在 Debian 和 Ubuntu 上安装
安装 Bazelisk。
按照官方 Bazel 文档安装 Bazelisk。
检出 MediaPipe 代码库。
$ cd $HOME $ git clone --depth 1 https://github.com/google/mediapipe.git # Change directory into MediaPipe root directory $ cd mediapipe安装 OpenCV 和 FFmpeg。
选项 1。使用软件包管理器工具安装预编译的 OpenCV 库。FFmpeg 将通过
libopencv-video-dev安装。操作系统 OpenCV Debian 9（拉伸） 2.4 Debian 10 (buster) 3.2 Debian 11 (bullseye) 4.5 Ubuntu 16.04 LTS 2.4 Ubuntu 18.04 LTS 3.2 Ubuntu 20.04 LTS 4.2 Ubuntu 20.04 LTS 4.2 Ubuntu 21.04 4.5 $ sudo apt-get install -y \ libopencv-core-dev \ libopencv-highgui-dev \ libopencv-calib3d-dev \ libopencv-features2d-dev \ libopencv-imgproc-dev \ libopencv-video-dev注意：在 Debian 11/Ubuntu 21.04 上，如果通过
libopencv-video-dev安装 OpenCV 4.5，则也应该安装libopencv-contrib-dev。$ sudo apt-get install -y libopencv-contrib-devMediaPipe 的
opencv_linux.BUILD和WORKSPACE已针对 OpenCV 2/3 进行了配置，应该在任何架构上都能正常运行：# WORKSPACE new_local_repository( name = "linux_opencv", build_file = "@//third_party:opencv_linux.BUILD", path = "/usr", ) # opencv_linux.BUILD for OpenCV 2/3 installed from Debian package cc_library( name = "opencv", linkopts = [ "-l:libopencv_core.so", "-l:libopencv_calib3d.so", "-l:libopencv_features2d.so", "-l:libopencv_highgui.so", "-l:libopencv_imgcodecs.so", "-l:libopencv_imgproc.so", "-l:libopencv_video.so", "-l:libopencv_videoio.so", ], )对于 OpenCV 4，您需要根据当前架构修改
opencv_linux.BUILD：# WORKSPACE new_local_repository( name = "linux_opencv", build_file = "@//third_party:opencv_linux.BUILD", path = "/usr", ) # opencv_linux.BUILD for OpenCV 4 installed from Debian package cc_library( name = "opencv", hdrs = glob([ # Uncomment according to your multiarch value (gcc -print-multiarch): # "include/aarch64-linux-gnu/opencv4/opencv2/cvconfig.h", # "include/arm-linux-gnueabihf/opencv4/opencv2/cvconfig.h", # "include/x86_64-linux-gnu/opencv4/opencv2/cvconfig.h", "include/opencv4/opencv2/**/*.h*", ]), includes = [ # Uncomment according to your multiarch value (gcc -print-multiarch): # "include/aarch64-linux-gnu/opencv4/", # "include/arm-linux-gnueabihf/opencv4/", # "include/x86_64-linux-gnu/opencv4/", "include/opencv4/", ], linkopts = [ "-l:libopencv_core.so", "-l:libopencv_calib3d.so", "-l:libopencv_features2d.so", "-l:libopencv_highgui.so", "-l:libopencv_imgcodecs.so", "-l:libopencv_imgproc.so", "-l:libopencv_video.so", "-l:libopencv_videoio.so", ], )方法 2.运行
setup_opencv.sh以根据源代码自动构建 OpenCV 并修改 MediaPipe 的 OpenCV 配置。此选项会自动执行选项 3 中定义的所有步骤。选项 3。按照 OpenCV 的文档，从源代码手动构建 OpenCV。
您可能需要修改
WORKSPACE和opencv_linux.BUILD以将 MediaPipe 指向您自己的 OpenCV 库。假设 OpenCV 将安装到/usr/local/（默认情况下推荐此选项）。OpenCV 2/3 设置：
# WORKSPACE new_local_repository( name = "linux_opencv", build_file = "@//third_party:opencv_linux.BUILD", path = "/usr/local", ) # opencv_linux.BUILD for OpenCV 2/3 installed to /usr/local cc_library( name = "opencv", linkopts = [ "-L/usr/local/lib", "-l:libopencv_core.so", "-l:libopencv_calib3d.so", "-l:libopencv_features2d.so", "-l:libopencv_highgui.so", "-l:libopencv_imgcodecs.so", "-l:libopencv_imgproc.so", "-l:libopencv_video.so", "-l:libopencv_videoio.so", ], )OpenCV 4 设置：
# WORKSPACE new_local_repository( name = "linux_opencv", build_file = "@//third_party:opencv_linux.BUILD", path = "/usr/local", ) # opencv_linux.BUILD