• Hardware Platform (Jetson / GPU): Jetson Nano
• DeepStream Version: 5.01
• JetPack Version (valid for Jetson only): 4.4
• TensorRT Version: N/A
• NVIDIA GPU Driver Version (valid for GPU only): N/A
• Issue Type( questions, new requirements, bugs): questions
By looking at the deepstream-imagedata-multistream sample, I am able to retrieve a frame image as an
numpy.ndarray object using
Now I want to do some calculation on it and modify the output buffer.
It seems modifying the ndarray in place does not work.
How can I achieve that?
You need to use NvBufSurfaceSyncForDevice() to put the modified array back.
Thanks. How can I retrieve a
NvBufSurface pointer, which is expected as an argument to
Seems it is not suitable to use pyds.get_nvds_buf_surface() which is a integrated interface.
You can refer to the C/C++ sample Deepstream sample code snippet, and try to translate them into python.
The available python bindings of pyds can be found Deepstream Python API Reference — Deepstream Deepstream Version: 6.1.1 documentation
How can I configure
pyds.NvBufSurfaceCreateParams in Python as in the C++ code?
It seems its properties are read-only.
Traceback (most recent call last):
File "run.py", line 394, in test_probe
params.gpuId = 0
AttributeError: can't set attribute
We don’t have such bindings. You can modify the input buffer directly without the intermediate buffer then you don’t need the pyds.NvBufSurfaceCreateParams.
Could you give a bit more detail?
How can I retrieve the input buffer (pointer?) without using
I checked again. We don’t have the related python bindings, seems it does not work.
OK. Thank you for clarification!