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Mediapipe VS Nvidia's Deep Stream #37

ShettyHarapanahalli opened this issue Aug 21, 2019 · 1 comment


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commented Aug 21, 2019


Just curious to understand the differences between the Mediapipe and Deepstream (, are these both addressing the same problem space. Maybe solutions spaces could be different, but are problem spaces same?

Best Regards,


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commented Aug 21, 2019

Good question; at first glance, Medaipipe (MP) and DeepStream (DS) may seem similar. At the core of it, they both provide a framework that can run an inference task.
There are a few important differences:

  • Data types: DS supports only video/image streams, while MP operates on generic packets (which can include video, audio, image, primitives, or any user-defined object types)
  • Graphs: Data flow in both frameworks are described by a graph. DS is built on top of Gstreamer, which has a strictly linear pipeline model with very basic control flow. MP graphs offer more flexibility in design, and allows for very complex graph construction, including dynamic control flow and back edges.
  • Hardware/OS: DS is restricted to high-end desktop Nvidia GPUs (and appears to be Linux only). MP supports running on desktop/mobile CPUs and mobile GPUs (via OpenGL), and desktop GPU support is planned. MP runs on Android/iOS/Linux/OSX.
  • Tools: MP provides a powerful graph visualizer for interactive building and analyzing graphs, including graph performance tracing. I think DS relies on existing Gstreamer visualization tools like graphviz or dot (which is not interactive).
  • Plugins/Calculators: Each node in a DS pipeline is a Gstreamer filter (limited to how you write Gstreamer plugins). Each node in a MP graph is a Calculator, representing a very generic operation[s] to any or multiple packet stream types, also not limited to inference or even machine learning at all.

Hope that can help distinguish the two frameworks.

@jiuqiant jiuqiant closed this Aug 23, 2019

@mgyong mgyong added the general label Aug 27, 2019

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