Open-source alternatives to Cgal

This project provides a collection of algorithmic implementations for computational geometry, focusing on spatial analysis, mesh construction, and geometric data processing. It serves as a toolkit for generating and manipulating complex shapes, surfaces, and spatial relationships within interactive three-dimensional applications. The library distinguishes itself through a suite of mathematical functions designed for procedural mesh generation and geometric partitioning. It includes specialized routines for calculating convex hulls, performing boolean operations on polygons, and detecting inte

This project is a comprehensive library of reference implementations for fundamental data structures and algorithms, designed to support technical interview preparation and software engineering assessments. It provides a structured collection of computational techniques for solving complex problems involving arrays, strings, graphs, trees, and mathematical analysis. The library distinguishes itself by offering specialized implementations for advanced topics, including concurrent programming patterns and geometric algorithms. It features thread-safe primitives for managing shared state and tas

This project is a header-only C++ library designed for graphics mathematics, providing a comprehensive suite of vector, matrix, and quaternion types. It is built using template metaprogramming to generate mathematical primitives at compile time, eliminating the need for precompiled binary libraries and allowing for direct integration into existing build systems. The library is distinguished by its strict adherence to the OpenGL Shading Language specification, ensuring that mathematical results remain consistent across both CPU and GPU code. It provides specialized utilities for managing float

MeshLab is an open-source 3D mesh processing system designed for editing and analyzing unstructured triangular meshes. It functions as a triangular mesh editor, a model visualization suite, and a conversion tool for transforming 3D mesh data between various file formats. The software provides tools for cleaning, healing, and optimizing large 3D models generated from raw digitization and scanning data. It enables the preparation of models for physical 3D printing and the application of surface textures to evaluate the visual appearance of digital models. The system covers a broad range of cap

This project is a physically based rendering system and ray tracing engine designed to generate photorealistic images. It operates as a spectral rendering system that records radiance across discretized wavelength buckets and functions as a volumetric path tracer to compute light scattering and absorption within participating media. The engine utilizes GPU acceleration to execute its rendering pipeline on parallel graphics hardware. It integrates real-world optical data, such as measured spectral power distributions and lens description files, to simulate the behavior of physical camera syste

regl is a declarative WebGL library that manages graphics state and GPU resources through functional commands instead of manual binding and state tracking. It provides a command-based drawing abstraction where shaders, attributes, and render state are encapsulated into reusable, compiled functions that can be executed efficiently. What sets regl apart is its scoped state inheritance system, which allows nested drawing commands to inherit and override render state from parent scopes for organized rendering. The library automatically recovers from GPU context loss by restoring buffer and textur

The Point Cloud Library is a collection of C++ algorithms designed for filtering, registering, and analyzing large-scale 3D spatial datasets. It provides a framework for 3D point cloud processing, incorporating tools for spatial data filtering and geometric feature estimation. The library includes specialized systems for aligning multiple spatial datasets into a single unified coordinate system and a rendering engine for the visual inspection and analysis of processed point cloud data. It also features tools for calculating spatial descriptors to identify structural patterns and shapes within

GET3D is a generative 3D mesh model and rendering framework designed to synthesize high-quality textured shapes and tetrahedral meshes. It functions as an image-to-3D reconstructor and text-to-3D generator, utilizing a differentiable 3D renderer to produce realistic visual perspectives and material effects. The system enables the creation of 3D assets from single 2D images, point clouds, or descriptive text prompts. It features a latent space interpolator for creating smooth transitions between different 3D objects and supports the independent control of geometry and texture. The project cov

This project is a comprehensive reference for algorithms and data structures used to solve complex computational problems in competitive programming. It serves as a technical resource for implementing advanced mathematical programming, computational geometry, and graph theory. The repository provides detailed implementation guides for diversifying algorithmic techniques, including top-down and bottom-up dynamic programming optimization, number theory, and linear algebra. It features specific guides for complex tasks such as constructing planar graphs, solving linear Diophantine equations, and