for OpenCV 4 installed to /usr/local cc_library( name = "opencv", hdrs = glob([ "include/opencv4/opencv2/**/*.h*", ]), includes = [ "include/opencv4/", ], linkopts = [ "-L/usr/local/lib", "-l:libopencv_core.so", "-l:libopencv_calib3d.so", "-l:libopencv_features2d.so", "-l:libopencv_highgui.so", "-l:libopencv_imgcodecs.so", "-l:libopencv_imgproc.so", "-l:libopencv_video.so", "-l:libopencv_videoio.so", ], )当前 FFmpeg 设置在
ffmpeg_linux.BUILD中定义，应适用于任何架构：# WORKSPACE new_local_repository( name = "linux_ffmpeg", build_file = "@//third_party:ffmpeg_linux.BUILD", path = "/usr" ) # ffmpeg_linux.BUILD for FFmpeg installed from Debian package cc_library( name = "libffmpeg", linkopts = [ "-l:libavcodec.so", "-l:libavformat.so", "-l:libavutil.so", ], )仅适用于在 Linux（而不是 OS X）上使用 GPU 加速运行桌面示例的应用。
# Requires a GPU with EGL driver support. # Can use mesa GPU libraries for desktop, (or Nvidia/AMD equivalent). sudo apt-get install mesa-common-dev libegl1-mesa-dev libgles2-mesa-dev # To compile with GPU support, replace --define MEDIAPIPE_DISABLE_GPU=1 # with --copt -DMESA_EGL_NO_X11_HEADERS --copt -DEGL_NO_X11 # when building GPU examples.-
$ export GLOG_logtostderr=1 # if you are running on Linux desktop with CPU only $ bazel run --define MEDIAPIPE_DISABLE_GPU=1 \ mediapipe/examples/desktop/hello_world:hello_world # If you are running on Linux desktop with GPU support enabled (via mesa drivers) $ bazel run --copt -DMESA_EGL_NO_X11_HEADERS --copt -DEGL_NO_X11 \ mediapipe/examples/desktop/hello_world:hello_world # Should print: # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World!
如果您遇到构建错误，请参阅问题排查，查找一些常见构建问题的解决方案。
在 CentOS 上安装
免责声明：在 CentOS 上运行 MediaPipe 目前处于实验阶段。
安装 Bazelisk。
按照官方 Bazel 文档安装 Bazelisk。
检出 MediaPipe 代码库。
$ git clone --depth 1 https://github.com/google/mediapipe.git # Change directory into MediaPipe root directory $ cd mediapipe安装 OpenCV。
方法 1. 使用软件包管理器工具安装预编译版本。
$ sudo yum install opencv-devel方法 2. 从源代码构建 OpenCV。
new_local_repository( name = "linux_opencv", build_file = "@//third_party:opencv_linux.BUILD", path = "/usr/local", ) new_local_repository( name = "linux_ffmpeg", build_file = "@//third_party:ffmpeg_linux.BUILD", path = "/usr/local", ) cc_library( name = "opencv", srcs = glob( [ "lib/libopencv_core.so", "lib/libopencv_highgui.so", "lib/libopencv_imgcodecs.so", "lib/libopencv_imgproc.so", "lib/libopencv_video.so", "lib/libopencv_videoio.so", ], ), hdrs = glob([ # For OpenCV 3.x "include/opencv2/**/*.h*", # For OpenCV 4.x # "include/opencv4/opencv2/**/*.h*", ]), includes = [ # For OpenCV 3.x "include/", # For OpenCV 4.x # "include/opencv4/", ], linkstatic = 1, visibility = ["//visibility:public"], ) cc_library( name = "libffmpeg", srcs = glob( [ "lib/libav*.so", ], ), hdrs = glob(["include/libav*/*.h"]), includes = ["include"], linkopts = [ "-lavcodec", "-lavformat", "-lavutil", ], linkstatic = 1, visibility = ["//visibility:public"], )-
$ export GLOG_logtostderr=1 # Need bazel flag 'MEDIAPIPE_DISABLE_GPU=1' if you are running on Linux desktop with CPU only $ bazel run --define MEDIAPIPE_DISABLE_GPU=1 \ mediapipe/examples/desktop/hello_world:hello_world # Should print: # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World!
