From a7b539b36d95f673bfa5a918af5f91d078b8e2e8 Mon Sep 17 00:00:00 2001 From: laviddichterman Date: Mon, 8 Sep 2025 18:35:56 -0700 Subject: [PATCH] Enhance YOLOv9 export instructions in documentation Updated YOLOv9 export command to include IMG_SIZE parameter and clarified model size options. --- docs/docs/configuration/object_detectors.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/docs/configuration/object_detectors.md b/docs/docs/configuration/object_detectors.md index b4c5604d8..44071c580 100644 --- a/docs/docs/configuration/object_detectors.md +++ b/docs/docs/configuration/object_detectors.md @@ -699,6 +699,7 @@ To verify that the integration is working correctly, start Frigate and observe t # Community Supported Detectors ## NVidia TensorRT Detector + Nvidia Jetson devices may be used for object detection using the TensorRT libraries. Due to the size of the additional libraries, this detector is only provided in images with the `-tensorrt-jp6` tag suffix, e.g. `ghcr.io/blakeblackshear/frigate:stable-tensorrt-jp6`. This detector is designed to work with Yolo models for object detection. ### Generate Models @@ -716,7 +717,6 @@ If your GPU does not support FP16 operations, you can pass the environment varia Specific models can be selected by passing an environment variable to the `docker run` command or in your `docker-compose.yml` file. Use the form `-e YOLO_MODELS=yolov4-416,yolov4-tiny-416` to select one or more model names. The models available are shown below.
- Available Models ``` yolov3-288 @@ -1030,10 +1030,10 @@ python3 yolo_to_onnx.py -m yolov7-320 #### YOLOv9 -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` in the first line to the [model size](https://github.com/WongKinYiu/yolov9#performance) you would like to convert (available sizes are `t`, `s`, `m`, `c`, and `e`). +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`). ```sh -docker build . --build-arg MODEL_SIZE=t --build-arg IMG_SIZE=640 --output . -f- <<'EOF' +docker build . --build-arg MODEL_SIZE=t --build-arg IMG_SIZE=320 --output . -f- <<'EOF' FROM python:3.11 AS build RUN apt-get update && apt-get install --no-install-recommends -y libgl1 && rm -rf /var/lib/apt/lists/* COPY --from=ghcr.io/astral-sh/uv:0.8.0 /uv /bin/