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human
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initial work on skipTime

pull/233/head
Vladimir Mandic 2021-10-22 16:09:52 -04:00
parent 54498226a0
commit ebfd0b01e0
67 changed files with 30731 additions and 121501 deletions
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3
CHANGELOG.md
View File

@ -11,6 +11,9 @@
### **HEAD -> main** 2021/10/22 mandic00@live.com
### **origin/main** 2021/10/22 mandic00@live.com
- add optional autodetected custom wasm path
### **2.3.6** 2021/10/21 mandic00@live.com

1
build.json
View File

@ -137,6 +137,7 @@
"format": "esm",
"input": "tfjs/tf-browser.ts",
"output": "dist/tfjs.esm.js",
"minify": true,
"sourcemap": true,
"external": ["fs", "os", "buffer", "util"]
},

4
demo/benchmark/browser.js
View File

@ -1,6 +1,4 @@
// import * as tf from '../../assets/tf.es2017.js';
// import '../../assets/tf-backend-webgpu.es2017.js';
import Human from '../../dist/human.esm.js';
import Human from '../../dist/human.custom.esm.js';
const loop = 20;

171
dist/human.custom.esm.js vendored
View File

@ -136,6 +136,7 @@ var config = {
rotation: true,
maxDetected: 1,
skipFrames: 11,
skipTime: 2e3,
minConfidence: 0.2,
iouThreshold: 0.1,
return: false
@ -152,17 +153,20 @@ var config = {
enabled: true,
minConfidence: 0.1,
skipFrames: 12,
skipTime: 2e3,
modelPath: "emotion.json"
},
description: {
enabled: true,
modelPath: "faceres.json",
skipFrames: 13,
skipTime: 2e3,
minConfidence: 0.1
},
antispoof: {
enabled: false,
skipFrames: 14,
skipTime: 2e3,
modelPath: "antispoof.json"
}
},
@ -174,12 +178,14 @@ var config = {
},
maxDetected: -1,
minConfidence: 0.3,
skipFrames: 1
skipFrames: 1,
skipTime: 2e3
},
hand: {
enabled: true,
rotation: true,
skipFrames: 2,
skipTime: 2e3,
minConfidence: 0.5,
iouThreshold: 0.2,
maxDetected: -1,
@ -197,7 +203,8 @@ var config = {
minConfidence: 0.2,
iouThreshold: 0.4,
maxDetected: 10,
skipFrames: 15
skipFrames: 15,
skipTime: 2e3
},
segmentation: {
enabled: false,
@ -17734,14 +17741,14 @@ function formatAsFriendlyString(value) {
}
}
function debounce(f, waitMs, nowFunc) {
let lastTime = nowFunc != null ? nowFunc() : util_exports.now();
let lastTime8 = nowFunc != null ? nowFunc() : util_exports.now();
let lastResult;
const f2 = (...args) => {
const now22 = nowFunc != null ? nowFunc() : util_exports.now();
if (now22 - lastTime < waitMs) {
if (now22 - lastTime8 < waitMs) {
return lastResult;
}
lastTime = now22;
lastTime8 = now22;
lastResult = f(...args);
return lastResult;
};
@ -71352,6 +71359,7 @@ var model3;
var cached = [];
var skipped2 = Number.MAX_SAFE_INTEGER;
var lastCount = 0;
var last = 0;
async function load2(config3) {
var _a, _b;
if (env2.initial)
@ -71367,10 +71375,10 @@ async function load2(config3) {
return model3;
}
async function predict(image7, config3, idx, count3) {
var _a;
var _a, _b;
if (!model3)
return null;
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount === count3 && cached[idx]) {
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count3 && cached[idx]) {
skipped2++;
return cached[idx];
}
@ -71381,6 +71389,7 @@ async function predict(image7, config3, idx, count3) {
const num = (await res.data())[0];
cached[idx] = Math.round(100 * num) / 100;
lastCount = count3;
last = now();
dispose([resize, res]);
resolve(cached[idx]);
});
@ -74956,6 +74965,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
var outputNodes;
var cache = null;
var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
var last2 = 0;
async function loadDetect(config3) {
var _a, _b, _c;
if (env3.initial)
@ -75072,10 +75082,11 @@ async function detectParts(input2, config3, outputSize2) {
}
async function predict2(input2, config3) {
const outputSize2 = [input2.shape[2] || 0, input2.shape[1] || 0];
if (skipped3 < (config3.body.skipFrames || 0) && config3.skipFrame && cache !== null) {
if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
skipped3++;
} else {
cache = await detectParts(input2, config3, outputSize2);
last2 = now();
skipped3 = 0;
}
if (cache)
@ -75170,7 +75181,8 @@ var labels = [
// src/object/centernet.ts
var model5;
var inputSize3 = 0;
var last = [];
var last3 = [];
var lastTime = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
async function load4(config3) {
if (env2.initial)
@ -75235,20 +75247,21 @@ async function process3(res, outputShape, config3) {
return results;
}
async function predict3(input2, config3) {
if (skipped4 < (config3.object.skipFrames || 0) && config3.skipFrame && last.length > 0) {
if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
skipped4++;
return last;
return last3;
}
skipped4 = 0;
if (!env2.kernels.includes("mod") || !env2.kernels.includes("sparsetodense"))
return last;
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [input2.shape[2], input2.shape[1]];
const resize = image.resizeBilinear(input2, [inputSize3, inputSize3]);
const objectT = config3.object.enabled ? model5 == null ? void 0 : model5.execute(resize, ["tower_0/detections"]) : null;
lastTime = now();
dispose(resize);
const obj = await process3(objectT, outputSize2, config3);
last = obj;
last3 = obj;
resolve(obj);
});
}
@ -75288,6 +75301,7 @@ var connected2 = {
// src/body/efficientpose.ts
var model6;
var last4 = 0;
var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
var skipped5 = Number.MAX_SAFE_INTEGER;
async function load5(config3) {
@ -75320,7 +75334,7 @@ function max2d(inputs, minScore) {
}
async function predict4(image7, config3) {
var _a;
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0) {
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
skipped5++;
return [cache2];
}
@ -75338,6 +75352,7 @@ async function predict4(image7, config3) {
let resT;
if (config3.body.enabled)
resT = await (model6 == null ? void 0 : model6.predict(tensor2));
last4 = now();
dispose(tensor2);
if (resT) {
cache2.keypoints.length = 0;
@ -75398,8 +75413,9 @@ async function predict4(image7, config3) {
// src/gear/emotion.ts
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model7;
var last2 = [];
var last5 = [];
var lastCount2 = 0;
var lastTime2 = 0;
var skipped6 = Number.MAX_SAFE_INTEGER;
var rgb = [0.2989, 0.587, 0.114];
async function load6(config3) {
@ -75417,44 +75433,45 @@ async function load6(config3) {
return model7;
}
async function predict5(image7, config3, idx, count3) {
var _a;
var _a, _b;
if (!model7)
return null;
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount2 === count3 && last2[idx] && last2[idx].length > 0) {
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count3 && last5[idx] && last5[idx].length > 0) {
skipped6++;
return last2[idx];
return last5[idx];
}
skipped6 = 0;
return new Promise(async (resolve) => {
var _a2, _b;
const resize = image.resizeBilinear(image7, [(model7 == null ? void 0 : model7.inputs[0].shape) ? model7.inputs[0].shape[2] : 0, (model7 == null ? void 0 : model7.inputs[0].shape) ? model7.inputs[0].shape[1] : 0], false);
const [red, green, blue] = split(resize, 3, 3);
dispose(resize);
const redNorm = mul(red, rgb[0]);
const greenNorm = mul(green, rgb[1]);
const blueNorm = mul(blue, rgb[2]);
dispose(red);
dispose(green);
dispose(blue);
const grayscale = addN([redNorm, greenNorm, blueNorm]);
dispose(redNorm);
dispose(greenNorm);
dispose(blueNorm);
const normalize = tidy(() => mul(sub(grayscale, 0.5), 2));
dispose(grayscale);
var _a2, _b2;
const obj = [];
if ((_a2 = config3.face.emotion) == null ? void 0 : _a2.enabled) {
const resize = image.resizeBilinear(image7, [(model7 == null ? void 0 : model7.inputs[0].shape) ? model7.inputs[0].shape[2] : 0, (model7 == null ? void 0 : model7.inputs[0].shape) ? model7.inputs[0].shape[1] : 0], false);
const [red, green, blue] = split(resize, 3, 3);
dispose(resize);
const redNorm = mul(red, rgb[0]);
const greenNorm = mul(green, rgb[1]);
const blueNorm = mul(blue, rgb[2]);
dispose(red);
dispose(green);
dispose(blue);
const grayscale = addN([redNorm, greenNorm, blueNorm]);
dispose(redNorm);
dispose(greenNorm);
dispose(blueNorm);
const normalize = tidy(() => mul(sub(grayscale, 0.5), 2));
dispose(grayscale);
const emotionT = await (model7 == null ? void 0 : model7.predict(normalize));
lastTime2 = now();
const data = await emotionT.data();
dispose(emotionT);
for (let i = 0; i < data.length; i++) {
if (data[i] > (((_b = config3.face.emotion) == null ? void 0 : _b.minConfidence) || 0))
if (data[i] > (((_b2 = config3.face.emotion) == null ? void 0 : _b2.minConfidence) || 0))
obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });
}
obj.sort((a, b) => b.score - a.score);
dispose(normalize);
}
dispose(normalize);
last2[idx] = obj;
last5[idx] = obj;
lastCount2 = count3;
resolve(obj);
});
@ -75597,11 +75614,13 @@ var boxCache = [];
var model9 = null;
var inputSize5 = 0;
var skipped7 = Number.MAX_SAFE_INTEGER;
var lastTime3 = 0;
var detectedFaces = 0;
async function predict6(input2, config3) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0)) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
const newBoxes2 = await getBoxes(input2, config3);
lastTime3 = now();
boxCache = [];
for (const possible of newBoxes2.boxes) {
const startPoint = await possible.box.startPoint.data();
@ -75637,16 +75656,16 @@ async function predict6(input2, config3) {
faceScore: 0,
annotations: {}
};
if (((_d = config3.face.detector) == null ? void 0 : _d.rotation) && ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) && env2.kernels.includes("rotatewithoffset")) {
if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env2.kernels.includes("rotatewithoffset")) {
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input2, inputSize5);
} else {
rotationMatrix = IDENTITY_MATRIX;
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input2, ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input2, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
face5.tensor = div(cut, 255);
dispose(cut);
}
face5.boxScore = Math.round(100 * box4.confidence) / 100;
if (!((_g = config3.face.mesh) == null ? void 0 : _g.enabled)) {
if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
face5.box = getClampedBox(box4, input2);
face5.boxRaw = getRawBox(box4, input2);
face5.score = Math.round(100 * box4.confidence || 0) / 100;
@ -75669,17 +75688,17 @@ async function predict6(input2, config3) {
let rawCoords = await coordsReshaped.array();
dispose(contourCoords);
dispose(coordsReshaped);
if (faceConfidence < (((_h = config3.face.detector) == null ? void 0 : _h.minConfidence) || 1)) {
if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
box4.confidence = faceConfidence;
} else {
if ((_i = config3.face.iris) == null ? void 0 : _i.enabled)
if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input2.shape[2] || 0), pt[1] / (input2.shape[1] || 0), (pt[2] || 0) / inputSize5]);
box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
for (const key of Object.keys(meshAnnotations))
face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
if (((_j = config3.face.detector) == null ? void 0 : _j.rotation) && config3.face.mesh.enabled && ((_k = config3.face.description) == null ? void 0 : _k.enabled) && env2.kernels.includes("rotatewithoffset")) {
if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env2.kernels.includes("rotatewithoffset")) {
dispose(face5.tensor);
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input2, inputSize5);
}
@ -75693,7 +75712,7 @@ async function predict6(input2, config3) {
faces.push(face5);
newBoxes.push(box4);
}
if ((_l = config3.face.mesh) == null ? void 0 : _l.enabled)
if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
boxCache = newBoxes.filter((a) => {
var _a2;
return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@ -75723,7 +75742,8 @@ var uvmap = UV468;
// src/face/faceres.ts
var model10;
var last3 = [];
var last6 = [];
var lastTime4 = 0;
var lastCount3 = 0;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load9(config3) {
@ -75756,29 +75776,29 @@ function enhance(input2) {
return image7;
}
async function predict7(image7, config3, idx, count3) {
var _a, _b, _c;
var _a, _b, _c, _d;
if (!model10)
return null;
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount3 === count3 && ((_b = last3[idx]) == null ? void 0 : _b.age) && ((_c = last3[idx]) == null ? void 0 : _c.age) > 0) {
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count3 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
skipped8++;
return last3[idx];
return last6[idx];
}
skipped8 = 0;
return new Promise(async (resolve) => {
var _a2, _b2;
const enhanced = enhance(image7);
let resT;
const obj = {
age: 0,
gender: "unknown",
genderScore: 0,
descriptor: []
};
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled)
resT = await (model10 == null ? void 0 : model10.predict(enhanced));
dispose(enhanced);
if (resT) {
const gender = await resT.find((t) => t.shape[1] === 1).data();
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
const enhanced = enhance(image7);
const resT = await (model10 == null ? void 0 : model10.predict(enhanced));
lastTime4 = now();
dispose(enhanced);
const genderT = await resT.find((t) => t.shape[1] === 1);
const gender = await genderT.data();
const confidence = Math.trunc(200 * Math.abs(gender[0] - 0.5)) / 100;
if (confidence > (((_b2 = config3.face.description) == null ? void 0 : _b2.minConfidence) || 0)) {
obj.gender = gender[0] <= 0.5 ? "female" : "male";
@ -75787,14 +75807,15 @@ async function predict7(image7, config3, idx, count3) {
const argmax2 = argMax(resT.find((t) => t.shape[1] === 100), 1);
const age = (await argmax2.data())[0];
dispose(argmax2);
const all6 = await resT.find((t) => t.shape[1] === 100).data();
const ageT = resT.find((t) => t.shape[1] === 100);
const all6 = await ageT.data();
obj.age = Math.round(all6[age - 1] > all6[age + 1] ? 10 * age - 100 * all6[age - 1] : 10 * age + 100 * all6[age + 1]) / 10;
const desc = resT.find((t) => t.shape[1] === 1024);
const descriptor = await desc.data();
obj.descriptor = [...descriptor];
const descriptor = desc ? await desc.data() : [];
obj.descriptor = Array.from(descriptor);
resT.forEach((t) => dispose(t));
}
last3[idx] = obj;
last6[idx] = obj;
lastCount3 = count3;
resolve(obj);
});
@ -78941,6 +78962,7 @@ var handBoxEnlargeFactor = 1.65;
var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
var palmLandmarksPalmBase = 0;
var palmLandmarksMiddleFingerBase = 2;
var lastTime5 = 0;
var HandPipeline = class {
constructor(handDetector, handPoseModel2) {
__publicField(this, "handDetector");
@ -79005,7 +79027,7 @@ var HandPipeline = class {
async estimateHands(image7, config3) {
let useFreshBox = false;
let boxes;
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames || !config3.hand.landmarks || !config3.skipFrame) {
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
boxes = await this.handDetector.estimateHandBounds(image7, config3);
this.skipped = 0;
}
@ -79034,6 +79056,7 @@ var HandPipeline = class {
dispose(croppedInput);
dispose(rotatedImage);
const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
lastTime5 = now();
dispose(handImage);
const confidence = (await confidenceT.data())[0];
dispose(confidenceT);
@ -79602,6 +79625,7 @@ var boxExpandFact = 1.6;
var maxDetectorResolution = 512;
var detectorExpandFact = 1.4;
var skipped9 = 0;
var lastTime6 = 0;
var outputSize = [0, 0];
var cache3 = {
boxes: [],
@ -79741,16 +79765,17 @@ async function predict9(input2, config3) {
return [];
outputSize = [input2.shape[2] || 0, input2.shape[1] || 0];
skipped9++;
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0)) {
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
return cache3.hands;
}
return new Promise(async (resolve) => {
if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input2, handBox, config3)));
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && cache3.hands.length > 0) {
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input2, handBox, config3)));
} else {
cache3.boxes = await detectHands(input2, config3);
lastTime6 = now();
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input2, handBox, config3)));
skipped9 = 0;
}
@ -79937,7 +79962,8 @@ var inputSize7 = 0;
var skipped10 = Number.MAX_SAFE_INTEGER;
var cache5 = {
boxes: [],
bodies: []
bodies: [],
last: 0
};
async function load11(config3) {
if (env2.initial)
@ -80047,7 +80073,7 @@ async function predict10(input2, config3) {
if (!config3.skipFrame)
cache5.boxes.length = 0;
skipped10++;
if (config3.skipFrame && skipped10 <= (config3.body.skipFrames || 0)) {
if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
return cache5.bodies;
}
return new Promise(async (resolve) => {
@ -80055,6 +80081,7 @@ async function predict10(input2, config3) {
skipped10 = 0;
t.input = padInput(input2, inputSize7);
t.res = await (model11 == null ? void 0 : model11.predict(t.input));
cache5.last = now();
const res = await t.res.array();
cache5.bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input2, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input2, [0, 0, 1, 1]);
for (const body4 of cache5.bodies) {
@ -80068,7 +80095,8 @@ async function predict10(input2, config3) {
// src/object/nanodet.ts
var model12;
var last4 = [];
var last7 = [];
var lastTime7 = 0;
var skipped11 = Number.MAX_SAFE_INTEGER;
var scaleBox = 2.5;
async function load12(config3) {
@ -80148,13 +80176,13 @@ async function process4(res, inputSize8, outputShape, config3) {
return results;
}
async function predict11(image7, config3) {
if (skipped11 < (config3.object.skipFrames || 0) && config3.skipFrame && last4.length > 0) {
if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
skipped11++;
return last4;
return last7;
}
skipped11 = 0;
if (!env2.kernels.includes("mod") || !env2.kernels.includes("sparsetodense"))
return last4;
return last7;
return new Promise(async (resolve) => {
const outputSize2 = [image7.shape[2], image7.shape[1]];
const resize = image.resizeBilinear(image7, [model12.inputSize, model12.inputSize], false);
@ -80165,9 +80193,10 @@ async function predict11(image7, config3) {
let objectT;
if (config3.object.enabled)
objectT = await model12.predict(transpose6);
lastTime7 = now();
dispose(transpose6);
const obj = await process4(objectT, model12.inputSize, outputSize2, config3);
last4 = obj;
last7 = obj;
resolve(obj);
});
}

4
dist/human.custom.esm.js.map vendored
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File diff suppressed because one or more lines are too long

