Updated
| Date | Update |
|---|---|
| 2019-09-07 | New: A Face detecting and recognition with "face-api.js". |
Introduction of WeChat MiniProgram AR with TFJS
TensorFlow.js is a library for machine learning in JavaScript. There is a WeChat Mini-program plugin for TensorFlow.js.
We can create AR effects with TensorFlow.js. A "face-api.js" library is base on TensorFlow.js.
The "face-api.js" brings face detection and face recognition in the browser environment.
Why choose "face-api.js"?
Because I do not find a tiny model of TensorFlow.js for face detectiong until I found the "face-api.js".
This demo demonstrates a face detecting and recognition using "face-api.js" library.
Index Page
Face Detecting
Use the demo to scan people's face.
Expect the effect below.
Use "Take a Photo" mode.
Use "Access a Camera" mode.
Face Recognition
Two persons recognited are below.
Use the demo to scan people's face.
Expect the effect below.
Use "Take a Photo" mode.
Use "Access a Camera" mode.
How to build
The WeChat Mini-program plugin depends on "abab" and "fetch-wechat" npm packages.
step 1: npm install
step 2: run "微信开发者工具--工具--构建npm", a folder "miniprogram_npm" will be updated.
The project has included a folder "miniprogram_npm" precompiled.
File: /package.json
"dependencies": {
"abab": "^2.0.0",
"fetch-wechat": "0.0.3"
}What changes to face-api.js
You can search a keyword "2019.8.22 modified" in face-api.js. The search result is a code modified.
For example, added a export of function "setEnv". Use the function "setEnv" to set a environment of Tensorflow.js on Wechat.
File: /utils/face-api.js
// 2019.8.22 modified
exports.setEnv = setEnv;Set your website url of models
The project includes 3 models that are depolyed on a website. The default value of parameter "modelUrl" is a website url that may be very slow in your network. You can replace the default url with a web site url.
Download models: https://github.com/sanyuered/sanyuered.github.io/tree/master/models
// your website url
const modelUrl = 'https://sanyuered.github.io/models/';
// const modelUrl = 'http://127.0.0.1/models/';Known Issues
When using face detecting with face landmarks, a memory leak will occur on Android Wechat. The Mini-program will be slower and slower on a few minutes, but iOS Wechat has no the issue. When using "Access a Camera" mode, the default value of parameter "isWithFaceLandmarks" is "false".