Accessing GPU buffers in deepstream filter on Jetson nano

Accelerated Computing Intelligent Video Analytics DeepStream SDK
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Hi! I’m trying to write a transform-in-place deepstream filter for processing NV12 frames on the Jetson nano with Deepstream 5.0.
I would like to access the NV12 frame from within CUDA kernels.

On dGPU this was simple, however on the Jetson I’m having trouble accessing these buffers. I understand I should go though the CUeglFrame structs.

I’ve done the cuGraphicsEGLRegisterImage and cuGraphicsResourceGetMappedEglFrame calls that seem to give sensible results.
However, whenever I then try to pass a GPU pointer from the CUeglFrame (i.e. egl_frame.frame.pPitch[0]) to a cuda kernel and access it, I get “CUDA error: unspecified launch failure”.

Apart from the commented out sections in the sample plugins, I cannot find an actual example of how to access these buffers. Am I missing a call that should happen before accessing the buffers?

Any help would be appreciated!
Davy

Jetson Nano 4GB
JetPack 4.5
Deepstream 5.0
Cuda 10.2
TensorRT 7.1.3
NVIDIA driver 32.4.4

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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)

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Small update for people with a similar issue:
after using the information and code in this post I managed to map the UV12 data to a CUsurfObject that I can read in a CUDA kernel.
Next question would be if there is a way to directly modify the UV12 data in a gstreamer buffer as well?

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please refer to opensource nvdspreprocess plugin. it will use CUeglFrame, NvBufSurfTransformAsync to do format conversion with hardware acceleration.

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Thank you for the reply!
The NvBufSurfTransformAsync() function only does basic operations like cropping/scaling or format conversion and is closed source. Is there any way to modify the actual pixels of a NvBufSurface directly in a CUDA kernel?
Thanks,
Davy

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please refer to this topic for “Use NvBufSurface together with a custom cuda kernel”.

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Thanks again for the reply.
The topic you referenced works for EGLFrames of type CU_EGL_FRAME_TYPE_PITCH.
However, in my case on the Jetson Nano, I’m receiving frames of type CU_EGL_FRAME_TYPE_ARRAY.
Simply converting the CUeglFrame.frame.pPitch[0] or CUeglFrame.frame.pArray[0] values to a uint8_t * pointer results in a “unspecified launch failure”.

But in the mean time I did find that by putting them in a CUsurfObject (using cuSurfObjectCreate) you can access them using the surf2Dread and surf2Dwrite functions, so this solves my issue.

Thanks for the help.

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