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Code Issues Projects Releases Wiki Activity

Miscellaneous Fixes (#20841)

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* 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>
This commit is contained in:
Josh Hawkins
2025-11-08 06:44:30 -06:00
committed by GitHub
parent ef19332fe5
commit 01452e4c51
15 changed files with 232 additions and 132 deletions
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4
docs/docs/configuration/hardware_acceleration_enrichments.md
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@@ -5,7 +5,7 @@ title: Enrichments
# Enrichments
Some of Frigate's enrichments can use a discrete GPU / NPU for accelerated processing.
Some of Frigate's enrichments can use a discrete GPU or integrated GPU for accelerated processing.
## Requirements
@@ -18,8 +18,10 @@ Object detection and enrichments (like Semantic Search, Face Recognition, and Li
- **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.
- **Nvidia**
- 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.

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docs/docs/configuration/object_detectors.md
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@@ -261,6 +261,8 @@ OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. It will al
:::tip
**NPU + GPU Systems:** If you have both NPU and GPU available (Intel Core Ultra processors), use NPU for object detection and GPU for enrichments (semantic search, face recognition, etc.) for best performance and compatibility.
When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be:
```yaml
@@ -283,7 +285,7 @@ detectors:
| [RF-DETR](#rf-detr) | ✅ | ✅ | Requires XE iGPU or Arc |
| [YOLO-NAS](#yolo-nas) | ✅ | ✅ | |
| [MobileNet v2](#ssdlite-mobilenet-v2) | ✅ | ✅ | Fast and lightweight model, less accurate than larger models |
| [YOLOX](#yolox) | ✅ | ? | |
| [YOLOX](#yolox) | ✅ | ? | |
| [D-FINE](#d-fine) | ❌ | ❌ | |
#### SSDLite MobileNet v2

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docs/docs/configuration/semantic_search.md
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@@ -78,7 +78,7 @@ Switching between V1 and V2 requires reindexing your embeddings. The embeddings
### GPU Acceleration
The CLIP models are downloaded in ONNX format, and the `large` model can be accelerated using GPU / NPU hardware, when available. This depends on the Docker build that is used. You can also target a specific device in a multi-GPU installation.
The CLIP models are downloaded in ONNX format, and the `large` model can be accelerated using GPU hardware, when available. This depends on the Docker build that is used. You can also target a specific device in a multi-GPU installation.
```yaml
semantic_search:
@@ -90,7 +90,7 @@ semantic_search:
:::info
If the correct build is used for your GPU / NPU and the `large` model is configured, then the GPU / NPU will be detected and used automatically.
If the correct build is used for your GPU / NPU and the `large` model is configured, then the GPU will be detected and used automatically.
Specify the `device` option to target a specific GPU in a multi-GPU system (see [onnxruntime's provider options](https://onnxruntime.ai/docs/execution-providers/)).
If you do not specify a device, the first available GPU will be used.