
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"imports": []
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},
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"src/image.js": {
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"bytes": 5841,
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"bytes": 5871,
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"imports": [
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{
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"path": "src/log.js"
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@ -362,7 +362,7 @@
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"imports": []
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},
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"src/human.js": {
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"bytes": 16727,
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"bytes": 17375,
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"imports": [
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{
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"path": "src/log.js"
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"dist/human.esm.js.map": {
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"imports": [],
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"inputs": {},
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"bytes": 1776771
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"bytes": 1774476
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},
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"dist/human.esm.js": {
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"imports": [],
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"bytesInOutput": 9513
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},
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"src/face/facemesh.js": {
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"bytesInOutput": 2378
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"bytesInOutput": 2317
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},
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"src/profile.js": {
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"bytesInOutput": 846
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@ -503,16 +503,16 @@
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"bytesInOutput": 127032
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},
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"src/hand/handpose.js": {
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"bytesInOutput": 2022
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"bytesInOutput": 2018
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},
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"src/gesture/gesture.js": {
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"bytesInOutput": 2463
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},
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"src/imagefx.js": {
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"bytesInOutput": 13576
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"bytesInOutput": 13628
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},
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"src/image.js": {
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"bytesInOutput": 4041
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"bytesInOutput": 3637
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},
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"src/log.js": {
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"bytesInOutput": 266
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"bytesInOutput": 938
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},
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"src/human.js": {
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"bytesInOutput": 11039
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"bytesInOutput": 11170
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},
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"src/hand/box.js": {
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"bytesInOutput": 1473
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"bytesInOutput": 22
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}
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},
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"bytes": 1839826
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"bytes": 1838836
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}
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}
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}
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"imports": []
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},
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"src/tfjs/backend.js": {
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"bytes": 1340,
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"bytes": 1376,
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"imports": [
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{
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"path": "dist/tfjs.esm.js"
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]
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},
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"src/face/blazeface.js": {
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"bytes": 6986,
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"bytes": 7024,
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"imports": [
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{
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"path": "src/log.js"
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"imports": []
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},
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"src/face/facepipeline.js": {
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"bytes": 14062,
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"imports": [
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{
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"path": "dist/tfjs.esm.js"
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]
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},
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"src/face/facemesh.js": {
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"bytes": 3054,
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"imports": [
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"path": "src/log.js"
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},
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"src/age/age.js": {
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"bytes": 2017,
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"bytes": 2037,
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"imports": [
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{
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"path": "src/log.js"
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},
