Dockerfile.jetson

# NVIDIA Jetson embedded device support with GPU accelerated local model execution for https://github.com/microsoft/JARVIS

# Base image for ffmpeg build env: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-jetpack/tags
FROM nvcr.io/nvidia/l4t-jetpack:r35.2.1 AS build

RUN apt update && apt install -y --no-install-recommends \
    build-essential git libass-dev cmake && \
    rm -rf /var/lib/apt/lists/*

# Build ffmpeg dependency libraries
RUN git clone https://github.com/jocover/jetson-ffmpeg.git  && \
    cd jetson-ffmpeg && \
    sed -i 's=Libs: -L${libdir} -lnvmpi=Libs: -L${libdir} -lnvmpi -L/usr/lib/aarch64-linux-gnu/tegra -lnvbufsurface=g' nvmpi.pc.in && \
    mkdir build && \
    cd build && \
    cmake .. && \
    make -j$(nproc) && \
    sudo make install && \
    sudo ldconfig && \ 
    git clone git://source.ffmpeg.org/ffmpeg.git -b release/4.2 --depth=1 && \
    cd ffmpeg && \
    wget https://github.com/jocover/jetson-ffmpeg/raw/master/ffmpeg_nvmpi.patch && \
    git apply ffmpeg_nvmpi.patch && \
    ./configure --enable-nvmpi --enable-libass&& \
    make -j$(nproc)

# Base image: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-pytorch/tags
# For running JARVIS application layer
from nvcr.io/nvidia/l4t-pytorch:r35.2.1-pth2.0-py3

ENV LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
COPY --from=build /usr/local/lib/libnvmpi.a /usr/local/lib
COPY --from=build /usr/local/lib/libnvmpi.so.1.0.0 /usr/local/lib
COPY --from=build jetson-ffmpeg/build/ffmpeg/ffmpeg /usr/local/bin
COPY --from=build jetson-ffmpeg/build/ffmpeg/ffprobe /usr/local/bin
RUN ln /usr/local/lib/libnvmpi.so.1.0.0 /usr/local/lib/libnvmpi.so
ENV MAKEFLAGS="-j$(nproc)"

COPY ./server/requirements.txt .

# Install model server dependencies
RUN apt update && apt remove -y \
    opencv-dev opencv-libs opencv-licenses opencv-main opencv-python opencv-scripts python3-numpy && \
    rm -rf /var/lib/apt/lists/*

RUN python3 -m pip install importlib-metadata==4.13.0 && \
    python3 -m pip install -r requirements.txt && \
    rm -rf requirements.txt

# Update torch deps via reinstall
RUN python3 -m pip install torch==2.0.0a0+ec3941ad.nv23.2 torchaudio==0.13.1+b90d798 torchvision==0.14.1a0+5e8e2f1

# Downgrade opencv-python to v4.5
RUN python3 -m pip install opencv-python==4.5.5.64 

# Install nvidia-opencv-dev
RUN apt update && apt install -y --no-install-recommends \
    nvidia-opencv-dev && \
    rm -rf /var/lib/apt/lists/* 

# Fix loading of scikit dep at runtime
ENV LD_PRELOAD='/usr/local/lib/python3.8/dist-packages/scikit_learn.libs/libgomp-d22c30c5.so.1.0.0'

# Install nodejs npm from nodesource
ENV NVM_DIR /root/.nvm
ENV NODE_VERSION v18.16.0
RUN wget -q -O - https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.3/install.sh | bash  && \
    . "$NVM_DIR/nvm.sh" && \
    nvm install $NODE_VERSION && \
    nvm alias default $NODE_VERSION && \
    nvm use default 
ENV NODE_PATH $NVM_DIR/versions/node/$NODE_VERSION/lib/node_modules
ENV PATH $NVM_DIR/versions/node/$NODE_VERSION/bin:$PATH

WORKDIR /app

# Copy source files
COPY . .

# Install web server dependencies
RUN apt update && apt install -y --no-install-recommends \
    xdg-utils && \
    rm -rf /var/lib/apt/lists/* && \
    cd web && \
    npm install

# Download local models
# RUN apt update && apt install -y --no-install-recommends \
#    git-lfs && \
#    rm -rf /var/lib/apt/lists/* && \
#    cd server/models && \
#    bash download.sh

# Expose the model server ports
EXPOSE 8004
EXPOSE 8005
# Expose the web server port
EXPOSE 9999

WORKDIR /app/server

# Start the model and web server
CMD python3 models_server.py --config configs/config.default.yaml;