diff --git a/config.js b/config.js
index c011d9e7..68381f3b 100644
--- a/config.js
+++ b/config.js
@@ -56,9 +56,9 @@ export default {
skipFrames: 15, // how many frames to go without re-running the face bounding box detector, only used for video inputs
// if model is running st 25 FPS, we can re-use existing bounding box for updated face mesh analysis
// as face probably hasn't moved much in short time (10 * 1/25 = 0.25 sec)
- minConfidence: 0.3, // threshold for discarding a prediction
+ minConfidence: 0.5, // threshold for discarding a prediction
iouThreshold: 0.3, // threshold for deciding whether boxes overlap too much in non-maximum suppression
- scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score in non-maximum suppression
+ scoreThreshold: 0.8, // threshold for deciding when to remove boxes based on score in non-maximum suppression
},
mesh: {
enabled: true,
@@ -80,13 +80,13 @@ export default {
},
gender: {
enabled: true,
- minConfidence: 0.3, // threshold for discarding a prediction
+ minConfidence: 0.5, // threshold for discarding a prediction
modelPath: '../models/ssrnet-gender-imdb.json',
},
emotion: {
enabled: true,
inputSize: 64, // fixed value
- minConfidence: 0.3, // threshold for discarding a prediction
+ minConfidence: 0.5, // threshold for discarding a prediction
skipFrames: 15, // how many frames to go without re-running the detector
modelPath: '../models/emotion-large.json', // can be 'mini', 'large'
},
@@ -97,7 +97,7 @@ export default {
inputResolution: 257, // fixed value
outputStride: 16, // fixed value
maxDetections: 10, // maximum number of people detected in the input, should be set to the minimum number for performance
- scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score in non-maximum suppression
+ scoreThreshold: 0.8, // threshold for deciding when to remove boxes based on score in non-maximum suppression
nmsRadius: 20, // radius for deciding points are too close in non-maximum suppression
},
hand: {
@@ -106,9 +106,9 @@ export default {
skipFrames: 15, // how many frames to go without re-running the hand bounding box detector, only used for video inputs
// if model is running st 25 FPS, we can re-use existing bounding box for updated hand skeleton analysis
// as the hand probably hasn't moved much in short time (10 * 1/25 = 0.25 sec)
- minConfidence: 0.3, // threshold for discarding a prediction
+ minConfidence: 0.5, // threshold for discarding a prediction
iouThreshold: 0.3, // threshold for deciding whether boxes overlap too much in non-maximum suppression
- scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score in non-maximum suppression
+ scoreThreshold: 0.8, // threshold for deciding when to remove boxes based on score in non-maximum suppression
enlargeFactor: 1.65, // empiric tuning as skeleton prediction prefers hand box with some whitespace
maxHands: 10, // maximum number of hands detected in the input, should be set to the minimum number for performance
detector: {
diff --git a/demo/browser.js b/demo/browser.js
index 541ae5c3..f2015ba8 100644
--- a/demo/browser.js
+++ b/demo/browser.js
@@ -16,7 +16,7 @@ const ui = {
busy: false,
facing: true,
useWorker: false,
- worker: 'worker.js',
+ worker: 'demo/worker.js',
samples: ['../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg'],
drawBoxes: true,
drawPoints: false,
@@ -29,45 +29,6 @@ const ui = {
modelsWarmup: true,
};
-// configuration overrides
-const config = {
- backend: 'webgl',
- profile: false,
- deallocate: false,
- wasm: { path: '../assets' },
- async: true,
- filter: {
- enabled: true,
- width: 0,
- 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,
- detector: { maxFaces: 10, skipFrames: 15, minConfidence: 0.3, iouThreshold: 0.3, scoreThreshold: 0.5 },
- mesh: { enabled: true },
- iris: { enabled: true },
- age: { enabled: true, skipFrames: 15 },
- gender: { enabled: true },
- emotion: { enabled: true, minConfidence: 0.3, useGrayscale: true },
- },
- body: { enabled: true, maxDetections: 10, scoreThreshold: 0.5, nmsRadius: 20 },
