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refactoring

pull/193/head
Vladimir Mandic 2021-09-27 13:58:13 -04:00
parent 3a89251e51
commit 07696845df
107 changed files with 2088 additions and 1755 deletions
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1
CHANGELOG.md
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@ -11,6 +11,7 @@
### **HEAD -> main** 2021/09/27 mandic00@live.com
- implement box caching for movenet
- autodetect number of bodies and hands
- upload new samples
- new samples gallery and major code folder restructure

490
dist/human.esm-nobundle.js vendored
View File

@ -46,7 +46,7 @@ var __privateSet = (obj, member, value, setter) => {
return value;
};
// src/util.ts
// src/util/util.ts
function join(folder, file) {
const separator = folder.endsWith("/") ? "" : "/";
const skipJoin = file.startsWith(".") || file.startsWith("/") || file.startsWith("http:") || file.startsWith("https:") || file.startsWith("file:");
@ -99,31 +99,6 @@ function mergeDeep(...objects) {
return prev;
}, {});
}
function scaleBox(keypoints3, boxScaleFact2, outputSize2) {
const coords3 = [keypoints3.map((pt) => pt[0]), keypoints3.map((pt) => pt[1])];
const maxmin = [Math.max(...coords3[0]), Math.min(...coords3[0]), Math.max(...coords3[1]), Math.min(...coords3[1])];
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2];
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact2;
const box5 = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff)
];
const boxRaw2 = [
box5[0] / outputSize2[0],
box5[1] / outputSize2[1],
box5[2] / outputSize2[0],
box5[3] / outputSize2[1]
];
const yxBox = [
boxRaw2[1],
boxRaw2[0],
boxRaw2[3] + boxRaw2[1],
boxRaw2[2] + boxRaw2[0]
];
return { box: box5, boxRaw: boxRaw2, yxBox };
}
// src/config.ts
var config = {
@ -193,6 +168,9 @@ var config = {
body: {
enabled: true,
modelPath: "movenet-lightning.json",
detector: {
modelPath: ""
},
maxDetected: -1,
minConfidence: 0.2,
skipFrames: 1
@ -380,13 +358,13 @@ function rotatePoint(homogeneousCoordinate, rotationMatrix) {
dot(homogeneousCoordinate, rotationMatrix[1])
];
}
function generateAnchors(inputSize4) {
const spec = { strides: [inputSize4 / 16, inputSize4 / 8], anchors: [2, 6] };
function generateAnchors(inputSize5) {
const spec = { strides: [inputSize5 / 16, inputSize5 / 8], anchors: [2, 6] };
const anchors3 = [];
for (let i = 0; i < spec.strides.length; i++) {
const stride = spec.strides[i];
const gridRows = Math.floor((inputSize4 + stride - 1) / stride);
const gridCols = Math.floor((inputSize4 + stride - 1) / stride);
const gridRows = Math.floor((inputSize5 + stride - 1) / stride);
const gridCols = Math.floor((inputSize5 + stride - 1) / stride);
const anchorsNum = spec.anchors[i];
for (let gridY = 0; gridY < gridRows; gridY++) {
const anchorY = stride * (gridY + 0.5);
@ -403,31 +381,31 @@ function generateAnchors(inputSize4) {
// src/blazeface/blazeface.ts
var keypointsCount = 6;
function decodeBounds(boxOutputs, anchors3, inputSize4) {
function decodeBounds(boxOutputs, anchors3, inputSize5) {
const boxStarts = tfjs_esm_exports.slice(boxOutputs, [0, 1], [-1, 2]);
const centers = tfjs_esm_exports.add(boxStarts, anchors3);
const boxSizes = tfjs_esm_exports.slice(boxOutputs, [0, 3], [-1, 2]);
const boxSizesNormalized = tfjs_esm_exports.div(boxSizes, inputSize4);
const centersNormalized = tfjs_esm_exports.div(centers, inputSize4);
const boxSizesNormalized = tfjs_esm_exports.div(boxSizes, inputSize5);
const centersNormalized = tfjs_esm_exports.div(centers, inputSize5);
const halfBoxSize = tfjs_esm_exports.div(boxSizesNormalized, 2);
const starts = tfjs_esm_exports.sub(centersNormalized, halfBoxSize);
const ends = tfjs_esm_exports.add(centersNormalized, halfBoxSize);
const startNormalized = tfjs_esm_exports.mul(starts, inputSize4);
const endNormalized = tfjs_esm_exports.mul(ends, inputSize4);
const startNormalized = tfjs_esm_exports.mul(starts, inputSize5);
const endNormalized = tfjs_esm_exports.mul(ends, inputSize5);
const concatAxis = 1;
return tfjs_esm_exports.concat2d([startNormalized, endNormalized], concatAxis);
}
var BlazeFaceModel = class {
constructor(model11, config3) {
constructor(model10, config3) {
__publicField(this, "model");
__publicField(this, "anchorsData");
__publicField(this, "anchors");
__publicField(this, "inputSize");
__publicField(this, "config");
this.model = model11;
this.anchorsData = generateAnchors(model11.inputs[0].shape[1]);
this.model = model10;
this.anchorsData = generateAnchors(model10.inputs[0].shape[1]);
this.anchors = tfjs_esm_exports.tensor2d(this.anchorsData);
this.inputSize = model11.inputs[0].shape[2];
this.inputSize = model10.inputs[0].shape[2];
this.config = config3;
}
async getBoundingBoxes(inputImage, userConfig) {
@ -479,12 +457,12 @@ var BlazeFaceModel = class {
};
async function load(config3) {
var _a, _b, _c;
const model11 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, ((_a = config3.face.detector) == null ? void 0 : _a.modelPath) || ""), { fromTFHub: (((_b = config3.face.detector) == null ? void 0 : _b.modelPath) || "").includes("tfhub.dev") });
const blazeFace = new BlazeFaceModel(model11, config3);
if (!model11 || !model11.modelUrl)
const model10 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, ((_a = config3.face.detector) == null ? void 0 : _a.modelPath) || ""), { fromTFHub: (((_b = config3.face.detector) == null ? void 0 : _b.modelPath) || "").includes("tfhub.dev") });
const blazeFace = new BlazeFaceModel(model10, config3);
if (!model10 || !model10.modelUrl)
log("load model failed:", ((_c = config3.face.detector) == null ? void 0 : _c.modelPath) || "");
else if (config3.debug)
log("load model:", model11.modelUrl);
log("load model:", model10.modelUrl);
return blazeFace;
}
@ -4671,7 +4649,7 @@ async function skip(config3, input) {
return skipFrame;
}
// src/env.ts
// src/util/env.ts
var env = {
browser: void 0,
node: void 0,
@ -5132,7 +5110,7 @@ async function load2(config3) {
var triangulation = TRI468;
var uvmap = UV468;
// src/faceres/faceres.ts
// src/face/faceres.ts
var model;
var last = [];
var lastCount = 0;
@ -5235,7 +5213,7 @@ async function predict2(image24, config3, idx, count2) {
});
}
// src/emotion/emotion.ts
// src/gear/emotion.ts
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model2;
var last2 = [];
@ -8645,14 +8623,14 @@ var anchors = [
// src/handpose/handdetector.ts
var HandDetector = class {
constructor(model11) {
constructor(model10) {
__publicField(this, "model");
__publicField(this, "anchors");
__publicField(this, "anchorsTensor");
__publicField(this, "inputSize");
__publicField(this, "inputSizeTensor");
__publicField(this, "doubleInputSizeTensor");
this.model = model11;
this.model = model10;
this.anchors = anchors.map((anchor) => [anchor.x, anchor.y]);
this.anchorsTensor = tfjs_esm_exports.tensor2d(this.anchors);
this.inputSize = this.model && this.model.inputs && this.model.inputs[0].shape ? this.model.inputs[0].shape[2] : 0;
@ -9408,6 +9386,33 @@ async function load6(config3) {
return [handDetectorModel, handPoseModel];
}
// src/util/box.ts
function scale(keypoints3, boxScaleFact2, outputSize3) {
const coords3 = [keypoints3.map((pt) => pt[0]), keypoints3.map((pt) => pt[1])];
const maxmin = [Math.max(...coords3[0]), Math.min(...coords3[0]), Math.max(...coords3[1]), Math.min(...coords3[1])];
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2];
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact2;
const box5 = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff)
];
const boxRaw2 = [
box5[0] / outputSize3[0],
box5[1] / outputSize3[1],
box5[2] / outputSize3[0],
box5[3] / outputSize3[1]
];
const yxBox = [
boxRaw2[1],
boxRaw2[0],
boxRaw2[3] + boxRaw2[1],
boxRaw2[2] + boxRaw2[0]
];
return { box: box5, boxRaw: boxRaw2, yxBox };
}
// src/tfjs/humangl.ts
var config2 = {
name: "humangl",
@ -9610,7 +9615,7 @@ function fakeOps(kernelNames, config3) {
env.kernels = tfjs_esm_exports.getKernelsForBackend(tfjs_esm_exports.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());
}
// src/handtrack/handtrack.ts
// src/hand/handtrack.ts
var boxScaleFact = 1.5;
var models2 = [null, null];
var modelOutputNodes = ["StatefulPartitionedCall/Postprocessor/Slice", "StatefulPartitionedCall/Postprocessor/ExpandDims_1"];
@ -9748,7 +9753,7 @@ async function detectFingers(input, h, config3) {
h.box[3] * coord[1] / inputSize[1][1] + h.box[1],
(h.box[2] + h.box[3]) / 2 / inputSize[1][0] * coord[2]
]);
const updatedBox = scaleBox(hand3.keypoints, boxScaleFact, outputSize);
const updatedBox = scale(hand3.keypoints, boxScaleFact, outputSize);
h.box = updatedBox.box;
h.boxRaw = updatedBox.boxRaw;
h.yxBox = updatedBox.yxBox;
@ -9785,7 +9790,7 @@ async function predict6(input, config3) {
return hands;
}
// src/blazepose/annotations.ts
// src/body/annotations.ts
var full = [
"nose",
"leftEyeInside",
@ -9861,57 +9866,71 @@ var upper = [
"right:30"
];
// src/blazepose/blazepose.ts
var model4;
async function load7(config3) {
// src/body/blazepose.ts
var models3 = [null, null];
var outputNodes = ["ld_3d", "activation_segmentation", "activation_heatmap", "world_3d", "output_poseflag"];
var inputSize2 = [[0, 0], [0, 0]];
var outputSize2 = [0, 0];
async function loadDetect2(config3) {
var _a;
if (env.initial)
model4 = null;
if (!model4) {
model4 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
model4["width"] = parseInt(model4["signature"].inputs["input_1:0"].tensorShape.dim[2].size);
model4["height"] = parseInt(model4["signature"].inputs["input_1:0"].tensorShape.dim[1].size);
if (!model4 || !model4["modelUrl"])
log("load model failed:", config3.body.modelPath);
models3[0] = null;
if (!models3[0]) {
models3[0] = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, ((_a = config3.body.detector) == null ? void 0 : _a.modelPath) || ""));
const inputs = Object.values(models3[0].modelSignature["inputs"]);
inputSize2[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize2[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models3[0] || !models3[0]["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model4["modelUrl"]);
log("load model:", models3[0]["modelUrl"]);
} else if (config3.debug)
log("cached model:", model4["modelUrl"]);
return model4;
log("cached model:", models3[0]["modelUrl"]);
return models3[0];
}
async function predict7(image24, config3) {
if (!model4)
return [];
if (!config3.body.enabled)
return [];
const imgSize = { width: image24.shape[2] || 0, height: image24.shape[1] || 0 };
const resize = tfjs_esm_exports.image.resizeBilinear(image24, [model4["width"], model4["height"]], false);
const normalize = tfjs_esm_exports.div(resize, [255]);
tfjs_esm_exports.dispose(resize);
const resT = await model4.predict(normalize);
const findT = resT.find((t) => t.size === 195 || t.size === 155);
const points = await (findT == null ? void 0 : findT.data()) || [];
resT.forEach((t) => tfjs_esm_exports.dispose(t));
tfjs_esm_exports.dispose(normalize);
async function loadPose(config3) {
if (env.initial)
models3[1] = null;
if (!models3[1]) {
models3[1] = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
const inputs = Object.values(models3[1].modelSignature["inputs"]);
inputSize2[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize2[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models3[1] || !models3[1]["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", models3[1]["modelUrl"]);
} else if (config3.debug)
log("cached model:", models3[1]["modelUrl"]);
return models3[1];
}
async function detectParts(input, config3) {
var _a;
const t = {};
t.resize = tfjs_esm_exports.image.resizeBilinear(input, [inputSize2[1][0], inputSize2[1][1]]);
[t.ld, t.segmentation, t.heatmap, t.world, t.poseflag] = await ((_a = models3[1]) == null ? void 0 : _a.execute(t.resize, outputNodes));
const points = await t.ld.data();
const keypoints3 = [];
const labels2 = (points == null ? void 0 : points.length) === 195 ? full : upper;
const depth = 5;
for (let i = 0; i < points.length / depth; i++) {
keypoints3.push({
id: i,
part: labels2[i],
position: [
Math.trunc(imgSize.width * points[depth * i + 0] / 255),
Math.trunc(imgSize.height * points[depth * i + 1] / 255),
Math.trunc(points[depth * i + 2]) + 0
],
positionRaw: [
points[depth * i + 0] / 255,
points[depth * i + 1] / 255,
points[depth * i + 2] + 0
],
score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100,
presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100
});
const score3 = (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100;
if (score3 > (config3.body.minConfidence || 0)) {
keypoints3.push({
part: labels2[i],
position: [
Math.trunc(outputSize2[0] * points[depth * i + 0] / 255),
Math.trunc(outputSize2[1] * points[depth * i + 1] / 255),
Math.trunc(points[depth * i + 2]) + 0
],
positionRaw: [
points[depth * i + 0] / 255,
points[depth * i + 1] / 255,
points[depth * i + 2] + 0
],
score: score3
});
}
}
const x = keypoints3.map((a) => a.position[0]);
const y = keypoints3.map((a) => a.position[1]);
@ -9923,29 +9942,37 @@ async function predict7(image24, config3) {
];
const boxRaw2 = [0, 0, 0, 0];
const score2 = keypoints3.reduce((prev, curr) => curr.score > prev ? curr.score : prev, 0);
return [{ id: 0, score: score2, box: box5, boxRaw: boxRaw2, keypoints: keypoints3 }];
Object.keys(t).forEach((tensor3) => tfjs_esm_exports.dispose(t[tensor3]));
return { id: 0, score: score2, box: box5, boxRaw: boxRaw2, keypoints: keypoints3 };
}
async function predict7(input, config3) {
outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
const bodies = [];
const body4 = await detectParts(input, config3);
bodies.push(body4);
return bodies;
}
// src/efficientpose/efficientpose.ts
var model5;
// src/body/efficientpose.ts
var model4;
var keypoints = [];
var box4 = [0, 0, 0, 0];
var boxRaw = [0, 0, 0, 0];
var score = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
var bodyParts = ["head", "neck", "rightShoulder", "rightElbow", "rightWrist", "chest", "leftShoulder", "leftElbow", "leftWrist", "pelvis", "rightHip", "rightKnee", "rightAnkle", "leftHip", "leftKnee", "leftAnkle"];
async function load8(config3) {
async function load7(config3) {
if (env.initial)
model5 = null;
if (!model5) {
model5 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model5 || !model5["modelUrl"])
model4 = null;
if (!model4) {
model4 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model4 || !model4["modelUrl"])
log("load model failed:", config3.body.modelPath);
else if (config3.debug)
log("load model:", model5["modelUrl"]);
log("load model:", model4["modelUrl"]);
} else if (config3.debug)
log("cached model:", model5["modelUrl"]);
return model5;
log("cached model:", model4["modelUrl"]);
return model4;
}
function max2d(inputs, minScore) {
const [width, height] = inputs.shape;
@ -9972,16 +9999,16 @@ async function predict8(image24, config3) {
return new Promise(async (resolve) => {
var _a2;
const tensor3 = tfjs_esm_exports.tidy(() => {
if (!(model5 == null ? void 0 : model5.inputs[0].shape))
if (!(model4 == null ? void 0 : model4.inputs[0].shape))
return null;
const resize = tfjs_esm_exports.image.resizeBilinear(image24, [model5.inputs[0].shape[2], model5.inputs[0].shape[1]], false);
const resize = tfjs_esm_exports.image.resizeBilinear(image24, [model4.inputs[0].shape[2], model4.inputs[0].shape[1]], false);
const enhance2 = tfjs_esm_exports.mul(resize, 2);
const norm = enhance2.sub(1);
return norm;
});
let resT;
if (config3.body.enabled)
resT = await (model5 == null ? void 0 : model5.predict(tensor3));
resT = await (model4 == null ? void 0 : model4.predict(tensor3));
tfjs_esm_exports.dispose(tensor3);
if (resT) {
keypoints.length = 0;
@ -9996,12 +10023,12 @@ async function predict8(image24, config3) {
score: Math.round(100 * partScore) / 100,
part: bodyParts[id],
positionRaw: [
x2 / model5.inputs[0].shape[2],
y2 / model5.inputs[0].shape[1]
x2 / model4.inputs[0].shape[2],
y2 / model4.inputs[0].shape[1]
],
position: [
Math.round(image24.shape[2] * x2 / model5.inputs[0].shape[2]),
Math.round(image24.shape[1] * y2 / model5.inputs[0].shape[1])
Math.round(image24.shape[2] * x2 / model4.inputs[0].shape[2]),
Math.round(image24.shape[1] * y2 / model4.inputs[0].shape[1])
]
});
}
@ -10029,29 +10056,29 @@ async function predict8(image24, config3) {
});
}
// src/movenet/movenet.ts
var model6;
var inputSize2 = 0;
// src/body/movenet.ts
var model5;
var inputSize3 = 0;
var cachedBoxes = [];
var skipped5 = Number.MAX_SAFE_INTEGER;
var keypoints2 = [];
var bodyParts2 = ["nose", "leftEye", "rightEye", "leftEar", "rightEar", "leftShoulder", "rightShoulder", "leftElbow", "rightElbow", "leftWrist", "rightWrist", "leftHip", "rightHip", "leftKnee", "rightKnee", "leftAnkle", "rightAnkle"];
async function load9(config3) {
async function load8(config3) {
if (env.initial)
model6 = null;
if (!model6) {
model5 = null;
if (!model5) {
fakeOps(["size"], config3);
model6 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model6 || !model6["modelUrl"])
model5 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model5 || !model5["modelUrl"])
log("load model failed:", config3.body.modelPath);
else if (config3.debug)
log("load model:", model6["modelUrl"]);
log("load model:", model5["modelUrl"]);
} else if (config3.debug)
log("cached model:", model6["modelUrl"]);
inputSize2 = model6.inputs[0].shape ? model6.inputs[0].shape[2] : 0;
if (inputSize2 === -1)
inputSize2 = 256;
return model6;
log("cached model:", model5["modelUrl"]);
inputSize3 = model5.inputs[0].shape ? model5.inputs[0].shape[2] : 0;
if (inputSize3 === -1)
inputSize3 = 256;
return model5;
}
async function parseSinglePose(res, config3, image24, inputBox) {
const kpt3 = res[0][0];
@ -10136,7 +10163,7 @@ async function parseMultiPose(res, config3, image24, inputBox) {
return bodies;
}
async function predict9(input, config3) {
if (!model6 || !(model6 == null ? void 0 : model6.inputs[0].shape))
if (!model5 || !(model5 == null ? void 0 : model5.inputs[0].shape))
return [];
return new Promise(async (resolve) => {
const t = {};
@ -10145,18 +10172,18 @@ async function predict9(input, config3) {
cachedBoxes.length = 0;
skipped5++;
for (let i = 0; i < cachedBoxes.length; i++) {
t.crop = tfjs_esm_exports.image.cropAndResize(input, [cachedBoxes[i]], [0], [inputSize2, inputSize2], "bilinear");
t.crop = tfjs_esm_exports.image.cropAndResize(input, [cachedBoxes[i]], [0], [inputSize3, inputSize3], "bilinear");
t.cast = tfjs_esm_exports.cast(t.crop, "int32");
t.res = await (model6 == null ? void 0 : model6.predict(t.cast));
t.res = await (model5 == null ? void 0 : model5.predict(t.cast));
const res = await t.res.array();
const newBodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, cachedBoxes[i]) : await parseMultiPose(res, config3, input, cachedBoxes[i]);
bodies = bodies.concat(newBodies);
Object.keys(t).forEach((tensor3) => tfjs_esm_exports.dispose(t[tensor3]));
}
if (bodies.length !== config3.body.maxDetected && skipped5 > (config3.body.skipFrames || 0)) {
t.resized = tfjs_esm_exports.image.resizeBilinear(input, [inputSize2, inputSize2], false);
t.resized = tfjs_esm_exports.image.resizeBilinear(input, [inputSize3, inputSize3], false);
t.cast = tfjs_esm_exports.cast(t.resized, "int32");
t.res = await (model6 == null ? void 0 : model6.predict(t.cast));
t.res = await (model5 == null ? void 0 : model5.predict(t.cast));
const res = await t.res.array();
bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input, [0, 0, 1, 1]);
Object.keys(t).forEach((tensor3) => tfjs_esm_exports.dispose(t[tensor3]));
@ -10168,7 +10195,7 @@ async function predict9(input, config3) {
for (let i = 0; i < bodies.length; i++) {
if (bodies[i].keypoints.length > 10) {
const kpts = bodies[i].keypoints.map((kpt3) => kpt3.position);
const newBox = scaleBox(kpts, 1.5, [input.shape[2], input.shape[1]]);
const newBox = scale(kpts, 1.5, [input.shape[2], input.shape[1]]);
cachedBoxes.push([...newBox.yxBox]);
}
}
@ -10262,26 +10289,26 @@ var labels = [
];
// src/object/nanodet.ts
var model7;
var model6;
var last3 = [];
var skipped6 = Number.MAX_SAFE_INTEGER;
var scaleBox2 = 2.5;
async function load10(config3) {
if (!model7 || env.initial) {
model7 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model7.modelSignature["inputs"]);
model7.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
if (!model7.inputSize)
var scaleBox = 2.5;
async function load9(config3) {
if (!model6 || env.initial) {
model6 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model6.modelSignature["inputs"]);
model6.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
if (!model6.inputSize)
throw new Error(`cannot determine model inputSize: ${config3.object.modelPath}`);
if (!model7 || !model7.modelUrl)
if (!model6 || !model6.modelUrl)
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model7.modelUrl);
log("load model:", model6.modelUrl);
} else if (config3.debug)
log("cached model:", model7.modelUrl);
return model7;
log("cached model:", model6.modelUrl);
return model6;
}
async function process3(res, inputSize4, outputShape, config3) {
async function process3(res, inputSize5, outputShape, config3) {
let id = 0;
let results = [];
for (const strideSize of [1, 2, 4]) {
@ -10299,14 +10326,14 @@ async function process3(res, inputSize4, outputShape, config3) {
if (score2 > config3.object.minConfidence && j !== 61) {
const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize;
const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize;
const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize4));
const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize5));
const [x, y] = [
cx - scaleBox2 / strideSize * boxOffset[0],
cy - scaleBox2 / strideSize * boxOffset[1]
cx - scaleBox / strideSize * boxOffset[0],
cy - scaleBox / strideSize * boxOffset[1]
];
const [w, h] = [
cx + scaleBox2 / strideSize * boxOffset[2] - x,
cy + scaleBox2 / strideSize * boxOffset[3] - y
cx + scaleBox / strideSize * boxOffset[2] - x,
cy + scaleBox / strideSize * boxOffset[3] - y
];
let boxRaw2 = [x, y, w, h];
boxRaw2 = boxRaw2.map((a) => Math.max(0, Math.min(a, 1)));
@ -10351,42 +10378,42 @@ async function predict10(image24, config3) {
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [image24.shape[2], image24.shape[1]];
const resize = tfjs_esm_exports.image.resizeBilinear(image24, [model7.inputSize, model7.inputSize], false);
const outputSize3 = [image24.shape[2], image24.shape[1]];
const resize = tfjs_esm_exports.image.resizeBilinear(image24, [model6.inputSize, model6.inputSize], false);
const norm = tfjs_esm_exports.div(resize, 255);
const transpose = norm.transpose([0, 3, 1, 2]);
tfjs_esm_exports.dispose(norm);
tfjs_esm_exports.dispose(resize);
let objectT;
if (config3.object.enabled)
objectT = await model7.predict(transpose);
objectT = await model6.predict(transpose);
tfjs_esm_exports.dispose(transpose);
const obj = await process3(objectT, model7.inputSize, outputSize2, config3);
const obj = await process3(objectT, model6.inputSize, outputSize3, config3);
last3 = obj;
resolve(obj);
});
}
// src/object/centernet.ts
var model8;
var inputSize3 = 0;
var model7;
var inputSize4 = 0;
var last4 = [];
var skipped7 = Number.MAX_SAFE_INTEGER;
async function load11(config3) {
async function load10(config3) {
if (env.initial)
model8 = null;
if (!model8) {
model7 = null;
if (!model7) {
fakeOps(["floormod"], config3);
model8 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model8.modelSignature["inputs"]);
inputSize3 = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!model8 || !model8["modelUrl"])
model7 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model7.modelSignature["inputs"]);
inputSize4 = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!model7 || !model7["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model8["modelUrl"]);
log("load model:", model7["modelUrl"]);
} else if (config3.debug)
log("cached model:", model8["modelUrl"]);
return model8;
log("cached model:", model7["modelUrl"]);
return model7;
}
async function process4(res, outputShape, config3) {
if (!res)
@ -10415,14 +10442,14 @@ async function process4(res, outputShape, config3) {
const classVal = detections[0][id][5];
const label = labels[classVal].label;
const [x, y] = [
detections[0][id][0] / inputSize3,
detections[0][id][1] / inputSize3
detections[0][id][0] / inputSize4,
detections[0][id][1] / inputSize4
];
const boxRaw2 = [
x,
y,
detections[0][id][2] / inputSize3 - x,
detections[0][id][3] / inputSize3 - y
detections[0][id][2] / inputSize4 - x,
detections[0][id][3] / inputSize4 - y
];
const box5 = [
Math.trunc(boxRaw2[0] * outputShape[0]),
@ -10443,47 +10470,47 @@ async function predict11(input, config3) {
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last4;
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 ? model8 == null ? void 0 : model8.execute(resize, ["tower_0/detections"]) : null;
const outputSize3 = [input.shape[2], input.shape[1]];
const resize = tfjs_esm_exports.image.resizeBilinear(input, [inputSize4, inputSize4]);
const objectT = config3.object.enabled ? model7 == null ? void 0 : model7.execute(resize, ["tower_0/detections"]) : null;
tfjs_esm_exports.dispose(resize);
const obj = await process4(objectT, outputSize2, config3);
const obj = await process4(objectT, outputSize3, config3);
last4 = obj;
resolve(obj);
});
}
// src/segmentation/segmentation.ts
var model9;
var model8;
var busy = false;
async function load12(config3) {
if (!model9 || env.initial) {
model9 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.segmentation.modelPath || ""));
if (!model9 || !model9["modelUrl"])
async function load11(config3) {
if (!model8 || env.initial) {
model8 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.segmentation.modelPath || ""));
if (!model8 || !model8["modelUrl"])
log("load model failed:", config3.segmentation.modelPath);
else if (config3.debug)
log("load model:", model9["modelUrl"]);
log("load model:", model8["modelUrl"]);
} else if (config3.debug)
log("cached model:", model9["modelUrl"]);
return model9;
log("cached model:", model8["modelUrl"]);
return model8;
}
async function process5(input, background, config3) {
var _a, _b;
if (busy)
return { data: [], canvas: null, alpha: null };
busy = true;
if (!model9)
await load12(config3);
if (!model8)
await load11(config3);
const inputImage = process2(input, config3);
const width = ((_a = inputImage.canvas) == null ? void 0 : _a.width) || 0;
const height = ((_b = inputImage.canvas) == null ? void 0 : _b.height) || 0;
if (!inputImage.tensor)
return { data: [], canvas: null, alpha: null };
const t = {};
t.resize = tfjs_esm_exports.image.resizeBilinear(inputImage.tensor, [model9.inputs[0].shape ? model9.inputs[0].shape[1] : 0, model9.inputs[0].shape ? model9.inputs[0].shape[2] : 0], false);
t.resize = tfjs_esm_exports.image.resizeBilinear(inputImage.tensor, [model8.inputs[0].shape ? model8.inputs[0].shape[1] : 0, model8.inputs[0].shape ? model8.inputs[0].shape[2] : 0], false);
tfjs_esm_exports.dispose(inputImage.tensor);
t.norm = tfjs_esm_exports.div(t.resize, 255);
t.res = model9.predict(t.norm);
t.res = model8.predict(t.norm);
t.squeeze = tfjs_esm_exports.squeeze(t.res, 0);
if (t.squeeze.shape[2] === 2) {
t.softmax = tfjs_esm_exports.softmax(t.squeeze);
@ -10536,21 +10563,21 @@ async function process5(input, background, config3) {
return { data, canvas: mergedCanvas || compositeCanvas, alpha: alphaCanvas };
}
// src/gear/agegenderrace.ts
var model10;
// src/gear/gear-agegenderrace.ts
var model9;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load13(config3) {
async function load12(config3) {
if (env.initial)
model10 = null;
if (!model10) {
model10 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.face.agegenderrace.modelPath));
if (!model10 || !model10["modelUrl"])
model9 = null;
if (!model9) {
model9 = await tfjs_esm_exports.loadGraphModel(join(config3.modelBasePath, config3.face.agegenderrace.modelPath));
if (!model9 || !model9["modelUrl"])
log("load model failed:", config3.face.agegenderrace.modelPath);
else if (config3.debug)
log("load model:", model10["modelUrl"]);
log("load model:", model9["modelUrl"]);
} else if (config3.debug)
log("cached model:", model10["modelUrl"]);
return model10;
log("cached model:", model9["modelUrl"]);
return model9;
}
// src/models.ts
@ -10558,6 +10585,7 @@ var Models = class {
constructor() {
__publicField(this, "age", null);
__publicField(this, "agegenderrace", null);
__publicField(this, "blazeposedetect", null);
__publicField(this, "blazepose", null);
__publicField(this, "centernet", null);
__publicField(this, "efficientpose", null);
@ -10578,11 +10606,11 @@ var Models = class {
}
};
function reset(instance) {
for (const model11 of Object.keys(instance.models))
instance.models[model11] = null;
for (const model10 of Object.keys(instance.models))
instance.models[model10] = null;
}
async function load14(instance) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A;
async function load13(instance) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A, _B, _C, _D;
if (env.initial)
reset(instance);
if (instance.config.face.enabled) {
@ -10606,48 +10634,50 @@ async function load14(instance) {
if (instance.config.body.enabled && !instance.models.posenet && ((_l = (_k = instance.config.body) == null ? void 0 : _k.modelPath) == null ? void 0 : _l.includes("posenet")))
instance.models.posenet = load5(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_n = (_m = instance.config.body) == null ? void 0 : _m.modelPath) == null ? void 0 : _n.includes("efficientpose")))
instance.models.efficientpose = load8(instance.config);
if (instance.config.body.enabled && !instance.models.blazepose && ((_p = (_o = instance.config.body) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("blazepose")))
instance.models.blazepose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_r = (_q = instance.config.body) == null ? void 0 : _q.modelPath) == null ? void 0 : _r.includes("efficientpose")))
instance.models.efficientpose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && ((_t = (_s = instance.config.body) == null ? void 0 : _s.modelPath) == null ? void 0 : _t.includes("movenet")))
instance.models.movenet = load9(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && ((_v = (_u = instance.config.object) == null ? void 0 : _u.modelPath) == null ? void 0 : _v.includes("nanodet")))
instance.models.nanodet = load10(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && ((_x = (_w = instance.config.object) == null ? void 0 : _w.modelPath) == null ? void 0 : _x.includes("centernet")))
instance.models.centernet = load11(instance.config);
if (instance.config.face.enabled && ((_y = instance.config.face.emotion) == null ? void 0 : _y.enabled) && !instance.models.emotion)
if (instance.config.body.enabled && !instance.models.blazepose && ((_p = (_o = instance.config.body) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("blazepose")))
instance.models.blazepose = loadPose(instance.config);
if (instance.config.body.enabled && !instance.models.blazeposedetect && ((_q = instance.config.body.detector) == null ? void 0 : _q.modelPath) && ((_s = (_r = instance.config.body) == null ? void 0 : _r.modelPath) == null ? void 0 : _s.includes("blazepose")))
instance.models.blazeposedetect = loadDetect2(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_u = (_t = instance.config.body) == null ? void 0 : _t.modelPath) == null ? void 0 : _u.includes("efficientpose")))
instance.models.efficientpose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && ((_w = (_v = instance.config.body) == null ? void 0 : _v.modelPath) == null ? void 0 : _w.includes("movenet")))
instance.models.movenet = load8(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && ((_y = (_x = instance.config.object) == null ? void 0 : _x.modelPath) == null ? void 0 : _y.includes("nanodet")))
instance.models.nanodet = load9(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && ((_A = (_z = instance.config.object) == null ? void 0 : _z.modelPath) == null ? void 0 : _A.includes("centernet")))
instance.models.centernet = load10(instance.config);
if (instance.config.face.enabled && ((_B = instance.config.face.emotion) == null ? void 0 : _B.enabled) && !instance.models.emotion)
instance.models.emotion = load4(instance.config);
if (instance.config.face.enabled && ((_z = instance.config.face.description) == null ? void 0 : _z.enabled) && !instance.models.faceres)
if (instance.config.face.enabled && ((_C = instance.config.face.description) == null ? void 0 : _C.enabled) && !instance.models.faceres)
instance.models.faceres = load3(instance.config);
if (instance.config.segmentation.enabled && !instance.models.segmentation)
instance.models.segmentation = load12(instance.config);
if (instance.config.face.enabled && ((_A = instance.config.face["agegenderrace"]) == null ? void 0 : _A.enabled) && !instance.models.agegenderrace)
instance.models.agegenderrace = load13(instance.config);
for await (const model11 of Object.keys(instance.models)) {
if (instance.models[model11] && typeof instance.models[model11] !== "undefined")
instance.models[model11] = await instance.models[model11];
instance.models.segmentation = load11(instance.config);
if (instance.config.face.enabled && ((_D = instance.config.face["agegenderrace"]) == null ? void 0 : _D.enabled) && !instance.models.agegenderrace)
instance.models.agegenderrace = load12(instance.config);
for await (const model10 of Object.keys(instance.models)) {
if (instance.models[model10] && typeof instance.models[model10] !== "undefined")
instance.models[model10] = await instance.models[model10];
}
}
async function validate2(instance) {
const simpleOps = ["const", "placeholder", "noop", "pad", "squeeze", "add", "sub", "mul", "div"];
for (const defined of Object.keys(instance.models)) {
if (instance.models[defined]) {
let models4 = [];
let models5 = [];
if (Array.isArray(instance.models[defined])) {
models4 = instance.models[defined].filter((model11) => model11 !== null).map((model11) => model11 && model11.executor ? model11 : model11.model);
models5 = instance.models[defined].filter((model10) => model10 !== null).map((model10) => model10 && model10.executor ? model10 : model10.model);
} else {
models4 = [instance.models[defined]];
models5 = [instance.models[defined]];
}
for (const model11 of models4) {
if (!model11) {
for (const model10 of models5) {
if (!model10) {
if (instance.config.debug)
log("model marked as loaded but not defined:", defined);
continue;
}
const ops = [];
const executor = model11 == null ? void 0 : model11.executor;
const executor = model10 == null ? void 0 : model10.executor;
if (executor && executor.graph.nodes) {
for (const kernel of Object.values(executor.graph.nodes)) {
const op = kernel.op.toLowerCase();
@ -10671,7 +10701,7 @@ async function validate2(instance) {
}
}
// src/face.ts
// src/face/face.ts
var calculateGaze = (face5) => {
const radians = (pt1, pt2) => Math.atan2(pt1[1] - pt2[1], pt1[0] - pt2[0]);
if (!face5.annotations["rightEyeIris"] || !face5.annotations["leftEyeIris"])
@ -10978,7 +11008,7 @@ var hand = (res) => {
return gestures;
};
// src/draw.ts
// src/util/draw.ts
var options2 = {
color: "rgba(173, 216, 230, 0.6)",
labelColor: "rgba(173, 216, 230, 1)",
@ -11524,7 +11554,7 @@ function join2(faces, bodies, hands, gestures, shape) {
return persons2;
}
// src/interpolate.ts
// src/util/interpolate.ts
var bufferedResult = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0 };
function calc(newResult) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u;
@ -12570,7 +12600,7 @@ var Human = class {
async load(userConfig) {
this.state = "load";
const timeStamp = now();
const count2 = Object.values(this.models).filter((model11) => model11).length;
const count2 = Object.values(this.models).filter((model10) => model10).length;
if (userConfig)
this.config = mergeDeep(this.config, userConfig);
if (env.initial) {
@ -12588,11 +12618,11 @@ var Human = class {
log("tf flags:", this.tf.ENV.flags);
}
}
await load14(this);
await load13(this);
if (env.initial && this.config.debug)
log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
env.initial = false;
const loaded = Object.values(this.models).filter((model11) => model11).length;
const loaded = Object.values(this.models).filter((model10) => model10).length;
if (loaded !== count2) {
await validate2(this);
this.emit("load");