33
dist/human.d.ts vendored
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@ -1,33 +0,0 @@
// @ts-nocheck
declare module '@vladmandic/human/dist/tfjs.esm' {
export * from '@vladmandic/human/types/dist/tfjs.esm';
}
declare module '@vladmandic/human/dist/human' {
export * from '@vladmandic/human/types/src/human';
}
declare module '@vladmandic/human/dist/human.esm' {
export * from '@vladmandic/human/types/src/human';
}
declare module '@vladmandic/human/dist/human.esm-nobundle' {
export * from '@vladmandic/human/types/src/human';
}
declare module '@vladmandic/human/dist/human.custom.esm' {
export * from '@vladmandic/human/types/src/human';
}
declare module '@vladmandic/human/dist/human.node' {
export * from '@vladmandic/human/types/src/human';
}
declare module '@vladmandic/human/dist/human.node-gpu' {
export * from '@vladmandic/human/types/src/human';
}
declare module '@vladmandic/human/dist/human.node-wasm' {
export * from '@vladmandic/human/types/src/human';
}

167
dist/human.esm-nobundle.js vendored
View File

@ -147,6 +147,7 @@ var config = {
rotation: true,
maxDetected: 1,
skipFrames: 11,
skipTime: 2e3,
minConfidence: 0.2,
iouThreshold: 0.1,
return: false
@ -163,17 +164,20 @@ var config = {
enabled: true,
minConfidence: 0.1,
skipFrames: 12,
skipTime: 2e3,
modelPath: "emotion.json"
},
description: {
enabled: true,
modelPath: "faceres.json",
skipFrames: 13,
skipTime: 2e3,
minConfidence: 0.1
},
antispoof: {
enabled: false,
skipFrames: 14,
skipTime: 2e3,
modelPath: "antispoof.json"
}
},
@ -185,12 +189,14 @@ var config = {
},
maxDetected: -1,
minConfidence: 0.3,
skipFrames: 1
skipFrames: 1,
skipTime: 2e3
},
hand: {
enabled: true,
rotation: true,
skipFrames: 2,
skipTime: 2e3,
minConfidence: 0.5,
iouThreshold: 0.2,
maxDetected: -1,
@ -208,7 +214,8 @@ var config = {
minConfidence: 0.2,
iouThreshold: 0.4,
maxDetected: 10,
skipFrames: 15
skipFrames: 15,
skipTime: 2e3
},
segmentation: {
enabled: false,
@ -221,7 +228,6 @@ var config = {
var tfjs_esm_exports = {};
__export(tfjs_esm_exports, {
GraphModel: () => GraphModel,
OptimizerConstructors: () => OptimizerConstructors,
Tensor: () => Tensor,
version: () => version9
});
@ -251,7 +257,6 @@ var version9 = {
"tfjs-backend-webgl": version7,
"tfjs-backend-wasm": version8
};
var OptimizerConstructors = {};
// src/image/imagefxshaders.ts
var vertexIdentity = `
@ -1299,6 +1304,7 @@ var model2;
var cached = [];
var skipped2 = Number.MAX_SAFE_INTEGER;
var lastCount = 0;
var last = 0;
async function load2(config3) {
var _a, _b;
if (env.initial)
@ -1314,10 +1320,10 @@ async function load2(config3) {
return model2;
}
async function predict(image25, config3, idx, count2) {
var _a;
var _a, _b;
if (!model2)
return null;
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount === count2 && cached[idx]) {
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
skipped2++;
return cached[idx];
}
@ -1328,6 +1334,7 @@ async function predict(image25, config3, idx, count2) {
const num = (await res.data())[0];
cached[idx] = Math.round(100 * num) / 100;
lastCount = count2;
last = now();
tfjs_esm_exports.dispose([resize, res]);
resolve(cached[idx]);
});
@ -4903,6 +4910,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
var outputNodes;
var cache = null;
var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
var last2 = 0;
async function loadDetect(config3) {
var _a, _b, _c;
if (env3.initial)
@ -5019,10 +5027,11 @@ async function detectParts(input, config3, outputSize2) {
}
async function predict2(input, config3) {
const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
if (skipped3 < (config3.body.skipFrames || 0) && config3.skipFrame && cache !== null) {
if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
skipped3++;
} else {
cache = await detectParts(input, config3, outputSize2);
last2 = now();
skipped3 = 0;
}
if (cache)
@ -5117,7 +5126,8 @@ var labels = [
// src/object/centernet.ts
var model4;
var inputSize3 = 0;
var last = [];
var last3 = [];
var lastTime = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
async function load4(config3) {
if (env.initial)
@ -5182,20 +5192,21 @@ async function process3(res, outputShape, config3) {
return results;
}
async function predict3(input, config3) {
if (skipped4 < (config3.object.skipFrames || 0) && config3.skipFrame && last.length > 0) {
if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
skipped4++;
return last;
return last3;
}
skipped4 = 0;
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last;
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [input.shape[2], input.shape[1]];
const resize = tfjs_esm_exports.image.resizeBilinear(input, [inputSize3, inputSize3]);
const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
lastTime = now();
tfjs_esm_exports.dispose(resize);
const obj = await process3(objectT, outputSize2, config3);
last = obj;
last3 = obj;
resolve(obj);
});
}
@ -5235,6 +5246,7 @@ var connected2 = {
// src/body/efficientpose.ts
var model5;
var last4 = 0;
var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
var skipped5 = Number.MAX_SAFE_INTEGER;
async function load5(config3) {
@ -5267,7 +5279,7 @@ function max2d(inputs, minScore) {
}
async function predict4(image25, config3) {
var _a;
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0) {
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
skipped5++;
return [cache2];
}
@ -5285,6 +5297,7 @@ async function predict4(image25, config3) {
let resT;
if (config3.body.enabled)
resT = await (model5 == null ? void 0 : model5.predict(tensor3));
last4 = now();
tfjs_esm_exports.dispose(tensor3);
if (resT) {
cache2.keypoints.length = 0;
@ -5345,8 +5358,9 @@ async function predict4(image25, config3) {
// src/gear/emotion.ts
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model6;
var last2 = [];
var last5 = [];
var lastCount2 = 0;
var lastTime2 = 0;
var skipped6 = Number.MAX_SAFE_INTEGER;
var rgb = [0.2989, 0.587, 0.114];
async function load6(config3) {
@ -5364,44 +5378,45 @@ async function load6(config3) {
return model6;
}
async function predict5(image25, config3, idx, count2) {
var _a;
var _a, _b;
if (!model6)
return null;
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
skipped6++;
return last2[idx];
return last5[idx];
}
skipped6 = 0;
return new Promise(async (resolve) => {
var _a2, _b;
const resize = tfjs_esm_exports.image.resizeBilinear(image25, [(model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[2] : 0, (model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tfjs_esm_exports.split(resize, 3, 3);
tfjs_esm_exports.dispose(resize);
const redNorm = tfjs_esm_exports.mul(red, rgb[0]);
const greenNorm = tfjs_esm_exports.mul(green, rgb[1]);
const blueNorm = tfjs_esm_exports.mul(blue, rgb[2]);
tfjs_esm_exports.dispose(red);
tfjs_esm_exports.dispose(green);
tfjs_esm_exports.dispose(blue);
const grayscale = tfjs_esm_exports.addN([redNorm, greenNorm, blueNorm]);
tfjs_esm_exports.dispose(redNorm);
tfjs_esm_exports.dispose(greenNorm);
tfjs_esm_exports.dispose(blueNorm);
const normalize = tfjs_esm_exports.tidy(() => tfjs_esm_exports.mul(tfjs_esm_exports.sub(grayscale, 0.5), 2));
tfjs_esm_exports.dispose(grayscale);
var _a2, _b2;
const obj = [];
if ((_a2 = config3.face.emotion) == null ? void 0 : _a2.enabled) {
const resize = tfjs_esm_exports.image.resizeBilinear(image25, [(model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[2] : 0, (model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tfjs_esm_exports.split(resize, 3, 3);
tfjs_esm_exports.dispose(resize);
const redNorm = tfjs_esm_exports.mul(red, rgb[0]);
const greenNorm = tfjs_esm_exports.mul(green, rgb[1]);
const blueNorm = tfjs_esm_exports.mul(blue, rgb[2]);
tfjs_esm_exports.dispose(red);
tfjs_esm_exports.dispose(green);
tfjs_esm_exports.dispose(blue);
const grayscale = tfjs_esm_exports.addN([redNorm, greenNorm, blueNorm]);
tfjs_esm_exports.dispose(redNorm);
tfjs_esm_exports.dispose(greenNorm);
tfjs_esm_exports.dispose(blueNorm);
const normalize = tfjs_esm_exports.tidy(() => tfjs_esm_exports.mul(tfjs_esm_exports.sub(grayscale, 0.5), 2));
tfjs_esm_exports.dispose(grayscale);
const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
lastTime2 = now();
const data = await emotionT.data();
tfjs_esm_exports.dispose(emotionT);
for (let i = 0; i < data.length; i++) {
if (data[i] > (((_b = config3.face.emotion) == null ? void 0 : _b.minConfidence) || 0))
if (data[i] > (((_b2 = config3.face.emotion) == null ? void 0 : _b2.minConfidence) || 0))
obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });
}
obj.sort((a, b) => b.score - a.score);
tfjs_esm_exports.dispose(normalize);
}
tfjs_esm_exports.dispose(normalize);
last2[idx] = obj;
last5[idx] = obj;
lastCount2 = count2;
resolve(obj);
});
@ -5544,11 +5559,13 @@ var boxCache = [];
var model8 = null;
var inputSize5 = 0;
var skipped7 = Number.MAX_SAFE_INTEGER;
var lastTime3 = 0;
var detectedFaces = 0;
async function predict6(input, config3) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0)) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
const newBoxes2 = await getBoxes(input, config3);
lastTime3 = now();
boxCache = [];
for (const possible of newBoxes2.boxes) {
const startPoint = await possible.box.startPoint.data();
@ -5584,16 +5601,16 @@ async function predict6(input, config3) {
faceScore: 0,
annotations: {}
};
if (((_d = config3.face.detector) == null ? void 0 : _d.rotation) && ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) && env.kernels.includes("rotatewithoffset")) {
if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env.kernels.includes("rotatewithoffset")) {
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
} else {
rotationMatrix = IDENTITY_MATRIX;
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
face5.tensor = tfjs_esm_exports.div(cut, 255);
tfjs_esm_exports.dispose(cut);
}
face5.boxScore = Math.round(100 * box4.confidence) / 100;
if (!((_g = config3.face.mesh) == null ? void 0 : _g.enabled)) {
if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
face5.box = getClampedBox(box4, input);
face5.boxRaw = getRawBox(box4, input);
face5.score = Math.round(100 * box4.confidence || 0) / 100;
@ -5616,17 +5633,17 @@ async function predict6(input, config3) {
let rawCoords = await coordsReshaped.array();
tfjs_esm_exports.dispose(contourCoords);
tfjs_esm_exports.dispose(coordsReshaped);
if (faceConfidence < (((_h = config3.face.detector) == null ? void 0 : _h.minConfidence) || 1)) {
if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
box4.confidence = faceConfidence;
} else {
if ((_i = config3.face.iris) == null ? void 0 : _i.enabled)
if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
for (const key of Object.keys(meshAnnotations))
face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
if (((_j = config3.face.detector) == null ? void 0 : _j.rotation) && config3.face.mesh.enabled && ((_k = config3.face.description) == null ? void 0 : _k.enabled) && env.kernels.includes("rotatewithoffset")) {
if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env.kernels.includes("rotatewithoffset")) {
tfjs_esm_exports.dispose(face5.tensor);
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
}
@ -5640,7 +5657,7 @@ async function predict6(input, config3) {
faces.push(face5);
newBoxes.push(box4);
}
if ((_l = config3.face.mesh) == null ? void 0 : _l.enabled)
if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
boxCache = newBoxes.filter((a) => {
var _a2;
return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@ -5670,7 +5687,8 @@ var uvmap = UV468;
// src/face/faceres.ts
var model9;
var last3 = [];
var last6 = [];
var lastTime4 = 0;
var lastCount3 = 0;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load9(config3) {
@ -5703,29 +5721,29 @@ function enhance(input) {
return image25;
}
async function predict7(image25, config3, idx, count2) {
var _a, _b, _c;
var _a, _b, _c, _d;
if (!model9)
return null;
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount3 === count2 && ((_b = last3[idx]) == null ? void 0 : _b.age) && ((_c = last3[idx]) == null ? void 0 : _c.age) > 0) {
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
skipped8++;
return last3[idx];
return last6[idx];
}
skipped8 = 0;
return new Promise(async (resolve) => {
var _a2, _b2;
const enhanced = enhance(image25);
let resT;
const obj = {
age: 0,
gender: "unknown",
genderScore: 0,
descriptor: []
};
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled)
resT = await (model9 == null ? void 0 : model9.predict(enhanced));
tfjs_esm_exports.dispose(enhanced);
if (resT) {
const gender = await resT.find((t) => t.shape[1] === 1).data();
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
const enhanced = enhance(image25);
const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
lastTime4 = now();
tfjs_esm_exports.dispose(enhanced);
const genderT = await resT.find((t) => t.shape[1] === 1);
const gender = await genderT.data();
const confidence = Math.trunc(200 * Math.abs(gender[0] - 0.5)) / 100;
if (confidence > (((_b2 = config3.face.description) == null ? void 0 : _b2.minConfidence) || 0)) {
obj.gender = gender[0] <= 0.5 ? "female" : "male";
@ -5734,14 +5752,15 @@ async function predict7(image25, config3, idx, count2) {
const argmax = tfjs_esm_exports.argMax(resT.find((t) => t.shape[1] === 100), 1);
const age = (await argmax.data())[0];
tfjs_esm_exports.dispose(argmax);
const all2 = await resT.find((t) => t.shape[1] === 100).data();
const ageT = resT.find((t) => t.shape[1] === 100);
const all2 = await ageT.data();
obj.age = Math.round(all2[age - 1] > all2[age + 1] ? 10 * age - 100 * all2[age - 1] : 10 * age + 100 * all2[age + 1]) / 10;
const desc = resT.find((t) => t.shape[1] === 1024);
const descriptor = await desc.data();
obj.descriptor = [...descriptor];
const descriptor = desc ? await desc.data() : [];
obj.descriptor = Array.from(descriptor);
resT.forEach((t) => tfjs_esm_exports.dispose(t));
}
last3[idx] = obj;
last6[idx] = obj;
lastCount3 = count2;
resolve(obj);
});
@ -8888,6 +8907,7 @@ var handBoxEnlargeFactor = 1.65;
var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
var palmLandmarksPalmBase = 0;
var palmLandmarksMiddleFingerBase = 2;
var lastTime5 = 0;
var HandPipeline = class {
constructor(handDetector, handPoseModel2) {
__publicField(this, "handDetector");
@ -8952,7 +8972,7 @@ var HandPipeline = class {
async estimateHands(image25, config3) {
let useFreshBox = false;
let boxes;
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames || !config3.hand.landmarks || !config3.skipFrame) {
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
boxes = await this.handDetector.estimateHandBounds(image25, config3);
this.skipped = 0;
}
@ -8981,6 +9001,7 @@ var HandPipeline = class {
tfjs_esm_exports.dispose(croppedInput);
tfjs_esm_exports.dispose(rotatedImage);
const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
lastTime5 = now();
tfjs_esm_exports.dispose(handImage);
const confidence = (await confidenceT.data())[0];
tfjs_esm_exports.dispose(confidenceT);
@ -9549,6 +9570,7 @@ var boxExpandFact = 1.6;
var maxDetectorResolution = 512;
var detectorExpandFact = 1.4;
var skipped9 = 0;
var lastTime6 = 0;
var outputSize = [0, 0];
var cache3 = {
boxes: [],
@ -9688,16 +9710,17 @@ async function predict9(input, config3) {
return [];
outputSize = [input.shape[2] || 0, input.shape[1] || 0];
skipped9++;
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0)) {
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
return cache3.hands;
}
return new Promise(async (resolve) => {
if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && cache3.hands.length > 0) {
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
} else {
cache3.boxes = await detectHands(input, config3);
lastTime6 = now();
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
skipped9 = 0;
}
@ -9884,7 +9907,8 @@ var inputSize7 = 0;
var skipped10 = Number.MAX_SAFE_INTEGER;
var cache5 = {
boxes: [],
bodies: []
bodies: [],
last: 0
};
async function load11(config3) {
if (env.initial)
@ -9994,7 +10018,7 @@ async function predict10(input, config3) {
if (!config3.skipFrame)
cache5.boxes.length = 0;
skipped10++;
if (config3.skipFrame && skipped10 <= (config3.body.skipFrames || 0)) {
if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
return cache5.bodies;
}
return new Promise(async (resolve) => {
@ -10002,6 +10026,7 @@ async function predict10(input, config3) {
skipped10 = 0;
t.input = padInput(input, inputSize7);
t.res = await (model10 == null ? void 0 : model10.predict(t.input));
cache5.last = now();
const res = await t.res.array();
cache5.bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input, [0, 0, 1, 1]);
for (const body4 of cache5.bodies) {
@ -10015,7 +10040,8 @@ async function predict10(input, config3) {
// src/object/nanodet.ts
var model11;
var last4 = [];
var last7 = [];
var lastTime7 = 0;
var skipped11 = Number.MAX_SAFE_INTEGER;
var scaleBox = 2.5;
async function load12(config3) {
@ -10095,13 +10121,13 @@ async function process4(res, inputSize8, outputShape, config3) {
return results;
}
async function predict11(image25, config3) {
if (skipped11 < (config3.object.skipFrames || 0) && config3.skipFrame && last4.length > 0) {
if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
skipped11++;
return last4;
return last7;
}
skipped11 = 0;
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last4;
return last7;
return new Promise(async (resolve) => {
const outputSize2 = [image25.shape[2], image25.shape[1]];
const resize = tfjs_esm_exports.image.resizeBilinear(image25, [model11.inputSize, model11.inputSize], false);
@ -10112,9 +10138,10 @@ async function predict11(image25, config3) {
let objectT;
if (config3.object.enabled)
objectT = await model11.predict(transpose);
lastTime7 = now();
tfjs_esm_exports.dispose(transpose);
const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
last4 = obj;
last7 = obj;
resolve(obj);
});
}