如果您遇到构建错误，请参阅问题排查，查找一些常见构建问题的解决方案。
在 macOS 上安装
准备工作：
安装 Bazelisk。
按照官方 Bazel 文档安装 Bazelisk。
检出 MediaPipe 代码库。
$ git clone --depth 1 https://github.com/google/mediapipe.git $ cd mediapipe安装 OpenCV 和 FFmpeg。
方法 1. 使用 HomeBrew 软件包管理器工具安装预编译的 OpenCV 3 库。FFmpeg 将通过 OpenCV 安装。
$ brew install opencv@3 # There is a known issue caused by the glog dependency. Uninstall glog. $ brew uninstall --ignore-dependencies glog方法 2. 使用 MacPorts 软件包管理器工具安装 OpenCV 库。
$ port install opencvnew_local_repository( name = "macos_opencv", build_file = "@//third_party:opencv_macos.BUILD", path = "/opt", ) new_local_repository( name = "macos_ffmpeg", build_file = "@//third_party:ffmpeg_macos.BUILD", path = "/opt", ) cc_library( name = "opencv", srcs = glob( [ "local/lib/libopencv_core.dylib", "local/lib/libopencv_highgui.dylib", "local/lib/libopencv_imgcodecs.dylib", "local/lib/libopencv_imgproc.dylib", "local/lib/libopencv_video.dylib", "local/lib/libopencv_videoio.dylib", ], ), hdrs = glob(["local/include/opencv2/**/*.h*"]), includes = ["local/include/"], linkstatic = 1, visibility = ["//visibility:public"], ) cc_library( name = "libffmpeg", srcs = glob( [ "local/lib/libav*.dylib", ], ), hdrs = glob(["local/include/libav*/*.h"]), includes = ["local/include/"], linkopts = [ "-lavcodec", "-lavformat", "-lavutil", ], linkstatic = 1, visibility = ["//visibility:public"], )确保已安装 Python 3 和 Python“six”库。
$ brew install python $ sudo ln -s -f /usr/local/bin/python3.7 /usr/local/bin/python $ python --version Python 3.7.4 $ pip3 install --user six-
$ export GLOG_logtostderr=1 # Need bazel flag 'MEDIAPIPE_DISABLE_GPU=1' as desktop GPU is currently not supported $ bazel run --define MEDIAPIPE_DISABLE_GPU=1 \ mediapipe/examples/desktop/hello_world:hello_world # Should print: # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World!
