  Building applications that perceive the world around them is challenging. A
developer needs to (a) select and develop corresponding machine learning
algorithms and models, (b) build a series of prototypes and demos, (c) balance
resource consumption against the quality of the solutions, and finally (d)
identify and mitigate problematic cases. The MediaPipe framework addresses all
of these challenges. A developer can use MediaPipe to build prototypes by
combining existing perception components, to advance them to polished
cross-platform applications and measure system performance and resource
consumption on target platforms. We show that these features enable a developer
to focus on the algorithm or model development and use MediaPipe as an
environment for iteratively improving their application with results
reproducible across different devices and platforms. MediaPipe will be
open-sourced at https://github.com/google/mediapipe.
