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improved caching and warmup

pull/50/head
Vladimir Mandic 2020-12-11 10:11:49 -05:00
parent 4cf71ea08e
commit cebd075047
19 changed files with 1833 additions and 123 deletions
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12
config.js
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@ -26,7 +26,9 @@ export default {
// must be disabled for images // must be disabled for images
// basically this skips object box boundary detection for every n frames // basically this skips object box boundary detection for every n frames
// while maintaining in-box detection since objects cannot move that fast // while maintaining in-box detection since objects cannot move that fast
warmup: 'full', // what to use for human.warmup(), can be 'none', 'face', 'full'
// warmup pre-initializes all models for faster inference but can take
// significant time on startup
filter: { filter: {
enabled: true, // enable image pre-processing filters enabled: true, // enable image pre-processing filters
width: 0, // resize input width width: 0, // resize input width
@ -69,7 +71,7 @@ export default {
// false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees
maxFaces: 10, // maximum number of faces detected in the input maxFaces: 10, // maximum number of faces detected in the input
// should be set to the minimum number for performance // should be set to the minimum number for performance
skipFrames: 20, // how many frames to go without re-running the face bounding box detector skipFrames: 11, // how many frames to go without re-running the face bounding box detector
// only used for video inputs // only used for video inputs
// e.g., if model is running st 25 FPS, we can re-use existing bounding // e.g., if model is running st 25 FPS, we can re-use existing bounding
// box for updated face analysis as the head probably hasn't moved much // box for updated face analysis as the head probably hasn't moved much
@ -99,7 +101,7 @@ export default {
modelPath: '../models/age-ssrnet-imdb.json', // can be 'age-ssrnet-imdb' or 'age-ssrnet-wiki' modelPath: '../models/age-ssrnet-imdb.json', // can be 'age-ssrnet-imdb' or 'age-ssrnet-wiki'
// which determines training set for model // which determines training set for model
inputSize: 64, // fixed value inputSize: 64, // fixed value
skipFrames: 41, // how many frames to go without re-running the detector skipFrames: 31, // how many frames to go without re-running the detector
// only used for video inputs // only used for video inputs
}, },
@ -108,7 +110,7 @@ export default {
minConfidence: 0.1, // threshold for discarding a prediction minConfidence: 0.1, // threshold for discarding a prediction
modelPath: '../models/gender-ssrnet-imdb.json', // can be 'gender', 'gender-ssrnet-imdb' or 'gender-ssrnet-wiki' modelPath: '../models/gender-ssrnet-imdb.json', // can be 'gender', 'gender-ssrnet-imdb' or 'gender-ssrnet-wiki'
inputSize: 64, // fixed value inputSize: 64, // fixed value
skipFrames: 42, // how many frames to go without re-running the detector skipFrames: 41, // how many frames to go without re-running the detector
// only used for video inputs // only used for video inputs
}, },
@ -143,7 +145,7 @@ export default {
rotation: false, // use best-guess rotated hand image or just box with rotation as-is rotation: false, // use best-guess rotated hand image or just box with rotation as-is
// false means higher performance, but incorrect finger mapping if hand is inverted // false means higher performance, but incorrect finger mapping if hand is inverted
inputSize: 256, // fixed value inputSize: 256, // fixed value
skipFrames: 19, // how many frames to go without re-running the hand bounding box detector skipFrames: 12, // how many frames to go without re-running the hand bounding box detector
// only used for video inputs // only used for video inputs
// e.g., if model is running st 25 FPS, we can re-use existing bounding // e.g., if model is running st 25 FPS, we can re-use existing bounding
// box for updated hand skeleton analysis as the hand probably // box for updated hand skeleton analysis as the hand probably

