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    @vladmandic/face-api
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    1.3.1 • Public • Published

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    FaceAPI

    AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS


    Live Demo: https://vladmandic.github.io/face-api/demo/webcam.html


    Additional Documentation




    Examples


    Browser

    Browser example that uses static images and showcases both models
    as well as all of the extensions is included in /demo/index.html
    Example can be accessed directly using Git pages using URL:
    https://vladmandic.github.io/face-api/demo/index.html

    Browser example that uses live webcam is included in /demo/webcam.html
    Example can be accessed directly using Git pages using URL:
    https://vladmandic.github.io/face-api/demo/webcam.html


    Demo using FaceAPI to process images
    Note: Photos shown below are taken by me

    screenshot

    Demo using FaceAPI to process live webcam

    screenshot


    NodeJS

    Three NodeJS examples are:

    • /demo/node.js:
      Regular usage of FaceAPI from NodeJS
      Using TFJS native methods to load images without external dependencies
    • /demo/node-canvas.js:
      Regular usage of FaceAPI from NodeJS
      Using external canvas module to load images
      Which also allows for image drawing and saving inside NodeJS environment
    • /demo/node-wasm.js: Same as node-canvas, but using WASM backend in NodeJS environment
      Because why not :)
    • /demo/node-multiprocess.js:
      Multiprocessing showcase that uses pool of worker processes
      (node-multiprocess-worker.js)
      Main starts fixed pool of worker processes with each worker having
      it's instance of FaceAPI
      Workers communicate with main when they are ready and main dispaches
      job to each ready worker until job queue is empty
    2021-03-14 08:42:03 INFO:  @vladmandic/face-api version 1.0.2
    2021-03-14 08:42:03 INFO:  User: vlado Platform: linux Arch: x64 Node: v15.7.0
    2021-03-14 08:42:03 INFO:  FaceAPI multi-process test
    2021-03-14 08:42:03 STATE:  Main: started worker: 1888019
    2021-03-14 08:42:03 STATE:  Main: started worker: 1888025
    2021-03-14 08:42:04 STATE:  Worker: PID: 1888025 TensorFlow/JS 3.3.0 FaceAPI 1.0.2 Backend: tensorflow
    2021-03-14 08:42:04 STATE:  Worker: PID: 1888019 TensorFlow/JS 3.3.0 FaceAPI 1.0.2 Backend: tensorflow
    2021-03-14 08:42:04 STATE:  Main: dispatching to worker: 1888019
    2021-03-14 08:42:04 STATE:  Main: dispatching to worker: 1888025
    2021-03-14 08:42:04 DATA:  Worker received message: 1888019 { image: 'demo/sample1.jpg' }
    2021-03-14 08:42:04 DATA:  Worker received message: 1888025 { image: 'demo/sample2.jpg' }
    2021-03-14 08:42:06 DATA:  Main: worker finished: 1888025 detected faces: 3
    2021-03-14 08:42:06 STATE:  Main: dispatching to worker: 1888025
    2021-03-14 08:42:06 DATA:  Worker received message: 1888025 { image: 'demo/sample3.jpg' }
    2021-03-14 08:42:06 DATA:  Main: worker finished: 1888019 detected faces: 3
    2021-03-14 08:42:06 STATE:  Main: dispatching to worker: 1888019
    2021-03-14 08:42:06 DATA:  Worker received message: 1888019 { image: 'demo/sample4.jpg' }
    2021-03-14 08:42:07 DATA:  Main: worker finished: 1888025 detected faces: 3
    2021-03-14 08:42:07 STATE:  Main: dispatching to worker: 1888025
    2021-03-14 08:42:07 DATA:  Worker received message: 1888025 { image: 'demo/sample5.jpg' }
    2021-03-14 08:42:08 DATA:  Main: worker finished: 1888019 detected faces: 4
    2021-03-14 08:42:08 STATE:  Main: dispatching to worker: 1888019
    2021-03-14 08:42:08 DATA:  Worker received message: 1888019 { image: 'demo/sample6.jpg' }
    2021-03-14 08:42:09 DATA:  Main: worker finished: 1888025 detected faces: 5
    2021-03-14 08:42:09 STATE:  Main: worker exit: 1888025 0
    2021-03-14 08:42:09 DATA:  Main: worker finished: 1888019 detected faces: 4
    2021-03-14 08:42:09 INFO:  Processed 15 images in 5944 ms
    2021-03-14 08:42:09 STATE:  Main: worker exit: 1888019 0

    Note that @tensorflow/tfjs-node or @tensorflow/tfjs-node-gpu
    must be installed before using NodeJS example




