# 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
# Supports JetPack 7.0 and DGX OS for YOLO on Jetson AGX Thor (T5000) and DGX Spark

# Start FROM PyTorch image nvcr.io/nvidia/pytorch:25.10-py3
FROM nvcr.io/nvidia/pytorch:25.10-py3

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1 \
    PIP_NO_CACHE_DIR=1 \
    PIP_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/

# Install linux packages
RUN apt-get update && \
    apt-get install -y --no-install-recommends libgl1 && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Create working directory
WORKDIR /ultralytics

# Copy contents and configure git
COPY . .
RUN sed -i '/^\[http "https:\/\/github\.com\/"\]/,+1d' .git/config && \
    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 (uv already installed in base image)
RUN uv pip install --system \
    https://github.com/ultralytics/assets/releases/download/v0.0.0/onnxruntime_gpu-1.24.0-cp312-cp312-linux_aarch64.whl --break-system-packages && \
    # Reinstall torch and torchvision to ensure CUDA 13.0 compatibility
    uv pip install --system --force-reinstall torch torchvision --index-url https://download.pytorch.org/whl/cu130 --break-system-packages && \
    uv pip install --system -e ".[export]" --break-system-packages && \
    # 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): docker run -it --ipc=host --runtime=nvidia $t
# Example (run-with-volume): docker run -it --ipc=host --runtime=nvidia -v "$PWD/shared/datasets:/datasets" $t && docker push $tnew