3
demo/browser.js
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@ -37,7 +37,6 @@ const ui = {
console: true, console: true,
maxFPSframes: 10, maxFPSframes: 10,
modelsPreload: true, modelsPreload: true,
modelsWarmup: true,
menuWidth: 0, menuWidth: 0,
menuHeight: 0, menuHeight: 0,
camera: {}, camera: {},
@ -518,7 +517,7 @@ async function main() {
status('loading'); status('loading');
await human.load(userConfig); // this is not required, just pre-loads all models await human.load(userConfig); // this is not required, just pre-loads all models
} }
if (ui.modelsWarmup && !ui.useWorker) { if (!ui.useWorker) {
status('initializing'); status('initializing');
await human.warmup(userConfig); // this is not required, just pre-warms all models for faster initial inference await human.warmup(userConfig); // this is not required, just pre-warms all models for faster initial inference
} }

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dist/demo-browser-index.json vendored
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@ -1,7 +1,7 @@
{ {
"inputs": { "inputs": {
"dist/human.esm.js": { "dist/human.esm.js": {
"bytes": 1786155, "bytes": 1830186,
"imports": [] "imports": []
}, },
"demo/draw.js": { "demo/draw.js": {
@ -17,7 +17,7 @@
"imports": [] "imports": []
}, },
"demo/browser.js": { "demo/browser.js": {
"bytes": 25469, "bytes": 25428,
"imports": [ "imports": [
{ {
"path": "dist/human.esm.js" "path": "dist/human.esm.js"
@ -38,14 +38,14 @@
"dist/demo-browser-index.js.map": { "dist/demo-browser-index.js.map": {
"imports": [], "imports": [],
"inputs": {}, "inputs": {},
"bytes": 2747800 "bytes": 2749760
}, },
"dist/demo-browser-index.js": { "dist/demo-browser-index.js": {
"imports": [], "imports": [],
"exports": [], "exports": [],
"inputs": { "inputs": {
"dist/human.esm.js": { "dist/human.esm.js": {
"bytesInOutput": 1778915 "bytesInOutput": 1822946
}, },
"demo/draw.js": { "demo/draw.js": {
"bytesInOutput": 7816 "bytesInOutput": 7816
@ -57,10 +57,10 @@
"bytesInOutput": 7382 "bytesInOutput": 7382
}, },
"demo/browser.js": { "demo/browser.js": {
"bytesInOutput": 19563 "bytesInOutput": 19529
} }
}, },
"bytes": 1832865 "bytes": 1876862
} }
} }
} }

