Showing 4 open source projects for "linux mac windows"

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    Segments.ai

    Segments.ai

    Segments.ai Python SDK

    Multi-sensor labeling platform for robotics and autonomous vehicles. The platform for fast and accurate multi-sensor data annotation. Label in-house or with an external workforce. Intuitive labeling interfaces for images, videos, and 3D point clouds (lidar and RGBD). Obtain segmentation labels, vector labels, and more. Our labeling interfaces are set up to label fast and precise. Powerful ML assistance lets you label faster and reduce costs. Integrate data labeling into your existing ML...
    Downloads: 2 This Week
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    whiteboxgui

    whiteboxgui

    An interactive GUI for WhiteboxTools in a Jupyter-based environment

    The whiteboxgui Python package is a Jupyter frontend for WhiteboxTools, an advanced geospatial data analysis platform developed by Prof. John Lindsay (webpage; jblindsay) at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. WhiteboxTools can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image...
    Downloads: 0 This Week
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  • 3
    BEVFormer

    BEVFormer

    Implementation of BEVFormer, a camera-only framework

    3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV...
    Downloads: 0 This Week
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  • 4

    Planar Roof Top Detection in LiDAR

    This tool detects and classifies roof tops from raw spatial LiDAR

    A new algorithm for extracting roof tops was developed. Using the assumption that roof tops are planar in construction, a new approach was developed using volume of point clouds to determine whether a cluster contains planar points. This approach yields very promising results and with attention applied to its weaknesses, should provide another algorithm which can rival currently available roof top detection methods.
    Downloads: 0 This Week
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