Dockerfile 1.72 KB
# 使用NVIDIA的CUDA基础镜像
#FROM nvidia/cuda:11.3.0-cudnn8-runtime-ubuntu18.04
#FROM m11007322/cuda11.3.0-cudnn8-devel-ubuntu20.04-jupyterlab
FROM nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04
# 安装Python和pip
RUN apt-get update && apt-get install -y --no-install-recommends \
        python3 \
        python3-pip \
    && rm -rf /var/lib/apt/lists/*

# 安装Jupyter
RUN pip3 install --no-cache-dir jupyter

# 安装基础工具
RUN apt-get update -yq --fix-missing \
 && DEBIAN_FRONTEND=noninteractive apt-get install -yq --no-install-recommends \
    pkg-config \
    wget \
    cmake \
    curl \
    git \
    vim

# 创建一个新的Conda环境
RUN apt-get update && apt-get install -y wget \
    && wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
    && /bin/bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/conda \
    && rm Miniconda3-latest-Linux-x86_64.sh \
    && apt-get remove --purge --auto-remove -y wget \
    && apt-get clean \
    && ln -s /opt/conda/bin/conda /usr/bin/conda \
    && conda update -n base -c defaults conda 

SHELL ["/bin/bash","-ic"]
# 增加cuda全局变量
RUN echo "export CUDA_HOME=/usr/local/cuda" >> ~/.bashrc \
    && echo "export PATH=${CUDA_HOME}/bin:$PATH" >> ~/.bashrc \
    && echo "export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:$LD_LIBRARY_PATH" >> ~/.bashrc \
    && source ~/.bashrc
    
    #&& echo "nameserver 8.8.8.8" >> /etc/resolv.conf

# 安装cv2依赖,修复libGL.so.1错误
RUN apt-get update
RUN apt-get install ffmpeg libsm6 libxext6  -y

# 配置Jupyter
ENV JUPYTER_ENABLE_LAB=yes
ENV USER=root
ENV HOME=/home/$USER

# 设置工作目录
WORKDIR /root

# 设置启动命令
CMD ["jupyter", "lab", "--ip='*'", "--port=8888", "--no-browser", "--allow-root"]