8 repositorios
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 es una librería de aprendizaje profundo 3D para PyTorch que proporciona un conjunto integral de herramientas para el procesamiento de geometría 3D, simulación física, visualización de datos y renderizado basado en gradientes para visión artificial. La librería incluye un renderizador 3D diferenciable y un kit de herramientas de procesamiento de geometría para convertir y transformar representaciones 3D como mallas (meshes) y nubes de puntos. También cuenta con un motor de simulación física 3D para calcular interacciones físicas y colisiones entre objetos y escenas tridimensionales. El kit de herramientas proporciona utilidades para la visualización de datos 3D, incluyendo la creación de vistas interactivas y animaciones de rotación. Las capacidades adicionales cubren la gestión de datasets 3D, preprocesamiento de datos y renderizado de representaciones 3D.
NVIDIA library for accelerating 3D deep learning research.
3D visualization and mesh analysis for science and engineering
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.