Search Results for "installation tutorial"

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

MiModD is a software package for genomic variant identification from next-generation sequencing (NGS) data with optimized usage of system resources and a user-friendly interface. For most model organism genomes it lets the user carry out a complete analysis from unaligned genomic NGS read data to an annotated list of variants on a regular Desktop PC within a few hours. Its user-interface is beginner-friendly and designed to encourage geneticists to analyze NGS data themselves without the...

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.