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 (stretch) 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，使用
libopencv-video-dev安装 OpenCV 4.5 时，还应安装libopencv-contrib-dev。$ sudo apt-get install -y libopencv-contrib-devMediaPipe 的
opencv_linux.BUILD和WORKSPACE已针对 OpenCV 2/3 进行配置，应该可以在任何架构上正常运行：# 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以自动从源代码构建 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 的文档手动从源代码构建 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 将安装到默认推荐的/usr/local/。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", ], )当前的 FFmpeg 设置在
ffmpeg_linux.BUILD中定义，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（而非 OS X）上使用 GPU 加速运行桌面示例。
# 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，了解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，了解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，了解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 是一项实验性功能。
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 可执行文件并进行安装。
安装 Visual C++ 生成工具和 WinSDK
前往 Visual Studio 网站，下载构建工具，然后安装 Microsoft Visual C++ 2022 Redistributable 和 Microsoft Build Tools 2022。
从 Microsoft 官方网站下载 WinSDK 并进行安装。
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 Bazel 官方文档中的说明安装 Bazel 6.5.0 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\<version>\BuildTools C:\> set BAZEL_VC=C:\Program Files (x86)\Microsoft Visual Studio\<version>\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 可执行文件并进行安装。MediaPipe 0.10.x 支持 OpenCV 3.4.10。如果 OpenCV 未安装在
C:\opencv下，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，了解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以自动从源代码构建 OpenCV 并修改 MediaPipe 的 OpenCV 配置。方法 3. 按照 OpenCV 的文档手动从源代码构建 OpenCV。
new_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，了解一些常见构建问题的解决方案。
使用 Docker 进行安装
这将使用一个 Docker 映像，以便将 MediaPipe 的安装与系统的其余部分隔离开来。
在宿主系统上安装 Docker。
构建标记为“mediapipe”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，了解一些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