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@ -184,6 +184,7 @@ var config = {
rotation: true,
maxDetected: 1,
skipFrames: 11,
skipTime: 2e3,
minConfidence: 0.2,
iouThreshold: 0.1,
return: false
@ -200,17 +201,20 @@ var config = {
enabled: true,
minConfidence: 0.1,
skipFrames: 12,
skipTime: 2e3,
modelPath: "emotion.json"
},
description: {
enabled: true,
modelPath: "faceres.json",
skipFrames: 13,
skipTime: 2e3,
minConfidence: 0.1
},
antispoof: {
enabled: false,
skipFrames: 14,
skipTime: 2e3,
modelPath: "antispoof.json"
}
},
@ -222,12 +226,14 @@ var config = {
},
maxDetected: -1,
minConfidence: 0.3,
skipFrames: 1
skipFrames: 1,
skipTime: 2e3
},
hand: {
enabled: true,
rotation: true,
skipFrames: 2,
skipTime: 2e3,
minConfidence: 0.5,
iouThreshold: 0.2,
maxDetected: -1,
@ -245,7 +251,8 @@ var config = {
minConfidence: 0.2,
iouThreshold: 0.4,
maxDetected: 10,
skipFrames: 15
skipFrames: 15,
skipTime: 2e3
},
segmentation: {
enabled: false,
@ -1314,6 +1321,7 @@ var model2;
var cached = [];
var skipped2 = Number.MAX_SAFE_INTEGER;
var lastCount = 0;
var last = 0;
async function load2(config3) {
var _a, _b;
if (env.initial)
@ -1329,10 +1337,10 @@ async function load2(config3) {
return model2;
}
async function predict(image25, config3, idx, count2) {
var _a;
var _a, _b;
if (!model2)
return null;
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount === count2 && cached[idx]) {
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
skipped2++;
return cached[idx];
}
@ -1343,6 +1351,7 @@ async function predict(image25, config3, idx, count2) {
const num = (await res.data())[0];
cached[idx] = Math.round(100 * num) / 100;
lastCount = count2;
last = now();
tf4.dispose([resize, res]);
resolve(cached[idx]);
});
@ -4927,6 +4936,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
var outputNodes;
var cache = null;
var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
var last2 = 0;
async function loadDetect(config3) {
var _a, _b, _c;
if (env3.initial)
@ -5043,10 +5053,11 @@ async function detectParts(input, config3, outputSize2) {
}
async function predict2(input, config3) {
const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
if (skipped3 < (config3.body.skipFrames || 0) && config3.skipFrame && cache !== null) {
if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
skipped3++;
} else {
cache = await detectParts(input, config3, outputSize2);
last2 = now();
skipped3 = 0;
}
if (cache)
@ -5144,7 +5155,8 @@ var labels = [
// src/object/centernet.ts
var model4;
var inputSize3 = 0;
var last = [];
var last3 = [];
var lastTime = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
async function load4(config3) {
if (env.initial)
@ -5209,20 +5221,21 @@ async function process3(res, outputShape, config3) {
return results;
}
async function predict3(input, config3) {
if (skipped4 < (config3.object.skipFrames || 0) && config3.skipFrame && last.length > 0) {
if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
skipped4++;
return last;
return last3;
}
skipped4 = 0;
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last;
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [input.shape[2], input.shape[1]];
const resize = tf8.image.resizeBilinear(input, [inputSize3, inputSize3]);
const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
lastTime = now();
tf8.dispose(resize);
const obj = await process3(objectT, outputSize2, config3);
last = obj;
last3 = obj;
resolve(obj);
});
}
@ -5265,6 +5278,7 @@ var connected2 = {
// src/body/efficientpose.ts
var model5;
var last4 = 0;
var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
var skipped5 = Number.MAX_SAFE_INTEGER;
async function load5(config3) {
@ -5297,7 +5311,7 @@ function max2d(inputs, minScore) {
}
async function predict4(image25, config3) {
var _a;
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0) {
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
skipped5++;
return [cache2];
}
@ -5315,6 +5329,7 @@ async function predict4(image25, config3) {
let resT;
if (config3.body.enabled)
resT = await (model5 == null ? void 0 : model5.predict(tensor3));
last4 = now();
tf9.dispose(tensor3);
if (resT) {
cache2.keypoints.length = 0;
@ -5376,8 +5391,9 @@ async function predict4(image25, config3) {
var tf10 = __toModule(require_tfjs_esm());
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model6;
var last2 = [];
var last5 = [];
var lastCount2 = 0;
var lastTime2 = 0;
var skipped6 = Number.MAX_SAFE_INTEGER;
var rgb = [0.2989, 0.587, 0.114];
async function load6(config3) {
@ -5395,44 +5411,45 @@ async function load6(config3) {
return model6;
}
async function predict5(image25, config3, idx, count2) {
var _a;
var _a, _b;
if (!model6)
return null;
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
skipped6++;
return last2[idx];
return last5[idx];
}
skipped6 = 0;
return new Promise(async (resolve) => {
var _a2, _b;
const resize = tf10.image.resizeBilinear(image25, [(model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[2] : 0, (model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tf10.split(resize, 3, 3);
tf10.dispose(resize);
const redNorm = tf10.mul(red, rgb[0]);
const greenNorm = tf10.mul(green, rgb[1]);
const blueNorm = tf10.mul(blue, rgb[2]);
tf10.dispose(red);
tf10.dispose(green);
tf10.dispose(blue);
const grayscale = tf10.addN([redNorm, greenNorm, blueNorm]);
tf10.dispose(redNorm);
tf10.dispose(greenNorm);
tf10.dispose(blueNorm);
const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
tf10.dispose(grayscale);
var _a2, _b2;
const obj = [];
if ((_a2 = config3.face.emotion) == null ? void 0 : _a2.enabled) {
const resize = tf10.image.resizeBilinear(image25, [(model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[2] : 0, (model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tf10.split(resize, 3, 3);
tf10.dispose(resize);
const redNorm = tf10.mul(red, rgb[0]);
const greenNorm = tf10.mul(green, rgb[1]);
const blueNorm = tf10.mul(blue, rgb[2]);
tf10.dispose(red);
tf10.dispose(green);
tf10.dispose(blue);
const grayscale = tf10.addN([redNorm, greenNorm, blueNorm]);
tf10.dispose(redNorm);
tf10.dispose(greenNorm);
tf10.dispose(blueNorm);
const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
tf10.dispose(grayscale);
const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
lastTime2 = now();
const data = await emotionT.data();
tf10.dispose(emotionT);
for (let i = 0; i < data.length; i++) {
if (data[i] > (((_b = config3.face.emotion) == null ? void 0 : _b.minConfidence) || 0))
if (data[i] > (((_b2 = config3.face.emotion) == null ? void 0 : _b2.minConfidence) || 0))
obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });
}
obj.sort((a, b) => b.score - a.score);
tf10.dispose(normalize);
}
tf10.dispose(normalize);
last2[idx] = obj;
last5[idx] = obj;
lastCount2 = count2;
resolve(obj);
});
@ -5579,11 +5596,13 @@ var boxCache = [];
var model8 = null;
var inputSize5 = 0;
var skipped7 = Number.MAX_SAFE_INTEGER;
var lastTime3 = 0;
var detectedFaces = 0;
async function predict6(input, config3) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0)) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
const newBoxes2 = await getBoxes(input, config3);
lastTime3 = now();
boxCache = [];
for (const possible of newBoxes2.boxes) {
const startPoint = await possible.box.startPoint.data();
@ -5619,16 +5638,16 @@ async function predict6(input, config3) {
faceScore: 0,
annotations: {}
};
if (((_d = config3.face.detector) == null ? void 0 : _d.rotation) && ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) && env.kernels.includes("rotatewithoffset")) {
if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env.kernels.includes("rotatewithoffset")) {
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
} else {
rotationMatrix = IDENTITY_MATRIX;
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
face5.tensor = tf12.div(cut, 255);
tf12.dispose(cut);
}
face5.boxScore = Math.round(100 * box4.confidence) / 100;
if (!((_g = config3.face.mesh) == null ? void 0 : _g.enabled)) {
if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
face5.box = getClampedBox(box4, input);
face5.boxRaw = getRawBox(box4, input);
face5.score = Math.round(100 * box4.confidence || 0) / 100;
@ -5651,17 +5670,17 @@ async function predict6(input, config3) {
let rawCoords = await coordsReshaped.array();
tf12.dispose(contourCoords);
tf12.dispose(coordsReshaped);
if (faceConfidence < (((_h = config3.face.detector) == null ? void 0 : _h.minConfidence) || 1)) {
if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
box4.confidence = faceConfidence;
} else {
if ((_i = config3.face.iris) == null ? void 0 : _i.enabled)
if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
for (const key of Object.keys(meshAnnotations))
face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
if (((_j = config3.face.detector) == null ? void 0 : _j.rotation) && config3.face.mesh.enabled && ((_k = config3.face.description) == null ? void 0 : _k.enabled) && env.kernels.includes("rotatewithoffset")) {
if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env.kernels.includes("rotatewithoffset")) {
tf12.dispose(face5.tensor);
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
}
@ -5675,7 +5694,7 @@ async function predict6(input, config3) {
faces.push(face5);
newBoxes.push(box4);
}
if ((_l = config3.face.mesh) == null ? void 0 : _l.enabled)
if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
boxCache = newBoxes.filter((a) => {
var _a2;
return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@ -5706,7 +5725,8 @@ var uvmap = UV468;
// src/face/faceres.ts
var tf13 = __toModule(require_tfjs_esm());
var model9;
var last3 = [];
var last6 = [];
var lastTime4 = 0;
var lastCount3 = 0;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load9(config3) {
@ -5739,29 +5759,29 @@ function enhance(input) {
return image25;
}
async function predict7(image25, config3, idx, count2) {
var _a, _b, _c;
var _a, _b, _c, _d;
if (!model9)
return null;
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount3 === count2 && ((_b = last3[idx]) == null ? void 0 : _b.age) && ((_c = last3[idx]) == null ? void 0 : _c.age) > 0) {
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
skipped8++;
return last3[idx];
return last6[idx];
}
skipped8 = 0;
return new Promise(async (resolve) => {
var _a2, _b2;
const enhanced = enhance(image25);
let resT;
const obj = {
age: 0,
gender: "unknown",
genderScore: 0,
descriptor: []
};
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled)
resT = await (model9 == null ? void 0 : model9.predict(enhanced));
tf13.dispose(enhanced);
if (resT) {
const gender = await resT.find((t) => t.shape[1] === 1).data();
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
const enhanced = enhance(image25);
const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
lastTime4 = now();
tf13.dispose(enhanced);
const genderT = await resT.find((t) => t.shape[1] === 1);
const gender = await genderT.data();
const confidence = Math.trunc(200 * Math.abs(gender[0] - 0.5)) / 100;
if (confidence > (((_b2 = config3.face.description) == null ? void 0 : _b2.minConfidence) || 0)) {
obj.gender = gender[0] <= 0.5 ? "female" : "male";
@ -5770,14 +5790,15 @@ async function predict7(image25, config3, idx, count2) {
const argmax = tf13.argMax(resT.find((t) => t.shape[1] === 100), 1);
const age = (await argmax.data())[0];
tf13.dispose(argmax);
const all2 = await resT.find((t) => t.shape[1] === 100).data();
const ageT = resT.find((t) => t.shape[1] === 100);
const all2 = await ageT.data();
obj.age = Math.round(all2[age - 1] > all2[age + 1] ? 10 * age - 100 * all2[age - 1] : 10 * age + 100 * all2[age + 1]) / 10;
const desc = resT.find((t) => t.shape[1] === 1024);
const descriptor = await desc.data();
obj.descriptor = [...descriptor];
const descriptor = desc ? await desc.data() : [];
obj.descriptor = Array.from(descriptor);
resT.forEach((t) => tf13.dispose(t));
}
last3[idx] = obj;
last6[idx] = obj;
lastCount3 = count2;
resolve(obj);
});
@ -8932,6 +8953,7 @@ var handBoxEnlargeFactor = 1.65;
var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
var palmLandmarksPalmBase = 0;
var palmLandmarksMiddleFingerBase = 2;
var lastTime5 = 0;
var HandPipeline = class {
constructor(handDetector, handPoseModel2) {
__publicField(this, "handDetector");
@ -8996,7 +9018,7 @@ var HandPipeline = class {
async estimateHands(image25, config3) {
let useFreshBox = false;
let boxes;
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames || !config3.hand.landmarks || !config3.skipFrame) {
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
boxes = await this.handDetector.estimateHandBounds(image25, config3);
this.skipped = 0;
}
@ -9025,6 +9047,7 @@ var HandPipeline = class {
tf16.dispose(croppedInput);
tf16.dispose(rotatedImage);
const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
lastTime5 = now();
tf16.dispose(handImage);
const confidence = (await confidenceT.data())[0];
tf16.dispose(confidenceT);
@ -9594,6 +9617,7 @@ var boxExpandFact = 1.6;
var maxDetectorResolution = 512;
var detectorExpandFact = 1.4;
var skipped9 = 0;
var lastTime6 = 0;
var outputSize = [0, 0];
var cache3 = {
boxes: [],
@ -9733,16 +9757,17 @@ async function predict9(input, config3) {
return [];
outputSize = [input.shape[2] || 0, input.shape[1] || 0];
skipped9++;
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0)) {
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
return cache3.hands;
}
return new Promise(async (resolve) => {
if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && cache3.hands.length > 0) {
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
} else {
cache3.boxes = await detectHands(input, config3);
lastTime6 = now();
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
skipped9 = 0;
}
@ -9933,7 +9958,8 @@ var inputSize7 = 0;
var skipped10 = Number.MAX_SAFE_INTEGER;
var cache5 = {
boxes: [],
bodies: []
bodies: [],
last: 0
};
async function load11(config3) {
if (env.initial)
@ -10043,7 +10069,7 @@ async function predict10(input, config3) {
if (!config3.skipFrame)
cache5.boxes.length = 0;
skipped10++;
if (config3.skipFrame && skipped10 <= (config3.body.skipFrames || 0)) {
if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
return cache5.bodies;
}
return new Promise(async (resolve) => {
@ -10051,6 +10077,7 @@ async function predict10(input, config3) {
skipped10 = 0;
t.input = padInput(input, inputSize7);
t.res = await (model10 == null ? void 0 : model10.predict(t.input));
cache5.last = now();
const res = await t.res.array();
cache5.bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input, [0, 0, 1, 1]);
for (const body4 of cache5.bodies) {
@ -10065,7 +10092,8 @@ async function predict10(input, config3) {
// src/object/nanodet.ts
var tf21 = __toModule(require_tfjs_esm());
var model11;
var last4 = [];
var last7 = [];
var lastTime7 = 0;
var skipped11 = Number.MAX_SAFE_INTEGER;
var scaleBox = 2.5;
async function load12(config3) {
@ -10145,13 +10173,13 @@ async function process4(res, inputSize8, outputShape, config3) {
return results;
}
async function predict11(image25, config3) {
if (skipped11 < (config3.object.skipFrames || 0) && config3.skipFrame && last4.length > 0) {
if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
skipped11++;
return last4;
return last7;
}
skipped11 = 0;
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last4;
return last7;
return new Promise(async (resolve) => {
const outputSize2 = [image25.shape[2], image25.shape[1]];
const resize = tf21.image.resizeBilinear(image25, [model11.inputSize, model11.inputSize], false);
@ -10162,9 +10190,10 @@ async function predict11(image25, config3) {
let objectT;
if (config3.object.enabled)
objectT = await model11.predict(transpose);
lastTime7 = now();
tf21.dispose(transpose);
const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
last4 = obj;
last7 = obj;
resolve(obj);
});
}