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"src/gender/gender.js": {
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"imports": [
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},
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"src/emotion/emotion.js": {
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"bytes": 3055,
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"imports": [
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"path": "src/log.js"
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},
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"src/embedding/embedding.js": {
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"bytes": 2041,
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"imports": [
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{
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"path": "src/log.js"
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]
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},
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"src/body/decodePose.js": {
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"bytes": 5216,
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"bytes": 5368,
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"imports": [
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{
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"path": "src/body/keypoints.js"
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},
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"src/body/decodeMultiple.js": {
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"bytes": 2303,
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"imports": [
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"path": "src/body/buildParts.js"
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]
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},
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"src/body/modelPoseNet.js": {
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"bytes": 2395,
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"imports": [
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},
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"path": "src/body/modelPoseNet.js"
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"src/hand/box.js": {
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},
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"src/hand/handdetector.js": {
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"path": "dist/tfjs.esm.js"
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},
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"src/hand/util.js": {
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"imports": []
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},
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"src/hand/handpipeline.js": {
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"imports": [
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{
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"path": "dist/tfjs.esm.js"
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"imports": []
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},
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"src/hand/handpose.js": {
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"imports": [
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"path": "src/log.js"
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},
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"src/imagefx.js": {
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"imports": []
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},
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"src/image.js": {
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"imports": [
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{
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"imports": []
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},
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"src/human.js": {
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"imports": [
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{
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"dist/human.js.map": {
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"imports": [],
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"inputs": {},
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"bytes": 1776778
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"bytes": 1774483
|
||||
},
|
||||
"dist/human.js": {
|
||||
"imports": [],
|
||||
|
|
@ -441,7 +441,7 @@
|
|||
"bytesInOutput": 9513
|
||||
},
|
||||
"src/face/facemesh.js": {
|
||||
"bytesInOutput": 2378
|
||||
"bytesInOutput": 2317
|
||||
},
|
||||
"src/profile.js": {
|
||||
"bytesInOutput": 846
|
||||
|
|
@ -501,19 +501,19 @@
|
|||
"bytesInOutput": 127032
|
||||
},
|
||||
"src/hand/handpose.js": {
|
||||
"bytesInOutput": 2022
|
||||
"bytesInOutput": 2018
|
||||
},
|
||||
"src/gesture/gesture.js": {
|
||||
"bytesInOutput": 2463
|
||||
},
|
||||
"src/imagefx.js": {
|
||||
"bytesInOutput": 13576
|
||||
"bytesInOutput": 13628
|
||||
},
|
||||
"src/image.js": {
|
||||
"bytesInOutput": 4040
|
||||
"bytesInOutput": 3636
|
||||
},
|
||||
"src/human.js": {
|
||||
"bytesInOutput": 11100
|
||||
"bytesInOutput": 11231
|
||||
},
|
||||
"src/log.js": {
|
||||
"bytesInOutput": 266
|
||||
|
|
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|
|||
"bytesInOutput": 22
|
||||
}
|
||||
},
|
||||
"bytes": 1839900
|
||||
"bytes": 1838910
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
|
|
@ -9,7 +9,7 @@
|
|||
"imports": []
|
||||
},
|
||||
"src/tfjs/backend.js": {
|
||||
"bytes": 1340,
|
||||
"bytes": 1376,
|
||||
"imports": [
|
||||
{
|
||||
"path": "dist/tfjs.esm.js"
|
||||
|
|
@ -17,7 +17,7 @@
|
|||
]
|
||||
},
|
||||
"src/face/blazeface.js": {
|
||||
"bytes": 6986,
|
||||
"bytes": 7024,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -44,7 +44,7 @@
|
|||
"imports": []
|
||||
},
|
||||
"src/face/facepipeline.js": {
|
||||
"bytes": 14062,
|
||||
"bytes": 14306,
|
||||
"imports": [
|
||||
{
|
||||
"path": "dist/tfjs.esm.js"
|
||||
|
|
@ -64,7 +64,7 @@
|
|||
]
|
||||
},
|
||||
"src/face/facemesh.js": {
|
||||
"bytes": 3054,
|
||||
"bytes": 2991,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -92,7 +92,7 @@
|
|||
]
|
||||
},
|
||||
"src/age/age.js": {
|
||||
"bytes": 2017,
|
||||
"bytes": 2037,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -106,7 +106,7 @@
|
|||
]
|
||||
},
|
||||
"src/gender/gender.js": {
|
||||
"bytes": 2886,
|
||||
"bytes": 2906,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -120,7 +120,7 @@
|
|||
]
|
||||
},
|
||||
"src/emotion/emotion.js": {
|
||||
"bytes": 3055,
|
||||
"bytes": 3077,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -134,7 +134,7 @@
|
|||
]
|
||||
},
|
||||
"src/embedding/embedding.js": {
|
||||
"bytes": 2041,
|
||||
"bytes": 2063,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -191,7 +191,7 @@
|
|||
]
|
||||
},
|
||||
"src/body/decodePose.js": {
|
||||
"bytes": 5216,
|
||||
"bytes": 5368,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/body/keypoints.js"
|
||||
