SLOW Semantic Segmentation on NVIDIA DRIVE Open Script
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Paolo Rosettani
el 27 de Sept. de 2022
Comentada: Hariprasad Ravishankar
el 3 de Oct. de 2022
Hello,
I'm using a NVIDIA Jetson AGX Xavier
I'm trying the Semantic Segmentation on NVIDIA DRIVE Open Script: https://it.mathworks.com/help/supportpkg/nvidia/ug/semantic-segmentation-on-nvidia-drive.html
I've only chaned the
opencv_link_flags = '`pkg-config --cflags --libs opencv`';
to
opencv_link_flags = '`pkg-config --cflags --libs opencv4`';
because without it it doesn't compile.
There is another problem: Why the FPS are so slow? Mine goes at 0.39 FPS (as shown in the screenshot below)
I've checked the screenshot in the example and it goes at 8.73 FPS.
Thank you for your help.
Paolo R
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Hariprasad Ravishankar
el 30 de Sept. de 2022
Hi Paolo,
Can you try setting the deep learning target library to TensorRT?
cfg = coder.gpuConfig('exe');
cfg.DeepLearningConfig = coder.DeepLearningConfig(TargetLibrary = 'tensorrt');
Hari
1 comentario
Hariprasad Ravishankar
el 3 de Oct. de 2022
In addition to this, you can also try the following to get a little bit more peformance.
1.TensorRT FP16 mode. Note that FP16 computation can result in lower accuracy from baseline FP32 computation.
cfg = coder.gpuConfig('exe');
dlcfg = coder.DeepLearningConfig(TargetLibrary = 'tensorrt');
dlcfg.DataType = 'FP16';
cfg.DeepLearningConfig = dlcfg;
2.You can use the nvpmodel tool to change the clock mode
For example:
sudo nvpmodel -m 0
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