165
dist/human.node-wasm.js vendored
View File

@ -185,6 +185,7 @@ var config = {
rotation: true,
maxDetected: 1,
skipFrames: 11,
skipTime: 2e3,
minConfidence: 0.2,
iouThreshold: 0.1,
return: false
@ -201,17 +202,20 @@ var config = {
enabled: true,
minConfidence: 0.1,
skipFrames: 12,
skipTime: 2e3,
modelPath: "emotion.json"
},
description: {
enabled: true,
modelPath: "faceres.json",
skipFrames: 13,
skipTime: 2e3,
minConfidence: 0.1
},
antispoof: {
enabled: false,
skipFrames: 14,
skipTime: 2e3,
modelPath: "antispoof.json"
}
},
@ -223,12 +227,14 @@ var config = {
},
maxDetected: -1,
minConfidence: 0.3,
skipFrames: 1
skipFrames: 1,
skipTime: 2e3
},
hand: {
enabled: true,
rotation: true,
skipFrames: 2,
skipTime: 2e3,
minConfidence: 0.5,
iouThreshold: 0.2,
maxDetected: -1,
@ -246,7 +252,8 @@ var config = {
minConfidence: 0.2,
iouThreshold: 0.4,
maxDetected: 10,
skipFrames: 15
skipFrames: 15,
skipTime: 2e3
},
segmentation: {
enabled: false,
@ -1315,6 +1322,7 @@ var model2;
var cached = [];
var skipped2 = Number.MAX_SAFE_INTEGER;
var lastCount = 0;
var last = 0;
async function load2(config3) {
var _a, _b;
if (env.initial)
@ -1330,10 +1338,10 @@ async function load2(config3) {
return model2;
}
async function predict(image25, config3, idx, count2) {
var _a;
var _a, _b;
if (!model2)
return null;
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount === count2 && cached[idx]) {
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
skipped2++;
return cached[idx];
}
@ -1344,6 +1352,7 @@ async function predict(image25, config3, idx, count2) {
const num = (await res.data())[0];
cached[idx] = Math.round(100 * num) / 100;
lastCount = count2;
last = now();
tf4.dispose([resize, res]);
resolve(cached[idx]);
});
@ -4928,6 +4937,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
var outputNodes;
var cache = null;
var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
var last2 = 0;
async function loadDetect(config3) {
var _a, _b, _c;
if (env3.initial)
@ -5044,10 +5054,11 @@ async function detectParts(input, config3, outputSize2) {
}
async function predict2(input, config3) {
const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
if (skipped3 < (config3.body.skipFrames || 0) && config3.skipFrame && cache !== null) {
if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
skipped3++;
} else {
cache = await detectParts(input, config3, outputSize2);
last2 = now();
skipped3 = 0;
}
if (cache)
@ -5145,7 +5156,8 @@ var labels = [
// src/object/centernet.ts
var model4;
var inputSize3 = 0;
var last = [];
var last3 = [];
var lastTime = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
async function load4(config3) {
if (env.initial)
@ -5210,20 +5222,21 @@ async function process3(res, outputShape, config3) {
return results;
}
async function predict3(input, config3) {
if (skipped4 < (config3.object.skipFrames || 0) && config3.skipFrame && last.length > 0) {
if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
skipped4++;
return last;
return last3;
}
skipped4 = 0;
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last;
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [input.shape[2], input.shape[1]];
const resize = tf8.image.resizeBilinear(input, [inputSize3, inputSize3]);
const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
lastTime = now();
tf8.dispose(resize);
const obj = await process3(objectT, outputSize2, config3);
last = obj;
last3 = obj;
resolve(obj);
});
}
@ -5266,6 +5279,7 @@ var connected2 = {
// src/body/efficientpose.ts
var model5;
var last4 = 0;
var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
var skipped5 = Number.MAX_SAFE_INTEGER;
async function load5(config3) {
@ -5298,7 +5312,7 @@ function max2d(inputs, minScore) {
}
async function predict4(image25, config3) {
var _a;
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0) {
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
skipped5++;
return [cache2];
}
@ -5316,6 +5330,7 @@ async function predict4(image25, config3) {
let resT;
if (config3.body.enabled)
resT = await (model5 == null ? void 0 : model5.predict(tensor3));
last4 = now();
tf9.dispose(tensor3);
if (resT) {
cache2.keypoints.length = 0;
@ -5377,8 +5392,9 @@ async function predict4(image25, config3) {
var tf10 = __toModule(require_tfjs_esm());
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model6;
var last2 = [];
var last5 = [];
var lastCount2 = 0;
var lastTime2 = 0;
var skipped6 = Number.MAX_SAFE_INTEGER;
var rgb = [0.2989, 0.587, 0.114];
async function load6(config3) {
@ -5396,44 +5412,45 @@ async function load6(config3) {
return model6;
}
async function predict5(image25, config3, idx, count2) {
var _a;
var _a, _b;
if (!model6)
return null;
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
skipped6++;
return last2[idx];
return last5[idx];
}
skipped6 = 0;
return new Promise(async (resolve) => {
var _a2, _b;
const resize = tf10.image.resizeBilinear(image25, [(model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[2] : 0, (model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tf10.split(resize, 3, 3);
tf10.dispose(resize);
const redNorm = tf10.mul(red, rgb[0]);
const greenNorm = tf10.mul(green, rgb[1]);
const blueNorm = tf10.mul(blue, rgb[2]);
tf10.dispose(red);
tf10.dispose(green);
tf10.dispose(blue);
const grayscale = tf10.addN([redNorm, greenNorm, blueNorm]);
tf10.dispose(redNorm);
tf10.dispose(greenNorm);
tf10.dispose(blueNorm);
const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
tf10.dispose(grayscale);
var _a2, _b2;
const obj = [];
if ((_a2 = config3.face.emotion) == null ? void 0 : _a2.enabled) {
const resize = tf10.image.resizeBilinear(image25, [(model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[2] : 0, (model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tf10.split(resize, 3, 3);
tf10.dispose(resize);
const redNorm = tf10.mul(red, rgb[0]);
const greenNorm = tf10.mul(green, rgb[1]);
const blueNorm = tf10.mul(blue, rgb[2]);
tf10.dispose(red);
tf10.dispose(green);
tf10.dispose(blue);
const grayscale = tf10.addN([redNorm, greenNorm, blueNorm]);
tf10.dispose(redNorm);
tf10.dispose(greenNorm);
tf10.dispose(blueNorm);
const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
tf10.dispose(grayscale);
const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
lastTime2 = now();
const data = await emotionT.data();
tf10.dispose(emotionT);
for (let i = 0; i < data.length; i++) {
if (data[i] > (((_b = config3.face.emotion) == null ? void 0 : _b.minConfidence) || 0))
if (data[i] > (((_b2 = config3.face.emotion) == null ? void 0 : _b2.minConfidence) || 0))
obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });
}
obj.sort((a, b) => b.score - a.score);
tf10.dispose(normalize);
}
tf10.dispose(normalize);
last2[idx] = obj;
last5[idx] = obj;
lastCount2 = count2;
resolve(obj);
});
@ -5580,11 +5597,13 @@ var boxCache = [];
var model8 = null;
var inputSize5 = 0;
var skipped7 = Number.MAX_SAFE_INTEGER;
var lastTime3 = 0;
var detectedFaces = 0;
async function predict6(input, config3) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0)) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
const newBoxes2 = await getBoxes(input, config3);
lastTime3 = now();
boxCache = [];
for (const possible of newBoxes2.boxes) {
const startPoint = await possible.box.startPoint.data();
@ -5620,16 +5639,16 @@ async function predict6(input, config3) {
faceScore: 0,
annotations: {}
};
if (((_d = config3.face.detector) == null ? void 0 : _d.rotation) && ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) && env.kernels.includes("rotatewithoffset")) {
if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env.kernels.includes("rotatewithoffset")) {
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
} else {
rotationMatrix = IDENTITY_MATRIX;
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
face5.tensor = tf12.div(cut, 255);
tf12.dispose(cut);
}
face5.boxScore = Math.round(100 * box4.confidence) / 100;
if (!((_g = config3.face.mesh) == null ? void 0 : _g.enabled)) {
if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
face5.box = getClampedBox(box4, input);
face5.boxRaw = getRawBox(box4, input);
face5.score = Math.round(100 * box4.confidence || 0) / 100;
@ -5652,17 +5671,17 @@ async function predict6(input, config3) {
let rawCoords = await coordsReshaped.array();
tf12.dispose(contourCoords);
tf12.dispose(coordsReshaped);
if (faceConfidence < (((_h = config3.face.detector) == null ? void 0 : _h.minConfidence) || 1)) {
if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
box4.confidence = faceConfidence;
} else {
if ((_i = config3.face.iris) == null ? void 0 : _i.enabled)
if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
for (const key of Object.keys(meshAnnotations))
face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
if (((_j = config3.face.detector) == null ? void 0 : _j.rotation) && config3.face.mesh.enabled && ((_k = config3.face.description) == null ? void 0 : _k.enabled) && env.kernels.includes("rotatewithoffset")) {
if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env.kernels.includes("rotatewithoffset")) {
tf12.dispose(face5.tensor);
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
}
@ -5676,7 +5695,7 @@ async function predict6(input, config3) {
faces.push(face5);
newBoxes.push(box4);
}
if ((_l = config3.face.mesh) == null ? void 0 : _l.enabled)
if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
boxCache = newBoxes.filter((a) => {
var _a2;
return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@ -5707,7 +5726,8 @@ var uvmap = UV468;
// src/face/faceres.ts
var tf13 = __toModule(require_tfjs_esm());
var model9;
var last3 = [];
var last6 = [];
var lastTime4 = 0;
var lastCount3 = 0;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load9(config3) {
@ -5740,29 +5760,29 @@ function enhance(input) {
return image25;
}
async function predict7(image25, config3, idx, count2) {
var _a, _b, _c;
var _a, _b, _c, _d;
if (!model9)
return null;
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount3 === count2 && ((_b = last3[idx]) == null ? void 0 : _b.age) && ((_c = last3[idx]) == null ? void 0 : _c.age) > 0) {
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
skipped8++;
return last3[idx];
return last6[idx];
}
skipped8 = 0;
return new Promise(async (resolve) => {
var _a2, _b2;
const enhanced = enhance(image25);
let resT;
const obj = {
age: 0,
gender: "unknown",
genderScore: 0,
descriptor: []
};
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled)
resT = await (model9 == null ? void 0 : model9.predict(enhanced));
tf13.dispose(enhanced);
if (resT) {
const gender = await resT.find((t) => t.shape[1] === 1).data();
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
const enhanced = enhance(image25);
const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
lastTime4 = now();
tf13.dispose(enhanced);
const genderT = await resT.find((t) => t.shape[1] === 1);
const gender = await genderT.data();
const confidence = Math.trunc(200 * Math.abs(gender[0] - 0.5)) / 100;
if (confidence > (((_b2 = config3.face.description) == null ? void 0 : _b2.minConfidence) || 0)) {
obj.gender = gender[0] <= 0.5 ? "female" : "male";
@ -5771,14 +5791,15 @@ async function predict7(image25, config3, idx, count2) {
const argmax = tf13.argMax(resT.find((t) => t.shape[1] === 100), 1);
const age = (await argmax.data())[0];
tf13.dispose(argmax);
const all2 = await resT.find((t) => t.shape[1] === 100).data();
const ageT = resT.find((t) => t.shape[1] === 100);
const all2 = await ageT.data();
obj.age = Math.round(all2[age - 1] > all2[age + 1] ? 10 * age - 100 * all2[age - 1] : 10 * age + 100 * all2[age + 1]) / 10;
const desc = resT.find((t) => t.shape[1] === 1024);
const descriptor = await desc.data();
obj.descriptor = [...descriptor];
const descriptor = desc ? await desc.data() : [];
obj.descriptor = Array.from(descriptor);
resT.forEach((t) => tf13.dispose(t));
}
last3[idx] = obj;
last6[idx] = obj;
lastCount3 = count2;
resolve(obj);
});
@ -8933,6 +8954,7 @@ var handBoxEnlargeFactor = 1.65;
var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
var palmLandmarksPalmBase = 0;
var palmLandmarksMiddleFingerBase = 2;
var lastTime5 = 0;
var HandPipeline = class {
constructor(handDetector, handPoseModel2) {
__publicField(this, "handDetector");
@ -8997,7 +9019,7 @@ var HandPipeline = class {
async estimateHands(image25, config3) {
let useFreshBox = false;
let boxes;
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames || !config3.hand.landmarks || !config3.skipFrame) {
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
boxes = await this.handDetector.estimateHandBounds(image25, config3);
this.skipped = 0;
}
@ -9026,6 +9048,7 @@ var HandPipeline = class {
tf16.dispose(croppedInput);
tf16.dispose(rotatedImage);
const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
lastTime5 = now();
tf16.dispose(handImage);
const confidence = (await confidenceT.data())[0];
tf16.dispose(confidenceT);
@ -9595,6 +9618,7 @@ var boxExpandFact = 1.6;
var maxDetectorResolution = 512;
var detectorExpandFact = 1.4;
var skipped9 = 0;
var lastTime6 = 0;
var outputSize = [0, 0];
var cache3 = {
boxes: [],
@ -9734,16 +9758,17 @@ async function predict9(input, config3) {
return [];
outputSize = [input.shape[2] || 0, input.shape[1] || 0];
skipped9++;
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0)) {
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
return cache3.hands;
}
return new Promise(async (resolve) => {
if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && cache3.hands.length > 0) {
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
} else {
cache3.boxes = await detectHands(input, config3);
lastTime6 = now();
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
skipped9 = 0;
}
@ -9934,7 +9959,8 @@ var inputSize7 = 0;
var skipped10 = Number.MAX_SAFE_INTEGER;
var cache5 = {
boxes: [],
bodies: []
bodies: [],
last: 0
};
async function load11(config3) {
if (env.initial)
@ -10044,7 +10070,7 @@ async function predict10(input, config3) {
if (!config3.skipFrame)
cache5.boxes.length = 0;
skipped10++;
if (config3.skipFrame && skipped10 <= (config3.body.skipFrames || 0)) {
if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
return cache5.bodies;
}
return new Promise(async (resolve) => {
@ -10052,6 +10078,7 @@ async function predict10(input, config3) {
skipped10 = 0;
t.input = padInput(input, inputSize7);
t.res = await (model10 == null ? void 0 : model10.predict(t.input));
cache5.last = now();
const res = await t.res.array();
cache5.bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input, [0, 0, 1, 1]);
for (const body4 of cache5.bodies) {
@ -10066,7 +10093,8 @@ async function predict10(input, config3) {
// src/object/nanodet.ts
var tf21 = __toModule(require_tfjs_esm());
var model11;
var last4 = [];
var last7 = [];
var lastTime7 = 0;
var skipped11 = Number.MAX_SAFE_INTEGER;
var scaleBox = 2.5;
async function load12(config3) {
@ -10146,13 +10174,13 @@ async function process4(res, inputSize8, outputShape, config3) {
return results;
}
async function predict11(image25, config3) {
if (skipped11 < (config3.object.skipFrames || 0) && config3.skipFrame && last4.length > 0) {
if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
skipped11++;
return last4;
return last7;
}
skipped11 = 0;
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last4;
return last7;
return new Promise(async (resolve) => {
const outputSize2 = [image25.shape[2], image25.shape[1]];
const resize = tf21.image.resizeBilinear(image25, [model11.inputSize, model11.inputSize], false);
@ -10163,9 +10191,10 @@ async function predict11(image25, config3) {
let objectT;
if (config3.object.enabled)
objectT = await model11.predict(transpose);
lastTime7 = now();
tf21.dispose(transpose);
const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
last4 = obj;
last7 = obj;
resolve(obj);
});
}

