TEMPLATE = app CONFIG += console c++11 CONFIG -= app_bundle CONFIG -= qt TARGET = cudaQTS CUDA_SOURCES += main.cu INCLUDEPATH += /usr/include/opencv4 #添加头文件路径 LIBS += -L/usr/lib/aarch64-linux-gnu -lopencv_core -lopencv_imgcodecs -lopencv_imgproc -lopencv_highgui -lopencv_objdetect #添加需要链接的库 LIBS += -L"/usr/local/lib" -L"/usr/local/cuda/lib64" -lcudart -lcufft CUDA_SDK = "/usr/local/cuda-10.2/" # Path to cuda SDK install CUDA_DIR = "/usr/local/cuda-10.2/" # Path to cuda toolkit install #####系统类型,计算能力########### SYSTEM_NAME = linux # Depending on your system either ‘Win32‘, ‘x64‘, or ‘Win64‘ SYSTEM_TYPE = 64 # ‘32‘ or ‘64‘, depending on your system CUDA_ARCH = sm_53 # Type of CUDA architecture, for example ‘compute_10‘, ‘compute_11‘, ‘sm_10‘ NVCC_OPTIONS = --use_fast_math INCLUDEPATH += $$CUDA_DIR/include QMAKE_LIBDIR += $$CUDA_DIR/lib64/ CUDA_OBJECTS_DIR = ./ CUDA_LIBS = cudart cufft CUDA_INC = $$join(INCLUDEPATH,‘" -I"‘,‘-I"‘,‘"‘) NVCC_LIBS = $$join(CUDA_LIBS,‘ -l‘,‘-l‘, ‘‘) CONFIG(debug, debug|release) { # Debug mode cuda_d.input = CUDA_SOURCES cuda_d.output = $$CUDA_OBJECTS_DIR/${QMAKE_FILE_BASE}_cuda.o cuda_d.commands = $$CUDA_DIR/bin/nvcc -D_DEBUG $$NVCC_OPTIONS $$CUDA_INC $$NVCC_LIBS --machine $$SYSTEM_TYPE -arch=$$CUDA_ARCH -c -o ${QMAKE_FILE_OUT} ${QMAKE_FILE_NAME} cuda_d.dependency_type = TYPE_C QMAKE_EXTRA_COMPILERS += cuda_d } else { # Release mode cuda.input = CUDA_SOURCES cuda.output = $$CUDA_OBJECTS_DIR/${QMAKE_FILE_BASE}_cuda.o cuda.commands = $$CUDA_DIR/bin/nvcc $$NVCC_OPTIONS $$CUDA_INC $$NVCC_LIBS --machine $$SYSTEM_TYPE -arch=$$CUDA_ARCH -O3 -c -o ${QMAKE_FILE_OUT} ${QMAKE_FILE_NAME} cuda.dependency_type = TYPE_C QMAKE_EXTRA_COMPILERS += cuda } DISTFILES += main.cu
NVIDIA Tegra X1 下OPencv+GPU在QT下配置
原文:https://www.cnblogs.com/almn/p/14964978.html