6
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@ -89,7 +89,7 @@ __export(exports, {
env: () => env
});
// src/util.ts
// src/util/util.ts
function join(folder, file) {
const separator = folder.endsWith("/") ? "" : "/";
const skipJoin = file.startsWith(".") || file.startsWith("/") || file.startsWith("http:") || file.startsWith("https:") || file.startsWith("file:");
@ -142,31 +142,6 @@ function mergeDeep(...objects) {
return prev;
}, {});
}
function scaleBox(keypoints3, boxScaleFact2, outputSize2) {
const coords3 = [keypoints3.map((pt) => pt[0]), keypoints3.map((pt) => pt[1])];
const maxmin = [Math.max(...coords3[0]), Math.min(...coords3[0]), Math.max(...coords3[1]), Math.min(...coords3[1])];
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2];
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact2;
const box5 = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff)
];
const boxRaw2 = [
box5[0] / outputSize2[0],
box5[1] / outputSize2[1],
box5[2] / outputSize2[0],
box5[3] / outputSize2[1]
];
const yxBox = [
boxRaw2[1],
boxRaw2[0],
boxRaw2[3] + boxRaw2[1],
boxRaw2[2] + boxRaw2[0]
];
return { box: box5, boxRaw: boxRaw2, yxBox };
}
// src/config.ts
var config = {
@ -236,6 +211,9 @@ var config = {
body: {
enabled: true,
modelPath: "movenet-lightning.json",
detector: {
modelPath: ""
},
maxDetected: -1,
minConfidence: 0.2,
skipFrames: 1
@ -403,13 +381,13 @@ function rotatePoint(homogeneousCoordinate, rotationMatrix) {
dot(homogeneousCoordinate, rotationMatrix[1])
];
}
function generateAnchors(inputSize4) {
const spec = { strides: [inputSize4 / 16, inputSize4 / 8], anchors: [2, 6] };
function generateAnchors(inputSize5) {
const spec = { strides: [inputSize5 / 16, inputSize5 / 8], anchors: [2, 6] };
const anchors3 = [];
for (let i = 0; i < spec.strides.length; i++) {
const stride = spec.strides[i];
const gridRows = Math.floor((inputSize4 + stride - 1) / stride);
const gridCols = Math.floor((inputSize4 + stride - 1) / stride);
const gridRows = Math.floor((inputSize5 + stride - 1) / stride);
const gridCols = Math.floor((inputSize5 + stride - 1) / stride);
const anchorsNum = spec.anchors[i];
for (let gridY = 0; gridY < gridRows; gridY++) {
const anchorY = stride * (gridY + 0.5);
@ -426,31 +404,31 @@ function generateAnchors(inputSize4) {
// src/blazeface/blazeface.ts
var keypointsCount = 6;
function decodeBounds(boxOutputs, anchors3, inputSize4) {
function decodeBounds(boxOutputs, anchors3, inputSize5) {
const boxStarts = tf2.slice(boxOutputs, [0, 1], [-1, 2]);
const centers = tf2.add(boxStarts, anchors3);
const boxSizes = tf2.slice(boxOutputs, [0, 3], [-1, 2]);
const boxSizesNormalized = tf2.div(boxSizes, inputSize4);
const centersNormalized = tf2.div(centers, inputSize4);
const boxSizesNormalized = tf2.div(boxSizes, inputSize5);
const centersNormalized = tf2.div(centers, inputSize5);
const halfBoxSize = tf2.div(boxSizesNormalized, 2);
const starts = tf2.sub(centersNormalized, halfBoxSize);
const ends = tf2.add(centersNormalized, halfBoxSize);
const startNormalized = tf2.mul(starts, inputSize4);
const endNormalized = tf2.mul(ends, inputSize4);
const startNormalized = tf2.mul(starts, inputSize5);
const endNormalized = tf2.mul(ends, inputSize5);
const concatAxis = 1;
return tf2.concat2d([startNormalized, endNormalized], concatAxis);
}
var BlazeFaceModel = class {
constructor(model11, config3) {
constructor(model10, config3) {
__publicField(this, "model");
__publicField(this, "anchorsData");
__publicField(this, "anchors");
__publicField(this, "inputSize");
__publicField(this, "config");
this.model = model11;
this.anchorsData = generateAnchors(model11.inputs[0].shape[1]);
this.model = model10;
this.anchorsData = generateAnchors(model10.inputs[0].shape[1]);
this.anchors = tf2.tensor2d(this.anchorsData);
this.inputSize = model11.inputs[0].shape[2];
this.inputSize = model10.inputs[0].shape[2];
this.config = config3;
}
async getBoundingBoxes(inputImage, userConfig) {
@ -502,12 +480,12 @@ var BlazeFaceModel = class {
};
async function load(config3) {
var _a, _b, _c;
const model11 = await tf2.loadGraphModel(join(config3.modelBasePath, ((_a = config3.face.detector) == null ? void 0 : _a.modelPath) || ""), { fromTFHub: (((_b = config3.face.detector) == null ? void 0 : _b.modelPath) || "").includes("tfhub.dev") });
const blazeFace = new BlazeFaceModel(model11, config3);
if (!model11 || !model11.modelUrl)
const model10 = await tf2.loadGraphModel(join(config3.modelBasePath, ((_a = config3.face.detector) == null ? void 0 : _a.modelPath) || ""), { fromTFHub: (((_b = config3.face.detector) == null ? void 0 : _b.modelPath) || "").includes("tfhub.dev") });
const blazeFace = new BlazeFaceModel(model10, config3);
if (!model10 || !model10.modelUrl)
log("load model failed:", ((_c = config3.face.detector) == null ? void 0 : _c.modelPath) || "");
else if (config3.debug)
log("load model:", model11.modelUrl);
log("load model:", model10.modelUrl);
return blazeFace;
}
@ -3783,7 +3761,7 @@ var UV68 = VTX68.map((x) => UV468[x]);
var UV33 = VTX33.map((x) => UV468[x]);
var UV7 = VTX7.map((x) => UV468[x]);
// src/env.ts
// src/util/env.ts
var tf4 = __toModule(require_tfjs_esm());
// src/image/image.ts
@ -4703,7 +4681,7 @@ async function skip(config3, input) {
return skipFrame;
}
// src/env.ts
// src/util/env.ts
var env = {
browser: void 0,
node: void 0,
@ -5164,7 +5142,7 @@ async function load2(config3) {
var triangulation = TRI468;
var uvmap = UV468;
// src/faceres/faceres.ts
// src/face/faceres.ts
var tf7 = __toModule(require_tfjs_esm());
var model;
var last = [];
@ -5268,7 +5246,7 @@ async function predict2(image24, config3, idx, count2) {
});
}
// src/emotion/emotion.ts
// src/gear/emotion.ts
var tf8 = __toModule(require_tfjs_esm());
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model2;
@ -8689,14 +8667,14 @@ var anchors = [
// src/handpose/handdetector.ts
var HandDetector = class {
constructor(model11) {
constructor(model10) {
__publicField(this, "model");
__publicField(this, "anchors");
__publicField(this, "anchorsTensor");
__publicField(this, "inputSize");
__publicField(this, "inputSizeTensor");
__publicField(this, "doubleInputSizeTensor");
this.model = model11;
this.model = model10;
this.anchors = anchors.map((anchor) => [anchor.x, anchor.y]);
this.anchorsTensor = tf11.tensor2d(this.anchors);
this.inputSize = this.model && this.model.inputs && this.model.inputs[0].shape ? this.model.inputs[0].shape[2] : 0;
@ -9455,7 +9433,34 @@ async function load6(config3) {
return [handDetectorModel, handPoseModel];
}
// src/handtrack/handtrack.ts
// src/util/box.ts
function scale(keypoints3, boxScaleFact2, outputSize3) {
const coords3 = [keypoints3.map((pt) => pt[0]), keypoints3.map((pt) => pt[1])];
const maxmin = [Math.max(...coords3[0]), Math.min(...coords3[0]), Math.max(...coords3[1]), Math.min(...coords3[1])];
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2];
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact2;
const box5 = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff)
];
const boxRaw2 = [
box5[0] / outputSize3[0],
box5[1] / outputSize3[1],
box5[2] / outputSize3[0],
box5[3] / outputSize3[1]
];
const yxBox = [
boxRaw2[1],
boxRaw2[0],
boxRaw2[3] + boxRaw2[1],
boxRaw2[2] + boxRaw2[0]
];
return { box: box5, boxRaw: boxRaw2, yxBox };
}
// src/hand/handtrack.ts
var tf16 = __toModule(require_tfjs_esm());
// src/tfjs/humangl.ts
@ -9662,7 +9667,7 @@ function fakeOps(kernelNames, config3) {
env.kernels = tf15.getKernelsForBackend(tf15.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());
}
// src/handtrack/handtrack.ts
// src/hand/handtrack.ts
var boxScaleFact = 1.5;
var models2 = [null, null];
var modelOutputNodes = ["StatefulPartitionedCall/Postprocessor/Slice", "StatefulPartitionedCall/Postprocessor/ExpandDims_1"];
@ -9800,7 +9805,7 @@ async function detectFingers(input, h, config3) {
h.box[3] * coord[1] / inputSize[1][1] + h.box[1],
(h.box[2] + h.box[3]) / 2 / inputSize[1][0] * coord[2]
]);
const updatedBox = scaleBox(hand3.keypoints, boxScaleFact, outputSize);
const updatedBox = scale(hand3.keypoints, boxScaleFact, outputSize);
h.box = updatedBox.box;
h.boxRaw = updatedBox.boxRaw;
h.yxBox = updatedBox.yxBox;
@ -9837,10 +9842,10 @@ async function predict6(input, config3) {
return hands;
}
// src/blazepose/blazepose.ts
// src/body/blazepose.ts
var tf17 = __toModule(require_tfjs_esm());
// src/blazepose/annotations.ts
// src/body/annotations.ts
var full = [
"nose",
"leftEyeInside",
@ -9916,57 +9921,71 @@ var upper = [
"right:30"
];
// src/blazepose/blazepose.ts
var model4;
async function load7(config3) {
// src/body/blazepose.ts
var models3 = [null, null];
var outputNodes = ["ld_3d", "activation_segmentation", "activation_heatmap", "world_3d", "output_poseflag"];
var inputSize2 = [[0, 0], [0, 0]];
var outputSize2 = [0, 0];
async function loadDetect2(config3) {
var _a;
if (env.initial)
model4 = null;
if (!model4) {
model4 = await tf17.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
model4["width"] = parseInt(model4["signature"].inputs["input_1:0"].tensorShape.dim[2].size);
model4["height"] = parseInt(model4["signature"].inputs["input_1:0"].tensorShape.dim[1].size);
if (!model4 || !model4["modelUrl"])
log("load model failed:", config3.body.modelPath);
models3[0] = null;
if (!models3[0]) {
models3[0] = await tf17.loadGraphModel(join(config3.modelBasePath, ((_a = config3.body.detector) == null ? void 0 : _a.modelPath) || ""));
const inputs = Object.values(models3[0].modelSignature["inputs"]);
inputSize2[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize2[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models3[0] || !models3[0]["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model4["modelUrl"]);
log("load model:", models3[0]["modelUrl"]);
} else if (config3.debug)
log("cached model:", model4["modelUrl"]);
return model4;
log("cached model:", models3[0]["modelUrl"]);
return models3[0];
}
async function predict7(image24, config3) {
if (!model4)
return [];
if (!config3.body.enabled)
return [];
const imgSize = { width: image24.shape[2] || 0, height: image24.shape[1] || 0 };
const resize = tf17.image.resizeBilinear(image24, [model4["width"], model4["height"]], false);
const normalize = tf17.div(resize, [255]);
tf17.dispose(resize);
const resT = await model4.predict(normalize);
const findT = resT.find((t) => t.size === 195 || t.size === 155);
const points = await (findT == null ? void 0 : findT.data()) || [];
resT.forEach((t) => tf17.dispose(t));
tf17.dispose(normalize);
async function loadPose(config3) {
if (env.initial)
models3[1] = null;
if (!models3[1]) {
models3[1] = await tf17.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
const inputs = Object.values(models3[1].modelSignature["inputs"]);
inputSize2[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize2[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models3[1] || !models3[1]["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", models3[1]["modelUrl"]);
} else if (config3.debug)
log("cached model:", models3[1]["modelUrl"]);
return models3[1];
}
async function detectParts(input, config3) {
var _a;
const t = {};
t.resize = tf17.image.resizeBilinear(input, [inputSize2[1][0], inputSize2[1][1]]);
[t.ld, t.segmentation, t.heatmap, t.world, t.poseflag] = await ((_a = models3[1]) == null ? void 0 : _a.execute(t.resize, outputNodes));
const points = await t.ld.data();
const keypoints3 = [];
const labels2 = (points == null ? void 0 : points.length) === 195 ? full : upper;
const depth = 5;
for (let i = 0; i < points.length / depth; i++) {
keypoints3.push({
id: i,
part: labels2[i],
position: [
Math.trunc(imgSize.width * points[depth * i + 0] / 255),
Math.trunc(imgSize.height * points[depth * i + 1] / 255),
Math.trunc(points[depth * i + 2]) + 0
],
positionRaw: [
points[depth * i + 0] / 255,
points[depth * i + 1] / 255,
points[depth * i + 2] + 0
],
score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100,
presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100
});
const score3 = (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100;
if (score3 > (config3.body.minConfidence || 0)) {
keypoints3.push({
part: labels2[i],
position: [
Math.trunc(outputSize2[0] * points[depth * i + 0] / 255),
Math.trunc(outputSize2[1] * points[depth * i + 1] / 255),
Math.trunc(points[depth * i + 2]) + 0
],
positionRaw: [
points[depth * i + 0] / 255,
points[depth * i + 1] / 255,
points[depth * i + 2] + 0
],
score: score3
});
}
}
const x = keypoints3.map((a) => a.position[0]);
const y = keypoints3.map((a) => a.position[1]);
@ -9978,30 +9997,38 @@ async function predict7(image24, config3) {
];
const boxRaw2 = [0, 0, 0, 0];
const score2 = keypoints3.reduce((prev, curr) => curr.score > prev ? curr.score : prev, 0);
return [{ id: 0, score: score2, box: box5, boxRaw: boxRaw2, keypoints: keypoints3 }];
Object.keys(t).forEach((tensor3) => tf17.dispose(t[tensor3]));
return { id: 0, score: score2, box: box5, boxRaw: boxRaw2, keypoints: keypoints3 };
}
async function predict7(input, config3) {
outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
const bodies = [];
const body4 = await detectParts(input, config3);
bodies.push(body4);
return bodies;
}
// src/efficientpose/efficientpose.ts
// src/body/efficientpose.ts
var tf18 = __toModule(require_tfjs_esm());
var model5;
var model4;
var keypoints = [];
var box4 = [0, 0, 0, 0];
var boxRaw = [0, 0, 0, 0];
var score = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
var bodyParts = ["head", "neck", "rightShoulder", "rightElbow", "rightWrist", "chest", "leftShoulder", "leftElbow", "leftWrist", "pelvis", "rightHip", "rightKnee", "rightAnkle", "leftHip", "leftKnee", "leftAnkle"];
async function load8(config3) {
async function load7(config3) {
if (env.initial)
model5 = null;
if (!model5) {
model5 = await tf18.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model5 || !model5["modelUrl"])
model4 = null;
if (!model4) {
model4 = await tf18.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model4 || !model4["modelUrl"])
log("load model failed:", config3.body.modelPath);
else if (config3.debug)
log("load model:", model5["modelUrl"]);
log("load model:", model4["modelUrl"]);
} else if (config3.debug)
log("cached model:", model5["modelUrl"]);
return model5;
log("cached model:", model4["modelUrl"]);
return model4;
}
function max2d(inputs, minScore) {
const [width, height] = inputs.shape;
@ -10028,16 +10055,16 @@ async function predict8(image24, config3) {
return new Promise(async (resolve) => {
var _a2;
const tensor3 = tf18.tidy(() => {
if (!(model5 == null ? void 0 : model5.inputs[0].shape))
if (!(model4 == null ? void 0 : model4.inputs[0].shape))
return null;
const resize = tf18.image.resizeBilinear(image24, [model5.inputs[0].shape[2], model5.inputs[0].shape[1]], false);
const resize = tf18.image.resizeBilinear(image24, [model4.inputs[0].shape[2], model4.inputs[0].shape[1]], false);
const enhance2 = tf18.mul(resize, 2);
const norm = enhance2.sub(1);
return norm;
});
let resT;
if (config3.body.enabled)
resT = await (model5 == null ? void 0 : model5.predict(tensor3));
resT = await (model4 == null ? void 0 : model4.predict(tensor3));
tf18.dispose(tensor3);
if (resT) {
keypoints.length = 0;
@ -10052,12 +10079,12 @@ async function predict8(image24, config3) {
score: Math.round(100 * partScore) / 100,
part: bodyParts[id],
positionRaw: [
x2 / model5.inputs[0].shape[2],
y2 / model5.inputs[0].shape[1]
x2 / model4.inputs[0].shape[2],
y2 / model4.inputs[0].shape[1]
],
position: [
Math.round(image24.shape[2] * x2 / model5.inputs[0].shape[2]),
Math.round(image24.shape[1] * y2 / model5.inputs[0].shape[1])
Math.round(image24.shape[2] * x2 / model4.inputs[0].shape[2]),
Math.round(image24.shape[1] * y2 / model4.inputs[0].shape[1])
]
});
}
@ -10085,30 +10112,30 @@ async function predict8(image24, config3) {
});
}
// src/movenet/movenet.ts
// src/body/movenet.ts
var tf19 = __toModule(require_tfjs_esm());
var model6;
var inputSize2 = 0;
var model5;
var inputSize3 = 0;
var cachedBoxes = [];
var skipped5 = Number.MAX_SAFE_INTEGER;
var keypoints2 = [];
var bodyParts2 = ["nose", "leftEye", "rightEye", "leftEar", "rightEar", "leftShoulder", "rightShoulder", "leftElbow", "rightElbow", "leftWrist", "rightWrist", "leftHip", "rightHip", "leftKnee", "rightKnee", "leftAnkle", "rightAnkle"];
async function load9(config3) {
async function load8(config3) {
if (env.initial)
model6 = null;
if (!model6) {
model5 = null;
if (!model5) {
fakeOps(["size"], config3);
model6 = await tf19.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model6 || !model6["modelUrl"])
model5 = await tf19.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model5 || !model5["modelUrl"])
log("load model failed:", config3.body.modelPath);
else if (config3.debug)
log("load model:", model6["modelUrl"]);
log("load model:", model5["modelUrl"]);
} else if (config3.debug)
log("cached model:", model6["modelUrl"]);
inputSize2 = model6.inputs[0].shape ? model6.inputs[0].shape[2] : 0;
if (inputSize2 === -1)
inputSize2 = 256;
return model6;
log("cached model:", model5["modelUrl"]);
inputSize3 = model5.inputs[0].shape ? model5.inputs[0].shape[2] : 0;
if (inputSize3 === -1)
inputSize3 = 256;
return model5;
}
async function parseSinglePose(res, config3, image24, inputBox) {
const kpt3 = res[0][0];
@ -10193,7 +10220,7 @@ async function parseMultiPose(res, config3, image24, inputBox) {
return bodies;
}
async function predict9(input, config3) {
if (!model6 || !(model6 == null ? void 0 : model6.inputs[0].shape))
if (!model5 || !(model5 == null ? void 0 : model5.inputs[0].shape))
return [];
return new Promise(async (resolve) => {
const t = {};
@ -10202,18 +10229,18 @@ async function predict9(input, config3) {
cachedBoxes.length = 0;
skipped5++;
for (let i = 0; i < cachedBoxes.length; i++) {
t.crop = tf19.image.cropAndResize(input, [cachedBoxes[i]], [0], [inputSize2, inputSize2], "bilinear");
t.crop = tf19.image.cropAndResize(input, [cachedBoxes[i]], [0], [inputSize3, inputSize3], "bilinear");
t.cast = tf19.cast(t.crop, "int32");
t.res = await (model6 == null ? void 0 : model6.predict(t.cast));
t.res = await (model5 == null ? void 0 : model5.predict(t.cast));
const res = await t.res.array();
const newBodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, cachedBoxes[i]) : await parseMultiPose(res, config3, input, cachedBoxes[i]);
bodies = bodies.concat(newBodies);
Object.keys(t).forEach((tensor3) => tf19.dispose(t[tensor3]));
}
if (bodies.length !== config3.body.maxDetected && skipped5 > (config3.body.skipFrames || 0)) {
t.resized = tf19.image.resizeBilinear(input, [inputSize2, inputSize2], false);
t.resized = tf19.image.resizeBilinear(input, [inputSize3, inputSize3], false);
t.cast = tf19.cast(t.resized, "int32");
t.res = await (model6 == null ? void 0 : model6.predict(t.cast));
t.res = await (model5 == null ? void 0 : model5.predict(t.cast));
const res = await t.res.array();
bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input, [0, 0, 1, 1]);
Object.keys(t).forEach((tensor3) => tf19.dispose(t[tensor3]));
@ -10225,7 +10252,7 @@ async function predict9(input, config3) {
for (let i = 0; i < bodies.length; i++) {
if (bodies[i].keypoints.length > 10) {
const kpts = bodies[i].keypoints.map((kpt3) => kpt3.position);
const newBox = scaleBox(kpts, 1.5, [input.shape[2], input.shape[1]]);
const newBox = scale(kpts, 1.5, [input.shape[2], input.shape[1]]);
cachedBoxes.push([...newBox.yxBox]);
}
}
@ -10322,26 +10349,26 @@ var labels = [
];
// src/object/nanodet.ts
var model7;
var model6;
var last3 = [];
var skipped6 = Number.MAX_SAFE_INTEGER;
var scaleBox2 = 2.5;
async function load10(config3) {
if (!model7 || env.initial) {
model7 = await tf20.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model7.modelSignature["inputs"]);
model7.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
if (!model7.inputSize)
var scaleBox = 2.5;
async function load9(config3) {
if (!model6 || env.initial) {
model6 = await tf20.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model6.modelSignature["inputs"]);
model6.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
if (!model6.inputSize)
throw new Error(`cannot determine model inputSize: ${config3.object.modelPath}`);
if (!model7 || !model7.modelUrl)
if (!model6 || !model6.modelUrl)
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model7.modelUrl);
log("load model:", model6.modelUrl);
} else if (config3.debug)
log("cached model:", model7.modelUrl);
return model7;
log("cached model:", model6.modelUrl);
return model6;
}
async function process3(res, inputSize4, outputShape, config3) {
async function process3(res, inputSize5, outputShape, config3) {
let id = 0;
let results = [];
for (const strideSize of [1, 2, 4]) {
@ -10359,14 +10386,14 @@ async function process3(res, inputSize4, outputShape, config3) {
if (score2 > config3.object.minConfidence && j !== 61) {
const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize;
const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize;
const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize4));
const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize5));
const [x, y] = [
cx - scaleBox2 / strideSize * boxOffset[0],
cy - scaleBox2 / strideSize * boxOffset[1]
cx - scaleBox / strideSize * boxOffset[0],
cy - scaleBox / strideSize * boxOffset[1]
];
const [w, h] = [
cx + scaleBox2 / strideSize * boxOffset[2] - x,
cy + scaleBox2 / strideSize * boxOffset[3] - y
cx + scaleBox / strideSize * boxOffset[2] - x,
cy + scaleBox / strideSize * boxOffset[3] - y
];
let boxRaw2 = [x, y, w, h];
boxRaw2 = boxRaw2.map((a) => Math.max(0, Math.min(a, 1)));
@ -10411,17 +10438,17 @@ async function predict10(image24, config3) {
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [image24.shape[2], image24.shape[1]];
const resize = tf20.image.resizeBilinear(image24, [model7.inputSize, model7.inputSize], false);
const outputSize3 = [image24.shape[2], image24.shape[1]];
const resize = tf20.image.resizeBilinear(image24, [model6.inputSize, model6.inputSize], false);
const norm = tf20.div(resize, 255);
const transpose = norm.transpose([0, 3, 1, 2]);
tf20.dispose(norm);
tf20.dispose(resize);
let objectT;
if (config3.object.enabled)
objectT = await model7.predict(transpose);
objectT = await model6.predict(transpose);
tf20.dispose(transpose);
const obj = await process3(objectT, model7.inputSize, outputSize2, config3);
const obj = await process3(objectT, model6.inputSize, outputSize3, config3);
last3 = obj;
resolve(obj);
});
@ -10429,25 +10456,25 @@ async function predict10(image24, config3) {
// src/object/centernet.ts
var tf21 = __toModule(require_tfjs_esm());
var model8;
var inputSize3 = 0;
var model7;
var inputSize4 = 0;
var last4 = [];
var skipped7 = Number.MAX_SAFE_INTEGER;
async function load11(config3) {
async function load10(config3) {
if (env.initial)
model8 = null;
if (!model8) {
model7 = null;
if (!model7) {
fakeOps(["floormod"], config3);
model8 = await tf21.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model8.modelSignature["inputs"]);
inputSize3 = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!model8 || !model8["modelUrl"])
model7 = await tf21.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model7.modelSignature["inputs"]);
inputSize4 = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!model7 || !model7["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model8["modelUrl"]);
log("load model:", model7["modelUrl"]);
} else if (config3.debug)
log("cached model:", model8["modelUrl"]);
return model8;
log("cached model:", model7["modelUrl"]);
return model7;
}
async function process4(res, outputShape, config3) {
if (!res)
@ -10476,14 +10503,14 @@ async function process4(res, outputShape, config3) {
const classVal = detections[0][id][5];
const label = labels[classVal].label;
const [x, y] = [
detections[0][id][0] / inputSize3,
detections[0][id][1] / inputSize3
detections[0][id][0] / inputSize4,
detections[0][id][1] / inputSize4
];
const boxRaw2 = [
x,
y,
detections[0][id][2] / inputSize3 - x,
detections[0][id][3] / inputSize3 - y
detections[0][id][2] / inputSize4 - x,
detections[0][id][3] / inputSize4 - y
];
const box5 = [
Math.trunc(boxRaw2[0] * outputShape[0]),
@ -10504,11 +10531,11 @@ async function predict11(input, config3) {
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last4;
return new Promise(async (resolve) => {
const outputSize2 = [input.shape[2], input.shape[1]];
const resize = tf21.image.resizeBilinear(input, [inputSize3, inputSize3]);
const objectT = config3.object.enabled ? model8 == null ? void 0 : model8.execute(resize, ["tower_0/detections"]) : null;
const outputSize3 = [input.shape[2], input.shape[1]];
const resize = tf21.image.resizeBilinear(input, [inputSize4, inputSize4]);
const objectT = config3.object.enabled ? model7 == null ? void 0 : model7.execute(resize, ["tower_0/detections"]) : null;
tf21.dispose(resize);
const obj = await process4(objectT, outputSize2, config3);
const obj = await process4(objectT, outputSize3, config3);
last4 = obj;
resolve(obj);
});
@ -10516,36 +10543,36 @@ async function predict11(input, config3) {
// src/segmentation/segmentation.ts
var tf22 = __toModule(require_tfjs_esm());
var model9;
var model8;
var busy = false;
async function load12(config3) {
if (!model9 || env.initial) {
model9 = await tf22.loadGraphModel(join(config3.modelBasePath, config3.segmentation.modelPath || ""));
if (!model9 || !model9["modelUrl"])
async function load11(config3) {
if (!model8 || env.initial) {
model8 = await tf22.loadGraphModel(join(config3.modelBasePath, config3.segmentation.modelPath || ""));
if (!model8 || !model8["modelUrl"])
log("load model failed:", config3.segmentation.modelPath);
else if (config3.debug)
log("load model:", model9["modelUrl"]);
log("load model:", model8["modelUrl"]);
} else if (config3.debug)
log("cached model:", model9["modelUrl"]);
return model9;
log("cached model:", model8["modelUrl"]);
return model8;
}
async function process5(input, background, config3) {
var _a, _b;
if (busy)
return { data: [], canvas: null, alpha: null };
busy = true;
if (!model9)
await load12(config3);
if (!model8)
await load11(config3);
const inputImage = process2(input, config3);
const width = ((_a = inputImage.canvas) == null ? void 0 : _a.width) || 0;
const height = ((_b = inputImage.canvas) == null ? void 0 : _b.height) || 0;
if (!inputImage.tensor)
return { data: [], canvas: null, alpha: null };
const t = {};
t.resize = tf22.image.resizeBilinear(inputImage.tensor, [model9.inputs[0].shape ? model9.inputs[0].shape[1] : 0, model9.inputs[0].shape ? model9.inputs[0].shape[2] : 0], false);
t.resize = tf22.image.resizeBilinear(inputImage.tensor, [model8.inputs[0].shape ? model8.inputs[0].shape[1] : 0, model8.inputs[0].shape ? model8.inputs[0].shape[2] : 0], false);
tf22.dispose(inputImage.tensor);
t.norm = tf22.div(t.resize, 255);
t.res = model9.predict(t.norm);
t.res = model8.predict(t.norm);
t.squeeze = tf22.squeeze(t.res, 0);
if (t.squeeze.shape[2] === 2) {
t.softmax = tf22.softmax(t.squeeze);
@ -10598,22 +10625,22 @@ async function process5(input, background, config3) {
return { data, canvas: mergedCanvas || compositeCanvas, alpha: alphaCanvas };
}
// src/gear/agegenderrace.ts
// src/gear/gear-agegenderrace.ts
var tf23 = __toModule(require_tfjs_esm());
var model10;
var model9;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load13(config3) {
async function load12(config3) {
if (env.initial)
model10 = null;
if (!model10) {
model10 = await tf23.loadGraphModel(join(config3.modelBasePath, config3.face.agegenderrace.modelPath));
if (!model10 || !model10["modelUrl"])
model9 = null;
if (!model9) {
model9 = await tf23.loadGraphModel(join(config3.modelBasePath, config3.face.agegenderrace.modelPath));
if (!model9 || !model9["modelUrl"])
log("load model failed:", config3.face.agegenderrace.modelPath);
else if (config3.debug)
log("load model:", model10["modelUrl"]);
log("load model:", model9["modelUrl"]);
} else if (config3.debug)
log("cached model:", model10["modelUrl"]);
return model10;
log("cached model:", model9["modelUrl"]);
return model9;
}
// src/models.ts
@ -10621,6 +10648,7 @@ var Models = class {
constructor() {
__publicField(this, "age", null);
__publicField(this, "agegenderrace", null);
__publicField(this, "blazeposedetect", null);
__publicField(this, "blazepose", null);
__publicField(this, "centernet", null);
__publicField(this, "efficientpose", null);
@ -10641,11 +10669,11 @@ var Models = class {
}
};
function reset(instance) {
for (const model11 of Object.keys(instance.models))
instance.models[model11] = null;
for (const model10 of Object.keys(instance.models))
instance.models[model10] = null;
}
async function load14(instance) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A;
async function load13(instance) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A, _B, _C, _D;
if (env.initial)
reset(instance);
if (instance.config.face.enabled) {
@ -10669,48 +10697,50 @@ async function load14(instance) {
if (instance.config.body.enabled && !instance.models.posenet && ((_l = (_k = instance.config.body) == null ? void 0 : _k.modelPath) == null ? void 0 : _l.includes("posenet")))
instance.models.posenet = load5(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_n = (_m = instance.config.body) == null ? void 0 : _m.modelPath) == null ? void 0 : _n.includes("efficientpose")))
instance.models.efficientpose = load8(instance.config);
if (instance.config.body.enabled && !instance.models.blazepose && ((_p = (_o = instance.config.body) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("blazepose")))
instance.models.blazepose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_r = (_q = instance.config.body) == null ? void 0 : _q.modelPath) == null ? void 0 : _r.includes("efficientpose")))
instance.models.efficientpose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && ((_t = (_s = instance.config.body) == null ? void 0 : _s.modelPath) == null ? void 0 : _t.includes("movenet")))
instance.models.movenet = load9(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && ((_v = (_u = instance.config.object) == null ? void 0 : _u.modelPath) == null ? void 0 : _v.includes("nanodet")))
instance.models.nanodet = load10(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && ((_x = (_w = instance.config.object) == null ? void 0 : _w.modelPath) == null ? void 0 : _x.includes("centernet")))
instance.models.centernet = load11(instance.config);
if (instance.config.face.enabled && ((_y = instance.config.face.emotion) == null ? void 0 : _y.enabled) && !instance.models.emotion)
if (instance.config.body.enabled && !instance.models.blazepose && ((_p = (_o = instance.config.body) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("blazepose")))
instance.models.blazepose = loadPose(instance.config);
if (instance.config.body.enabled && !instance.models.blazeposedetect && ((_q = instance.config.body.detector) == null ? void 0 : _q.modelPath) && ((_s = (_r = instance.config.body) == null ? void 0 : _r.modelPath) == null ? void 0 : _s.includes("blazepose")))
instance.models.blazeposedetect = loadDetect2(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_u = (_t = instance.config.body) == null ? void 0 : _t.modelPath) == null ? void 0 : _u.includes("efficientpose")))
instance.models.efficientpose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && ((_w = (_v = instance.config.body) == null ? void 0 : _v.modelPath) == null ? void 0 : _w.includes("movenet")))
instance.models.movenet = load8(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && ((_y = (_x = instance.config.object) == null ? void 0 : _x.modelPath) == null ? void 0 : _y.includes("nanodet")))
instance.models.nanodet = load9(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && ((_A = (_z = instance.config.object) == null ? void 0 : _z.modelPath) == null ? void 0 : _A.includes("centernet")))
instance.models.centernet = load10(instance.config);
if (instance.config.face.enabled && ((_B = instance.config.face.emotion) == null ? void 0 : _B.enabled) && !instance.models.emotion)
instance.models.emotion = load4(instance.config);
if (instance.config.face.enabled && ((_z = instance.config.face.description) == null ? void 0 : _z.enabled) && !instance.models.faceres)
if (instance.config.face.enabled && ((_C = instance.config.face.description) == null ? void 0 : _C.enabled) && !instance.models.faceres)
instance.models.faceres = load3(instance.config);
if (instance.config.segmentation.enabled && !instance.models.segmentation)
instance.models.segmentation = load12(instance.config);
if (instance.config.face.enabled && ((_A = instance.config.face["agegenderrace"]) == null ? void 0 : _A.enabled) && !instance.models.agegenderrace)
instance.models.agegenderrace = load13(instance.config);
for await (const model11 of Object.keys(instance.models)) {
if (instance.models[model11] && typeof instance.models[model11] !== "undefined")
instance.models[model11] = await instance.models[model11];
instance.models.segmentation = load11(instance.config);
if (instance.config.face.enabled && ((_D = instance.config.face["agegenderrace"]) == null ? void 0 : _D.enabled) && !instance.models.agegenderrace)
instance.models.agegenderrace = load12(instance.config);
for await (const model10 of Object.keys(instance.models)) {
if (instance.models[model10] && typeof instance.models[model10] !== "undefined")
instance.models[model10] = await instance.models[model10];
}
}
async function validate2(instance) {
const simpleOps = ["const", "placeholder", "noop", "pad", "squeeze", "add", "sub", "mul", "div"];
for (const defined of Object.keys(instance.models)) {
if (instance.models[defined]) {
let models4 = [];
let models5 = [];
if (Array.isArray(instance.models[defined])) {
models4 = instance.models[defined].filter((model11) => model11 !== null).map((model11) => model11 && model11.executor ? model11 : model11.model);
models5 = instance.models[defined].filter((model10) => model10 !== null).map((model10) => model10 && model10.executor ? model10 : model10.model);
} else {
models4 = [instance.models[defined]];
models5 = [instance.models[defined]];
}
for (const model11 of models4) {
if (!model11) {
for (const model10 of models5) {
if (!model10) {
if (instance.config.debug)
log("model marked as loaded but not defined:", defined);
continue;
}
const ops = [];
const executor = model11 == null ? void 0 : model11.executor;
const executor = model10 == null ? void 0 : model10.executor;
if (executor && executor.graph.nodes) {
for (const kernel of Object.values(executor.graph.nodes)) {
const op = kernel.op.toLowerCase();
@ -10734,7 +10764,7 @@ async function validate2(instance) {
}
}
// src/face.ts
// src/face/face.ts
var tf24 = __toModule(require_tfjs_esm());
var calculateGaze = (face5) => {
const radians = (pt1, pt2) => Math.atan2(pt1[1] - pt2[1], pt1[0] - pt2[0]);
@ -11042,7 +11072,7 @@ var hand = (res) => {
return gestures;
};
// src/draw.ts
// src/util/draw.ts
var options2 = {
color: "rgba(173, 216, 230, 0.6)",
labelColor: "rgba(173, 216, 230, 1)",
@ -11588,7 +11618,7 @@ function join2(faces, bodies, hands, gestures, shape) {
return persons2;
}
// src/interpolate.ts
// src/util/interpolate.ts
var bufferedResult = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0 };
function calc(newResult) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u;
@ -12635,7 +12665,7 @@ var Human = class {
async load(userConfig) {
this.state = "load";
const timeStamp = now();
const count2 = Object.values(this.models).filter((model11) => model11).length;
const count2 = Object.values(this.models).filter((model10) => model10).length;
if (userConfig)
this.config = mergeDeep(this.config, userConfig);
if (env.initial) {
@ -12653,11 +12683,11 @@ var Human = class {
log("tf flags:", this.tf.ENV.flags);
}
}
await load14(this);
await load13(this);
if (env.initial && this.config.debug)
log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
env.initial = false;
const loaded = Object.values(this.models).filter((model11) => model11).length;
const loaded = Object.values(this.models).filter((model10) => model10).length;
if (loaded !== count2) {
await validate2(this);
this.emit("load");

