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Revamp YOLOv9 export guide

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Felipe Santos 2025-07-20 02:49:09 -03:00 committed by GitHub
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docs/docs/configuration/object_detectors.md
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@ -1032,22 +1032,21 @@ python3 yolo_to_onnx.py -m yolov7-320
#### YOLOv9 #### YOLOv9
YOLOv9 models can be exported using the below code YOLOv9 model can be exported as ONNX using the below command:
```sh ```sh
git clone https://github.com/WongKinYiu/yolov9 docker build . --output . -f- <<'EOF'
cd yolov9 FROM python:3.11 AS build
RUN apt-get update && apt-get install --no-install-recommends -y libgl1 && rm -rf /var/lib/apt/lists/*
# setup the virtual environment so installation doesn't affect main system COPY --from=ghcr.io/astral-sh/uv:0.8.0 /uv /bin/
# NOTE: Virtual environment must be using Python 3.11 or older. WORKDIR /yolov9
python3 -m venv ./ ADD https://github.com/WongKinYiu/yolov9.git .
bin/pip install -r requirements.txt RUN uv pip install --system -r requirements.txt
bin/pip install onnx onnxruntime onnx-simplifier>=0.4.1 RUN uv pip install --system onnx onnxruntime onnx-simplifier>=0.4.1
ADD https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-t-converted.pt yolov9-t.pt
# download the weights RUN sed -i "s/ckpt = torch.load(attempt_download(w), map_location='cpu')/ckpt = torch.load(attempt_download(w), map_location='cpu', weights_only=False)/g" models/experimental.py
wget -O yolov9-t.pt "https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-t-converted.pt" # download the weights RUN python3 export.py --weights ./yolov9-t.pt --imgsz 320 --simplify --include onnx
FROM scratch
# prepare and run export script COPY --from=build /yolov9/yolov9-t.onnx /
sed -i "s/ckpt = torch.load(attempt_download(w), map_location='cpu')/ckpt = torch.load(attempt_download(w), map_location='cpu', weights_only=False)/g" ./models/experimental.py EOF
bin/python3 export.py --weights ./yolov9-t.pt --imgsz 320 --simplify --include onnx
``` ```