    Quick Start

    Simply include latest version of FaceAPI directly from a CDN in your HTML:
    (pick one, jsdelivr or unpkg)

    <script src="https://cdn.jsdelivr.net/npm/@vladmandic/face-api/dist/face-api.js"></script>
    <script src="https://unpkg.dev/@vladmandic/face-api/dist/face-api.js"></script>

    Installation

    FaceAPI ships with several pre-build versions of the library:

    • dist/face-api.js: IIFE format for client-side Browser execution
      with TFJS pre-bundled
    • dist/face-api.esm.js: ESM format for client-side Browser execution
      with TFJS pre-bundled
    • dist/face-api.esm-nobundle.js: ESM format for client-side Browser execution
      without TFJS pre-bundled
    • dist/face-api.node.js: CommonJS format for server-side NodeJS execution
      without TFJS pre-bundled
    • dist/face-api.node-gpu.js: CommonJS format for server-side NodeJS execution
      without TFJS pre-bundled and optimized for CUDA GPU acceleration
    • dist/face-api.node-cpu.js: CommonJS format for server-side NodeJS execution
      without TFJS pre-bundled and using JS engine for platforms where tensorflow binary library version is not available

    Defaults are:

    {
      "main": "dist/face-api.node-js",
      "module": "dist/face-api.esm.js",
      "browser": "dist/face-api.esm.js",
    }

    Bundled TFJS can be used directly via export: faceapi.tf

    Reason for additional nobundle version is if you want to
    include a specific version of TFJS and not rely on pre-packaged one

    FaceAPI is compatible with TFJS 2.0+

    All versions include sourcemap




    There are several ways to use FaceAPI:

    1. IIFE script

    Recommened for quick tests and backward compatibility with older Browsers that do not support ESM such as IE

    This is simplest way for usage within Browser
    Simply download dist/face-api.js, include it in your HTML file & it's ready to use:

    <script src="dist/face-api.js"><script>

    Or skip the download and include it directly from a CDN:

    <script src="https://cdn.jsdelivr.net/npm/@vladmandic/face-api/dist/face-api.js"></script>

    IIFE script bundles TFJS and auto-registers global namespace faceapi within Window object which can be accessed directly from a <script> tag or from your JS file.


    2. ESM module

    Recommended for usage within Browser

    2.1. Direct Import

    To use ESM import directly in a Browser, you must import your script (e.g. index.js) with a type="module"

      <script src="./index.js" type="module">

    and then in your index.js

      import * as faceapi from 'dist/face-api.esm.js';

    2.2. With Bundler

    Same as above, but expectation is that you've installed @vladmandic/faceapi package:

      npm install @vladmandic/face-api 

    and that you'll package your application using a bundler such as webpack, rollup or esbuild
    in which case, you do not need to import a script as module - that depends on your bundler configuration

      import * as faceapi from '@vladmandic/face-api';

    or if your bundler doesn't recognize recommended type, force usage with:

      import * as faceapi from '@vladmandic/face-api/dist/face-api.esm.js';

    or to use non-bundled version

      import * as tf from `@tensorflow/tfjs`;
      import * as faceapi from '@vladmandic/face-api/dist/face-api.esm-nobundle.js';

    3. NPM module

    3.1. Import CommonJS

    Recommended for NodeJS projects

    Node: FaceAPI for NodeJS does not bundle TFJS due to binary dependencies that are installed during TFJS installation

    Install with:

      npm install @tensorflow/tfjs-node
      npm install @vladmandic/face-api 

    And then use with:

      const tf = require('@tensorflow/tfjs-node')
      const faceapi = require('@vladmandic/face-api');

    If you want to force CommonJS module instead of relying on recommended field:

      const faceapi = require('@vladmandic/face-api/dist/face-api.node.js');

    If you want to GPU Accelerated execution in NodeJS, you must have CUDA libraries already installed and working
    Then install appropriate version of FaceAPI:

      npm install @tensorflow/tfjs-node
      npm install @vladmandic/face-api 

    And then use with:

      const tf = require('@tensorflow/tfjs-node-gpu')
      const faceapi = require('@vladmandic/face-api/dist/face-api.node-gpu.js'); // this loads face-api version with correct bindings for tfjs-node-gpu

    If you want to use FaceAPI in a NodeJS on platforms where NodeJS binary libraries are not supported, you can use JavaScript CPU backend.

      npm install @tensorflow/tfjs
      npm install @vladmandic/face-api 

    And then use with:

      const tf = require('@tensorflow/tfjs')
      const faceapi = require('@vladmandic/face-api/dist/face-api.node-cpu.js');

    If you want to use graphical functions inside NodeJS,
    you must provide appropriate graphical library as
    NodeJS does not include implementation for DOM elements
    such as HTMLImageElement or HTMLCanvasElement:

    Install Canvas for NodeJS:

    npm install canvas

    Patch NodeJS environment to use newly installed Canvas library:

    const canvas = require('canvas');
    const faceapi = require('@vladmandic/face-api');
    
    const { Canvas, Image, ImageData } = canvas
    faceapi.env.monkeyPatch({ Canvas, Image, ImageData })




    Weights

    Pretrained models and their weights are includes in ./model.




