8 个仓库
Software libraries for manipulating, visualizing, and analyzing 3D point cloud data.
Explore 8 awesome GitHub repositories matching part of an awesome list · Processing Libraries. Refine with filters or upvote what's useful.
Open3D is a 3D data processing library, visualization engine, and machine learning library. It provides a framework for manipulating point clouds and meshes through specialized algorithms designed for 3D data science workflows. The project includes a toolkit for 3D scene reconstruction to generate spatial models and align surfaces from raw data. It also functions as a GPU accelerated framework that offloads intensive spatial computations to the graphics processor to increase processing speed. The library covers a broad range of capabilities including physically based light simulations for vi
Library for 3D data processing, visualization, and algorithm development.
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
Highly parallel library for industrial and research point cloud processing.
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
Deep learning library for 3D data processing and research.
Kaolin 是一个 PyTorch 3D 深度学习库,提供了一套全面的工具,用于 3D 几何处理、物理模拟、数据可视化和用于计算机视觉的梯度渲染。 该库包括一个可微分的 3D 渲染器和一个用于转换和变换 3D 表示(如网格和点云)的几何处理工具包。它还具有一个 3D 物理模拟引擎,用于计算三维物体和场景之间的物理交互和碰撞。 该工具包提供用于 3D 数据可视化的实用工具,包括创建交互式视图和转盘动画。其他功能涵盖 3D 数据集管理、数据预处理和 3D 表示渲染。
NVIDIA library for accelerating 3D deep learning research.
PyVista is a scientific 3D plotting framework and visualization library that provides a Python interface for rendering and analyzing spatial datasets using a VTK backend. It functions as a volumetric rendering engine and a 3D mesh analysis tool for computing geometric properties and performing boolean operations on surface and volumetric meshes. The project is distinguished by its ability to operate as a headless 3D renderer, generating high-quality renders and animations on remote servers without a physical display. It also features a lazy-accessor extension mechanism that allows the registr
Interface for 3D plotting and mesh analysis using VTK.
Making point clouds fun again
Python library for scientific point cloud data manipulation.
efficient tools for LiDAR processing
Command-line tools and C++ library for point cloud processing.
pointcloudset
Efficient analysis of time-series point cloud datasets.