mirror of https://github.com/vladmandic/human
package updates
Vladimir Mandic
parent
0f92e3023e
commit
b509489ed7
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@ -9,8 +9,12 @@
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## Changelog
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### **HEAD -> main** 2021/10/10 mandic00@live.com
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### **HEAD -> main** 2021/10/12 mandic00@live.com
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### **release: 2.3.2** 2021/10/11 mandic00@live.com
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- major precision improvements to movenet and handtrack
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- image processing fixes
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- redesign body and hand caching and interpolation
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- demo default config cleanup
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19
TODO.md
19
TODO.md
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@ -6,16 +6,13 @@
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### Models
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- Implement BlazePose end-to-end
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- Optimize BlazePose
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- Add Anti-Spoofing
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<br>
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### Backends
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#### WebGL
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- Optimize shader packing for WebGL backend:
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<https://github.com/tensorflow/tfjs/issues/5343>
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#### WASM
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- Backend WASM incorrect handling of `int32` tensors
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@ -23,17 +20,9 @@
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#### WebGPU
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Implementation of WebGPU backend
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Experimental support only until support is officially added in Chromium
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- Evaluate WGSL vs GLSL for WebGPU
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- Backend WebGPU missing kernel ops
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<https://github.com/tensorflow/tfjs/issues/5496>
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- Backend WebGPU incompatible with web workers
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<https://github.com/tensorflow/tfjs/issues/5467>
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- Backend WebGPU incompatible with sync read calls
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<https://github.com/tensorflow/tfjs/issues/5468>
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- Performance issues:
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<https://github.com/tensorflow/tfjs/issues/5689>
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<br>
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@ -12,13 +12,13 @@ const userConfig = {
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backend: 'wasm',
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async: false,
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warmup: 'none',
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cacheSimilarity: 0,
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cacheSensitivity: 0,
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debug: true,
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modelBasePath: '../../models/',
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// wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.9.0/dist/',
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face: {
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enabled: true,
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detector: { rotation: true, return: true, maxDetected: 20 },
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detector: { rotation: true, return: true, maxDetected: 50 },
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mesh: { enabled: true },
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embedding: { enabled: false },
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iris: { enabled: true },
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@ -120,7 +120,7 @@ async function SelectFaceCanvas(face) {
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ctx.font = 'small-caps 1rem "Lato"';
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const start = performance.now();
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const arr = db.map((rec) => rec.embedding);
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const res = await human.match(face.embedding, arr);
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const res = await human.match(current.embedding, arr);
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time += (performance.now() - start);
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if (res.similarity > minScore) ctx.fillText(`DB: ${(100 * res.similarity).toFixed(1)}% ${db[res.index].name}`, 4, canvas.height - 30);
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}
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@ -226,7 +226,7 @@ async function main() {
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// could not dynamically enumerate images so using static list
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if (images.length === 0) {
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images = [
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'ai-body.jpg', 'ai-upper.jpg',
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'ai-body.jpg', 'solvay1927.jpg', 'ai-upper.jpg',
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'person-carolina.jpg', 'person-celeste.jpg', 'person-leila1.jpg', 'person-leila2.jpg', 'person-lexi.jpg', 'person-linda.jpg', 'person-nicole.jpg', 'person-tasia.jpg',
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'person-tetiana.jpg', 'person-vlado1.jpg', 'person-vlado5.jpg', 'person-vlado.jpg', 'person-christina.jpg', 'person-lauren.jpg',
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'group-1.jpg', 'group-2.jpg', 'group-3.jpg', 'group-4.jpg', 'group-5.jpg', 'group-6.jpg', 'group-7.jpg',
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@ -243,6 +243,8 @@ async function main() {
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log('Discovered images:', images);
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}
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// images = ['/samples/in/solvay1927.jpg'];
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// download and analyze all images
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for (let i = 0; i < images.length; i++) await AddImageElement(i, images[i], images.length);
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File diff suppressed because one or more lines are too long
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@ -1,8 +1,9 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<title>Human</title>
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<meta http-equiv="content-type" content="text/html; charset=utf-8">
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<!-- <meta http-equiv="content-type" content="text/html; charset=utf-8"> -->
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<meta name="viewport" content="width=device-width, shrink-to-fit=yes">
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<meta name="keywords" content="Human">
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<meta name="application-name" content="Human">
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@ -146,7 +146,7 @@ let bench;
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let lastDetectedResult = {};
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// helper function: async pause
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// eslint-disable-next-line @typescript-eslint/no-unused-vars
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// eslint-disable-next-line @typescript-eslint/no-unused-vars, no-unused-vars
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const delay = (ms) => new Promise((resolve) => setTimeout(resolve, ms));
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// helper function: translates json to human readable string
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@ -7,4 +7,4 @@
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"display": "standalone",
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"background_color": "#000000",
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"theme_color": "#000000"
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}
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}
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18
package.json
18
package.json
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@ -1,6 +1,6 @@
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{
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"name": "@vladmandic/human",
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"version": "2.3.2",
