Showing 3 open source projects for "cpu benchmark linux"

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    ncnn

    ncnn

    High-performance neural network inference framework for mobile

    ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including...
    Downloads: 38 This Week
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  • 2
    AI File Sorter

    AI File Sorter

    Local AI file organization with categorization and rename suggestions

    AI File Sorter is a cross-platform desktop application that uses AI (local LLMs run on your computer) to organize files and suggest meaningful file names based on real content, not just filenames or extensions. The app can analyze images locally and propose descriptive rename suggestions (for example, IMG_2048.jpg → clouds_over_lake.jpg). It can also analyze document text to improve categorization and renaming. Supported formats include PDF, DOCX, XLSX, PPTX, ODT, ODS, ODP, and common...
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    Downloads: 236 This Week
    Last Update:
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  • 3
    libfacedetection

    libfacedetection

    Library for face detection in images

    ...The CNN model has been converted to static variables in C source files. The source code does not depend on any other libraries. What you need is just a C++ compiler. You can compile the source code under Windows, Linux, ARM and any platform with a C++ compiler. SIMD instructions are used to speed up the detection. You can enable AVX2 if you use Intel CPU or NEON for ARM. The model file has also been provided in directory ./models/. The file examples/detect-image.cpp and examples/detect-camera.cpp show how to use the library. The library was trained by libfacedetection.train. ...
    Downloads: 0 This Week
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