|
|
@ -205,7 +205,7 @@
|
|||
]
|
||||
},
|
||||
"src/body/decodeMultiple.js": {
|
||||
"bytes": 2303,
|
||||
"bytes": 2373,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/body/buildParts.js"
|
||||
|
|
@ -227,7 +227,7 @@
|
|||
]
|
||||
},
|
||||
"src/body/modelPoseNet.js": {
|
||||
"bytes": 2395,
|
||||
"bytes": 2519,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -250,7 +250,7 @@
|
|||
]
|
||||
},
|
||||
"src/body/posenet.js": {
|
||||
"bytes": 614,
|
||||
"bytes": 712,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/body/modelPoseNet.js"
|
||||
|
|
@ -264,7 +264,7 @@
|
|||
]
|
||||
},
|
||||
"src/hand/box.js": {
|
||||
"bytes": 3226,
|
||||
"bytes": 2522,
|
||||
"imports": [
|
||||
{
|
||||
"path": "dist/tfjs.esm.js"
|
||||
|
|
@ -272,7 +272,7 @@
|
|||
]
|
||||
},
|
||||
"src/hand/handdetector.js": {
|
||||
"bytes": 4253,
|
||||
"bytes": 3548,
|
||||
"imports": [
|
||||
{
|
||||
"path": "dist/tfjs.esm.js"
|
||||
|
|
@ -283,11 +283,11 @@
|
|||
]
|
||||
},
|
||||
"src/hand/util.js": {
|
||||
"bytes": 3030,
|
||||
"bytes": 2346,
|
||||
"imports": []
|
||||
},
|
||||
"src/hand/handpipeline.js": {
|
||||
"bytes": 7951,
|
||||
"bytes": 7246,
|
||||
"imports": [
|
||||
{
|
||||
"path": "dist/tfjs.esm.js"
|
||||
|
|
@ -308,7 +308,7 @@
|
|||
"imports": []
|
||||
},
|
||||
"src/hand/handpose.js": {
|
||||
"bytes": 3250,
|
||||
"bytes": 2578,
|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -332,11 +332,11 @@
|
|||
"imports": []
|
||||
},
|
||||
"src/imagefx.js": {
|
||||
"bytes": 19352,
|
||||
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|
||||
"imports": []
|
||||
},
|
||||
"src/image.js": {
|
||||
"bytes": 5841,
|
||||
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|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -362,7 +362,7 @@
|
|||
"imports": []
|
||||
},
|
||||
"src/human.js": {
|
||||
"bytes": 16727,
|
||||
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|
||||
"imports": [
|
||||
{
|
||||
"path": "src/log.js"
|
||||
|
|
@ -419,7 +419,7 @@
|
|||
"dist/human.node-gpu.js.map": {
|
||||
"imports": [],
|
||||
"inputs": {},
|
||||
"bytes": 702698
|
||||
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|
||||
},
|
||||
"dist/human.node-gpu.js": {
|
||||
"imports": [],
|
||||
|
|
@ -444,7 +444,7 @@
|
|||
"bytesInOutput": 9563
|
||||
},
|
||||
"src/face/facemesh.js": {
|
||||
"bytesInOutput": 2421
|
||||
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|
||||
},
|
||||
"src/profile.js": {
|
||||
"bytesInOutput": 846
|
||||
|
|
@ -495,28 +495,28 @@
|
|||
"bytesInOutput": 634
|
||||
},
|
||||
"src/hand/handdetector.js": {
|
||||
"bytesInOutput": 2880
|
||||
"bytesInOutput": 2876
|
||||
},
|
||||
"src/hand/handpipeline.js": {
|
||||
"bytesInOutput": 4559
|
||||
"bytesInOutput": 4555
|
||||
},
|
||||
"src/hand/anchors.js": {
|
||||
"bytesInOutput": 127034
|
||||
},
|
||||
"src/hand/handpose.js": {
|
||||
"bytesInOutput": 2064
|
||||
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|
||||
},
|
||||
"src/gesture/gesture.js": {
|
||||
"bytesInOutput": 2467
|
||||
},
|
||||
"src/imagefx.js": {
|
||||
"bytesInOutput": 13558
|
||||
"bytesInOutput": 13610
|
||||
},
|
||||
"src/image.js": {
|
||||
"bytesInOutput": 4069
|
||||
"bytesInOutput": 3665
|
||||
},
|
||||
"src/human.js": {
|
||||
"bytesInOutput": 11126
|
||||
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|
||||
},
|
||||
"src/log.js": {
|
||||
"bytesInOutput": 266
|
||||
|
|
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|
|||
"bytesInOutput": 20
|
||||
}
|
||||
},
|
||||
"bytes": 310199
|
||||
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|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -46,6 +46,7 @@ async function predict(image, config) {
|
|||
const profileAge = config.face.age.enabled ? await tf.profile(() => models.age.predict(enhance)) : {};
|
||||
ageT = profileAge.result.clone();
|
||||
profileAge.result.dispose();
|
||||
// @ts-ignore
|
||||
profile.run('age', profileAge);
|
||||
}
|
||||
enhance.dispose();
|
||||
|
|
|
|||
|
|
@ -7,6 +7,7 @@ const kLocalMaximumRadius = 1;
|
|||
function withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {
|
||||
return poses.some(({ keypoints }) => {
|
||||
const correspondingKeypoint = keypoints[keypointId].position;
|
||||
// @ts-ignore
|
||||
return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;
|
||||
});
|
||||
}
|
||||
|
|
@ -21,6 +22,7 @@ function getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {
|
|||
|
||||
function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config) {
|
||||
const poses = [];
|
||||
// @ts-ignore
|
||||
const queue = buildParts.buildPartWithScoreQueue(config.body.scoreThreshold, kLocalMaximumRadius, scoresBuffer);
|
||||
const squaredNmsRadius = config.body.nmsRadius ^ 2;
|
||||
// Generate at most maxDetections object instances per image in decreasing root part score order.
|
||||
|
|
@ -28,9 +30,11 @@ function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer
|
|||
// The top element in the queue is the next root candidate.
|
||||
const root = queue.dequeue();
|
||||
// Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.
|
||||
// @ts-ignore
|
||||
const rootImageCoords = vectors.getImageCoords(root.part, config.body.outputStride, offsetsBuffer);
|
||||
if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;
|
||||
// Else start a new detection instance at the position of the root.
|
||||
// @ts-ignore
|
||||
const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, config.body.outputStride, displacementsFwdBuffer, displacementsBwdBuffer);
|
||||
const score = getInstanceScore(poses, squaredNmsRadius, keypoints);
|
||||
if (score > config.body.scoreThreshold) poses.push({ keypoints, score });
|
||||
|
|
|
|||
|
|
@ -14,7 +14,9 @@ function getDisplacement(edgeId, point, displacements) {
|
|||
}
|
||||
function getStridedIndexNearPoint(point, outputStride, height, width) {
|
||||
return {
|
||||
// @ts-ignore
|
||||
y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),
|
||||
// @ts-ignore
|
||||
x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),
|
||||
};
|
||||
}
|
||||
|
|
@ -24,11 +26,14 @@ function traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scor
|
|||
// Nearest neighbor interpolation for the source->target displacements.
|
||||
const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);
|
||||
const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);
|
||||
// @ts-ignore
|
||||
const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);
|
||||
let targetKeypoint = displacedPoint;
|
||||
for (let i = 0; i < offsetRefineStep; i++) {
|
||||
const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);
|
||||
// @ts-ignore
|
||||
const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);
|
||||
// @ts-ignore
|
||||
targetKeypoint = vectors.addVectors({
|
||||
x: targetKeypointIndices.x * outputStride,
|
||||
y: targetKeypointIndices.y * outputStride,
|
||||
|
|
@ -45,6 +50,7 @@ function decodePose(root, scores, offsets, outputStride, displacementsFwd, displ
|
|||
const instanceKeypoints = new Array(numParts);
|
||||
// Start a new detection instance at the position of the root.
