[Feature] Add docker files

docker/CPU/Dockerfile

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+FROM openvino/ubuntu18_dev:2021.4.2
+ARG PYTHON_VERSION=3.7
+ARG TORCH_VERSION=1.8.0
+ARG TORCHVISION_VERSION=0.9.0
+ARG ONNXRUNTIME_VERSION=1.8.1
+USER root
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        ca-certificates \
+        libopencv-dev libspdlog-dev \
+        gnupg \
+        libssl-dev \
+        libprotobuf-dev protobuf-compiler \
+        build-essential \
+        libjpeg-dev \
+        libpng-dev \
+        ccache \
+        cmake \
+        gcc \
+        g++ \
+        git \
+        vim \
+        wget \
+        curl \
+    && 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 && \
+    ~/miniconda.sh -b -p /opt/conda && \
+    rm ~/miniconda.sh && \
+    /opt/conda/bin/conda install -y python=${PYTHON_VERSION} conda-build pyyaml numpy ipython cython typing typing_extensions mkl mkl-include ninja && \
+    /opt/conda/bin/conda clean -ya
+
+### pytorch
+RUN /opt/conda/bin/pip install torch==${TORCH_VERSION}+cpu torchvision==${TORCHVISION_VERSION}+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
+ENV PATH /opt/conda/bin:$PATH
+
+### install open-mim
+RUN /opt/conda/bin/pip install mmcv-full==1.4.0 -f https://download.openmmlab.com/mmcv/dist/cpu/torch${TORCH_VERSION}/index.html
+
+WORKDIR /root/workspace
+RUN git clone https://github.com/open-mmlab/mmclassification
+
+
+### get onnxruntime
+RUN wget https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz \
+    && tar -zxvf onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz
+
+ENV ONNXRUNTIME_DIR=/root/workspace/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}
+
+### update cmake to 20
+RUN wget https://github.com/Kitware/CMake/releases/download/v3.20.0/cmake-3.20.0.tar.gz &&\
+    tar -zxvf cmake-3.20.0.tar.gz &&\
+    cd cmake-3.20.0 &&\
+    ./bootstrap &&\
+    make &&\
+    make install
+
+### install onnxruntme and openvino
+RUN /opt/conda/bin/pip install onnxruntime==${ONNXRUNTIME_VERSION} openvino-dev
+
+### build ncnn
+RUN git clone https://github.com/Tencent/ncnn.git &&\
+    cd ncnn &&\
+    export NCNN_DIR=$(pwd) &&\
+    git submodule update --init &&\
+    mkdir -p build && cd build &&\
+    cmake -DNCNN_VULKAN=OFF -DNCNN_SYSTEM_GLSLANG=ON -DNCNN_BUILD_EXAMPLES=ON -DNCNN_PYTHON=ON -DNCNN_BUILD_TOOLS=ON -DNCNN_BUILD_BENCHMARK=ON -DNCNN_BUILD_TESTS=ON .. &&\
+    make install &&\
+    cd /root/workspace/ncnn/python &&\
+    pip install -e .
+
+### install mmdeploy
+WORKDIR /root/workspace
+ARG VERSION
+RUN git clone https://github.com/open-mmlab/mmdeploy.git &&\
+    cd mmdeploy &&\
+    if [ -z ${VERSION} ] ; then echo "No MMDeploy version passed in, building on master" ; else git checkout tags/v${VERSION} -b tag_v${VERSION} ; fi &&\
+    git submodule update --init --recursive &&\
+    rm -rf build &&\
+    mkdir build &&\
+    cd build &&\
+    cmake -DMMDEPLOY_TARGET_BACKENDS=ncnn -Dncnn_DIR=/root/workspace/ncnn/build/install/lib/cmake/ncnn .. &&\
+    make -j$(nproc) &&\
+    cmake -DMMDEPLOY_TARGET_BACKENDS=ort .. &&\
+    make -j$(nproc) &&\
+    cd .. &&\
+    pip install -e .
+
+### build SDK
+RUN cd mmdeploy && rm -rf build/CM* && mkdir -p build && cd build && cmake .. \
+    -DMMDEPLOY_BUILD_SDK=ON \
+    -DCMAKE_CXX_COMPILER=g++-7 \
+    -DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \
+    -Dncnn_DIR=/root/workspace/ncnn/build/install/lib/cmake/ncnn \
+    -DInferenceEngine_DIR=/opt/intel/openvino/deployment_tools/inference_engine/share \
+    -DMMDEPLOY_TARGET_DEVICES=cpu \
+    -DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
+    -DMMDEPLOY_TARGET_BACKENDS="ort;ncnn;openvino" \
+    -DMMDEPLOY_CODEBASES=all &&\
+    cmake --build . -- -j$(nproc) && cmake --install . &&\
+    if [ -z ${VERSION} ] ; then echo "Build MMDeploy master for CPU devices succeed!" ; else echo "Build MMDeploy version v${VERSION} for CPU devices succeed!" ; fi