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@ -36,7 +36,7 @@
"imports": [] "imports": []
}, },
"src/face/facepipeline.js": { "src/face/facepipeline.js": {
"bytes": 13856, "bytes": 13836,
"imports": [ "imports": [
{ {
"path": "dist/tfjs.esm.js" "path": "dist/tfjs.esm.js"
@ -84,7 +84,7 @@
] ]
}, },
"src/age/age.js": { "src/age/age.js": {
"bytes": 1943, "bytes": 2017,
"imports": [ "imports": [
{ {
"path": "src/log.js" "path": "src/log.js"
@ -98,7 +98,7 @@
] ]
}, },
"src/gender/gender.js": { "src/gender/gender.js": {
"bytes": 3384, "bytes": 2886,
"imports": [ "imports": [
{ {
"path": "src/log.js" "path": "src/log.js"
@ -112,7 +112,7 @@
] ]
}, },
"src/emotion/emotion.js": { "src/emotion/emotion.js": {
"bytes": 2981, "bytes": 3055,
"imports": [ "imports": [
{ {
"path": "src/log.js" "path": "src/log.js"
@ -264,7 +264,7 @@
] ]
}, },
"src/hand/handdetector.js": { "src/hand/handdetector.js": {
"bytes": 4252, "bytes": 4253,
"imports": [ "imports": [
{ {
"path": "dist/tfjs.esm.js" "path": "dist/tfjs.esm.js"
@ -279,7 +279,7 @@
"imports": [] "imports": []
}, },
"src/hand/handpipeline.js": { "src/hand/handpipeline.js": {
"bytes": 7923, "bytes": 7886,
"imports": [ "imports": [
{ {
"path": "dist/tfjs.esm.js" "path": "dist/tfjs.esm.js"
@ -342,7 +342,7 @@
] ]
}, },
"config.js": { "config.js": {
"bytes": 8990, "bytes": 9243,
"imports": [] "imports": []
}, },
"src/sample.js": { "src/sample.js": {
@ -354,7 +354,7 @@
"imports": [] "imports": []
}, },
"src/human.js": { "src/human.js": {
"bytes": 16524, "bytes": 16894,
"imports": [ "imports": [
{ {
"path": "src/log.js" "path": "src/log.js"
@ -408,7 +408,7 @@
"dist/human.esm.js.map": { "dist/human.esm.js.map": {
"imports": [], "imports": [],
"inputs": {}, "inputs": {},
"bytes": 2652161 "bytes": 2656485
}, },
"dist/human.esm.js": { "dist/human.esm.js": {
"imports": [], "imports": [],
@ -429,7 +429,7 @@
"bytesInOutput": 30817 "bytesInOutput": 30817
}, },
"src/face/facepipeline.js": { "src/face/facepipeline.js": {
"bytesInOutput": 9323 "bytesInOutput": 9314
}, },
"src/face/facemesh.js": { "src/face/facemesh.js": {
"bytesInOutput": 2182 "bytesInOutput": 2182
@ -438,13 +438,13 @@
"bytesInOutput": 846 "bytesInOutput": 846
}, },
"src/age/age.js": { "src/age/age.js": {
"bytesInOutput": 1112 "bytesInOutput": 1169
}, },
"src/gender/gender.js": { "src/gender/gender.js": {
"bytesInOutput": 1858 "bytesInOutput": 1915
}, },
"src/emotion/emotion.js": { "src/emotion/emotion.js": {
"bytesInOutput": 1738 "bytesInOutput": 1795
}, },
"src/embedding/embedding.js": { "src/embedding/embedding.js": {
"bytesInOutput": 1310 "bytesInOutput": 1310
@ -483,10 +483,10 @@
"bytesInOutput": 832 "bytesInOutput": 832
}, },
"src/hand/handdetector.js": { "src/hand/handdetector.js": {
"bytesInOutput": 2730 "bytesInOutput": 2731
}, },
"src/hand/handpipeline.js": { "src/hand/handpipeline.js": {
"bytesInOutput": 4456 "bytesInOutput": 4447
}, },
"src/hand/anchors.js": { "src/hand/anchors.js": {
"bytesInOutput": 127032 "bytesInOutput": 127032
@ -510,7 +510,7 @@
"bytesInOutput": 1520210 "bytesInOutput": 1520210
}, },
"src/human.js": { "src/human.js": {
"bytesInOutput": 10905 "bytesInOutput": 11073
}, },
"src/hand/box.js": { "src/hand/box.js": {
"bytesInOutput": 1473 "bytesInOutput": 1473
@ -519,16 +519,16 @@
"bytesInOutput": 1796 "bytesInOutput": 1796
}, },
"config.js": { "config.js": {
"bytesInOutput": 1440 "bytesInOutput": 1454
}, },
"src/sample.js": { "src/sample.js": {
"bytesInOutput": 11646 "bytesInOutput": 55341
}, },
"package.json": { "package.json": {
"bytesInOutput": 21 "bytesInOutput": 21
} }
}, },
"bytes": 1786155 "bytes": 1830186
} }
} }
} }

