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NVR with realtime local object detection for IP cameras
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Nate Meyer e5fe323aca
Add OpenVino Detector (#3768) 
* Initial work for adding OpenVino detector.  Not functional

* Load model and submit for inference.

Sucessfully load model and initialize OpenVino engine with either CPU or GPU as device.
Does not parse results for objects.

* Detection working with ssdlite_mobilenetv2 FP16 model

* Add OpenVIno support and model to docker image

* Add documentation for OpenVino detector configuration

* Adds support for ARM32/ARM64 and the Myriad X hardware

-  Use custom-built openvino wheel for all platforms
-  Add libusb build without udev for NCS2 support

* Add documentation around Intel CPU requirements and NCS2 setup

* Print all available output tensors

* Update documentation for config parameters
2022-12-03 10:19:34 -06:00
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config Improve the devcontainer experience (#3492) 2022-11-20 07:34:12 -06:00
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docs Add OpenVino Detector (#3768) 2022-12-03 10:19:34 -06:00
frigate Add OpenVino Detector (#3768) 2022-12-03 10:19:34 -06:00
migrations Limit recording retention to available storage (#3942) 2022-10-09 06:28:26 -05:00
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.dockerignore Improve the devcontainer experience (#3492) 2022-11-20 07:34:12 -06:00
.gitignore Set User Agent for FFmpeg calls (#4555) 2022-11-30 16:53:45 -06:00
.pylintrc use fstr log style 2021-02-25 07:01:59 -06:00
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LICENSE switch to MIT license 2020-07-26 12:07:47 -05:00
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README.md

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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.

  • Tight integration with Home Assistant via a custom component
  • Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
  • Leverages multiprocessing heavily with an emphasis on realtime over processing every frame
  • Uses a very low overhead motion detection to determine where to run object detection
  • Object detection with TensorFlow runs in separate processes for maximum FPS
  • Communicates over MQTT for easy integration into other systems
  • Records video with retention settings based on detected objects
  • 24/7 recording
  • Re-streaming via RTMP to reduce the number of connections to your camera

Documentation

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

Donations

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

Screenshots

Integration into Home Assistant

Also comes with a builtin UI:

Events