Performance Issues on Jetson Xavier NX

[MsWik]

CV 4.5.0 + CUDA, jetpack 4.5.1. Low performance of models like yolo4, yolo4x (lower than in the original darcnet), performance of tiny models is correct. Also, when I try to convention any model in INT8, I get the following error: failed to open  /home/andry/test_jetson_xavier/tkDNN-master/tkDNN/src/Int8BatchStream.cpp:69 Aborting...

[perseusdg]

Regarding the int8 model conversion ,have you downloaded the dataset and followed the steps mentioned in the Readme? Cause it looks there is a problem with your dataFilePath for image paths

And about the low performance on Xavier nx ...are you using the current master branch ?

[MsWik]

FP16 / FP32 dimension models are obtained correctly, the error occurs only when I use INT8. yes, the current master branch is used

[MsWik]

Yolo 4, yolo 4x performance issue resolved by reinstalling tkDNN, int8 issue not resolved yet.

[mive93]

@MsWik have you downloaded the dataset as suggested by @perseusdg ? Have you exported the needed env variables as explained here?

I tested everything yesterday on a Jetson Xavier AGX and I got no problems.