Showing 3 open source projects for "computer vision"

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    ReductStore

    ReductStore

    The fastest time series object store for Edge AI

    ...Store billions of time-stamped blobs with AI labels and access them with low latency. Outperform other databases with a customized solution for time-series object data. Capture and access blob data as time series, tailored for edge computing, computer vision, and IoT. ReductStore handles blob data without size limits; your disk capacity is the only boundary. Ensure optimal storage management with FIFO quotas, preventing disk space shortages in real-time. Manage your time-series blob data with ease: annotate, filter, and save AI labels or meta-data. Integrate and communicate with ReductStore using our feature-rich and secure API.
    Downloads: 8 This Week
    Last Update:
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  • 2
    pipeless

    pipeless

    A computer vision framework to create and deploy apps in minutes

    Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision.
    Downloads: 23 This Week
    Last Update:
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  • 3

    Savant

    Python Computer Vision & Video Analytics Framework With Batteries Incl

    Savant is an open-source, high-level framework for building real-time, streaming, highly efficient multimedia AI applications on the Nvidia stack. It helps to develop dynamic, fault-tolerant inference pipelines that utilize the best Nvidia approaches for data center and edge accelerators. Savant is built on DeepStream and provides a high-level abstraction layer for building inference pipelines. It is designed to be easy to use, flexible, and scalable. It is a great choice for building...
    Downloads: 0 This Week
    Last Update:
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