- hand: { enabled: true, skipFrames: 15, minConfidence: 0.3, iouThreshold: 0.3, scoreThreshold: 0.5 },
- gesture: { enabled: true },
-};
-
// global variables
let menu;
let menuFX;
@@ -218,7 +179,7 @@ function webWorker(input, image, canvas) {
});
}
// pass image data as arraybuffer to worker by reference to avoid copy
- worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, config }, [image.data.buffer]);
+ worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height }, [image.data.buffer]);
}
// main processing function when input is webcam, can use direct invocation or web worker
@@ -242,10 +203,10 @@ function runHumanDetect(input, canvas) {
// perform detection in worker
webWorker(input, data, canvas);
} else {
- human.detect(input, config).then((result) => {
+ human.detect(input).then((result) => {
if (result.error) log(result.error);
else drawResults(input, result, canvas);
- if (config.profile) log('profile data:', human.profile());
+ if (human.config.profile) log('profile data:', human.profile());
});
}
}
@@ -260,9 +221,9 @@ async function processImage(input) {
const canvas = document.getElementById('canvas');
image.width = image.naturalWidth;
image.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);
+ canvas.width = human.config.filter.width && human.config.filter.width > 0 ? human.config.filter.width : image.naturalWidth;
+ canvas.height = human.config.filter.height && human.config.filter.height > 0 ? human.config.filter.height : image.naturalHeight;
+ const result = await human.detect(image);
drawResults(image, result, canvas);
const thumb = document.createElement('canvas');
thumb.className = 'thumbnail';
@@ -280,7 +241,7 @@ async function processImage(input) {
// just initialize everything and call main function
async function detectVideo() {
- config.videoOptimized = true;
+ human.config.videoOptimized = true;
document.getElementById('samples-container').style.display = 'none';
document.getElementById('canvas').style.display = 'block';
const video = document.getElementById('video');
@@ -304,7 +265,7 @@ async function detectVideo() {
// just initialize everything and call main function
async function detectSampleImages() {
document.getElementById('play').style.display = 'none';
- config.videoOptimized = false;
+ human.config.videoOptimized = false;
const size = Math.trunc(ui.columns * 25600 / window.innerWidth);
ui.baseFont = ui.baseFontProto.replace(/{size}/, `${size}px`);
ui.baseLineHeight = ui.baseLineHeightProto * ui.columns;
@@ -324,49 +285,49 @@ function setupMenu() {
document.getElementById('play').addEventListener('click', () => btn.click());
menu.addHTML('
');
- menu.addList('Backend', ['cpu', 'webgl', 'wasm', 'webgpu'], config.backend, (val) => config.backend = val);
- menu.addBool('Async Operations', config, 'async');
- menu.addBool('Enable Profiler', config, 'profile');
- menu.addBool('Memory Shield', config, 'deallocate');
+ menu.addList('Backend', ['cpu', 'webgl', 'wasm', 'webgpu'], human.config.backend, (val) => human.config.backend = val);
+ menu.addBool('Async Operations', human.config, 'async');
+ menu.addBool('Enable Profiler', human.config, 'profile');
+ menu.addBool('Memory Shield', human.config, 'deallocate');
menu.addBool('Use Web Worker', ui, 'useWorker');
menu.addHTML('
');
menu.addLabel('Enabled Models');
- menu.addBool('Face Detect', config.face, 'enabled');
- menu.addBool('Face Mesh', config.face.mesh, 'enabled');
- menu.addBool('Face Iris', config.face.iris, 'enabled');
- menu.addBool('Face Age', config.face.age, 'enabled');
- menu.addBool('Face Gender', config.face.gender, 'enabled');
- menu.addBool('Face Emotion', config.face.emotion, 'enabled');
- menu.addBool('Body Pose', config.body, 'enabled');
- menu.addBool('Hand Pose', config.hand, 'enabled');
- menu.addBool('Gesture Analysis', config.gesture, 'enabled');
+ menu.addBool('Face Detect', human.config.face, 'enabled');
+ menu.addBool('Face Mesh', human.config.face.mesh, 'enabled');
