human/src/index.js

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const tf = require('@tensorflow/tfjs');
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const facemesh = require('./facemesh/index.js');
const ssrnet = require('./ssrnet/index.js');
const posenet = require('./posenet/index.js');
const handpose = require('./handpose/index.js');
const defaults = require('./config.js').default;
const models = {
facemesh: null,
blazeface: null,
ssrnet: null,
iris: null,
};
function mergeDeep(...objects) {
const isObject = (obj) => obj && typeof obj === 'object';
return objects.reduce((prev, obj) => {
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Object.keys(obj || {}).forEach((key) => {
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const pVal = prev[key];
const oVal = obj[key];
if (Array.isArray(pVal) && Array.isArray(oVal)) {
prev[key] = pVal.concat(...oVal);
} else if (isObject(pVal) && isObject(oVal)) {
prev[key] = mergeDeep(pVal, oVal);
} else {
prev[key] = oVal;
}
});
return prev;
}, {});
}
async function detect(input, userConfig) {
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// eslint-disable-next-line no-async-promise-executor
return new Promise(async (resolve) => {
const config = mergeDeep(defaults, userConfig);
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// load models if enabled
if (config.face.age.enabled) await ssrnet.loadAge(config);
if (config.face.gender.enabled) await ssrnet.loadGender(config);
if (config.body.enabled && !models.posenet) models.posenet = await posenet.load(config.body);
if (config.hand.enabled && !models.handpose) models.handpose = await handpose.load(config.hand);
if (config.face.enabled && !models.facemesh) models.facemesh = await facemesh.load(config.face);
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tf.engine().startScope();
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// run posenet
let poseRes = [];
if (config.body.enabled) poseRes = await models.posenet.estimateMultiplePoses(input, config.body);
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// run handpose
let handRes = [];
if (config.hand.enabled) handRes = await models.handpose.estimateHands(input, config.hand);
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// run facemesh, includes blazeface and iris
const faceRes = [];
if (config.face.enabled) {
const faces = await models.facemesh.estimateFaces(input, config.face);
for (const face of faces) {
// run ssr-net age & gender, inherits face from blazeface
const ssrdata = (config.face.age.enabled || config.face.gender.enabled) ? await ssrnet.predict(face.image, config) : {};
face.image.dispose();
// iris: array[ bottom, left, top, right, center ]
const iris = (face.annotations.leftEyeIris && face.annotations.rightEyeIris)
? Math.max(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0], face.annotations.rightEyeIris[3][0] - face.annotations.rightEyeIris[1][0])
: 0;
faceRes.push({
confidence: face.confidence,
box: face.box,
mesh: face.mesh,
annotations: face.annotations,
age: ssrdata.age,
gender: ssrdata.gender,
iris: (iris !== 0) ? Math.trunc(100 * 11.7 / iris) / 100 : 0,
});
}
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}
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tf.engine().endScope();
// combine results
resolve({ face: faceRes, body: poseRes, hand: handRes });
});
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}
exports.detect = detect;
exports.defaults = defaults;
exports.models = models;
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exports.facemesh = facemesh;
exports.ssrnet = ssrnet;
exports.posenet = posenet;
exports.handpose = handpose;
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exports.tf = tf;