CVAT部署以及半自动标注（GPU）上篇

标的越快活越多我是tm服啦Docker安装及换源Docker官方的安装教程Install Docker Engine on Ubuntu | Docker Docs如果之前安装过可以运行这条命令进行清除sudo apt remove $(dpkg --get-selections docker.io docker-compose docker-compose-v2 docker-doc docker-buildx podman-docker containerd runc | cut -f1)添加docker的仓库源# Add Dockers official GPG key: sudo apt update sudo apt install ca-certificates curl sudo install -m 0755 -d /etc/apt/keyrings sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc sudo chmod ar /etc/apt/keyrings/docker.asc # Add the repository to Apt sources: sudo tee /etc/apt/sources.list.d/docker.sources EOF Types: deb URIs: https://download.docker.com/linux/ubuntu Suites: $(. /etc/os-release echo ${UBUNTU_CODENAME:-$VERSION_CODENAME}) Components: stable Architectures: $(dpkg --print-architecture) Signed-By: /etc/apt/keyrings/docker.asc EOF sudo apt update安装docker直接装最新版了sudo apt install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin输入docker -v 检查是否安装成功返回版本号则安装完成。接着添加当前用户到docker组里# 添加用户到组 sudo usermod -aG docker $USER # 刷新权限 newgrp docker配置镜像网站sudo tee /etc/docker/daemon.json EOF { registry-mirrors: [ https://docker.xuanyuan.me, https://docker.1ms.run, https://docker.aityp.com ] } EOF //重启docker再拉docker镜像 sudo systemctl daemon-reload sudo systemctl restart docker随便拉取一个镜像测试即可至此docker安装完成下面进行nvidia container toolkit安装安装步骤如下一步步执行即可# Install the prerequisites for the instructions below sudo apt-get update sudo apt-get install -y --no-install-recommends \ ca-certificates \ curl \ gnupg2 # Configure the production repository # 1. 从国内镜像拉取GPG密钥改用国内镜像 curl -fsSL https://mirrors.ustc.edu.cn/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \ curl -s -L https://mirrors.ustc.edu.cn/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \ sed s#deb https://nvidia.github.io#deb [signed-by/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://mirrors.ustc.edu.cn#g | \ sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list # Update the packages list from the repository sudo apt-get update # Install the NVIDIA Container Toolkit packages export NVIDIA_CONTAINER_TOOLKIT_VERSION1.19.1-1 sudo apt-get install -y \ nvidia-container-toolkit${NVIDIA_CONTAINER_TOOLKIT_VERSION} \ nvidia-container-toolkit-base${NVIDIA_CONTAINER_TOOLKIT_VERSION} \ libnvidia-container-tools${NVIDIA_CONTAINER_TOOLKIT_VERSION} \ libnvidia-container1${NVIDIA_CONTAINER_TOOLKIT_VERSION}修改配置文件# 自动配置会修改 /etc/docker/daemon.json sudo nvidia-ctk runtime configure --runtimedocker # 重启 Docker sudo systemctl restart docker检查是否可用docker run --rm --gpus all docker.io/nvidia/cuda:11.8.0-base-ubuntu22.04 nvidia-smi输出如图所示则GPU可用以上前期的准备工作完成