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human
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implelented input resizing

pull/50/head
Vladimir Mandic 2020-10-27 10:06:01 -04:00
parent a89e56b8a6
commit f185d44513
19 changed files with 10761 additions and 21866 deletions
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12
README.md
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@ -37,7 +37,7 @@ Detailed configuration options are explained below, but they are best seen in th
## Installation
**Important**
*The packaged (IIFE and ESM) version of `Human` includes `TensorFlow/JS (TFJS) 2.6.0` library which can be accessed via `human.tf`*
*The packaged (IIFE and ESM) version of `Human` includes `TensorFlow/JS (TFJS) 2.7.0` library which can be accessed via `human.tf`*
*You should NOT manually load another instance of `tfjs`, but if you do, be aware of possible version conflicts*
There are multiple ways to use `Human` library, pick one that suits you:
@ -253,6 +253,12 @@ config = {
filter: { // note: image filters are only available in Browser environments and not in NodeJS as they require WebGL for processing
enabled: true, // enable image pre-processing filters
return: true, // return processed canvas imagedata in result
width: 0, // resize input width
height: 0, // resize input height
// usefull on low-performance devices to reduce the size of processed input
// if both width and height are set to 0, there is no resizing
// if just one is set, second one is scaled automatically
// if both are set, values are used as-is
brightness: 0, // range: -1 (darken) to 1 (lighten)
contrast: 0, // range: -1 (reduce contrast) to 1 (increase contrast)
sharpness: 0, // range: 0 (no sharpening) to 1 (maximum sharpening)
@ -436,7 +442,7 @@ Performance will vary depending on your hardware, but also on number of resoluti
For example, it can perform multiple face detections at 60+ FPS, but drops to ~15 FPS on a medium complex images if all modules are enabled
### Performance per module on a **notebook** with nVidia GTX1050 GPU:
### Performance per module on a **notebook** with nVidia GTX1050 GPU on a FullHD input:
- Enabled all: 15 FPS
- Image filters: 80 FPS (standalone)
@ -449,7 +455,7 @@ For example, it can perform multiple face detections at 60+ FPS, but drops to ~1
- Hand: 40 FPS (standalone)
- Body: 50 FPS (standalone)
### Performance per module on a **smartphone** with Snapdragon 855:
### Performance per module on a **smartphone** with Snapdragon 855 on a FullHD input:
- Enabled all: 3 FPS
- Image filters: 30 FPS (standalone)

5
config.js
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@ -10,6 +10,11 @@ export default {
videoOptimized: true, // perform additional optimizations when input is video, must be disabled for images
filter: {
enabled: true, // enable image pre-processing filters
width: 0, // resize input width
height: 0, // resize input height
// if both width and height are set to 0, there is no resizing
// if just one is set, second one is scaled automatically
// if both are set, values are used as-is
return: true, // return processed canvas imagedata in result
brightness: 0, // range: -1 (darken) to 1 (lighten)
contrast: 0, // range: -1 (reduce contrast) to 1 (increase contrast)

