mirror of https://github.com/vladmandic/human
cache invalidation improvements
Vladimir Mandic
parent
4c2bc9a48a
commit
f705ce9dce
14
config.js
14
config.js
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@ -56,9 +56,9 @@ export default {
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skipFrames: 15, // how many frames to go without re-running the face bounding box detector, only used for video inputs
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// if model is running st 25 FPS, we can re-use existing bounding box for updated face mesh analysis
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// as face probably hasn't moved much in short time (10 * 1/25 = 0.25 sec)
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minConfidence: 0.3, // threshold for discarding a prediction
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minConfidence: 0.5, // threshold for discarding a prediction
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iouThreshold: 0.3, // threshold for deciding whether boxes overlap too much in non-maximum suppression
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scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score in non-maximum suppression
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scoreThreshold: 0.8, // threshold for deciding when to remove boxes based on score in non-maximum suppression
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},
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mesh: {
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enabled: true,
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@ -80,13 +80,13 @@ export default {
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},
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gender: {
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enabled: true,
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minConfidence: 0.3, // threshold for discarding a prediction
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minConfidence: 0.5, // threshold for discarding a prediction
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modelPath: '../models/ssrnet-gender-imdb.json',
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},
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emotion: {
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enabled: true,
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inputSize: 64, // fixed value
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minConfidence: 0.3, // threshold for discarding a prediction
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minConfidence: 0.5, // threshold for discarding a prediction
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skipFrames: 15, // how many frames to go without re-running the detector
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modelPath: '../models/emotion-large.json', // can be 'mini', 'large'
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},
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@ -97,7 +97,7 @@ export default {
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inputResolution: 257, // fixed value
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outputStride: 16, // fixed value
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maxDetections: 10, // maximum number of people detected in the input, should be set to the minimum number for performance
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scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score in non-maximum suppression
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scoreThreshold: 0.8, // threshold for deciding when to remove boxes based on score in non-maximum suppression
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nmsRadius: 20, // radius for deciding points are too close in non-maximum suppression
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},
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hand: {
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@ -106,9 +106,9 @@ export default {
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skipFrames: 15, // how many frames to go without re-running the hand bounding box detector, only used for video inputs
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// if model is running st 25 FPS, we can re-use existing bounding box for updated hand skeleton analysis
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// as the hand probably hasn't moved much in short time (10 * 1/25 = 0.25 sec)
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minConfidence: 0.3, // threshold for discarding a prediction
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minConfidence: 0.5, // threshold for discarding a prediction
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iouThreshold: 0.3, // threshold for deciding whether boxes overlap too much in non-maximum suppression
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scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score in non-maximum suppression
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scoreThreshold: 0.8, // threshold for deciding when to remove boxes based on score in non-maximum suppression
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enlargeFactor: 1.65, // empiric tuning as skeleton prediction prefers hand box with some whitespace
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maxHands: 10, // maximum number of hands detected in the input, should be set to the minimum number for performance
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detector: {
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155
demo/browser.js
155
demo/browser.js
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@ -16,7 +16,7 @@ const ui = {
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busy: false,
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facing: true,
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useWorker: false,
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worker: 'worker.js',
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worker: 'demo/worker.js',
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samples: ['../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg'],
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drawBoxes: true,
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drawPoints: false,
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@ -29,45 +29,6 @@ const ui = {
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modelsWarmup: true,
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};
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// configuration overrides
