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

# Builds ultralytics/ultralytics:latest-jetson-jetpack6 image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Supports JetPack6.1 for YOLO on Jetson AGX Orin, Orin NX and Orin Nano Series

# Start FROM https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-jetpack
FROM nvcr.io/nvidia/l4t-jetpack:r36.4.0

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

# Install dependencies and cleanup
ADD https://developer.download.nvidia.com/compute/cudss/0.7.1/local_installers/cudss-local-tegra-repo-ubuntu2204-0.7.1_0.7.1-1_arm64.deb .
RUN dpkg -i cudss-local-tegra-repo-ubuntu2204-0.7.1_0.7.1-1_arm64.deb && \
    cp /var/cudss-local-tegra-repo-ubuntu2204-0.7.1/cudss-*-keyring.gpg /usr/share/keyrings/ && \
    apt-get update && \
    apt-get install -y --no-install-recommends \
    git python3-pip libopenmpi-dev libopenblas-base libomp-dev cudss && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Upgrade TensorRT from 10.3.0 to 10.7.0 to fix INT8 + end2end build issues on JetPack 6
# https://github.com/ultralytics/ultralytics/issues/23841
ADD https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb .
RUN dpkg -i cuda-keyring_1.1-1_all.deb && \
    apt-get update && \
    apt-get install -y tensorrt && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/* cuda-keyring_1.1-1_all.deb

# 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 .

# Pip install onnxruntime-gpu, torch, torchvision and ultralytics, then remove build files
RUN python3 -m pip install --upgrade pip uv && \
    uv pip install --system \
    https://github.com/ultralytics/assets/releases/download/v0.0.0/onnxruntime_gpu-1.23.0-cp310-cp310-linux_aarch64.whl \
    https://github.com/ultralytics/assets/releases/download/v0.0.0/torch-2.10.0-cp310-cp310-linux_aarch64.whl \
    https://github.com/ultralytics/assets/releases/download/v0.0.0/torchvision-0.25.0-cp310-cp310-linux_aarch64.whl && \
    uv pip install --system -e ".[export]" && \
    # 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-jetson-jetpack6 && docker build --platform linux/arm64 -f docker/Dockerfile-jetson-jetpack6 -t $t .
# Example (push): docker push $t
# Example (pull): t=ultralytics/ultralytics:latest-jetson-jetpack6 && 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
