AlexeyAB / darknet

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
http://pjreddie.com/darknet/
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darknet.sln doesn't build successfully in Release ×64 on win10 #3477

Open yilanwanglu opened 5 years ago

yilanwanglu commented 5 years ago

I try to compile darknet following your intructions on VS2015 but when I build darknet.sln in Release×64 mode,the error happen. Environment:Win10 opencv3.4.0 VS2015 CUDA8.0 Cudnn6.0.

identifier "__shfl_xor" is undefined darknet

MSB3721 命令“"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin\nvcc.exe" -gencode=arch=compute_20,code=\"sm_20,compute_20\" --use-local-env --cl-version 2015 -ccbin "D:\vs\VC\bin\x86_amd64" -I"C:\Program Files (x86)\Windows Kits\10\Include\10.0.10150.0\ucrt" -I\include -IC:\opencv_3.0\opencv\build\include -I....\include -I....\3rdparty\stb\include -I....\3rdparty\pthreads\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -cudart static -DOPENCV -DCUDNN_HALF -DCUDNN -D_TIMESPEC_DEFINED -D_SCL_SECURE_NO_WARNINGS -D_CRT_SECURE_NO_WARNINGS -D_CRT_RAND_S -DGPU -DWIN32 -D_CONSOLE -D_LIB -D_MBCS -Xcompiler "/EHsc /W3 /nologo /O2 /FS /Zi /MD " -o x64\Release\convolutional_kernels.cu.obj "G:\YOLO\darknet-master\src\convolutional_kernels.cu"”已退出,返回代码为 2。

identifier "__shfl" is undefined

AlexeyAB commented 5 years ago

@yilanwanglu

MSB3721 命令“"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin\nvcc.exe" -gencode=arch=compute_20,code="sm_20,compute_20" -

GPU with Compute Capability 2.0 doesn't support __shfl_xor() CUDA-function. So you should compile with CC 3.0 or higher and use GPU with 3.0 or higher: https://en.wikipedia.org/wiki/CUDA#GPUs_supported