Assimp is a cross-platform 3D asset pipeline and import library that loads numerous industry-standard 3D file formats into a single unified internal data structure. It functions as a framework for converting 3D models between different file formats across multiple operating systems and architectures. The project provides a 3D mesh processing tool for normalizing and optimizing geometry through triangulation, vertex removal, and normal generation. It also includes a 3D asset export utility to write internal scene data back into various external file formats. The system covers broad capability

OpenCVSharp is a .NET library that wraps native OpenCV functions, providing C# developers with access to OpenCV's computer vision capabilities through an API that mirrors the native C/C++ style. It serves as a managed wrapper for image processing, feature detection, object detection, and image manipulation tasks, while also handling automatic disposal of unmanaged OpenCV resources like Mat objects to prevent memory leaks in .NET applications. The library enables keypoint detection and descriptor extraction using algorithms such as AKAZE, BRISK, or FAST, with brute-force or FLANN-based matchin

PyTorch3D is a 3D geometric deep learning library and mesh processing toolkit designed for learning from point clouds and complex 3D surface geometries. It provides a collection of reusable components and data structures for deep learning with 3D data, including a framework for training and evaluating neural radiance fields to enable photorealistic view synthesis. The project features a differentiable 3D renderer that converts meshes and point clouds into 2D images while allowing gradients to flow back into the geometry and textures. This enables 3D shape optimization, where mesh geometry, te

mmocr is a PyTorch-based optical character recognition framework designed for training and deploying text detection, recognition, and key information extraction models. It serves as a comprehensive toolbox for scene text detection and recognition, providing specialized libraries for locating text regions and converting visual text into machine-encoded strings. The project distinguishes itself through a research framework for key information extraction and advanced text spotting capabilities. These include point-based spotting using transformers and the use of parameterized Bezier curves to id

This project is a browser-based, physically based path-tracing renderer built on WebGL and integrated with Three.js. It functions as a real-time global illumination engine, calculating light bouncing, soft shadows, reflections, refractions, and color bleeding interactively within web environments. The rendering system incorporates progressive multi-pass accumulation to refine noisy images iteratively over multiple frames, alongside GPU-accelerated spatial acceleration structures and bounding volume hierarchies to handle complex geometry. It supports diverse material types such as refractive

libigl is a C++ geometry processing library used for analyzing and manipulating 3D triangle and tetrahedral meshes. It functions as a numerical linear algebra suite and a mesh manipulation framework, integrating a geometric deformation engine to implement rigid and polyharmonic transformations. The project is distinguished by its header-only library design and its implementation of specialized deformation techniques, including rigid-as-possible and polyharmonic shape deformation. It also provides a visualization tool for rendering surfaces and scalar fields with interactive scene controls and

FAST_LIO is a real-time SLAM system and LiDAR-inertial odometry package designed for simultaneous localization and mapping. It functions as a state estimation engine and 3D mapping tool that fuses LiDAR point clouds with inertial measurement unit data to provide robust robot state estimation. The system utilizes a tightly-coupled sensor fusion approach with an iterative Kalman filter to estimate position and orientation. It distinguishes itself through direct point-to-plane matching, which calculates odometry by matching raw lidar points to the map surface without manual geometric feature ext

This project is a comprehensive collection of computer science implementations and an algorithm tutorial repository. It serves as a study guide and reference for competitive programming, providing executable code examples that demonstrate fundamental algorithmic problem solving and mathematical computation. The library covers a wide range of specialized domains, including cryptography and security primitives, lossless data compression techniques, and computational geometry for spatial analysis. It also features implementations of machine learning models, linear algebra operations, and formal

sigma.js is a JavaScript graph visualization library and WebGL network renderer designed for drawing large-scale network graphs in web browsers. It functions as a high-performance engine capable of rendering network structures containing thousands of nodes and edges interactively. The library provides a customizable graph engine that allows for the creation of specialized visualizations using low-level graphics primitives and custom drawing layers. It supports the rendering of diverse node shapes, such as images or piecharts, and enables the integration of graph visualizations as overlays on

