RGB process on nvmedia 2D engine

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Software Version
[*] DRIVE OS Linux 5.2.0
DRIVE OS Linux 5.2.0 and DriveWorks 3.5
NVIDIA DRIVE™ Software 10.0 (Linux)
NVIDIA DRIVE™ Software 9.0 (Linux)
other DRIVE OS version
other

Target Operating System
[*] Linux
QNX
other

Hardware Platform
[*] NVIDIA DRIVE™ AGX Xavier DevKit (E3550)
NVIDIA DRIVE™ AGX Pegasus DevKit (E3550)
other

SDK Manager Version
1.5.0.7774
other

Host Machine Version
[*] native Ubuntu 18.04
other

We found Image 2D engine only support below surface component which doesn’t include RGB items.
So if we want to yuv422p to RGB converting, with the help of Image 2D we can convert from yuv422p to RGBA stream. About the rest of converting from RGBA to RGB, except software code method(low performance, cpu costing and time consuming), is there any hardware engine we can apply?

Is there any plan to image 2D support RGB as supported component?

Preformatted textSource surface component order:

1: NVM_SURF_ATTR_COMPONENT_ORDER_LUMA
2: NVM_SURF_ATTR_COMPONENT_ORDER_YUV
3: NVM_SURF_ATTR_COMPONENT_ORDER_YVU
4: NVM_SURF_ATTR_COMPONENT_ORDER_YUYV
5: NVM_SURF_ATTR_COMPONENT_ORDER_YVYU
6: NVM_SURF_ATTR_COMPONENT_ORDER_VYUY
10: NVM_SURF_ATTR_COMPONENT_ORDER_VUYX
18: NVM_SURF_ATTR_COMPONENT_ORDER_RGBA
20: NVM_SURF_ATTR_COMPONENT_ORDER_BGRA

Dear @Peter_Pertrili,
AFAIK, we do not have APIs for RGBA → RGB conversion. I will check with engineering team and update you if there is any plan to support it in future plan.

BTW, May I know, why do you need RGBA → RGB conversion? Could you share your use case here or via private message for better guidance.

@SivaRamaKrishnaNV
Two main reasons:
1.Our deep learn need to be feed with RGB stream.
2.Our display use RGB for picture review.
Therefore our original goal is use 2D to convert yuv422p to RGB…

Can we let 2D support RGB output directly without one more RGBA to RGB conversion?

Dear @Peter_Pertrili,
Currently, you can get only RGBA image from NVmedia. You can send NVmedia Image to CUDA using EGLStream and convert RGBA → RGB buffer on GPU by writing a CUDA kernel before feeding it model.