Showing 7 open source projects for "android windows"

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  • 1
    OpenCV

    OpenCV

    Open Source Computer Vision Library

    OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations.
    Downloads: 37 This Week
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  • 2
    LiteRT-LM

    LiteRT-LM

    LiteRT-LM is Google's production-ready inference framework

    LiteRT-LM is Google’s open-source inference framework for deploying large language models on edge devices. It is built for production-oriented local LLM execution across Android, iOS, desktop, web, embedded, and IoT environments. The framework focuses on performance, hardware acceleration, and efficient model serving close to the user instead of relying only on remote cloud inference. It supports CPU execution across major platforms and adds GPU or NPU acceleration where available. LiteRT-LM...
    Downloads: 2 This Week
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  • 3
    MegEngine

    MegEngine

    Easy-to-use deep learning framework with 3 key features

    ...Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference.
    Downloads: 48 This Week
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  • 4
    MACE

    MACE

    Deep learning inference framework optimized for mobile platforms

    Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes obligatory when running a model. ...
    Downloads: 0 This Week
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  • 5
    TNN

    TNN

    Uniform deep learning inference framework for mobile

    TNN, a high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's...
    Downloads: 0 This Week
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  • 6
    nunn

    nunn

    This is an implementation of a machine learning library in C++17

    nunn is a collection of ML algorithms and related examples written in modern C++17.
    Downloads: 0 This Week
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  • 7
    libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
    Downloads: 0 This Week
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