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Fixes (#18379)

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* Don't return weighted name if it has the same number of results

* Remove link to incorrect format yolov9 models

* Fix command list from appearing when other inputs are focused

the description box in the tracked object details pane was causing the command input list to show when focused.

* clarify face docs

* Add note about python yolov9 export

* Check if hailort thread is still alive when timeout error is run into

* Reduce inference timeout

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
This commit is contained in:
Nicolas Mowen
2025-05-27 09:25:34 -06:00
committed by GitHub
parent 63f9689b0e
commit cbdac9ece5
5 changed files with 36 additions and 8 deletions
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4
docs/docs/configuration/face_recognition.md
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@@ -74,8 +74,10 @@ Fine-tune face recognition with these optional parameters at the global level of
## Usage
Follow these steps to begin:
1. **Enable face recognition** in your configuration file and restart Frigate.
2. **Upload your face** using the **Add Face** button's wizard in the Face Library section of the Frigate UI.
2. **Upload one face** using the **Add Face** button's wizard in the Face Library section of the Frigate UI. Read below for the best practices on expanding your training set.
3. When Frigate detects and attempts to recognize a face, it will appear in the **Train** tab of the Face Library, along with its associated recognition confidence.
4. From the **Train** tab, you can **assign the face** to a new or existing person to improve recognition accuracy for the future.

3
docs/docs/configuration/object_detectors.md
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@@ -1053,13 +1053,14 @@ python3 yolo_to_onnx.py -m yolov7-320
#### YOLOv9
YOLOv9 models can be exported using the below code or they [can be downloaded from hugging face](https://huggingface.co/Xenova/yolov9-onnx/tree/main)
YOLOv9 models can be exported using the below code
```sh
git clone https://github.com/WongKinYiu/yolov9
cd yolov9
# setup the virtual environment so installation doesn't affect main system
# NOTE: Virtual environment must be using Python 3.11 or older.
python3 -m venv ./
bin/pip install -r requirements.txt
bin/pip install onnx onnxruntime onnx-simplifier>=0.4.1