I have Jetson TX2 with JetPack 3.3, TensorRT 4 and CUDA 9
dpkg -l | grep tensorrt
ii tensorrt 4.0.2.0-1+cuda9.0 arm64 Meta package of TensorRT
Following the tutorial here : https://github.com/NVIDIA-AI-IOT/deepstream_reference_apps/tree/master/yolo , I got several problems.
First, the table on Readme file says that if I only want to use TRT stand alone app, I don’t need deepstream and CUDA 10.
jetson-TX1/TX2 trt-yolo-app Not required Jetpack 3.3 (Cuda 9.0, TensorRT 4, OpenCV 3.3)
But when I build using CMAKE, in CMakeLists.txt line 36 (https://github.com/NVIDIA-AI-IOT/deepstream_reference_apps/blob/master/yolo/apps/trt-yolo/CMakeLists.txt) , you can see that CUDA 10 is required.
find_package(CUDA 10.0 EXACT REQUIRED cudart cublas curand)
Why is CUDA 10 required meanwhile the readme file says CUDA 9 is required?
Second, I changed the CMakeLists.txt so it will accept CUDA 9. When I did sudo make install it gave error like this :
In file included from /home/boulderai/deepstream_reference_apps/yolo/lib/ds_image.h:28:0,
from /home/boulderai/deepstream_reference_apps/yolo/lib/calibrator.h:29,
from /home/boulderai/deepstream_reference_apps/yolo/lib/calibrator.cpp:26:
/home/boulderai/deepstream_reference_apps/yolo/lib/trt_utils.h:84:22: error: ‘nvinfer1::DimsHW YoloTinyMaxpoolPaddingFormula::compute(nvinfer1::DimsHW, nvinfer1::DimsHW, nvinfer1::DimsHW, nvinfer1::DimsHW, nvinfer1::DimsHW, const char*) const’ marked ‘override’, but does not override
nvinfer1::DimsHW compute(nvinfer1::DimsHW inputDims, nvinfer1::DimsHW kernelSize,
^
compilation terminated due to -Wfatal-errors.
lib/CMakeFiles/yolo-lib.dir/build.make:69: recipe for target 'lib/CMakeFiles/yolo-lib.dir/calibrator.cpp.o' failed
make[2]: *** [lib/CMakeFiles/yolo-lib.dir/calibrator.cpp.o] Error 1
CMakeFiles/Makefile2:127: recipe for target 'lib/CMakeFiles/yolo-lib.dir/all' failed
make[1]: *** [lib/CMakeFiles/yolo-lib.dir/all] Error 2
Makefile:129: recipe for target 'all' failed
make: *** [all] Error 2
As far as I know, this problem is related to either Jetson Xavier or TensorRT 5, then why did I get this problem? Thank you.