+ menu.addBool('Face Iris', human.config.face.iris, 'enabled');
+ menu.addBool('Face Age', human.config.face.age, 'enabled');
+ menu.addBool('Face Gender', human.config.face.gender, 'enabled');
+ menu.addBool('Face Emotion', human.config.face.emotion, 'enabled');
+ menu.addBool('Body Pose', human.config.body, 'enabled');
+ menu.addBool('Hand Pose', human.config.hand, 'enabled');
+ menu.addBool('Gesture Analysis', human.config.gesture, 'enabled');
menu.addHTML('
');
menu.addLabel('Model Parameters');
- menu.addRange('Max Objects', config.face.detector, 'maxFaces', 1, 50, 1, (val) => {
- config.face.detector.maxFaces = parseInt(val);
- config.body.maxDetections = parseInt(val);
- config.hand.maxHands = parseInt(val);
+ menu.addRange('Max Objects', human.config.face.detector, 'maxFaces', 1, 50, 1, (val) => {
+ human.config.face.detector.maxFaces = parseInt(val);
+ human.config.body.maxDetections = parseInt(val);
+ human.config.hand.maxHands = parseInt(val);
});
- menu.addRange('Skip Frames', config.face.detector, 'skipFrames', 0, 50, 1, (val) => {
- config.face.detector.skipFrames = parseInt(val);
- config.face.emotion.skipFrames = parseInt(val);
- config.face.age.skipFrames = parseInt(val);
- config.hand.skipFrames = parseInt(val);
+ menu.addRange('Skip Frames', human.config.face.detector, 'skipFrames', 0, 50, 1, (val) => {
+ human.config.face.detector.skipFrames = parseInt(val);
+ human.config.face.emotion.skipFrames = parseInt(val);
+ human.config.face.age.skipFrames = parseInt(val);
+ human.config.hand.skipFrames = parseInt(val);
});
- menu.addRange('Min Confidence', config.face.detector, 'minConfidence', 0.0, 1.0, 0.05, (val) => {
- config.face.detector.minConfidence = parseFloat(val);
- config.face.emotion.minConfidence = parseFloat(val);
- config.hand.minConfidence = parseFloat(val);
+ menu.addRange('Min Confidence', human.config.face.detector, 'minConfidence', 0.0, 1.0, 0.05, (val) => {
+ human.config.face.detector.minConfidence = parseFloat(val);
+ human.config.face.emotion.minConfidence = parseFloat(val);
+ human.config.hand.minConfidence = parseFloat(val);
});
- menu.addRange('Score Threshold', config.face.detector, 'scoreThreshold', 0.1, 1.0, 0.05, (val) => {
- config.face.detector.scoreThreshold = parseFloat(val);
- config.hand.scoreThreshold = parseFloat(val);
- config.body.scoreThreshold = parseFloat(val);
+ menu.addRange('Score Threshold', human.config.face.detector, 'scoreThreshold', 0.1, 1.0, 0.05, (val) => {
+ human.config.face.detector.scoreThreshold = parseFloat(val);
+ human.config.hand.scoreThreshold = parseFloat(val);
+ human.config.body.scoreThreshold = parseFloat(val);
});
- menu.addRange('IOU Threshold', config.face.detector, 'iouThreshold', 0.1, 1.0, 0.05, (val) => {
- config.face.detector.iouThreshold = parseFloat(val);
- config.hand.iouThreshold = parseFloat(val);
+ menu.addRange('IOU Threshold', human.config.face.detector, 'iouThreshold', 0.1, 1.0, 0.05, (val) => {
+ human.config.face.detector.iouThreshold = parseFloat(val);
+ human.config.hand.iouThreshold = parseFloat(val);
});
menu.addHTML('
');
@@ -382,22 +343,22 @@ function setupMenu() {
menuFX.addBool('Fill Polygons', ui, 'fillPolygons');
menuFX.addHTML('
');
menuFX.addLabel('Image Processing');
- menuFX.addBool('Enabled', config.filter, 'enabled');
- menuFX.addRange('Image width', config.filter, 'width', 0, 3840, 10, (val) => config.filter.width = parseInt(val));
- menuFX.addRange('Image height', config.filter, 'height', 0, 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));
- menuFX.addRange('Blur', config.filter, 'blur', 0, 20, 1, (val) => config.filter.blur = parseInt(val));
- menuFX.addRange('Saturation', config.filter, 'saturation', -1.0, 1.0, 0.05, (val) => config.filter.saturation = parseFloat(val));
- menuFX.addRange('Hue', config.filter, 'hue', 0, 360, 5, (val) => config.filter.hue = parseInt(val));
- menuFX.addRange('Pixelate', config.filter, 'pixelate', 0, 32, 1, (val) => config.filter.pixelate = parseInt(val));
