# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

# Builds ultralytics/ultralytics:latest-export image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Export-optimized derivative of ultralytics/ultralytics:latest for testing and benchmarks
# Includes all export format dependencies and pre-installed export packages

FROM ultralytics/ultralytics:latest

# Install export dependencies and run exports to AutoInstall packages
# Numpy 1.26.4 required for TensorFlow export compatibility
# Note tensorrt installed on-demand as depends on runtime environment CUDA version
RUN uv pip install --system -e ".[export]" "onnxruntime-gpu" paddlepaddle x2paddle numpy==1.26.4 && \
    # Run exports to AutoInstall packages \
    yolo export model=tmp/yolo26n.pt format=edgetpu imgsz=32 && \
    yolo export model=tmp/yolo26n.pt format=ncnn imgsz=32 && \
    # Remove temporary files \
    rm -rf tmp /root/.config/Ultralytics/persistent_cache.json

# Usage --------------------------------------------------------------------------------------------------------------

# Production builds: https://github.com/ultralytics/ultralytics/blob/main/.github/workflows/docker.yml
# Example (build): t=ultralytics/ultralytics:latest-export && docker build -f docker/Dockerfile-export -t $t .
# Example (push): docker push $t
# Example (pull): t=ultralytics/ultralytics:latest-export && docker pull $t
# Example (run): docker run -it --ipc=host --runtime=nvidia --gpus all $t
# Example (run-with-volume): docker run -it --ipc=host --runtime=nvidia --gpus all -v "$PWD/shared/datasets:/datasets" $t