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@ -36,7 +36,7 @@
"imports": [] "imports": []
}, },
"src/face/facepipeline.js": { "src/face/facepipeline.js": {
"bytes": 13856, "bytes": 13836,
"imports": [ "imports": [
{ {
"path": "dist/tfjs.esm.js" "path": "dist/tfjs.esm.js"
@ -84,7 +84,7 @@
] ]
}, },
"src/age/age.js": { "src/age/age.js": {
"bytes": 1943, "bytes": 2017,
"imports": [ "imports": [
{ {
"path": "src/log.js" "path": "src/log.js"
@ -98,7 +98,7 @@
] ]
}, },
"src/gender/gender.js": { "src/gender/gender.js": {
"bytes": 3384, "bytes": 2886,
"imports": [ "imports": [
{ {
"path": "src/log.js" "path": "src/log.js"
@ -112,7 +112,7 @@
] ]
}, },
"src/emotion/emotion.js": { "src/emotion/emotion.js": {
"bytes": 2981, "bytes": 3055,
"imports": [ "imports": [
{ {
"path": "src/log.js" "path": "src/log.js"
@ -264,7 +264,7 @@
] ]
}, },
"src/hand/handdetector.js": { "src/hand/handdetector.js": {
"bytes": 4252, "bytes": 4253,
"imports": [ "imports": [
{ {
"path": "dist/tfjs.esm.js" "path": "dist/tfjs.esm.js"
@ -279,7 +279,7 @@
"imports": [] "imports": []
}, },
"src/hand/handpipeline.js": { "src/hand/handpipeline.js": {
"bytes": 7923, "bytes": 7886,
"imports": [ "imports": [
{ {
"path": "dist/tfjs.esm.js" "path": "dist/tfjs.esm.js"
@ -342,7 +342,7 @@
] ]
}, },
"config.js": { "config.js": {
"bytes": 8990, "bytes": 9243,
"imports": [] "imports": []
}, },
"src/sample.js": { "src/sample.js": {
@ -354,7 +354,7 @@
"imports": [] "imports": []
}, },
"src/human.js": { "src/human.js": {
"bytes": 16524, "bytes": 16894,
"imports": [ "imports": [
{ {
"path": "src/log.js" "path": "src/log.js"
@ -408,7 +408,7 @@
"dist/human.js.map": { "dist/human.js.map": {
"imports": [], "imports": [],
"inputs": {}, "inputs": {},
"bytes": 2669160 "bytes": 2673870
}, },
"dist/human.js": { "dist/human.js": {
"imports": [], "imports": [],
@ -427,7 +427,7 @@
"bytesInOutput": 30817 "bytesInOutput": 30817
}, },
"src/face/facepipeline.js": { "src/face/facepipeline.js": {
"bytesInOutput": 9323 "bytesInOutput": 9314
}, },
"src/face/facemesh.js": { "src/face/facemesh.js": {
"bytesInOutput": 2182 "bytesInOutput": 2182
@ -436,13 +436,13 @@
"bytesInOutput": 846 "bytesInOutput": 846
}, },
"src/age/age.js": { "src/age/age.js": {
"bytesInOutput": 1112 "bytesInOutput": 1169
}, },
"src/gender/gender.js": { "src/gender/gender.js": {
"bytesInOutput": 1858 "bytesInOutput": 1915
}, },
"src/emotion/emotion.js": { "src/emotion/emotion.js": {
"bytesInOutput": 1738 "bytesInOutput": 1795
}, },
"src/embedding/embedding.js": { "src/embedding/embedding.js": {
"bytesInOutput": 1310 "bytesInOutput": 1310
@ -481,10 +481,10 @@
"bytesInOutput": 832 "bytesInOutput": 832
}, },
"src/hand/handdetector.js": { "src/hand/handdetector.js": {
"bytesInOutput": 2730 "bytesInOutput": 2731
}, },
"src/hand/handpipeline.js": { "src/hand/handpipeline.js": {
"bytesInOutput": 4456 "bytesInOutput": 4447
}, },
"src/hand/anchors.js": { "src/hand/anchors.js": {
"bytesInOutput": 127032 "bytesInOutput": 127032
@ -502,7 +502,7 @@
"bytesInOutput": 4008 "bytesInOutput": 4008
}, },
"src/human.js": { "src/human.js": {
"bytesInOutput": 10966 "bytesInOutput": 11134
}, },
"src/log.js": { "src/log.js": {
"bytesInOutput": 266 "bytesInOutput": 266
@ -517,16 +517,16 @@
"bytesInOutput": 1796 "bytesInOutput": 1796
}, },
"config.js": { "config.js": {
"bytesInOutput": 1440 "bytesInOutput": 1454
}, },
"src/sample.js": { "src/sample.js": {
"bytesInOutput": 11646 "bytesInOutput": 55341
}, },
"package.json": { "package.json": {
"bytesInOutput": 21 "bytesInOutput": 21
} }
}, },
"bytes": 1786229 "bytes": 1830260
} }
} }
} }

