human/src/age/age.ts

57 lines
1.7 KiB
TypeScript

/**
* Module that analyzes person age
* Obsolete
*/
import { log, join } from '../helpers';
import * as tf from '../../dist/tfjs.esm.js';
import { Config } from '../config';
import { GraphModel, Tensor } from '../tfjs/types';
let model: GraphModel;
let last = { age: 0 };
let skipped = Number.MAX_SAFE_INTEGER;
// eslint-disable-next-line @typescript-eslint/no-explicit-any
export async function load(config: Config | any) {
if (!model) {
// @ts-ignore type mismatch on GraphModel
model = await tf.loadGraphModel(join(config.modelBasePath, config.face.age.modelPath));
if (!model || !model['modelUrl']) log('load model failed:', config.face.age.modelPath);
else if (config.debug) log('load model:', model['modelUrl']);
} else if (config.debug) log('cached model:', model['modelUrl']);
return model;
}
// eslint-disable-next-line @typescript-eslint/no-explicit-any
export async function predict(image: Tensor, config: Config | any) {
if (!model) return null;
if ((skipped < config.face.age.skipFrames) && config.skipFrame && last.age && (last.age > 0)) {
skipped++;
return last;
}
skipped = 0;
return new Promise(async (resolve) => {
if (!model.inputs[0].shape) return;
const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);
const enhance = tf.mul(resize, [255.0]);
tf.dispose(resize);
let ageT;
const obj = { age: 0 };
if (config.face.age.enabled) ageT = await model.predict(enhance);
enhance.dispose();
if (ageT) {
const data = ageT.dataSync();
obj.age = Math.trunc(10 * data[0]) / 10;
}
ageT.dispose();
last = obj;
resolve(obj);
});
}