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1–16 of 16 · Most stars

Extremely fast, in memory, serialization, reflection, and RPC library for C++. JSON, BEVE, BSON, CBOR, CSV, JSONB, MessagePack, TOML, YAML, EETF

  • api
  • binary
  • cplusplus
  • cpp

QuadriFlow: A Scalable and Robust Method for Quadrangulation

  • quadriflow
  • quad
  • remeshing
  • quadrangulation

Free, open-source 3D sculpting for Linux, macOS and Windows: dense meshes, remeshing, painting, built-in AI (image/text to 3D), Send to Unreal, game-ready LODs, Gaussian splats and OpenUSD.

  • 3d
  • cpp
  • dear-imgui
  • digital-sculpting

A C++14-compatible physical units library with no dependencies and a single-file delivery option. Emphasis on safety, accessibility, performance, and developer experience.

  • cpp
  • cpp14
  • cpp14-library
  • dimensional-analysis

The Open Capture and Analytics Tool (OCAT) provides an FPS overlay and performance measurement for D3D11, D3D12, and Vulkan

  • mit-license
  • vulkan
  • fps-overlay
  • d3d12

VeloView performs real-time visualization and easy processing of live captured 3D LiDAR data from Velodyne sensors (Alpha Prime™, Puck™, Ultra Puck™, Puck Hi-Res™, Alpha Puck™, Puck LITE™, HDL-32, HDL-64E). Runs on Windows, Linux and MacOS. This repository is a mirror of https://gitlab.kitware.com/LidarView/VeloView-Velodyne.

  • lidar
  • lidar-camera-calibration
  • lidar-data-manipulation
  • lidar-measurements

Very fast, high-quality hash function, discrete-incremental and streamed hashing-capable (non-cryptographic, header-only C/C++) 27GB/s + PRNG

A few classes for extremely fast json parsing/serializing in modern C++. Possibly the fastest json parser in C++. Possibly the fastest json serializer in C++.

  • cpp
  • json
  • json-parsing
  • json-parsing-library

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.