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 05:44:30 -07:00
committed by GitHub
co-authored by Nicolas Mowen
parent ef19332fe5
commit 01452e4c51
15 changed files with 232 additions and 132 deletions
+2 -2
View File
@@ -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.