[{"data":1,"prerenderedAt":495},["ShallowReactive",2],{"wiki-page-/zh-tw/wiki/2024-10-03-docker-jiao-cheng/ch7-ge-zhong-docker-rong-qi-bu-shu":3,"wiki-doc-items-/zh-tw/wiki/2024-10-03-docker-jiao-cheng/ch7-ge-zhong-docker-rong-qi-bu-shu":414,"language-switcher-data-/zh-tw/wiki/2024-10-03-docker-jiao-cheng/ch7-ge-zhong-docker-rong-qi-bu-shu":479,"wiki-i18n-paths-/zh-tw/wiki/2024-10-03-docker-jiao-cheng/ch7-ge-zhong-docker-rong-qi-bu-shu":494},{"id":4,"title":5,"body":6,"canonicalPath":395,"chapter":396,"chapterSort":397,"date":398,"description":131,"docI18nKey":399,"docKey":400,"docRoot":401,"docTitle":402,"extension":403,"i18nKey":404,"isBlogPost":405,"isWikiDoc":194,"isWikiIndex":405,"layout":406,"legacyPath":406,"locale":407,"localeSlug":408,"meta":409,"navigation":194,"path":395,"seo":410,"sourcePath":411,"sourceStem":404,"stem":412,"wikiDepth":139,"__hash__":413},"content/_i18n/zh-tw/wiki/2024-10-03-Docker教程/ch7-各种Docker容器部署.md","各種Docker容器部署",{"type":7,"value":8,"toc":391},"minimark",[9,13,22,25,28,33,38,46,52,55,88,91,117,120,125,151,155,161,168,172,175,221,225,231,236,239,242,248,251,291,295,301,306,347,387],[10,11,12],"h3",{"id":12},"部署容器步驟",[14,15,16,17,21],"p",{},"先從dockerhub拉取（docker pull）鏡像，",[18,19,20],"strong",{},"然後再通過docker run命令創建容器即可。","（直接運行docker run命令也行，這會自己尋找本地鏡像並創建，如果本地沒有則會自動去dockerhub上尋找鏡像並拉取創建容器一條龍服務。）",[14,23,24],{},"下面是各大容器拉取的命令（均支持amd64和arm64架構）：",[10,26,27],{"id":27},"各大容器拉取",[29,30,32],"h4",{"id":31},"vinci機器人隊暫時主使用的docker版本","Vinci機器人隊暫時主使用的docker版本",[14,34,35],{},[18,36,37],{},"（該版本暫未構建上傳到dockerhub，但是tungchiahui/ros-opencv:humble-411-cuda128-cudnn970-jammy已經實現了下列說的全部了）",[14,39,40],{},[41,42,43],"a",{"href":43,"rel":44},"https://hub.docker.com/repositories/sdutvincirobot",[45],"nofollow",[14,47,48],{},[41,49,50],{"href":50,"rel":51},"https://github.com/SDUTVINCI/docker",[45],[14,53,54],{},"使用以下帶有CUDA和CuDNN的Docker必須滿足的條件:",[56,57,58,62,65,68],"ol",{},[59,60,61],"li",{},"有英偉達NVIDIA獨立顯卡",[59,63,64],{},"顯卡驅動必須滿足≥570.86.10",[59,66,67],{},"設備的架構必須為amd64(x86_64)架構或者aarch64(arm64)架構。(絕大多數設備均滿足)",[59,69,70,71],{},"支持的顯卡型號如下:",[56,72,73,76,79,82,85],{},[59,74,75],{},"GTX10系列桌面端、移動端顯卡均已支持",[59,77,78],{},"RTX20-RTX50系列桌面端、移動端顯卡均已支持",[59,80,81],{},"NVIDIA Jetson AGX Orin、NVIDIA Jetson Orin NX、NVIDIA Jetson Orin Nano工控機已支持",[59,83,84],{},"NVIDIA Jetson AGX Xavier、NVIDIA Jetson Xavier NX工控機已支持",[59,86,87],{},"其他顯卡均未適配，強行使用其他顯卡肯定會有不兼容的問題，如果想要適配你的顯卡型號，請單獨聯繫學長",[14,89,90],{},"該鏡像包含的內容：",[56,92,93,96,99,102,105,108,111,114],{},[59,94,95],{},"Ubuntu22.04",[59,97,98],{},"ROS2 Humble",[59,100,101],{},"OpenCV4.11",[59,103,104],{},"CUDA12.8",[59,106,107],{},"CuDNN9.7.0",[59,109,110],{},"cv_bridge(amd64支持，但arm64暫時沒構建，請自行構建)",[59,112,113],{},"Livox-SDK2",[59,115,116],{},"(但無Livox-ROS-Driver2，自己在ws下編譯吧)",[14,118,119],{},"請電控組成員在組長的允許下，變更該docker鏡像內容，dockerfile和鏡像均上傳到github及dockerhub上了。",[56,121,122],{},[59,123,124],{},"從dockerhub上拉取鏡像",[126,127,132],"pre",{"className":128,"code":129,"language":130,"meta":131,"style":131},"language-bash shiki shiki-themes github-light github-dark","docker pull 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tungchiahui/ros:jazzy-noble\n",[29,222,224],{"id":223},"無rosopencv411cuda128cudnn970","（無ROS）OpenCV4.11+CUDA12.8+CuDNN9.7.0",[14,226,227],{},[41,228,229],{"href":229,"rel":230},"https://hub.docker.com/repository/docker/tungchiahui/opencv",[45],[14,232,233],{},[41,234,167],{"href":165,"rel":235},[45],[14,237,238],{},"OpenCV4.11+CUDA12.8+CuDNN9.7.0：",[14,240,241],{},"（因為50系顯卡最低要跑CUDA12.8,所以拉高門檻）",[14,243,244],{},[41,245,246],{"href":246,"rel":247},"https://pcnveplwrxf8.feishu.cn/sync/HtRPdZxPHsfwnwbXDsjcBfVcnah",[45],[14,249,250],{},"暫時主要維護Ubuntu Jammy的版本，其他版本隨緣更新，但也基本都是非常夠用的狀態（隨著戰隊主要使用的版本而變化）",[126,252,254],{"className":128,"code":253,"language":130,"meta":131,"style":131},"docker pull tungchiahui/opencv:411-cuda128-cudnn970-focal\n\ndocker pull tungchiahui/opencv:411-cuda128-cudnn971-jammy\n\ndocker pull 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