496
dist/human.node-wasm.js vendored
View File

@ -90,7 +90,7 @@ __export(exports, {
env: () => env
});
// src/util.ts
// src/util/util.ts
function join(folder, file) {
const separator = folder.endsWith("/") ? "" : "/";
const skipJoin = file.startsWith(".") || file.startsWith("/") || file.startsWith("http:") || file.startsWith("https:") || file.startsWith("file:");
@ -143,31 +143,6 @@ function mergeDeep(...objects) {
return prev;
}, {});
}
function scaleBox(keypoints3, boxScaleFact2, outputSize2) {
const coords3 = [keypoints3.map((pt) => pt[0]), keypoints3.map((pt) => pt[1])];
const maxmin = [Math.max(...coords3[0]), Math.min(...coords3[0]), Math.max(...coords3[1]), Math.min(...coords3[1])];
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2];
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact2;
const box5 = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff)
];
const boxRaw2 = [
box5[0] / outputSize2[0],
box5[1] / outputSize2[1],
box5[2] / outputSize2[0],
box5[3] / outputSize2[1]
];
const yxBox = [
boxRaw2[1],
boxRaw2[0],
boxRaw2[3] + boxRaw2[1],
boxRaw2[2] + boxRaw2[0]
];
return { box: box5, boxRaw: boxRaw2, yxBox };
}
// src/config.ts
var config = {
@ -237,6 +212,9 @@ var config = {
body: {
enabled: true,
modelPath: "movenet-lightning.json",
detector: {
modelPath: ""
},
maxDetected: -1,
minConfidence: 0.2,
skipFrames: 1
@ -404,13 +382,13 @@ function rotatePoint(homogeneousCoordinate, rotationMatrix) {
dot(homogeneousCoordinate, rotationMatrix[1])
];
}
function generateAnchors(inputSize4) {
const spec = { strides: [inputSize4 / 16, inputSize4 / 8], anchors: [2, 6] };
function generateAnchors(inputSize5) {
const spec = { strides: [inputSize5 / 16, inputSize5 / 8], anchors: [2, 6] };
const anchors3 = [];
for (let i = 0; i < spec.strides.length; i++) {
const stride = spec.strides[i];
const gridRows = Math.floor((inputSize4 + stride - 1) / stride);
const gridCols = Math.floor((inputSize4 + stride - 1) / stride);
const gridRows = Math.floor((inputSize5 + stride - 1) / stride);
const gridCols = Math.floor((inputSize5 + stride - 1) / stride);
const anchorsNum = spec.anchors[i];
for (let gridY = 0; gridY < gridRows; gridY++) {
const anchorY = stride * (gridY + 0.5);
@ -427,31 +405,31 @@ function generateAnchors(inputSize4) {
// src/blazeface/blazeface.ts
var keypointsCount = 6;
function decodeBounds(boxOutputs, anchors3, inputSize4) {
function decodeBounds(boxOutputs, anchors3, inputSize5) {
const boxStarts = tf2.slice(boxOutputs, [0, 1], [-1, 2]);
const centers = tf2.add(boxStarts, anchors3);
const boxSizes = tf2.slice(boxOutputs, [0, 3], [-1, 2]);
const boxSizesNormalized = tf2.div(boxSizes, inputSize4);
const centersNormalized = tf2.div(centers, inputSize4);
const boxSizesNormalized = tf2.div(boxSizes, inputSize5);
const centersNormalized = tf2.div(centers, inputSize5);
const halfBoxSize = tf2.div(boxSizesNormalized, 2);
const starts = tf2.sub(centersNormalized, halfBoxSize);
const ends = tf2.add(centersNormalized, halfBoxSize);
const startNormalized = tf2.mul(starts, inputSize4);
const endNormalized = tf2.mul(ends, inputSize4);
const startNormalized = tf2.mul(starts, inputSize5);
const endNormalized = tf2.mul(ends, inputSize5);
const concatAxis = 1;
return tf2.concat2d([startNormalized, endNormalized], concatAxis);
}
var BlazeFaceModel = class {
constructor(model11, config3) {
constructor(model10, config3) {
__publicField(this, "model");
__publicField(this, "anchorsData");
__publicField(this, "anchors");
__publicField(this, "inputSize");
__publicField(this, "config");
this.model = model11;
this.anchorsData = generateAnchors(model11.inputs[0].shape[1]);
this.model = model10;
this.anchorsData = generateAnchors(model10.inputs[0].shape[1]);
this.anchors = tf2.tensor2d(this.anchorsData);
this.inputSize = model11.inputs[0].shape[2];
this.inputSize = model10.inputs[0].shape[2];
this.config = config3;
}
async getBoundingBoxes(inputImage, userConfig) {
@ -503,12 +481,12 @@ var BlazeFaceModel = class {
};
async function load(config3) {
var _a, _b, _c;
const model11 = await tf2.loadGraphModel(join(config3.modelBasePath, ((_a = config3.face.detector) == null ? void 0 : _a.modelPath) || ""), { fromTFHub: (((_b = config3.face.detector) == null ? void 0 : _b.modelPath) || "").includes("tfhub.dev") });
const blazeFace = new BlazeFaceModel(model11, config3);
if (!model11 || !model11.modelUrl)
const model10 = await tf2.loadGraphModel(join(config3.modelBasePath, ((_a = config3.face.detector) == null ? void 0 : _a.modelPath) || ""), { fromTFHub: (((_b = config3.face.detector) == null ? void 0 : _b.modelPath) || "").includes("tfhub.dev") });
const blazeFace = new BlazeFaceModel(model10, config3);
if (!model10 || !model10.modelUrl)
log("load model failed:", ((_c = config3.face.detector) == null ? void 0 : _c.modelPath) || "");
else if (config3.debug)
log("load model:", model11.modelUrl);
log("load model:", model10.modelUrl);
return blazeFace;
}
@ -3784,7 +3762,7 @@ var UV68 = VTX68.map((x) => UV468[x]);
var UV33 = VTX33.map((x) => UV468[x]);
var UV7 = VTX7.map((x) => UV468[x]);
// src/env.ts
// src/util/env.ts
var tf4 = __toModule(require_tfjs_esm());
// src/image/image.ts
@ -4704,7 +4682,7 @@ async function skip(config3, input) {
return skipFrame;
}
// src/env.ts
// src/util/env.ts
var env = {
browser: void 0,
node: void 0,
@ -5165,7 +5143,7 @@ async function load2(config3) {
var triangulation = TRI468;
var uvmap = UV468;
// src/faceres/faceres.ts
// src/face/faceres.ts
var tf7 = __toModule(require_tfjs_esm());
var model;
var last = [];
@ -5269,7 +5247,7 @@ async function predict2(image24, config3, idx, count2) {
});
}
// src/emotion/emotion.ts
// src/gear/emotion.ts
var tf8 = __toModule(require_tfjs_esm());
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model2;
@ -8690,14 +8668,14 @@ var anchors = [
// src/handpose/handdetector.ts
var HandDetector = class {
constructor(model11) {
constructor(model10) {
__publicField(this, "model");
__publicField(this, "anchors");
__publicField(this, "anchorsTensor");
__publicField(this, "inputSize");
__publicField(this, "inputSizeTensor");
__publicField(this, "doubleInputSizeTensor");
this.model = model11;
this.model = model10;
this.anchors = anchors.map((anchor) => [anchor.x, anchor.y]);
this.anchorsTensor = tf11.tensor2d(this.anchors);
this.inputSize = this.model && this.model.inputs && this.model.inputs[0].shape ? this.model.inputs[0].shape[2] : 0;
@ -9456,7 +9434,34 @@ async function load6(config3) {
return [handDetectorModel, handPoseModel];
}
// src/handtrack/handtrack.ts
// src/util/box.ts
function scale(keypoints3, boxScaleFact2, outputSize3) {
const coords3 = [keypoints3.map((pt) => pt[0]), keypoints3.map((pt) => pt[1])];
const maxmin = [Math.max(...coords3[0]), Math.min(...coords3[0]), Math.max(...coords3[1]), Math.min(...coords3[1])];
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2];
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact2;
const box5 = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff)
];
const boxRaw2 = [
box5[0] / outputSize3[0],
box5[1] / outputSize3[1],
box5[2] / outputSize3[0],
box5[3] / outputSize3[1]
];
const yxBox = [
boxRaw2[1],
boxRaw2[0],
boxRaw2[3] + boxRaw2[1],
boxRaw2[2] + boxRaw2[0]
];
return { box: box5, boxRaw: boxRaw2, yxBox };
}
// src/hand/handtrack.ts
var tf16 = __toModule(require_tfjs_esm());
// src/tfjs/humangl.ts
@ -9663,7 +9668,7 @@ function fakeOps(kernelNames, config3) {
env.kernels = tf15.getKernelsForBackend(tf15.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());
}
// src/handtrack/handtrack.ts
// src/hand/handtrack.ts
var boxScaleFact = 1.5;
var models2 = [null, null];
var modelOutputNodes = ["StatefulPartitionedCall/Postprocessor/Slice", "StatefulPartitionedCall/Postprocessor/ExpandDims_1"];
@ -9801,7 +9806,7 @@ async function detectFingers(input, h, config3) {
h.box[3] * coord[1] / inputSize[1][1] + h.box[1],
(h.box[2] + h.box[3]) / 2 / inputSize[1][0] * coord[2]
]);
const updatedBox = scaleBox(hand3.keypoints, boxScaleFact, outputSize);
const updatedBox = scale(hand3.keypoints, boxScaleFact, outputSize);
h.box = updatedBox.box;
h.boxRaw = updatedBox.boxRaw;
h.yxBox = updatedBox.yxBox;
@ -9838,10 +9843,10 @@ async function predict6(input, config3) {
return hands;
}
// src/blazepose/blazepose.ts
// src/body/blazepose.ts
var tf17 = __toModule(require_tfjs_esm());
// src/blazepose/annotations.ts
// src/body/annotations.ts
var full = [
"nose",
"leftEyeInside",
@ -9917,57 +9922,71 @@ var upper = [
"right:30"
];
// src/blazepose/blazepose.ts
var model4;
async function load7(config3) {
// src/body/blazepose.ts
var models3 = [null, null];
var outputNodes = ["ld_3d", "activation_segmentation", "activation_heatmap", "world_3d", "output_poseflag"];
var inputSize2 = [[0, 0], [0, 0]];
var outputSize2 = [0, 0];
async function loadDetect2(config3) {
var _a;
if (env.initial)
model4 = null;
if (!model4) {
model4 = await tf17.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
model4["width"] = parseInt(model4["signature"].inputs["input_1:0"].tensorShape.dim[2].size);
model4["height"] = parseInt(model4["signature"].inputs["input_1:0"].tensorShape.dim[1].size);
if (!model4 || !model4["modelUrl"])
log("load model failed:", config3.body.modelPath);
models3[0] = null;
if (!models3[0]) {
models3[0] = await tf17.loadGraphModel(join(config3.modelBasePath, ((_a = config3.body.detector) == null ? void 0 : _a.modelPath) || ""));
const inputs = Object.values(models3[0].modelSignature["inputs"]);
inputSize2[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize2[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models3[0] || !models3[0]["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model4["modelUrl"]);
log("load model:", models3[0]["modelUrl"]);
} else if (config3.debug)
log("cached model:", model4["modelUrl"]);
return model4;
log("cached model:", models3[0]["modelUrl"]);
return models3[0];
}
async function predict7(image24, config3) {
if (!model4)
return [];
if (!config3.body.enabled)
return [];
const imgSize = { width: image24.shape[2] || 0, height: image24.shape[1] || 0 };
const resize = tf17.image.resizeBilinear(image24, [model4["width"], model4["height"]], false);
const normalize = tf17.div(resize, [255]);
tf17.dispose(resize);
const resT = await model4.predict(normalize);
const findT = resT.find((t) => t.size === 195 || t.size === 155);
const points = await (findT == null ? void 0 : findT.data()) || [];
resT.forEach((t) => tf17.dispose(t));
tf17.dispose(normalize);
async function loadPose(config3) {
if (env.initial)
models3[1] = null;
if (!models3[1]) {
models3[1] = await tf17.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
const inputs = Object.values(models3[1].modelSignature["inputs"]);
inputSize2[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize2[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models3[1] || !models3[1]["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", models3[1]["modelUrl"]);
} else if (config3.debug)
log("cached model:", models3[1]["modelUrl"]);
return models3[1];
}
async function detectParts(input, config3) {
var _a;
const t = {};
t.resize = tf17.image.resizeBilinear(input, [inputSize2[1][0], inputSize2[1][1]]);
[t.ld, t.segmentation, t.heatmap, t.world, t.poseflag] = await ((_a = models3[1]) == null ? void 0 : _a.execute(t.resize, outputNodes));
const points = await t.ld.data();
const keypoints3 = [];
const labels2 = (points == null ? void 0 : points.length) === 195 ? full : upper;
const depth = 5;
for (let i = 0; i < points.length / depth; i++) {
keypoints3.push({
id: i,
part: labels2[i],
position: [
Math.trunc(imgSize.width * points[depth * i + 0] / 255),
Math.trunc(imgSize.height * points[depth * i + 1] / 255),
Math.trunc(points[depth * i + 2]) + 0
],
positionRaw: [
points[depth * i + 0] / 255,
points[depth * i + 1] / 255,
points[depth * i + 2] + 0
],
score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100,
presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100
});
const score3 = (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100;
if (score3 > (config3.body.minConfidence || 0)) {
keypoints3.push({
part: labels2[i],
position: [
Math.trunc(outputSize2[0] * points[depth * i + 0] / 255),
Math.trunc(outputSize2[1] * points[depth * i + 1] / 255),
Math.trunc(points[depth * i + 2]) + 0
],
positionRaw: [
points[depth * i + 0] / 255,
points[depth * i + 1] / 255,
points[depth * i + 2] + 0
],
score: score3
});
}
}
const x = keypoints3.map((a) => a.position[0]);
const y = keypoints3.map((a) => a.position[1]);
@ -9979,30 +9998,38 @@ async function predict7(image24, config3) {
];
const boxRaw2 = [0, 0, 0, 0];
const score2 = keypoints3.reduce((prev, curr) => curr.score > prev ? curr.score : prev, 0);
return [{ id: 0, score: score2, box: box5, boxRaw: boxRaw2, keypoints: keypoints3 }];
Object.keys(t).forEach((tensor3) => tf17.dispose(t[tensor3]));
return { id: 0, score: score2, box: box5, boxRaw: boxRaw2, keypoints: keypoints3 };
}
async function predict7(input, config3) {
outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
const bodies = [];
const body4 = await detectParts(input, config3);
bodies.push(body4);
return bodies;
}
// src/efficientpose/efficientpose.ts
// src/body/efficientpose.ts
var tf18 = __toModule(require_tfjs_esm());
var model5;
var model4;
var keypoints = [];
var box4 = [0, 0, 0, 0];
var boxRaw = [0, 0, 0, 0];
var score = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
var bodyParts = ["head", "neck", "rightShoulder", "rightElbow", "rightWrist", "chest", "leftShoulder", "leftElbow", "leftWrist", "pelvis", "rightHip", "rightKnee", "rightAnkle", "leftHip", "leftKnee", "leftAnkle"];
async function load8(config3) {
async function load7(config3) {
if (env.initial)
model5 = null;
if (!model5) {
model5 = await tf18.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model5 || !model5["modelUrl"])
model4 = null;
if (!model4) {
model4 = await tf18.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model4 || !model4["modelUrl"])
log("load model failed:", config3.body.modelPath);
else if (config3.debug)
log("load model:", model5["modelUrl"]);
log("load model:", model4["modelUrl"]);
} else if (config3.debug)
log("cached model:", model5["modelUrl"]);
return model5;
log("cached model:", model4["modelUrl"]);
return model4;
}
function max2d(inputs, minScore) {
const [width, height] = inputs.shape;
@ -10029,16 +10056,16 @@ async function predict8(image24, config3) {
return new Promise(async (resolve) => {
var _a2;
const tensor3 = tf18.tidy(() => {
if (!(model5 == null ? void 0 : model5.inputs[0].shape))
if (!(model4 == null ? void 0 : model4.inputs[0].shape))
return null;
const resize = tf18.image.resizeBilinear(image24, [model5.inputs[0].shape[2], model5.inputs[0].shape[1]], false);
const resize = tf18.image.resizeBilinear(image24, [model4.inputs[0].shape[2], model4.inputs[0].shape[1]], false);
const enhance2 = tf18.mul(resize, 2);
const norm = enhance2.sub(1);
return norm;
});
let resT;
if (config3.body.enabled)
resT = await (model5 == null ? void 0 : model5.predict(tensor3));
resT = await (model4 == null ? void 0 : model4.predict(tensor3));
tf18.dispose(tensor3);
if (resT) {
keypoints.length = 0;
@ -10053,12 +10080,12 @@ async function predict8(image24, config3) {
score: Math.round(100 * partScore) / 100,
part: bodyParts[id],
positionRaw: [
x2 / model5.inputs[0].shape[2],
y2 / model5.inputs[0].shape[1]
x2 / model4.inputs[0].shape[2],
y2 / model4.inputs[0].shape[1]
],
position: [
Math.round(image24.shape[2] * x2 / model5.inputs[0].shape[2]),
Math.round(image24.shape[1] * y2 / model5.inputs[0].shape[1])
Math.round(image24.shape[2] * x2 / model4.inputs[0].shape[2]),
Math.round(image24.shape[1] * y2 / model4.inputs[0].shape[1])
]
});
}
@ -10086,30 +10113,30 @@ async function predict8(image24, config3) {
});
}
// src/movenet/movenet.ts
// src/body/movenet.ts
var tf19 = __toModule(require_tfjs_esm());
var model6;
var inputSize2 = 0;
var model5;
var inputSize3 = 0;
var cachedBoxes = [];
var skipped5 = Number.MAX_SAFE_INTEGER;
var keypoints2 = [];
var bodyParts2 = ["nose", "leftEye", "rightEye", "leftEar", "rightEar", "leftShoulder", "rightShoulder", "leftElbow", "rightElbow", "leftWrist", "rightWrist", "leftHip", "rightHip", "leftKnee", "rightKnee", "leftAnkle", "rightAnkle"];
async function load9(config3) {
async function load8(config3) {
if (env.initial)
model6 = null;
if (!model6) {
model5 = null;
if (!model5) {
fakeOps(["size"], config3);
model6 = await tf19.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model6 || !model6["modelUrl"])
model5 = await tf19.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model5 || !model5["modelUrl"])
log("load model failed:", config3.body.modelPath);
else if (config3.debug)
log("load model:", model6["modelUrl"]);
log("load model:", model5["modelUrl"]);
} else if (config3.debug)
log("cached model:", model6["modelUrl"]);
inputSize2 = model6.inputs[0].shape ? model6.inputs[0].shape[2] : 0;
if (inputSize2 === -1)
inputSize2 = 256;
return model6;
log("cached model:", model5["modelUrl"]);
inputSize3 = model5.inputs[0].shape ? model5.inputs[0].shape[2] : 0;
if (inputSize3 === -1)
inputSize3 = 256;
return model5;
}
async function parseSinglePose(res, config3, image24, inputBox) {
const kpt3 = res[0][0];
@ -10194,7 +10221,7 @@ async function parseMultiPose(res, config3, image24, inputBox) {
return bodies;
}
async function predict9(input, config3) {
if (!model6 || !(model6 == null ? void 0 : model6.inputs[0].shape))
if (!model5 || !(model5 == null ? void 0 : model5.inputs[0].shape))
return [];
return new Promise(async (resolve) => {
const t = {};
@ -10203,18 +10230,18 @@ async function predict9(input, config3) {
cachedBoxes.length = 0;
skipped5++;
for (let i = 0; i < cachedBoxes.length; i++) {
t.crop = tf19.image.cropAndResize(input, [cachedBoxes[i]], [0], [inputSize2, inputSize2], "bilinear");
t.crop = tf19.image.cropAndResize(input, [cachedBoxes[i]], [0], [inputSize3, inputSize3], "bilinear");
t.cast = tf19.cast(t.crop, "int32");
t.res = await (model6 == null ? void 0 : model6.predict(t.cast));
t.res = await (model5 == null ? void 0 : model5.predict(t.cast));
const res = await t.res.array();
const newBodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, cachedBoxes[i]) : await parseMultiPose(res, config3, input, cachedBoxes[i]);
bodies = bodies.concat(newBodies);
Object.keys(t).forEach((tensor3) => tf19.dispose(t[tensor3]));
}
if (bodies.length !== config3.body.maxDetected && skipped5 > (config3.body.skipFrames || 0)) {
t.resized = tf19.image.resizeBilinear(input, [inputSize2, inputSize2], false);
t.resized = tf19.image.resizeBilinear(input, [inputSize3, inputSize3], false);
t.cast = tf19.cast(t.resized, "int32");
t.res = await (model6 == null ? void 0 : model6.predict(t.cast));
t.res = await (model5 == null ? void 0 : model5.predict(t.cast));
const res = await t.res.array();
bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input, [0, 0, 1, 1]);
Object.keys(t).forEach((tensor3) => tf19.dispose(t[tensor3]));
@ -10226,7 +10253,7 @@ async function predict9(input, config3) {
for (let i = 0; i < bodies.length; i++) {
if (bodies[i].keypoints.length > 10) {
const kpts = bodies[i].keypoints.map((kpt3) => kpt3.position);
const newBox = scaleBox(kpts, 1.5, [input.shape[2], input.shape[1]]);
const newBox = scale(kpts, 1.5, [input.shape[2], input.shape[1]]);
cachedBoxes.push([...newBox.yxBox]);
}
}
@ -10323,26 +10350,26 @@ var labels = [
];
// src/object/nanodet.ts
var model7;
var model6;
var last3 = [];
var skipped6 = Number.MAX_SAFE_INTEGER;
var scaleBox2 = 2.5;
async function load10(config3) {
if (!model7 || env.initial) {
model7 = await tf20.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model7.modelSignature["inputs"]);
model7.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
if (!model7.inputSize)
var scaleBox = 2.5;
async function load9(config3) {
if (!model6 || env.initial) {
model6 = await tf20.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model6.modelSignature["inputs"]);
model6.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
if (!model6.inputSize)
throw new Error(`cannot determine model inputSize: ${config3.object.modelPath}`);
if (!model7 || !model7.modelUrl)
if (!model6 || !model6.modelUrl)
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model7.modelUrl);
log("load model:", model6.modelUrl);
} else if (config3.debug)
log("cached model:", model7.modelUrl);
return model7;
log("cached model:", model6.modelUrl);
return model6;
}
async function process3(res, inputSize4, outputShape, config3) {
async function process3(res, inputSize5, outputShape, config3) {
let id = 0;
let results = [];
for (const strideSize of [1, 2, 4]) {
@ -10360,14 +10387,14 @@ async function process3(res, inputSize4, outputShape, config3) {
if (score2 > config3.object.minConfidence && j !== 61) {
const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize;
const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize;
const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize4));
const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize5));
const [x, y] = [
cx - scaleBox2 / strideSize * boxOffset[0],
cy - scaleBox2 / strideSize * boxOffset[1]
cx - scaleBox / strideSize * boxOffset[0],
cy - scaleBox / strideSize * boxOffset[1]
];
const [w, h] = [
cx + scaleBox2 / strideSize * boxOffset[2] - x,
cy + scaleBox2 / strideSize * boxOffset[3] - y
cx + scaleBox / strideSize * boxOffset[2] - x,
cy + scaleBox / strideSize * boxOffset[3] - y
];
let boxRaw2 = [x, y, w, h];
boxRaw2 = boxRaw2.map((a) => Math.max(0, Math.min(a, 1)));
@ -10412,17 +10439,17 @@ async function predict10(image24, config3) {
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [image24.shape[2], image24.shape[1]];
const resize = tf20.image.resizeBilinear(image24, [model7.inputSize, model7.inputSize], false);
const outputSize3 = [image24.shape[2], image24.shape[1]];
const resize = tf20.image.resizeBilinear(image24, [model6.inputSize, model6.inputSize], false);
const norm = tf20.div(resize, 255);
const transpose = norm.transpose([0, 3, 1, 2]);
tf20.dispose(norm);
tf20.dispose(resize);
let objectT;
if (config3.object.enabled)
objectT = await model7.predict(transpose);
objectT = await model6.predict(transpose);
tf20.dispose(transpose);
const obj = await process3(objectT, model7.inputSize, outputSize2, config3);
const obj = await process3(objectT, model6.inputSize, outputSize3, config3);
last3 = obj;
resolve(obj);
});
@ -10430,25 +10457,25 @@ async function predict10(image24, config3) {
// src/object/centernet.ts
var tf21 = __toModule(require_tfjs_esm());
var model8;
var inputSize3 = 0;
var model7;
var inputSize4 = 0;
var last4 = [];
var skipped7 = Number.MAX_SAFE_INTEGER;
async function load11(config3) {
async function load10(config3) {
if (env.initial)
model8 = null;
if (!model8) {
model7 = null;
if (!model7) {
fakeOps(["floormod"], config3);
model8 = await tf21.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model8.modelSignature["inputs"]);
inputSize3 = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!model8 || !model8["modelUrl"])
model7 = await tf21.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model7.modelSignature["inputs"]);
inputSize4 = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!model7 || !model7["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model8["modelUrl"]);
log("load model:", model7["modelUrl"]);
} else if (config3.debug)
log("cached model:", model8["modelUrl"]);
return model8;
log("cached model:", model7["modelUrl"]);
return model7;
}
async function process4(res, outputShape, config3) {
if (!res)
@ -10477,14 +10504,14 @@ async function process4(res, outputShape, config3) {
const classVal = detections[0][id][5];
const label = labels[classVal].label;
const [x, y] = [
detections[0][id][0] / inputSize3,
detections[0][id][1] / inputSize3
detections[0][id][0] / inputSize4,
detections[0][id][1] / inputSize4
];
const boxRaw2 = [
x,
y,
detections[0][id][2] / inputSize3 - x,
detections[0][id][3] / inputSize3 - y
detections[0][id][2] / inputSize4 - x,
detections[0][id][3] / inputSize4 - y
];
const box5 = [
Math.trunc(boxRaw2[0] * outputShape[0]),
@ -10505,11 +10532,11 @@ async function predict11(input, config3) {
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last4;
return new Promise(async (resolve) => {
const outputSize2 = [input.shape[2], input.shape[1]];
const resize = tf21.image.resizeBilinear(input, [inputSize3, inputSize3]);
const objectT = config3.object.enabled ? model8 == null ? void 0 : model8.execute(resize, ["tower_0/detections"]) : null;
const outputSize3 = [input.shape[2], input.shape[1]];
const resize = tf21.image.resizeBilinear(input, [inputSize4, inputSize4]);
const objectT = config3.object.enabled ? model7 == null ? void 0 : model7.execute(resize, ["tower_0/detections"]) : null;
tf21.dispose(resize);
const obj = await process4(objectT, outputSize2, config3);
const obj = await process4(objectT, outputSize3, config3);
last4 = obj;
resolve(obj);
});
@ -10517,36 +10544,36 @@ async function predict11(input, config3) {
// src/segmentation/segmentation.ts
var tf22 = __toModule(require_tfjs_esm());
var model9;
var model8;
var busy = false;
async function load12(config3) {
if (!model9 || env.initial) {
model9 = await tf22.loadGraphModel(join(config3.modelBasePath, config3.segmentation.modelPath || ""));
if (!model9 || !model9["modelUrl"])
async function load11(config3) {
if (!model8 || env.initial) {
model8 = await tf22.loadGraphModel(join(config3.modelBasePath, config3.segmentation.modelPath || ""));
if (!model8 || !model8["modelUrl"])
log("load model failed:", config3.segmentation.modelPath);
else if (config3.debug)
log("load model:", model9["modelUrl"]);
log("load model:", model8["modelUrl"]);
} else if (config3.debug)
log("cached model:", model9["modelUrl"]);
return model9;
log("cached model:", model8["modelUrl"]);
return model8;
}
async function process5(input, background, config3) {
var _a, _b;
if (busy)
return { data: [], canvas: null, alpha: null };
busy = true;
if (!model9)
await load12(config3);
if (!model8)
await load11(config3);
const inputImage = process2(input, config3);
const width = ((_a = inputImage.canvas) == null ? void 0 : _a.width) || 0;
const height = ((_b = inputImage.canvas) == null ? void 0 : _b.height) || 0;
if (!inputImage.tensor)
return { data: [], canvas: null, alpha: null };
const t = {};
t.resize = tf22.image.resizeBilinear(inputImage.tensor, [model9.inputs[0].shape ? model9.inputs[0].shape[1] : 0, model9.inputs[0].shape ? model9.inputs[0].shape[2] : 0], false);
t.resize = tf22.image.resizeBilinear(inputImage.tensor, [model8.inputs[0].shape ? model8.inputs[0].shape[1] : 0, model8.inputs[0].shape ? model8.inputs[0].shape[2] : 0], false);
tf22.dispose(inputImage.tensor);
t.norm = tf22.div(t.resize, 255);
t.res = model9.predict(t.norm);
t.res = model8.predict(t.norm);
t.squeeze = tf22.squeeze(t.res, 0);
if (t.squeeze.shape[2] === 2) {
t.softmax = tf22.softmax(t.squeeze);
@ -10599,22 +10626,22 @@ async function process5(input, background, config3) {
return { data, canvas: mergedCanvas || compositeCanvas, alpha: alphaCanvas };
}
// src/gear/agegenderrace.ts
// src/gear/gear-agegenderrace.ts
var tf23 = __toModule(require_tfjs_esm());
var model10;
var model9;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load13(config3) {
async function load12(config3) {
if (env.initial)
model10 = null;
if (!model10) {
model10 = await tf23.loadGraphModel(join(config3.modelBasePath, config3.face.agegenderrace.modelPath));
if (!model10 || !model10["modelUrl"])
model9 = null;
if (!model9) {
model9 = await tf23.loadGraphModel(join(config3.modelBasePath, config3.face.agegenderrace.modelPath));
if (!model9 || !model9["modelUrl"])
log("load model failed:", config3.face.agegenderrace.modelPath);
else if (config3.debug)
log("load model:", model10["modelUrl"]);
log("load model:", model9["modelUrl"]);
} else if (config3.debug)
log("cached model:", model10["modelUrl"]);
return model10;
log("cached model:", model9["modelUrl"]);
return model9;
}
// src/models.ts
@ -10622,6 +10649,7 @@ var Models = class {
constructor() {
__publicField(this, "age", null);
__publicField(this, "agegenderrace", null);
__publicField(this, "blazeposedetect", null);
__publicField(this, "blazepose", null);
__publicField(this, "centernet", null);
__publicField(this, "efficientpose", null);
@ -10642,11 +10670,11 @@ var Models = class {
}
};
function reset(instance) {
for (const model11 of Object.keys(instance.models))
instance.models[model11] = null;
for (const model10 of Object.keys(instance.models))
instance.models[model10] = null;
}
async function load14(instance) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A;
async function load13(instance) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A, _B, _C, _D;
if (env.initial)
reset(instance);
if (instance.config.face.enabled) {
@ -10670,48 +10698,50 @@ async function load14(instance) {
if (instance.config.body.enabled && !instance.models.posenet && ((_l = (_k = instance.config.body) == null ? void 0 : _k.modelPath) == null ? void 0 : _l.includes("posenet")))
instance.models.posenet = load5(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_n = (_m = instance.config.body) == null ? void 0 : _m.modelPath) == null ? void 0 : _n.includes("efficientpose")))
instance.models.efficientpose = load8(instance.config);
if (instance.config.body.enabled && !instance.models.blazepose && ((_p = (_o = instance.config.body) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("blazepose")))
instance.models.blazepose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_r = (_q = instance.config.body) == null ? void 0 : _q.modelPath) == null ? void 0 : _r.includes("efficientpose")))
instance.models.efficientpose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && ((_t = (_s = instance.config.body) == null ? void 0 : _s.modelPath) == null ? void 0 : _t.includes("movenet")))
instance.models.movenet = load9(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && ((_v = (_u = instance.config.object) == null ? void 0 : _u.modelPath) == null ? void 0 : _v.includes("nanodet")))
instance.models.nanodet = load10(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && ((_x = (_w = instance.config.object) == null ? void 0 : _w.modelPath) == null ? void 0 : _x.includes("centernet")))
instance.models.centernet = load11(instance.config);
if (instance.config.face.enabled && ((_y = instance.config.face.emotion) == null ? void 0 : _y.enabled) && !instance.models.emotion)
if (instance.config.body.enabled && !instance.models.blazepose && ((_p = (_o = instance.config.body) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("blazepose")))
instance.models.blazepose = loadPose(instance.config);
if (instance.config.body.enabled && !instance.models.blazeposedetect && ((_q = instance.config.body.detector) == null ? void 0 : _q.modelPath) && ((_s = (_r = instance.config.body) == null ? void 0 : _r.modelPath) == null ? void 0 : _s.includes("blazepose")))
instance.models.blazeposedetect = loadDetect2(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_u = (_t = instance.config.body) == null ? void 0 : _t.modelPath) == null ? void 0 : _u.includes("efficientpose")))
instance.models.efficientpose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && ((_w = (_v = instance.config.body) == null ? void 0 : _v.modelPath) == null ? void 0 : _w.includes("movenet")))
instance.models.movenet = load8(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && ((_y = (_x = instance.config.object) == null ? void 0 : _x.modelPath) == null ? void 0 : _y.includes("nanodet")))
instance.models.nanodet = load9(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && ((_A = (_z = instance.config.object) == null ? void 0 : _z.modelPath) == null ? void 0 : _A.includes("centernet")))
instance.models.centernet = load10(instance.config);
if (instance.config.face.enabled && ((_B = instance.config.face.emotion) == null ? void 0 : _B.enabled) && !instance.models.emotion)
instance.models.emotion = load4(instance.config);
if (instance.config.face.enabled && ((_z = instance.config.face.description) == null ? void 0 : _z.enabled) && !instance.models.faceres)
if (instance.config.face.enabled && ((_C = instance.config.face.description) == null ? void 0 : _C.enabled) && !instance.models.faceres)
instance.models.faceres = load3(instance.config);
if (instance.config.segmentation.enabled && !instance.models.segmentation)
instance.models.segmentation = load12(instance.config);
if (instance.config.face.enabled && ((_A = instance.config.face["agegenderrace"]) == null ? void 0 : _A.enabled) && !instance.models.agegenderrace)
instance.models.agegenderrace = load13(instance.config);
for await (const model11 of Object.keys(instance.models)) {
if (instance.models[model11] && typeof instance.models[model11] !== "undefined")
instance.models[model11] = await instance.models[model11];
instance.models.segmentation = load11(instance.config);
if (instance.config.face.enabled && ((_D = instance.config.face["agegenderrace"]) == null ? void 0 : _D.enabled) && !instance.models.agegenderrace)
instance.models.agegenderrace = load12(instance.config);
for await (const model10 of Object.keys(instance.models)) {
if (instance.models[model10] && typeof instance.models[model10] !== "undefined")
instance.models[model10] = await instance.models[model10];
}
}
async function validate2(instance) {
const simpleOps = ["const", "placeholder", "noop", "pad", "squeeze", "add", "sub", "mul", "div"];
for (const defined of Object.keys(instance.models)) {
if (instance.models[defined]) {
let models4 = [];
let models5 = [];
if (Array.isArray(instance.models[defined])) {
models4 = instance.models[defined].filter((model11) => model11 !== null).map((model11) => model11 && model11.executor ? model11 : model11.model);
models5 = instance.models[defined].filter((model10) => model10 !== null).map((model10) => model10 && model10.executor ? model10 : model10.model);
} else {
models4 = [instance.models[defined]];
models5 = [instance.models[defined]];
}
for (const model11 of models4) {
if (!model11) {
for (const model10 of models5) {
if (!model10) {
if (instance.config.debug)
log("model marked as loaded but not defined:", defined);
continue;
}
const ops = [];
const executor = model11 == null ? void 0 : model11.executor;
const executor = model10 == null ? void 0 : model10.executor;
if (executor && executor.graph.nodes) {
for (const kernel of Object.values(executor.graph.nodes)) {
const op = kernel.op.toLowerCase();
@ -10735,7 +10765,7 @@ async function validate2(instance) {
}
}
// src/face.ts
// src/face/face.ts
var tf24 = __toModule(require_tfjs_esm());
var calculateGaze = (face5) => {
const radians = (pt1, pt2) => Math.atan2(pt1[1] - pt2[1], pt1[0] - pt2[0]);
@ -11043,7 +11073,7 @@ var hand = (res) => {
return gestures;
};
// src/draw.ts
// src/util/draw.ts
var options2 = {
color: "rgba(173, 216, 230, 0.6)",
labelColor: "rgba(173, 216, 230, 1)",
@ -11589,7 +11619,7 @@ function join2(faces, bodies, hands, gestures, shape) {
return persons2;
}
// src/interpolate.ts
// src/util/interpolate.ts
var bufferedResult = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0 };
function calc(newResult) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u;
@ -12636,7 +12666,7 @@ var Human = class {
async load(userConfig) {
this.state = "load";
const timeStamp = now();
const count2 = Object.values(this.models).filter((model11) => model11).length;
const count2 = Object.values(this.models).filter((model10) => model10).length;
if (userConfig)
this.config = mergeDeep(this.config, userConfig);
if (env.initial) {
@ -12654,11 +12684,11 @@ var Human = class {
log("tf flags:", this.tf.ENV.flags);
}
}
await load14(this);
await load13(this);
if (env.initial && this.config.debug)
log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
env.initial = false;
const loaded = Object.values(this.models).filter((model11) => model11).length;
const loaded = Object.values(this.models).filter((model10) => model10).length;
if (loaded !== count2) {
await validate2(this);
this.emit("load");

