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  • 1
    dlib C++ Library
    Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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    Downloads: 67 This Week
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  • 2

    avio

    Python version of ffplay with built-in AI

    See the Files tab above for installation instructions
    Downloads: 8 This Week
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  • 3
    Flashlight library

    Flashlight library

    A C++ standalone library for machine learning

    ...Each component can be incrementally built by specifying the correct build options. Flashlight is most-easily built and installed with vcpkg. Both the CUDA and CPU backends are supported with vcpkg. For either backend, first, install Intel MKL. Flashlight app binaries are also built for the selected features and are installed into the vcpkg install tree's tools directory.
    Downloads: 1 This Week
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  • 4
    YOLO ROS

    YOLO ROS

    YOLO ROS: Real-Time Object Detection for ROS

    ...Darknet on the CPU is fast (approximately 1.5 seconds on an Intel Core i7-6700HQ CPU @ 2.60GHz × 8) but it's like 500 times faster on GPU! You'll have to have an Nvidia GPU and you'll have to install CUDA. The CMakeLists.txt file automatically detects if you have CUDA installed or not. CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia.
    Downloads: 0 This Week
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    Enterprise-grade ITSM, for every business

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  • 5
    Turi Create

    Turi Create

    Simplifies the development of custom machine learning models

    ...Turi Create supports macOS 10.12+, Linux (with glibc 2.10+), Windows 10 (via WSL). Turi Create requires Python 2.7, 3.5, 3.6, 3.7, 3.8. Also, x86_64 architecture, and at least 4 GB of RAM. We recommend using virtualenv to use, install, or build Turi Create. The package User Guide and API Docs contain more details on how to use Turi Create. If you want to build Turi Create from source, see BUILD.md. Turi Create does not require a GPU, but certain models can be accelerated 9-13x by utilizing a GPU.
    Downloads: 0 This Week
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  • 6
    ChainerCV

    ChainerCV

    ChainerCV: a Library for Deep Learning in Computer Vision

    ChainerCV is a collection of tools to train and run neural networks for computer vision tasks using Chainer. In ChainerCV, we define the object detection task as a problem of, given an image, bounding box-based localization and categorization of objects. Bounding boxes in an image are represented as a two-dimensional array of shape (R,4), where R is the number of bounding boxes and the second axis corresponds to the coordinates of bounding boxes. ChainerCV supports dataset loaders, which can...
    Downloads: 0 This Week
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