最详细的编译paddleOcrGPU C++版本指南（包含遇到坑的解决办法）
前言：
我是之前编译过调用CPU的paddleOcr的C++版本，其实CPU版本与GPU版本并无太大不同，只不过是调用库版本的不同，然后原项目中几个相关参数改一下就可以，但是在这个过程中我找不到关于编译paddleOcrGPU C++版本的详细教程介绍，没有目的的踩了一些坑，在这里详细的记录下来整个过程与解决办法。
配环境的准备工作
首先需要看官方提供的库需要什么什么版本的CUDA，ｃｕｄｎｎ，ｔｅｎｓｏｒＲＴ，官方库地址在这里
https://paddleinference.paddlepaddle.org.cn/user_guides/download_lib.html#windows
我是选的最后一个版本，可以看到上面需要cuda11.6，cudnn8.4，tensorRT8.4.1.5，所以按照需要的版本进行安装，我是参考的这篇https://blog.csdn.net/weixin_42408280/article/details/125933323写的非常好
- cuda下载路径
https://developer.nvidia.com/cuda-toolkit-archive
这个Version10是windows10的意思 - cudnn下载路径
https://developer.nvidia.com/rdp/cudnn-archive - tensorRT下载路径（GA是指稳定版）
https://developer.nvidia.com/nvidia-tensorrt-8x-download
配环境
其实配环境很简单，cuda就直接继续安装就行，会默认安装到C盘，测试就算我该地址到D盘，还是会装到C盘，需要C盘空间足够
- 配置cudnn与TensorRT
将下载好的cudnn和TensorRT分别解压，并分别将两个解压后的文件夹内的：bin, include, lib\ 目录复制到cuda安装路径下，cuda的默认安装路径为:C:\Program Files\NVIDIA GPU Computing Toolkit\CUD
下载Paddle库
地址：https://paddleinference.paddlepaddle.org.cn/user_guides/download_lib.html#windows
解压后的文件
改代码
之前如果部署过cpu版本的就非常简单了，只需要将CMakeLists里调用的静态库（.lib）改成GPU版本的库即可
这是我的CMakeLists.txt
# cmake_minimum_required(VERSION 3.5)
# # 设置c++标准
# set(CMAKE_CXX_STANDARD 17)
# project(PaddleOcr)
# # 默认arm
# set(path lib/arm)
# set(opencvVersion opencv410)#设置opencv版本
# # 头文件
# include_directories(./include)
# include_directories(/home/nvidia/paddleOCR/PaddleOCR-release-2.6/deploy/cpp_infer)
# include_directories(/usr/include)
# include_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/paddle/include)
# include_directories(/home/nvidia/opencv-4.1.0/include/opencv2)
# include_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/third_party/install/glog/include)
# include_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/third_party/AutoLog-main)
# include_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/third_party/install/gflags/include)
# include_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/third_party/install/protobuf/include)
# include_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/third_party/threadpool)
# # 库文件
# link_directories(/usr/lib)
# link_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/third_party/install/glog/lib)
# link_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/paddle/lib)
# link_directories(/home/nvidia/opencv-4.1.0/build/lib)
# link_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/third_party/install/protobuf/lib)
# link_directories(/home/nvidia/paddleOCR/paddle_inference_install_dir/third_party/install/gflags/lib)
# aux_source_directory (src SRC_LIST)
# add_executable (test ${SRC_LIST})
# # c++17
# target_link_libraries(test opencv_highgui opencv_core opencv_imgproc opencv_imgcodecs opencv_calib3d opencv_features2d opencv_videoio protobuf glog gflags paddle_inference pthread)
# # 注意测试
# set (EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/bin/arm)
##################################################################################################
set(CMAKE_BUILD_TYPE "Release") #option: Debug / Release
if (CMAKE_BUILD_TYPE MATCHES "Debug"
OR CMAKE_BUILD_TYPE MATCHES "None")
message(STATUS "CMAKE_BUILD_TYPE is Debug")
elseif (CMAKE_BUILD_TYPE MATCHES "Release")
message(STATUS "CMAKE_BUILD_TYPE is Release")
endif()
cmake_minimum_required(VERSION 3.5)
# 设置c++标准
set(CMAKE_CXX_STANDARD 17)
project(DsOcr)
set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON)
option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON)
option(WITH_GPU "Compile demo with GPU/CPU, default use CPU." ON)
option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static." ON)
option(WITH_TENSORRT "Compile demo with TensorRT." OFF)
macro(safe_set_static_flag)
foreach(flag_var
CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO)
if(${flag_var} MATCHES "/MD")