496
dist/human.node.js vendored
View File

@ -89,7 +89,7 @@ __export(exports, {
env: () => env
});
// src/util.ts
// src/util/util.ts
function join(folder, file) {
const separator = folder.endsWith("/") ? "" : "/";
const skipJoin = file.startsWith(".") || file.startsWith("/") || file.startsWith("http:") || file.startsWith("https:") || file.startsWith("file:");
@ -142,31 +142,6 @@ function mergeDeep(...objects) {
return prev;
}, {});
}
function scaleBox(keypoints3, boxScaleFact2, outputSize2) {
const coords3 = [keypoints3.map((pt) => pt[0]), keypoints3.map((pt) => pt[1])];
const maxmin = [Math.max(...coords3[0]), Math.min(...coords3[0]), Math.max(...coords3[1]), Math.min(...coords3[1])];
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2];
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact2;
const box5 = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff)
];
const boxRaw2 = [
box5[0] / outputSize2[0],
box5[1] / outputSize2[1],
box5[2] / outputSize2[0],
box5[3] / outputSize2[1]
];
const yxBox = [
boxRaw2[1],
boxRaw2[0],
boxRaw2[3] + boxRaw2[1],
boxRaw2[2] + boxRaw2[0]
];
return { box: box5, boxRaw: boxRaw2, yxBox };
}
// src/config.ts
var config = {
@ -236,6 +211,9 @@ var config = {
body: {
enabled: true,
modelPath: "movenet-lightning.json",
detector: {
modelPath: ""
},
maxDetected: -1,
minConfidence: 0.2,
skipFrames: 1
@ -403,13 +381,13 @@ function rotatePoint(homogeneousCoordinate, rotationMatrix) {
dot(homogeneousCoordinate, rotationMatrix[1])
];
}
function generateAnchors(inputSize4) {
const spec = { strides: [inputSize4 / 16, inputSize4 / 8], anchors: [2, 6] };
function generateAnchors(inputSize5) {
const spec = { strides: [inputSize5 / 16, inputSize5 / 8], anchors: [2, 6] };
const anchors3 = [];
for (let i = 0; i < spec.strides.length; i++) {
const stride = spec.strides[i];
const gridRows = Math.floor((inputSize4 + stride - 1) / stride);
const gridCols = Math.floor((inputSize4 + stride - 1) / stride);
const gridRows = Math.floor((inputSize5 + stride - 1) / stride);
const gridCols = Math.floor((inputSize5 + stride - 1) / stride);
const anchorsNum = spec.anchors[i];
for (let gridY = 0; gridY < gridRows; gridY++) {
const anchorY = stride * (gridY + 0.5);
@ -426,31 +404,31 @@ function generateAnchors(inputSize4) {
// src/blazeface/blazeface.ts
var keypointsCount = 6;
function decodeBounds(boxOutputs, anchors3, inputSize4) {
function decodeBounds(boxOutputs, anchors3, inputSize5) {
const boxStarts = tf2.slice(boxOutputs, [0, 1], [-1, 2]);
const centers = tf2.add(boxStarts, anchors3);
const boxSizes = tf2.slice(boxOutputs, [0, 3], [-1, 2]);
const boxSizesNormalized = tf2.div(boxSizes, inputSize4);
const centersNormalized = tf2.div(centers, inputSize4);
const boxSizesNormalized = tf2.div(boxSizes, inputSize5);
const centersNormalized = tf2.div(centers, inputSize5);
const halfBoxSize = tf2.div(boxSizesNormalized, 2);
const starts = tf2.sub(centersNormalized, halfBoxSize);
const ends = tf2.add(centersNormalized, halfBoxSize);
const startNormalized = tf2.mul(starts, inputSize4);
const endNormalized = tf2.mul(ends, inputSize4);
const startNormalized = tf2.mul(starts, inputSize5);
const endNormalized = tf2.mul(ends, inputSize5);
const concatAxis = 1;
return tf2.concat2d([startNormalized, endNormalized], concatAxis);
}
var BlazeFaceModel = class {
constructor(model11, config3) {
constructor(model10, config3) {
__publicField(this, "model");
__publicField(this, "anchorsData");
__publicField(this, "anchors");
__publicField(this, "inputSize");
__publicField(this, "config");
this.model = model11;
this.anchorsData = generateAnchors(model11.inputs[0].shape[1]);
this.model = model10;
this.anchorsData = generateAnchors(model10.inputs[0].shape[1]);
this.anchors = tf2.tensor2d(this.anchorsData);
this.inputSize = model11.inputs[0].shape[2];
this.inputSize = model10.inputs[0].shape[2];
this.config = config3;
}
async getBoundingBoxes(inputImage, userConfig) {
@ -502,12 +480,12 @@ var BlazeFaceModel = class {
};
async function load(config3) {
var _a, _b, _c;
const model11 = await tf2.loadGraphModel(join(config3.modelBasePath, ((_a = config3.face.detector) == null ? void 0 : _a.modelPath) || ""), { fromTFHub: (((_b = config3.face.detector) == null ? void 0 : _b.modelPath) || "").includes("tfhub.dev") });
const blazeFace = new BlazeFaceModel(model11, config3);
if (!model11 || !model11.modelUrl)
const model10 = await tf2.loadGraphModel(join(config3.modelBasePath, ((_a = config3.face.detector) == null ? void 0 : _a.modelPath) || ""), { fromTFHub: (((_b = config3.face.detector) == null ? void 0 : _b.modelPath) || "").includes("tfhub.dev") });
const blazeFace = new BlazeFaceModel(model10, config3);
if (!model10 || !model10.modelUrl)
log("load model failed:", ((_c = config3.face.detector) == null ? void 0 : _c.modelPath) || "");
else if (config3.debug)
log("load model:", model11.modelUrl);
log("load model:", model10.modelUrl);
return blazeFace;
}
@ -3783,7 +3761,7 @@ var UV68 = VTX68.map((x) => UV468[x]);
var UV33 = VTX33.map((x) => UV468[x]);
var UV7 = VTX7.map((x) => UV468[x]);
// src/env.ts
// src/util/env.ts
var tf4 = __toModule(require_tfjs_esm());
// src/image/image.ts
@ -4703,7 +4681,7 @@ async function skip(config3, input) {
return skipFrame;
}
// src/env.ts
// src/util/env.ts
var env = {
browser: void 0,
node: void 0,
@ -5164,7 +5142,7 @@ async function load2(config3) {
var triangulation = TRI468;
var uvmap = UV468;
// src/faceres/faceres.ts
// src/face/faceres.ts
var tf7 = __toModule(require_tfjs_esm());
var model;
var last = [];
@ -5268,7 +5246,7 @@ async function predict2(image24, config3, idx, count2) {
});
}
// src/emotion/emotion.ts
// src/gear/emotion.ts
var tf8 = __toModule(require_tfjs_esm());
var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
var model2;
@ -8689,14 +8667,14 @@ var anchors = [
// src/handpose/handdetector.ts
var HandDetector = class {
constructor(model11) {
constructor(model10) {
__publicField(this, "model");
__publicField(this, "anchors");
__publicField(this, "anchorsTensor");
__publicField(this, "inputSize");
__publicField(this, "inputSizeTensor");
__publicField(this, "doubleInputSizeTensor");
this.model = model11;
this.model = model10;
this.anchors = anchors.map((anchor) => [anchor.x, anchor.y]);
this.anchorsTensor = tf11.tensor2d(this.anchors);
this.inputSize = this.model && this.model.inputs && this.model.inputs[0].shape ? this.model.inputs[0].shape[2] : 0;
@ -9455,7 +9433,34 @@ async function load6(config3) {
return [handDetectorModel, handPoseModel];
}
// src/handtrack/handtrack.ts
// src/util/box.ts
function scale(keypoints3, boxScaleFact2, outputSize3) {
const coords3 = [keypoints3.map((pt) => pt[0]), keypoints3.map((pt) => pt[1])];
const maxmin = [Math.max(...coords3[0]), Math.min(...coords3[0]), Math.max(...coords3[1]), Math.min(...coords3[1])];
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2];
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact2;
const box5 = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff)
];
const boxRaw2 = [
box5[0] / outputSize3[0],
box5[1] / outputSize3[1],
box5[2] / outputSize3[0],
box5[3] / outputSize3[1]
];
const yxBox = [
boxRaw2[1],
boxRaw2[0],
boxRaw2[3] + boxRaw2[1],
boxRaw2[2] + boxRaw2[0]
];
return { box: box5, boxRaw: boxRaw2, yxBox };
}
// src/hand/handtrack.ts
var tf16 = __toModule(require_tfjs_esm());
// src/tfjs/humangl.ts
@ -9662,7 +9667,7 @@ function fakeOps(kernelNames, config3) {
env.kernels = tf15.getKernelsForBackend(tf15.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());
}
// src/handtrack/handtrack.ts
// src/hand/handtrack.ts
var boxScaleFact = 1.5;
var models2 = [null, null];
var modelOutputNodes = ["StatefulPartitionedCall/Postprocessor/Slice", "StatefulPartitionedCall/Postprocessor/ExpandDims_1"];
@ -9800,7 +9805,7 @@ async function detectFingers(input, h, config3) {
h.box[3] * coord[1] / inputSize[1][1] + h.box[1],
(h.box[2] + h.box[3]) / 2 / inputSize[1][0] * coord[2]
]);
const updatedBox = scaleBox(hand3.keypoints, boxScaleFact, outputSize);
const updatedBox = scale(hand3.keypoints, boxScaleFact, outputSize);
h.box = updatedBox.box;
h.boxRaw = updatedBox.boxRaw;
h.yxBox = updatedBox.yxBox;
@ -9837,10 +9842,10 @@ async function predict6(input, config3) {
return hands;
}
// src/blazepose/blazepose.ts
// src/body/blazepose.ts
var tf17 = __toModule(require_tfjs_esm());
// src/blazepose/annotations.ts
// src/body/annotations.ts
var full = [
"nose",
"leftEyeInside",
@ -9916,57 +9921,71 @@ var upper = [
"right:30"
];
// src/blazepose/blazepose.ts
var model4;
async function load7(config3) {
// src/body/blazepose.ts
var models3 = [null, null];
var outputNodes = ["ld_3d", "activation_segmentation", "activation_heatmap", "world_3d", "output_poseflag"];
var inputSize2 = [[0, 0], [0, 0]];
var outputSize2 = [0, 0];
async function loadDetect2(config3) {
var _a;
if (env.initial)
model4 = null;
if (!model4) {
model4 = await tf17.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
model4["width"] = parseInt(model4["signature"].inputs["input_1:0"].tensorShape.dim[2].size);
model4["height"] = parseInt(model4["signature"].inputs["input_1:0"].tensorShape.dim[1].size);
if (!model4 || !model4["modelUrl"])
log("load model failed:", config3.body.modelPath);
models3[0] = null;
if (!models3[0]) {
models3[0] = await tf17.loadGraphModel(join(config3.modelBasePath, ((_a = config3.body.detector) == null ? void 0 : _a.modelPath) || ""));
const inputs = Object.values(models3[0].modelSignature["inputs"]);
inputSize2[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize2[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models3[0] || !models3[0]["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model4["modelUrl"]);
log("load model:", models3[0]["modelUrl"]);
} else if (config3.debug)
log("cached model:", model4["modelUrl"]);
return model4;
log("cached model:", models3[0]["modelUrl"]);
return models3[0];
}
async function predict7(image24, config3) {
if (!model4)
return [];
if (!config3.body.enabled)
return [];
const imgSize = { width: image24.shape[2] || 0, height: image24.shape[1] || 0 };
const resize = tf17.image.resizeBilinear(image24, [model4["width"], model4["height"]], false);
const normalize = tf17.div(resize, [255]);
tf17.dispose(resize);
const resT = await model4.predict(normalize);
const findT = resT.find((t) => t.size === 195 || t.size === 155);
const points = await (findT == null ? void 0 : findT.data()) || [];
resT.forEach((t) => tf17.dispose(t));
tf17.dispose(normalize);
async function loadPose(config3) {
if (env.initial)
models3[1] = null;
if (!models3[1]) {
models3[1] = await tf17.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
const inputs = Object.values(models3[1].modelSignature["inputs"]);
inputSize2[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize2[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models3[1] || !models3[1]["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", models3[1]["modelUrl"]);
} else if (config3.debug)
log("cached model:", models3[1]["modelUrl"]);
return models3[1];
}
async function detectParts(input, config3) {
var _a;
const t = {};
t.resize = tf17.image.resizeBilinear(input, [inputSize2[1][0], inputSize2[1][1]]);
[t.ld, t.segmentation, t.heatmap, t.world, t.poseflag] = await ((_a = models3[1]) == null ? void 0 : _a.execute(t.resize, outputNodes));
const points = await t.ld.data();
const keypoints3 = [];
const labels2 = (points == null ? void 0 : points.length) === 195 ? full : upper;
const depth = 5;
for (let i = 0; i < points.length / depth; i++) {
keypoints3.push({
id: i,
part: labels2[i],
position: [
Math.trunc(imgSize.width * points[depth * i + 0] / 255),
Math.trunc(imgSize.height * points[depth * i + 1] / 255),
Math.trunc(points[depth * i + 2]) + 0
],
positionRaw: [
points[depth * i + 0] / 255,
points[depth * i + 1] / 255,
points[depth * i + 2] + 0
],
score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100,
presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100
});
const score3 = (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100;
if (score3 > (config3.body.minConfidence || 0)) {
keypoints3.push({
part: labels2[i],
position: [
Math.trunc(outputSize2[0] * points[depth * i + 0] / 255),
Math.trunc(outputSize2[1] * points[depth * i + 1] / 255),
Math.trunc(points[depth * i + 2]) + 0
],
positionRaw: [
points[depth * i + 0] / 255,
points[depth * i + 1] / 255,
points[depth * i + 2] + 0
],
score: score3
});
}
}
const x = keypoints3.map((a) => a.position[0]);
const y = keypoints3.map((a) => a.position[1]);
@ -9978,30 +9997,38 @@ async function predict7(image24, config3) {
];
const boxRaw2 = [0, 0, 0, 0];
const score2 = keypoints3.reduce((prev, curr) => curr.score > prev ? curr.score : prev, 0);
return [{ id: 0, score: score2, box: box5, boxRaw: boxRaw2, keypoints: keypoints3 }];
Object.keys(t).forEach((tensor3) => tf17.dispose(t[tensor3]));
return { id: 0, score: score2, box: box5, boxRaw: boxRaw2, keypoints: keypoints3 };
}
async function predict7(input, config3) {
outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
const bodies = [];
const body4 = await detectParts(input, config3);
bodies.push(body4);
return bodies;
}
// src/efficientpose/efficientpose.ts
// src/body/efficientpose.ts
var tf18 = __toModule(require_tfjs_esm());
var model5;
var model4;
var keypoints = [];
var box4 = [0, 0, 0, 0];
var boxRaw = [0, 0, 0, 0];
var score = 0;
var skipped4 = Number.MAX_SAFE_INTEGER;
var bodyParts = ["head", "neck", "rightShoulder", "rightElbow", "rightWrist", "chest", "leftShoulder", "leftElbow", "leftWrist", "pelvis", "rightHip", "rightKnee", "rightAnkle", "leftHip", "leftKnee", "leftAnkle"];
async function load8(config3) {
async function load7(config3) {
if (env.initial)
model5 = null;
if (!model5) {
model5 = await tf18.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model5 || !model5["modelUrl"])
model4 = null;
if (!model4) {
model4 = await tf18.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model4 || !model4["modelUrl"])
log("load model failed:", config3.body.modelPath);
else if (config3.debug)
log("load model:", model5["modelUrl"]);
log("load model:", model4["modelUrl"]);
} else if (config3.debug)
log("cached model:", model5["modelUrl"]);
return model5;
log("cached model:", model4["modelUrl"]);
return model4;
}
function max2d(inputs, minScore) {
const [width, height] = inputs.shape;
@ -10028,16 +10055,16 @@ async function predict8(image24, config3) {
return new Promise(async (resolve) => {
var _a2;
const tensor3 = tf18.tidy(() => {
if (!(model5 == null ? void 0 : model5.inputs[0].shape))
if (!(model4 == null ? void 0 : model4.inputs[0].shape))
return null;
const resize = tf18.image.resizeBilinear(image24, [model5.inputs[0].shape[2], model5.inputs[0].shape[1]], false);
const resize = tf18.image.resizeBilinear(image24, [model4.inputs[0].shape[2], model4.inputs[0].shape[1]], false);
const enhance2 = tf18.mul(resize, 2);
const norm = enhance2.sub(1);
return norm;
});
let resT;
if (config3.body.enabled)
resT = await (model5 == null ? void 0 : model5.predict(tensor3));
resT = await (model4 == null ? void 0 : model4.predict(tensor3));
tf18.dispose(tensor3);
if (resT) {
keypoints.length = 0;
@ -10052,12 +10079,12 @@ async function predict8(image24, config3) {
score: Math.round(100 * partScore) / 100,
part: bodyParts[id],
positionRaw: [
x2 / model5.inputs[0].shape[2],
y2 / model5.inputs[0].shape[1]
x2 / model4.inputs[0].shape[2],
y2 / model4.inputs[0].shape[1]
],
position: [
Math.round(image24.shape[2] * x2 / model5.inputs[0].shape[2]),
Math.round(image24.shape[1] * y2 / model5.inputs[0].shape[1])
Math.round(image24.shape[2] * x2 / model4.inputs[0].shape[2]),
Math.round(image24.shape[1] * y2 / model4.inputs[0].shape[1])
]
});
}
@ -10085,30 +10112,30 @@ async function predict8(image24, config3) {
});
}
// src/movenet/movenet.ts
// src/body/movenet.ts
var tf19 = __toModule(require_tfjs_esm());
var model6;
var inputSize2 = 0;
var model5;
var inputSize3 = 0;
var cachedBoxes = [];
var skipped5 = Number.MAX_SAFE_INTEGER;
var keypoints2 = [];
var bodyParts2 = ["nose", "leftEye", "rightEye", "leftEar", "rightEar", "leftShoulder", "rightShoulder", "leftElbow", "rightElbow", "leftWrist", "rightWrist", "leftHip", "rightHip", "leftKnee", "rightKnee", "leftAnkle", "rightAnkle"];
async function load9(config3) {
async function load8(config3) {
if (env.initial)
model6 = null;
if (!model6) {
model5 = null;
if (!model5) {
fakeOps(["size"], config3);
model6 = await tf19.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model6 || !model6["modelUrl"])
model5 = await tf19.loadGraphModel(join(config3.modelBasePath, config3.body.modelPath || ""));
if (!model5 || !model5["modelUrl"])
log("load model failed:", config3.body.modelPath);
else if (config3.debug)
log("load model:", model6["modelUrl"]);
log("load model:", model5["modelUrl"]);
} else if (config3.debug)
log("cached model:", model6["modelUrl"]);
inputSize2 = model6.inputs[0].shape ? model6.inputs[0].shape[2] : 0;
if (inputSize2 === -1)
inputSize2 = 256;
return model6;
log("cached model:", model5["modelUrl"]);
inputSize3 = model5.inputs[0].shape ? model5.inputs[0].shape[2] : 0;
if (inputSize3 === -1)
inputSize3 = 256;
return model5;
}
async function parseSinglePose(res, config3, image24, inputBox) {
const kpt3 = res[0][0];
@ -10193,7 +10220,7 @@ async function parseMultiPose(res, config3, image24, inputBox) {
return bodies;
}
async function predict9(input, config3) {
if (!model6 || !(model6 == null ? void 0 : model6.inputs[0].shape))
if (!model5 || !(model5 == null ? void 0 : model5.inputs[0].shape))
return [];
return new Promise(async (resolve) => {
const t = {};
@ -10202,18 +10229,18 @@ async function predict9(input, config3) {
cachedBoxes.length = 0;
skipped5++;
for (let i = 0; i < cachedBoxes.length; i++) {
t.crop = tf19.image.cropAndResize(input, [cachedBoxes[i]], [0], [inputSize2, inputSize2], "bilinear");
t.crop = tf19.image.cropAndResize(input, [cachedBoxes[i]], [0], [inputSize3, inputSize3], "bilinear");
t.cast = tf19.cast(t.crop, "int32");
t.res = await (model6 == null ? void 0 : model6.predict(t.cast));
t.res = await (model5 == null ? void 0 : model5.predict(t.cast));
const res = await t.res.array();
const newBodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, cachedBoxes[i]) : await parseMultiPose(res, config3, input, cachedBoxes[i]);
bodies = bodies.concat(newBodies);
Object.keys(t).forEach((tensor3) => tf19.dispose(t[tensor3]));
}
if (bodies.length !== config3.body.maxDetected && skipped5 > (config3.body.skipFrames || 0)) {
t.resized = tf19.image.resizeBilinear(input, [inputSize2, inputSize2], false);
t.resized = tf19.image.resizeBilinear(input, [inputSize3, inputSize3], false);
t.cast = tf19.cast(t.resized, "int32");
t.res = await (model6 == null ? void 0 : model6.predict(t.cast));
t.res = await (model5 == null ? void 0 : model5.predict(t.cast));
const res = await t.res.array();
bodies = t.res.shape[2] === 17 ? await parseSinglePose(res, config3, input, [0, 0, 1, 1]) : await parseMultiPose(res, config3, input, [0, 0, 1, 1]);
Object.keys(t).forEach((tensor3) => tf19.dispose(t[tensor3]));
@ -10225,7 +10252,7 @@ async function predict9(input, config3) {
for (let i = 0; i < bodies.length; i++) {
if (bodies[i].keypoints.length > 10) {
const kpts = bodies[i].keypoints.map((kpt3) => kpt3.position);
const newBox = scaleBox(kpts, 1.5, [input.shape[2], input.shape[1]]);
const newBox = scale(kpts, 1.5, [input.shape[2], input.shape[1]]);
cachedBoxes.push([...newBox.yxBox]);
}
}
@ -10322,26 +10349,26 @@ var labels = [
];
// src/object/nanodet.ts
var model7;
var model6;
var last3 = [];
var skipped6 = Number.MAX_SAFE_INTEGER;
var scaleBox2 = 2.5;
async function load10(config3) {
if (!model7 || env.initial) {
model7 = await tf20.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model7.modelSignature["inputs"]);
model7.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
if (!model7.inputSize)
var scaleBox = 2.5;
async function load9(config3) {
if (!model6 || env.initial) {
model6 = await tf20.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model6.modelSignature["inputs"]);
model6.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
if (!model6.inputSize)
throw new Error(`cannot determine model inputSize: ${config3.object.modelPath}`);
if (!model7 || !model7.modelUrl)
if (!model6 || !model6.modelUrl)
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model7.modelUrl);
log("load model:", model6.modelUrl);
} else if (config3.debug)
log("cached model:", model7.modelUrl);
return model7;
log("cached model:", model6.modelUrl);
return model6;
}
async function process3(res, inputSize4, outputShape, config3) {
async function process3(res, inputSize5, outputShape, config3) {
let id = 0;
let results = [];
for (const strideSize of [1, 2, 4]) {
@ -10359,14 +10386,14 @@ async function process3(res, inputSize4, outputShape, config3) {
if (score2 > config3.object.minConfidence && j !== 61) {
const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize;
const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize;
const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize4));
const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize5));
const [x, y] = [
cx - scaleBox2 / strideSize * boxOffset[0],
cy - scaleBox2 / strideSize * boxOffset[1]
cx - scaleBox / strideSize * boxOffset[0],
cy - scaleBox / strideSize * boxOffset[1]
];
const [w, h] = [
cx + scaleBox2 / strideSize * boxOffset[2] - x,
cy + scaleBox2 / strideSize * boxOffset[3] - y
cx + scaleBox / strideSize * boxOffset[2] - x,
cy + scaleBox / strideSize * boxOffset[3] - y
];
let boxRaw2 = [x, y, w, h];
boxRaw2 = boxRaw2.map((a) => Math.max(0, Math.min(a, 1)));
@ -10411,17 +10438,17 @@ async function predict10(image24, config3) {
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last3;
return new Promise(async (resolve) => {
const outputSize2 = [image24.shape[2], image24.shape[1]];
const resize = tf20.image.resizeBilinear(image24, [model7.inputSize, model7.inputSize], false);
const outputSize3 = [image24.shape[2], image24.shape[1]];
const resize = tf20.image.resizeBilinear(image24, [model6.inputSize, model6.inputSize], false);
const norm = tf20.div(resize, 255);
const transpose = norm.transpose([0, 3, 1, 2]);
tf20.dispose(norm);
tf20.dispose(resize);
let objectT;
if (config3.object.enabled)
objectT = await model7.predict(transpose);
objectT = await model6.predict(transpose);
tf20.dispose(transpose);
const obj = await process3(objectT, model7.inputSize, outputSize2, config3);
const obj = await process3(objectT, model6.inputSize, outputSize3, config3);
last3 = obj;
resolve(obj);
});
@ -10429,25 +10456,25 @@ async function predict10(image24, config3) {
// src/object/centernet.ts
var tf21 = __toModule(require_tfjs_esm());
var model8;
var inputSize3 = 0;
var model7;
var inputSize4 = 0;
var last4 = [];
var skipped7 = Number.MAX_SAFE_INTEGER;
async function load11(config3) {
async function load10(config3) {
if (env.initial)
model8 = null;
if (!model8) {
model7 = null;
if (!model7) {
fakeOps(["floormod"], config3);
model8 = await tf21.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model8.modelSignature["inputs"]);
inputSize3 = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!model8 || !model8["modelUrl"])
model7 = await tf21.loadGraphModel(join(config3.modelBasePath, config3.object.modelPath || ""));
const inputs = Object.values(model7.modelSignature["inputs"]);
inputSize4 = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!model7 || !model7["modelUrl"])
log("load model failed:", config3.object.modelPath);
else if (config3.debug)
log("load model:", model8["modelUrl"]);
log("load model:", model7["modelUrl"]);
} else if (config3.debug)
log("cached model:", model8["modelUrl"]);
return model8;
log("cached model:", model7["modelUrl"]);
return model7;
}
async function process4(res, outputShape, config3) {
if (!res)
@ -10476,14 +10503,14 @@ async function process4(res, outputShape, config3) {
const classVal = detections[0][id][5];
const label = labels[classVal].label;
const [x, y] = [
detections[0][id][0] / inputSize3,
detections[0][id][1] / inputSize3
detections[0][id][0] / inputSize4,
detections[0][id][1] / inputSize4
];
const boxRaw2 = [
x,
y,
detections[0][id][2] / inputSize3 - x,
detections[0][id][3] / inputSize3 - y
detections[0][id][2] / inputSize4 - x,
detections[0][id][3] / inputSize4 - y
];
const box5 = [
Math.trunc(boxRaw2[0] * outputShape[0]),
@ -10504,11 +10531,11 @@ async function predict11(input, config3) {
if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
return last4;
return new Promise(async (resolve) => {
const outputSize2 = [input.shape[2], input.shape[1]];
const resize = tf21.image.resizeBilinear(input, [inputSize3, inputSize3]);
const objectT = config3.object.enabled ? model8 == null ? void 0 : model8.execute(resize, ["tower_0/detections"]) : null;
const outputSize3 = [input.shape[2], input.shape[1]];
const resize = tf21.image.resizeBilinear(input, [inputSize4, inputSize4]);
const objectT = config3.object.enabled ? model7 == null ? void 0 : model7.execute(resize, ["tower_0/detections"]) : null;
tf21.dispose(resize);
const obj = await process4(objectT, outputSize2, config3);
const obj = await process4(objectT, outputSize3, config3);
last4 = obj;
resolve(obj);
});
@ -10516,36 +10543,36 @@ async function predict11(input, config3) {
// src/segmentation/segmentation.ts
var tf22 = __toModule(require_tfjs_esm());
var model9;
var model8;
var busy = false;
async function load12(config3) {
if (!model9 || env.initial) {
model9 = await tf22.loadGraphModel(join(config3.modelBasePath, config3.segmentation.modelPath || ""));
if (!model9 || !model9["modelUrl"])
async function load11(config3) {
if (!model8 || env.initial) {
model8 = await tf22.loadGraphModel(join(config3.modelBasePath, config3.segmentation.modelPath || ""));
if (!model8 || !model8["modelUrl"])
log("load model failed:", config3.segmentation.modelPath);
else if (config3.debug)
log("load model:", model9["modelUrl"]);
log("load model:", model8["modelUrl"]);
} else if (config3.debug)
log("cached model:", model9["modelUrl"]);
return model9;
log("cached model:", model8["modelUrl"]);
return model8;
}
async function process5(input, background, config3) {
var _a, _b;
if (busy)
return { data: [], canvas: null, alpha: null };
busy = true;
if (!model9)
await load12(config3);
if (!model8)
await load11(config3);
const inputImage = process2(input, config3);
const width = ((_a = inputImage.canvas) == null ? void 0 : _a.width) || 0;
const height = ((_b = inputImage.canvas) == null ? void 0 : _b.height) || 0;
if (!inputImage.tensor)
return { data: [], canvas: null, alpha: null };
const t = {};
t.resize = tf22.image.resizeBilinear(inputImage.tensor, [model9.inputs[0].shape ? model9.inputs[0].shape[1] : 0, model9.inputs[0].shape ? model9.inputs[0].shape[2] : 0], false);
t.resize = tf22.image.resizeBilinear(inputImage.tensor, [model8.inputs[0].shape ? model8.inputs[0].shape[1] : 0, model8.inputs[0].shape ? model8.inputs[0].shape[2] : 0], false);
tf22.dispose(inputImage.tensor);
t.norm = tf22.div(t.resize, 255);
t.res = model9.predict(t.norm);
t.res = model8.predict(t.norm);
t.squeeze = tf22.squeeze(t.res, 0);
if (t.squeeze.shape[2] === 2) {
t.softmax = tf22.softmax(t.squeeze);
@ -10598,22 +10625,22 @@ async function process5(input, background, config3) {
return { data, canvas: mergedCanvas || compositeCanvas, alpha: alphaCanvas };
}
// src/gear/agegenderrace.ts
// src/gear/gear-agegenderrace.ts
var tf23 = __toModule(require_tfjs_esm());
var model10;
var model9;
var skipped8 = Number.MAX_SAFE_INTEGER;
async function load13(config3) {
async function load12(config3) {
if (env.initial)
model10 = null;
if (!model10) {
model10 = await tf23.loadGraphModel(join(config3.modelBasePath, config3.face.agegenderrace.modelPath));
if (!model10 || !model10["modelUrl"])
model9 = null;
if (!model9) {
model9 = await tf23.loadGraphModel(join(config3.modelBasePath, config3.face.agegenderrace.modelPath));
if (!model9 || !model9["modelUrl"])
log("load model failed:", config3.face.agegenderrace.modelPath);
else if (config3.debug)
log("load model:", model10["modelUrl"]);
log("load model:", model9["modelUrl"]);
} else if (config3.debug)
log("cached model:", model10["modelUrl"]);
return model10;
log("cached model:", model9["modelUrl"]);
return model9;
}
// src/models.ts
@ -10621,6 +10648,7 @@ var Models = class {
constructor() {
__publicField(this, "age", null);
__publicField(this, "agegenderrace", null);
__publicField(this, "blazeposedetect", null);
__publicField(this, "blazepose", null);
__publicField(this, "centernet", null);
__publicField(this, "efficientpose", null);
@ -10641,11 +10669,11 @@ var Models = class {
}
};
function reset(instance) {
for (const model11 of Object.keys(instance.models))
instance.models[model11] = null;
for (const model10 of Object.keys(instance.models))
instance.models[model10] = null;
}
async function load14(instance) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A;
async function load13(instance) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A, _B, _C, _D;
if (env.initial)
reset(instance);
if (instance.config.face.enabled) {
@ -10669,48 +10697,50 @@ async function load14(instance) {
if (instance.config.body.enabled && !instance.models.posenet && ((_l = (_k = instance.config.body) == null ? void 0 : _k.modelPath) == null ? void 0 : _l.includes("posenet")))
instance.models.posenet = load5(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_n = (_m = instance.config.body) == null ? void 0 : _m.modelPath) == null ? void 0 : _n.includes("efficientpose")))
instance.models.efficientpose = load8(instance.config);
if (instance.config.body.enabled && !instance.models.blazepose && ((_p = (_o = instance.config.body) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("blazepose")))
instance.models.blazepose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_r = (_q = instance.config.body) == null ? void 0 : _q.modelPath) == null ? void 0 : _r.includes("efficientpose")))
instance.models.efficientpose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && ((_t = (_s = instance.config.body) == null ? void 0 : _s.modelPath) == null ? void 0 : _t.includes("movenet")))
instance.models.movenet = load9(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && ((_v = (_u = instance.config.object) == null ? void 0 : _u.modelPath) == null ? void 0 : _v.includes("nanodet")))
instance.models.nanodet = load10(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && ((_x = (_w = instance.config.object) == null ? void 0 : _w.modelPath) == null ? void 0 : _x.includes("centernet")))
instance.models.centernet = load11(instance.config);
if (instance.config.face.enabled && ((_y = instance.config.face.emotion) == null ? void 0 : _y.enabled) && !instance.models.emotion)
if (instance.config.body.enabled && !instance.models.blazepose && ((_p = (_o = instance.config.body) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("blazepose")))
instance.models.blazepose = loadPose(instance.config);
if (instance.config.body.enabled && !instance.models.blazeposedetect && ((_q = instance.config.body.detector) == null ? void 0 : _q.modelPath) && ((_s = (_r = instance.config.body) == null ? void 0 : _r.modelPath) == null ? void 0 : _s.includes("blazepose")))
instance.models.blazeposedetect = loadDetect2(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && ((_u = (_t = instance.config.body) == null ? void 0 : _t.modelPath) == null ? void 0 : _u.includes("efficientpose")))
instance.models.efficientpose = load7(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && ((_w = (_v = instance.config.body) == null ? void 0 : _v.modelPath) == null ? void 0 : _w.includes("movenet")))
instance.models.movenet = load8(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && ((_y = (_x = instance.config.object) == null ? void 0 : _x.modelPath) == null ? void 0 : _y.includes("nanodet")))
instance.models.nanodet = load9(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && ((_A = (_z = instance.config.object) == null ? void 0 : _z.modelPath) == null ? void 0 : _A.includes("centernet")))
instance.models.centernet = load10(instance.config);
if (instance.config.face.enabled && ((_B = instance.config.face.emotion) == null ? void 0 : _B.enabled) && !instance.models.emotion)
instance.models.emotion = load4(instance.config);
if (instance.config.face.enabled && ((_z = instance.config.face.description) == null ? void 0 : _z.enabled) && !instance.models.faceres)
if (instance.config.face.enabled && ((_C = instance.config.face.description) == null ? void 0 : _C.enabled) && !instance.models.faceres)
instance.models.faceres = load3(instance.config);
if (instance.config.segmentation.enabled && !instance.models.segmentation)
instance.models.segmentation = load12(instance.config);
if (instance.config.face.enabled && ((_A = instance.config.face["agegenderrace"]) == null ? void 0 : _A.enabled) && !instance.models.agegenderrace)
instance.models.agegenderrace = load13(instance.config);
for await (const model11 of Object.keys(instance.models)) {
if (instance.models[model11] && typeof instance.models[model11] !== "undefined")
instance.models[model11] = await instance.models[model11];
instance.models.segmentation = load11(instance.config);
if (instance.config.face.enabled && ((_D = instance.config.face["agegenderrace"]) == null ? void 0 : _D.enabled) && !instance.models.agegenderrace)
instance.models.agegenderrace = load12(instance.config);
for await (const model10 of Object.keys(instance.models)) {
if (instance.models[model10] && typeof instance.models[model10] !== "undefined")
instance.models[model10] = await instance.models[model10];
}
}
async function validate2(instance) {
const simpleOps = ["const", "placeholder", "noop", "pad", "squeeze", "add", "sub", "mul", "div"];
for (const defined of Object.keys(instance.models)) {
if (instance.models[defined]) {
let models4 = [];
let models5 = [];
if (Array.isArray(instance.models[defined])) {
models4 = instance.models[defined].filter((model11) => model11 !== null).map((model11) => model11 && model11.executor ? model11 : model11.model);
models5 = instance.models[defined].filter((model10) => model10 !== null).map((model10) => model10 && model10.executor ? model10 : model10.model);
} else {
models4 = [instance.models[defined]];
models5 = [instance.models[defined]];
}
for (const model11 of models4) {
if (!model11) {
for (const model10 of models5) {
if (!model10) {
if (instance.config.debug)
log("model marked as loaded but not defined:", defined);
continue;
}
const ops = [];
const executor = model11 == null ? void 0 : model11.executor;
const executor = model10 == null ? void 0 : model10.executor;
if (executor && executor.graph.nodes) {
for (const kernel of Object.values(executor.graph.nodes)) {
const op = kernel.op.toLowerCase();
@ -10734,7 +10764,7 @@ async function validate2(instance) {
}
}
// src/face.ts
// src/face/face.ts
var tf24 = __toModule(require_tfjs_esm());
var calculateGaze = (face5) => {
const radians = (pt1, pt2) => Math.atan2(pt1[1] - pt2[1], pt1[0] - pt2[0]);
@ -11042,7 +11072,7 @@ var hand = (res) => {
return gestures;
};
// src/draw.ts
// src/util/draw.ts
var options2 = {
color: "rgba(173, 216, 230, 0.6)",
labelColor: "rgba(173, 216, 230, 1)",
@ -11588,7 +11618,7 @@ function join2(faces, bodies, hands, gestures, shape) {
return persons2;
}
// src/interpolate.ts
// src/util/interpolate.ts
var bufferedResult = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0 };
function calc(newResult) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u;
@ -12635,7 +12665,7 @@ var Human = class {
async load(userConfig) {
this.state = "load";
const timeStamp = now();
const count2 = Object.values(this.models).filter((model11) => model11).length;
const count2 = Object.values(this.models).filter((model10) => model10).length;
if (userConfig)
this.config = mergeDeep(this.config, userConfig);
if (env.initial) {
@ -12653,11 +12683,11 @@ var Human = class {
log("tf flags:", this.tf.ENV.flags);
}
}
await load14(this);
await load13(this);
if (env.initial && this.config.debug)
log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
env.initial = false;
const loaded = Object.values(this.models).filter((model11) => model11).length;
const loaded = Object.values(this.models).filter((model10) => model10).length;
if (loaded !== count2) {
await validate2(this);
this.emit("load");

