Understanding make when using darknet YOLOv3 GPU

The environment is
Ubuntu 16.04
CUDA 9.1
Opencv3.3.0

I tried to use YOLOv3 using GPU, but I got an error in make.
What I did below

 git clone https://github.com/pjreddie/darknet
cd darknet
Change to vim Makefile#GPU=1, OPENCV=1
make

Error Contents

gcc-Iinclude/-Isrc/-DOPENCV`pkg-config --cflags opencv`-DGPU-I/usr/local/cuda-9.1/include/-Wall-Wno-unused-result-Wno-unknown-pragmas-Watal-errors-fstICP-DV/OV/DVpulm.
File included from /usr/local/include/opencv2/core/types_c.h:59:0 ,
                 from /usr/local/include/opencv2/core/core_c.h:48,
                 from/usr/local/include/opencv2/highgui/highgui_c.h:45,
                 from include/darknet.h:25,
                 from./src/utils.h —5,
                 from./src/gemm.c:2:
/usr/local/include/opencv2/core/cvdef.h:485:1:error:unknown type name 'namespace'
 namespace cv {
compilation terminated due to-Wfatal-errors.
Makefile:85: recipe for target'obj/gemm.o'failed
make:***[obj/gemm.o]Error1

ubuntu deep-learning gpu

2022-09-30 16:35

2 Answers

In conclusion, I was able to run darknet make in Opencv 3.4.0.
I don't know which one really worked because I've tried many things, but I'll write down what I did I do.
In the darknet Makefile, first set OPENCV=1 and set the others to 0 to make.
After make can be executed, make clean.
Finally, in the darknet Makefile, OPENCV=1, GPU=1 and make to run it.

2022-09-30 16:35

OpenCV related error.The OpenCV namespace itself has not been found, so I think OpenCV is probably not well recognized.Review the configuration settings around OpenCV.

Also, the version is different from this question, but OpenCV 3.4.1 has a bug and cannot be built.Wait for it to fix or downgrade (Reference).The same version of OpenCV 3.3.0, which is the same as this question, has been successfully built in this environment.

2022-09-30 16:35

If you have any answers or tips

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