docker/GPU/Dockerfile

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+FROM nvcr.io/nvidia/tensorrt:21.04-py3
+
+ARG CUDA=10.2
+ARG PYTHON_VERSION=3.8
+ARG TORCH_VERSION=1.8.0
+ARG TORCHVISION_VERSION=0.9.0
+ARG ONNXRUNTIME_VERSION=1.8.1
+ENV FORCE_CUDA="1"
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+### 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 && \
+    ~/miniconda.sh -b -p /opt/conda && \
+    rm ~/miniconda.sh && \
+    /opt/conda/bin/conda install -y python=${PYTHON_VERSION} conda-build pyyaml numpy ipython cython typing typing_extensions mkl mkl-include ninja && \
+    /opt/conda/bin/conda clean -ya
+
+### pytorch
+RUN /opt/conda/bin/conda install pytorch==${TORCH_VERSION} torchvision==${TORCHVISION_VERSION} cudatoolkit=${CUDA} -c pytorch
+ENV PATH /opt/conda/bin:$PATH
+
+### install mmcv-full
+RUN /opt/conda/bin/pip install mmcv-full==1.4.0 -f https://download.openmmlab.com/mmcv/dist/cu${CUDA//./}/torch${TORCH_VERSION}/index.html &&\
+    /opt/conda/bin/pip install mmdet==2.19.0
+
+WORKDIR /root/workspace
+### get onnxruntime
+RUN wget https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz \
+    && tar -zxvf onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz &&\
+    pip install onnxruntime-gpu==${ONNXRUNTIME_VERSION}
+
+### cp trt from pip to conda
+RUN cp -r /usr/local/lib/python3.8/dist-packages/tensorrt* /opt/conda/lib/python3.8/site-packages/
+
+### update cmake to 20
+RUN  wget https://github.com/Kitware/CMake/releases/download/v3.20.0/cmake-3.20.0.tar.gz &&\
+    tar -zxvf cmake-3.20.0.tar.gz &&\
+    cd cmake-3.20.0 &&\
+    ./bootstrap &&\
+    make &&\
+    make install
+
+### install mmdeploy
+ENV ONNXRUNTIME_DIR=/root/workspace/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}
+ENV TENSORRT_DIR=/workspace/tensorrt
+ARG VERSION
+RUN git clone https://github.com/open-mmlab/mmdeploy &&\
+    cd mmdeploy &&\
+    if [ -z ${VERSION} ] ; then echo "No MMDeploy version passed in, building on master" ; else git checkout tags/v${VERSION} -b tag_v${VERSION} ; fi &&\
+    git submodule update --init --recursive &&\
+    rm -rf build &&\
+    mkdir build &&\
+    cd build &&\
+    cmake -DMMDEPLOY_TARGET_BACKENDS=ort .. &&\
+    make -j$(nproc) &&\
+    cmake -DMMDEPLOY_TARGET_BACKENDS=trt .. &&\
+    make -j$(nproc) &&\
+    cd .. &&\
+    pip install -e .
+
+### build sdk
+RUN git clone https://github.com/openppl-public/ppl.cv.git &&\
+    cd ppl.cv &&\
+    ./build.sh cuda
+RUN cd /root/workspace/mmdeploy &&\
+    rm -rf build/CM* &&\
+    mkdir -p build && cd build &&\
+    cmake .. \
+        -DMMDEPLOY_BUILD_SDK=ON \
+        -DCMAKE_CXX_COMPILER=g++ \
+        -Dpplcv_DIR=/root/workspace/ppl.cv/cuda-build/install/lib/cmake/ppl \
+        -DTENSORRT_DIR=${TENSORRT_DIR} \
+        -DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
+        -DMMDEPLOY_TARGET_DEVICES="cuda;cpu" \
+        -DMMDEPLOY_TARGET_BACKENDS="trt" \
+        -DMMDEPLOY_CODEBASES=all &&\
+    cmake --build . -- -j$(nproc) && cmake --install . &&\
+    if [ -z ${VERSION} ] ; then echo "Build MMDeploy master for GPU devices succeed!" ; else echo "Build MMDeploy version v${VERSION} for GPU devices succeed!" ; fi

docker/README.md

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+## Docker usage
+
+We provide two dockerfiles for CPU and GPU respectively. For CPU users, we install MMDeploy with ONNXRuntime, ncnn and OpenVINO backends. For GPU users, we install MMDeploy with TensorRT backend. Besides, users can install mmdeploy with different versions when building the docker image.
+
+### Build docker image
+
+For CPU users, we can build the docker image with the latest MMDeploy through:
+```
+cd mmdeploy
+docker build docker/CPU/ -t mmdeploy:master
+```
+For GPU users, we can build the docker image with the latest MMDeploy through:
+```
+cd mmdeploy
+docker build docker/GPU/ -t mmdeploy:master
+```
+
+For installing MMDeploy with a specific version, we can append `--build-arg VERSION=${VERSION}` to build command. GPU for example:
+```
+cd mmdeploy
+docker build docker/GPU/ -t mmdeploy:0.1.0 --build-arg  VERSION=0.1.0
+```
+
+### Run docker container
+
+After building the docker image succeed, we can use `docker run` to launch the docker service. GPU docker image for example:
+```
+docker run --gpus all -it -p 8080:8081 mmdeploy:master
+```