33
demo/browser.js
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@ -7,6 +7,7 @@ const human = new Human();
// ui options
const ui = {
baseColor: 'rgba(173, 216, 230, 0.3)', // this is 'lightblue', just with alpha channel
baseBackground: 'rgba(50, 50, 50, 1)', // this is 'lightblue', just with alpha channel
baseLabel: 'rgba(173, 216, 230, 0.9)',
baseFontProto: 'small-caps {size} "Segoe UI"',
baseLineWidth: 16,
@ -29,7 +30,23 @@ const ui = {
// configuration overrides
const config = {
backend: 'webgl', // if you want to use 'wasm' backend, enable script load of tf and tf-backend-wasm in index.html
filter: { enabled: true, brightness: 0, contrast: 0, sharpness: 0, blur: 0, saturation: 0, hue: 0, negative: false, sepia: false, vintage: false, kodachrome: false, technicolor: false, polaroid: false, pixelate: 0 },
filter: {
enabled: true,
width: 720,
height: 0,
brightness: 0,
contrast: 0,
sharpness: 0,
blur: 0,
saturation: 0,
hue: 0,
negative: false,
sepia: false,
vintage: false,
kodachrome: false,
technicolor: false,
polaroid: false,
pixelate: 0 },
videoOptimized: true,
face: {
enabled: true,
@ -80,7 +97,9 @@ function drawResults(input, result, canvas) {
// draw image from video
const ctx = canvas.getContext('2d');
if (result.canvas) ctx.drawImage(result.canvas, 0, 0, result.canvas.width, result.canvas.height, 0, 0, canvas.width, canvas.height);
ctx.fillStyle = ui.baseBackground;
ctx.fillRect(0, 0, canvas.width, canvas.height);
if (result.canvas) ctx.drawImage(result.canvas, 0, 0, result.canvas.width, result.canvas.height, 0, 0, result.canvas.width, result.canvas.height);
else ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);
// draw all results
draw.face(result.face, canvas, ui, human.facemesh.triangulation);
@ -130,8 +149,8 @@ async function setupCamera() {
video.onloadeddata = async () => {
video.width = video.videoWidth;
video.height = video.videoHeight;
canvas.width = video.videoWidth;
canvas.height = video.videoHeight;
canvas.width = video.width;
canvas.height = video.height;
if (live) video.play();
ui.busy = false;
// do once more because onresize events can be delayed or skipped
@ -194,8 +213,8 @@ async function processImage(input) {
const canvas = document.getElementById('canvas');
image.width = image.naturalWidth;
image.height = image.naturalHeight;
canvas.width = image.naturalWidth;
canvas.height = image.naturalHeight;
canvas.width = config.filter.width && config.filter.width > 0 ? config.filter.width : image.naturalWidth;
canvas.height = config.filter.height && config.filter.height > 0 ? config.filter.height : image.naturalHeight;
const result = await human.detect(image, config);
drawResults(image, result, canvas);
const thumb = document.createElement('canvas');
@ -302,6 +321,8 @@ function setupMenu() {
menuFX.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
menuFX.addLabel('Image Filters');
menuFX.addBool('Enabled', config.filter, 'enabled');
menuFX.addRange('Image width', config.filter, 'width', 100, 3840, 10, (val) => config.filter.width = parseInt(val));
menuFX.addRange('Image height', config.filter, 'height', 100, 2160, 10, (val) => config.filter.height = parseInt(val));
menuFX.addRange('Brightness', config.filter, 'brightness', -1.0, 1.0, 0.05, (val) => config.filter.brightness = parseFloat(val));
menuFX.addRange('Contrast', config.filter, 'contrast', -1.0, 1.0, 0.05, (val) => config.filter.contrast = parseFloat(val));
menuFX.addRange('Sharpness', config.filter, 'sharpness', 0, 1.0, 0.05, (val) => config.filter.sharpness = parseFloat(val));