|
||||
const { part: rootPart, score: rootScore } = root;
|
||||
// @ts-ignore
|
||||
const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);
|
||||
instanceKeypoints[rootPart.id] = {
|
||||
score: rootScore,
|
||||
|
|
@ -73,13 +79,16 @@ exports.decodePose = decodePose;
|
|||
|
||||
async function decodeSinglePose(heatmapScores, offsets, config) {
|
||||
let totalScore = 0.0;
|
||||
// @ts-ignore
|
||||
const heatmapValues = decoders.argmax2d(heatmapScores);
|
||||
const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);
|
||||
const scoresBuffer = allTensorBuffers[0];
|
||||
const offsetsBuffer = allTensorBuffers[1];
|
||||
const heatmapValuesBuffer = allTensorBuffers[2];
|
||||
// @ts-ignore
|
||||
const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, config.body.outputStride, offsetsBuffer);
|
||||
const offsetPointsBuffer = await offsetPoints.buffer();
|
||||
// @ts-ignore
|
||||
const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));
|
||||
const instanceKeypoints = keypointConfidence.map((score, i) => {
|
||||
totalScore += score;
|
||||
|
|
|
|||
|
|
@ -9,12 +9,15 @@ async function estimateMultiple(input, res, config) {
|
|||
return new Promise(async (resolve) => {
|
||||
const height = input.shape[1];
|
||||
const width = input.shape[2];
|
||||
// @ts-ignore
|
||||
const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);
|
||||
const scoresBuffer = allTensorBuffers[0];
|
||||
const offsetsBuffer = allTensorBuffers[1];
|
||||
const displacementsFwdBuffer = allTensorBuffers[2];
|
||||
const displacementsBwdBuffer = allTensorBuffers[3];
|
||||
// @ts-ignore
|
||||
const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config);
|
||||
// @ts-ignore
|
||||
const scaled = util.scaleAndFlipPoses(poses, [height, width], [config.body.inputSize, config.body.inputSize]);
|
||||
resolve(scaled);
|
||||
});
|
||||
|
|
@ -24,8 +27,10 @@ async function estimateSingle(input, res, config) {
|
|||
return new Promise(async (resolve) => {
|
||||
const height = input.shape[1];
|
||||
const width = input.shape[2];
|
||||
// @ts-ignore
|
||||
const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config);
|
||||
const poses = [pose];
|
||||
// @ts-ignore
|
||||
const scaled = util.scaleAndFlipPoses(poses, [height, width], [config.body.inputSize, config.body.inputSize]);
|
||||
resolve(scaled);
|
||||
});
|
||||
|
|
@ -37,6 +42,7 @@ class PoseNet {
|
|||
}
|
||||
|
||||
async estimatePoses(input, config) {
|
||||
// @ts-ignore
|
||||
const resized = util.resizeTo(input, [config.body.inputSize, config.body.inputSize]);
|
||||
const res = this.baseModel.predict(resized, config);
|
||||
|
||||
|
|
@ -59,6 +65,7 @@ exports.PoseNet = PoseNet;
|
|||
|
||||
async function load(config) {
|
||||
const model = await tf.loadGraphModel(config.body.modelPath);
|
||||
// @ts-ignore
|
||||
const mobilenet = new modelBase.BaseModel(model);
|
||||
log(`load model: ${config.body.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
return new PoseNet(mobilenet);
|
||||
|
|
|
|||
|
|
@ -2,15 +2,22 @@ import * as modelPoseNet from './modelPoseNet';
|
|||
import * as keypoints from './keypoints';
|
||||
import * as util from './util';
|
||||
|
||||
// @ts-ignore
|
||||
exports.load = modelPoseNet.load;
|
||||
// @ts-ignore
|
||||
exports.PoseNet = modelPoseNet.PoseNet;
|
||||
|
||||
exports.partChannels = keypoints.partChannels;
|
||||
exports.partIds = keypoints.partIds;
|
||||
exports.partNames = keypoints.partNames;
|
||||
exports.poseChain = keypoints.poseChain;
|
||||
// @ts-ignore
|
||||
exports.getAdjacentKeyPoints = util.getAdjacentKeyPoints;
|
||||
// @ts-ignore
|
||||
exports.getBoundingBox = util.getBoundingBox;
|
||||
// @ts-ignore
|
||||
exports.getBoundingBoxPoints = util.getBoundingBoxPoints;
|
||||
// @ts-ignore
|
||||
exports.scaleAndFlipPoses = util.scaleAndFlipPoses;
|
||||
// @ts-ignore
|
||||
exports.scalePose = util.scalePose;
|
||||
|
|
|
|||
|
|
@ -39,6 +39,7 @@ async function predict(image, config) {
|
|||
const profileData = await tf.profile(() => models.embedding.predict({ img_inputs: resize }));
|
||||
data = [...profileData.result.dataSync()];
|
||||
profileData.result.dispose();
|
||||
// @ts-ignore
|
||||
profile.run('emotion', profileData);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -65,6 +65,7 @@ async function predict(image, config) {
|
|||
const profileData = await tf.profile(() => models.emotion.predict(normalize));
|
||||
data = profileData.result.dataSync();
|
||||
profileData.result.dispose();
|
||||
// @ts-ignore
|
||||
profile.run('emotion', profileData);
|
||||
}
|
||||
for (let i = 0; i < data.length; i++) {
|
||||
|
|
|
|||
|
|
@ -134,11 +134,13 @@ class BlazeFaceModel {
|
|||
}
|
||||
|
||||
async estimateFaces(input) {
|
||||
// @ts-ignore
|
||||
const { boxes, scaleFactor } = await this.getBoundingBoxes(input);
|
||||
const faces = [];
|
||||
for (const face of boxes) {
|
||||
const landmarkData = face.landmarks.arraySync();
|
||||
const scaledBox = scaleBoxFromPrediction(face, scaleFactor);
|
||||
// @ts-ignore
|
||||
const boxData = scaleBox.arraySync();
|
||||
const probabilityData = face.probability.arraySync();
|
||||
const anchor = face.anchor;
|
||||
|
|
|
|||
|
|
@ -6,6 +6,7 @@ import * as coords from './coords.js';
|
|||
|
||||
class MediaPipeFaceMesh {
|
||||
constructor(blazeFace, blazeMeshModel, irisModel, config) {
