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
Draco is a library and toolset for compressing, transcoding, and decoding 3D geometric meshes and point cloud data. Its primary purpose is to reduce storage size and transmission bandwidth for 3D assets. The project includes a geometry optimizer specifically for glTF file containers to reduce asset footprints. It also features a hardened decoder designed to process malformed or untrusted 3D geometric data safely to prevent memory corruption and crashes. The software covers a broad range of 3D data processing capabilities, including geometric data reconstruction, point attribute management, a
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
OpenPCDet is a PyTorch deep learning library and toolbox for LiDAR 3D object detection. It functions as a point cloud processing framework designed to develop, train, and evaluate machine learning models that identify and locate objects in three dimensional space. The project includes a GPU-accelerated geometry engine for high-performance implementation of 3D intersection over union and rotated non-maximum suppression. It also provides a distributed model training tool to scale the training and testing of detection models across multiple GPUs and computing nodes. The framework covers point c
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.
intel-isl/open3d की मुख्य विशेषताएं हैं: 3D Data Processing Libraries, 3D Machine Learning, Scene Reconstruction, 3D Engines, Spatial Analysis Viewers, Analytical Rendering, 3D Machine Learning Libraries, 3D Detection and Segmentation।
intel-isl/open3d के ओपन-सोर्स विकल्पों में शामिल हैं: pointcloudlibrary/pcl — The Point Cloud Library is a collection of C++ algorithms designed for filtering, registering, and analyzing… google/draco — Draco is a library and toolset for compressing, transcoding, and decoding 3D geometric meshes and point cloud data.… facebookresearch/pytorch3d — PyTorch3D is a 3D geometric deep learning library and mesh processing toolkit designed for learning from point clouds… poodarchu/det3d — World's first general purpose 3D object detection codebse. open-mmlab/openpcdet — OpenPCDet is a PyTorch deep learning library and toolbox for LiDAR 3D object detection. It functions as a point cloud… lastools/lastools — efficient tools for LiDAR processing.