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

# Builds ultralytics/ultralytics:latest-nvidia-arm64 image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# NVIDIA ARM64 image for DGX Spark; PyTorch on Thor/JetPack 7.1 (bundled TensorRT 11.2 does not support JetPack).

# Start FROM PyTorch image nvcr.io/nvidia/pytorch:26.08-py3
FROM nvcr.io/nvidia/pytorch:26.08-py3

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    PIP_NO_CACHE_DIR=1 \
    PIP_BREAK_SYSTEM_PACKAGES=1 \
    UV_BREAK_SYSTEM_PACKAGES=1

# Downloads to user config dir
ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
    https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.Unicode.ttf \
    /root/.config/Ultralytics/

# Create working directory
WORKDIR /ultralytics

# Copy contents and configure dependencies
COPY . .
RUN sed -i'' -e 's/"opencv-python/"opencv-python-headless/' pyproject.toml
ADD https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26n.pt .

# Install pip packages
RUN python -m pip install --no-cache-dir uv && \
    uv pip install --system --no-cache -e ".[export]" onnxruntime-gpu && \
    # Remove extra build files
    rm -rf *.whl /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-nvidia-arm64 && docker build --platform linux/arm64 -f docker/Dockerfile-nvidia-arm64 -t $t .
# Example (push): docker push $t
# Example (pull): t=ultralytics/ultralytics:latest-nvidia-arm64 && docker pull $t
# Example (run-dgx-spark): docker run -it --ipc=host --device nvidia.com/gpu=all $t
# Example (run-dgx-spark-with-volume): docker run -it --ipc=host --device nvidia.com/gpu=all -v "$PWD/shared/datasets:/datasets" $t
# Example (run-jetson-thor): docker run -it --ipc=host --runtime=nvidia $t
# Example (run-jetson-thor-with-volume): docker run -it --ipc=host --runtime=nvidia -v "$PWD/shared/datasets:/datasets" $t
# CDI requires Docker >= 28.2.0 and nvidia-container-toolkit >= 1.18.
# Legacy --gpus all can lose GPU access after host systemd daemon reloads (nvidia-container-toolkit#48).