2
src/blazeface/blazeface.ts
View File

@ -3,7 +3,7 @@
* See `facemesh.ts` for entry point
*/
import { log, join, mergeDeep } from '../util';
import { log, join, mergeDeep } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as box from './box';
import * as util from './util';

4
src/blazeface/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';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as blazeface from './blazeface';
import * as facepipeline from './facepipeline';
@ -15,7 +15,7 @@ import * as coords from './coords';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { FaceResult, Box } from '../result';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
let faceModels: [blazeface.BlazeFaceModel | null, GraphModel | null, GraphModel | null] = [null, null, null];
let facePipeline;

4
src/blazeface/facepipeline.ts
View File

@ -9,8 +9,8 @@ import * as util from './util';
import * as coords from './coords';
import type { Tensor, GraphModel } from '../tfjs/types';
import type { BlazeFaceModel } from './blazeface';
import { env } from '../env';
import { log } from '../util';
import { env } from '../util/env';
import { log } from '../util/util';
import type { Point } from '../result';
const leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];

0
src/blazepose/annotations.ts → src/body/annotations.ts
View File

4
src/blazepose/blazepose.ts → src/body/blazepose-v1.ts
View File

@ -4,13 +4,13 @@
* Based on : [**BlazePose**](https://drive.google.com/file/d/10IU-DRP2ioSNjKFdiGbmmQX81xAYj88s/view)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as annotations from './annotations';
import type { Tensor, GraphModel } from '../tfjs/types';
import type { BodyResult, Box, Point } from '../result';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
let model: GraphModel | null;

161
src/body/blazepose.ts Normal file
View File

@ -0,0 +1,161 @@
/**
* BlazePose model implementation
*
* Based on : [**BlazePose**](https://github.com/google/mediapipe/blob/master/mediapipe/modules/pose_detection)
*/
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import type { BodyResult, Box, Point } from '../result';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../util/env';
import * as annotations from './annotations';
// const boxScaleFact = 1.5; // hand finger model prefers slighly larger box
const models: [GraphModel | null, GraphModel | null] = [null, null];
const outputNodes = ['ld_3d', 'activation_segmentation', 'activation_heatmap', 'world_3d', 'output_poseflag'];
const inputSize = [[0, 0], [0, 0]];
// let skipped = 0;
let outputSize: [number, number] = [0, 0];
type Keypoints = { score: number, part: string, position: Point, positionRaw: Point };
/*
type BodyDetectResult = {
id: number,
score: number,
box: Box,
boxRaw: Box,
label: string,
yxBox: Box,
}
const cache: {
bodyBoxes: Array<BodyDetectResult>,
partBoxes: Array<BodyDetectResult>
tmpBoxes: Array<BodyDetectResult>
} = {
bodyBoxes: [],
partBoxes: [],
tmpBoxes: [],
};
*/
export async function loadDetect(config: Config): Promise<GraphModel> {
if (env.initial) models[0] = null;
if (!models[0]) {
models[0] = await tf.loadGraphModel(join(config.modelBasePath, config.body.detector?.modelPath || '')) as unknown as GraphModel;
const inputs = Object.values(models[0].modelSignature['inputs']);
inputSize[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models[0] || !models[0]['modelUrl']) log('load model failed:', config.object.modelPath);
else if (config.debug) log('load model:', models[0]['modelUrl']);
} else if (config.debug) log('cached model:', models[0]['modelUrl']);
return models[0];
}
export async function loadPose(config: Config): Promise<GraphModel> {
if (env.initial) models[1] = null;
if (!models[1]) {
models[1] = await tf.loadGraphModel(join(config.modelBasePath, config.body.modelPath || '')) as unknown as GraphModel;
const inputs = Object.values(models[1].modelSignature['inputs']);
inputSize[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
if (!models[1] || !models[1]['modelUrl']) log('load model failed:', config.object.modelPath);
else if (config.debug) log('load model:', models[1]['modelUrl']);
} else if (config.debug) log('cached model:', models[1]['modelUrl']);
return models[1];
}
export async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {
if (!models[0]) await loadDetect(config);
if (!models[1]) await loadPose(config);
return models;
}
/*
async function detectBody(input: Tensor, config: Config): Promise<BodyDetectResult[]> {
if ((config.body.detector?.modelPath.length || 0) > 0 && models[0]) {
const t: Record<string, Tensor> = {};
t.resize = tf.image.resizeBilinear(input, [inputSize[0][0], inputSize[0][1]]);
t.res = await models[0]?.predict(t.resize) as Tensor; // [1,2254,13]
t.logits = tf.slice(t.res, [0, 0, 0], [1, -1, 1]);
t.sigmoid = tf.sigmoid(t.logits);
t.rawBoxes = tf.slice(t.res, [0, 0, 1], [1, -1, -1]);
t.packedBoxes = tf.squeeze(t.rawBoxes); // [2254,12]
t.scores = tf.squeeze(t.sigmoid); // [2254,1]
// boxes need to be decoded based on anchors
Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));
}
return [];
}
*/
async function detectParts(input: Tensor, config: Config): Promise<BodyResult> {
const t: Record<string, Tensor> = {};
t.resize = tf.image.resizeBilinear(input, [inputSize[1][0], inputSize[1][1]]);
[t.ld/* 1,195 */, t.segmentation/* 1,256,256,1 */, t.heatmap/* 1,64,64,39 */, t.world/* 1,117 */, t.poseflag/* 1,1 */] = await models[1]?.execute(t.resize, outputNodes) as Tensor[]; // [1,2254,13]
const points = await t.ld.data();
const keypoints: Array<Keypoints> = [];
const labels = points?.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints
const depth = 5; // each points has x,y,z,visibility,presence
for (let i = 0; i < points.length / depth; i++) {
const score = (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100; // reverse sigmoid value
// const presence = (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100; // reverse sigmoid value
if (score > (config.body.minConfidence || 0)) {
keypoints.push({
part: labels[i],
position: [
Math.trunc(outputSize[0] * points[depth * i + 0] / 255), // return normalized x value istead of 0..255
Math.trunc(outputSize[1] * points[depth * i + 1] / 255), // return normalized y value istead of 0..255
Math.trunc(points[depth * i + 2]) + 0, // fix negative zero
],
positionRaw: [
points[depth * i + 0] / 255, // return x value normalized to 0..1
points[depth * i + 1] / 255, // return y value normalized to 0..1
points[depth * i + 2] + 0, // fix negative zero
],
score,
});
}
}
const x = keypoints.map((a) => a.position[0]);
const y = keypoints.map((a) => a.position[1]);
const box: Box = [
Math.min(...x),
Math.min(...y),
Math.max(...x) - Math.min(...x),
Math.max(...y) - Math.min(...x),
];
const boxRaw: Box = [0, 0, 0, 0]; // not yet implemented
const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);
Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));
return { id: 0, score, box, boxRaw, keypoints };
}
export async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {
outputSize = [input.shape[2] || 0, input.shape[1] || 0];
const bodies: Array<BodyResult> = [];
const body = await detectParts(input, config);
bodies.push(body);
/*
cache.tmpBoxes = []; // clear temp cache
if ((skipped < (config.body.skipFrames || 0)) && config.skipFrame) { // just run part detection while reusing cached boxes
skipped++;
bodies = await Promise.all(cache.partBoxes.map((body) => detectParts(input, body, config))); // run from parts box cache
} else { // calculate new boxes and run part detection
skipped = 0;
bodies = await Promise.all(cache.partBoxes.map((body) => detectParts(input, body, config))); // run from part box cache
if (bodies.length !== config.body.maxDetected) { // run body detection only if we dont have enough bodies in cache
cache.bodyBoxes = await detectBody(input, config);
const newBodies = await Promise.all(cache.bodyBoxes.map((body) => detectParts(input, body, config)));
bodies = bodies.concat(newBodies);
}
}
cache.partBoxes = [...cache.tmpBoxes]; // repopulate cache with validated bodies
*/
return bodies as BodyResult[];
}

4
src/efficientpose/efficientpose.ts → src/body/efficientpose.ts
View File

@ -4,12 +4,12 @@
* Based on: [**EfficientPose**](https://github.com/daniegr/EfficientPose)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import type { BodyResult, Box } from '../result';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
let model: GraphModel | null;

11
src/movenet/movenet.ts → src/body/movenet.ts
View File

@ -4,19 +4,20 @@
* Based on: [**MoveNet**](https://blog.tensorflow.org/2021/05/next-generation-pose-detection-with-movenet-and-tensorflowjs.html)
*/
import { log, join, scaleBox } from '../util';
import { log, join } from '../util/util';
import { scale } from '../util/box';
import * as tf from '../../dist/tfjs.esm.js';
import type { BodyResult, Box } from '../result';
import type { BodyResult, Box, Point } from '../result';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { fakeOps } from '../tfjs/backend';
import { env } from '../env';
import { env } from '../util/env';
let model: GraphModel | null;
let inputSize = 0;
const cachedBoxes: Array<Box> = [];
type Keypoints = { score: number, part: string, position: [number, number], positionRaw: [number, number] };
type Keypoints = { score: number, part: string, position: Point, positionRaw: Point };
type Body = { id: number, score: number, box: Box, boxRaw: Box, keypoints: Array<Keypoints> }
let skipped = Number.MAX_SAFE_INTEGER;
@ -157,7 +158,7 @@ export async function predict(input: Tensor, config: Config): Promise<BodyResult
for (let i = 0; i < bodies.length; i++) {
if (bodies[i].keypoints.length > 10) { // only update cache if we detected sufficient number of keypoints
const kpts = bodies[i].keypoints.map((kpt) => kpt.position);
const newBox = scaleBox(kpts, 1.5, [input.shape[2], input.shape[1]]);
const newBox = scale(kpts, 1.5, [input.shape[2], input.shape[1]]);
cachedBoxes.push([...newBox.yxBox]);
}
}

7
src/config.ts
View File

@ -70,6 +70,7 @@ export interface FaceConfig {
* - modelPath: body pose model, can be absolute path or relative to modelBasePath
* - minConfidence: threshold for discarding a prediction
* - maxDetected: maximum number of people detected in the input, should be set to the minimum number for performance
* - detector: optional body detector
*
* `maxDetected` is valid for `posenet` and `movenet-multipose` as other models are single-pose only
* `maxDetected` can be set to -1 to auto-detect based on number of detected faces
@ -83,6 +84,9 @@ export interface BodyConfig {
maxDetected: number,
minConfidence: number,
skipFrames: number,
detector?: {
modelPath: string
},
}
/** Controlls and configures all hand detection specific options
@ -399,6 +403,9 @@ const config: Config = {
enabled: true,
modelPath: 'movenet-lightning.json', // body model, can be absolute path or relative to modelBasePath
// can be 'posenet', 'blazepose', 'efficientpose', 'movenet-lightning', 'movenet-thunder'
detector: {
modelPath: '', // optional body detector
},
maxDetected: -1, // maximum number of people detected in the input
// should be set to the minimum number for performance
// only valid for posenet and movenet-multipose as other models detects single pose

4
src/embedding/embedding.ts → src/face/embedding.ts
View File

@ -6,10 +6,10 @@
* Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import type { Tensor, GraphModel } from '../tfjs/types';
import { env } from '../env';
import { env } from '../util/env';
type DB = Array<{ name: string, source: string, embedding: number[] }>;
let model: GraphModel | null;

14
src/face.ts → src/face/face.ts
View File

@ -3,13 +3,13 @@
* Uses FaceMesh, Emotion and FaceRes models to create a unified pipeline
*/
import { log, now } from './util';
import * as tf from '../dist/tfjs.esm.js';
import * as facemesh from './blazeface/facemesh';
import * as emotion from './emotion/emotion';
import * as faceres from './faceres/faceres';
import type { FaceResult } from './result';
import type { Tensor } from './tfjs/types';
import { log, now } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as facemesh from '../blazeface/facemesh';
import * as emotion from '../gear/emotion';
import * as faceres from './faceres';
import type { FaceResult } from '../result';
import type { Tensor } from '../tfjs/types';
// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars
const rad2deg = (theta) => Math.round((theta * 180) / Math.PI);

4
src/faceres/faceres.ts → src/face/faceres.ts
View File

@ -7,11 +7,11 @@
* Based on: [**HSE-FaceRes**](https://github.com/HSE-asavchenko/HSE_FaceRec_tf)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import type { Tensor, GraphModel } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
let model: GraphModel | null;
const last: Array<{

4
src/emotion/emotion.ts → src/gear/emotion.ts
View File

@ -4,11 +4,11 @@
* [**Oarriaga**](https://github.com/oarriaga/face_classification)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import type { Config } from '../config';
import type { GraphModel, Tensor } from '../tfjs/types';
import * as tf from '../../dist/tfjs.esm.js';
import { env } from '../env';
import { env } from '../util/env';
const annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];
let model: GraphModel | null;