44
dist/human.cjs vendored
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@ -1,4 +1,5 @@
var __defineProperty = Object.defineProperty;
var __defProp = Object.defineProperty;
var __markAsModule = (target) => __defProp(target, "__esModule", {value: true});
var __commonJS = (callback, module2) => () => {
if (!module2) {
module2 = {exports: {}};
@ -6,13 +7,10 @@ var __commonJS = (callback, module2) => () => {
}
return module2.exports;
};
var __markAsModule = (target) => {
return __defineProperty(target, "__esModule", {value: true});
};
var __export = (target, all) => {
__markAsModule(target);
for (var name in all)
__defineProperty(target, name, {get: all[name], enumerable: true});
__defProp(target, name, {get: all[name], enumerable: true});
};
// src/facemesh/blazeface.js
@ -5688,6 +5686,8 @@ var require_config = __commonJS((exports2) => {
videoOptimized: true,
filter: {
enabled: true,
width: 0,
height: 0,
return: true,
brightness: 0,
contrast: 0,
@ -5777,7 +5777,7 @@ var require_config = __commonJS((exports2) => {
var require_package = __commonJS((exports2, module2) => {
module2.exports = {
name: "@vladmandic/human",
version: "0.4.2",
version: "0.4.3",
description: "human: 3D Face Detection, Iris Tracking and Age & Gender Prediction",
sideEffects: false,
main: "dist/human.cjs",
@ -5799,19 +5799,19 @@ var require_package = __commonJS((exports2, module2) => {
dependencies: {},
peerDependencies: {},
devDependencies: {
"@tensorflow/tfjs": "^2.7.0",
"@tensorflow/tfjs-node": "^2.7.0",
"@vladmandic/pilogger": "^0.2.6",
dayjs: "^1.9.3",
"simple-git": "^2.21.0",
"@tensorflow/tfjs": "^2.6.0",
"@tensorflow/tfjs-node": "^2.6.0",
esbuild: "^0.7.15",
eslint: "^7.10.0",
dayjs: "^1.9.4",
esbuild: "^0.7.21",
eslint: "^7.12.1",
"eslint-config-airbnb-base": "^14.2.0",
"eslint-plugin-import": "^2.22.1",
"eslint-plugin-json": "^2.1.2",
"eslint-plugin-node": "^11.1.0",
"eslint-plugin-promise": "^4.2.1",
rimraf: "^3.0.2"
rimraf: "^3.0.2",
"simple-git": "^2.21.0"
},
scripts: {
start: "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",
@ -5962,14 +5962,24 @@ class Human {
tfImage(input) {
let filtered;
if (this.fx && this.config.filter.enabled && !(input instanceof tf.Tensor)) {
const width = input.naturalWidth || input.videoWidth || input.width || input.shape && input.shape[1] > 0;
const height = input.naturalHeight || input.videoHeight || input.height || input.shape && input.shape[2] > 0;
const offscreenCanvas = new OffscreenCanvas(width, height);
const originalWidth = input.naturalWidth || input.videoWidth || input.width || input.shape && input.shape[1] > 0;
const originalHeight = input.naturalHeight || input.videoHeight || input.height || input.shape && input.shape[2] > 0;
let targetWidth = originalWidth;
if (this.config.filter.width > 0)
targetWidth = this.config.filter.width;
else if (this.config.filter.height > 0)
targetWidth = originalWidth * (this.config.filter.height / originalHeight);
let targetHeight = originalHeight;
if (this.config.filter.height > 0)
targetHeight = this.config.filter.height;
else if (this.config.filter.width > 0)
targetHeight = originalHeight * (this.config.filter.width / originalWidth);
const offscreenCanvas = new OffscreenCanvas(targetWidth, targetHeight);
const ctx = offscreenCanvas.getContext("2d");
if (input instanceof ImageData)
ctx.putImageData(input, 0, 0);
else
ctx.drawImage(input, 0, 0, width, height, 0, 0, offscreenCanvas.width, offscreenCanvas.height);
ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, offscreenCanvas.width, offscreenCanvas.height);
this.fx.reset();
this.fx.addFilter("brightness", this.config.filter.brightness);
if (this.config.filter.contrast !== 0)

12
dist/human.cjs.json vendored
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@ -1,7 +1,7 @@
{
"inputs": {
"config.js": {
"bytes": 5942,
"bytes": 6295,
"imports": []
},
"package.json": {
@ -116,7 +116,7 @@
"imports": []
},
"src/human.js": {
"bytes": 11355,
"bytes": 11887,
"imports": [
{
"path": "src/facemesh/facemesh.js"
@ -260,7 +260,7 @@
"dist/human.cjs.map": {
"imports": [],
"inputs": {},
"bytes": 263891
"bytes": 260858
},
"dist/human.cjs": {
"imports": [],
@ -350,7 +350,7 @@
"bytesInOutput": 20197
},
"config.js": {
"bytesInOutput": 2199
"bytesInOutput": 2232
},
"package.json": {
"bytesInOutput": 2750
@ -359,10 +359,10 @@
"bytesInOutput": 47
},
"src/human.js": {
"bytesInOutput": 10193
"bytesInOutput": 10755
}
},
"bytes": 154534
"bytes": 155094
}
}
}

