Showing 5 open source projects for "cpu memory usage"

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  • 1
    whisper.cpp

    whisper.cpp

    Port of OpenAI's Whisper model in C/C++

    whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples....
    Downloads: 473 This Week
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  • 2
    VulkanSceneGraph

    VulkanSceneGraph

    Vulkan & C++17 based Scene Graph Project

    VulkanSceneGraph (VSG), is a modern, cross-platform, high-performance scene graph library built upon Vulkan graphics/compute API. The software is written in C++17 and follows the CppCoreGuidelines and FOSS Best Practices. The source code is published under the MIT License, with the exception of vulkan.h, used for Vulkan extensions, which is under Apache License 2.0. This repository contains C++ headers and source and CMake build scripts to build the libvsg library. Additional support...
    Downloads: 2 This Week
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  • 3
    OnnxStream

    OnnxStream

    Lightweight inference library for ONNX files, written in C++

    ...Generally, major machine learning frameworks and libraries are focused on minimizing inference latency and/or maximizing throughput, all of which at the cost of RAM usage. So I decided to write a super small and hackable inference library specifically focused on minimizing memory consumption: OnnxStream. OnnxStream is based on the idea of decoupling the inference engine from the component responsible for providing the model weights, which is a class derived from WeightsProvider. A WeightsProvider specialization can implement any type of loading, caching, and prefetching of the model parameters.
    Downloads: 8 This Week
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  • 4
    LaMa

    LaMa

    LaMa - A Localization and Mapping library

    ...It includes a framework for 3D volumetric grids (for mapping), a localization algorithm based on scan matching, and two SLAM solutions (an Online SLAM and a Particle Filter SLAM). The main feature is efficiency. Low computational effort and low memory usage whenever possible. The minimum viable computer to run our localization and SLAM solutions is a Raspberry Pi 3 Model B+. We provide a fast scan-matching approach to mobile robot localization supported by a continuous likelihood field. It can be used to provide accurate localization for robots equipped with a laser and a not-so-good odometry. ...
    Downloads: 0 This Week
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  • 5
    hyperion-project

    hyperion-project

    An open source ambient light for many systems

    Hyperion is an open source ambient light implementation controlled primarily by an Raspberry Pi. The main features of Hyperion are: 1. Low CPU load. For a led string of 50 leds the CPU usage will typically be below 2% on a non-overclocked Pi. 2. Json interface which allows easy integration into scripts. 3. A command line utility allows easy testing and configuration of the color transforms (Transformation settings are not preserved over a restart at the moment...). 4. ...
    Downloads: 51 This Week
    Last Update:
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