I am working on a traffic analytics project using Deepstream on a Jetson nano 2gb. I want to run my code using the deepstream app and not the python code which uses gstreamer. But I cannot find a good way to extract all the metadata and then easily extract information from it like how many cars or trucks passed down from one lane. Can anyone please suggest a solution apart from using additional services like Kafka ?
Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU)
• DeepStream Version
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only)
• Issue Type( questions, new requirements, bugs)
• 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)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)
Hardware- Jetson nano 2gb
Deepstream version-6.0.1
Jetpack version-4.6
Tensorrt version-8
I just installed deepstream with python bindings And I want to run my code using the deepstream app and not the python code which uses gstreamer. But I cannot find a good way to extract all the metadata and then easily extract information from it like how many cars or trucks passed down from one lane. Can anyone please suggest a solution apart from using additional services like Kafka ?
Can you refer /opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-test1/ for parse metadata?
Ya I can surely use that but I want to use deepstream using config files and there is also no proper documentation to form a python deepstream app for custom models or applications. If you can recommend any proper sources from where I can learn how to make a deepstream pipeline using python.
Can below sample helps:
I have seen these examples but I cannot understand the code exactly as the documentation is quite poor.
Are you familiar with buffer probes in Gstreamer? You can connect a buffer probe to an element after your inference component and you should be able to access all the metadata that you need.
How about you try to run this [python file](https://github.com/NVIDIA-AI-
IOT/deepstream_python_apps/blob/master/apps/deepstream-test2/deepstream_test_2.py).
You should be able to get all the object metadata that you need in this function.
This function uses some Deepstream data structures that are defined here:
NvDsObjectMeta — Deepstream Python ##DeepStream_VERSION## documentation
Yes I am familiar with the probe functions they were not easy to understand and I am working with deepstream for about 6 months and now the code makes sense. So you should improve the examples or give detailed api usage. The graph composer is pretty good actually. Thanks for the help.
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