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const config = {
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backend: 'webgl',
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profile: false,
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deallocate: false,
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wasm: { path: '../assets' },
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async: true,
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filter: {
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enabled: true,
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width: 0,
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height: 0,
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brightness: 0,
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contrast: 0,
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sharpness: 0,
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blur: 0,
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saturation: 0,
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hue: 0,
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negative: false,
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sepia: false,
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vintage: false,
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kodachrome: false,
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technicolor: false,
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polaroid: false,
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pixelate: 0 },
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videoOptimized: true,
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face: {
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enabled: true,
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detector: { maxFaces: 10, skipFrames: 15, minConfidence: 0.3, iouThreshold: 0.3, scoreThreshold: 0.5 },
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mesh: { enabled: true },
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iris: { enabled: true },
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age: { enabled: true, skipFrames: 15 },
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gender: { enabled: true },
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emotion: { enabled: true, minConfidence: 0.3, useGrayscale: true },
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},
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body: { enabled: true, maxDetections: 10, scoreThreshold: 0.5, nmsRadius: 20 },
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hand: { enabled: true, skipFrames: 15, minConfidence: 0.3, iouThreshold: 0.3, scoreThreshold: 0.5 },
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gesture: { enabled: true },
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};
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// global variables
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let menu;
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let menuFX;
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@ -218,7 +179,7 @@ function webWorker(input, image, canvas) {
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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, config }, [image.data.buffer]);
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worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height }, [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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@ -242,10 +203,10 @@ function runHumanDetect(input, canvas) {
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// perform detection in worker
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webWorker(input, data, canvas);
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} else {
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human.detect(input, config).then((result) => {
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human.detect(input).then((result) => {
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if (result.error) log(result.error);
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else drawResults(input, result, canvas);
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if (config.profile) log('profile data:', human.profile());
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if (human.config.profile) log('profile data:', human.profile());
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});
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}
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}
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@ -260,9 +221,9 @@ async function processImage(input) {
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const canvas = document.getElementById('canvas');
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image.width = image.naturalWidth;
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image.height = image.naturalHeight;
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canvas.width = config.filter.width && config.filter.width > 0 ? config.filter.width : image.naturalWidth;
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canvas.height = config.filter.height && config.filter.height > 0 ? config.filter.height : image.naturalHeight;
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const result = await human.detect(image, config);
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canvas.width = human.config.filter.width && human.config.filter.width > 0 ? human.config.filter.width : image.naturalWidth;
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canvas.height = human.config.filter.height && human.config.filter.height > 0 ? human.config.filter.height : image.naturalHeight;
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const result = await human.detect(image);
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drawResults(image, result, canvas);
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const thumb = document.createElement('canvas');
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thumb.className = 'thumbnail';
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@ -280,7 +241,7 @@ async function processImage(input) {
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// just initialize everything and call main function
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async function detectVideo() {
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config.videoOptimized = true;
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human.config.videoOptimized = true;
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document.getElementById('samples-container').style.display = 'none';