165
dist/human.node.js vendored
View File

@ -184,6 +184,7 @@ var config = {
rotation: true,
maxDetected: 1,
skipFrames: 11,
skipTime: 2e3,
minConfidence: 0.2,
iouThreshold: 0.1,
return: false
@ -200,17 +201,20 @@ var config = {
enabled: true,
minConfidence: 0.1,
skipFrames: 12,
skipTime: 2e3,
modelPath: "emotion.json"
},
description: {
enabled: true,
modelPath: "faceres.json",
skipFrames: 13,
skipTime: 2e3,
minConfidence: 0.1
},
antispoof: {
enabled: false,
skipFrames: 14,
skipTime: 2e3,
modelPath: "antispoof.json"
}
},
@ -222,12 +226,14 @@ var config = {
},
maxDetected: -1,
minConfidence: 0.3,
skipFrames: 1
skipFrames: 1,
skipTime: 2e3
},
hand: {
enabled: true,
rotation: true,
skipFrames: 2,
skipTime: 2e3,
minConfidence: 0.5,
iouThreshold: 0.2,
maxDetected: -1,
@ -245,7 +251,8 @@ var config = {
minConfidence: 0.2,
iouThreshold: 0.4,
maxDetected: 10,
skipFrames: 15
skipFrames: 15,
skipTime: 2e3
},
segmentation: {
enabled: false,
@ -1314,6 +1321,7 @@ var model2;
var cached = [];
var skipped2 = Number.MAX_SAFE_INTEGER;
var lastCount = 0;
var last = 0;
async function load2(config3) {
var _a, _b;
if (env.initial)
@ -1329,10 +1337,10 @@ async function load2(config3) {
return model2;
}
async function predict(image25, config3, idx, count2) {
var _a;
var _a, _b;
if (!model2)
return null;
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount === count2 && cached[idx]) {
if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
skipped2++;
return cached[idx];
}
@ -1343,6 +1351,7 @@ async function predict(image25, config3, idx, count2) {
const num = (await res.data())[0];
cached[idx] = Math.round(100 * num) / 100;
lastCount = count2;
last = now();
tf4.dispose([resize, res]);
resolve(cached[idx]);
});
@ -4927,6 +4936,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
var outputNodes;
var cache = null;
var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
var last2 = 0;
async function loadDetect(config3) {
var _a, _b, _c;
if (env3.initial)
@ -5043,10 +5053,11 @@ async function detectParts(input, config3, outputSize2) {
}
async function predict2(input, config3) {
const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
if (skipped3 < (config3.body.skipFrames || 0) && config3.skipFrame && cache !== null) {
if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
skipped3++;
} else {
cache = await detectParts(input, config3, outputSize2);
last2 = now();
skipped3 = 0;
}
if (cache)
@ -5144,7 +5155,8 @@ var labels = [
// src/object/centernet.ts
var model4;
var inputSize3 = 0;
var last = [];
var last3 = [];
var lastTime = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
async function load4(config3) {
if (env.initial)
@ -5209,20 +5221,21 @@ async function process3(res, outputShape, config3) {
return results;
}
async function predict3(input, config3) {
if (skipped4 < (config3.object.skipFrames || 0) && config3.skipFrame && last.length > 0) {
if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
skipped4++;
return last;
return last3;
}
skipped4 = 0;
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last;
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [input.shape[2], input.shape[1]];
const resize = tf8.image.resizeBilinear(input, [inputSize3, inputSize3]);
const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
lastTime = now();
tf8.dispose(resize);
const obj = await process3(objectT, outputSize2, config3);
last = obj;
last3 = obj;
resolve(obj);
});
}
@ -5265,6 +5278,7 @@ var connected2 = {
// src/body/efficientpose.ts
var model5;
var last4 = 0;
var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
var skipped5 = Number.MAX_SAFE_INTEGER;
async function load5(config3) {
@ -5297,7 +5311,7 @@ function max2d(inputs, minScore) {
}
async function predict4(image25, config3) {
var _a;
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0) {
if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
skipped5++;
return [cache2];
}
@ -5315,6 +5329,7 @@ async function predict4(image25, config3) {
let resT;
if (config3.body.enabled)
resT = await (model5 == null ? void 0 : model5.predict(tensor3));
last4 = now();
tf9.dispose(tensor3);
if (resT) {
cache2.keypoints.length = 0;
@ -5376,8 +5391,9 @@ async function predict4(image25, config3) {
var tf10 = __toModule(require_tfjs_esm());
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model6;
var last2 = [];
var last5 = [];
var lastCount2 = 0;
var lastTime2 = 0;
var skipped6 = Number.MAX_SAFE_INTEGER;
var rgb = [0.2989, 0.587, 0.114];
async function load6(config3) {
@ -5395,44 +5411,45 @@ async function load6(config3) {
return model6;
}
async function predict5(image25, config3, idx, count2) {
var _a;
var _a, _b;
if (!model6)
return null;
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
skipped6++;
return last2[idx];
return last5[idx];
}
skipped6 = 0;
return new Promise(async (resolve) => {
var _a2, _b;
const resize = tf10.image.resizeBilinear(image25, [(model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[2] : 0, (model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tf10.split(resize, 3, 3);
tf10.dispose(resize);
const redNorm = tf10.mul(red, rgb[0]);
const greenNorm = tf10.mul(green, rgb[1]);
const blueNorm = tf10.mul(blue, rgb[2]);
tf10.dispose(red);
tf10.dispose(green);
tf10.dispose(blue);
const grayscale = tf10.addN([redNorm, greenNorm, blueNorm]);
tf10.dispose(redNorm);
tf10.dispose(greenNorm);
tf10.dispose(blueNorm);
const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
tf10.dispose(grayscale);
var _a2, _b2;
const obj = [];
if ((_a2 = config3.face.emotion) == null ? void 0 : _a2.enabled) {
const resize = tf10.image.resizeBilinear(image25, [(model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[2] : 0, (model6 == null ? void 0 : model6.inputs[0].shape) ? model6.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tf10.split(resize, 3, 3);
tf10.dispose(resize);
const redNorm = tf10.mul(red, rgb[0]);
const greenNorm = tf10.mul(green, rgb[1]);
const blueNorm = tf10.mul(blue, rgb[2]);
tf10.dispose(red);
tf10.dispose(green);
tf10.dispose(blue);
const grayscale = tf10.addN([redNorm, greenNorm, blueNorm]);
tf10.dispose(redNorm);
tf10.dispose(greenNorm);
tf10.dispose(blueNorm);
const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
tf10.dispose(grayscale);
const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
lastTime2 = now();
const data = await emotionT.data();
tf10.dispose(emotionT);
for (let i = 0; i < data.length; i++) {
if (data[i] > (((_b = config3.face.emotion) == null ? void 0 : _b.minConfidence) || 0))
if (data[i] > (((_b2 = config3.face.emotion) == null ? void 0 : _b2.minConfidence) || 0))
obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });
}
obj.sort((a, b) => b.score - a.score);
tf10.dispose(normalize);
}
tf10.dispose(normalize);
last2[idx] = obj;
last5[idx] = obj;
lastCount2 = count2;
resolve(obj);
});
@ -5579,11 +5596,13 @@ var boxCache = [];
var model8 = null;
var inputSize5 = 0;
var skipped7 = Number.MAX_SAFE_INTEGER;
var lastTime3 = 0;
var detectedFaces = 0;
async function predict6(input, config3) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0)) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
const newBoxes2 = await getBoxes(input, config3);
lastTime3 = now();
boxCache = [];
for (const possible of newBoxes2.boxes) {
const startPoint = await possible.box.startPoint.data();
@ -5619,16 +5638,16 @@ async function predict6(input, config3) {
faceScore: 0,
annotations: {}
};
if (((_d = config3.face.detector) == null ? void 0 : _d.rotation) && ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) && env.kernels.includes("rotatewithoffset")) {
if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env.kernels.includes("rotatewithoffset")) {
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
} else {
rotationMatrix = IDENTITY_MATRIX;
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
face5.tensor = tf12.div(cut, 255);
tf12.dispose(cut);
}
face5.boxScore = Math.round(100 * box4.confidence) / 100;
if (!((_g = config3.face.mesh) == null ? void 0 : _g.enabled)) {
if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
face5.box = getClampedBox(box4, input);
face5.boxRaw = getRawBox(box4, input);
face5.score = Math.round(100 * box4.confidence || 0) / 100;
@ -5651,17 +5670,17 @@ async function predict6(input, config3) {
let rawCoords = await coordsReshaped.array();
tf12.dispose(contourCoords);
tf12.dispose(coordsReshaped);
if (faceConfidence < (((_h = config3.face.detector) == null ? void 0 : _h.minConfidence) || 1)) {
if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
box4.confidence = faceConfidence;
} else {
if ((_i = config3.face.iris) == null ? void 0 : _i.enabled)
if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
for (const key of Object.keys(meshAnnotations))
face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
if (((_j = config3.face.detector) == null ? void 0 : _j.rotation) && config3.face.mesh.enabled && ((_k = config3.face.description) == null ? void 0 : _k.enabled) && env.kernels.includes("rotatewithoffset")) {
if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env.kernels.includes("rotatewithoffset")) {
tf12.dispose(face5.tensor);
[angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
}
@ -5675,7 +5694,7 @@ async function predict6(input, config3) {
faces.push(face5);
newBoxes.push(box4);
}
if ((_l = config3.face.mesh) == null ? void 0 : _l.enabled)
if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
boxCache = newBoxes.filter((a) => {
var _a2;
return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@ -5706,7 +5725,8 @@ var uvmap = UV468;
// src/face/faceres.ts
var tf13 = __toModule(require_tfjs_esm());
var model9;
var last3 = [];
var last6 = [];
var lastTime4 = 0;
var lastCount3 = 0;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load9(config3) {
@ -5739,29 +5759,29 @@ function enhance(input) {
return image25;
}
async function predict7(image25, config3, idx, count2) {
var _a, _b, _c;
var _a, _b, _c, _d;
if (!model9)
return null;
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && lastCount3 === count2 && ((_b = last3[idx]) == null ? void 0 : _b.age) && ((_c = last3[idx]) == null ? void 0 : _c.age) > 0) {
if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
skipped8++;
return last3[idx];
return last6[idx];
}
skipped8 = 0;
return new Promise(async (resolve) => {
var _a2, _b2;
const enhanced = enhance(image25);
let resT;
const obj = {
age: 0,
gender: "unknown",
genderScore: 0,
descriptor: []
};
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled)
resT = await (model9 == null ? void 0 : model9.predict(enhanced));
tf13.dispose(enhanced);
if (resT) {
const gender = await resT.find((t) => t.shape[1] === 1).data();
if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
const enhanced = enhance(image25);
const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
lastTime4 = now();
tf13.dispose(enhanced);
const genderT = await resT.find((t) => t.shape[1] === 1);
const gender = await genderT.data();
const confidence = Math.trunc(200 * Math.abs(gender[0] - 0.5)) / 100;
if (confidence > (((_b2 = config3.face.description) == null ? void 0 : _b2.minConfidence) || 0)) {
obj.gender = gender[0] <= 0.5 ? "female" : "male";
@ -5770,14 +5790,15 @@ async function predict7(image25, config3, idx, count2) {
const argmax = tf13.argMax(resT.find((t) => t.shape[1] === 100), 1);
const age = (await argmax.data())[0];
tf13.dispose(argmax);
const all2 = await resT.find((t) => t.shape[1] === 100).data();
const ageT = resT.find((t) => t.shape[1] === 100);
const all2 = await ageT.data();
obj.age = Math.round(all2[age - 1] > all2[age + 1] ? 10 * age - 100 * all2[age - 1] : 10 * age + 100 * all2[age + 1]) / 10;
const desc = resT.find((t) => t.shape[1] === 1024);
const descriptor = await desc.data();
obj.descriptor = [...descriptor];
const descriptor = desc ? await desc.data() : [];
obj.descriptor = Array.from(descriptor);
resT.forEach((t) => tf13.dispose(t));
}
last3[idx] = obj;
last6[idx] = obj;
lastCount3 = count2;
resolve(obj);
});
@ -8932,6 +8953,7 @@ var handBoxEnlargeFactor = 1.65;
var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
var palmLandmarksPalmBase = 0;
var palmLandmarksMiddleFingerBase = 2;
var lastTime5 = 0;
var HandPipeline = class {
constructor(handDetector, handPoseModel2) {
__publicField(this, "handDetector");
@ -8996,7 +9018,7 @@ var HandPipeline = class {
async estimateHands(image25, config3) {
let useFreshBox = false;
let boxes;
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames || !config3.hand.landmarks || !config3.skipFrame) {
if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
boxes = await this.handDetector.estimateHandBounds(image25, config3);
this.skipped = 0;
}
@ -9025,6 +9047,7 @@ var HandPipeline = class {
tf16.dispose(croppedInput);
tf16.dispose(rotatedImage);
const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
lastTime5 = now();
tf16.dispose(handImage);
const confidence = (await confidenceT.data())[0];
tf16.dispose(confidenceT);
@ -9594,6 +9617,7 @@ var boxExpandFact = 1.6;
var maxDetectorResolution = 512;
var detectorExpandFact = 1.4;
var skipped9 = 0;
var lastTime6 = 0;
var outputSize = [0, 0];
var cache3 = {
boxes: [],
@ -9733,16 +9757,17 @@ async function predict9(input, config3) {
return [];
outputSize = [input.shape[2] || 0, input.shape[1] || 0];
skipped9++;
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0)) {
if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
return cache3.hands;
}
return new Promise(async (resolve) => {
if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && cache3.hands.length > 0) {
} else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
} else {
cache3.boxes = await detectHands(input, config3);
lastTime6 = now();
cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
skipped9 = 0;
}
@ -9933,7 +9958,8 @@ var inputSize7 = 0;
var skipped10 = Number.MAX_SAFE_INTEGER;
var cache5 = {
boxes: [],
bodies: []
bodies: [],
last: 0
};
async function load11(config3) {
if (env.initial)
@ -10043,7 +10069,7 @@ async function predict10(input, config3) {
if (!config3.skipFrame)
cache5.boxes.length = 0;
skipped10++;
if (config3.skipFrame && skipped10 <= (config3.body.skipFrames || 0)) {
if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
return cache5.bodies;
}
return new Promise(async (resolve) => {
@ -10051,6 +10077,7 @@ async function predict10(input, config3) {
skipped10 = 0;
t.input = padInput(input, inputSize7);
t.res = await (model10 == null ? void 0 : model10.predict(t.input));
cache5.last = now();
const res = await t.res.array();
cache5.bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input, [0, 0, 1, 1]);
for (const body4 of cache5.bodies) {
@ -10065,7 +10092,8 @@ async function predict10(input, config3) {
// src/object/nanodet.ts
var tf21 = __toModule(require_tfjs_esm());
var model11;
var last4 = [];
var last7 = [];
var lastTime7 = 0;
var skipped11 = Number.MAX_SAFE_INTEGER;
var scaleBox = 2.5;
async function load12(config3) {
@ -10145,13 +10173,13 @@ async function process4(res, inputSize8, outputShape, config3) {
return results;
}
async function predict11(image25, config3) {
if (skipped11 < (config3.object.skipFrames || 0) && config3.skipFrame && last4.length > 0) {
if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
skipped11++;
return last4;
return last7;
}
skipped11 = 0;
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last4;
return last7;
return new Promise(async (resolve) => {
const outputSize2 = [image25.shape[2], image25.shape[1]];
const resize = tf21.image.resizeBilinear(image25, [model11.inputSize, model11.inputSize], false);
@ -10162,9 +10190,10 @@ async function predict11(image25, config3) {
let objectT;
if (config3.object.enabled)
objectT = await model11.predict(transpose);
lastTime7 = now();
tf21.dispose(transpose);
const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
last4 = obj;
last7 = obj;
resolve(obj);
});
}

64326
dist/tfjs.esm.js vendored
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6
dist/tfjs.esm.js.map vendored
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6
src/body/blazepose.ts
View File

@ -3,7 +3,7 @@
*/
import * as tf from '../../dist/tfjs.esm.js';
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import type { BodyKeypoint, BodyResult, Box, Point } from '../result';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
@ -16,6 +16,7 @@ let skipped = Number.MAX_SAFE_INTEGER;
let outputNodes: string[]; // different for lite/full/heavy
let cache: BodyResult | null = null;
let padding: [number, number][] = [[0, 0], [0, 0], [0, 0], [0, 0]];
let last = 0;
export async function loadDetect(config: Config): Promise<GraphModel> {
if (env.initial) models[0] = null;
@ -135,10 +136,11 @@ async function detectParts(input: Tensor, config: Config, outputSize: [number, n
export async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {
const outputSize: [number, number] = [input.shape[2] || 0, input.shape[1] || 0];
if ((skipped < (config.body.skipFrames || 0)) && config.skipFrame && cache !== null) {
if ((skipped < (config.body.skipFrames || 0)) && ((config.body.skipTime || 0) <= (now() - last)) && config.skipFrame && cache !== null) {
skipped++;
} else {
cache = await detectParts(input, config, outputSize);
last = now();
skipped = 0;
}
if (cache) return [cache];

12
src/body/efficientpose.ts
View File

@ -4,7 +4,7 @@
* Based on: [**EfficientPose**](https://github.com/daniegr/EfficientPose)
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as coords from './efficientposecoords';
import type { BodyResult, Point } from '../result';
@ -13,7 +13,7 @@ import type { Config } from '../config';
import { env } from '../util/env';
let model: GraphModel | null;
let last = 0;
const cache: BodyResult = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
// const keypoints: Array<BodyKeypoint> = [];
@ -50,12 +50,7 @@ function max2d(inputs, minScore) {
}
export async function predict(image: Tensor, config: Config): Promise<BodyResult[]> {
/** blazepose caching
* not fully implemented
* 1. if skipFrame returned cached
* 2. run detection based on squared full frame
*/
if ((skipped < (config.body?.skipFrames || 0)) && config.skipFrame && Object.keys(cache.keypoints).length > 0) {
if ((skipped < (config.body?.skipFrames || 0)) && config.skipFrame && Object.keys(cache.keypoints).length > 0 && ((config.body.skipTime || 0) <= (now() - last))) {
skipped++;
return [cache];
}
@ -71,6 +66,7 @@ export async function predict(image: Tensor, config: Config): Promise<BodyResult
let resT;
if (config.body.enabled) resT = await model?.predict(tensor);
last = now();
tf.dispose(tensor);
if (resT) {

14
src/body/movenet.ts
View File

@ -4,7 +4,7 @@
* Based on: [**MoveNet**](https://blog.tensorflow.org/2021/05/next-generation-pose-detection-with-movenet-and-tensorflowjs.html)
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as box from '../util/box';
import * as tf from '../../dist/tfjs.esm.js';
import * as coords from './movenetcoords';
@ -23,9 +23,11 @@ let skipped = Number.MAX_SAFE_INTEGER;
const cache: {
boxes: Array<Box>, // unused
bodies: Array<BodyResult>;
last: number,
} = {
boxes: [],
bodies: [],
last: 0,
};
export async function load(config: Config): Promise<GraphModel> {
@ -129,17 +131,10 @@ async function parseMultiPose(res, config, image, inputBox) {
}
export async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {
/** movenet caching
* 1. if skipFrame returned cached
* 2. if enough cached boxes run using cached boxes
* 3. if not enough detected bodies rerun using full frame
* 4. regenerate cached boxes based on current keypoints
*/
if (!model || !model?.inputs[0].shape) return []; // something is wrong with the model
if (!config.skipFrame) cache.boxes.length = 0; // allowed to use cache or not
skipped++; // increment skip frames
if (config.skipFrame && (skipped <= (config.body.skipFrames || 0))) {
if (config.skipFrame && (skipped <= (config.body.skipFrames || 0) && ((config.body.skipTime || 0) <= (now() - cache.last)))) {
return cache.bodies; // return cached results without running anything
}
return new Promise(async (resolve) => {
@ -181,6 +176,7 @@ export async function predict(input: Tensor, config: Config): Promise<BodyResult
// run detection on squared input and no cached boxes
t.input = fix.padInput(input, inputSize);
t.res = await model?.predict(t.input) as Tensor;
cache.last = now();
const res = await t.res.array();
cache.bodies = (t.res.shape[2] === 17)
? await parseSinglePose(res, config, input, [0, 0, 1, 1])

73
src/config.ts
View File

@ -1,53 +1,42 @@
/* eslint-disable indent */
/* eslint-disable no-multi-spaces */
/** Dectector part of face configuration */
export interface FaceDetectorConfig {
export interface GenericConfig {
enabled: boolean,
modelPath: string,
skipFrames: number,
skipTime: number,
}
/** Dectector part of face configuration */
export interface FaceDetectorConfig extends GenericConfig {
rotation: boolean,
maxDetected: number,
skipFrames: number,
minConfidence: number,
iouThreshold: number,
return: boolean,
}
/** Mesh part of face configuration */
export interface FaceMeshConfig {
enabled: boolean,
modelPath: string,
}
export type FaceMeshConfig = GenericConfig
/** Iris part of face configuration */
export interface FaceIrisConfig {
enabled: boolean,
modelPath: string,
}
export type FaceIrisConfig = GenericConfig
/** Description or face embedding part of face configuration
* - also used by age and gender detection
*/
export interface FaceDescriptionConfig {
enabled: boolean,
modelPath: string,
skipFrames: number,
export interface FaceDescriptionConfig extends GenericConfig {
minConfidence: number,
}
/** Emotion part of face configuration */
export interface FaceEmotionConfig {
enabled: boolean,
export interface FaceEmotionConfig extends GenericConfig {
minConfidence: number,
skipFrames: number,
modelPath: string,
}
/** Emotion part of face configuration */
export interface FaceAntiSpoofConfig {
enabled: boolean,
skipFrames: number,
modelPath: string,
}
export type FaceAntiSpoofConfig = GenericConfig
/** Controlls and configures all face-specific options:
* - face detection, face mesh detection, age, gender, emotion detection and face description
@ -86,18 +75,15 @@ export interface FaceConfig {
* Changing `modelPath` will change module responsible for hand detection and tracking
* Allowed values are `posenet.json`, `blazepose.json`, `efficientpose.json`, `movenet-lightning.json`, `movenet-thunder.json`, `movenet-multipose.json`
*/
export interface BodyConfig {
enabled: boolean,
modelPath: string,
export interface BodyConfig extends GenericConfig {
maxDetected: number,
minConfidence: number,
skipFrames: number,
detector?: {
modelPath: string
},
}
/** Controlls and configures all hand detection specific options
/** Controls and configures all hand detection specific options
*
* Parameters:
* - enabled: true/false
@ -113,10 +99,8 @@ export interface BodyConfig {
* Changing `detector.modelPath` will change module responsible for hand detection and tracking
* Allowed values are `handdetect.json` and `handtrack.json`
*/
export interface HandConfig {
enabled: boolean,
export interface HandConfig extends GenericConfig {
rotation: boolean,
skipFrames: number,
minConfidence: number,
iouThreshold: number,
maxDetected: number,
@ -139,13 +123,10 @@ export interface HandConfig {
* Changing `modelPath` will change module responsible for hand detection and tracking
* Allowed values are `mb3-centernet.json` and `nanodet.json`
*/
export interface ObjectConfig {
enabled: boolean,
modelPath: string,
export interface ObjectConfig extends GenericConfig {
minConfidence: number,
iouThreshold: number,
maxDetected: number,
skipFrames: number,
}
/** Controlls and configures all body segmentation module
@ -368,9 +349,8 @@ const config: Config = {
// should be set to the minimum number for performance
skipFrames: 11, // how many max frames to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
// e.g., if model is running st 25 FPS, we can re-use existing bounding
// box for updated face analysis as the head does not move fast
// in short time (10 * 1/25 = 0.25 sec)
skipTime: 2000, // how many ms to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
minConfidence: 0.2, // threshold for discarding a prediction
iouThreshold: 0.1, // ammount of overlap between two detected objects before one object is removed
return: false, // return extracted face as tensor
@ -393,6 +373,8 @@ const config: Config = {
minConfidence: 0.1, // threshold for discarding a prediction
skipFrames: 12, // how max many frames to go without re-running the detector
// only used when cacheSensitivity is not zero
skipTime: 2000, // how many ms to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
modelPath: 'emotion.json', // face emotion model, can be absolute path or relative to modelBasePath
},
@ -403,6 +385,8 @@ const config: Config = {
// can be either absolute path or relative to modelBasePath
skipFrames: 13, // how many max frames to go without re-running the detector
// only used when cacheSensitivity is not zero
skipTime: 2000, // how many ms to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
minConfidence: 0.1, // threshold for discarding a prediction
},
@ -410,6 +394,8 @@ const config: Config = {
enabled: false,
skipFrames: 14, // how max many frames to go without re-running the detector
// only used when cacheSensitivity is not zero
skipTime: 2000, // how many ms to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
modelPath: 'antispoof.json', // face description model
// can be either absolute path or relative to modelBasePath
},
@ -429,6 +415,8 @@ const config: Config = {
minConfidence: 0.3, // threshold for discarding a prediction
skipFrames: 1, // how many max frames to go without re-running the detector
// only used when cacheSensitivity is not zero
skipTime: 2000, // how many ms to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
},
hand: {
@ -438,9 +426,8 @@ const config: Config = {
// only valid for `handdetect` variation
skipFrames: 2, // how many max frames to go without re-running the hand bounding box detector
// only used when cacheSensitivity is not zero
// e.g., if model is running st 25 FPS, we can re-use existing bounding
// box for updated hand skeleton analysis as the hand
// hasn't moved much in short time (10 * 1/25 = 0.25 sec)
skipTime: 2000, // how many ms to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
minConfidence: 0.50, // threshold for discarding a prediction
iouThreshold: 0.2, // ammount of overlap between two detected objects before one object is removed
maxDetected: -1, // maximum number of hands detected in the input
@ -465,6 +452,8 @@ const config: Config = {
maxDetected: 10, // maximum number of objects detected in the input
skipFrames: 15, // how many max frames to go without re-running the detector
// only used when cacheSensitivity is not zero
skipTime: 2000, // how many ms to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
},
segmentation: {

