ambiser
/
face-api
mirror of https://github.com/vladmandic/face-api.git
9
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

remove old demo

pull/34/head
Vladimir Mandic 2020-12-08 08:36:54 -05:00
parent 2f9ee919fd
commit cab92932ef
1 changed files with 0 additions and 84 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

84
example/node.js
View File

@ -1,84 +0,0 @@
process.stderr.write = null; // silly hack to stock tfjs logging too much to stderr
const fs = require('fs');
const path = require('path');
const tf = require('@tensorflow/tfjs-node');
const faceapi = require('../dist/face-api.node.js');
// if you have module installed, this would be
// const faceapi = require('@vladmandic/face-api');
// configuration options
const modelPathRoot = '../model/'; // path to model folder that will be loaded
const imgSize = 512; // maximum image size in pixels
const minScore = 0.1; // minimum score
const maxResults = 5; // maximum number of results to return
const samples = ['sample (1).jpg', 'sample (2).jpg', 'sample (3).jpg', 'sample (4).jpg', 'sample (5).jpg', 'sample (6).jpg']; // sample images to be loaded
// helper function to pretty-print json object to string
function str(json) {
const text = json ? JSON.stringify(json).replace(/{|}|"|\[|\]/g, '').replace(/,/g, ', ') : '';
return text;
}
// helper function to print strings to html document as a log
function log(...txt) {
// eslint-disable-next-line no-console
console.log(...txt);
}
async function image(img) {
const buffer = fs.readFileSync(img);
const decoded = tf.node.decodeImage(buffer);
const casted = decoded.toFloat();
const result = casted.expandDims(0);
decoded.dispose();
casted.dispose();
return result;
}
async function main() {
// initialize tfjs
log('FaceAPI Test');
await faceapi.tf.setBackend('tensorflow'); //Sets the backend (cpu, webgl, wasm, tensorflow, etc) responsible for creating tensors and executing operations on those tensors.
await faceapi.tf.enableProdMode();
await faceapi.tf.ENV.set('DEBUG', false);
await faceapi.tf.ready(); //Returns a promise that resolves when the currently selected backend (or the highest priority one) has initialized.
// check version
log(`Version: TensorFlow/JS ${str(faceapi.tf?.version_core || '(not loaded)')} FaceAPI ${str(faceapi?.version || '(not loaded)')} Backend: ${str(faceapi.tf?.getBackend() || '(not loaded)')}`);
log(`Flags: ${JSON.stringify(faceapi.tf.ENV.flags)}`);
// load face-api models
log('Loading FaceAPI models');
const modelPath = path.join(__dirname, modelPathRoot);
await faceapi.nets.ssdMobilenetv1.loadFromDisk(modelPath);
await faceapi.nets.ageGenderNet.loadFromDisk(modelPath);
await faceapi.nets.faceLandmark68Net.loadFromDisk(modelPath);
await faceapi.nets.faceRecognitionNet.loadFromDisk(modelPath);
await faceapi.nets.faceExpressionNet.loadFromDisk(modelPath);
const optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence: minScore, maxResults });
// check tf engine state
const engine = await faceapi.tf.engine();
log(`TF Engine State: ${str(engine.state)}`);
const dir = fs.readdirSync(__dirname);
for (const img of dir) {
if (!img.toLocaleLowerCase().endsWith('.jpg')) continue;
// load image
const tensor = await image(path.join(__dirname, img));
// actual model execution
const result = await faceapi
.detectAllFaces(tensor, optionsSSDMobileNet)
.withFaceLandmarks()
.withFaceExpressions()
.withFaceDescriptors()
.withAgeAndGender();
log('Image:', img, 'Detected faces:', result.length);
// you can access entire result object
// console.log(result);
tensor.dispose();
}
}
main();