67 lines
2.5 KiB
ReStructuredText
67 lines
2.5 KiB
ReStructuredText
MediaPipe
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=====================================
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`MediaPipe <http://github.com/google/mediapipe>`_ is a graph-based framework for
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building multimodal (video, audio, and sensor) applied machine learning pipelines.
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MediaPipe is cross-platform running on mobile devices, workstations and servers,
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and supports mobile GPU acceleration. With MediaPipe, an applied
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machine learning pipeline can be built as a graph of modular components,
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including, for instance, inference models and media processing functions. Sensory
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data such as audio and video streams enter the graph, and perceived descriptions
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such as object-localization and face-landmark streams exit the graph. An example
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graph that performs real-time hand tracking on mobile GPU is shown below.
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.. image:: images/mobile/hand_tracking_mobile.png
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:width: 400
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:alt: Example MediaPipe graph
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MediaPipe is designed for machine learning (ML) practitioners, including
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researchers, students, and software developers, who implement production-ready
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ML applications, publish code accompanying research work, and build technology
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prototypes. The main use case for MediaPipe is rapid prototyping of applied
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machine learning pipelines with inference models and other reusable components.
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MediaPipe also facilitates the deployment of machine learning technology into
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demos and applications on a wide variety of different hardware platforms
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(e.g., Android, iOS, workstations).
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APIs for MediaPipe
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* Calculator API in C++
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* Graph Construction API in ProtoBuf
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* (Coming Soon) Graph Construction API in C++
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* Graph Execution API in C++
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* Graph Execution API in Java (Android)
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* Graph Execution API in Objective-C (iOS)
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Alpha Disclaimer
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==================
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MediaPipe is currently in alpha for v0.6. We are still making breaking API changes and expect to get to stable API by v1.0. We recommend that you target a specific version of MediaPipe, and periodically bump to the latest release. That way you have control over when a breaking change affects you.
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User Documentation
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==================
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.. toctree::
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:maxdepth: 3
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getting_started/install
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Examples <examples>
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tools/visualizer
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tools/tracing_and_profiling
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tools/performance_benchmarking
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getting_started/help
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getting_started/faq
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getting_started/troubleshooting
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framework_concepts/framework_concepts
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framework_concepts/calculators
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framework_concepts/graphs
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framework_concepts/packets
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framework_concepts/synchronization
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framework_concepts/gpu
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license
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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