lipan
29f1d45d66
算法更新: delivery v1.2.1、平整度v1.5、测距v2.2、整车配准v1.3 适配器: vehicle-registration 新增、各算法 manifest 和 adapter 更新 后端: taskCadFiles/source 字段迁移、derivedPointClouds 注册、取消任务联动 前端: ElapsedTime 时长显示、两步算法流程、canRun 逻辑修复 文档: 新增5份算法性能分析报告
112 lines
5.1 KiB
Docker
112 lines
5.1 KiB
Docker
# 开发镜像（GPU）：Ubuntu 22.04 + CUDA 12.1 runtime + Node 22 + cadquery + PyTorch(cu121) + PyTorch3D
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# 用于装配检测「最近零件」服务端 GPU（scripts/assembly_nearest_gpu.py）
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# 宿主机需：NVIDIA 驱动 + nvidia-container-toolkit；构建不要求 GPU，运行需 --gpus
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#
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# 构建：docker build -t massive-point-cloud-app-dev:local -f docker/Dockerfile.dev.gpu .
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#
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# 无 NVIDIA 的机器请改用 docker/Dockerfile.dev（仅 CPU），compose 中去掉 gpus 与 ASSEMBLY_USE_GPU
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FROM nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04
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ENV DEBIAN_FRONTEND=noninteractive \
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PYTHON3_PATH=/usr/bin/python3 \
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ASSEMBLY_USE_GPU=1 \
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NVIDIA_VISIBLE_DEVICES=all \
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NVIDIA_DRIVER_CAPABILITIES=compute,utility
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# apt 换阿里云（国内构建加速）；需官方源时可在下方注释掉本段
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RUN set -eux; \
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if [ -f /etc/apt/sources.list ]; then \
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sed -i 's|http://archive.ubuntu.com/ubuntu|http://mirrors.aliyun.com/ubuntu|g' /etc/apt/sources.list; \
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sed -i 's|http://security.ubuntu.com/ubuntu|http://mirrors.aliyun.com/ubuntu|g' /etc/apt/sources.list; \
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fi
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RUN apt-get update && apt-get install -y --no-install-recommends \
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python3 \
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python3-pip \
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python3-dev \
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ca-certificates \
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curl \
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gnupg \
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libgl1 \
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libglib2.0-0 \
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libxrender1 \
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libxext6 \
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libsm6 \
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libice6 \
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libx11-6 \
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libgomp1 \
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&& rm -rf /var/lib/apt/lists/*
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# CUDA runtime 镜像默认不带 nvidia-smi；装 Ubuntu 的 nvidia-utils（主版本与宿主机驱动大版本一致，如 535/550）
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# 构建失败时改：--build-arg NVIDIA_UTILS_MAJOR=550
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ARG NVIDIA_UTILS_MAJOR=535
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RUN apt-get update && apt-get install -y --no-install-recommends \
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"nvidia-utils-${NVIDIA_UTILS_MAJOR}" \
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&& rm -rf /var/lib/apt/lists/*
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RUN mkdir -p /etc/apt/keyrings \
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&& curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg \
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&& echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_22.x nodistro main" > /etc/apt/sources.list.d/nodesource.list \
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&& apt-get update && apt-get install -y --no-install-recommends nodejs \
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&& rm -rf /var/lib/apt/lists/*
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RUN python3 -m pip install --no-cache-dir --upgrade pip setuptools wheel
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# 安装 Miniforge + pythonocc-core（conda-forge，无 Anaconda ToS 限制）
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ARG MINIFORGE_URL=https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh
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RUN set -eux \
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&& curl -fsSL "${MINIFORGE_URL}" -o /tmp/miniforge.sh \
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&& bash /tmp/miniforge.sh -b -p /opt/conda \
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&& rm /tmp/miniforge.sh \
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&& /opt/conda/bin/conda install -y -n base -c conda-forge \
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"python=3.10" pythonocc-core=7.9.3 \
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&& /opt/conda/bin/conda clean -afy \
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&& ln -sf /opt/conda/lib/python3.10/site-packages/OCC \
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/usr/local/lib/python3.10/dist-packages/OCC
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# conda-forge 编译的 .so 需要新版 libstdc++（CXXABI_1.3.15）；
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# 动态查找 conda 提供的最新真实文件，避免硬编码版本号或双重软链问题
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RUN set -eux \
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&& LIBSTDCPP=$(ls /opt/conda/lib/libstdc++.so.6.0.* 2>/dev/null | sort -V | tail -1) \
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&& [ -n "$LIBSTDCPP" ] \
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&& ln -sf "$LIBSTDCPP" /usr/lib/x86_64-linux-gnu/libstdc++.so.6 \
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&& echo "libstdc++ -> $LIBSTDCPP" \
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&& python3 -c "from OCC.Core.STEPControl import STEPControl_Reader; print('pythonocc-core OK')" \
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&& python3 -c "from OCC.Core.BRep import BRep_Builder; print('OCC BRep OK')"
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# cadquery（与 Dockerfile.dev 一致）
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ARG PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
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ARG PIP_DEFAULT_TIMEOUT=300
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COPY requirements-geometry.txt /tmp/requirements-geometry.txt
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RUN python3 -m pip install --no-cache-dir --break-system-packages \
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--default-timeout="${PIP_DEFAULT_TIMEOUT}" \
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--retries 10 \
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-i "${PIP_INDEX_URL}" \
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-r /tmp/requirements-geometry.txt \
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&& rm /tmp/requirements-geometry.txt \
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&& python3 -c "import cadquery; print('cadquery OK')"
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# PyTorch CUDA 12.1：默认官方 CDN；覆盖示例：--build-arg TORCH_INDEX_URL=https://download.pytorch.org/whl/cu121
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ARG TORCH_INDEX_URL=https://download.pytorch.org/whl/cu121
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RUN python3 -m pip install --no-cache-dir --break-system-packages \
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--default-timeout=600 --retries 10 \
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torch==2.3.1 torchvision==0.18.1 \
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--index-url "${TORCH_INDEX_URL}"
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# PyTorch3D 预编译轮仅 Meta 官方 CDN，无稳定国内镜像；加大超时。可本地下载 wheel 后 COPY + pip install。
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RUN python3 -m pip install --no-cache-dir --break-system-packages \
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--default-timeout=300 --retries 10 \
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-i https://pypi.tuna.tsinghua.edu.cn/simple \
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trimesh \
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&& python3 -m pip install --no-cache-dir --break-system-packages \
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--default-timeout=600 --retries 15 \
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pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py310_cu121_pyt231/download.html
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RUN python3 -c "import torch; import pytorch3d; import trimesh; print('pytorch', torch.__version__, 'pytorch3d', pytorch3d.__version__)"
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WORKDIR /app
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RUN corepack enable && corepack prepare pnpm@latest --activate
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CMD ["node", "-e", "console.log('use docker-compose command')"]
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