链接：
Clion+Opencv3.2终极配置教程 - 简书 (jianshu.com)
CMAKE代码
# OpenCV
set(OpenCV_DIR "your\\opencv\\path")
# set(OpenCV_DIR "D:\\software\\opencv\\opencv\\mingw-build")
find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})
add_executable(TwoSum main.cpp)
target_link_libraries(TwoSum ${OpenCV_LIBS})
LibTorch C++ API使用
安装cuda和cudnn
给出教程
CMAKE代码
需要执行build文件夹下面的exe文件时，需要将dll文件拷贝过来。由于其过程繁琐，故直接将其写入cmake中，这样就可以在加载cmake时就将需要的dll文件拷贝到build文件夹下。
cmake_minimum_required(VERSION 3.22)
project(libtorch_test) # 项目名称
set(CMAKE_CXX_STANDARD 14) # CMAKE版本
# LibTorch
set(CMAKE_PREFIX_PATH "D:\\software\\libtorch 1.11\\libtorch\\share\\cmake\\Torch") # prefix path
find_package(Torch REQUIRED) # 找到Torch
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}")
add_executable(libtorch_test main.cpp) # 添加可执行文件
target_link_libraries(libtorch_test "${TORCH_LIBRARIES}") # 链接库
set_property(TARGET libtorch_test PROPERTY CXX_STANDARD 14)
# copy cuda and cudnn dll files to cmake-build-debug(or release)
# The following code block is suggested to be used on Windows.
# According to https://github.com/pytorch/pytorch/issues/25457,
# the DLLs need to be copied to avoid memory errors.
# add this codeblock at the end.
if (MSVC)
file(GLOB TORCH_DLLS "${TORCH_INSTALL_PREFIX}/lib/*.dll")
add_custom_command(TARGET libtorch_test
POST_BUILD
COMMAND ${CMAKE_COMMAND} -E copy_if_different
${TORCH_DLLS}
$<TARGET_FILE_DIR:libtorch_test>)
endif (MSVC)
测试代码
#include <iostream>
#include <torch/torch.h>
int main() {
auto x = torch::randn({2, 2});
x = x.to(torch::kCUDA);
std::cout << x << std::endl;
}
输出：