9
src/age/age.js
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@ -4,7 +4,7 @@ import * as profile from '../profile.js';
const models = {}; const models = {};
let last = { age: 0 }; let last = { age: 0 };
let frame = Number.MAX_SAFE_INTEGER; let skipped = Number.MAX_SAFE_INTEGER;
async function load(config) { async function load(config) {
if (!models.age) { if (!models.age) {
@ -16,11 +16,12 @@ async function load(config) {
async function predict(image, config) { async function predict(image, config) {
if (!models.age) return null; if (!models.age) return null;
if ((frame < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) { if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {
frame += 1; skipped++;
return last; return last;
} }
frame = 0; if (config.videoOptimized) skipped = 0;
else skipped = Number.MAX_SAFE_INTEGER;
return new Promise(async (resolve) => { return new Promise(async (resolve) => {
/* /*
const zoom = [0, 0]; // 0..1 meaning 0%..100% const zoom = [0, 0]; // 0..1 meaning 0%..100%

9
src/emotion/emotion.js
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@ -5,7 +5,7 @@ import * as profile from '../profile.js';
const annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surpise', 'neutral']; const annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surpise', 'neutral'];
const models = {}; const models = {};
let last = []; let last = [];
let frame = Number.MAX_SAFE_INTEGER; let skipped = Number.MAX_SAFE_INTEGER;
// tuning values // tuning values
const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale
@ -21,11 +21,12 @@ async function load(config) {
async function predict(image, config) { async function predict(image, config) {
if (!models.emotion) return null; if (!models.emotion) return null;
if ((frame < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) { if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {
frame += 1; skipped++;
return last; return last;
} }
frame = 0; if (config.videoOptimized) skipped = 0;
else skipped = Number.MAX_SAFE_INTEGER;
return new Promise(async (resolve) => { return new Promise(async (resolve) => {
/* /*
const zoom = [0, 0]; // 0..1 meaning 0%..100% const zoom = [0, 0]; // 0..1 meaning 0%..100%

12
src/face/facepipeline.js
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@ -51,7 +51,7 @@ class Pipeline {
this.meshHeight = config.face.mesh.inputSize; this.meshHeight = config.face.mesh.inputSize;
this.irisSize = config.face.iris.inputSize; this.irisSize = config.face.iris.inputSize;
this.irisEnlarge = 2.3; this.irisEnlarge = 2.3;
this.skipped = 1000; this.skipped = 0;
this.detectedFaces = 0; this.detectedFaces = 0;
} }
@ -129,15 +129,14 @@ class Pipeline {
} }
async predict(input, config) { async predict(input, config) {
this.skipped++;
let useFreshBox = false; let useFreshBox = false;
// run new detector every skipFrames unless we only want box to start with // run new detector every skipFrames unless we only want box to start with
let detector; let detector;
if ((this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) { if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {
detector = await this.boundingBoxDetector.getBoundingBoxes(input); detector = await this.boundingBoxDetector.getBoundingBoxes(input);
// don't reset on test image this.skipped = 0;
if ((input.shape[1] !== 255) && (input.shape[2] !== 255)) this.skipped = 0;
} }
if (config.videoOptimized) this.skipped++;
// if detector result count doesn't match current working set, use it to reset current working set // if detector result count doesn't match current working set, use it to reset current working set
if (detector && detector.boxes && (detector.boxes.length > 0) && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) { if (detector && detector.boxes && (detector.boxes.length > 0) && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {
@ -172,7 +171,7 @@ class Pipeline {
}); });
} }
// log(this.skipped, config.face.detector.skipFrames, this.detectedFaces, config.face.detector.maxFaces, detector?.boxes.length, this.storedBoxes.length); // log('face', `skipped: ${this.skipped} max: ${config.face.detector.maxFaces} detected: ${this.detectedFaces} stored: ${this.storedBoxes.length} new: ${detector?.boxes?.length}`);
let results = tf.tidy(() => this.storedBoxes.map((box, i) => { let results = tf.tidy(() => this.storedBoxes.map((box, i) => {
// The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box). // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).
let face; let face;
@ -207,7 +206,6 @@ class Pipeline {
const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours, which are included in the coordinates. const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours, which are included in the coordinates.
const confidenceVal = confidence.dataSync()[0]; const confidenceVal = confidence.dataSync()[0];
if (confidenceVal < config.face.detector.minConfidence) return null; // if below confidence just exit if (confidenceVal < config.face.detector.minConfidence) return null; // if below confidence just exit
const coordsReshaped = tf.reshape(contourCoords, [-1, 3]); const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);
let rawCoords = coordsReshaped.arraySync(); let rawCoords = coordsReshaped.arraySync();