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dist/human.esm-nobundle.js vendored
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@ -1,4 +1,5 @@
var __defineProperty = Object.defineProperty;
var __defProp = Object.defineProperty;
var __markAsModule = (target) => __defProp(target, "__esModule", {value: true});
var __commonJS = (callback, module) => () => {
if (!module) {
module = {exports: {}};
@ -6,13 +7,10 @@ var __commonJS = (callback, module) => () => {
}
return module.exports;
};
var __markAsModule = (target) => {
return __defineProperty(target, "__esModule", {value: true});
};
var __export = (target, all) => {
__markAsModule(target);
for (var name in all)
__defineProperty(target, name, {get: all[name], enumerable: true});
__defProp(target, name, {get: all[name], enumerable: true});
};
// src/facemesh/blazeface.js
@ -5688,6 +5686,8 @@ var require_config = __commonJS((exports) => {
videoOptimized: true,
filter: {
enabled: true,
width: 0,
height: 0,
return: true,
brightness: 0,
contrast: 0,
@ -5777,7 +5777,7 @@ var require_config = __commonJS((exports) => {
var require_package = __commonJS((exports, module) => {
module.exports = {
name: "@vladmandic/human",
version: "0.4.2",
version: "0.4.3",
description: "human: 3D Face Detection, Iris Tracking and Age & Gender Prediction",
sideEffects: false,
main: "dist/human.cjs",
@ -5799,19 +5799,19 @@ var require_package = __commonJS((exports, module) => {
dependencies: {},
peerDependencies: {},
devDependencies: {
"@tensorflow/tfjs": "^2.7.0",
"@tensorflow/tfjs-node": "^2.7.0",
"@vladmandic/pilogger": "^0.2.6",
dayjs: "^1.9.3",
"simple-git": "^2.21.0",
"@tensorflow/tfjs": "^2.6.0",
"@tensorflow/tfjs-node": "^2.6.0",
esbuild: "^0.7.15",
eslint: "^7.10.0",
dayjs: "^1.9.4",
esbuild: "^0.7.21",
eslint: "^7.12.1",
"eslint-config-airbnb-base": "^14.2.0",
"eslint-plugin-import": "^2.22.1",
"eslint-plugin-json": "^2.1.2",
"eslint-plugin-node": "^11.1.0",
"eslint-plugin-promise": "^4.2.1",
rimraf: "^3.0.2"
rimraf: "^3.0.2",
"simple-git": "^2.21.0"
},
scripts: {
start: "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",
@ -5959,14 +5959,24 @@ class Human {
tfImage(input) {
let filtered;
if (this.fx && this.config.filter.enabled && !(input instanceof tf.Tensor)) {
const width = input.naturalWidth || input.videoWidth || input.width || input.shape && input.shape[1] > 0;
const height = input.naturalHeight || input.videoHeight || input.height || input.shape && input.shape[2] > 0;
const offscreenCanvas = new OffscreenCanvas(width, height);
const originalWidth = input.naturalWidth || input.videoWidth || input.width || input.shape && input.shape[1] > 0;
const originalHeight = input.naturalHeight || input.videoHeight || input.height || input.shape && input.shape[2] > 0;
let targetWidth = originalWidth;
if (this.config.filter.width > 0)
targetWidth = this.config.filter.width;
else if (this.config.filter.height > 0)
targetWidth = originalWidth * (this.config.filter.height / originalHeight);
let targetHeight = originalHeight;
if (this.config.filter.height > 0)
targetHeight = this.config.filter.height;
else if (this.config.filter.width > 0)
targetHeight = originalHeight * (this.config.filter.width / originalWidth);
const offscreenCanvas = new OffscreenCanvas(targetWidth, targetHeight);
const ctx = offscreenCanvas.getContext("2d");
if (input instanceof ImageData)
ctx.putImageData(input, 0, 0);
else
ctx.drawImage(input, 0, 0, width, height, 0, 0, offscreenCanvas.width, offscreenCanvas.height);
ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, offscreenCanvas.width, offscreenCanvas.height);
this.fx.reset();
this.fx.addFilter("brightness", this.config.filter.brightness);
if (this.config.filter.contrast !== 0)

