frigate/Dockerfile.gpu

FROM frigate AS base

#
# CUDA 10.2 base
#
# https://gitlab.com/nvidia/container-images/cuda/blob/master/dist/ubuntu18.04/10.2/base/Dockerfile
#
RUN apt-get update && apt-get install -y --no-install-recommends \
gnupg2 curl ca-certificates && \
    curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub | apt-key add - && \
    echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/cuda.list && \
    echo "deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list && \
    apt-get purge --autoremove -y curl && \
rm -rf /var/lib/apt/lists/*

ENV CUDA_VERSION 10.2.89
LABEL com.nvidia.cuda.version="${CUDA_VERSION}"

ENV CUDA_PKG_VERSION 10-2=$CUDA_VERSION-1

# For libraries in the cuda-compat-* package: https://docs.nvidia.com/cuda/eula/index.html#attachment-a
RUN apt-get update && apt-get install -y --no-install-recommends \
        cuda-cudart-$CUDA_PKG_VERSION \
cuda-compat-10-2 && \
ln -s cuda-10.2 /usr/local/cuda && \
    rm -rf /var/lib/apt/lists/*

# Required for nvidia-docker v1
RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
    echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf

ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64

# nvidia-container-runtime
ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
ENV NVIDIA_REQUIRE_CUDA "cuda>=10.2 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=396,driver<397 brand=tesla,driver>=410,driver<411 brand=tesla,driver>=418,driver<419"

#
# CUDA 10.2 runtime
#
# https://gitlab.com/nvidia/container-images/cuda/blob/master/dist/ubuntu18.04/10.2/runtime/Dockerfile
#
ENV NCCL_VERSION 2.5.6

RUN apt-get update && apt-get install -y --no-install-recommends \
    cuda-libraries-$CUDA_PKG_VERSION \
cuda-nvtx-$CUDA_PKG_VERSION \
libcublas10=10.2.2.89-1 \
libnccl2=$NCCL_VERSION-1+cuda10.2 && \
    apt-mark hold libnccl2 && \
    rm -rf /var/lib/apt/lists/*

#
# cuDNN 7.6.5.32 runtime
#
# https://gitlab.com/nvidia/container-images/cuda/blob/master/dist/ubuntu18.04/10.2/runtime/cudnn7/Dockerfile
#
ENV CUDNN_VERSION 7.6.5.32
LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"

RUN apt-get update && apt-get install -y --no-install-recommends \
    libcudnn7=$CUDNN_VERSION-1+cuda10.2 \
&& \
    apt-mark hold libcudnn7 && \
    rm -rf /var/lib/apt/lists/*

#
# TensorRT 6.0.1.8
#
# https://docs.nvidia.com/deeplearning/sdk/tensorrt-archived/tensorrt-601/tensorrt-install-guide/index.html#maclearn-net-repo-install
#
ENV TENSORRT_VERSION 6.0.1
LABEL com.nvidia.tensorrt.version="${TENSORRT_VERSION}"

RUN version=$TENSORRT_VERSION-1+cuda10.2 && \
    apt-get update && apt-get install -y --no-install-recommends \
    libnvinfer6=${version} \
    libnvonnxparsers6=${version} libnvparsers6=${version} \
    libnvinfer-plugin6=${version} \
    python3-libnvinfer=${version} \
&& \
    apt-mark hold \
    libnvinfer6 \
    libnvonnxparsers6 libnvparsers6 \
    libnvinfer-plugin6 \
    python3-libnvinfer \
&& \
    rm -rf /var/lib/apt/lists/*

#
# Use a previous stage as a new temporary stage for building libraries
#
FROM base AS builder

#
# CUDA 10.2 devel
#
# https://gitlab.com/nvidia/container-images/cuda/blob/master/dist/ubuntu18.04/10.2/devel/Dockerfile
#
RUN apt-get update && apt-get install -y --no-install-recommends \
        cuda-nvml-dev-$CUDA_PKG_VERSION \
        cuda-command-line-tools-$CUDA_PKG_VERSION \
cuda-libraries-dev-$CUDA_PKG_VERSION \
        cuda-minimal-build-$CUDA_PKG_VERSION \
        libnccl-dev=$NCCL_VERSION-1+cuda10.2 \
libcublas-dev=10.2.2.89-1 \
&& \
    rm -rf /var/lib/apt/lists/*

ENV LIBRARY_PATH /usr/local/cuda/lib64/stubs

#
# cuDNN 7.6.5.32 devel
#
# https://gitlab.com/nvidia/container-images/cuda/blob/master/dist/ubuntu18.04/10.2/devel/cudnn7/Dockerfile
#
RUN apt-get update && apt-get install -y --no-install-recommends \
    libcudnn7-dev=$CUDNN_VERSION-1+cuda10.2 \
&& \
    rm -rf /var/lib/apt/lists/*

#
# TensorRT 6.0.1.8 devel
#
# https://docs.nvidia.com/deeplearning/sdk/tensorrt-archived/tensorrt-601/tensorrt-install-guide/index.html#maclearn-net-repo-install
#
RUN version=$TENSORRT_VERSION-1+cuda10.2 && \
    apt-get update && apt-get install -y --no-install-recommends \
    libnvinfer-dev=${version} \
    libnvonnxparsers-dev=${version} libnvparsers-dev=${version} \
    libnvinfer-plugin-dev=${version} \
&& \
    apt-mark hold \
    libnvinfer-dev \
    libnvonnxparsers-dev libnvparsers-dev \
    libnvinfer-plugin-dev \
&& \
    rm -rf /var/lib/apt/lists/*

# Install PyCUDA
RUN python3 -m pip install pycuda \
    && python3 -m pip wheel --wheel-dir install pycuda

# Install Cmake
ENV CMAKE_VERSION 3.14.4

RUN cd /tmp && \
    wget https://github.com/Kitware/CMake/releases/download/v$CMAKE_VERSION/cmake-$CMAKE_VERSION-Linux-x86_64.sh && \
    chmod +x cmake-$CMAKE_VERSION-Linux-x86_64.sh && \
    ./cmake-$CMAKE_VERSION-Linux-x86_64.sh --prefix=/usr/local --exclude-subdir --skip-license && \
    rm ./cmake-$CMAKE_VERSION-Linux-x86_64.sh

# Build plugin
ADD plugin plugin/
RUN mkdir -p build \
    && cd build \
    && cmake ../plugin \
    && make \
    && cd ..

#
# Copy libraries to the final image
#
FROM base AS result

COPY --from=builder /opt/frigate/install install
COPY --from=builder /opt/frigate/build/libflattenconcat.so /usr/lib

RUN python3 -m pip install install/* \
    && rm -r install

# Get UFF model
RUN wget -q https://github.com/dusty-nv/jetson-inference/releases/download/model-mirror-190618/SSD-Mobilenet-v2.tar.gz -O /gpu_model.tar.gz && \
    tar -xf /gpu_model.tar.gz -C / SSD-Mobilenet-v2/ssd_mobilenet_v2_coco.uff --strip-components 1 && \
    mv /ssd_mobilenet_v2_coco.uff /gpu_model.uff && \
    rm /gpu_model.tar.gz

COPY engine.py .
COPY detect_objects_gpu.py .

CMD ["python3", "-u", "detect_objects_gpu.py"]