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"version": "2.3.3",
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"description": "Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gesture Recognition",
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"sideEffects": false,
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"main": "dist/human.node.js",
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@ -55,7 +55,6 @@
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"tensorflow"
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],
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"devDependencies": {
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"@tensorflow/tfjs": "^3.9.0",
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"@tensorflow/tfjs-backend-cpu": "^3.9.0",
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"@tensorflow/tfjs-backend-wasm": "^3.9.0",
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"@tensorflow/tfjs-backend-webgl": "^3.9.0",
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@ -64,21 +63,23 @@
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"@tensorflow/tfjs-core": "^3.9.0",
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"@tensorflow/tfjs-data": "^3.9.0",
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"@tensorflow/tfjs-layers": "^3.9.0",
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"@tensorflow/tfjs-node": "^3.9.0",
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"@tensorflow/tfjs-node-gpu": "^3.9.0",
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"@types/node": "^16.10.3",
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"@typescript-eslint/eslint-plugin": "^4.33.0",
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"@typescript-eslint/parser": "^4.33.0",
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"@vladmandic/build": "^0.5.3",
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"@tensorflow/tfjs-node": "^3.9.0",
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"@tensorflow/tfjs": "^3.9.0",
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"@types/node": "^16.10.4",
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"@typescript-eslint/eslint-plugin": "^5.0.0",
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"@typescript-eslint/parser": "^5.0.0",
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"@vladmandic/build": "^0.6.0",
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"@vladmandic/pilogger": "^0.3.3",
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"canvas": "^2.8.0",
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"dayjs": "^1.10.7",
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"esbuild": "^0.13.4",
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"eslint-config-airbnb-base": "^14.2.1",
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"eslint-plugin-import": "^2.24.2",
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"eslint-plugin-import": "^2.25.1",
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"eslint-plugin-json": "^3.1.0",
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"eslint-plugin-node": "^11.1.0",
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"eslint-plugin-promise": "^5.1.0",
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"eslint": "8.0.0",
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"node-fetch": "^3.0.0",
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"rimraf": "^3.0.2",
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"seedrandom": "^3.0.5",
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@ -87,6 +88,5 @@
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"typescript": "4.4.3"
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},
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"dependencies": {
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"eslint": "7.32.0"
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}
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}
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After Width: | Height: | Size: 211 KiB |
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@ -227,7 +227,7 @@ export class Human {
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this.#numTensors = currentTensors;
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const leaked = currentTensors - previousTensors;
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if (leaked !== 0) log(...msg, leaked);
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}
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};
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// quick sanity check on inputs
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/** @hidden */
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@ -241,7 +241,7 @@ export class Human {
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return 'backend not loaded';
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}
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return null;
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}
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};
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/** Reset configuration to default values */
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reset(): void {
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@ -350,7 +350,7 @@ export class Human {
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/** @hidden */
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emit = (event: string) => {
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if (this.events && this.events.dispatchEvent) this.events?.dispatchEvent(new Event(event));
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}
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};
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/** Runs interpolation using last known result and returns smoothened result
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* Interpolation is based on time since last known result so can be called independently
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@ -5,6 +5,14 @@
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import * as shaders from './imagefxshaders';
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const collect = (source, prefix, collection) => {
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const r = new RegExp('\\b' + prefix + ' \\w+ (\\w+)', 'ig');
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source.replace(r, (match, name) => {
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collection[name] = 0;
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return match;
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});
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};
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class GLProgram {
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uniform = {};
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attribute = {};
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@ -20,21 +28,13 @@ class GLProgram {
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this.gl.linkProgram(this.id);
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if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) throw new Error(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);
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this.gl.useProgram(this.id);
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this.collect(vertexSource, 'attribute', this.attribute); // Collect attributes
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collect(vertexSource, 'attribute', this.attribute); // Collect attributes
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for (const a in this.attribute) this.attribute[a] = this.gl.getAttribLocation(this.id, a);
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this.collect(vertexSource, 'uniform', this.uniform); // Collect uniforms
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this.collect(fragmentSource, 'uniform', this.uniform);
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collect(vertexSource, 'uniform', this.uniform); // Collect uniforms
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collect(fragmentSource, 'uniform', this.uniform);
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for (const u in this.uniform) this.uniform[u] = this.gl.getUniformLocation(this.id, u);
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}
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collect = (source, prefix, collection) => {
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const r = new RegExp('\\b' + prefix + ' \\w+ (\\w+)', 'ig');
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source.replace(r, (match, name) => {
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collection[name] = 0;
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return match;
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});
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};
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compile = (source, type): WebGLShader => {
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const shader = this.gl.createShader(type) as WebGLShader;
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this.gl.shaderSource(shader, source);
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