【vscode】使用vscode多源文件结合opencv编译调试 C/C++
使用vscode多源文件结合opencv库进行开发
vscode插件只需要安装
1、新建文件夹OPENCVTEST
2、添加文件main.cpp
内容如下：
#include "Lib/OpencvTest.h"
#include
int main()
{
OpencvTest* opencvtest = new OpencvTest();
opencvtest->readImage();
delete opencvtest;
return 0;
} 3、新建文件夹Lib
4、添加文件OpencvTest.cpp与OpencvTest.h
内容如下：
OpencvTest.h
#pragma once
class OpencvTest
{
public:
void readImage();
OpencvTest();
~OpencvTest();
};
#include "OpencvTest.h"
#include
#include
void OpencvTest::readImage()
{
cv::Mat img = cv::imread("lena.jpg");
cv::imshow("ImageShow", img);
cv::waitKey(0);
}
OpencvTest::OpencvTest()
{
std::cout << "OpencvTest Object Constructed" << std::cout;
}
OpencvTest::~OpencvTest()
{
std::cout << "OpencvTest Object Destructed" << std::cout;
} 5、F5运行，选择C++(GDB/LLDB)，生成launch.json文件，用以下内容替换该文件内容
（注意修改miDebuggerPath的值，同样的如果用qt提供的mingw，我这里修改为D:/Qt/Qt5.7.0/Tools/mingw530_32/bin/gdb.exe同样可以调试运行）
//launch.json
{
"version": "0.2.0",
"configurations": [
{
"name": "C++ Launch",
"type": "cppdbg",
"request": "launch",
"program": "${file}.o",
"args": [],
"cwd": "${workspaceRoot}",
"environment": [],
"externalConsole": true,
"preLaunchTask": "g++",
"linux": {
"miDebuggerPath": "/usr/bin/gdb",
"MIMode": "gdb",
"setupCommands": [
{
"description": "Enable pretty-printing for gdb",
"text": "-enable-pretty-printing",
"ignoreFailures": true
}
]
},
"osx": {
"MIMode": "lldb"
},
"windows": {
"miDebuggerPath": "D:/Qt/Qt5.7.0/Tools/mingw530_32/bin/gdb.exe",
"MIMode": "gdb",
"setupCommands": [
{
"description": "Enable pretty-printing for gdb",
"text": "-enable-pretty-printing",
"ignoreFailures": true
}
]
}
}
]
}
//tasks.json
{
"version": "0.1.0",
"command": "g++",
"args": [
"-g",
"${file}",
"-o",
"${file}.o"
],
"problemMatcher": {
"owner": "cpp",
"fileLocation": [
"relative",
"${workspaceRoot}"
],
"pattern": {
"regexp": "^(.*):(\\d+):(\\d+):\\s+(warning|error):\\s+(.*)$",
"file": 1,
"line": 2,
"column": 3,
"severity": 4,
"message": 5
}
}
} 7、编写CMakeList.txt
每一个包含源文件的目录中都要编写CMakeLists.txt
根目录中的CMakeLists.txt，一般程序入口在此。内容如下：
# 使用CMake Tools插件（可选，如果这个项目去到一个没有这个插件的机器也同样可以生成项目）
include(CMakeToolsHelpers OPTIONAL)
# CMake 最低版本号要求
cmake_minimum_required(VERSION 2.8)
# 项目名称
project(OpencvTest)
# 查找当前目录下的所有源文件
# 并将名称保存到 DIR_ROOT_SRCS变量
aux_source_directory(. DIR_ROOT_SRCS)
# 添加 Lib子目录
add_subdirectory(Lib)
# 指定生成目标
add_executable(OpencvTest main.cpp ${DIR_ROOT_SRCS})
# 添加链接库
target_link_libraries(OpencvTest OpencvLib)子目录中的Lib/CMakeLists.txt，一般将子目录中的源文件编译为静态链接库。内容如下：
opencv链接库是使用cmake用mingw编译出来的，可参考 http://blog.csdn.net/qq_15947787/article/details/77600099
opencv头文件以及链接库路径可根据实际情况进行修改
include(CMakeToolsHelpers OPTIONAL)
cmake_minimum_required(VERSION 2.8)
#添加opencv头文件的搜索路径
INCLUDE_DIRECTORIES(D:/opencv2.4.9/build/include/opencv)
INCLUDE_DIRECTORIES(D:/opencv2.4.9/build/include/opencv2)
INCLUDE_DIRECTORIES(D:/opencv2.4.9/build/include)
# 查找路径下的所有源文件
aux_source_directory(. DIR_LIB_SRCS)
# 生成链接库
add_library(OpencvLib ${DIR_LIB_SRCS})
# 添加链接库
TARGET_LINK_LIBRARIES(OpencvLib D:/opencv2.4.9/build/x86/mingw/lib/libopencv_core249.dll.a)
TARGET_LINK_LIBRARIES(OpencvLib D:/opencv2.4.9/build/x86/mingw/lib/libopencv_highgui249.dll.a)
TARGET_LINK_LIBRARIES(OpencvLib D:/opencv2.4.9/build/x86/mingw/lib/libopencv_imgproc249.dll.a) 8、在vscode终端下输入（找不到终端？F5调试就弹出来了）
cmake -G "MinGW Makefiles"
mingw32-make
9、运行程序
在vscode终端下输入（也就是刚才CMakeLists.txt中的project项目名称，前提要在opencvtest中放入lena.jpg这张图）
.\OpencvTest.exe最终的工程截图：
工程下载：http://download.csdn.net/download/qq_15947787/10151111
参考：http://www.jianshu.com/p/a0ae073e973b