Showing 5 open source projects for "gpu max performance"

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  • 1
    Starling Framework

    Starling Framework

    2D GPU-accelerated framework for ActionScript developers

    Starling is an open-source 2D framework for ActionScript developers that leverages GPU acceleration via Adobe's Stage3D API to create smooth, high-performance games and applications across desktop and mobile platforms. It mimics the traditional Flash display list while dramatically improving performance, making it a popular choice for Flash developers transitioning into more efficient, hardware-accelerated environments.
    Downloads: 0 This Week
    Last Update:
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  • 2
    MediaPipe

    MediaPipe

    Cross-platform, customizable ML solutions for live and streaming media

    ...It employs machine learning (ML) to infer the 3D surface geometry, requiring only a single camera input without the need for a dedicated depth sensor. Utilizing lightweight model architectures together with GPU acceleration throughout the pipeline, the solution delivers real-time performance-critical for live experiences. Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control. For example, it can form the basis for yoga, dance, and fitness applications. ...
    Downloads: 57 This Week
    Last Update:
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  • 3
    MNN

    MNN

    MNN is a blazing fast, lightweight deep learning framework

    ...Android platform, core so size is about 400KB, OpenCL so is about 400KB, Vulkan so is about 400KB. Supports hybrid computing on multiple devices. Currently supports CPU and GPU.
    Downloads: 9 This Week
    Last Update:
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  • 4
    QtAV

    QtAV

    A multimedia framework based on Qt and FFmpeg

    QtAV is a cross-platform and high performance multimedia playback framework based on Qt and FFmpeg. Features: timeline preview, gpu decoding etc
    Downloads: 24 This Week
    Last Update:
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  • 5
    pipeless

    pipeless

    A computer vision framework to create and deploy apps in minutes

    ...You can easily use industry-standard models, such as YOLO, or load your custom model in one of the supported inference runtimes. Pipeless ships some of the most popular inference runtimes, such as the ONNX Runtime, allowing you to run inference with high performance on CPU or GPU out-of-the-box. You can deploy your Pipeless application with a single command to edge and IoT devices or the cloud.
    Downloads: 2 This Week
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