01452e4c51
* show id field when editing zone * improve zone capitalization * Update NPU models and docs * fix mobilepage in tracked object details * Use thread lock for openvino to avoid concurrent requests with JinaV2 * fix hashing function to avoid collisions * remove extra flex div causing overflow * ensure header stays on top of video controls * don't smart capitalize friendly names * Fix incorrect object classification crop * don't display submit to plus if object doesn't have a snapshot * check for snapshot and clip in actions menu * frigate plus submission fix still show frigate+ section if snapshot has already been submitted and run optimistic update, local state was being overridden * Don't fail to show 0% when showing classification * Don't fail on file system error * Improve title and description for review genai * fix overflowing truncated review item description in detail stream * catch events with review items that start after the first timeline entry review items may start later than events within them, so subtract a padding from the start time in the filter so the start of events are not incorrectly filtered out of the list in the detail stream * also pad on review end_time * fix * change order of timeline zoom buttons on mobile * use grid to ensure genai title does not cause overflow * small tweaks * Cleanup --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
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| id | title |
|---|---|
| hardware_acceleration_enrichments | Enrichments |
Enrichments
Some of Frigate's enrichments can use a discrete GPU or integrated GPU for accelerated processing.
Requirements
Object detection and enrichments (like Semantic Search, Face Recognition, and License Plate Recognition) are independent features. To use a GPU / NPU for object detection, see the Object Detectors documentation. If you want to use your GPU for any supported enrichments, you must choose the appropriate Frigate Docker image for your GPU / NPU and configure the enrichment according to its specific documentation.
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AMD
- ROCm will automatically be detected and used for enrichments in the
-rocmFrigate image.
- ROCm will automatically be detected and used for enrichments in the
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Intel
- OpenVINO will automatically be detected and used for enrichments in the default Frigate image.
- Note: Intel NPUs have limited model support for enrichments. GPU is recommended for enrichments when available.
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Nvidia
- Nvidia GPUs will automatically be detected and used for enrichments in the
-tensorrtFrigate image. - Jetson devices will automatically be detected and used for enrichments in the
-tensorrt-jp6Frigate image.
- Nvidia GPUs will automatically be detected and used for enrichments in the
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RockChip
- RockChip NPU will automatically be detected and used for semantic search v1 and face recognition in the
-rkFrigate image.
- RockChip NPU will automatically be detected and used for semantic search v1 and face recognition in the
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
A Google Coral is a TPU (Tensor Processing Unit), not a dedicated GPU (Graphics Processing Unit) and therefore does not provide any kind of acceleration for Frigate's enrichments.
:::