Showing 3 open source projects for "project tracker"

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  • 1
    firerpa LAMDA

    firerpa LAMDA

    The most powerful Android RPA agent framework

    lamda is an Android RPA agent framework that provides visual remote desktop control and automation at scale, geared toward testing, automation validation, and device management. It exposes a clean UI to monitor and interact with connected devices and includes tooling to script actions reliably across apps and OS versions. The project emphasizes low-friction setup and powerful control primitives so teams can move from interactive validation to repeatable automation. A public wiki, releases, and issue tracker show active development across areas like connectivity, instrumentation compatibility, and robustness under detection. Together with companion projects (e.g., a device hub), lamda is positioned as a next-generation mobile automation stack rather than a single tool. ...
    Downloads: 3 This Week
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  • 2
    AB3DMOT

    AB3DMOT

    Official Python Implementation for "3D Multi-Object Tracking

    ...Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. This relatively simple design allows the tracker to achieve very high processing speeds while maintaining competitive tracking accuracy. The project also introduces new evaluation metrics specifically designed for assessing performance in 3D tracking benchmarks. The framework has been evaluated on widely used datasets such as KITTI and nuScenes and demonstrates strong performance compared with more complex tracking systems.
    Downloads: 0 This Week
    Last Update:
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  • 3
    DetectAndTrack

    DetectAndTrack

    The implementation of an algorithm presented in the CVPR18 paper

    ...Code and instructions are organized to replicate paper results and to serve as a starting point for researchers working on pose in video. Although the repo has been archived and is now read-only, its issue tracker and artifacts remain useful for understanding implementation details and experimental settings. The project sits alongside other Facebook Research vision efforts, offering historical context for the evolution of video pose and tracking techniques. Researchers can still study the algorithms, adapt the pipeline, or port ideas into modern frameworks.
    Downloads: 0 This Week
    Last Update:
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