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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Real time WebGL and JavaScript library for face tracking, expression detection and animated emoticons in the browser, with both SVG and Three.js demos included 😄
| Date | Stars |
|---|---|
| 2026-07-24 | 1098 |
| 2026-07-25 | 1098 |
| 2026-07-28 | 1098 |
| 2026-07-30 | 1098 |
| 2026-08-06 | 1098 |
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**NOTICE: Apple<sup>©</sup>'s lawyers threatened us to file a complain on the 21th of August 2019 for infringing their intellectual property. So we have replaced the 3D animated fox by a raccoon.** **Indeed, Apple<sup>©</sup> owns the intellectual property of 3D animated foxes (but not on raccoons yet). Thank you for your understanding.** # JavaScript/WebGL library to detect and reproduce facial expressions You can build your own animated emoticon embedded in your web application thanks to this library. The video is processed exclusively on the client-side. The computing power of your GPU is important. If your GPU is powerful, many detections per second will be processed and the result will be smooth and accurate. The face detection should work even if the lighting is not great. However, the better is the input image, the better is the face expressions detection. Here are some tips to get a good experience: * The face should be well enlighted: the nose, the eyes should be distinguishable, * Avoid backlighting: The background should be a wall, not a window, * The face should not be too far, neither too close to the camera: the face should ideally cover 1/3 of the camera height. It should be fully visible, * The camera should be placed in front of the user. A side view is not recommended, * Beards and mustaches can make mouth movement detection harder, and glasses can disturb eyes detection. ## Table of contents * [Features](#features) * [Architecture](#architecture) * [Demonstrations](#demonstrations) * [Run locally](#run-locally) * [Using module](#using-module) * [Integration](#integration) * [With a bundler](#with-a-bundler) * [With JavaScript frontend frameworks](#with-javascript-frontend-frameworks) * [Native](#native) * [Hosting](#hosting) * [About the tech](#about-the-tech) * [Under the hood](#under-the-hood) * [Compatibility](#compatibility) * [Documentation](#documentation) * [License](#license) * [References](#references) ## Features * face detection and tracking, * detects 11 facial expressions, * face rotation around the 3 axis, * robust to lighting conditions, * mobile friendly, * examples provided using SVG and THREE.js. ## Architecture * `/assets/`: assets, both for 3D and 2D demonstrations (3D meshes, images), * `/demos/`: the most interesting: the demos!, * `/dist/`: heart of the library: * `jeelizFaceExpressions.js`: main minified script. It gets the camera video feed, exploit the neural network to detect the face and the expressions and stabilize the result, * `jeelizFaceExpressionsNNC.json`: neural network model loaded by the main script, * `/doc/`: some additionnal documentation, * `/helpers/`: The outputs of the main script are very raw. It is convenient to use these helpers to animate a 3D model with the THREE.js helper or a SVG file with the SVG helper. All demos use these helpers, * `/libs/`: some javascript libs, * `/meshConverter/`: only for the THREE.js use. Tool to build the 3D model file including morphs from separate .OBJ files. ## Demonstrations All the following demos are included in this repository, in the `/demos` path. You can try them: * THREE.JS based demos: * **Cute raccoon**: [source code](/demos/three/raccoon/), [live demo](https://jeeliz.com/demos/weboji/demos/three/raccoon/) * **Cute raccoon from a MP4 video**: [source code](/demos/three/externalVideo/), [live demo](https://jeeliz.com/demos/weboji/demos/three/externalVideo/) * **Ready Player Me**! [source code](/demos/three/readyPlayerMe/), [live demo](https://jeeliz.com/demos/weboji/demos/three/readyPlayerMe/) * SVG based demos: * **Cool Cartman**: [source code](/demos/svg), [live demo](https://jeeliz.com/demos/weboji/demos/svg/) * Native demos: * **Cute raccoon**: [source code and instruction to build and run it](/demos/cordova/raccoon) This demo works as a native application using Apache Cordova. It has been tested successfully on iOS. The base code is the same than t
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:d670700ee876009c, topic:deep-learning
matched fp:d670700ee876009c, topic:computer-vision