string(REGEX REPLACE "/MD" "/MT" ${flag_var} "${${flag_var}}")
endif(${flag_var} MATCHES "/MD")
endforeach(flag_var)
endmacro()
if (WITH_MKL)
ADD_DEFINITIONS(-DUSE_MKL)
endif()
if (MSVC)
add_definitions(-w)
#add_definitions(-W0)
endif()
if (WIN32)
add_definitions("/DGOOGLE_GLOG_DLL_DECL=")
set(CMAKE_C_FLAGS /source-charset:utf-8)
add_definitions(-D_CRT_SECURE_NO_WARNINGS)
add_definitions(-D_CRT_NONSTDC_NO_DEPRECATE)
if(WITH_MKL)
set(FLAG_OPENMP "/openmp")
endif()
set(CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG} /bigobj /MTd ${FLAG_OPENMP}")
set(CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE} /bigobj /MT ${FLAG_OPENMP}")
set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} /bigobj /MTd ${FLAG_OPENMP}")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT ${FLAG_OPENMP}")
if (WITH_STATIC_LIB)
safe_set_static_flag()
add_definitions(-DSTATIC_LIB)
endif()
message("cmake c debug flags " ${CMAKE_C_FLAGS_DEBUG})
message("cmake c release flags " ${CMAKE_C_FLAGS_RELEASE})
message("cmake cxx debug flags " ${CMAKE_CXX_FLAGS_DEBUG})
message("cmake cxx release flags " ${CMAKE_CXX_FLAGS_RELEASE})
endif()
set(opencvVersion opencv410)#设置opencv版本
# 头文件
include_directories(${PROJECT_SOURCE_DIR}/include)
#include_directories(/home/nvidia/paddleOCR/PaddleOCR-release-2.6/deploy/cpp_infer/include)
#include_directories(/home/nvidia/paddleOCR/PaddleOCR-release-2.6/deploy/cpp_infer)
#include_directories(/usr/include)
include_directories(./)
include_directories(./include)
include_directories(./Ds_inference/opencv410/include/opencv4)
include_directories(./Ds_inference/opencv410/include/opencv4/opencv2)
include_directories(./Ds_inference/third_party/install/mklml/include)
include_directories(./Ds_inference/third_party/install/mkldnn/include)
include_directories(./Ds_inference/third_party/install/glog/include)
include_directories(./Ds_inference/third_party/AutoLog-main)
include_directories(./Ds_inference/third_party/install/gflags/include)
include_directories(./Ds_inference/third_party/install/protobuf/include)
include_directories(./Ds_inference/third_party/threadpool)
include_directories(./Ds_inference/paddle_gpu11.6/include)
# 库文件
#link_directories(/usr/lib)
link_directories(./Ds_inference/third_party/install/mklml/lib)
link_directories(./Ds_inference/third_party/install/mkldnn/lib)
link_directories(./Ds_inference/third_party/install/glog/lib)
link_directories(./Ds_inference/opencv410/lib)
link_directories(./Ds_inference/third_party/install/protobuf/lib)
link_directories(./Ds_inference/third_party/install/gflags/lib)
link_directories(./Ds_inference/paddle_gpu11.6/lib)
aux_source_directory (src SRC_LIST)
add_executable (test ${SRC_LIST})
set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/bin/win)
set(output)
target_link_libraries(test
opencv_world410
#opencv_highgui opencv_core opencv_imgproc opencv_imgcodecs opencv_calib3d opencv_features2d opencv_videoio
paddle_inference mklml libiomp5md mkldnn glog gflags_static libprotobuf libcmt shlwapi
)
# 注意测试
set (EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/bin)
除了改CMakeLists文件，只需要改args.cpp里的参数就可以了
- use_gpu打开
- use_tensorrt我选择true，然后运行的时候会报这个错，我不知道怎么解决，就暂时不使用这个功能
- gpu_id是gpu的编号，默认为一个，即调用一个GPU
- benchmark打开可以看到具体的推理速度等信息
编译出exe可执行文件
使用vscode编译
如果是ｘ６４系统就选择这个
特别注意一定要选好是ｒｅｌｅａｓｅ版本还是ｄｅｂｕｇ版本，我之前没有注意到这个地方，默认选的ｄｅｂｕｇ，然后会报好多找不到库的错，然后我就用的ｖｉｓｕａｌ ｓｔｕｄｉｏ生成ｅｘｅ，ｖｓ太庞大了，运行很慢，所以很麻烦，后来才发现是我没有选成ｒｅｌｅａｓｅ模式。
- 用ｖｓｃｏｄｅ编译可执行文件非常简单丝滑，先在ｂｕｉｌｄ文件夹下ｃｍａｋｅ ．．生成ｓｌｎ文件
- 然后按ｂｕｉｌｄ生成ｅｘｅ文件
- 最后按４那个箭头就可以直接运行生成好的ｅｘｅ文件
遇到的大坑
因为我之前编译过ｃｐｕ版本的，所以我属于直接复制了之前的项目，然后改了几个参数，到运行的时候报错
我排查了好久，网上根本找不到同种报错的解决办法，最后知道这类错误就属于ｄｌｌ与ｌｉｂ的版本不匹配的问题，我突然想去来我的ｅｘｅ文件夹内还是用的之前的ｃｐｕ版本的ｄｌｌ，而我的ｌｉｂ使用的ｇｐｕ版本的ｌｉｂ，我把ｄｌｌ替换为ｇｐｕ版本的就没有报这个错了，这给了我一个解决办法的思路，如果解决问题时没有方向可以把整个项目清空，从头开始搭建项目，就不会受其他因素影响，有可能就能解决项目的报错。
- ｅｘｅ需要的ｄｌｌ文件
都是从官方库里下载的库里的ｔｈｉｒｄｐａｒｔｙ或者ｌｉｂ里复制过来的