About

We develop JavaScript libraries to bring real-time computer vision to web developers. They are powered by the fastest deep learning engine running in the web browser. It is so fast that it can analyze a video stream in real-time even on mid range mobile devices.

We don't rely on any mainstream deep learning framework or computer vision library like OpenCV or Tensorflow. Our software is home-made, lightweight, standalone, efficient and our license fees are affordable.

You can browse our libraries in our Github page.

Contact

You can contact us at [email protected].

Follow

You can follow US:

• On Twitter: @WebARRocks
  
  
• On Linkedin: @WebAR.rocks

WebAR.rocks.hand

This is our hand detection and tracking computer vision solution.

• It is fully web based and mobile friendly,
• It is featured with these demos:
  • Hand based navigation (as on this website),
  • 3D Object manipulation in the palm of your hand,
  • Shoes virtual try-on (both barefoot and shoes on),
  • Wristwatch and ring virtual try-on
• Virtual try-on demos are provided using THREE.js as rendering engine,
• Integration demos are provided both in static JavaScript and in a React / Three fiber / NPM / ES6 environment.

Source code and demos are hosted on Github here: github.com/WebAR-rocks/WebAR.rocks.hand.

WebAR.rocks.image

This is our image detection and tracking solution.

• It is fully web based and mobile friendly,
• THREE.js is used as 3D rendering engine,
• Can track an unlimited number of target images,
• Specific neural network needs to be trained in some cases,
• It can be used to track generic plane objects like QRCodes, screens with web content, identity documents, ...
• Integration demos are provided both in static JavaScript and in a React / Three fiber / NPM / ES6 environment.

The source code and demos are hosted in a private Github repository. To access it, please contact us at [email protected].

WebAR.rocks.face

This is our face detection and tracking solution.

• It is fully web based and mobile friendly,
• THREE.js is used as 3D rendering engine,
• It detects specific facial landmarks,
• It is featured with these demos:
  • Flexible mask face filter,
  • Accessories VTO: earrings, hats, glasses, motorcycle helmet/headphones,
  • Makeup VTO: sport makeup, lipstick, full makeup,
  • Face replacement.
• Integration demos are provided both in static JavaScript and in a React / Three fiber / NPM / ES6 environment,
• We provide support and upgrades through a yearly licencing plan.

Source code and demos are hosted on Github here: github.com/WebAR-rocks/WebAR.rocks.face.

WebAR.rocks.object

This is our generalistic object detection and tracking solution.

• It is fully web based and mobile friendly,
• THREE.js is used as 3D rendering engine,
• It detects object orientation to overlay 3D content with 6DoF,
• It can also be used with SLAM engines (8th Wall, WebXR) to handle the tracking once object is detected,
• Neural network training is done from a 3D model of the object,
• We can train a neural network to detect a general concept (like a car or a cup) or a specific 3D object (like a specific can model),
• Integration demos are provided both in static JavaScript and in a React / Three fiber / NPM / ES6 environment,

Source code and demos are hosted on Github here: github.com/WebAR-rocks/WebAR.rocks.object.