|
||||
// @ts-ignore
|
||||
this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel, config);
|
||||
this.config = config;
|
||||
}
|
||||
|
|
@ -19,21 +20,17 @@ class MediaPipeFaceMesh {
|
|||
const meshRaw = prediction.rawCoords;
|
||||
const annotations = {};
|
||||
if (mesh && mesh.length > 0) {
|
||||
for (let key = 0; key < coords.MESH_ANNOTATIONS.length; key++) {
|
||||
if (config.face.iris.enabled || key.includes('Iris') === false) {
|
||||
for (const key of Object.keys(coords.MESH_ANNOTATIONS)) {
|
||||
annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);
|
||||
}
|
||||
}
|
||||
}
|
||||
const boxRaw = (config.face.mesh.returnRawData && prediction.box) ? { topLeft: prediction.box.startPoint, bottomRight: prediction.box.endPoint } : null;
|
||||
|
||||
const box = prediction.box ? [
|
||||
Math.max(0, prediction.box.startPoint[0]),
|
||||
Math.max(0, prediction.box.startPoint[1]),
|
||||
Math.min(input.shape[2], prediction.box.endPoint[0]) - prediction.box.startPoint[0],
|
||||
Math.min(input.shape[1], prediction.box.endPoint[1]) - prediction.box.startPoint[1],
|
||||
] : 0;
|
||||
|
||||
results.push({
|
||||
confidence: prediction.confidence || 0,
|
||||
box,
|
||||
|
|
@ -53,6 +50,7 @@ class MediaPipeFaceMesh {
|
|||
let faceModels = [null, null, null];
|
||||
async function load(config) {
|
||||
faceModels = await Promise.all([
|
||||
// @ts-ignore
|
||||
(!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,
|
||||
(!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,
|
||||
(!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,
|
||||
|
|
|
|||
|
|
@ -56,6 +56,7 @@ class Pipeline {
|
|||
}
|
||||
|
||||
transformRawCoords(rawCoords, box, angle, rotationMatrix) {
|
||||
// @ts-ignore
|
||||
const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });
|
||||
const scaleFactor = [boxSize[0] / this.meshWidth, boxSize[1] / this.meshHeight];
|
||||
const coordsScaled = rawCoords.map((coord) => ([
|
||||
|
|
@ -65,6 +66,7 @@ class Pipeline {
|
|||
const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;
|
||||
const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;
|
||||
const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;
|
||||
// @ts-ignore
|
||||
const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];
|
||||
return coordsRotated.map((coord) => ([
|
||||
coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),
|
||||
|
|
@ -81,7 +83,9 @@ class Pipeline {
|
|||
|
||||
// Returns a box describing a cropped region around the eye fit for passing to the iris model.
|
||||
getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {
|
||||
// @ts-ignore
|
||||
const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));
|
||||
// @ts-ignore
|
||||
const boxSize = bounding.getBoxSize(box);
|
||||
let crop = tf.image.cropAndResize(face, [[
|
||||
box.startPoint[1] / this.meshHeight,
|
||||
|
|
@ -155,8 +159,11 @@ class Pipeline {
|
|||
return null;
|
||||
}
|
||||
for (let i = 0; i < this.storedBoxes.length; i++) {
|
||||
// @ts-ignore
|
||||
const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);
|
||||
// @ts-ignore
|
||||
const enlargedBox = bounding.enlargeBox(scaledBox);
|
||||
// @ts-ignore
|
||||
const squarifiedBox = bounding.squarifyBox(enlargedBox);
|
||||
const landmarks = this.storedBoxes[i].landmarks.arraySync();
|
||||
const confidence = this.storedBoxes[i].confidence;
|
||||
|
|
@ -181,14 +188,17 @@ class Pipeline {
|
|||
if (config.face.detector.rotation) {
|
||||
const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= LANDMARKS_COUNT) ? MESH_KEYPOINTS_LINE_OF_SYMMETRY_INDICES : BLAZEFACE_KEYPOINTS_LINE_OF_SYMMETRY_INDICES;
|
||||
angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);
|
||||
// @ts-ignore
|
||||
const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });
|
||||
const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];
|
||||
const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized);
|
||||
rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);
|
||||
// @ts-ignore
|
||||
face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshHeight, this.meshWidth]).div(255);
|
||||
} else {
|
||||
rotationMatrix = util.IDENTITY_MATRIX;
|
||||
const cloned = input.clone();
|
||||
// @ts-ignore
|
||||
face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, cloned, [this.meshHeight, this.meshWidth]).div(255);
|
||||
}
|
||||
|
||||
|
|
@ -235,7 +245,9 @@ class Pipeline {
|
|||
}
|
||||
|
||||
const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);
|
||||
// @ts-ignore
|
||||
const landmarksBox = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData));
|
||||
// @ts-ignore
|
||||
const squarifiedLandmarksBox = bounding.squarifyBox(landmarksBox);
|
||||
const transformedCoords = tf.tensor2d(transformedCoordsData);
|
||||
const prediction = {
|
||||
|
|
|
|||
|
|
@ -53,6 +53,7 @@ async function predict(image, config) {
|
|||
const profileGender = config.face.gender.enabled ? await tf.profile(() => models.gender.predict(enhance)) : {};
|
||||
genderT = profileGender.result.clone();
|
||||
profileGender.result.dispose();
|
||||
// @ts-ignore
|
||||
profile.run('gender', profileGender);
|
||||
}
|
||||
enhance.dispose();
|
||||
|
|
|
|||
|
|
@ -1,19 +1,3 @@
|
|||
/**
|
||||
* @license
|
||||
* Copyright 2020 Google LLC. All Rights Reserved.
