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updates for yolov9 coral support (#22136)

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Blake Blackshear
2026-02-26 20:36:26 -06:00
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commit 7df3622243
4 changed files with 27 additions and 15 deletions
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docs/docs/configuration/object_detectors.md
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@@ -157,7 +157,13 @@ A TensorFlow Lite model is provided in the container at `/edgetpu_model.tflite`
#### YOLOv9
YOLOv9 models that are compiled for TensorFlow Lite and properly quantized are supported, but not included by default. [Download the model](https://github.com/dbro/frigate-detector-edgetpu-yolo9/releases/download/v1.0/yolov9-s-relu6-best_320_int8_edgetpu.tflite), bind mount the file into the container, and provide the path with `model.path`. Note that the linked model requires a 17-label [labelmap file](https://raw.githubusercontent.com/dbro/frigate-detector-edgetpu-yolo9/refs/heads/main/labels-coco17.txt) that includes only 17 COCO classes.
YOLOv9 models that are compiled for TensorFlow Lite and properly quantized are supported, but not included by default. [Instructions](#yolov9-for-google-coral-support) for downloading a model with support for the Google Coral.
:::tip
**Frigate+ Users:** Follow the [instructions](../integrations/plus#use-models) to set a model ID in your config file.
:::
<details>
<summary>YOLOv9 Setup & Config</summary>
@@ -1554,7 +1560,11 @@ cd tensorrt_demos/yolo
python3 yolo_to_onnx.py -m yolov7-320
```
#### YOLOv9
#### YOLOv9 for Google Coral Support
[Download the model](https://github.com/dbro/frigate-detector-edgetpu-yolo9/releases/download/v1.0/yolov9-s-relu6-best_320_int8_edgetpu.tflite), bind mount the file into the container, and provide the path with `model.path`. Note that the linked model requires a 17-label [labelmap file](https://raw.githubusercontent.com/dbro/frigate-detector-edgetpu-yolo9/refs/heads/main/labels-coco17.txt) that includes only 17 COCO classes.
#### YOLOv9 for other detectors
YOLOv9 model can be exported as ONNX using the command below. You can copy and paste the whole thing to your terminal and execute, altering `MODEL_SIZE=t` and `IMG_SIZE=320` in the first line to the [model size](https://github.com/WongKinYiu/yolov9#performance) you would like to convert (available model sizes are `t`, `s`, `m`, `c`, and `e`, common image sizes are `320` and `640`).