Official source code of FreeCAD, a free and opensource multiplatform 3D parametric modeler.
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Official source code of FreeCAD, a free and opensource multiplatform 3D parametric modeler.
OpenTTD is an open source simulation game based upon Transport Tycoon Deluxe
Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.
Instant Kubernetes-Native Application Observability
Parametric 2d/3d CAD
Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
Intel® Performance Counter Monitor (Intel® PCM)
Ultra-low-latency asynchronous C++17 logging and metrics library for performance-critical applications
Fallout for modern operating systems
Open Source Biometrics, Face Recognition
a programming library with geometric algorithms
Fallout 2 for modern operating systems
The fastest unified streaming SQL Engine in a single C++ binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute stateful context from streams, logs, metrics, events, and CDC.
The core of our monitoring platform with a powerful configuration language and REST API.
:white_square_button: Geometrize is a desktop app that geometrizes images into geometric primitives
Application Layer DoS attack simulator
GemRB is a portable open-source implementation of Bioware’s Infinity Engine.
Real-Time 3D Semantic Reconstruction from 2D data
(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping
Open-source parametric 3D CAD for makers — constraint sketches, solid modeling, threads, SVG & text engraving, STL/STEP export. Android, iPad, Linux, Mac, Windows. Vibe coded.
Fast lossless data compression in C++
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.
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