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* https://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
* =============================================================================
|
||||
*/
|
||||
import * as tf from '../../dist/tfjs.esm.js';
|
||||
|
||||
function getBoxSize(box) {
|
||||
|
|
|
|||
|
|
@ -1,20 +1,3 @@
|
|||
/**
|
||||
* @license
|
||||
* Copyright 2020 Google LLC. All Rights Reserved.
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* https://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
* =============================================================================
|
||||
*/
|
||||
|
||||
import * as tf from '../../dist/tfjs.esm.js';
|
||||
import * as box from './box';
|
||||
|
||||
|
|
|
|||
|
|
@ -1,20 +1,3 @@
|
|||
/**
|
||||
* @license
|
||||
* Copyright 2020 Google LLC. All Rights Reserved.
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* https://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
* =============================================================================
|
||||
*/
|
||||
|
||||
import * as tf from '../../dist/tfjs.esm.js';
|
||||
import * as box from './box';
|
||||
import * as util from './util';
|
||||
|
|
|
|||
|
|
@ -1,19 +1,3 @@
|
|||
/**
|
||||
* @license
|
||||
* Copyright 2020 Google LLC. All Rights Reserved.
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* https://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
* =============================================================================
|
||||
*/
|
||||
// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html
|
||||
|
||||
import { log } from '../log.js';
|
||||
|
|
@ -74,7 +58,9 @@ async function load(config) {
|
|||
config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,
|
||||
config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,
|
||||
]);
|
||||
// @ts-ignore
|
||||
const handDetector = new handdetector.HandDetector(handDetectorModel, config.hand.inputSize, anchors.anchors);
|
||||
// @ts-ignore
|
||||
const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, config.hand.inputSize);
|
||||
const handPose = new HandPose(handPipeline);
|
||||
if (config.hand.enabled) log(`load model: ${config.hand.detector.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
|
|
|
|||
|
|
@ -1,19 +1,3 @@
|
|||
/**
|
||||
* @license
|
||||
* Copyright 2020 Google LLC. All Rights Reserved.
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* https://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
* =============================================================================
|
||||
*/
|
||||
function normalizeRadians(angle) {
|
||||
return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));
|
||||
}
|
||||
|
|
@ -42,6 +26,7 @@ function multiplyTransformMatrices(mat1, mat2) {
|
|||
for (let row = 0; row < size; row++) {
|
||||
product.push([]);
|
||||
for (let col = 0; col < size; col++) {
|
||||
// @ts-ignore
|
||||
product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));
|
||||
}
|
||||
}
|
||||
|
|
|
|||
43
src/human.js
43
src/human.js
|
|
@ -18,6 +18,7 @@ import * as app from '../package.json';
|
|||
// helper function: gets elapsed time on both browser and nodejs
|
||||
const now = () => {
|
||||
if (typeof performance !== 'undefined') return performance.now();
|
||||
// @ts-ignore
|
||||
return parseInt(Number(process.hrtime.bigint()) / 1000 / 1000);
|
||||
};
|
||||
|
||||
|
|
@ -72,6 +73,7 @@ class Human {
|
|||
}
|
||||
|
||||
profile() {
|
||||
// @ts-ignore
|
||||
if (this.config.profile) return profile.data;
|
||||
return {};
|
||||
}
|
||||
|
|
@ -102,6 +104,7 @@ class Human {
|
|||
}
|
||||
|
||||
simmilarity(embedding1, embedding2) {
|
||||
// @ts-ignore
|
||||
if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);
|
||||
return 0;
|
||||
}
|
||||
|
|
@ -132,21 +135,35 @@ class Human {
|
|||
this.models.posenet,
|
||||
this.models.handpose,
|
||||
] = await Promise.all([
|
||||
// @ts-ignore
|
||||
this.models.facemesh || (this.config.face.enabled ? facemesh.load(this.config) : null),
|
||||
// @ts-ignore
|
||||
this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),
|
||||
// @ts-ignore
|
||||
this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),
|
||||
// @ts-ignore
|
||||
this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),
|
||||
// @ts-ignore
|
||||
this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),
|
||||
// @ts-ignore
|
||||
this.models.posenet || (this.config.body.enabled ? posenet.load(this.config) : null),
|
||||
// @ts-ignore
|
||||
this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),
|
||||
]);
|
||||
} else {
|
||||
// @ts-ignore
|
||||
if (this.config.face.enabled && !this.models.facemesh) this.models.facemesh = await facemesh.load(this.config);
|
||||
// @ts-ignore
|
||||
if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);
|
||||
// @ts-ignore
|
||||
if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);
|
||||
// @ts-ignore
|
||||
if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);
|
||||
// @ts-ignore
|
||||
