Showing 12 open source projects for "point clouds"

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  • 1
    Point Cloud Library

    Point Cloud Library

    A standalone, large scale, open project for 2D/3D image processing

    The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. An additional Wiki resource for developers is available too. To simplify both usage and...
    Downloads: 32 This Week
    Last Update:
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  • 2
    CloudCompare

    CloudCompare

    CloudCompare main repository

    CloudCompare is a 3D point cloud (and triangular mesh) processing software. It was originally designed to perform comparison between two 3D points clouds (such as the ones obtained with a laser scanner) or between a point cloud and a triangular mesh. It relies on an octree structure that is highly optimized for this particular use-case. It was also meant to deal with huge point clouds (typically more than 10 million points, and up to 120 million with 2 GB of memory).
    Downloads: 935 This Week
    Last Update:
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  • 3
    pyntcloud

    pyntcloud

    pyntcloud is a Python library for working with 3D point clouds

    This page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. ...
    Downloads: 1 This Week
    Last Update:
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  • 4
    Pytorch Points 3D

    Pytorch Points 3D

    Pytorch framework for doing deep learning on point clouds

    Torch Points 3D is a framework for developing and testing common deep learning models to solve tasks related to unstructured 3D spatial data i.e. Point Clouds. The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! We aim to build a tool that can be used for benchmarking SOTA models, while also allowing practitioners to efficiently pursue research into point cloud analysis, with the end goal of building models which can be applied to real-life applications. ...
    Downloads: 0 This Week
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  • 5
    Semantic Segmentation Editor

    Semantic Segmentation Editor

    Web labeling tool for bitmap images and point clouds

    A web-based labeling tool for creating AI training data sets (2D and 3D). The tool has been developed in the context of autonomous driving research. It supports images (.jpg or .png) and point clouds (.pcd). It is a Meteor app developed with React, Paper.js, and three.js.
    Downloads: 0 This Week
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  • 6
    Objectron

    Objectron

    A dataset of short, object-centric video clips

    The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists of 15K annotated video clips supplemented with over 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes. ...
    Downloads: 1 This Week
    Last Update:
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  • 7
    Dynamic Robot Localization

    Dynamic Robot Localization

    Point cloud registration pipeline for robot localization and 3D

    The dynamic_robot_localization is a ROS package that offers 3 DoF and 6 DoF localization using PCL and allows dynamic map update using OctoMap. It's a modular localization pipeline, that can be configured using yaml files (detailed configuration layout available in drl_configs.yaml and examples of configurations available in guardian_config and dynamic_robot_localization_tests). Even though this package was developed for robot self-localization and mapping, it was implemented as a generic,...
    Downloads: 0 This Week
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  • 8

    Point Cloud Skinner for Blender

    Python script (addon) for Blender to skin point cloud (verts to face).

    ...Features: This script, Point Cloud Skinner can skin a cloud of vertices, which means to create a 3D surfaced mesh out of just a cloud of vertices that has no faces. It can skin any shapes of point clouds, such as a surveyed geography point cloud that represents a landform somewhere, a fluid volumetric point cloud obtained by numerical fluid simulation, or anything you like.
    Downloads: 5 This Week
    Last Update:
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  • 9
    Manifold mesh processing

    Manifold mesh processing

    Mesh and point cloud processing tools

    A suite of tools for processing and analyzing meshes and point clouds. 1) Ensuring that meshes are manifold, ie, "nice" 2) Simple smoothing/noise reduction 3) Bare-bones point cloud to mesh and robust normals for point clouds 4) Mesh simplification 5) Curvature calculation on meshes 6) Local shape descriptors on meshes
    Downloads: 2 This Week
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  • 10
    Point cloud defect analizer

    Point cloud defect analizer

    Defect detection in point clouds

    Point cloud defect analyzer - software project written on C++ for surface defect detection in point clouds obtained from laser scanners.
    Downloads: 0 This Week
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  • 11

    connect3d

    Reconstruct Water-Tight Triangulation from Point Cloud

    This software reconstructs water-tight triangulations from point clouds, interpolating the points. It approximates the triangle mesh which minimizes the sum of all triangles' longest edge. As a result, it can interpolate much more sparse sampling as state-of-the-art algorithms. Run-time is in practice linear to that of the Delaunay triangulation of the points. The software is designed as a command-line tool.
    Downloads: 1 This Week
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  • 12
    Various tools for point cloud processing. Similarity transformations, 2.5D incisions and Point Cloud coloring.
    Downloads: 1 This Week
    Last Update:
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