- menuFX.addBool('Negative', config.filter, 'negative');
- menuFX.addBool('Sepia', config.filter, 'sepia');
- menuFX.addBool('Vintage', config.filter, 'vintage');
- menuFX.addBool('Kodachrome', config.filter, 'kodachrome');
- menuFX.addBool('Technicolor', config.filter, 'technicolor');
- menuFX.addBool('Polaroid', config.filter, 'polaroid');
+ menuFX.addBool('Enabled', human.config.filter, 'enabled');
+ menuFX.addRange('Image width', human.config.filter, 'width', 0, 3840, 10, (val) => human.config.filter.width = parseInt(val));
+ menuFX.addRange('Image height', human.config.filter, 'height', 0, 2160, 10, (val) => human.config.filter.height = parseInt(val));
+ menuFX.addRange('Brightness', human.config.filter, 'brightness', -1.0, 1.0, 0.05, (val) => human.config.filter.brightness = parseFloat(val));
+ menuFX.addRange('Contrast', human.config.filter, 'contrast', -1.0, 1.0, 0.05, (val) => human.config.filter.contrast = parseFloat(val));
+ menuFX.addRange('Sharpness', human.config.filter, 'sharpness', 0, 1.0, 0.05, (val) => human.config.filter.sharpness = parseFloat(val));
+ menuFX.addRange('Blur', human.config.filter, 'blur', 0, 20, 1, (val) => human.config.filter.blur = parseInt(val));
+ menuFX.addRange('Saturation', human.config.filter, 'saturation', -1.0, 1.0, 0.05, (val) => human.config.filter.saturation = parseFloat(val));
+ menuFX.addRange('Hue', human.config.filter, 'hue', 0, 360, 5, (val) => human.config.filter.hue = parseInt(val));
+ menuFX.addRange('Pixelate', human.config.filter, 'pixelate', 0, 32, 1, (val) => human.config.filter.pixelate = parseInt(val));
+ menuFX.addBool('Negative', human.config.filter, 'negative');
+ menuFX.addBool('Sepia', human.config.filter, 'sepia');
+ menuFX.addBool('Vintage', human.config.filter, 'vintage');
+ menuFX.addBool('Kodachrome', human.config.filter, 'kodachrome');
+ menuFX.addBool('Technicolor', human.config.filter, 'technicolor');
+ menuFX.addBool('Polaroid', human.config.filter, 'polaroid');
}
async function main() {
diff --git a/demo/worker.js b/demo/worker.js
index 3ba194c1..e796631e 100644
--- a/demo/worker.js
+++ b/demo/worker.js
@@ -14,10 +14,9 @@ onmessage = async (msg) => {
busy = true;
// worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, config }, [image.data.buffer]);
const image = new ImageData(new Uint8ClampedArray(msg.data.image), msg.data.width, msg.data.height);
- config = msg.data.config;
let result = {};
try {
- result = await human.detect(image, config);
+ result = await human.detect(image);
} catch (err) {
result.error = err.message;
log('worker thread error:', err.message);
diff --git a/package.json b/package.json
index 1951b5b2..37937ac0 100644
--- a/package.json
+++ b/package.json
@@ -41,7 +41,7 @@
"scripts": {
"start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",
"lint": "eslint src/*.js demo/*.js",
- "dev": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation dev-server.js",
+ "dev": "npm install && node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation dev-server.js",
"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",
"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",
"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",
diff --git a/src/age/ssrnet.js b/src/age/ssrnet.js
index 872d0a69..1e456c31 100644
--- a/src/age/ssrnet.js
+++ b/src/age/ssrnet.js
@@ -14,12 +14,12 @@ async function load(config) {
}
async function predict(image, config) {
+ if ((frame < config.face.age.skipFrames) && last.age && (last.age > 0)) {
+ 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],
diff --git a/src/emotion/emotion.js b/src/emotion/emotion.js
index 71e9b74d..c723cbd1 100644
--- a/src/emotion/emotion.js
+++ b/src/emotion/emotion.js
@@ -17,12 +17,12 @@ async function load(config) {
}
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],
diff --git a/src/gender/ssrnet.js b/src/gender/ssrnet.js
index 52f6a6a9..fcc5ec52 100644
--- a/src/gender/ssrnet.js
+++ b/src/gender/ssrnet.js
@@ -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],