一、VC Code配置

寻找路径的方法：在文件里，搜索“OpenCV4”，就可以显示出来了，我的路径是下面这个位置，每个人的不一样，和这个接近的就应该是了。

"/usr/include/opencv4"

在c_cpp_properties.json里的includepath增加路径，程序里头文件下面的波浪线就没了，说明vscode找到OpenCV库了。

二、读取图像

2.1 CMakeLists.txt

# CMake最低版本要求
cmake_minimum_required(VERSION 2.8)
# 项目信息
project(read_image)

find_package(OpenCV REQUIRED)

# 制定生成目标
add_executable (read_image read_image.cpp)
target_link_libraries(read_image ${OpenCV_LIBS} )

2.2 源代码

#include<iostream>
#include<opencv2/opencv.hpp>

using namespace cv;
using namespace std;

int main(int argc,char** argv){
    cv::Mat imagepath = imread("/home/bc/图片/屏幕截图.png");
    cv::imshow("input", imagepath);
    cv::waitKey(0);
    cv::destroyAllWindows();
    return 0;

}

imshow只能读8位图像和浮点型图像，通过imread读进来的图像都符合8位，通道顺序为B,G,R。

三、任意比例读取图像

cv::namedWindow("输入", cv::WINDOW_FREERATIO);

四、以灰度图方式读取

cv::Mat imagepath = imread("/mnt/hgfs/H/image.jpg",IMREAD_GRAYSCALE);

五、图像色彩转换

5.1 CMakeLists.txt

# CMake最低版本要求
cmake_minimum_required(VERSION 2.8)
# 项目信息
project(read_image)

find_package(OpenCV REQUIRED)
include_directories(
  include
	
  	)
aux_source_directory(. ALL_SRCS)

# 制定生成目标
add_executable (read_image read_image.cpp quickdemo.cpp)
target_link_libraries(read_image ${OpenCV_LIBS} )

5.2 源代码

#include<quickdemo.h>

void QuickDemo::colorSpace_Demo(Mat &image){
    Mat gray, hsv;
    cvtColor(image, hsv, COLOR_BGR2HSV);
    cvtColor(image, gray, COLOR_BGR2GRAY);
    imshow("HSV", hsv);
    imshow("灰度图", gray);
    imwrite("../image/hsv.png", hsv);
    imwrite("../image/gray.png", gray);
}

六、图像赋值

Mat m1, m2;
m1 = image.clone();
image.copyTo(m2)

Mat m3 = cv::Mat::zeros(Size(8, 8),CV_8UC3);
m3 = Scalar(0,255,0); // B,G,R
imshow("tuxiang", m3);

std::cout << "width " << m3.cols << "  height: " << m3.rows << "  channls:" << m3.channels() << std::endl;

clone和copyto都会产生新的内存，成为新的东西，直接=的话还是一个东西。

七、像素操作

Mat dst = image + 20;
Mat dst = image - 20;
Mat dst = image * 2;
Mat dst = image / 20;

八、滚动条操作

cv::Mat src, m, tsd;
int lightness = 50;
static void on_track(int, void *)
{
    m = Scalar(lightness, lightness, lightness);
    add(src, m, tsd);
    imshow("bar", tsd);
}
void QuickDemo::tracking_bar_demo(Mat &image){
    namedWindow("liangdutiaozheng", WINDOW_AUTOSIZE);
    tsd = Mat::zeros(image.size(), image.type());
    m = Mat::zeros(image.size(), image.type());
    src = image;
    Mat temp = image;
    int max_value = 100;
    
    createTrackbar("valuer bar", "liangdutiaozheng", &lightness, max_value,on_track);
    
}

可见一班

OpenCV学习笔记（一）基础操作