Showing 2 open source projects for "core-analyzer"

View related business solutions
  • Paessler: Easy to Use With Enterprise Power. Free Trial Icon
    Paessler: Easy to Use With Enterprise Power. Free Trial

    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

    You shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
    Get Free Download
  • Earn up to 16% annual interest with Nexo. Icon
    Earn up to 16% annual interest with Nexo.

    More flexibility. More control.

    Generate interest, access liquidity without selling, and execute trades seamlessly. All in one platform. Geographic restrictions, eligibility, and terms apply.
    Get started with Nexo.
  • 1
    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. Accurate 3D point clouds can nowadays be (easily and...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    Pytorch Points 3D

    Pytorch Points 3D

    Pytorch framework for doing deep learning on point clouds

    ...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. Task driven implementation with dynamic model and dataset resolution from arguments. Core implementation of common components for point cloud deep learning - greatly simplifying the creation of new models. 4 Base Convolution base classes to simplify the implementation of new convolutions. Each base class supports a different data format.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next