4 projects for "linux ai" with 2 filters applied:

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  • 1
    Frigate

    Frigate

    NVR with realtime local object detection for IP cameras

    Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.
    Downloads: 40 This Week
    Last Update:
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  • 2
    MoveNet

    MoveNet

    A CNN model that predicts human joints from RGB images of a person

    The MoveNet model is an efficient, real-time human pose estimation system designed for detecting and tracking keypoints of human bodies. It utilizes deep learning to accurately locate 17 key points across the body, providing precise tracking even with fast movements. Optimized for mobile and embedded devices, MoveNet can be integrated into applications for fitness tracking, augmented reality, and interactive systems.
    Downloads: 4 This Week
    Last Update:
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  • 3
    MediaPipe Face Detection

    MediaPipe Face Detection

    Detect faces in an image

    The MediaPipe Face Detection model is a high-performance, real-time face detection solution that uses machine learning to identify faces in images and video streams. It is optimized for mobile and embedded platforms, offering fast and accurate face detection while maintaining a small memory footprint. This model supports multiple face detections and is highly efficient, making it suitable for a variety of applications such as augmented reality, user authentication, and facial expression analysis.
    Downloads: 5 This Week
    Last Update:
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  • 4
    Blazeface

    Blazeface

    Blazeface is a lightweight model that detects faces in images

    Blazeface is a lightweight, high-performance face detection model designed for mobile and embedded devices, developed by TensorFlow. It is optimized for real-time face detection tasks and runs efficiently on mobile CPUs, ensuring minimal latency and power consumption. Blazeface is based on a fast architecture and uses deep learning techniques to detect faces with high accuracy, even in challenging conditions. It supports multiple face detection in varying lighting and poses, and is designed...
    Downloads: 6 This Week
    Last Update:
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