Search Results for "installation tutorial"

...How to immediately get started: Type #goto 1000 500 in chat to go to x=1000 z=500. Type #mine diamond_ore to mine diamond ore. Type #stop to stop. For more, read the usage page and/or watch this tutorial playlist. For other versions of Minecraft or more complicated situations or for development, see Installation & setup. Also consider just installing Impact, which comes with Baritone and is easier to install than wrangling with version JSONs and zips. For 1.16.5, click here and see description. Once Baritone is installed, look here for instructions on how to use it. ...

Isaac Lab is an open-source modular robotics learning framework built atop Isaac Sim. It simplifies research workflows across reinforcement learning, imitation learning, and motion planning by offering robust, GPU-accelerated simulation with realistic sensor and physics fidelity—ideal for sim-to-real robot training. Compatible and optimized for use with Isaac Sim versions (e.g., Sim 5.0 and 4.5). GPU-accelerated, high-fidelity physics and sensor simulation suitable for complex learning...

...The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. PyTorch Geometric Temporal makes implementing Dynamic and Temporal Graph Neural Networks quite easy - see the accompanying tutorial. Head over to our documentation to find out more about installation, creation of datasets and a full list of implemented methods and available datasets.

...SecurePose surpassed six existing methods in automated face detection and blurring and outperformed human performance in leg dystonia identification. This validation establishes its effectiveness and usability in clinically recorded gait videos for face blurring and kinematics extraction. For installation, https://www.rishabh-bajpai.com/secureposeinstallation Tutorial Videos https://www.youtube.com/playlist?list=PLO4_jCYO5Ib23MoBpn-Wpj1_b6DAYlDwk Please cite the paper: https://arxiv.org/abs/2402.14143

This project has been moved to https://github.com/fmipp/trnsys-fmu This open-source project provides a stand-alone tool for exporting FMUs for Co-Simulation from TRNSYS 17 models. The current release supports FMI version 1.0 and 2.0. Instructions on installation and usage are given in the documentation, which is provided as part of the download. This documentation also contains a tutorial on how to export a TRNSYS model as FMU for co-simulation and how to link it with a simple controller implemented in Modelica. The tool is based on code from the FMI++ library.