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Fixes (#18500)

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* fix i18n keys

* hide disable from context menu for viewers

* Fix auto live check for default dashboard and camera groups

Disabling the Automatic Live View switch in Settings should prevent streaming from occurring. Overriding any settings in a camera group will override the global setting. The check here incorrectly always returned false instead of undefined.

* clarify hardware accelerated enrichments

* clarify

* add note about detect stream to face rec docs

* add note about low end Dahuas for autotracking

* Catch invalid face box / image

* Video tab tweaks

With the changes in https://github.com/blakeblackshear/frigate/pull/18220, the video tab in the Tracked Object Details pane now correctly trims the in-browser HLS video. Because of keyframes and record/detect stream differences, we can manually subtract a couple of seconds from the event start_time to ensure the first few frames aren't cut off from the video

* Clarify

* Don't use Migraphx by default

* Provide better support for running embeddings on GPU

* correctly join cameras

* Adjust blur confidence reduction

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Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
This commit is contained in:
Josh Hawkins
2025-06-03 06:33:32 -06:00
committed by GitHub
co-authored by Nicolas Mowen
parent af5a9e7634
commit dba9206898
15 changed files with 96 additions and 46 deletions
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docs/docs/configuration/hardware_acceleration_enrichments.md
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@@ -23,7 +23,7 @@ Object detection and enrichments (like Semantic Search, Face Recognition, and Li
- Nvidia GPUs will automatically be detected and used for enrichments in the `-tensorrt` Frigate image.
- Jetson devices will automatically be detected and used for enrichments in the `-tensorrt-jp6` Frigate image.
Utilizing a GPU for enrichments does not require you to use the same GPU for object detection. For example, you can run the `tensorrt` Docker image for enrichments and still use other dedicated hardware for object detection.
Utilizing a GPU for enrichments does not require you to use the same GPU for object detection. For example, you can run the `tensorrt` Docker image for enrichments and still use other dedicated hardware like a Coral or Hailo for object detection. However, one combination that is not supported is TensorRT for object detection and OpenVINO for enrichments.
:::note