![]() The pose estimation model, for example, takes a lower, fixed resolution video frame (256x256) as input. However, because of their different specializations, the input to one component is not well-suited for the others. ![]() The MediaPipe Holistic pipeline integrates separate models for pose, face and hand components, each of which are optimized for their particular domain. Combining them all in real-time into a semantically consistent end-to-end solution is a uniquely difficult problem requiring simultaneous inference of multiple, dependent neural networks. MediaPipe already offers fast and accurate, yet separate, solutions for these tasks. Live perception of simultaneous human pose, face landmarks, and hand tracking in real-time on mobile devices can enable various modern life applications: fitness and sport analysis, gesture control and sign language recognition, augmented reality try-on and effects. This site uses Just the Docs, a documentation theme for Jekyll.
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