4
src/gear/agegenderrace.ts → src/gear/gear-agegenderrace.ts
View File

@ -7,11 +7,11 @@
* Config placeholder: agegenderrace: { enabled: true, modelPath: 'gear.json' },
*/
import { log, join } from '../util';
import { log, join } 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 '../env';
import { env } from '../util/env';
let model: GraphModel | null;

4
src/ssrnet/age.ts → src/gear/ssrnet-age.ts
View File

@ -6,11 +6,11 @@
* Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis
*/
import { log, join } from '../util';
import { log, join } 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 '../env';
import { env } from '../util/env';
let model: GraphModel | null;

4
src/ssrnet/gender.ts → src/gear/ssrnet-gender.ts
View File

@ -6,11 +6,11 @@
* Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis
*/
import { log, join } from '../util';
import { log, join } 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 '../env';
import { env } from '../util/env';
let model: GraphModel | null;
let last = { gender: '' };

7
src/handtrack/handtrack.ts → src/hand/handtrack.ts
View File

@ -6,12 +6,13 @@
* - Hand Tracking: [**HandTracking**](https://github.com/victordibia/handtracking)
*/
import { log, join, scaleBox } from '../util';
import { log, join } from '../util/util';
import { scale } from '../util/box';
import * as tf from '../../dist/tfjs.esm.js';
import type { HandResult, Box } from '../result';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
import * as fingerPose from '../fingerpose/fingerpose';
import { fakeOps } from '../tfjs/backend';
@ -168,7 +169,7 @@ async function detectFingers(input: Tensor, h: HandDetectResult, config: Config)
(h.box[3] * coord[1] / inputSize[1][1]) + h.box[1],
(h.box[2] + h.box[3]) / 2 / inputSize[1][0] * coord[2],
]);
const updatedBox = scaleBox(hand.keypoints, boxScaleFact, outputSize); // replace detected box with box calculated around keypoints
const updatedBox = scale(hand.keypoints, boxScaleFact, outputSize); // replace detected box with box calculated around keypoints
h.box = updatedBox.box;
h.boxRaw = updatedBox.boxRaw;
h.yxBox = updatedBox.yxBox;

2
src/handpose/handpipeline.ts
View File

@ -8,7 +8,7 @@ import * as box from './box';
import * as util from './util';
import type * as detector from './handdetector';
import type { Tensor, GraphModel } from '../tfjs/types';
import { env } from '../env';
import { env } from '../util/env';
const palmBoxEnlargeFactor = 5; // default 3
const handBoxEnlargeFactor = 1.65; // default 1.65

4
src/handpose/handpose.ts
View File

@ -4,7 +4,7 @@
* Based on: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as handdetector from './handdetector';
import * as handpipeline from './handpipeline';
@ -12,7 +12,7 @@ import * as fingerPose from '../fingerpose/fingerpose';
import type { HandResult, Box, Point } from '../result';
import type { Tensor, GraphModel } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
const meshAnnotations = {
thumb: [1, 2, 3, 4],

27
src/human.ts
View File

@ -2,41 +2,42 @@
* Human main module
*/
import { log, now, mergeDeep, validate } from './util';
import { log, now, mergeDeep, validate } from './util/util';
import { Config, defaults } from './config';
import type { Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, PersonResult } from './result';
import * as tf from '../dist/tfjs.esm.js';
import * as models from './models';
import * as face from './face';
import * as face from './face/face';
import * as facemesh from './blazeface/facemesh';
import * as faceres from './faceres/faceres';
import * as faceres from './face/faceres';
import * as posenet from './posenet/posenet';
import * as handtrack from './handtrack/handtrack';
import * as handtrack from './hand/handtrack';
import * as handpose from './handpose/handpose';
import * as blazepose from './blazepose/blazepose';
import * as efficientpose from './efficientpose/efficientpose';
import * as movenet from './movenet/movenet';
// import * as blazepose from './body/blazepose-v1';
import * as blazepose from './body/blazepose';
import * as efficientpose from './body/efficientpose';
import * as movenet from './body/movenet';
import * as nanodet from './object/nanodet';
import * as centernet from './object/centernet';
import * as segmentation from './segmentation/segmentation';
import * as gesture from './gesture/gesture';
import * as image from './image/image';
import * as draw from './draw';
import * as draw from './util/draw';
import * as persons from './persons';
import * as interpolate from './interpolate';
import * as env from './env';
import * as interpolate from './util/interpolate';
import * as env from './util/env';
import * as backend from './tfjs/backend';
import * as humangl from './tfjs/humangl';
import * as app from '../package.json';
import * as warmups from './warmup';
import type { Tensor } from './tfjs/types';
import type { DrawOptions } from './draw';
import type { DrawOptions } from './util/draw';
// export types
export * from './config';
export * from './result';
export type { DrawOptions } from './draw';
export { env, Env } from './env';
export type { DrawOptions } from './util/draw';
export { env, Env } from './util/env';
export { Box, Point } from './result';
export { Models } from './models';

4
src/image/image.ts
View File

@ -6,8 +6,8 @@ import * as tf from '../../dist/tfjs.esm.js';
import * as fxImage from './imagefx';
import type { Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { log } from '../util';
import { env } from '../util/env';
import { log } from '../util/util';
type Input = Tensor | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas | typeof Image | typeof env.Canvas;

24
src/models.ts
View File

@ -2,23 +2,23 @@
* Loader and Validator for all models used by Human
*/
import { log } from './util';
import { log } from './util/util';
import type { GraphModel } from './tfjs/types';
import * as facemesh from './blazeface/facemesh';
import * as faceres from './faceres/faceres';
import * as emotion from './emotion/emotion';
import * as faceres from './face/faceres';
import * as emotion from './gear/emotion';
import * as posenet from './posenet/posenet';
import * as handpose from './handpose/handpose';
import * as handtrack from './handtrack/handtrack';
import * as blazepose from './blazepose/blazepose';
import * as efficientpose from './efficientpose/efficientpose';
import * as movenet from './movenet/movenet';
import * as handtrack from './hand/handtrack';
import * as blazepose from './body/blazepose';
import * as efficientpose from './body/efficientpose';
import * as movenet from './body/movenet';
import * as nanodet from './object/nanodet';
import * as centernet from './object/centernet';
import * as segmentation from './segmentation/segmentation';
import type { Human } from './human';
import { env } from './env';
import * as agegenderrace from './gear/agegenderrace';
import { env } from './util/env';
import * as agegenderrace from './gear/gear-agegenderrace';
/** Instances of all possible TFJS Graph Models used by Human
* - loaded as needed based on configuration
@ -29,6 +29,7 @@ import * as agegenderrace from './gear/agegenderrace';
export class Models {
age: null | GraphModel | Promise<GraphModel> = null;
agegenderrace: null | GraphModel | Promise<GraphModel> = null;
blazeposedetect: null | GraphModel | Promise<GraphModel> = null;
blazepose: null | GraphModel | Promise<GraphModel> = null;
centernet: null | GraphModel | Promise<GraphModel> = null;
efficientpose: null | GraphModel | Promise<GraphModel> = null;
@ -69,8 +70,9 @@ export async function load(instance: Human) {
if (instance.config.hand.enabled && instance.config.hand.landmarks && !instance.models.handskeleton && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handskeleton = handtrack.loadSkeleton(instance.config);
if (instance.config.body.enabled && !instance.models.posenet && instance.config.body?.modelPath?.includes('posenet')) instance.models.posenet = posenet.load(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && instance.config.body?.modelPath?.includes('efficientpose')) instance.models.efficientpose = efficientpose.load(instance.config);
if (instance.config.body.enabled && !instance.models.blazepose && instance.config.body?.modelPath?.includes('blazepose')) instance.models.blazepose = blazepose.load(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && instance.config.body?.modelPath?.includes('efficientpose')) instance.models.efficientpose = blazepose.load(instance.config);
if (instance.config.body.enabled && !instance.models.blazepose && instance.config.body?.modelPath?.includes('blazepose')) instance.models.blazepose = blazepose.loadPose(instance.config);
if (instance.config.body.enabled && !instance.models.blazeposedetect && instance.config.body.detector?.modelPath && instance.config.body?.modelPath?.includes('blazepose')) instance.models.blazeposedetect = blazepose.loadDetect(instance.config);
if (instance.config.body.enabled && !instance.models.efficientpose && instance.config.body?.modelPath?.includes('efficientpose')) instance.models.efficientpose = efficientpose.load(instance.config);
if (instance.config.body.enabled && !instance.models.movenet && instance.config.body?.modelPath?.includes('movenet')) instance.models.movenet = movenet.load(instance.config);
if (instance.config.object.enabled && !instance.models.nanodet && instance.config.object?.modelPath?.includes('nanodet')) instance.models.nanodet = nanodet.load(instance.config);
if (instance.config.object.enabled && !instance.models.centernet && instance.config.object?.modelPath?.includes('centernet')) instance.models.centernet = centernet.load(instance.config);

4
src/object/centernet.ts
View File

@ -4,13 +4,13 @@
* Based on: [**NanoDet**](https://github.com/RangiLyu/nanodet)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import { labels } from './labels';
import type { ObjectResult, Box } from '../result';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
import { fakeOps } from '../tfjs/backend';
let model: GraphModel | null;

4
src/object/nanodet.ts
View File

@ -4,13 +4,13 @@
* Based on: [**MB3-CenterNet**](https://github.com/610265158/mobilenetv3_centernet)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import { labels } from './labels';
import type { ObjectResult, Box } from '../result';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
let model;
let last: Array<ObjectResult> = [];

4
src/posenet/posenet.ts
View File

@ -4,14 +4,14 @@
* Based on: [**PoseNet**](https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as poses from './poses';
import * as util from './utils';
import type { BodyResult } from '../result';
import type { Tensor, GraphModel } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
let model: GraphModel;
const poseNetOutputs = ['MobilenetV1/offset_2/BiasAdd'/* offsets */, 'MobilenetV1/heatmap_2/BiasAdd'/* heatmapScores */, 'MobilenetV1/displacement_fwd_2/BiasAdd'/* displacementFwd */, 'MobilenetV1/displacement_bwd_2/BiasAdd'/* displacementBwd */];

4
src/segmentation/segmentation.ts
View File

@ -6,12 +6,12 @@
* - [**MediaPipe Selfie**](https://drive.google.com/file/d/1dCfozqknMa068vVsO2j_1FgZkW_e3VWv/preview)
*/
import { log, join } from '../util';
import { log, join } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as image from '../image/image';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
type Input = Tensor | typeof Image | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;

4
src/tfjs/backend.ts
View File

@ -1,8 +1,8 @@
/** TFJS backend initialization and customization */
import { log, now } from '../util';
import { log, now } from '../util/util';
import * as humangl from './humangl';
import * as env from '../env';
import * as env from '../util/env';
import * as tf from '../../dist/tfjs.esm.js';
export async function check(instance, force = false) {

2
src/tfjs/humangl.ts
View File

@ -1,6 +1,6 @@
/** TFJS custom backend registration */
import { log } from '../util';
import { log } from '../util/util';
import * as tf from '../../dist/tfjs.esm.js';
import * as image from '../image/image';
import * as models from '../models';

28
src/util/box.ts Normal file
View File

@ -0,0 +1,28 @@
import type { Box } from '../result';
// helper function: find box around keypoints, square it and scale it
export function scale(keypoints, boxScaleFact, outputSize) {
const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords
const maxmin = [Math.max(...coords[0]), Math.min(...coords[0]), Math.max(...coords[1]), Math.min(...coords[1])]; // find min/max x/y coordinates
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2]; // find center x and y coord of all fingers
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact; // largest distance from center in any direction
const box = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff),
] as Box;
const boxRaw = [ // work backwards
box[0] / outputSize[0],
box[1] / outputSize[1],
box[2] / outputSize[0],
box[3] / outputSize[1],
] as Box;
const yxBox = [ // work backwards
boxRaw[1],
boxRaw[0],
boxRaw[3] + boxRaw[1],
boxRaw[2] + boxRaw[0],
] as Box;
return { box, boxRaw, yxBox };
}

4
src/draw.ts → src/util/draw.ts
View File

@ -2,9 +2,9 @@
* Module that implements helper draw functions, exposed as human.draw
*/
import { TRI468 as triangulation } from './blazeface/coords';
import { TRI468 as triangulation } from '../blazeface/coords';
import { mergeDeep, now } from './util';
import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult } from './result';
import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult } from '../result';
/**
* Draw Options

4
src/env.ts → src/util/env.ts
View File

@ -1,5 +1,5 @@
import * as tf from '../dist/tfjs.esm.js';
import * as image from './image/image';
import * as tf from '../../dist/tfjs.esm.js';
import * as image from '../image/image';
import { mergeDeep } from './util';
export type Env = {

2
src/interpolate.ts → src/util/interpolate.ts
View File

@ -2,7 +2,7 @@
* Results interpolation for smoothening of video detection results inbetween detected frames
*/
import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Box, Point } from './result';
import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Box, Point } from '../result';
const bufferedResult: Result = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0 };

0
src/profile.ts → src/util/profile.ts
View File

29
src/util.ts → src/util/util.ts
View File

@ -2,8 +2,6 @@
* Simple helper functions used accross codebase
*/
import type { Box } from './result';
// helper function: join two paths
export function join(folder: string, file: string): string {
const separator = folder.endsWith('/') ? '' : '/';
@ -71,30 +69,3 @@ export async function wait(time) {
const waiting = new Promise((resolve) => setTimeout(() => resolve(true), time));
await waiting;
}
// helper function: find box around keypoints, square it and scale it
export function scaleBox(keypoints, boxScaleFact, outputSize) {
const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords
const maxmin = [Math.max(...coords[0]), Math.min(...coords[0]), Math.max(...coords[1]), Math.min(...coords[1])]; // find min/max x/y coordinates
const center = [(maxmin[0] + maxmin[1]) / 2, (maxmin[2] + maxmin[3]) / 2]; // find center x and y coord of all fingers
const diff = Math.max(center[0] - maxmin[1], center[1] - maxmin[3], -center[0] + maxmin[0], -center[1] + maxmin[2]) * boxScaleFact; // largest distance from center in any direction
const box = [
Math.trunc(center[0] - diff),
Math.trunc(center[1] - diff),
Math.trunc(2 * diff),
Math.trunc(2 * diff),
] as Box;
const boxRaw = [ // work backwards
box[0] / outputSize[0],
box[1] / outputSize[1],
box[2] / outputSize[0],
box[3] / outputSize[1],
] as Box;
const yxBox = [ // work backwards
boxRaw[1],
boxRaw[0],
boxRaw[3] + boxRaw[1],
boxRaw[2] + boxRaw[0],
] as Box;
return { box, boxRaw, yxBox };
}

4
src/warmup.ts
View File

@ -2,13 +2,13 @@
* Warmup algorithm that uses embedded images to excercise loaded models for faster future inference
*/
import { log, now, mergeDeep } from './util';
import { log, now, mergeDeep } from './util/util';
import * as sample from './sample';
import * as tf from '../dist/tfjs.esm.js';
import * as image from './image/image';
import type { Config } from './config';
import type { Result } from './result';
import { env } from './env';
import { env } from './util/env';
async function warmupBitmap(instance) {
const b64toBlob = (base64: string, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());

48
test/build.log
View File

@ -1,24 +1,24 @@
2021-09-27 09:18:45 INFO:  @vladmandic/human version 2.2.3
2021-09-27 09:18:45 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.5.0
2021-09-27 09:18:45 INFO:  Application: {"name":"@vladmandic/human","version":"2.2.3"}
2021-09-27 09:18:45 INFO:  Environment: {"profile":"production","config":"build.json","tsconfig":true,"eslintrc":true,"git":true}
2021-09-27 09:18:45 INFO:  Toolchain: {"build":"0.5.3","esbuild":"0.13.2","typescript":"4.4.3","typedoc":"0.22.4","eslint":"7.32.0"}
2021-09-27 09:18:45 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]}
2021-09-27 09:18:45 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]}
2021-09-27 09:18:45 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}
2021-09-27 09:18:45 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":52,"inputBytes":506509,"outputBytes":422941}
2021-09-27 09:18:45 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}
2021-09-27 09:18:45 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":52,"inputBytes":506517,"outputBytes":422945}
2021-09-27 09:18:45 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}
2021-09-27 09:18:45 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":52,"inputBytes":506584,"outputBytes":423017}
2021-09-27 09:18:45 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":1631}
2021-09-27 09:18:45 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":3088,"outputBytes":793}
2021-09-27 09:18:45 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":52,"inputBytes":506027,"outputBytes":424428}
2021-09-27 09:18:45 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":3088,"outputBytes":2377041}
2021-09-27 09:18:46 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":52,"inputBytes":2882275,"outputBytes":1418176}
2021-09-27 09:18:46 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":52,"inputBytes":2882275,"outputBytes":2628827}
2021-09-27 09:18:57 STATE: Typings: {"input":"src/human.ts","output":"types","files":98}
2021-09-27 09:19:01 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":33,"generated":true}
2021-09-27 09:19:20 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":85,"errors":0,"warnings":0}
2021-09-27 09:19:20 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"}
2021-09-27 09:19:20 INFO:  Done...
2021-09-27 13:56:53 INFO:  @vladmandic/human version 2.2.3
2021-09-27 13:56:53 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.5.0
2021-09-27 13:56:53 INFO:  Application: {"name":"@vladmandic/human","version":"2.2.3"}
2021-09-27 13:56:53 INFO:  Environment: {"profile":"production","config":"build.json","tsconfig":true,"eslintrc":true,"git":true}
2021-09-27 13:56:53 INFO:  Toolchain: {"build":"0.5.3","esbuild":"0.13.2","typescript":"4.4.3","typedoc":"0.22.4","eslint":"7.32.0"}
2021-09-27 13:56:53 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]}
2021-09-27 13:56:53 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]}
2021-09-27 13:56:53 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}
2021-09-27 13:56:53 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":53,"inputBytes":510889,"outputBytes":424465}
2021-09-27 13:56:53 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}
2021-09-27 13:56:53 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":53,"inputBytes":510897,"outputBytes":424469}
2021-09-27 13:56:53 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}
2021-09-27 13:56:53 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":53,"inputBytes":510964,"outputBytes":424541}
2021-09-27 13:56:53 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":1631}
2021-09-27 13:56:53 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":3088,"outputBytes":793}
2021-09-27 13:56:53 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":53,"inputBytes":510407,"outputBytes":425933}
2021-09-27 13:56:54 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":3088,"outputBytes":2377041}
2021-09-27 13:56:54 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":53,"inputBytes":2886655,"outputBytes":1419179}
2021-09-27 13:56:55 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":53,"inputBytes":2886655,"outputBytes":2630435}
2021-09-27 13:57:11 STATE: Typings: {"input":"src/human.ts","output":"types","files":100}
2021-09-27 13:57:16 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":33,"generated":true}
2021-09-27 13:57:43 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":87,"errors":0,"warnings":0}
2021-09-27 13:57:43 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"}
2021-09-27 13:57:43 INFO:  Done...