6
src/face/antispoof.ts
View File

@ -2,7 +2,7 @@
* Anti-spoofing model implementation
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import type { Config } from '../config';
import type { GraphModel, Tensor } from '../tfjs/types';
import * as tf from '../../dist/tfjs.esm.js';
@ -12,6 +12,7 @@ let model: GraphModel | null;
const cached: Array<number> = [];
let skipped = Number.MAX_SAFE_INTEGER;
let lastCount = 0;
let last = 0;
export async function load(config: Config): Promise<GraphModel> {
if (env.initial) model = null;
@ -25,7 +26,7 @@ export async function load(config: Config): Promise<GraphModel> {
export async function predict(image: Tensor, config: Config, idx, count) {
if (!model) return null;
if ((skipped < (config.face.antispoof?.skipFrames || 0)) && config.skipFrame && (lastCount === count) && cached[idx]) {
if ((skipped < (config.face.antispoof?.skipFrames || 0)) && ((config.face.antispoof?.skipTime || 0) <= (now() - last)) && config.skipFrame && (lastCount === count) && cached[idx]) {
skipped++;
return cached[idx];
}
@ -36,6 +37,7 @@ export async function predict(image: Tensor, config: Config, idx, count) {
const num = (await res.data())[0];
cached[idx] = Math.round(100 * num) / 100;
lastCount = count;
last = now();
tf.dispose([resize, res]);
resolve(cached[idx]);
});

16
src/face/embedding.ts
View File

@ -112,19 +112,3 @@ export async function predict(input, config): Promise<number[]> {
resolve(data);
});
}
/*
git clone https://github.com/becauseofAI/MobileFace
cd MobileFace/MobileFace_Identification
mmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved
saved_model_cli show --dir saved/
tensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/
~/dev/detector/signature.js graph/
2021-03-12 08:25:12 DATA: created on: 2021-03-12T13:17:11.960Z
2021-03-12 08:25:12 INFO: graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json
2021-03-12 08:25:12 INFO: size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }
2021-03-12 08:25:12 INFO: model inputs based on signature
2021-03-12 08:25:12 INFO: model outputs based on signature
2021-03-12 08:25:12 DATA: inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]
2021-03-12 08:25:12 DATA: outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]
*/

7
src/face/facemesh.ts
View File

@ -7,7 +7,7 @@
* - Eye Iris Details: [**MediaPipe Iris**](https://drive.google.com/file/d/1bsWbokp9AklH2ANjCfmjqEzzxO1CNbMu/view)
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as blazeface from './blazeface';
import * as util from './facemeshutil';
@ -23,11 +23,14 @@ let boxCache: Array<BoxCache> = [];
let model: GraphModel | null = null;
let inputSize = 0;
let skipped = Number.MAX_SAFE_INTEGER;
let lastTime = 0;
let detectedFaces = 0;
export async function predict(input: Tensor, config: Config): Promise<FaceResult[]> {
if (!config.skipFrame || (((detectedFaces !== config.face.detector?.maxDetected) || !config.face.mesh?.enabled)) && (skipped > (config.face.detector?.skipFrames || 0))) { // reset cached boxes
// reset cached boxes
if (!config.skipFrame || (((detectedFaces !== config.face.detector?.maxDetected) || !config.face.mesh?.enabled)) && (skipped > (config.face.detector?.skipFrames || 0) && ((config.face.description?.skipTime || 0) <= (now() - lastTime)))) {
const newBoxes = await blazeface.getBoxes(input, config); // get results from blazeface detector
lastTime = now();
boxCache = []; // empty cache
for (const possible of newBoxes.boxes) { // extract data from detector
const startPoint = await possible.box.startPoint.data() as unknown as Point;

29
src/face/faceres.ts
View File

@ -7,7 +7,7 @@
* Based on: [**HSE-FaceRes**](https://github.com/HSE-asavchenko/HSE_FaceRec_tf)
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import type { Tensor, GraphModel } from '../tfjs/types';
import type { Config } from '../config';
@ -21,6 +21,7 @@ const last: Array<{
descriptor: number[],
}> = [];
let lastTime = 0;
let lastCount = 0;
let skipped = Number.MAX_SAFE_INTEGER;
@ -90,15 +91,12 @@ export function enhance(input): Tensor {
export async function predict(image: Tensor, config: Config, idx, count) {
if (!model) return null;
if ((skipped < (config.face.description?.skipFrames || 0)) && config.skipFrame && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {
if ((skipped < (config.face.description?.skipFrames || 0)) && ((config.face.description?.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {
skipped++;
return last[idx];
}
skipped = 0;
return new Promise(async (resolve) => {
const enhanced = enhance(image);
let resT;
const obj = {
age: <number>0,
gender: <string>'unknown',
@ -106,11 +104,13 @@ export async function predict(image: Tensor, config: Config, idx, count) {
descriptor: <number[]>[],
};
if (config.face.description?.enabled) resT = await model?.predict(enhanced);
tf.dispose(enhanced);
if (resT) {
const gender = await resT.find((t) => t.shape[1] === 1).data();
if (config.face.description?.enabled) {
const enhanced = enhance(image);
const resT = await model?.predict(enhanced) as Tensor[];
lastTime = now();
tf.dispose(enhanced);
const genderT = await resT.find((t) => t.shape[1] === 1) as Tensor;
const gender = await genderT.data();
const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;
if (confidence > (config.face.description?.minConfidence || 0)) {
obj.gender = gender[0] <= 0.5 ? 'female' : 'male';
@ -119,15 +119,16 @@ export async function predict(image: Tensor, config: Config, idx, count) {
const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100), 1);
const age = (await argmax.data())[0];
tf.dispose(argmax);
const all = await resT.find((t) => t.shape[1] === 100).data();
const ageT = resT.find((t) => t.shape[1] === 100) as Tensor;
const all = await ageT.data();
obj.age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;
const desc = resT.find((t) => t.shape[1] === 1024);
// const reshape = desc.reshape([128, 8]); // reshape large 1024-element descriptor to 128 x 8
// const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it which leaves us with 128-element descriptor
const descriptor = await desc.data();
obj.descriptor = [...descriptor];
const descriptor = desc ? await desc.data() : <number[]>[];
// obj.descriptor = [...descriptor];
obj.descriptor = Array.from(descriptor);
resT.forEach((t) => tf.dispose(t));
}
last[idx] = obj;

40
src/gear/emotion.ts
View File

@ -4,7 +4,7 @@
* [**Oarriaga**](https://github.com/oarriaga/face_classification)
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import type { Config } from '../config';
import type { GraphModel, Tensor } from '../tfjs/types';
import * as tf from '../../dist/tfjs.esm.js';
@ -15,6 +15,7 @@ let model: GraphModel | null;
// let last: Array<{ score: number, emotion: string }> = [];
const last: Array<Array<{ score: number, emotion: string }>> = [];
let lastCount = 0;
let lastTime = 0;
let skipped = Number.MAX_SAFE_INTEGER;
// tuning values
@ -32,39 +33,40 @@ export async function load(config: Config): Promise<GraphModel> {
export async function predict(image: Tensor, config: Config, idx, count) {
if (!model) return null;
if ((skipped < (config.face.emotion?.skipFrames || 0)) && config.skipFrame && (lastCount === count) && last[idx] && (last[idx].length > 0)) {
if ((skipped < (config.face.emotion?.skipFrames || 0)) && ((config.face.emotion?.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && (lastCount === count) && last[idx] && (last[idx].length > 0)) {
skipped++;
return last[idx];
}
skipped = 0;
return new Promise(async (resolve) => {
const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tf.split(resize, 3, 3);
tf.dispose(resize);
// weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html
const redNorm = tf.mul(red, rgb[0]);
const greenNorm = tf.mul(green, rgb[1]);
const blueNorm = tf.mul(blue, rgb[2]);
tf.dispose(red);
tf.dispose(green);
tf.dispose(blue);
const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);
tf.dispose(redNorm);
tf.dispose(greenNorm);
tf.dispose(blueNorm);
const normalize = tf.tidy(() => tf.mul(tf.sub(grayscale, 0.5), 2));
tf.dispose(grayscale);
const obj: Array<{ score: number, emotion: string }> = [];
if (config.face.emotion?.enabled) {
const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);
const [red, green, blue] = tf.split(resize, 3, 3);
tf.dispose(resize);
// weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html
const redNorm = tf.mul(red, rgb[0]);
const greenNorm = tf.mul(green, rgb[1]);
const blueNorm = tf.mul(blue, rgb[2]);
tf.dispose(red);
tf.dispose(green);
tf.dispose(blue);
const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);
tf.dispose(redNorm);
tf.dispose(greenNorm);
tf.dispose(blueNorm);
const normalize = tf.tidy(() => tf.mul(tf.sub(grayscale, 0.5), 2));
tf.dispose(grayscale);
const emotionT = await model?.predict(normalize) as Tensor; // result is already in range 0..1, no need for additional activation
lastTime = now();
const data = await emotionT.data();
tf.dispose(emotionT);
for (let i = 0; i < data.length; i++) {
if (data[i] > (config.face.emotion?.minConfidence || 0)) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });
}
obj.sort((a, b) => b.score - a.score);
tf.dispose(normalize);
}
tf.dispose(normalize);
last[idx] = obj;
lastCount = count;
resolve(obj);

6
src/gear/gear-agegenderrace.ts
View File

@ -7,7 +7,7 @@
* Config placeholder: agegenderrace: { enabled: true, modelPath: 'gear.json' },
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import type { Config } from '../config';
import type { GraphModel, Tensor } from '../tfjs/types';
@ -16,6 +16,7 @@ import { env } from '../util/env';
let model: GraphModel | null;
let last = { age: 0 };
let lastTime = 0;
let skipped = Number.MAX_SAFE_INTEGER;
// eslint-disable-next-line @typescript-eslint/no-explicit-any
@ -33,7 +34,7 @@ export async function load(config: Config | any) {
export async function predict(image: Tensor, config: Config) {
if (!model) return null;
// @ts-ignore config disabled
if ((skipped < config.face.agegenderrace.skipFrames) && config.skipFrame && last.age && (last.age > 0)) {
if ((skipped < config.face.agegenderrace?.skipFrames) && ((config.face.agegenderrace?.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && last.age && (last.age > 0)) {
skipped++;
return last;
}
@ -50,6 +51,7 @@ export async function predict(image: Tensor, config: Config) {
// @ts-ignore array definition unavailable at compile time
if (config.face.agegenderrace.enabled) [ageT, genderT, raceT] = await model.execute(resize, ['age_output', 'gender_output', 'race_output']);
lastTime = now();
tf.dispose(resize);
// tf.dispose(enhance);

7
src/gear/ssrnet-age.ts
View File

@ -6,15 +6,15 @@
* Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import type { Config } from '../config';
import type { GraphModel, Tensor } from '../tfjs/types';
import { env } from '../util/env';
let model: GraphModel | null;
let last = { age: 0 };
let lastTime = 0;
let skipped = Number.MAX_SAFE_INTEGER;
// eslint-disable-next-line @typescript-eslint/no-explicit-any
@ -33,7 +33,7 @@ export async function load(config: Config | any) {
// eslint-disable-next-line @typescript-eslint/no-explicit-any
export async function predict(image: Tensor, config: Config | any) {
if (!model) return null;
if ((skipped < config.face.age.skipFrames) && config.skipFrame && last.age && (last.age > 0)) {
if ((skipped < config.face.age.skipFrames) && ((config.face.age.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && last.age && (last.age > 0)) {
skipped++;
return last;
}
@ -48,6 +48,7 @@ export async function predict(image: Tensor, config: Config | any) {
const obj = { age: 0 };
if (config.face.age.enabled) ageT = await model.predict(enhance);
lastTime = now();
tf.dispose(enhance);
if (ageT) {

6
src/gear/ssrnet-gender.ts
View File

@ -6,7 +6,7 @@
* Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import type { Config } from '../config';
import type { GraphModel, Tensor } from '../tfjs/types';
@ -14,6 +14,7 @@ import { env } from '../util/env';
let model: GraphModel | null;
let last = { gender: '' };
let lastTime = 0;
let skipped = Number.MAX_SAFE_INTEGER;
let alternative = false;
@ -35,7 +36,7 @@ export async function load(config: Config | any) {
// eslint-disable-next-line @typescript-eslint/no-explicit-any
export async function predict(image: Tensor, config: Config | any) {
if (!model) return null;
if ((skipped < config.face.gender.skipFrames) && config.skipFrame && last.gender !== '') {
if ((skipped < config.face.gender.skipFrames) && ((config.face.gender.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && last.gender !== '') {
skipped++;
return last;
}
@ -63,6 +64,7 @@ export async function predict(image: Tensor, config: Config | any) {
const obj = { gender: '', confidence: 0 };
if (config.face.gender.enabled) genderT = await model.predict(enhance);
lastTime = now();
tf.dispose(enhance);
if (genderT) {

5
src/hand/handposepipeline.ts
View File

@ -8,12 +8,14 @@ import * as util from './handposeutil';
import type * as detector from './handposedetector';
import type { Tensor, GraphModel } from '../tfjs/types';
import { env } from '../util/env';
import { now } from '../util/util';
const palmBoxEnlargeFactor = 5; // default 3
const handBoxEnlargeFactor = 1.65; // default 1.65
const palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
const palmLandmarksPalmBase = 0;
const palmLandmarksMiddleFingerBase = 2;
let lastTime = 0;
export class HandPipeline {
handDetector: detector.HandDetector;
@ -90,7 +92,7 @@ export class HandPipeline {
let boxes;
// console.log('handpipeline:estimateHands:skip criteria', this.skipped, config.hand.skipFrames, !config.hand.landmarks, !config.skipFrame); // should skip hand detector?
if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.skipFrame) {
if ((this.skipped === 0) || ((this.skipped > config.hand.skipFrames) && ((config.hand.skipTime || 0) <= (now() - lastTime))) || !config.hand.landmarks || !config.skipFrame) {
boxes = await this.handDetector.estimateHandBounds(image, config);
this.skipped = 0;
}
@ -121,6 +123,7 @@ export class HandPipeline {
tf.dispose(croppedInput);
tf.dispose(rotatedImage);
const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage) as Array<Tensor>;
lastTime = now();
tf.dispose(handImage);
const confidence = (await confidenceT.data())[0];
tf.dispose(confidenceT);

10
src/hand/handtrack.ts
View File

@ -6,7 +6,7 @@
* - Hand Tracking: [**HandTracking**](https://github.com/victordibia/handtracking)
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as box from '../util/box';
import * as tf from '../../dist/tfjs.esm.js';
import type { HandResult, Box, Point } from '../result';
@ -29,6 +29,7 @@ const maxDetectorResolution = 512;
const detectorExpandFact = 1.4;
let skipped = 0;
let lastTime = 0;
let outputSize: [number, number] = [0, 0];
type HandDetectResult = {
@ -184,7 +185,7 @@ async function detectFingers(input: Tensor, h: HandDetectResult, config: Config)
export async function predict(input: Tensor, config: Config): Promise<HandResult[]> {
/** handtrack caching
* 1. if skipFrame returned cached
* 2. if any cached results but although not sure if its enough we continute anyhow for 5x skipframes
* 2. if any cached results but although not sure if its enough we continute anyhow for 3x skipframes
* 3. if not skipframe or eventually rerun detector to generated new cached boxes and reset skipped
* 4. generate cached boxes based on detected keypoints
*/
@ -192,16 +193,17 @@ export async function predict(input: Tensor, config: Config): Promise<HandResult
outputSize = [input.shape[2] || 0, input.shape[1] || 0];
skipped++; // increment skip frames
if (config.skipFrame && (skipped <= (config.hand.skipFrames || 0))) {
if (config.skipFrame && (skipped <= (config.hand.skipFrames || 0)) && ((config.hand.skipTime || 0) <= (now() - lastTime))) {
return cache.hands; // return cached results without running anything
}
return new Promise(async (resolve) => {
if (config.skipFrame && cache.hands.length === config.hand.maxDetected) { // we have all detected hands
cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));
} else if (config.skipFrame && skipped < 3 * (config.hand.skipFrames || 0) && cache.hands.length > 0) { // we have some cached results but although not sure if its enough we continute anyhow for bit longer
} else if (config.skipFrame && skipped < 3 * (config.hand.skipFrames || 0) && ((config.hand.skipTime || 0) <= 3 * (now() - lastTime)) && cache.hands.length > 0) { // we have some cached results: maybe not enough but anyhow continue for bit longer
cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));
} else { // finally rerun detector
cache.boxes = await detectHands(input, config);
lastTime = now();
cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));
skipped = 0;
}

6
src/object/centernet.ts
View File

@ -4,7 +4,7 @@
* Based on: [**NanoDet**](https://github.com/RangiLyu/nanodet)
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import { labels } from './labels';
import type { ObjectResult, Box } from '../result';
@ -16,6 +16,7 @@ import { fakeOps } from '../tfjs/backend';
let model: GraphModel | null;
let inputSize = 0;
let last: ObjectResult[] = [];
let lastTime = 0;
let skipped = Number.MAX_SAFE_INTEGER;
export async function load(config: Config): Promise<GraphModel> {
@ -78,7 +79,7 @@ async function process(res: Tensor | null, outputShape, config: Config) {
}
export async function predict(input: Tensor, config: Config): Promise<ObjectResult[]> {
if ((skipped < (config.object.skipFrames || 0)) && config.skipFrame && (last.length > 0)) {
if ((skipped < (config.object.skipFrames || 0)) && ((config.object.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && (last.length > 0)) {
skipped++;
return last;
}
@ -88,6 +89,7 @@ export async function predict(input: Tensor, config: Config): Promise<ObjectResu
const outputSize = [input.shape[2], input.shape[1]];
const resize = tf.image.resizeBilinear(input, [inputSize, inputSize]);
const objectT = config.object.enabled ? model?.execute(resize, ['tower_0/detections']) as Tensor : null;
lastTime = now();
tf.dispose(resize);
const obj = await process(objectT, outputSize, config);

6
src/object/nanodet.ts
View File

@ -4,7 +4,7 @@
* Based on: [**MB3-CenterNet**](https://github.com/610265158/mobilenetv3_centernet)
*/
import { log, join } from '../util/util';
import { log, join, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import { labels } from './labels';
import type { ObjectResult, Box } from '../result';
@ -14,6 +14,7 @@ import { env } from '../util/env';
let model;
let last: Array<ObjectResult> = [];
let lastTime = 0;
let skipped = Number.MAX_SAFE_INTEGER;
const scaleBox = 2.5; // increase box size
@ -106,7 +107,7 @@ async function process(res, inputSize, outputShape, config) {
}
export async function predict(image: Tensor, config: Config): Promise<ObjectResult[]> {
if ((skipped < (config.object.skipFrames || 0)) && config.skipFrame && (last.length > 0)) {
if ((skipped < (config.object.skipFrames || 0)) && ((config.object.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && (last.length > 0)) {
skipped++;
return last;
}
@ -122,6 +123,7 @@ export async function predict(image: Tensor, config: Config): Promise<ObjectResu
let objectT;
if (config.object.enabled) objectT = await model.predict(transpose);
lastTime = now();
tf.dispose(transpose);
const obj = await process(objectT, model.inputSize, outputSize, config);

