Showing 4 open source projects for "remote support software"

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    Intel RealSense

    Intel RealSense

    Intel® RealSense SDK

    Intel® RealSense™ SDK 2.0 is a cross-platform library for Intel® RealSense™ depth cameras. The SDK allows depth and color streaming and provides intrinsic and extrinsic calibration information. The library also offers synthetic streams (point cloud, depth aligned to color and vise-versa), and built-in support for recording and playback of streaming sessions. Intel has EOLed the LiDAR, Facial Authentication, and Tracking product lines. These products have been discontinued and will no longer...
    Downloads: 63 This Week
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  • 2
    SAGA GIS
    SAGA - System for Automated Geoscientific Analyses - is a Geographic Information System (GIS) software with immense capabilities for geodata processing and analysis. SAGA is programmed in the object oriented C++ language and supports the implementation of new functions with a very effective Application Programming Interface (API). Functions are organised as modules in framework independent Module Libraries and can be accessed via SAGA’s Graphical User Interface (GUI) or various scripting...
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    Downloads: 9,260 This Week
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  • 3
    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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  • 4
    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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