20
src/gender/gender.js
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@ -4,7 +4,7 @@ import * as profile from '../profile.js';
const models = {}; const models = {};
let last = { gender: '' }; let last = { gender: '' };
let frame = Number.MAX_SAFE_INTEGER; let skipped = Number.MAX_SAFE_INTEGER;
let alternative = false; let alternative = false;
// tuning values // tuning values
@ -21,22 +21,13 @@ async function load(config) {
async function predict(image, config) { async function predict(image, config) {
if (!models.gender) return null; if (!models.gender) return null;
if ((frame < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') { if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {
frame += 1; skipped++;
return last; return last;
} }
frame = 0; if (config.videoOptimized) skipped = 0;
else skipped = Number.MAX_SAFE_INTEGER;
return new Promise(async (resolve) => { return new Promise(async (resolve) => {
/*
const zoom = [0, 0]; // 0..1 meaning 0%..100%
const box = [[
(image.shape[1] * zoom[0]) / image.shape[1],
(image.shape[2] * zoom[1]) / image.shape[2],
(image.shape[1] - (image.shape[1] * zoom[0])) / image.shape[1],
(image.shape[2] - (image.shape[2] * zoom[1])) / image.shape[2],
]];
const resize = tf.image.cropAndResize(image, box, [0], [config.face.gender.inputSize, config.face.gender.inputSize]);
*/
const resize = tf.image.resizeBilinear(image, [config.face.gender.inputSize, config.face.gender.inputSize], false); const resize = tf.image.resizeBilinear(image, [config.face.gender.inputSize, config.face.gender.inputSize], false);
let enhance; let enhance;
if (alternative) { if (alternative) {
@ -51,7 +42,6 @@ async function predict(image, config) {
} else { } else {
enhance = tf.mul(resize, [255.0]); enhance = tf.mul(resize, [255.0]);
} }
// const resize = tf.image.resizeBilinear(image, [config.face.age.inputSize, config.face.age.inputSize], false);
tf.dispose(resize); tf.dispose(resize);
let genderT; let genderT;

2
src/hand/handdetector.js
View File

@ -81,8 +81,8 @@ class HandDetector {
const image = tf.tidy(() => input.resizeBilinear([config.hand.inputSize, config.hand.inputSize]).div(127.5).sub(1)); const image = tf.tidy(() => input.resizeBilinear([config.hand.inputSize, config.hand.inputSize]).div(127.5).sub(1));
const predictions = await this.getBoxes(image, config); const predictions = await this.getBoxes(image, config);
image.dispose(); image.dispose();
if (!predictions || predictions.length === 0) return null;
const hands = []; const hands = [];
if (!predictions || predictions.length === 0) return hands;
for (const prediction of predictions) { for (const prediction of predictions) {
const boxes = prediction.box.dataSync(); const boxes = prediction.box.dataSync();
const startPoint = boxes.slice(0, 2); const startPoint = boxes.slice(0, 2);