    Test & Dev Web Server

    Built-in test&dev web server can be started using

    npm run dev

    By default it starts HTTP server on port 8000 and HTTPS server on port 8001 and can be accessed as:

    2021-06-04 09:15:08 INFO:  @vladmandic/face-api version 1.3.0
    2021-06-04 09:15:08 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.0.0
    2021-06-04 09:15:08 INFO:  Build: file startup all target: es2018
    2021-06-04 09:15:08 STATE: HTTP server listening: 8000
    2021-06-04 09:15:08 STATE: HTTP2 server listening: 8001
    2021-06-04 09:15:08 STATE: Build for: node type: tfjs: { imports: 1, importBytes: 143, outputBytes: 1327, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:15:08 STATE: Monitoring: [ 'package.json', 'demo', 'src', [length]: 3 ]
    2021-06-04 09:15:08 STATE: Build for: node type: node: { imports: 162, importBytes: 234251, outputBytes: 175089, outputFiles: 'dist/face-api.node.js' }
    2021-06-04 09:15:09 STATE: Build for: nodeGPU type: tfjs: { imports: 1, importBytes: 147, outputBytes: 1335, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:15:09 STATE: Build for: nodeGPU type: node: { imports: 162, importBytes: 234259, outputBytes: 175097, outputFiles: 'dist/face-api.node-gpu.js' }
    2021-06-04 09:15:09 STATE: Build for: nodeCPU type: tfjs: { imports: 1, importBytes: 138, outputBytes: 1326, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:15:09 STATE: Build for: nodeCPU type: node: { imports: 162, importBytes: 234250, outputBytes: 175088, outputFiles: 'dist/face-api.node-cpu.js' }
    2021-06-04 09:15:09 STATE: Build for: browserNoBundle type: tfjs: { imports: 1, importBytes: 276, outputBytes: 277, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:15:09 STATE: Build for: browserNoBundle type: esm: { imports: 162, importBytes: 233201, outputBytes: 168707, outputFiles: 'dist/face-api.esm-nobundle.js' }
    2021-06-04 09:15:09 STATE: Build for: browserBundle type: tfjs: { modules: 1348, moduleBytes: 4323957, imports: 7, importBytes: 276, outputBytes: 2328203, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:15:10 STATE: Build for: browserBundle type: iife: { imports: 162, importBytes: 2561127, outputBytes: 2448241, outputFiles: 'dist/face-api.js' }
    2021-06-04 09:15:11 STATE: Build for: browserBundle type: esm: { imports: 162, importBytes: 2561127, outputBytes: 2327046, outputFiles: 'dist/face-api.esm.js' }




    Build

    If you want to do a full rebuild, either download npm module

    npm install @vladmandic/face-api
    cd node_modules/@vladmandic/face-api

    or clone a git project

    git clone https://github.com/vladmandic/face-api
    cd face-api

    Then install all dependencies and run rebuild:

    npm install
    npm run build

    Build process uses script build.js that creates optimized build for each target:

    > @vladmandic/face-api@1.0.2 build
    > rimraf dist/* types/* typedoc/* && node server/build.js
    