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document.getElementById('canvas').style.display = 'block';
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const video = document.getElementById('video');
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@ -304,7 +265,7 @@ async function detectVideo() {
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// just initialize everything and call main function
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async function detectSampleImages() {
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document.getElementById('play').style.display = 'none';
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config.videoOptimized = false;
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human.config.videoOptimized = false;
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const size = Math.trunc(ui.columns * 25600 / window.innerWidth);
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ui.baseFont = ui.baseFontProto.replace(/{size}/, `${size}px`);
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ui.baseLineHeight = ui.baseLineHeightProto * ui.columns;
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@ -324,49 +285,49 @@ function setupMenu() {
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document.getElementById('play').addEventListener('click', () => btn.click());
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menu.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menu.addList('Backend', ['cpu', 'webgl', 'wasm', 'webgpu'], config.backend, (val) => config.backend = val);
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menu.addBool('Async Operations', config, 'async');
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menu.addBool('Enable Profiler', config, 'profile');
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menu.addBool('Memory Shield', config, 'deallocate');
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menu.addList('Backend', ['cpu', 'webgl', 'wasm', 'webgpu'], human.config.backend, (val) => human.config.backend = val);
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menu.addBool('Async Operations', human.config, 'async');
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menu.addBool('Enable Profiler', human.config, 'profile');
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menu.addBool('Memory Shield', human.config, 'deallocate');
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menu.addBool('Use Web Worker', ui, 'useWorker');
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menu.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menu.addLabel('Enabled Models');
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menu.addBool('Face Detect', config.face, 'enabled');
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menu.addBool('Face Mesh', config.face.mesh, 'enabled');
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menu.addBool('Face Iris', config.face.iris, 'enabled');
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menu.addBool('Face Age', config.face.age, 'enabled');
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menu.addBool('Face Gender', config.face.gender, 'enabled');
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menu.addBool('Face Emotion', config.face.emotion, 'enabled');
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menu.addBool('Body Pose', config.body, 'enabled');
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menu.addBool('Hand Pose', config.hand, 'enabled');
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menu.addBool('Gesture Analysis', config.gesture, 'enabled');
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menu.addBool('Face Detect', human.config.face, 'enabled');
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menu.addBool('Face Mesh', human.config.face.mesh, 'enabled');
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menu.addBool('Face Iris', human.config.face.iris, 'enabled');
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menu.addBool('Face Age', human.config.face.age, 'enabled');
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menu.addBool('Face Gender', human.config.face.gender, 'enabled');
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menu.addBool('Face Emotion', human.config.face.emotion, 'enabled');
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menu.addBool('Body Pose', human.config.body, 'enabled');
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menu.addBool('Hand Pose', human.config.hand, 'enabled');
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menu.addBool('Gesture Analysis', human.config.gesture, 'enabled');
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menu.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menu.addLabel('Model Parameters');
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menu.addRange('Max Objects', config.face.detector, 'maxFaces', 1, 50, 1, (val) => {
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config.face.detector.maxFaces = parseInt(val);
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config.body.maxDetections = parseInt(val);
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config.hand.maxHands = parseInt(val);
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menu.addRange('Max Objects', human.config.face.detector, 'maxFaces', 1, 50, 1, (val) => {
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human.config.face.detector.maxFaces = parseInt(val);
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human.config.body.maxDetections = parseInt(val);
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human.config.hand.maxHands = parseInt(val);
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});
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menu.addRange('Skip Frames', config.face.detector, 'skipFrames', 0, 50, 1, (val) => {
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config.face.detector.skipFrames = parseInt(val);
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config.face.emotion.skipFrames = parseInt(val);
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config.face.age.skipFrames = parseInt(val);
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config.hand.skipFrames = parseInt(val);
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menu.addRange('Skip Frames', human.config.face.detector, 'skipFrames', 0, 50, 1, (val) => {
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human.config.face.detector.skipFrames = parseInt(val);
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human.config.face.emotion.skipFrames = parseInt(val);
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human.config.face.age.skipFrames = parseInt(val);