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@ -1,7 +1,7 @@
{
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"config.js": {
"bytes": 5942,
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"imports": []
},
"package.json": {
@ -116,7 +116,7 @@
"imports": []
},
"src/human.js": {
"bytes": 11355,
"bytes": 11887,
"imports": [
{
"path": "src/facemesh/facemesh.js"
@ -260,7 +260,7 @@
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"inputs": {},
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},
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@ -350,19 +350,19 @@
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@ -1,11 +1,11 @@
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{
"path": "node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js"
@ -16,7 +16,7 @@
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{
"path": "node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js"
@ -24,7 +24,7 @@
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{
"path": "node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js"
@ -32,7 +32,7 @@
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@ -46,7 +46,7 @@
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@ -291,7 +291,7 @@
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"path": "node_modules/@tensorflow/tfjs/dist/tf.node.js"
@ -468,7 +468,7 @@
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@ -483,19 +483,19 @@
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@ -522,10 +522,10 @@
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@ -615,19 +615,19 @@
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@ -1,11 +1,11 @@
{
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{
"path": "node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js"
@ -16,7 +16,7 @@
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"bytes": 571410,
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{
"path": "node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js"
@ -24,7 +24,7 @@
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"imports": [
{
"path": "node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js"
@ -32,7 +32,7 @@
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@ -46,7 +46,7 @@
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@ -291,7 +291,7 @@
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@ -468,7 +468,7 @@
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@ -483,19 +483,19 @@
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@ -1397,14 +1399,20 @@
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}
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@ -1430,14 +1438,12 @@
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},
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"dev": true,
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}
@ -1452,7 +1458,6 @@
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"resolved": "https://registry.npmjs.org/is-symbol/-/is-symbol-1.0.3.tgz",
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"dev": true,
"requires": {
"has-symbols": "^1.0.1"
}
@ -1611,7 +1616,8 @@
"ms": {
"version": "2.1.2",
"resolved": "https://registry.npmjs.org/ms/-/ms-2.1.2.tgz",
"integrity": "sha512-sGkPx+VjMtmA6MX27oA4FBFELFCZZ4S4XqeGOXCv68tT+jb3vk/RyaKWP0PTKyWtmLSM0b+adUTEvbs1PEaH2w=="
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"dev": true
},
"natural-compare": {
"version": "1.4.0",
@ -1740,20 +1746,17 @@
"object-inspect": {
"version": "1.8.0",
"resolved": "https://registry.npmjs.org/object-inspect/-/object-inspect-1.8.0.tgz",
"integrity": "sha512-jLdtEOB112fORuypAyl/50VRVIBIdVQOSUUGQHzJ4xBSbit81zRarz7GThkEFZy1RceYrWYcPcBFPQwHyAc1gA==",
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},
"object-keys": {
"version": "1.1.1",
"resolved": "https://registry.npmjs.org/object-keys/-/object-keys-1.1.1.tgz",
"integrity": "sha512-NuAESUOUMrlIXOfHKzD6bpPu3tYt3xvjNdRIQ+FeT0lNb4K8WR70CaDxhuNguS2XG+GjkyMwOzsN5ZktImfhLA==",
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"resolved": "https://registry.npmjs.org/object.assign/-/object.assign-4.1.1.tgz",
"integrity": "sha512-VT/cxmx5yaoHSOTSyrCygIDFco+RsibY2NM0a4RdEeY/4KgqezwFtK1yr3U67xYhqJSlASm2pKhLVzPj2lr4bA==",
"dev": true,
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"define-properties": "^1.1.3",
"es-abstract": "^1.18.0-next.0",
@ -1934,8 +1937,7 @@
"path-parse": {
"version": "1.0.6",
"resolved": "https://registry.npmjs.org/path-parse/-/path-parse-1.0.6.tgz",
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},
"path-type": {
"version": "2.0.0",
@ -2052,11 +2054,11 @@
"dev": true
},
"resolve": {
"version": "1.17.0",
"resolved": "https://registry.npmjs.org/resolve/-/resolve-1.17.0.tgz",
"integrity": "sha512-ic+7JYiV8Vi2yzQGFWOkiZD5Z9z7O2Zhm9XMaTxdJExKasieFCr+yXZ/WmXsckHiKl12ar0y6XiXDx3m4RHn1w==",
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"resolved": "https://registry.npmjs.org/resolve/-/resolve-1.18.1.tgz",
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"is-core-module": "^2.0.0",
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}
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@ -2136,6 +2138,7 @@
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"resolved": "https://registry.npmjs.org/simple-git/-/simple-git-2.21.0.tgz",
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"dev": true,
"requires": {
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"@kwsites/promise-deferred": "^1.1.1",
@ -2146,6 +2149,7 @@
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"resolved": "https://registry.npmjs.org/debug/-/debug-4.2.0.tgz",
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"dev": true,
"requires": {
"ms": "2.1.2"
}
@ -2245,65 +2249,21 @@
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},
"string.prototype.trimend": {
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"resolved": "https://registry.npmjs.org/string.prototype.trimend/-/string.prototype.trimend-1.0.1.tgz",
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"string.prototype.trimstart": "^1.0.1"
}
}
"es-abstract": "^1.18.0-next.1"
}
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"string.prototype.trimstart": {
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"dev": true,
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"function-bind": "^1.1.1",
"has": "^1.0.3",
"has-symbols": "^1.0.1",
"is-callable": "^1.2.2",
"is-regex": "^1.1.1",
"object-inspect": "^1.8.0",
"object-keys": "^1.1.1",
"object.assign": "^4.1.1",
"string.prototype.trimend": "^1.0.1",
"string.prototype.trimstart": "^1.0.1"
}
}
"es-abstract": "^1.18.0-next.1"
}
},
"string_decoder": {
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"dev": true,
"requires": {
"has-flag": "^4.0.0"
}
@ -2596,9 +2557,9 @@
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},
"y18n": {
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"resolved": "https://registry.npmjs.org/y18n/-/y18n-5.0.2.tgz",
"integrity": "sha512-CkwaeZw6dQgqgPGeTWKMXCRmMcBgETFlTml1+ZOO+q7kGst8NREJ+eWwFNPVUQ4QGdAaklbqCZHH6Zuep1RjiA==",
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"dev": true
},
"yallist": {
@ -2623,9 +2584,9 @@
}
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"dev": true
}
}

