Showing 4 open source projects for "small linux os"

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  • 1
    [OFFICIAL] tinyfiledialogs C C++ v3.21.3

    [OFFICIAL] tinyfiledialogs C C++ v3.21.3

    inputbox password WIN OSX GTK QT Console VCPKG C# Lua R Fortran Pascal

    one C/C++ file & header ==> 8 functions: - beep - tray notify popup - message & question - input & password - save file - open file(s) - select folder - color picker complements OpenGL Vulkan GLFW GLUT GLUI VTK SFML TGUI SDL Ogre Unity3d ION OpenCV CeGui MathGL GLM CPW GLOW Open3D ImGui MyGui GLT NGL STB Nuklear Fenster MicroUi & head-less programs NO INIT NO MAIN LOOP NO LINKING NO INCLUDE win (XP to 11) ASCII MBCS UTF-8 UTF-16 (wchar_t) - native dialogs osx/unix...
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    Downloads: 74 This Week
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  • 2
    ResNeXt

    ResNeXt

    Implementation of a classification framework

    ResNeXt is a deep neural network architecture for image classification built on the idea of aggregated residual transformations. Instead of simply increasing depth or width, ResNeXt introduces a new dimension called cardinality, which refers to the number of parallel transformation paths (i.e. the number of “branches”) that are aggregated together. Each branch is a small transformation (e.g. bottleneck block) and their outputs are summed—this enables richer representation without excessive...
    Downloads: 0 This Week
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  • 3
    json.lua

    json.lua

    A lightweight JSON library for Lua

    json.lua is a lightweight JSON library for Lua that provides straightforward encoding and decoding without requiring a large external package. It is designed to be dropped into an existing project as a single Lua file, then required directly from application code. The library exposes a simple API for turning Lua values into JSON strings and parsing JSON strings back into Lua values. Its small size makes it practical for games, plugins, scripts, embedded Lua environments, and projects where...
    Downloads: 1 This Week
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  • 4

    neuranep

    Neural Network Engineering Platform

    A parallel-programming framework for concurrently running large numbers of small autonomous jobs, or microthreads, across multiple cores in a CPU or CPUs in a cluster. NeuraNEP emulates a distributed processing environment capable of handling millions of microthreads in parallel, for example running neural networks with millions of spiking cells. Microthreads are general processing elements that can also represent non-neural elements, such as cell populations, extracellular space, emulating...
    Downloads: 0 This Week
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