谷歌Mediapipe安装部署教程

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MediaPipe Solutions 提供了一套库和工具，可帮助您在您的应用中快速应用人工智能 (AI) 和机器学习 (ML) 技术。您可以立即将这些解决方案插入到您的应用中，根据需要对其进行自定义，并在多个开发平台上使用。MediaPipe Solutions 是 MediaPipe 开源项目的一部分，因此您可以进一步自定义解决方案代码以满足您的应用需求。MediaPipe 解决方案套件包括以下内容：

MediaPipe 解决方案、Studio 和 Model Maker 的示意图

以下库和资源提供了每个 MediaPipe 解决方案的核心功能：

MediaPipe Tasks：用于部署解决方案的跨平台 API 和库。
MediaPipe 模型：预训练、可直接运行的模型，可与每个解决方案搭配使用。

借助以下工具，您可以自定义和评估解决方案：

MediaPipe Model Maker：为使用你的数据的解决方案自定义模型
MediaPipe Studio：在浏览器中直观呈现、评估解决方案并对其进行基准测试。

可用的解决方案

MediaPipe 解决方案适用于多个平台。每个解决方案都包含一个或多个模型，您也可以为某些解决方案自定义模型。以下列表显示了适用于每个受支持平台的解决方案，以及您是否可以使用 Model Maker 自定义模型：

解决方案	Android	网站	Python	iOS	自定义模型
LLM Inference API	$\surd$	$\surd$		$\surd$	$\surd$
对象检测	$\surd$	$\surd$	$\surd$	$\surd$	$\surd$
图片分类	$\surd$	$\surd$	$\surd$	$\surd$	$\surd$
图像分割	$\surd$	$\surd$	$\surd$
交互式分割	$\surd$	$\surd$	$\surd$
手部特征点检测	$\surd$	$\surd$	$\surd$	$\surd$
手势识别	$\surd$	$\surd$	$\surd$	$\surd$	$\surd$
图片嵌入	$\surd$	$\surd$	$\surd$
人脸检测	$\surd$	$\surd$	$\surd$	$\surd$
人脸特征点检测	$\surd$	$\surd$	$\surd$
人脸风格化	$\surd$	$\surd$	$\surd$		$\surd$
姿势特征点检测	$\surd$	$\surd$	$\surd$
图片生成	$\surd$				$\surd$
文本分类	$\surd$	$\surd$	$\surd$	$\surd$	$\surd$
文本嵌入	$\surd$	$\surd$	$\surd$
语言检测器	$\surd$	$\surd$	$\surd$
音频分类

安装

Python

pip安装mediapipe软件包

安装使用 mediapipe pip 软件包。您可以使用以下命令安装所需的软件包：

$ python -m pip install mediapipe

导入以下类来验证安装结果：

import mediapipe as mp
from mediapipe.tasks import python
from mediapipe.tasks.python import vision

运行示例

安装验证无误后，运行以下示例。

# STEP 1: Import the necessary modules.
import numpy as np
import mediapipe as mp
from mediapipe.tasks import python
from mediapipe.tasks.python import vision# STEP 2: Create an ObjectDetector object.
base_options = python.BaseOptions(model_asset_path='efficientdet.tflite')
options = vision.ObjectDetectorOptions(base_options=base_options,score_threshold=0.5)
detector = vision.ObjectDetector.create_from_options(options)# STEP 3: Load the input image.
image = mp.Image.create_from_file(IMAGE_FILE)# STEP 4: Detect objects in the input image.
detection_result = detector.detect(image)# STEP 5: Process the detection result. In this case, visualize it.
image_copy = np.copy(image.numpy_view())
annotated_image = visualize(image_copy, detection_result)
rgb_annotated_image = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
cv2_imshow(rgb_annotated_image)

C++

安装 Bazelisk。

Step 1: Add Bazel distribution URI as a package source

   sudo apt install apt-transport-https curl gnupg -ycurl -fsSL https://bazel.build/bazel-release.pub.gpg | gpg --dearmor >bazel-archive-keyring.gpgsudo mv bazel-archive-keyring.gpg /usr/share/keyringsecho "deb [arch=amd64 signed-by=/usr/share/keyrings/bazel-archive-keyring.gpg] https://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list```The component name "jdk1.8" is kept only for legacy reasons and doesn't relate to supported or included JDK versions. Bazel releases are Java-version agnostic. Changing the "jdk1.8" component name would break existing users of the repo.```### Step 2: Install and update Bazel```shsudo apt update && sudo apt install bazel```
Once installed, you can upgrade to a newer version of Bazel as part of your normal system updates:```sh
sudo apt update && sudo apt full-upgrade

The bazel package always installs the latest stable version of Bazel. You can install specific, older versions of Bazel in addition to the latest one, such as this:

sudo apt install bazel-1.0.0

This installs Bazel 1.0.0 as /usr/bin/bazel-1.0.0 on your system. This can be useful if you need a specific version of Bazel to build a project, for example because it uses a .bazelversion file to explicitly state with which Bazel version it should be built.

Optionally, you can set bazel to a specific version by creating a symlink:

sudo ln -s /usr/bin/bazel-1.0.0 /usr/bin/bazel
bazel --version  # 1.0.0

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

配置opencv编译选项，打开mediapipe-master/third_party/opencv_linux.BUILD。取消注释，若为手动编译安装opencv，应该选择最后一项，例如include/opencv4/：

# Description:
#   OpenCV libraries for video/image processing on Linuxlicenses(["notice"])  # BSD licenseexports_files(["LICENSE"])# The following build rule assumes that OpenCV is installed by
# 'apt-get install libopencv-core-dev libopencv-highgui-dev \'
# '                libopencv-calib3d-dev libopencv-features2d-dev \'
# '                libopencv-imgproc-dev libopencv-video-dev'
# on Debian Buster/Ubuntu 18.04.
# If you install OpenCV separately, please modify the build rule accordingly.
cc_library(name = "opencv",hdrs = glob([# For OpenCV 4.x#"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 = [# For OpenCV 4.x#"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",],visibility = ["//visibility:public"],
)

运行 [Hello World! in C++ 示例](https://ai.google.dev/edge/mediapipe/framework/getting_started/hello_world_cpp.md?hl=zh-cn)。```bash
$ 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
```

在 GPU 上运行

注意：此命令目前仅适用于 Linux，请先按照在 Linux 桌面上设置 OpenGL ES 进行操作。

例如，如需构建带 GPU 的旧版 MediaPipe 手部检测解决方案的 C++ 示例应用，请运行以下命令：

bazel build -c opt --copt -DMESA_EGL_NO_X11_HEADERS --copt -DEGL_NO_X11 \mediapipe/examples/desktop/hand_tracking:hand_tracking_gpu

如需运行该应用，请执行以下操作：
```
GLOG_logtostderr=1 bazel-bin/mediapipe/examples/desktop/hand_tracking/hand_tracking_gpu \--calculator_graph_config_file=mediapipe/graphs/hand_tracking/hand_tracking_desktop_live_gpu.pbtxt
```
只要摄像头已连接并开启，这就会打开摄像头。出现任何错误都可能是因为无法访问摄像头，或 GPU 驱动程序未正确设置。

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