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Fixes (#18245)

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* Only check if an object is stationary to avoid mqtt snapshot

* docs heading tweak

* Add more API descriptions

* Add missing lib for new rocm onnxruntime whl

* Update inference times to reflect better rocm performance

* Cleanup resetting tracked object activity

* remove print

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
This commit is contained in:
Nicolas Mowen
2025-05-15 16:13:18 -06:00
committed by GitHub
parent 3538a1df3d
commit f48356cbee
9 changed files with 46 additions and 35 deletions
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2
docs/docs/configuration/face_recognition.md
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@@ -172,6 +172,6 @@ Face recognition does not run on the recording stream, this would be suboptimal
By default iOS devices will use HEIC (High Efficiency Image Container) for images, but this format is not supported for uploads. Choosing `large` as the format instead of `original` will use JPG which will work correctly.
## How can I delete the face database and start over?
### How can I delete the face database and start over?
Frigate does not store anything in its database related to face recognition. You can simply delete all of your faces through the Frigate UI or remove the contents of the `/media/frigate/clips/faces` directory.

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docs/docs/frigate/hardware.md
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@@ -145,7 +145,7 @@ With the [rocm](../configuration/object_detectors.md#amdrocm-gpu-detector) detec
| Name | YOLOv9 Inference Time | YOLO-NAS Inference Time |
| --------- | --------------------- | ------------------------- |
| AMD 780M | ~ 14 ms | 320: ~ 30 ms 640: ~ 60 ms |
| AMD 780M | ~ 14 ms | 320: ~ 25 ms 640: ~ 50 ms |
| AMD 8700G | | 320: ~ 20 ms 640: ~ 40 ms |
## Community Supported Detectors