CMakeLists.txt文件详解

CMakeLists.txt 文件是用于描述 CMake 构建过程和项目配置的文件。它包含了一系列 CMake 命令、变量设置和流程控制结构，用于告诉 CMake 如何生成适合你的平台和编译器的构建系统文件。

CMakeListss.txt示例文件讲解：

# 声明要求的cmake最低版本
cmake_minimum_required(VERSION 2.6) 
# 声明cmake工程名字
project(pro)  

# 用于控制编译流程
option(CUDA_USE_STATIC_CUDA_RUNTIME OFF)
# set(KEY, VALUE) 设置标准
set(CMAKE_CXX_STANDARD 11) 
# 设置cmake编译模式，有debug和release两种 
set(CMAKE_BUILD_TYPE Debug)   
# 设置生成的可执行二进制文件存放的目录
set(EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/workspace)  

# 如果要支持python则设置python路径
set(HAS_PYTHON ON)
set(PythonRoot "/datav/software/anaconda3")
set(PythonName "python3.9")

# 如果你是不同显卡，请设置为显卡对应的号码参考这里：https://developer.nvidia.com/zh-cn/cuda-gpus#compute
#set(CUDA_GEN_CODE "-gencode=arch=compute_75,code=sm_75")

# 如果你的opencv找不到，可以自己指定目录
set(OpenCV_DIR   "/datav/lean/opencv-4.2.0/lib/cmake/opencv4/")

set(CUDA_TOOLKIT_ROOT_DIR     "/datav/lean/cuda-11.2")
set(CUDNN_DIR    "/datav/lean/cudnn8.2.4.15-cuda11.4")
set(TENSORRT_DIR "/datav/lean/TensorRT-8.2.3.0-cuda11.4-cudnn8.2")

# 因为protobuf，需要用特定版本，所以这里指定路径
set(PROTOBUF_DIR "/datav/lean/protobuf3.11.4")

# 寻找和配置依赖库
find_package(CUDA REQUIRED)
find_package(OpenCV)

# 设置头文件目录
include_directories(
    ${PROJECT_SOURCE_DIR}/src
    ${PROJECT_SOURCE_DIR}/src/application
    ${PROJECT_SOURCE_DIR}/src/tensorRT
    ${PROJECT_SOURCE_DIR}/src/tensorRT/common
    ${OpenCV_INCLUDE_DIRS}
    ${CUDA_TOOLKIT_ROOT_DIR}/include
    ${PROTOBUF_DIR}/include
    ${TENSORRT_DIR}/include
    ${CUDNN_DIR}/include
)  

# 切记，protobuf的lib目录一定要比tensorRT目录前面，因为tensorRTlib下带有protobuf的so文件，这可能带来错误
# 把该目录设置为链接目录
link_directories(
    ${PROTOBUF_DIR}/lib
    ${TENSORRT_DIR}/lib
    ${CUDA_TOOLKIT_ROOT_DIR}/lib64
    ${CUDNN_DIR}/lib
)  

# 条件判断
if("${HAS_PYTHON}" STREQUAL "ON")
    message("Usage Python ${PythonRoot}")  # 打印信息
    include_directories(${PythonRoot}/include/${PythonName})
    link_directories(${PythonRoot}/lib)
    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DHAS_PYTHON")
endif()

# 添加c++11标准支持
set(CMAKE_CXX_FLAGS  "${CMAKE_CXX_FLAGS} -std=c++11 -Wall -O0 -Wfatal-errors -pthread -w -g")
set(CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS} -std=c++11 -O0 -Xcompiler -fPIC -g -w ${CUDA_GEN_CODE}")
file(GLOB_RECURSE cpp_srcs ${PROJECT_SOURCE_DIR}/src/*.cpp)
file(GLOB_RECURSE cuda_srcs ${PROJECT_SOURCE_DIR}/src/*.cu)
# 使用CUDA_ADD_LIBRARY取代原来的ADD_LIBRARY
cuda_add_library(plugin_list SHARED ${cuda_srcs})
# 将库文件链接到可执行程序上
target_link_libraries(plugin_list nvinfer nvinfer_plugin)  
target_link_libraries(plugin_list cuda cublas cudart cudnn)
target_link_libraries(plugin_list protobuf pthread)
target_link_libraries(plugin_list ${OpenCV_LIBS})

# 添加一个可执行程序
add_executable(pro ${cpp_srcs})

# 如果提示插件找不到，请使用dlopen(xxx.so, NOW)的方式手动加载可以解决插件找不到问题
target_link_libraries(pro nvinfer nvinfer_plugin)
target_link_libraries(pro cuda cublas cudart cudnn)
target_link_libraries(pro protobuf pthread plugin_list)
target_link_libraries(pro ${OpenCV_LIBS})

if("${HAS_PYTHON}" STREQUAL "ON")
    set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/example-python/pytrt)
    add_library(pytrtc SHARED ${cpp_srcs})
    target_link_libraries(pytrtc nvinfer nvinfer_plugin)
    target_link_libraries(pytrtc cuda cublas cudart cudnn)
    target_link_libraries(pytrtc protobuf pthread plugin_list)
    target_link_libraries(pytrtc ${OpenCV_LIBS})
    target_link_libraries(pytrtc "${PythonName}")
    target_link_libraries(pro "${PythonName}")
endif()

# 添加一个没有输出的target，以便始终构建它
add_custom_target(
    yolo
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro yolo
)

add_custom_target(
    yolo_gpuptr
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro yolo_gpuptr
)

add_custom_target(
    yolo_fast
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro yolo_fast
)

add_custom_target(
    centernet
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro centernet
)

add_custom_target(
    alphapose 
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro alphapose
)

add_custom_target(
    retinaface
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro retinaface
)

add_custom_target(
    dbface
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro dbface
)

add_custom_target(
    arcface 
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro arcface
)

add_custom_target(
    bert 
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro bert
)

add_custom_target(
    fall
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro fall_recognize
)

add_custom_target(
    scrfd
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro scrfd
)

add_custom_target(
    lesson
    DEPENDS pro
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/workspace
    COMMAND ./pro lesson
)

add_custom_target(
    pyscrfd
    DEPENDS pytrtc
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/example-python
    COMMAND python test_scrfd.py
)

add_custom_target(
    pyinstall
    DEPENDS pytrtc
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/example-python
    COMMAND python setup.py install
)

add_custom_target(
    pytorch
    DEPENDS pytrtc
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/example-python
    COMMAND python test_torch.py
)

add_custom_target(
    pyyolov5
    DEPENDS pytrtc
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/example-python
    COMMAND python test_yolov5.py
)

add_custom_target(
    pycenternet
    DEPENDS pytrtc
    WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/example-python
    COMMAND python test_centernet.py
)