    2021-06-04 09:13:42 INFO:  @vladmandic/face-api version 1.3.0
    2021-06-04 09:13:42 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.0.0
    2021-06-04 09:13:42 INFO:  Toolchain: tfjs: 3.7.0 esbuild 0.12.6; typescript 4.2.4; typedoc: 0.20.36 eslint: 7.27.0
    2021-06-04 09:13:42 INFO:  Build: file startup all target: es2018
    2021-06-04 09:13:42 STATE: Build for: node type: tfjs: { imports: 1, importBytes: 143, outputBytes: 1327, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:13:42 STATE: Build for: node type: node: { imports: 162, importBytes: 234251, outputBytes: 175089, outputFiles: 'dist/face-api.node.js' }
    2021-06-04 09:13:42 STATE: Build for: nodeGPU type: tfjs: { imports: 1, importBytes: 147, outputBytes: 1335, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:13:42 STATE: Build for: nodeGPU type: node: { imports: 162, importBytes: 234259, outputBytes: 175097, outputFiles: 'dist/face-api.node-gpu.js' }
    2021-06-04 09:13:42 STATE: Build for: nodeCPU type: tfjs: { imports: 1, importBytes: 138, outputBytes: 1326, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:13:42 STATE: Build for: nodeCPU type: node: { imports: 162, importBytes: 234250, outputBytes: 175088, outputFiles: 'dist/face-api.node-cpu.js' }
    2021-06-04 09:13:42 STATE: Build for: browserNoBundle type: tfjs: { imports: 1, importBytes: 276, outputBytes: 277, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:13:42 STATE: Build for: browserNoBundle type: esm: { imports: 162, importBytes: 233201, outputBytes: 168707, outputFiles: 'dist/face-api.esm-nobundle.js' }
    2021-06-04 09:13:43 STATE: Build for: browserBundle type: tfjs: { modules: 1348, moduleBytes: 4323957, imports: 7, importBytes: 276, outputBytes: 2328203, outputFiles: 'dist/tfjs.esm.js' }
    2021-06-04 09:13:44 STATE: Build for: browserBundle type: iife: { imports: 162, importBytes: 2561127, outputBytes: 2448241, outputFiles: 'dist/face-api.js' }
    2021-06-04 09:13:45 STATE: Build for: browserBundle type: esm: { imports: 162, importBytes: 2561127, outputBytes: 2327046, outputFiles: 'dist/face-api.esm.js' }
    2021-06-04 09:13:45 INFO:  Running Linter: [ 'server/', 'demo/', 'src/', 'test/', [length]: 4 ]
    2021-06-04 09:14:10 INFO:  Linter complete: files: 183 errors: 0 warnings: 0
    2021-06-04 09:14:10 INFO:  Compile typings: [ 'src/index.ts', [length]: 1 ]
    2021-06-04 09:14:15 INFO:  Update Change log: [ '/home/vlado/dev/face-api/CHANGELOG.md', [length]: 1 ]
    2021-06-04 09:14:15 INFO:  Generate TypeDocs: [ 'src/index.ts', [length]: 1 ]




    Face Mesh

    FaceAPI landmark model returns 68-point face mesh as detailed in the image below:

    facemesh




    Note

    This is updated face-api.js with latest available TensorFlow/JS as the original is not compatible with tfjs 2.0+.
    Forked from face-api.js version 0.22.2 which was released on March 22nd, 2020

    Currently based on TensorFlow/JS 3.6.1

    Why? I needed FaceAPI that does not cause version conflict with newer versions of TensorFlow
    And since original FaceAPI was open-source, I've released this version as well

    Changes ended up being too large for a simple pull request
    and it ended up being a full-fledged version on its own

    Plus many features were added since original inception

    Although a lot of work has gone into this version of FaceAPI and it will continue to be maintained,
    at this time it is completely superseded by my newer library Human which covers the same use cases,
    but extends it with newer AI models, additional detection details, compatibility with latest web standard and more


    Differences

    Compared to face-api.js version 0.22.2:

    • Compatible with TensorFlow/JS 2.0+ & 3.0+
    • Compatible with WebGL, CPU and WASM TFJS Browser backends
    • Compatible with both tfjs-node and tfjs-node-gpu TFJS NodeJS backends
    • Updated all type castings for TypeScript type checking to TypeScript 4.2
    • Switched bundling from UMD to ESM + CommonJS with fallback to IIFE Resulting code is optimized per-platform instead of being universal Fully tree shakable when imported as an ESM module Browser bundle process uses ESBuild instead of Rollup
    • Typescript build process now targets ES2018 and instead of dual ES5/ES6 Resulting code is clean ES2018 JavaScript without polyfills
    • Removed old tests, docs, examples
    • Removed old package dependencies (karma, jasmine, babel, etc.)
    • Updated all package dependencies
    • Updated TensorFlow/JS dependencies since backends were removed from @tensorflow/tfjs-core
    • Updated mobileNetv1 model due to batchNorm() dependency
    • Added version class that returns JSON object with version of FaceAPI as well as linked TFJS
    • Added test/dev built-in HTTP & HTTPS Web server
    • Removed mtcnn and tinyYolov2 models as they were non-functional in latest public version of FaceAPI Which means valid models are tinyFaceDetector and mobileNetv1 If there is a demand, I can re-implement them back.
    • Added face angle calculations that returns roll, yaw and pitch
    • Added typdoc automatic API specification generation during build
    • Added changelog automatic generation during build

    Credits


    Stars Forks Code Size CDN
    Downloads Downloads Downloads

    Install

    npm i @vladmandic/face-api

    DownloadsWeekly Downloads

    524

    Version

    1.3.1

    License

    MIT

    Unpacked Size

    43.8 MB

    Total Files

    405

    Last publish

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