如果您遇到构建错误，请参阅问题排查，查找一些常见构建问题的解决方案。
在 Windows 上安装
免责声明：在 Windows 上运行 MediaPipe 目前处于实验阶段。
安装 MSYS2 并修改
%PATH%环境变量。如果 MSYS2 已安装到
C:\msys64下，请将C:\msys64\usr\bin添加到%PATH%环境变量中。安装必要的软件包。
C:\> pacman -S git patch unzip安装 Python 并允许可执行文件修改
%PATH%环境变量。从 https://www.python.org/downloads 下载 Python Windows 可执行文件并安装。
安装 Visual C++ Build Tools 2019 和 WinSDK
转到 Visual Studio 网站，下载构建工具，然后安装 Microsoft Visual C++ 2019 Redistributable 和 Microsoft Build Tools 2019。
从官方 MicroSoft 网站下载 WinSDK 并安装。
安装 Bazel 或 Bazelisk，并将 Bazel 可执行文件的位置添加到
%PATH%环境变量中。方法 1. 按照官方 Bazel 文档安装 Bazel 6.1.1 或更高版本。
方法 2. 按照官方 Bazel 文档安装 Bazelisk。
设置 Bazel 变量。如需详细了解“在 Windows 上构建”，请参阅 Bazel 官方文档。
# Please find the exact paths and version numbers from your local version. C:\> set BAZEL_VS=C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools C:\> set BAZEL_VC=C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools\VC C:\> set BAZEL_VC_FULL_VERSION=<Your local VC version> C:\> set BAZEL_WINSDK_FULL_VERSION=<Your local WinSDK version>检出 MediaPipe 代码库。
C:\Users\Username\mediapipe_repo> git clone --depth 1 https://github.com/google/mediapipe.git # Change directory into MediaPipe root directory C:\Users\Username\mediapipe_repo> cd mediapipe安装 OpenCV。
从 https://opencv.org/releases/ 下载 Windows 可执行文件并安装。MediaPipe 0.10.x 支持 OpenCV 3.4.10。如果 OpenCV 未在
C:\opencv上安装，请务必修改WORKSPACE文件。new_local_repository( name = "windows_opencv", build_file = "@//third_party:opencv_windows.BUILD", path = "C:\\<path to opencv>\\build", )-
C:\Users\Username\mediapipe_repo>bazel build -c opt --define MEDIAPIPE_DISABLE_GPU=1 --action_env PYTHON_BIN_PATH="C://python_36//python.exe" mediapipe/examples/desktop/hello_world C:\Users\Username\mediapipe_repo>set GLOG_logtostderr=1 C:\Users\Username\mediapipe_repo>bazel-bin\mediapipe\examples\desktop\hello_world\hello_world.exe # should print: # I20200514 20:43:12.277598 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.278597 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.279618 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.279618 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.279618 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.279618 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.279618 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.279618 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.279618 1200 hello_world.cc:56] Hello World! # I20200514 20:43:12.280613 1200 hello_world.cc:56] Hello World!
如果您遇到构建错误，请参阅问题排查，查找一些常见构建问题的解决方案。
在适用于 Linux 的 Windows 子系统 (WSL) 上安装
按照说明安装适用于 Linux (Ubuntu) 的 Windows 子系统。
安装 Windows ADB，并在 Windows 中启动 ADB 服务器。
启动 WSL。
安装所需的软件包。
username@DESKTOP-TMVLBJ1:~$ sudo apt-get update && sudo apt-get install -y build-essential git python zip adb openjdk-8-jdk安装 Bazelisk。
按照官方 Bazel 文档安装 Bazelisk。
检出 MediaPipe 代码库。
username@DESKTOP-TMVLBJ1:~$ git clone --depth 1 https://github.com/google/mediapipe.git username@DESKTOP-TMVLBJ1:~$ cd mediapipe安装 OpenCV 和 FFmpeg。
方法 1. 使用软件包管理器工具安装预编译的 OpenCV 库。FFmpeg 将通过 libopencv-video-dev 安装。
username@DESKTOP-TMVLBJ1:~/mediapipe$ sudo apt-get install libopencv-core-dev libopencv-highgui-dev \ libopencv-calib3d-dev libopencv-features2d-dev \ libopencv-imgproc-dev libopencv-video-dev方法 2. 运行
setup_opencv.sh以根据源代码自动构建 OpenCV 并修改 MediaPipe 的 OpenCV 配置。方法 3. 按照 OpenCV 的文档，从源代码手动构建 OpenCV。
opencv_linux.BUILDnew_local_repository( name = "linux_opencv", build_file = "@//third_party:opencv_linux.BUILD", path = "/usr/local", ) cc_library( name = "opencv", srcs = glob( [ "lib/libopencv_core.so", "lib/libopencv_highgui.so", "lib/libopencv_imgcodecs.so", "lib/libopencv_imgproc.so", "lib/libopencv_video.so", "lib/libopencv_videoio.so", ], ), hdrs = glob(["include/opencv4/**/*.h*"]), includes = ["include/opencv4/"], linkstatic = 1, visibility = ["//visibility:public"], )-
username@DESKTOP-TMVLBJ1:~/mediapipe$ export GLOG_logtostderr=1 # Need bazel flag 'MEDIAPIPE_DISABLE_GPU=1' as desktop GPU is currently not supported username@DESKTOP-TMVLBJ1:~/mediapipe$ bazel run --define MEDIAPIPE_DISABLE_GPU=1 \ mediapipe/examples/desktop/hello_world:hello_world # Should print: # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World!
