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NVR with realtime local object detection for IP cameras
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Add log message when discarding recording segments in cache (#3439) 
* Add log message when discarding recording segments in cache

Currently Frigate silently discards recording segments in cache if there's more than "keep_count" for a camera, which can happen on high load/busy/slow systems.
This results in recording segments being lost with no apparent cause in the logs (even when set to debug).
This PR adds a warning log entry when discarding segments, in the same way as discarding corrupted segments

* Add explanatory warning and properly format cache_path warning

* lint fixes

Co-authored-by: Blake Blackshear <blakeb@blakeshome.com>
2022-07-19 07:24:44 -05:00
.devcontainer include prettier in extensions 2022-04-10 09:11:16 -05:00
.github Http tests (#3350) 2022-06-30 07:53:46 -05:00
docker try ffmpeg5 again 2022-07-05 11:54:21 -05:00
docs Update hardware_acceleration.md 2022-07-19 07:06:40 -05:00
frigate Add log message when discarding recording segments in cache (#3439) 2022-07-19 07:24:44 -05:00
migrations optimize query performance 2022-05-12 06:29:43 -05:00
web improvement: better play/pause 2022-07-19 07:04:33 -05:00
.dockerignore swr events refactor 2022-03-11 07:49:06 -06:00
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.pylintrc use fstr log style 2021-02-25 07:01:59 -06:00
benchmark.py support multiple coral devices (fixes #100) 2020-10-18 13:47:13 -05:00
docker-compose.yml add additional render group 2022-07-19 06:44:11 -05:00
labelmap.txt refactor and reduce false positives 2020-09-17 07:37:27 -05:00
LICENSE switch to MIT license 2020-07-26 12:07:47 -05:00
Makefile Multi arch image with nvidia decode support 2022-04-24 13:52:12 -05:00
process_clip.py Ability to enable / disable motion detection via MQTT (#3117) 2022-04-26 07:29:28 -05:00
README.md update docs url 2021-09-26 16:43:26 -05:00
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README.md

logo

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