Search Results for "work tracking"

...The library also offers synthetic streams (point cloud, depth aligned to color and vise-versa), and built-in support for recording and playback of streaming sessions. Intel has EOLed the LiDAR, Facial Authentication, and Tracking product lines. These products have been discontinued and will no longer be available for new orders. Intel WILL continue to sell and support stereo products including the following: D410, D415, D430, , D401 ,D450 modules and D415, D435, D435i, D435f, D405, D455, D457 depth cameras. We will also continue the work to support and develop our LibRealSense open source SDK.

RLM (short for Reinforcement Learning Models) is a modular framework that makes it easier to build, train, evaluate, and deploy reinforcement learning (RL) agents across a wide range of environments and tasks. It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom agents, environments, policy networks, and reward structures while leveraging built-in dataset utilities, logging, and checkpointing for reproducible experiments. RLM also includes integration with popular simulation environments and benchmark suites, giving researchers a ready-made playground for algorithm comparison and performance tracking.

Microbundle produces esm, cjs, umd bundles with your code compiled to syntax that works pretty much everywhere. While it's possible to customize the browser or Node versions you wish to support using a browserslist configuration, the default setting is optimal and strongly recommended. In addition to the above formats, Microbundle also outputs a modern bundle specially designed to work in all modern browsers. This bundle preserves most modern JS features when compiling your code, but ensures...

...But thanks to the featured helpers, examples and boilerplates, you can quickly deal with a higher level context (for motion head tracking, for face filter or face replacement). We continuously add new demonstrations, so stay tuned!

AR.js is a lightweight JavaScript library for delivering augmented reality experiences on the web. It supports image tracking, location-based AR, and marker-based interactions—all without requiring native applications or plugins. AR.js was among those great projects, with great technologies, often disruptive ones, that eventually were lacking from documentation and support. We tried to carry on the author's terrific work by maintaining this project, handling new versions, issues, pull requests, the community itself. ...

...The library provides some generic face models that were trained on the MUCT database and some additional self-annotated images. Check out clmtools for building your own models. For tracking in video, it is recommended to use a browser with WebGL support, though the library should work on any modern browser. For some more information about Constrained Local Models, take a look at Xiaoguang Yan's excellent tutorial, which was of great help in implementing this library.