If you are a freelance developer, or if you represent a web agency or a software company able to build web applications using Jeeliz libraries, you should definitely join the Jeeliz Partner Network (JPN). Here is why: We will refer to your services when we receive development service requests, We will provide you premium support. Please fill this short Google form Conversely, if you are looking for a reliable service provider to help you with Read more…
The Jeeliz GlanceTracker API is a Javascript library that lets us detect if the user is looking towards his/her screen. The library uses our custom made deep learning framework to analyse the video stream coming from the user’s webcam in real time. Let us see together how to use it. Adding the script to our project We’ll firstly need to clone the repository. We will then add the library script in the head of our Read more…
Xavier Bourry is giving a 10 minutes talk about the next steps for Jeeliz. It will be on Wednesday 21th of August at NYC ARKit meetup at 7pm. You can subscribe here, on meetup.com. Come on to discover our plans for Jeeliz libraries and our latest improvements!
The Jeeliz Glasses VTO widget is a javascript library that lets us add a virtual try-on widget to a web app. The VTO experience combines the use of 3D technologies in the browser and of our custom deep learning framework. The latter is used to train neuron networks that can analyze a video stream in order to detect a human face. We already wrote an article on How to use the Jeeliz VTO widget in Read more…
JeelizAR is a JavaScript library that can detect elements in a video feed. By giving us the position of the detected object, it allows us to add augmented reality (AR) elements. Let’s learn together how to build amazing AR experiences for our users, in the **browser. Adding the source files to our project We’ll start off by setting up our index.html, where we’ll build our JeelizAR demo. Let’s add our source file. For this project, Read more…
Jeeliz AR is a JavaScript library that can detect an object in a video feed and give its precise position. Under the hood, we are using our custom deep learning algorithms to parse each video frame and analyse it, to try and find a target object. Here is a demo: Currently, our network can detect chairs, mugs, bicycles and cats (see the online demo). Let’s see together how to use the Jeeliz AR API in Read more…
The Jeeliz VTO widget API is a Javascript library that lets you add a glasses virtual try-on widget to your web app in minutes. The widget uses our custom JS deep learning framework to detect the user’s face and add to it the glasses frame in augmented reality (AR). Although the library is technically advanced, we made sure that any developer could easily add a Jeeliz VTO widget to his/her website, by creating a simple Read more…
The Jeeliz VTO widget API is a Javascript library that lets you add a glasses virtual try-on experience to your web app. The widget uses our custom JS deep learning framework to detect the user’s face and add to it the glasses frame in augmented reality (AR). Besides, we made available more than 300 glasses models for free to use (see the list of the skus here). We saw in a previous article, How to Read more…
The VTO Studio Lite is a web application made by Jeeliz. Anyone can build a glasses virtual try-on (VTO) experience in minutes! You can access to this amazing web application here: jeeliz.com/demos/glasses-studio. It requires 1366 pixels wide or above screen and a desktop computer. The VTO widget built won’t have these restrictions, it will even work on mobile devices. You can also watch a screenshot video of the application on our Youtube channel: https://www.youtube.com/watch?v=BwU3O05yx2A. In Read more…
Our solution We provide a cutting edge virtual try-on solution for head mounted accessories. It is perfect for glasses or ski masks. It works everywhere without installing anything: In a website browsed by a desktop computer or a mobile device, In a mobile application, On a showcase display. The glasses are displayed over the user’s head in real-time, using the video feed from its camera. If the device is too old or if the user Read more…