if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);
|
||||
// @ts-ignore
|
||||
if (this.config.body.enabled && !this.models.posenet) this.models.posenet = await posenet.load(this.config);
|
||||
// @ts-ignore
|
||||
if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);
|
||||
}
|
||||
const current = Math.trunc(now() - timeStamp);
|
||||
|
|
@ -213,7 +230,8 @@ class Human {
|
|||
const faceRes = [];
|
||||
this.state = 'run:face';
|
||||
timeStamp = now();
|
||||
const faces = await this.models.facemesh.estimateFaces(input, this.config);
|
||||
// @ts-ignore
|
||||
const faces = await this.models.facemesh?.estimateFaces(input, this.config);
|
||||
this.perf.face = Math.trunc(now() - timeStamp);
|
||||
for (const face of faces) {
|
||||
this.analyze('Get Face');
|
||||
|
|
@ -227,10 +245,12 @@ class Human {
|
|||
// run age, inherits face from blazeface
|
||||
this.analyze('Start Age:');
|
||||
if (this.config.async) {
|
||||
// @ts-ignore
|
||||
ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};
|
||||
} else {
|
||||
this.state = 'run:age';
|
||||
timeStamp = now();
|
||||
// @ts-ignore
|
||||
ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};
|
||||
this.perf.age = Math.trunc(now() - timeStamp);
|
||||
}
|
||||
|
|
@ -238,10 +258,12 @@ class Human {
|
|||
// run gender, inherits face from blazeface
|
||||
this.analyze('Start Gender:');
|
||||
if (this.config.async) {
|
||||
// @ts-ignore
|
||||
genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};
|
||||
} else {
|
||||
this.state = 'run:gender';
|
||||
timeStamp = now();
|
||||
// @ts-ignore
|
||||
genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};
|
||||
this.perf.gender = Math.trunc(now() - timeStamp);
|
||||
}
|
||||
|
|
@ -249,10 +271,12 @@ class Human {
|
|||
// run emotion, inherits face from blazeface
|
||||
this.analyze('Start Emotion:');
|
||||
if (this.config.async) {
|
||||
// @ts-ignore
|
||||
emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};
|
||||
} else {
|
||||
this.state = 'run:emotion';
|
||||
timeStamp = now();
|
||||
// @ts-ignore
|
||||
emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};
|
||||
this.perf.emotion = Math.trunc(now() - timeStamp);
|
||||
}
|
||||
|
|
@ -261,10 +285,12 @@ class Human {
|
|||
// run emotion, inherits face from blazeface
|
||||
this.analyze('Start Embedding:');
|
||||
if (this.config.async) {
|
||||
// @ts-ignore
|
||||
embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face.image, this.config) : {};
|
||||
} else {
|
||||
this.state = 'run:embedding';
|
||||
timeStamp = now();
|
||||
// @ts-ignore
|
||||
embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face.image, this.config) : {};
|
||||
this.perf.embedding = Math.trunc(now() - timeStamp);
|
||||
}
|
||||
|
|
@ -291,7 +317,6 @@ class Human {
|
|||
confidence: face.confidence,
|
||||
box: face.box,
|
||||
mesh: face.mesh,
|
||||
// AT: boxRaw, meshRaw
|
||||
boxRaw: face.boxRaw,
|
||||
meshRaw: face.meshRaw,
|
||||
annotations: face.annotations,
|
||||
|
|
@ -317,6 +342,7 @@ class Human {
|
|||
async image(input, userConfig = {}) {
|
||||
this.state = 'image';
|
||||
this.config = mergeDeep(this.config, userConfig);
|
||||
// @ts-ignore
|
||||
const process = image.process(input, this.config);
|
||||
process.tensor.dispose();
|
||||
return process.canvas;
|
||||
|
|
@ -356,6 +382,7 @@ class Human {
|
|||
this.analyze('Start Scope:');
|
||||
|
||||
timeStamp = now();
|
||||
// @ts-ignore
|
||||
const process = image.process(input, this.config);
|
||||
if (!process || !process.tensor) {
|
||||
log('could not convert input to tensor');
|
||||
|
|
@ -379,12 +406,14 @@ class Human {
|
|||
// run posenet
|
||||
this.analyze('Start Body:');
|
||||
if (this.config.async) {
|
||||
poseRes = this.config.body.enabled ? this.models.posenet.estimatePoses(process.tensor, this.config) : [];
|
||||
// @ts-ignore
|
||||
poseRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];
|
||||
if (this.perf.body) delete this.perf.body;
|
||||
} else {
|
||||
this.state = 'run:body';
|
||||
timeStamp = now();
|
||||
poseRes = this.config.body.enabled ? await this.models.posenet.estimatePoses(process.tensor, this.config) : [];
|
||||
// @ts-ignore
|
||||
poseRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];
|
||||
this.perf.body = Math.trunc(now() - timeStamp);
|
||||
}
|
||||
this.analyze('End Body:');
|
||||
|
|
@ -392,12 +421,14 @@ class Human {
|
|||
// run handpose
|
||||
this.analyze('Start Hand:');
|
||||
if (this.config.async) {
|
||||
handRes = this.config.hand.enabled ? this.models.handpose.estimateHands(process.tensor, this.config) : [];
|
||||
// @ts-ignore
|
||||
handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];
|
||||
if (this.perf.hand) delete this.perf.hand;
|
||||
} else {
|
||||
this.state = 'run:hand';
|
||||
timeStamp = now();
|
||||
handRes = this.config.hand.enabled ? await this.models.handpose.estimateHands(process.tensor, this.config) : [];
|
||||
// @ts-ignore
|
||||
handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];
|
||||
this.perf.hand = Math.trunc(now() - timeStamp);
|