52
test/build.log
View File

@ -1,26 +1,26 @@
2021-10-22 13:34:33 INFO:  @vladmandic/human version 2.4.0
2021-10-22 13:34:33 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.10.0
2021-10-22 13:34:33 INFO:  Application: {"name":"@vladmandic/human","version":"2.4.0"}
2021-10-22 13:34:33 INFO:  Environment: {"profile":"production","config":"build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true}
2021-10-22 13:34:33 INFO:  Toolchain: {"build":"0.6.2","esbuild":"0.13.8","typescript":"4.4.4","typedoc":"0.22.6","eslint":"8.0.1"}
2021-10-22 13:34:33 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]}
2021-10-22 13:34:33 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]}
2021-10-22 13:34:33 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":1275}
2021-10-22 13:34:33 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":54,"inputBytes":523578,"outputBytes":436010}
2021-10-22 13:34:33 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1283}
2021-10-22 13:34:33 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":54,"inputBytes":523586,"outputBytes":436014}
2021-10-22 13:34:33 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":1350}
2021-10-22 13:34:33 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":54,"inputBytes":523653,"outputBytes":436086}
2021-10-22 13:34:33 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":1652}
2021-10-22 13:34:33 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2365,"outputBytes":1030}
2021-10-22 13:34:33 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":54,"inputBytes":523333,"outputBytes":437997}
2021-10-22 13:34:33 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2572202,"outputBytes":2491625}
2021-10-22 13:34:34 STATE: Compile: {"name":"human/browser/esm/custom","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.custom.esm.js","files":54,"inputBytes":3013928,"outputBytes":2933042}
2021-10-22 13:34:35 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":2365,"outputBytes":2411315}
2021-10-22 13:34:35 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":54,"inputBytes":2933618,"outputBytes":1431470}
2021-10-22 13:34:36 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":54,"inputBytes":2933618,"outputBytes":2674673}
2021-10-22 13:34:56 STATE: Typings: {"input":"src/human.ts","output":"types","files":16}
2021-10-22 13:35:03 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":36,"generated":true}
2021-10-22 13:35:46 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":90,"errors":0,"warnings":0}
2021-10-22 13:35:46 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"}
2021-10-22 13:35:46 INFO:  Done...
2021-10-22 16:05:08 INFO:  @vladmandic/human version 2.4.0
2021-10-22 16:05:08 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.10.0
2021-10-22 16:05:08 INFO:  Application: {"name":"@vladmandic/human","version":"2.4.0"}
2021-10-22 16:05:08 INFO:  Environment: {"profile":"production","config":"build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true}
2021-10-22 16:05:08 INFO:  Toolchain: {"build":"0.6.2","esbuild":"0.13.8","typescript":"4.4.4","typedoc":"0.22.6","eslint":"8.0.1"}
2021-10-22 16:05:08 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]}
2021-10-22 16:05:08 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]}
2021-10-22 16:05:08 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":1275}
2021-10-22 16:05:08 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":54,"inputBytes":525194,"outputBytes":437512}
2021-10-22 16:05:08 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1283}
2021-10-22 16:05:08 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":54,"inputBytes":525202,"outputBytes":437516}
2021-10-22 16:05:08 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":1350}
2021-10-22 16:05:08 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":54,"inputBytes":525269,"outputBytes":437588}
2021-10-22 16:05:08 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":1652}
2021-10-22 16:05:08 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2323,"outputBytes":973}
2021-10-22 16:05:08 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":54,"inputBytes":524892,"outputBytes":439413}
2021-10-22 16:05:09 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2572202,"outputBytes":2491625}
2021-10-22 16:05:10 STATE: Compile: {"name":"human/browser/esm/custom","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.custom.esm.js","files":54,"inputBytes":3015544,"outputBytes":2934547}
2021-10-22 16:05:10 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":2323,"outputBytes":1155160}
2021-10-22 16:05:11 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":54,"inputBytes":1679079,"outputBytes":1430229}
2021-10-22 16:05:11 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":54,"inputBytes":1679079,"outputBytes":1878008}
2021-10-22 16:05:29 STATE: Typings: {"input":"src/human.ts","output":"types","files":16}
2021-10-22 16:05:36 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":37,"generated":true}
2021-10-22 16:06:18 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":90,"errors":0,"warnings":0}
2021-10-22 16:06:19 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"}
2021-10-22 16:06:19 INFO:  Done...

1018
test/test.log
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typedoc/assets/search.js
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typedoc/index.html
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typedoc/interfaces/Config.html
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@ -1,9 +1,9 @@
<!DOCTYPE html><html class="default no-js"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>Config | @vladmandic/human - v2.4.0</title><meta name="description" content="Documentation for @vladmandic/human - v2.4.0"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script async src="../assets/search.js" id="search-script"></script></head><body><script>document.body.classList.add(localStorage.getItem(&quot;tsd-theme&quot;) || &quot;os&quot;)</script><header><div class="tsd-page-toolbar"><div class="container"><div class="table-wrap"><div class="table-cell" id="tsd-search" data-base=".."><div class="field"><label for="tsd-search-field" class="tsd-widget search no-caption">Search</label><input type="text" id="tsd-search-field"/></div><ul class="results"><li class="state loading">Preparing search index...</li><li class="state failure">The search index is not available</li></ul><a href="../index.html" class="title">@vladmandic/human - v2.4.0</a></div><div class="table-cell" id="tsd-widgets"><div id="tsd-filter"><a href="#" class="tsd-widget options no-caption" data-toggle="options">Options</a><div class="tsd-filter-group"><div class="tsd-select" id="tsd-filter-visibility"><span class="tsd-select-label">All</span><ul class="tsd-select-list"><li data-value="public">Public</li><li data-value="protected">Public/Protected</li><li data-value="private" class="selected">All</li></ul></div> <input type="checkbox" id="tsd-filter-inherited" checked/><label class="tsd-widget" for="tsd-filter-inherited">Inherited</label></div></div><a href="#" class="tsd-widget menu no-caption" data-toggle="menu">Menu</a></div></div></div></div><div class="tsd-page-title"><div class="container"><ul class="tsd-breadcrumb"><li><a href="../index.html">@vladmandic/human - v2.4.0</a></li><li><a href="Config.html">Config</a></li></ul><h1>Interface Config</h1></div></div></header><div class="container container-main"><div class="row"><div class="col-8 col-content"><section class="tsd-panel tsd-comment"><div class="tsd-comment tsd-typography"><div class="lead">
<p>Configuration interface definition for <strong>Human</strong> library</p>
</div><div><p>Contains all configurable parameters</p>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">Config</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#async" class="tsd-kind-icon">async</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#backend" class="tsd-kind-icon">backend</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#body" class="tsd-kind-icon">body</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#cacheSensitivity" class="tsd-kind-icon">cache<wbr/>Sensitivity</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#debug" class="tsd-kind-icon">debug</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#face" class="tsd-kind-icon">face</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#filter" class="tsd-kind-icon">filter</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#gesture" class="tsd-kind-icon">gesture</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#hand" class="tsd-kind-icon">hand</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#modelBasePath" class="tsd-kind-icon">model<wbr/>Base<wbr/>Path</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#object" class="tsd-kind-icon">object</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#segmentation" class="tsd-kind-icon">segmentation</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#skipFrame" class="tsd-kind-icon">skip<wbr/>Frame</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#warmup" class="tsd-kind-icon">warmup</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#wasmPath" class="tsd-kind-icon">wasm<wbr/>Path</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="async" class="tsd-anchor"></a><h3>async</h3><div class="tsd-signature tsd-kind-icon">async<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L257">config.ts:257</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">Config</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#async" class="tsd-kind-icon">async</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#backend" class="tsd-kind-icon">backend</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#body" class="tsd-kind-icon">body</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#cacheSensitivity" class="tsd-kind-icon">cache<wbr/>Sensitivity</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#debug" class="tsd-kind-icon">debug</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#face" class="tsd-kind-icon">face</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#filter" class="tsd-kind-icon">filter</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#gesture" class="tsd-kind-icon">gesture</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#hand" class="tsd-kind-icon">hand</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#modelBasePath" class="tsd-kind-icon">model<wbr/>Base<wbr/>Path</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#object" class="tsd-kind-icon">object</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#segmentation" class="tsd-kind-icon">segmentation</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#skipFrame" class="tsd-kind-icon">skip<wbr/>Frame</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#warmup" class="tsd-kind-icon">warmup</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#wasmPath" class="tsd-kind-icon">wasm<wbr/>Path</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="async" class="tsd-anchor"></a><h3>async</h3><div class="tsd-signature tsd-kind-icon">async<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L238">config.ts:238</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Perform model loading and inference concurrently or sequentially</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="backend" class="tsd-anchor"></a><h3>backend</h3><div class="tsd-signature tsd-kind-icon">backend<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">&quot;&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;cpu&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;wasm&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;webgl&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;humangl&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;tensorflow&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;webgpu&quot;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L245">config.ts:245</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="backend" class="tsd-anchor"></a><h3>backend</h3><div class="tsd-signature tsd-kind-icon">backend<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">&quot;&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;cpu&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;wasm&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;webgl&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;humangl&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;tensorflow&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;webgpu&quot;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L226">config.ts:226</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Backend used for TFJS operations
Valid build-in backends are:</p>
<ul>
@ -15,45 +15,45 @@ Valid build-in backends are:</p>
<li>Browser: <code>webgpu</code> - requires custom build of <code>tfjs-backend-webgpu</code></li>
</ul>
<p>Defaults: <code>humangl</code> for browser and <code>tensorflow</code> for nodejs</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="body" class="tsd-anchor"></a><h3>body</h3><div class="tsd-signature tsd-kind-icon">body<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="BodyConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">BodyConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L293">config.ts:293</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="body" class="tsd-anchor"></a><h3>body</h3><div class="tsd-signature tsd-kind-icon">body<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="BodyConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">BodyConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L274">config.ts:274</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p><a href="BodyConfig.html">BodyConfig</a></p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="cacheSensitivity" class="tsd-anchor"></a><h3>cache<wbr/>Sensitivity</h3><div class="tsd-signature tsd-kind-icon">cache<wbr/>Sensitivity<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L274">config.ts:274</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="cacheSensitivity" class="tsd-anchor"></a><h3>cache<wbr/>Sensitivity</h3><div class="tsd-signature tsd-kind-icon">cache<wbr/>Sensitivity<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L255">config.ts:255</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Cache sensitivity</p>
<ul>
<li>values 0..1 where 0.01 means reset cache if input changed more than 1%</li>
<li>set to 0 to disable caching</li>
</ul>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="debug" class="tsd-anchor"></a><h3>debug</h3><div class="tsd-signature tsd-kind-icon">debug<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L254">config.ts:254</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="debug" class="tsd-anchor"></a><h3>debug</h3><div class="tsd-signature tsd-kind-icon">debug<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L235">config.ts:235</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Print debug statements to console</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="face" class="tsd-anchor"></a><h3>face</h3><div class="tsd-signature tsd-kind-icon">face<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="FaceConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">FaceConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L290">config.ts:290</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="face" class="tsd-anchor"></a><h3>face</h3><div class="tsd-signature tsd-kind-icon">face<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="FaceConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">FaceConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L271">config.ts:271</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p><a href="FaceConfig.html">FaceConfig</a></p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="filter" class="tsd-anchor"></a><h3>filter</h3><div class="tsd-signature tsd-kind-icon">filter<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="FilterConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">FilterConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L284">config.ts:284</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="filter" class="tsd-anchor"></a><h3>filter</h3><div class="tsd-signature tsd-kind-icon">filter<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="FilterConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">FilterConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L265">config.ts:265</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Run input through image filters before inference</p>
<ul>
<li>image filters run with near-zero latency as they are executed on the GPU</li>
</ul>
</div><div><p><a href="FilterConfig.html">FilterConfig</a></p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="gesture" class="tsd-anchor"></a><h3>gesture</h3><div class="tsd-signature tsd-kind-icon">gesture<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="GestureConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">GestureConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L287">config.ts:287</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="gesture" class="tsd-anchor"></a><h3>gesture</h3><div class="tsd-signature tsd-kind-icon">gesture<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="GestureConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">GestureConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L268">config.ts:268</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p><a href="GestureConfig.html">GestureConfig</a></p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="hand" class="tsd-anchor"></a><h3>hand</h3><div class="tsd-signature tsd-kind-icon">hand<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="HandConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">HandConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L296">config.ts:296</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="hand" class="tsd-anchor"></a><h3>hand</h3><div class="tsd-signature tsd-kind-icon">hand<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="HandConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">HandConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L277">config.ts:277</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p><a href="HandConfig.html">HandConfig</a></p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="modelBasePath" class="tsd-anchor"></a><h3>model<wbr/>Base<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">model<wbr/>Base<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L268">config.ts:268</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="modelBasePath" class="tsd-anchor"></a><h3>model<wbr/>Base<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">model<wbr/>Base<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L249">config.ts:249</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Base model path (typically starting with file://, http:// or https://) for all models</p>
<ul>
<li>individual modelPath values are relative to this path</li>
</ul>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="object" class="tsd-anchor"></a><h3>object</h3><div class="tsd-signature tsd-kind-icon">object<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="ObjectConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">ObjectConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L299">config.ts:299</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="object" class="tsd-anchor"></a><h3>object</h3><div class="tsd-signature tsd-kind-icon">object<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="ObjectConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">ObjectConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L280">config.ts:280</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p><a href="ObjectConfig.html">ObjectConfig</a></p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="segmentation" class="tsd-anchor"></a><h3>segmentation</h3><div class="tsd-signature tsd-kind-icon">segmentation<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="SegmentationConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">SegmentationConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L302">config.ts:302</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="segmentation" class="tsd-anchor"></a><h3>segmentation</h3><div class="tsd-signature tsd-kind-icon">segmentation<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="SegmentationConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">SegmentationConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L283">config.ts:283</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p><a href="SegmentationConfig.html">SegmentationConfig</a></p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="skipFrame" class="tsd-anchor"></a><h3>skip<wbr/>Frame</h3><div class="tsd-signature tsd-kind-icon">skip<wbr/>Frame<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L277">config.ts:277</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="skipFrame" class="tsd-anchor"></a><h3>skip<wbr/>Frame</h3><div class="tsd-signature tsd-kind-icon">skip<wbr/>Frame<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L258">config.ts:258</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Internal Variable</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="warmup" class="tsd-anchor"></a><h3>warmup</h3><div class="tsd-signature tsd-kind-icon">warmup<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">&quot;face&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;body&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;none&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;full&quot;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L262">config.ts:262</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="warmup" class="tsd-anchor"></a><h3>warmup</h3><div class="tsd-signature tsd-kind-icon">warmup<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">&quot;face&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;body&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;none&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;full&quot;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L243">config.ts:243</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>What to use for <code>human.warmup()</code></p>
<ul>
<li>warmup pre-initializes all models for faster inference but can take significant time on startup</li>
</ul>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="wasmPath" class="tsd-anchor"></a><h3>wasm<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">wasm<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L251">config.ts:251</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="wasmPath" class="tsd-anchor"></a><h3>wasm<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">wasm<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L232">config.ts:232</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Path to *.wasm files if backend is set to <code>wasm</code></p>
<ul>
<li>if not set, auto-detects to link to CDN <code>jsdelivr</code> when running in browser</li>

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<!DOCTYPE html><html class="default no-js"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>FaceAntiSpoofConfig | @vladmandic/human - v2.4.0</title><meta name="description" content="Documentation for @vladmandic/human - v2.4.0"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script async src="../assets/search.js" id="search-script"></script></head><body><script>document.body.classList.add(localStorage.getItem(&quot;tsd-theme&quot;) || &quot;os&quot;)</script><header><div class="tsd-page-toolbar"><div class="container"><div class="table-wrap"><div class="table-cell" id="tsd-search" data-base=".."><div class="field"><label for="tsd-search-field" class="tsd-widget search no-caption">Search</label><input type="text" id="tsd-search-field"/></div><ul class="results"><li class="state loading">Preparing search index...</li><li class="state failure">The search index is not available</li></ul><a href="../index.html" class="title">@vladmandic/human - v2.4.0</a></div><div class="table-cell" id="tsd-widgets"><div id="tsd-filter"><a href="#" class="tsd-widget options no-caption" data-toggle="options">Options</a><div class="tsd-filter-group"><div class="tsd-select" id="tsd-filter-visibility"><span class="tsd-select-label">All</span><ul class="tsd-select-list"><li data-value="public">Public</li><li data-value="protected">Public/Protected</li><li data-value="private" class="selected">All</li></ul></div> <input type="checkbox" id="tsd-filter-inherited" checked/><label class="tsd-widget" for="tsd-filter-inherited">Inherited</label></div></div><a href="#" class="tsd-widget menu no-caption" data-toggle="menu">Menu</a></div></div></div></div><div class="tsd-page-title"><div class="container"><ul class="tsd-breadcrumb"><li><a href="../index.html">@vladmandic/human - v2.4.0</a></li><li><a href="FaceAntiSpoofConfig.html">FaceAntiSpoofConfig</a></li></ul><h1>Interface FaceAntiSpoofConfig</h1></div></div></header><div class="container container-main"><div class="row"><div class="col-8 col-content"><section class="tsd-panel tsd-comment"><div class="tsd-comment tsd-typography"><div class="lead">
<p>Emotion part of face configuration</p>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">FaceAntiSpoofConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceAntiSpoofConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceAntiSpoofConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceAntiSpoofConfig.html#skipFrames" class="tsd-kind-icon">skip<wbr/>Frames</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L47">config.ts:47</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="modelPath" class="tsd-anchor"></a><h3>model<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">model<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L49">config.ts:49</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="skipFrames" class="tsd-anchor"></a><h3>skip<wbr/>Frames</h3><div class="tsd-signature tsd-kind-icon">skip<wbr/>Frames<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L48">config.ts:48</a></li></ul></aside></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="FaceAntiSpoofConfig.html" class="tsd-kind-icon">Face<wbr/>Anti<wbr/>Spoof<wbr/>Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceAntiSpoofConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceAntiSpoofConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceAntiSpoofConfig.html#skipFrames" class="tsd-kind-icon">skip<wbr/>Frames</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>

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<!DOCTYPE html><html class="default no-js"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>FaceIrisConfig | @vladmandic/human - v2.4.0</title><meta name="description" content="Documentation for @vladmandic/human - v2.4.0"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script async src="../assets/search.js" id="search-script"></script></head><body><script>document.body.classList.add(localStorage.getItem(&quot;tsd-theme&quot;) || &quot;os&quot;)</script><header><div class="tsd-page-toolbar"><div class="container"><div class="table-wrap"><div class="table-cell" id="tsd-search" data-base=".."><div class="field"><label for="tsd-search-field" class="tsd-widget search no-caption">Search</label><input type="text" id="tsd-search-field"/></div><ul class="results"><li class="state loading">Preparing search index...</li><li class="state failure">The search index is not available</li></ul><a href="../index.html" class="title">@vladmandic/human - v2.4.0</a></div><div class="table-cell" id="tsd-widgets"><div id="tsd-filter"><a href="#" class="tsd-widget options no-caption" data-toggle="options">Options</a><div class="tsd-filter-group"><div class="tsd-select" id="tsd-filter-visibility"><span class="tsd-select-label">All</span><ul class="tsd-select-list"><li data-value="public">Public</li><li data-value="protected">Public/Protected</li><li data-value="private" class="selected">All</li></ul></div> <input type="checkbox" id="tsd-filter-inherited" checked/><label class="tsd-widget" for="tsd-filter-inherited">Inherited</label></div></div><a href="#" class="tsd-widget menu no-caption" data-toggle="menu">Menu</a></div></div></div></div><div class="tsd-page-title"><div class="container"><ul class="tsd-breadcrumb"><li><a href="../index.html">@vladmandic/human - v2.4.0</a></li><li><a href="FaceIrisConfig.html">FaceIrisConfig</a></li></ul><h1>Interface FaceIrisConfig</h1></div></div></header><div class="container container-main"><div class="row"><div class="col-8 col-content"><section class="tsd-panel tsd-comment"><div class="tsd-comment tsd-typography"><div class="lead">
<p>Iris part of face configuration</p>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">FaceIrisConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceIrisConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceIrisConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L23">config.ts:23</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="modelPath" class="tsd-anchor"></a><h3>model<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">model<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L24">config.ts:24</a></li></ul></aside></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="FaceIrisConfig.html" class="tsd-kind-icon">Face<wbr/>Iris<wbr/>Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceIrisConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceIrisConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>