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@ -8,16 +8,16 @@
</ul>
</div><dl class="tsd-comment-tags"><dt>param userConfig:</dt><dd><p><a href="../interfaces/Config.html">Config</a></p>
</dd><dt>returns</dt><dd><p>instance</p>
</dd></dl></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">Human</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>Constructors</h3><ul class="tsd-index-list"><li class="tsd-kind-constructor tsd-parent-kind-class"><a href="Human.html#constructor" class="tsd-kind-icon">constructor</a></li></ul></section><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#config" class="tsd-kind-icon">config</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#draw" class="tsd-kind-icon">draw</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#env" class="tsd-kind-icon">env</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#events" class="tsd-kind-icon">events</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#faceTriangulation" class="tsd-kind-icon">face<wbr/>Triangulation</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#faceUVMap" class="tsd-kind-icon">faceUVMap</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#gl" class="tsd-kind-icon">gl</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#performance" class="tsd-kind-icon">performance</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#process" class="tsd-kind-icon">process</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#result" class="tsd-kind-icon">result</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#state" class="tsd-kind-icon">state</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#version" class="tsd-kind-icon">version</a></li></ul></section><section class="tsd-index-section "><h3>Methods</h3><ul class="tsd-index-list"><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#detect" class="tsd-kind-icon">detect</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#enhance" class="tsd-kind-icon">enhance</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#image" class="tsd-kind-icon">image</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#init" class="tsd-kind-icon">init</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#load" class="tsd-kind-icon">load</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#match" class="tsd-kind-icon">match</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#next" class="tsd-kind-icon">next</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#reset" class="tsd-kind-icon">reset</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#segmentation" class="tsd-kind-icon">segmentation</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#similarity" class="tsd-kind-icon">similarity</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#validate" class="tsd-kind-icon">validate</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#warmup" class="tsd-kind-icon">warmup</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Constructors</h2><section class="tsd-panel tsd-member tsd-kind-constructor tsd-parent-kind-class"><a name="constructor" class="tsd-anchor"></a><h3>constructor</h3><ul class="tsd-signatures tsd-kind-constructor tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">new <wbr/>Human<span class="tsd-signature-symbol">(</span>userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><a href="Human.html" class="tsd-signature-type" data-tsd-kind="Class">Human</a></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L161">human.ts:161</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</dd></dl></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">Human</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>Constructors</h3><ul class="tsd-index-list"><li class="tsd-kind-constructor tsd-parent-kind-class"><a href="Human.html#constructor" class="tsd-kind-icon">constructor</a></li></ul></section><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#config" class="tsd-kind-icon">config</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#draw" class="tsd-kind-icon">draw</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#env" class="tsd-kind-icon">env</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#events" class="tsd-kind-icon">events</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#faceTriangulation" class="tsd-kind-icon">face<wbr/>Triangulation</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#faceUVMap" class="tsd-kind-icon">faceUVMap</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#gl" class="tsd-kind-icon">gl</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#performance" class="tsd-kind-icon">performance</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#process" class="tsd-kind-icon">process</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#result" class="tsd-kind-icon">result</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#state" class="tsd-kind-icon">state</a></li><li class="tsd-kind-property tsd-parent-kind-class"><a href="Human.html#version" class="tsd-kind-icon">version</a></li></ul></section><section class="tsd-index-section "><h3>Methods</h3><ul class="tsd-index-list"><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#detect" class="tsd-kind-icon">detect</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#enhance" class="tsd-kind-icon">enhance</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#image" class="tsd-kind-icon">image</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#init" class="tsd-kind-icon">init</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#load" class="tsd-kind-icon">load</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#match" class="tsd-kind-icon">match</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#next" class="tsd-kind-icon">next</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#reset" class="tsd-kind-icon">reset</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#segmentation" class="tsd-kind-icon">segmentation</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#similarity" class="tsd-kind-icon">similarity</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#validate" class="tsd-kind-icon">validate</a></li><li class="tsd-kind-method tsd-parent-kind-class"><a href="Human.html#warmup" class="tsd-kind-icon">warmup</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Constructors</h2><section class="tsd-panel tsd-member tsd-kind-constructor tsd-parent-kind-class"><a name="constructor" class="tsd-anchor"></a><h3>constructor</h3><ul class="tsd-signatures tsd-kind-constructor tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">new <wbr/>Human<span class="tsd-signature-symbol">(</span>userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><a href="Human.html" class="tsd-signature-type" data-tsd-kind="Class">Human</a></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L162">human.ts:162</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Constructor for <strong>Human</strong> library that is futher used for all operations</p>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5><span class="tsd-flag ts-flagOptional">Optional</span> userConfig: <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span></h5></li></ul><h4 class="tsd-returns-title">Returns <a href="Human.html" class="tsd-signature-type" data-tsd-kind="Class">Human</a></h4><div><p>instance: <a href="Human.html">Human</a></p>
</div></li></ul></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-class"><a name="config" class="tsd-anchor"></a><h3>config</h3><div class="tsd-signature tsd-kind-icon">config<span class="tsd-signature-symbol">:</span> <a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L87">human.ts:87</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></li></ul></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-class"><a name="config" class="tsd-anchor"></a><h3>config</h3><div class="tsd-signature tsd-kind-icon">config<span class="tsd-signature-symbol">:</span> <a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L88">human.ts:88</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Current configuration</p>
<ul>
<li>Definition: <a href="../interfaces/Config.html">Config</a></li>
<li>Defaults: <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L292">config</a></li>
</ul>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="draw" class="tsd-anchor"></a><h3>draw</h3><div class="tsd-signature tsd-kind-icon">draw<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">{ </span>all<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>body<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>face<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>object<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>options<span class="tsd-signature-symbol">: </span><a href="../interfaces/DrawOptions.html" class="tsd-signature-type" data-tsd-kind="Interface">DrawOptions</a><span class="tsd-signature-symbol">; </span>person<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol"> }</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L123">human.ts:123</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-class"><a name="draw" class="tsd-anchor"></a><h3>draw</h3><div class="tsd-signature tsd-kind-icon">draw<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">{ </span>all<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>body<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>face<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>object<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">; </span>options<span class="tsd-signature-symbol">: </span><a href="../interfaces/DrawOptions.html" class="tsd-signature-type" data-tsd-kind="Interface">DrawOptions</a><span class="tsd-signature-symbol">; </span>person<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol"> }</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L124">human.ts:124</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Draw helper classes that can draw detected objects on canvas using specified draw</p>
<ul>
<li>options: <a href="../interfaces/DrawOptions.html">DrawOptions</a> global settings for all draw operations, can be overriden for each draw method</li>
@ -27,9 +27,9 @@
<li>canvas: draw processed canvas which is a processed copy of the input</li>
<li>all: meta-function that performs: canvas, face, body, hand</li>
</ul>
</div></div><div class="tsd-type-declaration"><h4>Type declaration</h4><ul class="tsd-parameters"><li class="tsd-parameter"><h5>all<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>body<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>face<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>object<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>options<span class="tsd-signature-symbol">: </span><a href="../interfaces/DrawOptions.html" class="tsd-signature-type" data-tsd-kind="Interface">DrawOptions</a></h5></li><li class="tsd-parameter"><h5>person<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li></ul></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="env" class="tsd-anchor"></a><h3>env</h3><div class="tsd-signature tsd-kind-icon">env<span class="tsd-signature-symbol">:</span> <a href="../index.html#Env" class="tsd-signature-type" data-tsd-kind="Type alias">Env</a></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L113">human.ts:113</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div><div class="tsd-type-declaration"><h4>Type declaration</h4><ul class="tsd-parameters"><li class="tsd-parameter"><h5>all<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>body<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>face<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>object<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li><li class="tsd-parameter"><h5>options<span class="tsd-signature-symbol">: </span><a href="../interfaces/DrawOptions.html" class="tsd-signature-type" data-tsd-kind="Interface">DrawOptions</a></h5></li><li class="tsd-parameter"><h5>person<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span></h5></li></ul></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="env" class="tsd-anchor"></a><h3>env</h3><div class="tsd-signature tsd-kind-icon">env<span class="tsd-signature-symbol">:</span> <a href="../index.html#Env" class="tsd-signature-type" data-tsd-kind="Type alias">Env</a></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L114">human.ts:114</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Object containing environment information used for diagnostics</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="events" class="tsd-anchor"></a><h3>events</h3><div class="tsd-signature tsd-kind-icon">events<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">EventTarget</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L141">human.ts:141</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-class"><a name="events" class="tsd-anchor"></a><h3>events</h3><div class="tsd-signature tsd-kind-icon">events<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">EventTarget</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L142">human.ts:142</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Container for events dispatched by Human</p>
</div><div><p>Possible events:</p>
<ul>
@ -40,31 +40,31 @@
<li><code>warmup</code>: triggered when warmup is complete</li>
<li><code>error</code>: triggered on some errors</li>
</ul>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="faceTriangulation" class="tsd-anchor"></a><h3>face<wbr/>Triangulation</h3><div class="tsd-signature tsd-kind-icon">face<wbr/>Triangulation<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L143">human.ts:143</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-class"><a name="faceTriangulation" class="tsd-anchor"></a><h3>face<wbr/>Triangulation</h3><div class="tsd-signature tsd-kind-icon">face<wbr/>Triangulation<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L144">human.ts:144</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Reference face triangualtion array of 468 points, used for triangle references between points</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="faceUVMap" class="tsd-anchor"></a><h3>faceUVMap</h3><div class="tsd-signature tsd-kind-icon">faceUVMap<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">[]</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L145">human.ts:145</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-class"><a name="faceUVMap" class="tsd-anchor"></a><h3>faceUVMap</h3><div class="tsd-signature tsd-kind-icon">faceUVMap<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">[]</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L146">human.ts:146</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Refernce UV map of 468 values, used for 3D mapping of the face mesh</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="gl" class="tsd-anchor"></a><h3>gl</h3><div class="tsd-signature tsd-kind-icon">gl<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">unknown</span><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/human.ts#L152">human.ts:152</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-class"><a name="gl" class="tsd-anchor"></a><h3>gl</h3><div class="tsd-signature tsd-kind-icon">gl<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">unknown</span><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/human.ts#L153">human.ts:153</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>WebGL debug info</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="performance" class="tsd-anchor"></a><h3>performance</h3><div class="tsd-signature tsd-kind-icon">performance<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">number</span><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/human.ts#L147">human.ts:147</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-class"><a name="performance" class="tsd-anchor"></a><h3>performance</h3><div class="tsd-signature tsd-kind-icon">performance<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">number</span><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/human.ts#L148">human.ts:148</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Performance object that contains values for all recently performed operations</p>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="process" class="tsd-anchor"></a><h3>process</h3><div class="tsd-signature tsd-kind-icon">process<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L102">human.ts:102</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-class"><a name="process" class="tsd-anchor"></a><h3>process</h3><div class="tsd-signature tsd-kind-icon">process<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L103">human.ts:103</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>currenty processed image tensor and canvas</p>
</div></div><div class="tsd-type-declaration"><h4>Type declaration</h4><ul class="tsd-parameters"><li class="tsd-parameter"><h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span></h5></li><li class="tsd-parameter"><h5>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="result" class="tsd-anchor"></a><h3>result</h3><div class="tsd-signature tsd-kind-icon">result<span class="tsd-signature-symbol">:</span> <a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L93">human.ts:93</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div><div class="tsd-type-declaration"><h4>Type declaration</h4><ul class="tsd-parameters"><li class="tsd-parameter"><h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span></h5></li><li class="tsd-parameter"><h5>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="result" class="tsd-anchor"></a><h3>result</h3><div class="tsd-signature tsd-kind-icon">result<span class="tsd-signature-symbol">:</span> <a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L94">human.ts:94</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Last known result of detect run</p>
<ul>
<li>Can be accessed anytime after initial detection</li>
<li>Definition: <a href="../interfaces/Result.html">Result</a></li>
</ul>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="state" class="tsd-anchor"></a><h3>state</h3><div class="tsd-signature tsd-kind-icon">state<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/human.ts#L99">human.ts:99</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-class"><a name="state" class="tsd-anchor"></a><h3>state</h3><div class="tsd-signature tsd-kind-icon">state<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/human.ts#L100">human.ts:100</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Current state of Human library</p>
<ul>
<li>Can be polled to determine operations that are currently executed</li>
<li>Progresses through: &#39;config&#39;, &#39;check&#39;, &#39;backend&#39;, &#39;load&#39;, &#39;run:<model>&#39;, &#39;idle&#39;</li>
</ul>
</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class"><a name="version" class="tsd-anchor"></a><h3>version</h3><div class="tsd-signature tsd-kind-icon">version<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/human.ts#L81">human.ts:81</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-class"><a name="version" class="tsd-anchor"></a><h3>version</h3><div class="tsd-signature tsd-kind-icon">version<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/human.ts#L82">human.ts:82</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Current version of Human library in <em>semver</em> format</p>
</div></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Methods</h2><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="detect" class="tsd-anchor"></a><h3>detect</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">detect<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a>, userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><a href="../index.html#Error" class="tsd-signature-type" data-tsd-kind="Type alias">Error</a><span class="tsd-signature-symbol"> | </span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L388">human.ts:388</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Methods</h2><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="detect" class="tsd-anchor"></a><h3>detect</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">detect<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a>, userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><a href="../index.html#Error" class="tsd-signature-type" data-tsd-kind="Type alias">Error</a><span class="tsd-signature-symbol"> | </span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L389">human.ts:389</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Main detection method</p>
<ul>
<li>Analyze configuration: <a href="../interfaces/Config.html">Config</a></li>
@ -73,12 +73,12 @@
<li>Process and return result: <a href="../interfaces/Result.html">Result</a></li>
</ul>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li><li><h5><span class="tsd-flag ts-flagOptional">Optional</span> userConfig: <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><a href="../index.html#Error" class="tsd-signature-type" data-tsd-kind="Type alias">Error</a><span class="tsd-signature-symbol"> | </span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol">&gt;</span></h4><div><p>result: <a href="../interfaces/Result.html">Result</a></p>
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="enhance" class="tsd-anchor"></a><h3>enhance</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">enhance<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L288">human.ts:288</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="enhance" class="tsd-anchor"></a><h3>enhance</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">enhance<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L289">human.ts:289</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Enhance method performs additional enhacements to face image previously detected for futher processing</p>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h4><div><p>Tensor</p>
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="image" class="tsd-anchor"></a><h3>image</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">image<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L248">human.ts:248</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="image" class="tsd-anchor"></a><h3>image</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">image<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L249">human.ts:249</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Process input as return canvas and tensor</p>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></h4><div></div><ul class="tsd-parameters"><li class="tsd-parameter"><h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span></h5></li><li class="tsd-parameter"><h5>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="init" class="tsd-anchor"></a><h3>init</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">init<span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L311">human.ts:311</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></h4><div></div><ul class="tsd-parameters"><li class="tsd-parameter"><h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span></h5></li><li class="tsd-parameter"><h5>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="init" class="tsd-anchor"></a><h3>init</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">init<span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L312">human.ts:312</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Explicit backend initialization</p>
<ul>
<li>Normally done implicitly during initial load phase</li>
@ -86,22 +86,22 @@
<li>Use when changing backend during runtime</li>
</ul>
</div></div><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></h4><div><p>Promise<void></p>
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="load" class="tsd-anchor"></a><h3>load</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">load<span class="tsd-signature-symbol">(</span>userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L323">human.ts:323</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="load" class="tsd-anchor"></a><h3>load</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">load<span class="tsd-signature-symbol">(</span>userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L324">human.ts:324</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Load method preloads all configured models on-demand</p>
<ul>
<li>Not explicitly required as any required model is load implicitly on it&#39;s first run</li>
</ul>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5><span class="tsd-flag ts-flagOptional">Optional</span> userConfig: <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></h4><div><p>Promise<void></p>
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="match" class="tsd-anchor"></a><h3>match</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">match<span class="tsd-signature-symbol">(</span>faceEmbedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span>, db<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>name<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>source<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span>, threshold<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>name<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>similarity<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>source<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L300">human.ts:300</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="match" class="tsd-anchor"></a><h3>match</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">match<span class="tsd-signature-symbol">(</span>faceEmbedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span>, db<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>name<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>source<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span>, threshold<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>name<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>similarity<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>source<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L301">human.ts:301</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Math method find best match between provided face descriptor and predefined database of known descriptors</p>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>faceEmbedding: <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span></h5></li><li><h5>db: <span class="tsd-signature-symbol">{ </span>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>name<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>source<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></h5></li><li><h5>threshold: <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 0</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-symbol">{ </span>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>name<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>similarity<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>source<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span></h4><div><p>best match</p>
</div><ul class="tsd-parameters"><li class="tsd-parameter"><h5>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span></h5></li><li class="tsd-parameter"><h5>name<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span></h5></li><li class="tsd-parameter"><h5>similarity<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span></h5></li><li class="tsd-parameter"><h5>source<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span></h5></li></ul></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="next" class="tsd-anchor"></a><h3>next</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">next<span class="tsd-signature-symbol">(</span>result<span class="tsd-signature-symbol">?: </span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L364">human.ts:364</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div><ul class="tsd-parameters"><li class="tsd-parameter"><h5>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span></h5></li><li class="tsd-parameter"><h5>name<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span></h5></li><li class="tsd-parameter"><h5>similarity<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span></h5></li><li class="tsd-parameter"><h5>source<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span></h5></li></ul></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="next" class="tsd-anchor"></a><h3>next</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">next<span class="tsd-signature-symbol">(</span>result<span class="tsd-signature-symbol">?: </span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L365">human.ts:365</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Runs interpolation using last known result and returns smoothened result
Interpolation is based on time since last known result so can be called independently</p>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>result: <a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol"> = ...</span></h5></li></ul><h4 class="tsd-returns-title">Returns <a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a></h4><div><p>result: <a href="../interfaces/Result.html">Result</a></p>
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="reset" class="tsd-anchor"></a><h3>reset</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">reset<span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">void</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L232">human.ts:232</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="reset" class="tsd-anchor"></a><h3>reset</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">reset<span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">void</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L233">human.ts:233</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Reset configuration to default values</p>
</div></div><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="segmentation" class="tsd-anchor"></a><h3>segmentation</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">segmentation<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a>, background<span class="tsd-signature-symbol">?: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-symbol">{ </span>alpha<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>data<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L278">human.ts:278</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="segmentation" class="tsd-anchor"></a><h3>segmentation</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">segmentation<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a>, background<span class="tsd-signature-symbol">?: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-symbol">{ </span>alpha<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>data<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L279">human.ts:279</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Segmentation method takes any input and returns processed canvas with body segmentation</p>
<ul>
<li>Optional parameter background is used to fill the background with specific input</li>
@ -113,16 +113,16 @@ Interpolation is based on time since last known result so can be called independ
<li><code>canvas</code> as canvas which is input image filtered with segementation data and optionally merged with background image. canvas alpha values are set to segmentation values for easy merging</li>
<li><code>alpha</code> as grayscale canvas that represents segmentation alpha values</li>
</ul>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li><li><h5><span class="tsd-flag ts-flagOptional">Optional</span> background: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-symbol">{ </span>alpha<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>data<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">&gt;</span></h4><div></div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="similarity" class="tsd-anchor"></a><h3>similarity</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">similarity<span class="tsd-signature-symbol">(</span>embedding1<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span>, embedding2<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L261">human.ts:261</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li><li><h5><span class="tsd-flag ts-flagOptional">Optional</span> background: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-symbol">{ </span>alpha<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>data<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">&gt;</span></h4><div></div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="similarity" class="tsd-anchor"></a><h3>similarity</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">similarity<span class="tsd-signature-symbol">(</span>embedding1<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span>, embedding2<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L262">human.ts:262</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Simmilarity method calculates simmilarity between two provided face descriptors (face embeddings)</p>
<ul>
<li>Calculation is based on normalized Minkowski distance between two descriptors</li>
<li>Default is Euclidean distance which is Minkowski distance of 2nd order</li>
</ul>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>embedding1: <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span></h5></li><li><h5>embedding2: <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><div><p>similarity: number</p>
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="validate" class="tsd-anchor"></a><h3>validate</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">validate<span class="tsd-signature-symbol">(</span>userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>expected<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>reason<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>where<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L239">human.ts:239</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="validate" class="tsd-anchor"></a><h3>validate</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">validate<span class="tsd-signature-symbol">(</span>userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>expected<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>reason<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>where<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L240">human.ts:240</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Validate current configuration schema</p>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5><span class="tsd-flag ts-flagOptional">Optional</span> userConfig: <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-symbol">{ </span>expected<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>reason<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>where<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></h4></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="warmup" class="tsd-anchor"></a><h3>warmup</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">warmup<span class="tsd-signature-symbol">(</span>userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-symbol">{ </span>error<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L374">human.ts:374</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5><span class="tsd-flag ts-flagOptional">Optional</span> userConfig: <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-symbol">{ </span>expected<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>reason<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>where<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></h4></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="warmup" class="tsd-anchor"></a><h3>warmup</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">warmup<span class="tsd-signature-symbol">(</span>userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-symbol">{ </span>error<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L375">human.ts:375</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Warmup method pre-initializes all configured models for faster inference</p>
<ul>
<li>can take significant time on startup</li>

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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 - v2.2.3</title><meta name="description" content="Documentation for @vladmandic/human - v2.2.3"/><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><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 - v2.2.3</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 - v2.2.3</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 name="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#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-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 name="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#L249">config.ts:249</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 name="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#L233">config.ts:233</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 name="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#L237">config.ts:237</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 name="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#L281">config.ts:281</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 name="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#L285">config.ts:285</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 name="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#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 name="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#L266">config.ts:266</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 name="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#L242">config.ts:242</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 name="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#L246">config.ts:246</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 name="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#L278">config.ts:278</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 name="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#L282">config.ts:282</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 name="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#L272">config.ts:272</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 name="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#L276">config.ts:276</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 name="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#L275">config.ts:275</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 name="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#L279">config.ts:279</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 name="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#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 name="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#L288">config.ts:288</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 name="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#L256">config.ts:256</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 name="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#L260">config.ts:260</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 name="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#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 name="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#L291">config.ts:291</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 name="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#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 name="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#L294">config.ts:294</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 name="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#L265">config.ts:265</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 name="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#L269">config.ts:269</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 name="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#L250">config.ts:250</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 name="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#L254">config.ts:254</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 name="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#L239">config.ts:239</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 name="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#L243">config.ts:243</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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<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 name="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#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-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 name="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#L192">config.ts:192</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 name="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#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 name="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#L186">config.ts:186</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 name="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#L184">config.ts:184</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 name="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#L188">config.ts:188</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 name="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#L164">config.ts:164</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a name="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#L180">config.ts:180</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 name="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#L168">config.ts:168</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a name="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#L184">config.ts:184</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 name="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#L176">config.ts:176</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 name="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#L180">config.ts:180</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 name="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#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 name="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#L196">config.ts:196</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 name="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#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-member tsd-kind-property tsd-parent-kind-interface"><a name="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#L204">config.ts:204</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 name="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#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 name="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#L198">config.ts:198</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 name="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#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 name="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#L210">config.ts:210</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 name="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#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 name="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#L208">config.ts:208</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 name="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#L178">config.ts:178</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 name="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#L182">config.ts:182</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 name="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#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 name="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#L194">config.ts:194</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 name="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#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 name="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#L200">config.ts:200</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 name="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#L186">config.ts:186</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 name="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#L190">config.ts:190</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 name="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#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 name="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#L206">config.ts:206</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 name="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#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 name="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#L202">config.ts:202</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 name="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#L170">config.ts:170</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 name="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#L174">config.ts:174</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>

2
typedoc/interfaces/GestureConfig.html
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@ -1,3 +1,3 @@
<!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 - v2.2.3</title><meta name="description" content="Documentation for @vladmandic/human - v2.2.3"/><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><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 - v2.2.3</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 - v2.2.3</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 name="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#L211">config.ts:211</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 name="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#L215">config.ts:215</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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typedoc/interfaces/SegmentationConfig.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 name="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#L156">config.ts:156</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a name="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#L154">config.ts:154</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a name="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#L155">config.ts:155</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 name="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#L160">config.ts:160</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a name="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#L158">config.ts:158</a></li></ul></aside></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a name="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#L159">config.ts:159</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 +0,0 @@
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@ -1,11 +0,0 @@
/**
* BlazePose model implementation
*
* Based on : [**BlazePose**](https://drive.google.com/file/d/10IU-DRP2ioSNjKFdiGbmmQX81xAYj88s/view)
*/
import type { Tensor, GraphModel } from '../tfjs/types';
import type { BodyResult } from '../result';
import type { Config } from '../config';
export declare function load(config: Config): Promise<GraphModel>;
export declare function predict(image: Tensor, config: Config): Promise<BodyResult[]>;
//# sourceMappingURL=blazepose.d.ts.map

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@ -1 +0,0 @@
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types/src/blazepose/annotations.d.ts → types/src/body/annotations.d.ts vendored
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@ -0,0 +1 @@
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@ -0,0 +1,13 @@
/**
* BlazePose model implementation
*
* Based on : [**BlazePose**](https://github.com/google/mediapipe/blob/master/mediapipe/modules/pose_detection)
*/
import type { BodyResult } from '../result';
import type { GraphModel, Tensor } from '../tfjs/types';
import type { Config } from '../config';
export declare function loadDetect(config: Config): Promise<GraphModel>;
export declare function loadPose(config: Config): Promise<GraphModel>;
export declare function load(config: Config): Promise<[GraphModel | null, GraphModel | null]>;
export declare function predict(input: Tensor, config: Config): Promise<BodyResult[]>;
//# sourceMappingURL=blazepose.d.ts.map

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{"version":3,"file":"efficientpose.d.ts","sourceRoot":"","sources":["../../../src/body/efficientpose.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAIH,OAAO,KAAK,EAAE,UAAU,EAAO,MAAM,WAAW,CAAC;AACjD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAexC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAQ9D;AAmBD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CAkElF"}

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@ -0,0 +1 @@
{"version":3,"file":"movenet.d.ts","sourceRoot":"","sources":["../../../src/body/movenet.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAKH,OAAO,KAAK,EAAE,UAAU,EAAc,MAAM,WAAW,CAAC;AACxD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAgBxC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAW9D;AAsFD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CA2ClF"}

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types/src/config.d.ts vendored
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@ -61,6 +61,7 @@ export interface FaceConfig {
* - modelPath: body pose model, can be absolute path or relative to modelBasePath
* - minConfidence: threshold for discarding a prediction
* - maxDetected: maximum number of people detected in the input, should be set to the minimum number for performance
* - detector: optional body detector
*
* `maxDetected` is valid for `posenet` and `movenet-multipose` as other models are single-pose only
* `maxDetected` can be set to -1 to auto-detect based on number of detected faces
@ -74,6 +75,9 @@ export interface BodyConfig {
maxDetected: number;
minConfidence: number;
skipFrames: number;
detector?: {
modelPath: string;
};
}
/** Controlls and configures all hand detection specific options
*

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@ -1 +1 @@
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1
types/src/draw.d.ts.map
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@ -1 +0,0 @@
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1
types/src/efficientpose/efficientpose.d.ts.map
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@ -1 +0,0 @@
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1
types/src/emotion/emotion.d.ts.map
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@ -1 +0,0 @@
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1
types/src/env.d.ts.map
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@ -1 +0,0 @@
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1
types/src/face.d.ts.map
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@ -1 +0,0 @@
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4
types/src/face.d.ts → types/src/face/face.d.ts vendored
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@ -2,7 +2,7 @@
* Face algorithm implementation
* Uses FaceMesh, Emotion and FaceRes models to create a unified pipeline
*/
import type { FaceResult } from './result';
import type { Tensor } from './tfjs/types';
import type { FaceResult } from '../result';
import type { Tensor } from '../tfjs/types';
export declare const detectFace: (parent: any, input: Tensor) => Promise<FaceResult[]>;
//# sourceMappingURL=face.d.ts.map

1
types/src/face/face.d.ts.map Normal file
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@ -0,0 +1 @@
{"version":3,"file":"face.d.ts","sourceRoot":"","sources":["../../../src/face/face.ts"],"names":[],"mappings":"AAAA;;;GAGG;AAOH,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,WAAW,CAAC;AAC5C,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AAwI5C,eAAO,MAAM,UAAU,uBAAiD,MAAM,KAAG,QAAQ,UAAU,EAAE,CAoHpG,CAAC"}

0
types/src/faceres/faceres.d.ts → types/src/face/faceres.d.ts vendored
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1
types/src/face/faceres.d.ts.map Normal file
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@ -0,0 +1 @@
{"version":3,"file":"faceres.d.ts","sourceRoot":"","sources":["../../../src/face/faceres.ts"],"names":[],"mappings":"AAAA;;;;;;;GAOG;AAIH,OAAO,KAAK,EAAE,MAAM,EAAE,UAAU,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAcxC,aAAK,EAAE,GAAG,KAAK,CAAC;IAAE,IAAI,EAAE,MAAM,CAAC;IAAC,MAAM,EAAE,MAAM,CAAC;IAAC,SAAS,EAAE,MAAM,EAAE,CAAA;CAAE,CAAC,CAAC;AAEvE,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAS9D;AAED,wBAAgB,UAAU,CAAC,UAAU,EAAE,KAAK,CAAC,MAAM,CAAC,EAAE,UAAU,EAAE,KAAK,CAAC,MAAM,CAAC,EAAE,KAAK,SAAI,GAAG,MAAM,CAWlG;AAED,wBAAgB,KAAK,CAAC,SAAS,EAAE,KAAK,CAAC,MAAM,CAAC,EAAE,EAAE,EAAE,EAAE,EAAE,SAAS,SAAI;;;;;EAUpE;AAED,wBAAgB,OAAO,CAAC,KAAK,KAAA,GAAG,MAAM,CAmDrC;AAED,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,EAAE,GAAG,KAAA,EAAE,KAAK,KAAA,oBA8CtE"}

1
types/src/faceres/faceres.d.ts.map
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@ -1 +0,0 @@
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1
types/src/gear/agegenderrace.d.ts.map
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@ -1 +0,0 @@
{"version":3,"file":"agegenderrace.d.ts","sourceRoot":"","sources":["../../../src/gear/agegenderrace.ts"],"names":[],"mappings":"AAAA;;;;;;;GAOG;AAIH,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AACxC,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AASxD,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,GAAG,uBAQ9C;AAGD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,oBA0C1D"}

0
types/src/emotion/emotion.d.ts → types/src/gear/emotion.d.ts vendored
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1
types/src/gear/emotion.d.ts.map Normal file
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@ -0,0 +1 @@
{"version":3,"file":"emotion.d.ts","sourceRoot":"","sources":["../../../src/gear/emotion.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAGH,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AACxC,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AAcxD,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAQ9D;AAED,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,EAAE,GAAG,KAAA,EAAE,KAAK,KAAA,oBAuCtE"}

2
types/src/gear/agegenderrace.d.ts → types/src/gear/gear-agegenderrace.d.ts vendored
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@ -10,4 +10,4 @@ import type { Config } from '../config';
import type { GraphModel, Tensor } from '../tfjs/types';
export declare function load(config: Config | any): Promise<GraphModel>;
export declare function predict(image: Tensor, config: Config): Promise<unknown>;
//# sourceMappingURL=agegenderrace.d.ts.map
//# sourceMappingURL=gear-agegenderrace.d.ts.map

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@ -0,0 +1 @@
{"version":3,"file":"gear-agegenderrace.d.ts","sourceRoot":"","sources":["../../../src/gear/gear-agegenderrace.ts"],"names":[],"mappings":"AAAA;;;;;;;GAOG;AAIH,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AACxC,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AASxD,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,GAAG,uBAQ9C;AAGD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,oBA0C1D"}

0
types/src/handtrack/handtrack.d.ts → types/src/hand/handtrack.d.ts vendored
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types/src/hand/handtrack.d.ts.map Normal file
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@ -0,0 +1 @@
{"version":3,"file":"handtrack.d.ts","sourceRoot":"","sources":["../../../src/hand/handtrack.ts"],"names":[],"mappings":"AAAA;;;;;;GAMG;AAKH,OAAO,KAAK,EAAE,UAAU,EAAO,MAAM,WAAW,CAAC;AACjD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AA4CxC,wBAAsB,UAAU,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAepE;AAED,wBAAsB,YAAY,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAWtE;AAED,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,CAAC,UAAU,GAAG,IAAI,EAAE,UAAU,GAAG,IAAI,CAAC,CAAC,CAI1F;AAgGD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CAmBlF"}

1
types/src/handtrack/handtrack.d.ts.map
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@ -1 +0,0 @@
{"version":3,"file":"handtrack.d.ts","sourceRoot":"","sources":["../../../src/handtrack/handtrack.ts"],"names":[],"mappings":"AAAA;;;;;;GAMG;AAIH,OAAO,KAAK,EAAE,UAAU,EAAO,MAAM,WAAW,CAAC;AACjD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AA4CxC,wBAAsB,UAAU,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAepE;AAED,wBAAsB,YAAY,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAWtE;AAED,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,CAAC,UAAU,GAAG,IAAI,EAAE,UAAU,GAAG,IAAI,CAAC,CAAC,CAI1F;AAgGD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CAmBlF"}

8
types/src/human.d.ts vendored
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@ -6,13 +6,13 @@ import type { Result } from './result';
import * as tf from '../dist/tfjs.esm.js';
import * as models from './models';
import * as facemesh from './blazeface/facemesh';
import * as env from './env';
import * as env from './util/env';
import type { Tensor } from './tfjs/types';
import type { DrawOptions } from './draw';
import type { DrawOptions } from './util/draw';
export * from './config';
export * from './result';
export type { DrawOptions } from './draw';
export { env, Env } from './env';
export type { DrawOptions } from './util/draw';
export { env, Env } from './util/env';
export { Box, Point } from './result';
export { Models } from './models';
/** Defines all possible input types for **Human** detection

2
types/src/human.d.ts.map
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@ -1 +1 @@
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2
types/src/image/image.d.ts vendored
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@ -3,7 +3,7 @@
*/
import type { Tensor } from '../tfjs/types';
import type { Config } from '../config';
import { env } from '../env';
import { env } from '../util/env';
declare type Input = Tensor | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas | typeof Image | typeof env.Canvas;
export declare function canvas(width: any, height: any): HTMLCanvasElement | OffscreenCanvas;
export declare function process(input: Input, config: Config): {

2
types/src/image/image.d.ts.map
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1
types/src/interpolate.d.ts.map
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@ -1 +0,0 @@
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1
types/src/models.d.ts vendored
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@ -12,6 +12,7 @@ import type { Human } from './human';
export declare class Models {
age: null | GraphModel | Promise<GraphModel>;
agegenderrace: null | GraphModel | Promise<GraphModel>;
blazeposedetect: null | GraphModel | Promise<GraphModel>;
blazepose: null | GraphModel | Promise<GraphModel>;
centernet: null | GraphModel | Promise<GraphModel>;
efficientpose: null | GraphModel | Promise<GraphModel>;

2
types/src/models.d.ts.map
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@ -1 +1 @@
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1
types/src/movenet/movenet.d.ts.map
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@ -1 +0,0 @@
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1
types/src/util.d.ts.map
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7
types/src/util/box.d.ts vendored Normal file
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@ -0,0 +1,7 @@
import type { Box } from '../result';
export declare function scale(keypoints: any, boxScaleFact: any, outputSize: any): {
box: Box;
boxRaw: Box;
yxBox: Box;
};
//# sourceMappingURL=box.d.ts.map

1
types/src/util/box.d.ts.map Normal file
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@ -0,0 +1 @@
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2
types/src/draw.d.ts → types/src/util/draw.d.ts vendored
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@ -1,7 +1,7 @@
/**
* Module that implements helper draw functions, exposed as human.draw
*/
import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult } from './result';
import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult } from '../result';
/**
* Draw Options
* Accessed via `human.draw.options` or provided per each draw method as the drawOptions optional parameter

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