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human.config.hand.skipFrames = parseInt(val);
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});
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menu.addRange('Min Confidence', config.face.detector, 'minConfidence', 0.0, 1.0, 0.05, (val) => {
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config.face.detector.minConfidence = parseFloat(val);
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config.face.emotion.minConfidence = parseFloat(val);
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config.hand.minConfidence = parseFloat(val);
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menu.addRange('Min Confidence', human.config.face.detector, 'minConfidence', 0.0, 1.0, 0.05, (val) => {
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human.config.face.detector.minConfidence = parseFloat(val);
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human.config.face.emotion.minConfidence = parseFloat(val);
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human.config.hand.minConfidence = parseFloat(val);
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});
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menu.addRange('Score Threshold', config.face.detector, 'scoreThreshold', 0.1, 1.0, 0.05, (val) => {
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config.face.detector.scoreThreshold = parseFloat(val);
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config.hand.scoreThreshold = parseFloat(val);
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config.body.scoreThreshold = parseFloat(val);
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menu.addRange('Score Threshold', human.config.face.detector, 'scoreThreshold', 0.1, 1.0, 0.05, (val) => {
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human.config.face.detector.scoreThreshold = parseFloat(val);
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human.config.hand.scoreThreshold = parseFloat(val);
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human.config.body.scoreThreshold = parseFloat(val);
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});
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menu.addRange('IOU Threshold', config.face.detector, 'iouThreshold', 0.1, 1.0, 0.05, (val) => {
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config.face.detector.iouThreshold = parseFloat(val);
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config.hand.iouThreshold = parseFloat(val);
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menu.addRange('IOU Threshold', human.config.face.detector, 'iouThreshold', 0.1, 1.0, 0.05, (val) => {
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human.config.face.detector.iouThreshold = parseFloat(val);
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human.config.hand.iouThreshold = parseFloat(val);
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});
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menu.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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@ -382,22 +343,22 @@ function setupMenu() {
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menuFX.addBool('Fill Polygons', ui, 'fillPolygons');
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menuFX.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
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menuFX.addLabel('Image Processing');
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menuFX.addBool('Enabled', config.filter, 'enabled');
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menuFX.addRange('Image width', config.filter, 'width', 0, 3840, 10, (val) => config.filter.width = parseInt(val));
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menuFX.addRange('Image height', config.filter, 'height', 0, 2160, 10, (val) => config.filter.height = parseInt(val));
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menuFX.addRange('Brightness', config.filter, 'brightness', -1.0, 1.0, 0.05, (val) => config.filter.brightness = parseFloat(val));
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menuFX.addRange('Contrast', config.filter, 'contrast', -1.0, 1.0, 0.05, (val) => config.filter.contrast = parseFloat(val));
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menuFX.addRange('Sharpness', config.filter, 'sharpness', 0, 1.0, 0.05, (val) => config.filter.sharpness = parseFloat(val));
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menuFX.addRange('Blur', config.filter, 'blur', 0, 20, 1, (val) => config.filter.blur = parseInt(val));
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menuFX.addRange('Saturation', config.filter, 'saturation', -1.0, 1.0, 0.05, (val) => config.filter.saturation = parseFloat(val));
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menuFX.addRange('Hue', config.filter, 'hue', 0, 360, 5, (val) => config.filter.hue = parseInt(val));
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menuFX.addRange('Pixelate', config.filter, 'pixelate', 0, 32, 1, (val) => config.filter.pixelate = parseInt(val));
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menuFX.addBool('Negative', config.filter, 'negative');
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menuFX.addBool('Sepia', config.filter, 'sepia');
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menuFX.addBool('Vintage', config.filter, 'vintage');
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menuFX.addBool('Kodachrome', config.filter, 'kodachrome');
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menuFX.addBool('Technicolor', config.filter, 'technicolor');
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menuFX.addBool('Polaroid', config.filter, 'polaroid');
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menuFX.addBool('Enabled', human.config.filter, 'enabled');
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menuFX.addRange('Image width', human.config.filter, 'width', 0, 3840, 10, (val) => human.config.filter.width = parseInt(val));
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menuFX.addRange('Image height', human.config.filter, 'height', 0, 2160, 10, (val) => human.config.filter.height = parseInt(val));
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menuFX.addRange('Brightness', human.config.filter, 'brightness', -1.0, 1.0, 0.05, (val) => human.config.filter.brightness = parseFloat(val));
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menuFX.addRange('Contrast', human.config.filter, 'contrast', -1.0, 1.0, 0.05, (val) => human.config.filter.contrast = parseFloat(val));
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menuFX.addRange('Sharpness', human.config.filter, 'sharpness', 0, 1.0, 0.05, (val) => human.config.filter.sharpness = parseFloat(val));
