mirror of https://github.com/vladmandic/human
60 lines
1.7 KiB
JavaScript
60 lines
1.7 KiB
JavaScript
const tf = require('@tensorflow/tfjs');
|
|
const profile = require('../profile.js');
|
|
|
|
const models = {};
|
|
let last = { age: 0 };
|
|
let frame = Number.MAX_SAFE_INTEGER;
|
|
|
|
// tuning values
|
|
const zoom = [0, 0]; // 0..1 meaning 0%..100%
|
|
|
|
async function load(config) {
|
|
if (!models.age) models.age = await tf.loadGraphModel(config.face.age.modelPath);
|
|
return models.age;
|
|
}
|
|
|
|
async function predict(image, config) {
|
|
return new Promise(async (resolve) => {
|
|
if (frame < config.face.age.skipFrames) {
|
|
frame += 1;
|
|
resolve(last);
|
|
}
|
|
frame = 0;
|
|
const box = [[
|
|
(image.shape[1] * zoom[0]) / image.shape[1],
|
|
(image.shape[2] * zoom[1]) / image.shape[2],
|
|
(image.shape[1] - (image.shape[1] * zoom[0])) / image.shape[1],
|
|
(image.shape[2] - (image.shape[2] * zoom[1])) / image.shape[2],
|
|
]];
|
|
const resize = tf.image.cropAndResize(image, box, [0], [config.face.age.inputSize, config.face.age.inputSize]);
|
|
// const resize = tf.image.resizeBilinear(image, [config.face.age.inputSize, config.face.age.inputSize], false);
|
|
const enhance = tf.mul(resize, [255.0]);
|
|
tf.dispose(resize);
|
|
|
|
let ageT;
|
|
const obj = {};
|
|
|
|
if (!config.profile) {
|
|
if (config.face.age.enabled) ageT = await models.age.predict(enhance);
|
|
} else {
|
|
const profileAge = config.face.age.enabled ? await tf.profile(() => models.age.predict(enhance)) : {};
|
|
ageT = profileAge.result.clone();
|
|
profileAge.result.dispose();
|
|
profile.run('age', profileAge);
|
|
}
|
|
enhance.dispose();
|
|
|
|
if (ageT) {
|
|
const data = ageT.dataSync();
|
|
obj.age = Math.trunc(10 * data[0]) / 10;
|
|
}
|
|
ageT.dispose();
|
|
|
|
last = obj;
|
|
resolve(obj);
|
|
});
|
|
}
|
|
|
|
exports.predict = predict;
|
|
exports.load = load;
|