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VUDA is a header-only library based on Vulkan that provides a CUDA Runtime API interface for writing GPU-accelerated applications.

A C++ binding for the OpenGL API, generated using the gl.xml specification.

  • c-plus-plus
  • c-plus-plus-11
  • library
  • opengl-bindings

A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter.

Fast CSV parser and writer for Modern C++

  • csv-parser
  • single-threaded
  • mit-license
  • header-only

A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

  • optimization
  • optimization-algorithms
  • optimization-methods
  • optimization-problem

GUI for Fancontrol. It uses the KAuth module of the KDE Frameworks 5 to write the generated config file. Furthermore it communicates with systemd via dbus to control the fancontrol service. If you want to compile without systemd support set the -DNO_SYSTEMD option.

Cross-platform C++20 GUI framework featuring MVVM architecture, reactive capabilities, and scalable, accelerated GPU rendering.

  • cpp20
  • cross-platform-gui
  • gui
  • modern-cpp

Precise map-matching for public transit feeds. Generates high-quality GTFS shapes from OSM data.

This is the GitHub home of Race Into Space, the computer version of the Liftoff! board game by Fritz Bronner. It was developed by Strategic Visions and published by Interplay as a disk-based game in 1993 and a CD-ROM in 1994. It was open-sourced in 2005 and a number of improvements have been made over the original.

  • lunar
  • lunar-lander
  • moon
  • probe

This repository provides a set of tools and libraries to integrate Intel® OpenVINO™ Toolkit with ROS 2 (Robot Operating System), enabling efficient deployment of deep learning models for computer vision applications on Intel® hardware.

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.