Showing 4 open source projects for "3d point cloud processing"

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  • 1
    OpenReco

    OpenReco

    Open-source photogrammetry for 3D reconstruction.

    OpenReco is an open-source photogrammetry and reality-capture platform designed to turn photographs into accurate 3D models, dense point clouds, textured meshes, DEMs, and orthomosaics. Built for researchers, drone operators, surveyors, developers, hobbyists, and digital artists, OpenReco aims to provide a transparent and extensible alternative to proprietary photogrammetry software. The project focuses on ease of use, performance, and reproducible workflows while embracing the...
    Downloads: 0 This Week
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  • 2
    pyntcloud

    pyntcloud

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

    ...Accurate 3D point clouds can nowadays be (easily and cheaply) acquired from different sources. pyntcloud enables simple and interactive exploration of point cloud data, regardless of which sensor was used to generate it or what the use case is. Although it was built for being used on Jupyter Notebooks, the library is suitable for other kinds of uses. pyntcloud is composed of several modules (as independent as possible) that englobe common point cloud processing operations.
    Downloads: 1 This Week
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  • 3
    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...
    Downloads: 1 This Week
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  • 4
    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: 1 This Week
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