Deepness/base/Dockerfile at main · SpharxTeam/Deepness · GitHub

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# Copyright (c) 2026 SPHARX. All Rights Reserved. "From data intelligence emerges".
# deepness基础镜像
# 所有模块均基于此镜像构建

FROM nvidia/cuda:12.1.0-cudnn8-runtime-ubuntu22.04

ENV DEBIAN_FRONTEND=noninteractive \
    TZ=Asia/Shanghai \
    PATH=/opt/conda/bin:$PATH \
    CUDA_HOME=/usr/local/cuda \
    LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

# === 1. 系统库安装（包含 ORB-SLAM3 和 Pangolin 所需的所有依赖）===
RUN apt-get update && apt-get install -y --no-install-recommends \
    build-essential \
    cmake \
    git \
    wget \
    ca-certificates \
    # GUI/图形库
    libgl1-mesa-glx \
    libgl1-mesa-dri \
    libglib2.0-0 \
    libsm6 \
    libxext6 \
    libxrender-dev \
    libgomp1 \
    libxi6 \
    libx11-6 \
    libglm-dev \
    # USB/设备相关
    libusb-1.0-0-dev \
    udev \
    # 多媒体处理
    curl \
    ffmpeg \
    libavcodec-extra \
    libavformat-dev \
    libavutil-dev \
    libswscale-dev \
    libx264-dev \
    libx265-dev \
    libvpx-dev \
    libtheora-dev \
    libvorbis-dev \
    libmp3lame-dev \
    libopencore-amrnb-dev \
    libopencore-amrwb-dev \
    # 时区
    tzdata \
    # ORB-SLAM3 和 Pangolin 必需依赖 [citation:2]
    libopencv-dev \
    libeigen3-dev \
    libboost-all-dev \
    libglew-dev \
    libpython3-dev \
    && ln -fs /usr/share/zoneinfo/Asia/Shanghai /etc/localtime \
    && dpkg-reconfigure -f noninteractive tzdata \
    && rm -rf /var/lib/apt/lists/*

# === 2. 安装 Miniforge（多源下载）===
RUN set -ex; \
    MINIFORGE_VERSION="23.11.0-0"; \
    MINIFORGE_FILE="Miniforge3-Linux-x86_64.sh"; \
    OFFICIAL_URL="https://github.com/conda-forge/miniforge/releases/download/${MINIFORGE_VERSION}/${MINIFORGE_FILE}"; \
    TSINGHUA_URL="https://mirrors.tuna.tsinghua.edu.cn/github-release/conda-forge/miniforge/${MINIFORGE_VERSION}/${MINIFORGE_FILE}"; \
    for url in $OFFICIAL_URL $TSINGHUA_URL; do \
        if wget --timeout=30 --tries=2 -O Miniforge3.sh "$url"; then \
            break; \
        fi; \
    done; \
    bash Miniforge3.sh -b -p /opt/conda; \
    rm Miniforge3.sh; \
    /opt/conda/bin/conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/; \
    /opt/conda/bin/conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/; \
    /opt/conda/bin/conda config --set channel_priority flexible

# === 3. 创建基础 conda 环境（Python 3.11）===
ENV ENV_NAME=deepness-base \
    PATH=/opt/conda/envs/deepness-base/bin:$PATH \
    CONDA_DEFAULT_ENV=deepness-base

RUN /opt/conda/bin/conda install -n base -y mamba && \
    /opt/conda/bin/mamba create -n $ENV_NAME python=3.11 -y

# === 4. 安装通用 Python 包（版本锁定）===
RUN /opt/conda/bin/mamba install -n $ENV_NAME -c conda-forge \
    numpy=1.24.0 \
    pyyaml=6.0.2 \
    scipy=1.10.0 \
    tqdm=4.66.0 \
    -y

# === 5. 配置 pip 镜像源（清华源）===
RUN pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

# === 6. 安装 PyTorch 及相关包（统一版本 2.5.1+cu121）[citation:3][citation:8] ===
RUN pip install --no-cache-dir \
    torch==2.5.1+cu121 \
    torchvision==0.20.1+cu121 \
    torchaudio==2.5.1+cu121 \
    --index-url https://download.pytorch.org/whl/cu121

# === 7. 创建目录结构（优化权限）===
RUN mkdir -p /app/common/{configs,schemas,scripts,patches} \
    && mkdir -p /app/partdata/{deps,models,logs} \
    && chmod 777 /app/partdata/logs

# === 8. 创建非 root 用户 ===
RUN useradd -m -u 1000 appuser && chown -R appuser:appuser /app

# === 9. 清理缓存（减小镜像体积）===
RUN conda clean -afy && pip cache purge && rm -rf /root/.cache/pip

WORKDIR /app
USER appuser
CMD ["/bin/bash"]