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deviant77 ed1897db71 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

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include prettier in extensions

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Http tests (#3350 )

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try ffmpeg5 again

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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

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improvement: better play/pause

2022-07-19 07:04:33 -05:00

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swr events refactor

2022-03-11 07:49:06 -06:00

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feat: Timeline UI (#2830 )

2022-02-27 08:04:12 -06:00

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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

requirements-dev.txt

Use requirement file for pip installs (#3090 )

2022-04-12 07:21:21 -05:00

requirements-wheels.txt

switch back to upgraded numpy

2022-07-04 16:51:48 -05:00

requirements.txt

Use requirement file for pip installs (#3090 )

2022-04-12 07:21:21 -05:00

README.md

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