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Building applications that perceive the world around them is challenging. Adeveloper needs to (a) select and develop corresponding machine learningalgorithms and models, (b) build a series of prototypes and demos, (c) balanceresource consumption against the quality of the solutions, and finally (d)identify and mitigate problematic cases. The MediaPipe framework addresses allof these challenges. A developer can use MediaPipe to build prototypes bycombining existing perception components, to advance them to polishedcross-platform applications and measure system performance and resourceconsumption on target platforms. We show that these features enable a developerto focus on the algorithm or model development and use MediaPipe as anenvironment for iteratively improving their application with resultsreproducible across different devices and platforms. MediaPipe will beopen-sourced at https://github.com/google/mediapipe.

MediaPipe: A Framework for Building Perception Pipelines