GStars
    blakeblackshear

    blakeblackshear/frigate

    NVR with realtime local object detection for IP cameras

    ai
    computer-vision
    machine-learning
    camera
    google-coral
    home-assistant
    home-automation
    homeautomation
    Python
    MIT
    37.3K stars
    3.8K forks
    263 GitHub watchers
    Updated Nov 8, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    3 releases in the last 90 days, the latest 24 days ago, with 420 contributors on GitHub.

    Peaked at #96 in the weekly ranking the week of Jan 11, its best in the past year.

    Use Cases & Benefits

    • Provides a local network video recorder with realtime AI-based object detection for IP cameras.
    • Delivers efficient, low-latency object detection using AI accelerators and multiprocessing to minimize resource use.
    • Use for integrating smart video surveillance with Home Assistant for automated home security.
    • Use for continuous 24/7 recording with intelligent video retention triggered by detected objects.
    • Use for low-latency live video streaming and multi-camera management with built-in zone and mask editing.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    MIT

    Permissive: commercial use, modification and redistribution are allowed with attribution.

    Community files

    • README: present
    • Contributing guide: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    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 GPU or AI accelerator such as a Google Coral or Hailo is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead.

    View the documentation at https://docs.frigate.video

    If you would like to make a donation to support development, please use Github Sponsors.

    Excerpt from the blakeblackshear/frigate README on GitHub (MIT license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Aug 14: +13Aug 15: +33Aug 16: +12Sep 15: +30

    +2,280 stars over 88 days across 11 snapshot days; best day +33 on Aug 15.

    Forks

    3.8K+318

    Open issues

    85-79

    Compared with peers in AI

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth

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