windows编译运行教程

2020-08-28 13:17:39 +08:00 · 2020-08-28 13:17:39 +08:00 · 88d7ff971b
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+# windows编译运行手把手教程
+
+## 说明
+
+本教程可以用于https://github.com/wang-xinyu/tensorrtx该仓库中所有项目，只需要修改几处代码即可，修改之处后面会详细注明。
+
+## 所需环境
+
+* vs 版本可不限（仅测试了 vs2015 vs2017）
+
+* cuda
+
+* TensorRT需要和本机的cuda版本适配（需要7.0以上版本）
+
+* Cmake 
+
+* opencv （需要和vs版本适配）
+
+* 增加windows下的文件夹处理头文件dirent.h，放在当前文件下include下。下载地址 https://github.com/tronkko/dirent
+
+  ![image-20200828131208257](imgs/image-20200828131208257.png)
+
+## 编译
+
+### 修改CmakeLists.txt
+
+```cmake
+cmake_minimum_required(VERSION 2.6)
+
+project(yolov5) # 1
+set(OpenCV_DIR "D:\\opencv\\opencv346\\build")  #2
+set(TRT_DIR "D:\\TensorRT-7.0.0.11.Windows10.x86_64.cuda-10.2.cudnn7.6\\TensorRT-7.0.0.11")  #3
+
+add_definitions(-std=c++11)
+option(CUDA_USE_STATIC_CUDA_RUNTIME OFF)
+set(CMAKE_CXX_STANDARD 11)
+set(CMAKE_BUILD_TYPE Debug)
+
+set(THREADS_PREFER_PTHREAD_FLAG ON)
+find_package(Threads)
+
+#设置cuda信息
+find_package(CUDA REQUIRED)
+message(STATUS "    libraries: ${CUDA_LIBRARIES}")
+message(STATUS "    include path: ${CUDA_INCLUDE_DIRS}")
+
+include_directories(${CUDA_INCLUDE_DIRS})
+
+set(CUDA_NVCC_PLAGS ${CUDA_NVCC_PLAGS};-std=c++11; -g; -G;-gencode; arch=compute_75;code=sm_75)
+####
+enable_language(CUDA)  # 这一句添加后 ，就会在vs中不需要再手动设置cuda 
+####
+include_directories(${PROJECT_SOURCE_DIR}/include)
+include_directories(${TRT_DIR}\\include)
+
+#-D_MWAITXINTRIN_H_INCLUDED  解决error: identifier "__builtin_ia32_mwaitx" is undefined
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -Wall -Ofast -D_MWAITXINTRIN_H_INCLUDED")
+
+# 设置opencv的信息
+find_package(OpenCV QUIET
+    NO_MODULE
+    NO_DEFAULT_PATH
+    NO_CMAKE_PATH
+    NO_CMAKE_ENVIRONMENT_PATH
+    NO_SYSTEM_ENVIRONMENT_PATH
+    NO_CMAKE_PACKAGE_REGISTRY
+    NO_CMAKE_BUILDS_PATH
+    NO_CMAKE_SYSTEM_PATH
+    NO_CMAKE_SYSTEM_PACKAGE_REGISTRY
+)
+
+message(STATUS "OpenCV library status:")
+message(STATUS "    version: ${OpenCV_VERSION}")
+message(STATUS "    libraries: ${OpenCV_LIBS}")
+message(STATUS "    include path: ${OpenCV_INCLUDE_DIRS}")
+
+include_directories(${OpenCV_INCLUDE_DIRS})
+link_directories(${TRT_DIR}\\lib)
+
+add_executable(yolov5 ${PROJECT_SOURCE_DIR}/yolov5.cpp ${PROJECT_SOURCE_DIR}/yololayer.cu ${PROJECT_SOURCE_DIR}/yololayer.h 
+                ${PROJECT_SOURCE_DIR}/hardswish.cu ${PROJECT_SOURCE_DIR}/hardswish.h)   #4
+
+target_link_libraries(yolov5  "nvinfer" "nvinfer_plugin")   #5
+target_link_libraries(yolov5 ${OpenCV_LIBS})          #6
+target_link_libraries(yolov5 ${CUDA_LIBRARIES})   #7
+target_link_libraries(yolov5 Threads::Threads)       #8
+```
+
+注意：在CamakeLists.txt中，有8处需要修改，在#1-#8标注的位置
+
+1. #1 为当前编译的工程名，根据你所编译的工程名修改，也可以自定义
+2. #2 为本机的opencv地址
+3. #3 为本机TensorRT的安装位置
+4. #4 为当前编译工程中所涉及的文件，包括.cpp .cu .h等文件，另外第一个参数要与#1设置的相同
+5. #5 -#8 为链接lib，工程名需要和#1设置的一样。
+
+### cmake-gui编译
+
+#### 1 打开cmake-gui，并设置相应路径：如下图
+
+![image-20200828124434245](imgs/image-20200828124434245.png)
+
+#### 点击1处**Configure**，弹出窗口，并选择相应环境：
+
+![image-20200828124902923](imgs/image-20200828124902923.png)
+
+点击Finish完成设置，等待生成完成：
+
+![image-20200828124951872](imgs/image-20200828124951872.png)
+
+#### 点击2处Generate
+
+![image-20200828125046738](imgs/image-20200828125046738.png)
+
+#### 点击3处Open Project，打开工程
+
+![image-20200828125215067](imgs/image-20200828125215067.png)
+
+## 运行
+
+点击“生成-生成解决方案”。等待编译完成。
+
+![image-20200828125402056](imgs/image-20200828125402056.png)
+
+### 运行方法1：命令行
+
+命令行cd到exe的路径（比如：E:\LearningCodes\GithubRepo\tensorrtx\yolov5\build\Debug）,
+
+```
+yolov5.exe -s             // serialize model to plan file i.e. 'yolov5s.engine'
+yolov5.exe -d  ../samples // deserialize plan file and run inference, the images in samples will be processed.
+```
+
+**注意：在生成engine时，wts文件要放置在工程文件xxx.vcxproj所在文件的上一级目录**，或者直接修改源码，直接指向绝对地址：
+
+![image-20200828125938472](imgs/image-20200828125938472.png)
+
+### 运行方法2：vs直接运行，可debug
+
+在vs中，在工程上右键，先选择“设为启动项”，然后选择“属性”。在属性页设置参数。设置完成后点击运行即可，可以打断点debug。
+
+![image-20200828130117902](imgs/image-20200828130117902.png)
+
+![image-20200828130415658](imgs/image-20200828130415658.png)
+
+![image-20200828131516231](imgs/image-20200828131516231.png)
+
+**注意：**
+
+**运行时需要将tensorRt的dll和opencv的dll拷贝到exe所在路径。或者将tensorRt和opencv的bin文件夹路径添加到环境变量中（不建议）**