14
package.json
View File

@ -22,19 +22,19 @@
"dependencies": {},
"peerDependencies": {},
"devDependencies": {
"@tensorflow/tfjs": "^2.7.0",
"@tensorflow/tfjs-node": "^2.7.0",
"@vladmandic/pilogger": "^0.2.6",
"dayjs": "^1.9.3",
"simple-git": "^2.21.0",
"@tensorflow/tfjs": "^2.6.0",
"@tensorflow/tfjs-node": "^2.6.0",
"esbuild": "^0.7.15",
"eslint": "^7.10.0",
"dayjs": "^1.9.4",
"esbuild": "^0.7.21",
"eslint": "^7.12.1",
"eslint-config-airbnb-base": "^14.2.0",
"eslint-plugin-import": "^2.22.1",
"eslint-plugin-json": "^2.1.2",
"eslint-plugin-node": "^11.1.0",
"eslint-plugin-promise": "^4.2.1",
"rimraf": "^3.0.2"
"rimraf": "^3.0.2",
"simple-git": "^2.21.0"
},
"scripts": {
"start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",

16
src/human.js
View File

@ -130,12 +130,20 @@ class Human {
// let imageData;
let filtered;
if (this.fx && this.config.filter.enabled && !(input instanceof tf.Tensor)) {
const width = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));
const height = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));
const offscreenCanvas = new OffscreenCanvas(width, height);
const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));
const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));
let targetWidth = originalWidth;
if (this.config.filter.width > 0) targetWidth = this.config.filter.width;
else if (this.config.filter.height > 0) targetWidth = originalWidth * (this.config.filter.height / originalHeight);
let targetHeight = originalHeight;
if (this.config.filter.height > 0) targetHeight = this.config.filter.height;
else if (this.config.filter.width > 0) targetHeight = originalHeight * (this.config.filter.width / originalWidth);
const offscreenCanvas = new OffscreenCanvas(targetWidth, targetHeight);
const ctx = offscreenCanvas.getContext('2d');
if (input instanceof ImageData) ctx.putImageData(input, 0, 0);
else ctx.drawImage(input, 0, 0, width, height, 0, 0, offscreenCanvas.width, offscreenCanvas.height);
else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, offscreenCanvas.width, offscreenCanvas.height);
this.fx.reset();
this.fx.addFilter('brightness', this.config.filter.brightness); // must have at least one filter enabled
if (this.config.filter.contrast !== 0) this.fx.addFilter('contrast', this.config.filter.contrast);