Warning: gst-core-error-quark: A lot of buffers are being dropped. (13)

Accelerated Computing Intelligent Video Analytics DeepStream SDK
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• Hardware Platform (Jetson / GPU) Jetson Xavier NX

• DeepStream Version 5.0

• JetPack Version (valid for Jetson only) R32 Revision: 5.0 GCID: 25531747 Board: t186ref

• TensorRT Version 7.1.3 + CUDA 10.2

• Issue Type( questions, new requirements, bugs) Warning: gst-core-error-quark: A lot of buffers are being dropped. (13): gstbasesink.c(2902): gst_base_sink_is_too_late (): /GstPipeline:pipeline0/GstEglGlesSink:nvvideo-renderer: There may be a timestamping problem, or this computer is too slow

• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing) please see below

• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description) please see below

Hi Deepstream team,

I am not sure if I should attach my code or just ask this to troubleshoot, so before I did, I wanted to ask first.
Would there be a common reason why this error would show up?
Warning: gst-core-error-quark: A lot of buffers are being dropped. (13): gstbasesink.c(2902): gst_base_sink_is_too_late (): /GstPipeline:pipeline0/GstEglGlesSink:nvvideo-renderer: There may be a timestamping problem, or this computer is too slow

I am running this example (Creating a Real-Time License Plate Detection and Recognition App | NVIDIA Technical Blog) in Python with some additional code I am running.

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Yes. The reason is that the loading is heavy and performance is poor so the pipeline has to drop frames to get itself running.

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@Fiona.Chen
Thanks for the quick response.
Is there a way to fix this then? Am i doing too much on each frame which causes this issue?

As I mentioned - I am running this example (Creating a Real-Time License Plate Detection and Recognition App | NVIDIA Developer Blog) in Python.

Would you need some more information to find what might be causing the issue and how to fix it?

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The original app is in c/c++, There is already performance data in the page. (Creating a Real-Time License Plate Detection and Recognition App | NVIDIA Developer Blog.

We don’t know how you run it with python, but python is less efficient than c/c++ in general.