如果您遇到构建错误，请参阅问题排查，了解几个常见构建问题的解决方案。
使用 Docker 进行安装
这将使用 Docker 映像，将 mediapipe 的安装与系统的其余部分隔离开来。
在主机系统上安装 Docker。
构建带有“mediapipe”标记的 Docker 映像。
$ git clone --depth 1 https://github.com/google/mediapipe.git $ cd mediapipe $ docker build --tag=mediapipe . # Should print: # Sending build context to Docker daemon 147.8MB # Step 1/9 : FROM ubuntu:latest # latest: Pulling from library/ubuntu # 6abc03819f3e: Pull complete # 05731e63f211: Pull complete # ........ # See http://bazel.build/docs/getting-started.html to start a new project! # Removing intermediate container 82901b5e79fa # ---> f5d5f402071b # Step 9/9 : COPY . /edge/mediapipe/ # ---> a95c212089c5 # Successfully built a95c212089c5 # Successfully tagged mediapipe:latest-
$ docker run -it --name mediapipe mediapipe:latest root@bca08b91ff63:/mediapipe# GLOG_logtostderr=1 bazel run --define MEDIAPIPE_DISABLE_GPU=1 mediapipe/examples/desktop/hello_world # Should print: # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World! # Hello World!
如果您遇到构建错误，请参阅问题排查，了解几个常见构建问题的解决方案。
构建 MediaPipe Android 示例。
$ docker run -it --name mediapipe mediapipe:latest root@bca08b91ff63:/mediapipe# bash ./setup_android_sdk_and_ndk.sh # Should print: # Android NDK is now installed. Consider setting $ANDROID_NDK_HOME environment variable to be /root/Android/Sdk/ndk-bundle/android-ndk-r19c # Set android_ndk_repository and android_sdk_repository in WORKSPACE # Done root@bca08b91ff63:/mediapipe# bazel build -c opt --config=android_arm64 mediapipe/examples/android/src/java/com/google/mediapipe/apps/objectdetectiongpu:objectdetectiongpu # Should print: # Target //mediapipe/examples/android/src/java/com/google/mediapipe/apps/objectdetectiongpu:objectdetectiongpu up-to-date: # bazel-bin/mediapipe/examples/android/src/java/com/google/mediapipe/apps/objectdetectiongpu/objectdetectiongpu_deploy.jar # bazel-bin/mediapipe/examples/android/src/java/com/google/mediapipe/apps/objectdetectiongpu/objectdetectiongpu_unsigned.apk # bazel-bin/mediapipe/examples/android/src/java/com/google/mediapipe/apps/objectdetectiongpu/objectdetectiongpu.apk # INFO: Elapsed time: 144.462s, Critical Path: 79.47s # INFO: 1958 processes: 1 local, 1863 processwrapper-sandbox, 94 worker. # INFO: Build completed successfully, 2028 total actions