||||
}
|
||||
// this.analyze('End Hand:');
|
||||
|
|
|
|||
10
src/image.js
10
src/image.js
|
|
@ -41,6 +41,7 @@ function process(input, config) {
|
|||
if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;
|
||||
this.fx = tf.ENV.flags.IS_BROWSER ? new fxImage.Canvas({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')
|
||||
}
|
||||
if (!this.fx) return inCanvas;
|
||||
this.fx.reset();
|
||||
this.fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled
|
||||
if (config.filter.contrast !== 0) this.fx.addFilter('contrast', config.filter.contrast);
|
||||
|
|
@ -58,8 +59,8 @@ function process(input, config) {
|
|||
if (config.filter.pixelate !== 0) this.fx.addFilter('pixelate', config.filter.pixelate);
|
||||
this.fx.apply(inCanvas);
|
||||
// read pixel data
|
||||
// const gl = outCanvas.getContext('webgl');
|
||||
const gl = false;
|
||||
/*
|
||||
const gl = outCanvas.getContext('webgl');
|
||||
if (gl) {
|
||||
const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);
|
||||
const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);
|
||||
|
|
@ -77,6 +78,7 @@ function process(input, config) {
|
|||
}
|
||||
outCanvas.data = pixBuffer;
|
||||
}
|
||||
*/
|
||||
} else {
|
||||
outCanvas = inCanvas;
|
||||
}
|
||||
|
|
@ -93,8 +95,8 @@ function process(input, config) {
|
|||
tempCanvas.width = targetWidth;
|
||||
tempCanvas.height = targetHeight;
|
||||
const tempCtx = tempCanvas.getContext('2d');
|
||||
tempCtx.drawImage(outCanvas, 0, 0);
|
||||
const data = tempCtx.getImageData(0, 0, targetWidth, targetHeight);
|
||||
tempCtx?.drawImage(outCanvas, 0, 0);
|
||||
const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);
|
||||
pixels = tf.browser.fromPixels(data);
|
||||
}
|
||||
const casted = pixels.toFloat();
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ const WebGLProgram = function (gl, vertexSource, fragmentSource) {
|
|||
gl.compileShader(shader);
|
||||
|
||||
if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {
|
||||
// @ts-ignore
|
||||
throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));
|
||||
}
|
||||
return shader;
|
||||
|
|
@ -37,6 +38,7 @@ const WebGLProgram = function (gl, vertexSource, fragmentSource) {
|
|||
gl.linkProgram(this.id);
|
||||
|
||||
if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {
|
||||
// @ts-ignore
|
||||
throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));
|
||||
}
|
||||
|
||||
|
|
@ -149,9 +151,8 @@ const WebGLImageFilter = function (params) {
|
|||
};
|
||||
|
||||
const _getTempFramebuffer = function (index) {
|
||||
_tempFramebuffers[index] = _tempFramebuffers[index]
|
||||
|| _createFramebufferTexture(_width, _height);
|
||||
|
||||
// @ts-ignore
|
||||
_tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);
|
||||
return _tempFramebuffers[index];
|
||||
};
|
||||
|
||||
|
|
@ -190,7 +191,8 @@ const WebGLImageFilter = function (params) {
|
|||
source = _sourceTexture;
|
||||
} else {
|
||||
// All following draw calls use the temp buffer last drawn to
|
||||
source = _getTempFramebuffer(_currentFramebufferIndex).texture;
|
||||
// @ts-ignore
|
||||
source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;
|
||||
}
|
||||
_drawCount++;
|
||||
|
||||
|
|
@ -203,7 +205,8 @@ const WebGLImageFilter = function (params) {
|
|||
} else {
|
||||
// Intermediate draw call - get a temp buffer to draw to
|
||||
_currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;
|
||||
target = _getTempFramebuffer(_currentFramebufferIndex).fbo;
|
||||
// @ts-ignore
|
||||
target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;
|
||||
}
|
||||
|
||||
// Bind the source and target and draw the two triangles
|
||||
|
|
|
|||
|
|
@ -20,7 +20,9 @@ export const config = {
|
|||
|
||||
export function register() {
|
||||
if (!tf.findBackend(config.name)) {
|
||||
// @ts-ignore
|
||||
config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');
|
||||
// @ts-ignore
|
||||
const gl = config.canvas.getContext('webgl2', config.webGLattr);
|
||||
tf.setWebGLContext(2, gl);
|
||||
const ctx = new tf.GPGPUContext(gl);
|
||||
|
|
|
|||
|
|
@ -0,0 +1,25 @@
|
|||
{
|
||||
"compilerOptions": {
|
||||
"module": "es2020",
|
||||
"target": "es2018",
|
||||
"moduleResolution": "node",
|
||||
"lib": ["es2018", "dom"],
|
||||
"typeRoots": ["node_modules/@types"],
|
||||
"outDir": "types",
|
||||
"declaration": true,
|
||||
"emitDeclarationOnly": true,
|
||||
"emitDecoratorMetadata": true,
|
||||
"experimentalDecorators": true,
|
||||
"importHelpers": true,
|
||||
"noImplicitAny": false,
|
||||
"preserveConstEnums": true,
|
||||
"removeComments": false,
|
||||
"resolveJsonModule": true,
|
||||
"skipLibCheck": true,
|
||||
"sourceMap": false,
|
||||
"strictNullChecks": false,
|
||||
"allowJs": true
|
||||
},
|
||||
"formatCodeOptions": { "indentSize": 2, "tabSize": 2 },
|
||||
"include": ["src/*", "demo/*"],
|
||||
}
|
||||
2
wiki
2
wiki
|
|
@ -1 +1 @@
|
|||
Subproject commit 699af2235b315ef24766839ddc49a198f7cc21c3
|
||||
Subproject commit 43425df86424e9b5f4bec3510f3565963255d4a9
|
||||
Loading…
Reference in New Issue