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menuFX.addRange('Blur', human.config.filter, 'blur', 0, 20, 1, (val) => human.config.filter.blur = parseInt(val));
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menuFX.addRange('Saturation', human.config.filter, 'saturation', -1.0, 1.0, 0.05, (val) => human.config.filter.saturation = parseFloat(val));
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menuFX.addRange('Hue', human.config.filter, 'hue', 0, 360, 5, (val) => human.config.filter.hue = parseInt(val));
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menuFX.addRange('Pixelate', human.config.filter, 'pixelate', 0, 32, 1, (val) => human.config.filter.pixelate = parseInt(val));
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menuFX.addBool('Negative', human.config.filter, 'negative');
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menuFX.addBool('Sepia', human.config.filter, 'sepia');
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menuFX.addBool('Vintage', human.config.filter, 'vintage');
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menuFX.addBool('Kodachrome', human.config.filter, 'kodachrome');
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menuFX.addBool('Technicolor', human.config.filter, 'technicolor');
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menuFX.addBool('Polaroid', human.config.filter, 'polaroid');
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}
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async function main() {
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@ -14,10 +14,9 @@ onmessage = async (msg) => {
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busy = true;
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// worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, config }, [image.data.buffer]);
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const image = new ImageData(new Uint8ClampedArray(msg.data.image), msg.data.width, msg.data.height);
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config = msg.data.config;
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let result = {};
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try {
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result = await human.detect(image, config);
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result = await human.detect(image);
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} catch (err) {
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result.error = err.message;
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log('worker thread error:', err.message);
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@ -41,7 +41,7 @@
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"scripts": {
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"start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",
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"lint": "eslint src/*.js demo/*.js",
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"dev": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation dev-server.js",
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"dev": "npm install && node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation dev-server.js",
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"build-iife": "esbuild --bundle --minify --platform=browser --sourcemap --target=es2018 --format=iife --external:fs --global-name=Human --metafile=dist/human.json --outfile=dist/human.js src/human.js",
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"build-esm-bundle": "esbuild --bundle --minify --platform=browser --sourcemap --target=es2018 --format=esm --external:fs --metafile=dist/human.esm.json --outfile=dist/human.esm.js src/human.js",
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"build-esm-nobundle": "esbuild --bundle --minify --platform=browser --sourcemap --target=es2018 --format=esm --external:@tensorflow --external:fs --metafile=dist/human.esm-nobundle.json --outfile=dist/human.esm-nobundle.js src/human.js",
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@ -14,12 +14,12 @@ async function load(config) {
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}
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async function predict(image, config) {
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if ((frame < config.face.age.skipFrames) && last.age && (last.age > 0)) {
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frame += 1;
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return last;
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}
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frame = 0;
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return new Promise(async (resolve) => {
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if (frame < config.face.age.skipFrames) {
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frame += 1;
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resolve(last);
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}
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frame = 0;
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const box = [[
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(image.shape[1] * zoom[0]) / image.shape[1],
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(image.shape[2] * zoom[1]) / image.shape[2],
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@ -17,12 +17,12 @@ async function load(config) {
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|||
}
|
||||
|
||||
async function predict(image, config) {
|
||||
if ((frame < config.face.emotion.skipFrames) && (last.length > 0)) {
|
||||
frame += 1;
|
||||
return last;
|
||||
}
|
||||
frame = 0;
|
||||
return new Promise(async (resolve) => {
|
||||
if (frame < config.face.emotion.skipFrames) {
|
||||
frame += 1;
|
||||
resolve(last);
|
||||
}
|
||||
frame = 0;
|
||||
const box = [[
|
||||
(image.shape[1] * zoom[0]) / image.shape[1],
|
||||
(image.shape[2] * zoom[1]) / image.shape[2],
|
||||
|
|
|
|||
|
|
@ -14,12 +14,12 @@ async function load(config) {
|
|||
}
|
||||
|
||||
async function predict(image, config) {
|
||||
if ((frame < config.face.age.skipFrames) && last.gender !== '') {
|
||||
frame += 1;
|
||||
return last;
|
||||
}
|
||||
frame = 0;
|
||||
return new Promise(async (resolve) => {
|
||||
if (frame < config.face.age.skipFrames) {
|
||||
frame += 1;
|
||||
resolve(last);
|
||||
}
|
||||
frame = 0;
|
||||
const box = [[
|
||||
(image.shape[1] * zoom[0]) / image.shape[1],
|
||||
(image.shape[2] * zoom[1]) / image.shape[2],
|
||||
|
|
|
|||
Loading…
Reference in New Issue