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Cross-platform, customizable ML solutions for live and streaming media. Forked for Unreal Engine embed usage.

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MediaPipe


Live ML anywhere

MediaPipe offers cross-platform, customizable ML solutions for live and streaming media.

accelerated.png cross_platform.png
End-to-End acceleration: Built-in fast ML inference and processing accelerated even on common hardware Build once, deploy anywhere: Unified solution works across Android, iOS, desktop/cloud, web and IoT
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Ready-to-use solutions: Cutting-edge ML solutions demonstrating full power of the framework Free and open source: Framework and solutions both under Apache 2.0, fully extensible and customizable

ML solutions in MediaPipe

Face Detection Face Mesh Iris Hands Pose Holistic
face_detection face_mesh iris hand pose hair_segmentation
Hair Segmentation Object Detection Box Tracking Instant Motion Tracking Objectron KNIFT
hair_segmentation object_detection box_tracking instant_motion_tracking objectron knift
Android iOS C++ Python JS Coral
Face Detection
Face Mesh
Iris
Hands
Pose
Holistic
Selfie Segmentation
Hair Segmentation
Object Detection
Box Tracking
Instant Motion Tracking
Objectron
KNIFT
AutoFlip
MediaSequence
YouTube 8M

See also MediaPipe Models and Model Cards for ML models released in MediaPipe.

Getting started

To start using MediaPipe solutions with only a few lines code, see example code and demos in MediaPipe in Python and MediaPipe in JavaScript.

To use MediaPipe in C++, Android and iOS, which allow further customization of the solutions as well as building your own, learn how to install MediaPipe and start building example applications in C++, Android and iOS.

The source code is hosted in the MediaPipe Github repository, and you can run code search using Google Open Source Code Search.

Publications

Videos

Events

Community

Alpha disclaimer

MediaPipe is currently in alpha at v0.7. We may be still making breaking API changes and expect to get to stable APIs by v1.0.

Contributing

We welcome contributions. Please follow these guidelines.

We use GitHub issues for tracking requests and bugs. Please post questions to the MediaPipe Stack Overflow with a mediapipe tag.

Debug Firefly

# 编译项目
bazel build --define MEDIAPIPE_DISABLE_GPU=1 --action_env PYTHON_BIN_PATH="D://Software//python//python.exe" mediapipe/examples/desktop/firefly_link

# 运行项目
bazel-bin/mediapipe/examples/desktop/firefly_link/firefly_link.exe

曾经做过的事情:

  • geometry_pipeline_metadata_landmarks.binarypb找不到:
# 编译依赖模型(不明白为啥要手动编译)
bazel build --action_env PYTHON_BIN_PATH="D://Software//python//python.exe" -c opt --define MEDIAPIPE_DISABLE_GPU=0 --copt -DMESA_EGL_NO_X11_HEADERS --copt -DEGL_NO_X11 mediapipe/modules/face_geometry/data:geometry_pipeline_metadata

然后手动找出来该文件并复制到目标地点。

调试

bazel build --define MEDIAPIPE_DISABLE_GPU=1 --action_env PYTHON_BIN_PATH="D://Software//python//python.exe" mediapipe/examples/desktop/firefly_link:firefly_link.dll

可以找到对应的dll和pdb一起复制到目标地点。

发布

bazel build --compilation_mode=opt --define MEDIAPIPE_DISABLE_GPU=1 --action_env PYTHON_BIN_PATH="D://Software//python//python.exe" mediapipe/examples/desktop/firefly_link:firefly_link.dll

然后找到dll(没有pdb)复制到目标地点

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Cross-platform, customizable ML solutions for live and streaming media. Forked for Unreal Engine embed usage.

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