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typedoc/interfaces/FaceMeshConfig.html
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<!DOCTYPE html><html class="default no-js"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>FaceMeshConfig | @vladmandic/human - v2.4.0</title><meta name="description" content="Documentation for @vladmandic/human - v2.4.0"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script async src="../assets/search.js" id="search-script"></script></head><body><script>document.body.classList.add(localStorage.getItem(&quot;tsd-theme&quot;) || &quot;os&quot;)</script><header><div class="tsd-page-toolbar"><div class="container"><div class="table-wrap"><div class="table-cell" id="tsd-search" data-base=".."><div class="field"><label for="tsd-search-field" class="tsd-widget search no-caption">Search</label><input type="text" id="tsd-search-field"/></div><ul class="results"><li class="state loading">Preparing search index...</li><li class="state failure">The search index is not available</li></ul><a href="../index.html" class="title">@vladmandic/human - v2.4.0</a></div><div class="table-cell" id="tsd-widgets"><div id="tsd-filter"><a href="#" class="tsd-widget options no-caption" data-toggle="options">Options</a><div class="tsd-filter-group"><div class="tsd-select" id="tsd-filter-visibility"><span class="tsd-select-label">All</span><ul class="tsd-select-list"><li data-value="public">Public</li><li data-value="protected">Public/Protected</li><li data-value="private" class="selected">All</li></ul></div> <input type="checkbox" id="tsd-filter-inherited" checked/><label class="tsd-widget" for="tsd-filter-inherited">Inherited</label></div></div><a href="#" class="tsd-widget menu no-caption" data-toggle="menu">Menu</a></div></div></div></div><div class="tsd-page-title"><div class="container"><ul class="tsd-breadcrumb"><li><a href="../index.html">@vladmandic/human - v2.4.0</a></li><li><a href="FaceMeshConfig.html">FaceMeshConfig</a></li></ul><h1>Interface FaceMeshConfig</h1></div></div></header><div class="container container-main"><div class="row"><div class="col-8 col-content"><section class="tsd-panel tsd-comment"><div class="tsd-comment tsd-typography"><div class="lead">
<p>Mesh part of face configuration</p>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">FaceMeshConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceMeshConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceMeshConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L17">config.ts:17</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="modelPath" class="tsd-anchor"></a><h3>model<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">model<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L18">config.ts:18</a></li></ul></aside></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="FaceMeshConfig.html" class="tsd-kind-icon">Face<wbr/>Mesh<wbr/>Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceMeshConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceMeshConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>

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<li>available only in Browser environments</li>
<li>image filters run with near-zero latency as they are executed on the GPU using WebGL</li>
</ul>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">FilterConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#blur" class="tsd-kind-icon">blur</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#brightness" class="tsd-kind-icon">brightness</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#contrast" class="tsd-kind-icon">contrast</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#flip" class="tsd-kind-icon">flip</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#height" class="tsd-kind-icon">height</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#hue" class="tsd-kind-icon">hue</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#kodachrome" class="tsd-kind-icon">kodachrome</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#negative" class="tsd-kind-icon">negative</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#pixelate" class="tsd-kind-icon">pixelate</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#polaroid" class="tsd-kind-icon">polaroid</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#return" class="tsd-kind-icon">return</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#saturation" class="tsd-kind-icon">saturation</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#sepia" class="tsd-kind-icon">sepia</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#sharpness" class="tsd-kind-icon">sharpness</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#technicolor" class="tsd-kind-icon">technicolor</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#vintage" class="tsd-kind-icon">vintage</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#width" class="tsd-kind-icon">width</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="blur" class="tsd-anchor"></a><h3>blur</h3><div class="tsd-signature tsd-kind-icon">blur<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L200">config.ts:200</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">FilterConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#blur" class="tsd-kind-icon">blur</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#brightness" class="tsd-kind-icon">brightness</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#contrast" class="tsd-kind-icon">contrast</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#flip" class="tsd-kind-icon">flip</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#height" class="tsd-kind-icon">height</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#hue" class="tsd-kind-icon">hue</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#kodachrome" class="tsd-kind-icon">kodachrome</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#negative" class="tsd-kind-icon">negative</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#pixelate" class="tsd-kind-icon">pixelate</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#polaroid" class="tsd-kind-icon">polaroid</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#return" class="tsd-kind-icon">return</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#saturation" class="tsd-kind-icon">saturation</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#sepia" class="tsd-kind-icon">sepia</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#sharpness" class="tsd-kind-icon">sharpness</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#technicolor" class="tsd-kind-icon">technicolor</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#vintage" class="tsd-kind-icon">vintage</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="FilterConfig.html#width" class="tsd-kind-icon">width</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="blur" class="tsd-anchor"></a><h3>blur</h3><div class="tsd-signature tsd-kind-icon">blur<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L181">config.ts:181</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Range: 0 (no blur) to N (blur radius in pixels)</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="brightness" class="tsd-anchor"></a><h3>brightness</h3><div class="tsd-signature tsd-kind-icon">brightness<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L194">config.ts:194</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="brightness" class="tsd-anchor"></a><h3>brightness</h3><div class="tsd-signature tsd-kind-icon">brightness<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L175">config.ts:175</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Range: -1 (darken) to 1 (lighten)</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="contrast" class="tsd-anchor"></a><h3>contrast</h3><div class="tsd-signature tsd-kind-icon">contrast<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L196">config.ts:196</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="contrast" class="tsd-anchor"></a><h3>contrast</h3><div class="tsd-signature tsd-kind-icon">contrast<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L177">config.ts:177</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Range: -1 (reduce contrast) to 1 (increase contrast)</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L176">config.ts:176</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="flip" class="tsd-anchor"></a><h3>flip</h3><div class="tsd-signature tsd-kind-icon">flip<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L192">config.ts:192</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L157">config.ts:157</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="flip" class="tsd-anchor"></a><h3>flip</h3><div class="tsd-signature tsd-kind-icon">flip<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L173">config.ts:173</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Flip input as mirror image</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="height" class="tsd-anchor"></a><h3>height</h3><div class="tsd-signature tsd-kind-icon">height<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L188">config.ts:188</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="height" class="tsd-anchor"></a><h3>height</h3><div class="tsd-signature tsd-kind-icon">height<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L169">config.ts:169</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Resize input height</p>
<ul>
<li>if both width and height are set to 0, there is no resizing</li>
<li>if just one is set, second one is scaled automatically</li>
<li>if both are set, values are used as-is</li>
</ul>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="hue" class="tsd-anchor"></a><h3>hue</h3><div class="tsd-signature tsd-kind-icon">hue<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L204">config.ts:204</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="hue" class="tsd-anchor"></a><h3>hue</h3><div class="tsd-signature tsd-kind-icon">hue<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L185">config.ts:185</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Range: 0 (no change) to 360 (hue rotation in degrees)</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="kodachrome" class="tsd-anchor"></a><h3>kodachrome</h3><div class="tsd-signature tsd-kind-icon">kodachrome<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L212">config.ts:212</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="kodachrome" class="tsd-anchor"></a><h3>kodachrome</h3><div class="tsd-signature tsd-kind-icon">kodachrome<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L193">config.ts:193</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Image kodachrome colors</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="negative" class="tsd-anchor"></a><h3>negative</h3><div class="tsd-signature tsd-kind-icon">negative<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L206">config.ts:206</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="negative" class="tsd-anchor"></a><h3>negative</h3><div class="tsd-signature tsd-kind-icon">negative<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L187">config.ts:187</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Image negative</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="pixelate" class="tsd-anchor"></a><h3>pixelate</h3><div class="tsd-signature tsd-kind-icon">pixelate<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L218">config.ts:218</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="pixelate" class="tsd-anchor"></a><h3>pixelate</h3><div class="tsd-signature tsd-kind-icon">pixelate<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L199">config.ts:199</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Range: 0 (no pixelate) to N (number of pixels to pixelate)</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="polaroid" class="tsd-anchor"></a><h3>polaroid</h3><div class="tsd-signature tsd-kind-icon">polaroid<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L216">config.ts:216</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="polaroid" class="tsd-anchor"></a><h3>polaroid</h3><div class="tsd-signature tsd-kind-icon">polaroid<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L197">config.ts:197</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Image polaroid camera effect</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="return" class="tsd-anchor"></a><h3>return</h3><div class="tsd-signature tsd-kind-icon">return<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L190">config.ts:190</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="return" class="tsd-anchor"></a><h3>return</h3><div class="tsd-signature tsd-kind-icon">return<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L171">config.ts:171</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Return processed canvas imagedata in result</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="saturation" class="tsd-anchor"></a><h3>saturation</h3><div class="tsd-signature tsd-kind-icon">saturation<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L202">config.ts:202</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="saturation" class="tsd-anchor"></a><h3>saturation</h3><div class="tsd-signature tsd-kind-icon">saturation<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L183">config.ts:183</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Range: -1 (reduce saturation) to 1 (increase saturation)</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="sepia" class="tsd-anchor"></a><h3>sepia</h3><div class="tsd-signature tsd-kind-icon">sepia<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L208">config.ts:208</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="sepia" class="tsd-anchor"></a><h3>sepia</h3><div class="tsd-signature tsd-kind-icon">sepia<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L189">config.ts:189</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Image sepia colors</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="sharpness" class="tsd-anchor"></a><h3>sharpness</h3><div class="tsd-signature tsd-kind-icon">sharpness<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L198">config.ts:198</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="sharpness" class="tsd-anchor"></a><h3>sharpness</h3><div class="tsd-signature tsd-kind-icon">sharpness<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L179">config.ts:179</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Range: 0 (no sharpening) to 1 (maximum sharpening)</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="technicolor" class="tsd-anchor"></a><h3>technicolor</h3><div class="tsd-signature tsd-kind-icon">technicolor<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L214">config.ts:214</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="technicolor" class="tsd-anchor"></a><h3>technicolor</h3><div class="tsd-signature tsd-kind-icon">technicolor<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L195">config.ts:195</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Image technicolor colors</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="vintage" class="tsd-anchor"></a><h3>vintage</h3><div class="tsd-signature tsd-kind-icon">vintage<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L210">config.ts:210</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="vintage" class="tsd-anchor"></a><h3>vintage</h3><div class="tsd-signature tsd-kind-icon">vintage<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L191">config.ts:191</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Image vintage colors</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="width" class="tsd-anchor"></a><h3>width</h3><div class="tsd-signature tsd-kind-icon">width<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L182">config.ts:182</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="width" class="tsd-anchor"></a><h3>width</h3><div class="tsd-signature tsd-kind-icon">width<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L163">config.ts:163</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Resize input width</p>
<ul>
<li>if both width and height are set to 0, there is no resizing</li>

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<!DOCTYPE html><html class="default no-js"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>GestureConfig | @vladmandic/human - v2.4.0</title><meta name="description" content="Documentation for @vladmandic/human - v2.4.0"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script async src="../assets/search.js" id="search-script"></script></head><body><script>document.body.classList.add(localStorage.getItem(&quot;tsd-theme&quot;) || &quot;os&quot;)</script><header><div class="tsd-page-toolbar"><div class="container"><div class="table-wrap"><div class="table-cell" id="tsd-search" data-base=".."><div class="field"><label for="tsd-search-field" class="tsd-widget search no-caption">Search</label><input type="text" id="tsd-search-field"/></div><ul class="results"><li class="state loading">Preparing search index...</li><li class="state failure">The search index is not available</li></ul><a href="../index.html" class="title">@vladmandic/human - v2.4.0</a></div><div class="table-cell" id="tsd-widgets"><div id="tsd-filter"><a href="#" class="tsd-widget options no-caption" data-toggle="options">Options</a><div class="tsd-filter-group"><div class="tsd-select" id="tsd-filter-visibility"><span class="tsd-select-label">All</span><ul class="tsd-select-list"><li data-value="public">Public</li><li data-value="protected">Public/Protected</li><li data-value="private" class="selected">All</li></ul></div> <input type="checkbox" id="tsd-filter-inherited" checked/><label class="tsd-widget" for="tsd-filter-inherited">Inherited</label></div></div><a href="#" class="tsd-widget menu no-caption" data-toggle="menu">Menu</a></div></div></div></div><div class="tsd-page-title"><div class="container"><ul class="tsd-breadcrumb"><li><a href="../index.html">@vladmandic/human - v2.4.0</a></li><li><a href="GestureConfig.html">GestureConfig</a></li></ul><h1>Interface GestureConfig</h1></div></div></header><div class="container container-main"><div class="row"><div class="col-8 col-content"><section class="tsd-panel tsd-comment"><div class="tsd-comment tsd-typography"><div class="lead">
<p>Controlls gesture detection</p>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">GestureConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="GestureConfig.html#enabled" class="tsd-kind-icon">enabled</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L223">config.ts:223</a></li></ul></aside></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="GestureConfig.html" class="tsd-kind-icon">Gesture<wbr/>Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="GestureConfig.html#enabled" class="tsd-kind-icon">enabled</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">GestureConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="GestureConfig.html#enabled" class="tsd-kind-icon">enabled</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L204">config.ts:204</a></li></ul></aside></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="GestureConfig.html" class="tsd-kind-icon">Gesture<wbr/>Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="GestureConfig.html#enabled" class="tsd-kind-icon">enabled</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>

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@ -11,4 +11,4 @@ remove background or replace it with user-provided background</p>
</ul>
<p>Changing <code>modelPath</code> will change module responsible for hand detection and tracking
Allowed values are <code>selfie.json</code> and <code>meet.json</code></p>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">SegmentationConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#blur" class="tsd-kind-icon">blur</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="blur" class="tsd-anchor"></a><h3>blur</h3><div class="tsd-signature tsd-kind-icon">blur<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L168">config.ts:168</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L166">config.ts:166</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="modelPath" class="tsd-anchor"></a><h3>model<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">model<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L167">config.ts:167</a></li></ul></aside></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="SegmentationConfig.html" class="tsd-kind-icon">Segmentation<wbr/>Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#blur" class="tsd-kind-icon">blur</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>
</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">SegmentationConfig</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#blur" class="tsd-kind-icon">blur</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="blur" class="tsd-anchor"></a><h3>blur</h3><div class="tsd-signature tsd-kind-icon">blur<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L149">config.ts:149</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="enabled" class="tsd-anchor"></a><h3>enabled</h3><div class="tsd-signature tsd-kind-icon">enabled<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L147">config.ts:147</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="modelPath" class="tsd-anchor"></a><h3>model<wbr/>Path</h3><div class="tsd-signature tsd-kind-icon">model<wbr/>Path<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L148">config.ts:148</a></li></ul></aside></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="SegmentationConfig.html" class="tsd-kind-icon">Segmentation<wbr/>Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#blur" class="tsd-kind-icon">blur</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#enabled" class="tsd-kind-icon">enabled</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="SegmentationConfig.html#modelPath" class="tsd-kind-icon">model<wbr/>Path</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>

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@ -1,45 +1,33 @@
/** Dectector part of face configuration */
export interface FaceDetectorConfig {
export interface GenericConfig {
enabled: boolean;
modelPath: string;
skipFrames: number;
skipTime: number;
}
/** Dectector part of face configuration */
export interface FaceDetectorConfig extends GenericConfig {
rotation: boolean;
maxDetected: number;
skipFrames: number;
minConfidence: number;
iouThreshold: number;
return: boolean;
}
/** Mesh part of face configuration */
export interface FaceMeshConfig {
enabled: boolean;
modelPath: string;
}
export declare type FaceMeshConfig = GenericConfig;
/** Iris part of face configuration */
export interface FaceIrisConfig {
enabled: boolean;
modelPath: string;
}
export declare type FaceIrisConfig = GenericConfig;
/** Description or face embedding part of face configuration
* - also used by age and gender detection
*/
export interface FaceDescriptionConfig {
enabled: boolean;
modelPath: string;
skipFrames: number;
export interface FaceDescriptionConfig extends GenericConfig {
minConfidence: number;
}
/** Emotion part of face configuration */
export interface FaceEmotionConfig {
enabled: boolean;
export interface FaceEmotionConfig extends GenericConfig {
minConfidence: number;
skipFrames: number;
modelPath: string;
}
/** Emotion part of face configuration */
export interface FaceAntiSpoofConfig {
enabled: boolean;
skipFrames: number;
modelPath: string;
}
export declare type FaceAntiSpoofConfig = GenericConfig;
/** Controlls and configures all face-specific options:
* - face detection, face mesh detection, age, gender, emotion detection and face description
*
@ -76,17 +64,14 @@ export interface FaceConfig {
* Changing `modelPath` will change module responsible for hand detection and tracking
* Allowed values are `posenet.json`, `blazepose.json`, `efficientpose.json`, `movenet-lightning.json`, `movenet-thunder.json`, `movenet-multipose.json`
*/
export interface BodyConfig {
enabled: boolean;
modelPath: string;
export interface BodyConfig extends GenericConfig {
maxDetected: number;
minConfidence: number;
skipFrames: number;
detector?: {
modelPath: string;
};
}
/** Controlls and configures all hand detection specific options
/** Controls and configures all hand detection specific options
*
* Parameters:
* - enabled: true/false
@ -102,10 +87,8 @@ export interface BodyConfig {
* Changing `detector.modelPath` will change module responsible for hand detection and tracking
* Allowed values are `handdetect.json` and `handtrack.json`
*/
export interface HandConfig {
enabled: boolean;
export interface HandConfig extends GenericConfig {
rotation: boolean;
skipFrames: number;
minConfidence: number;
iouThreshold: number;
maxDetected: number;
@ -127,13 +110,10 @@ export interface HandConfig {
* Changing `modelPath` will change module responsible for hand detection and tracking
* Allowed values are `mb3-centernet.json` and `nanodet.json`
*/
export interface ObjectConfig {
enabled: boolean;
modelPath: string;
export interface ObjectConfig extends GenericConfig {
minConfidence: number;
iouThreshold: number;
maxDetected: number;
skipFrames: number;
}
/** Controlls and configures all body segmentation module
* removes background from input containing person

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