Querydsl is a framework for the construction of type-safe queries. It uses a fluent API and annotation-based code generation to create mirror classes from domain models, enabling compile-time validation of database queries and removing the need for manual string concatenation. The project provides a unified query syntax that translates into specific dialects for multiple backends, including SQL, MongoDB, Lucene, and JDO. It supports advanced query capabilities such as common table expressions, window functions, geospatial operations, and complex nested subqueries. Beyond data retrieval, the

The Book of Shaders is an interactive educational guide and curriculum for learning GLSL fragment shader programming to create procedural graphics and visual effects. It provides a structured learning path and a categorized reference guide for data types, built-in functions, and mathematical operations used in shader development. The project features a web-based shader sandbox and interactive editor that allows for real-time iteration and visualization of GLSL code. Users can experiment with procedural art and share their results via unique URLs. The curriculum covers a wide range of graphic

Point-e is a system for 3D model synthesis that generates three-dimensional point clouds from natural language descriptions and two-dimensional images. It utilizes diffusion models to synthesize these spatial representations based on text prompts or source images. The project includes specialized tools for refining these outputs, such as a point cloud upsampler to increase the density and resolution of low-resolution models. It also provides a mesh converter that uses distance function regression to transform raw point cloud data into structured 3D meshes. The broader capability surface cove

This project is a ray tracing engine and C++ rendering project designed to simulate the physical behavior of light to generate 2D images from 3D scenes. It serves as a computer graphics tutorial and educational implementation intended to teach the fundamental mathematical and algorithmic principles of 3D graphics programming. The implementation focuses on the foundations of light transport and scene geometry. It utilizes Whitted-style recursive raytracing to simulate reflections and employs Lambertian diffuse shading to calculate surface brightness. The engine handles 3D scene rendering thro

CadQuery is a programmatic 3D modeling library and parametric CAD framework that allows for the generation of complex geometric solids and assemblies using a fluent Python API. It functions as a B-Rep geometry engine, enabling the construction of models through code rather than a graphical user interface. The project is built on the Open CASCADE Technology kernel and utilizes a method-chaining API to link geometric commands in sequence. It distinguishes itself through a workplane-based coordinate system and a powerful selection system that uses topological and spatial filtering to target spec

This project is a diffusion-based 3D generator and image-to-3D reconstruction system. It translates natural language descriptions or two-dimensional images into three-dimensional assets using neural radiance fields and diffusion models. The system utilizes score-distillation sampling and diffusion-based guidance to refine 3D shapes without requiring 3D training data. It includes specialized tools for transforming neural representations into exportable meshes with texture and material data, as well as a pipeline for iterative optimization of geometry and textures. The project covers a broad r

mmcv is a foundation library for computer vision based on PyTorch. It provides a comprehensive system for constructing convolutional neural networks, a toolkit for image and video preprocessing, and a collection of high-performance deep learning vision operators. The project is distinguished by its hardware-accelerated kernels for complex operations such as deformable convolutions and region pooling. It features a configuration-driven framework that allows for the dynamic instantiation of network layers and the registration of custom modules without modifying code. The library covers a broad

This project is a comprehensive collection of common computer science algorithms and data structures implemented in Swift. It serves as an educational reference and library for studying computational complexity, algorithmic logic, and data structure engineering through practical code examples. The repository provides a wide suite of data structure implementations, including various types of linked lists, heaps, hash tables, and an extensive range of hierarchical trees such as Red-Black, B-Tree, and Splay trees. It also covers diverse sorting and searching techniques, from basic bubble sort to

JoltPhysics is a high-performance C++ physics engine designed for multi-threaded simulation of 3D rigid bodies and soft bodies. It serves as a deterministic simulation framework, ensuring identical results across different platforms and architectures to support networked synchronization. The engine distinguishes itself through a focus on concurrent execution across multiple CPU cores to handle large numbers of active bodies. It provides specialized systems for vehicle physics, including wheeled and tracked models, as well as soft body physics for deformable objects and cloth. The simulation