11
src/hand/handpipeline.js
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@ -35,7 +35,7 @@ class HandPipeline {
this.landmarkDetector = landmarkDetector; this.landmarkDetector = landmarkDetector;
this.inputSize = inputSize; this.inputSize = inputSize;
this.storedBoxes = []; this.storedBoxes = [];
this.skipped = 1000; this.skipped = 0;
this.detectedHands = 0; this.detectedHands = 0;
} }
@ -84,16 +84,15 @@ class HandPipeline {
} }
async estimateHands(image, config) { async estimateHands(image, config) {
this.skipped++;
let useFreshBox = false; let useFreshBox = false;
// run new detector every skipFrames unless we only want box to start with // run new detector every skipFrames unless we only want box to start with
let boxes; let boxes;
if ((this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) { if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {
boxes = await this.handDetector.estimateHandBounds(image, config); boxes = await this.handDetector.estimateHandBounds(image, config);
// don't reset on test image this.skipped = 0;
if ((image.shape[1] !== 255) && (image.shape[2] !== 255)) this.skipped = 0;
} }
if (config.videoOptimized) this.skipped++;
// if detector result count doesn't match current working set, use it to reset current working set // if detector result count doesn't match current working set, use it to reset current working set
if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) { if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {
@ -103,7 +102,7 @@ class HandPipeline {
if (this.storedBoxes.length > 0) useFreshBox = true; if (this.storedBoxes.length > 0) useFreshBox = true;
} }
const hands = []; const hands = [];
// log(`skipped: ${this.skipped} max: ${config.hand.maxHands} detected: ${this.detectedHands} stored: ${this.storedBoxes.length} new: ${boxes?.length}`); // log('hand', `skipped: ${this.skipped} max: ${config.hand.maxHands} detected: ${this.detectedHands} stored: ${this.storedBoxes.length} new: ${boxes?.length}`);
// go through working set of boxes // go through working set of boxes
for (let i = 0; i < this.storedBoxes.length; i++) { for (let i = 0; i < this.storedBoxes.length; i++) {

36
src/human.js
View File

@ -418,26 +418,42 @@ class Human {
async warmup(userConfig) { async warmup(userConfig) {
if (userConfig) this.config = mergeDeep(this.config, userConfig); if (userConfig) this.config = mergeDeep(this.config, userConfig);
const width = 256; return new Promise((resolve) => {
const height = 256;
const video = this.config.videoOptimized; const video = this.config.videoOptimized;
this.config.videoOptimized = false; this.config.videoOptimized = false;
return new Promise((resolve) => { let src;
const img = new Image(width, height); let size;
switch (this.config.warmup) {
case 'face':
size = 256;
src = sample.face;
break;
case 'full':
size = 1200;
src = sample.body;
break;
default:
size = 0;
src = null;
}
const img = new Image(size, size);
img.onload = () => { img.onload = () => {
const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(width, height) : document.createElement('canvas'); const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');
canvas.width = width; canvas.width = size;
canvas.height = height; canvas.height = size;
const ctx = canvas.getContext('2d'); const ctx = canvas.getContext('2d');
ctx.drawImage(img, 0, 0); ctx.drawImage(img, 0, 0);
const data = ctx.getImageData(0, 0, width, height); const data = ctx.getImageData(0, 0, size, size);
const t0 = now();
this.detect(data, config).then((warmup) => { this.detect(data, config).then((warmup) => {
log('Warmup', warmup); const t1 = now();
log('Warmup', this.config.warmup, (t1 - t0), warmup);
this.config.videoOptimized = video; this.config.videoOptimized = video;
resolve(warmup); resolve(warmup);
}); });
}; };
img.src = sample.face; if (src) img.src = src;
else resolve(null);
}); });
} }
} }

2
wiki

@ -1 +1 @@
Subproject commit 785bde4caa1a29d8bfe82a4ae987ffde1d9a0a73 Subproject commit c4c8b30f6bf211ee267cf1884aaff9725f594631