Dockerfile

### This Dockerfile is modified from MMDeploy to build MMDeploy for GPU devices
### We update the tensorrt version and cuda version to 11.8
FROM nvcr.io/nvidia/tensorrt:23.08-py3

ARG CUDA=11.8
ARG PYTHON_VERSION=3.10
ARG TORCH_VERSION=2.0.0
ARG TORCHVISION_VERSION=0.15.1
ARG ONNXRUNTIME_VERSION=1.15.1
ARG PPLCV_VERSION=0.7.0
ENV FORCE_CUDA="1"
ARG MMCV_VERSION="==2.0.0"
ARG MMENGINE_VERSION="==0.8.4"

ENV DEBIAN_FRONTEND=noninteractive

### change the system source for installing libs
ARG USE_SRC_INSIDE=false
RUN if [ ${USE_SRC_INSIDE} == true ] ; \
    then \
        sed -i s/archive.ubuntu.com/mirrors.aliyun.com/g /etc/apt/sources.list ; \
        sed -i s/security.ubuntu.com/mirrors.aliyun.com/g /etc/apt/sources.list ; \
        echo "Use aliyun source for installing libs" ; \
    else \
        echo "Keep the download source unchanged" ; \
    fi

### update apt and install libs
RUN apt-get update &&\
    apt-get install -y vim libsm6 libxext6 libxrender-dev libgl1-mesa-glx git wget libssl-dev libopencv-dev libspdlog-dev --no-install-recommends &&\
    rm -rf /var/lib/apt/lists/*

RUN curl -fsSL -v -o ~/miniconda.sh -O  https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh  && \
    chmod +x ~/miniconda.sh && \
    bash ~/miniconda.sh -b -p /opt/conda && \
    rm ~/miniconda.sh && \
    /opt/conda/bin/conda install -y python=${PYTHON_VERSION} conda-build pyyaml numpy ipython cython typing typing_extensions mkl mkl-include ninja && \
    /opt/conda/bin/conda clean -ya

### change the pip source for installing packages
RUN if [ ${USE_SRC_INSIDE} == true ] ; \
    then \
        /opt/conda/bin/pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple; \
        echo "pip using tsinghua source" ; \
    else \
        echo "Keep pip the download source unchanged" ; \
    fi

### install pytorch openmim
RUN /opt/conda/bin/conda install pytorch==${TORCH_VERSION} torchvision==${TORCHVISION_VERSION} cudatoolkit=${CUDA} -c pytorch -c conda-forge -y \
    && /opt/conda/bin/pip install --no-cache-dir openmim

### pytorch mmcv onnxruntime
RUN /opt/conda/bin/mim install --no-cache-dir "mmcv"${MMCV_VERSION} onnxruntime-gpu==${ONNXRUNTIME_VERSION} mmengine${MMENGINE_VERSION}

ENV PATH /opt/conda/bin:$PATH
WORKDIR /root/workspace

### get onnxruntime
RUN wget https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz \
    && tar -zxvf onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz

### cp trt from pip to conda
RUN cp -r /usr/local/lib/python${PYTHON_VERSION}/dist-packages/tensorrt* /opt/conda/lib/python${PYTHON_VERSION}/site-packages/

### install mmdeploy
ENV ONNXRUNTIME_DIR=/root/workspace/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}
ENV TENSORRT_DIR=/workspace/tensorrt
ARG VERSION
RUN git clone -b main https://github.com/open-mmlab/mmdeploy &&\
    cd mmdeploy &&\
    if [ -z ${VERSION} ] ; then echo "No MMDeploy version passed in, building on main" ; else git checkout tags/v${VERSION} -b tag_v${VERSION} ; fi &&\
    git submodule update --init --recursive &&\
    mkdir -p build &&\
    cd build &&\
    cmake -DMMDEPLOY_TARGET_BACKENDS="ort;trt" .. &&\
    make -j$(nproc) &&\
    cd .. &&\
    /opt/conda/bin/mim install -e .

### build sdk
# RUN git clone https://github.com/openppl-public/ppl.cv.git &&\
#     cd ppl.cv &&\
#     git checkout tags/v${PPLCV_VERSION} -b v${PPLCV_VERSION} &&\
#     ./build.sh cuda

ENV BACKUP_LD_LIBRARY_PATH=$LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/compat/lib.real/:$LD_LIBRARY_PATH

RUN cd /root/workspace/mmdeploy &&\
    rm -rf build/CM* build/cmake-install.cmake build/Makefile build/csrc &&\
    mkdir -p build && cd build &&\
    cmake .. \
        -DMMDEPLOY_BUILD_EXAMPLES=ON \
        -DCMAKE_CXX_COMPILER=g++ \
        -DTENSORRT_DIR=${TENSORRT_DIR} \
        -DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \
        -DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
        -DMMDEPLOY_TARGET_DEVICES="cuda;cpu" \
        -DMMDEPLOY_TARGET_BACKENDS="ort;trt" \
        -DMMDEPLOY_CODEBASES=all &&\
    make -j$(nproc) && make install &&\
    export SPDLOG_LEVEL=warn &&\
    if [ -z ${VERSION} ] ; then echo "Built MMDeploy for GPU devices successfully!" ; else echo "Built MMDeploy version v${VERSION} for GPU devices successfully!" ; fi
        # -DMMDEPLOY_BUILD_SDK=ON \
        # -Dpplcv_DIR=/root/workspace/ppl.cv/cuda-build/install/lib/cmake/ppl \

ENV LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:${BACKUP_LD_LIBRARY_PATH}"
ENV CUDA_HOME /usr/local/cuda-11.8/


RUN rm -rf /var/lib/apt/lists/*
RUN apt-get update -y
RUN apt-get install ffmpeg libsm6 libxext6  -y
RUN apt-get clean -y
RUN pip install --upgrade pip

RUN useradd -m -u 1000 user
RUN chown -R user:user /root/workspace
USER user
ENV HOME=/home/user \
	PATH=/home/user/.local/bin:$PATH
WORKDIR $HOME/app
COPY --chown=user . $HOME/app
USER root
RUN mkdir -p /data && mv ./data /data/human_detection
RUN pip install --no-cache-dir --upgrade -r requirements.txt
RUN mim install mmdet==3.1.0
RUN mim install mmpose==1.1.0
RUN mim install mmyolo==0.6.0
RUN pip install cython-bbox==0.1.3
RUN pip install lap
RUN pip install gradio
RUN python setup.py develop
USER user

RUN echo 'export PYTHONPATH=$PYTHONPATH:./' >> ~/.bashrc

CMD /bin/bash -c "cd projects/human_detection && ./export_onnx_trt/export_trt_mmyolov8.sh && gradio app.py"