==如果有报无法找到opencv_world343.dll的Error,请把C:\opencv\build\x64\vc14\bin下的opencv_world343.dll文件复制到C:\Windows 目录下即可==
imread功能是加载图像文件成为一个Mat对象,其中第一个参数表示图像文件名称
第二个参数,表示加载的图像是什么类型,支持常见的三个参数值
==注意:== OpenCV支持JPG、PNG、TIFF等常见格式图像文件加载
c++
#include<opencv2/opencv.hpp>
#include<iostream>
#include<math.h>
using namespace cv;
int main(int argc, char ** argv) {
Mat src, dst;
src = imread("C:\\Users\\15646\\Pictures\\雷军.jpg");
if (!src.data)
{
printf("no image\n");
return -1;
}
namedWindow("input img", CV_WINDOW_AUTOSIZE);
imshow("input img", src);
int cols = (src.cols-1)* src.channels();
int offsetx = src.channels();
int rows = src.rows;
dst = Mat(src.size(), src.type());
for (int row = 1; row < rows-1; row++)
{
const uchar* current = src.ptr<uchar>(row);
const uchar* previous = src.ptr<uchar>(row - 1);
const uchar* next = src.ptr<uchar>(row);
uchar* output = dst.ptr<uchar>(row);
for (int col = offsetx; col<cols;col++)
{
output[col] = saturate_cast<uchar>(5 * current[col] - (current[col - offsetx] +
current[col + offsetx] + previous[col] + next[col]));
}
}
namedWindow("contrast img ", CV_WINDOW_AUTOSIZE);
imshow("contrast img ", dst);
waitKey(0);
return 0;
}
c++
Mat kernel = (Mat_<char>(3, 3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);
filter2D(src,dst,src.depth(),kernel);
==常用方法:==
void copyTo(Mat mat) 克隆
void convertTo(Mat dst, int type)
Mat clone() 克隆
int channels() 获取通道
int depth()
bool empty();
uchar* ptr(i=0) 获取指针
c++
Mat A= imread(imgFilePath);
Mat B(A) // 只复制
c++
Mat F = A.clone(); 或 Mat G; A.copyTo(G);
c++
cv::Mat::Mat构造函数
Mat M(2,2,CV_8UC3, Scalar(0,0,255))
其中前两个参数分别表示行(row)跟列(column)、第三个CV_8UC3中的8表示每个通道占8位、U表示无符号、C表示Char类型、3表示通道数目是3,
第四个参数是向量表示初始化每个像素值是多少,向量长度对应通道数目一致
创建多维数组cv::Mat::create
int sz[3] = {2,2,2};
Mat L(3,sz, CV_8UC1, Scalar::all(0));
c++
Mat C = (Mat_<double>(3,3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);
c++
Mat m2;
m2 = Mat::zeros(2, 2, CV_8UC1);
imshow("demo2", m2);
c++
Scalar intensity = img.at<uchar>(y, x);
或者 Scalar intensity = img.at<uchar>(Point(x, y));
c++
Vec3f intensity = img.at<Vec3f>(y, x);
float blue = intensity.val[0];
float green = intensity.val[1];
float red = intensity.val[2];
c++
img.at<uchar>(y, x) = 128;
img.at<Vec3b>(y,x)[0]=128; // blue
img.at<Vec3b>(y,x)[1]=128; // green
img.at<Vec3b>(y,x)[2]=128;
img = Scalar(0);
Rect r(10, 10, 100, 100);
Mat smallImg = img(r);
c++
int main(int argc, char ** argo) {
Mat src, gray_src;
src = imread("C:\\Users\\Administrator\\Pictures\\girl.jpg");
if (src.empty())
{
cout <<" read img error!"<< endl ;
}
namedWindow("src img", CV_WINDOW_AUTOSIZE);
imshow("src img", src);
cvtColor(src, gray_src, CV_BGR2GRAY);
//namedWindow("gray_src img", CV_WINDOW_AUTOSIZE);
//imshow("gray_src img", gray_src);
int height = gray_src.rows;
int width = gray_src.cols;
for (int row =0;row<height;row++)
{
for (int col = 0; col< width;col ++)
{
//获取像素值
int gray = gray_src.at<uchar>(row, col);
gray_src.at<uchar>(row, col) = 255 - gray;
}
}
namedWindow("gray_src_change img", CV_WINDOW_AUTOSIZE);
imshow("gray_src_change img", gray_src);
//Mat操作
Mat dst;
dst.create(src.size(), src.type());
height = src.rows;
width = src.cols;
//获取图片通道值
int nc = src.channels();
/*for (int row = 0; row < height; row++)
{
for (int col = 0; col < width; col++)
{
if (nc ==1)
{
int gray = gray_src.at<uchar>(row, col);
gray_src.at<uchar>(row, col) = 255 - gray;
}
else if(nc == 3)
{
int b = src.at<Vec3b>(row, col)[0];
int g = src.at<Vec3b>(row, col)[1];
int r = src.at<Vec3b>(row, col)[2];
dst.at<Vec3b>(row, col)[0] = 255 - b;
dst.at<Vec3b>(row, col)[1] = 255 - g;
dst.at<Vec3b>(row, col)[2] = 255 - r;
}
}
}*/
//上面的转换代码可以替换,效果相同
bitwise_not(src, dst);
imshow("gray_src_change_by_mat img", dst);
cout << "enter anything" << endl;
waitKey(0);
return 0;
}
其中a的取值范围为0~1之间
c++
void addWeighted(InputArray src1,
double alpha,
InputArray src2,
double beta,
double gamma,
OutputArray dst,
int dtype = -1);
参数1:输入图像Mat – src1
参数2:输入图像src1的alpha值
参数3:输入图像Mat – src2
参数4:输入图像src2的alpha值
参数5:gamma值
参数6:输出混合图像
注意点:两张图像的大小和类型必须一致才可以
c++
//设置权重
double alpha = 0.5;
if (src1.rows==src2.rows && src1.cols==src2.cols && src1.type() == src2.type())
{
addWeighted(src1, alpha, src2, (1.0 - alpha), 0.0, dst);
//multiply(src1, src2, dst, 1.0); 图像相乘
imshow("dst", dst);
}
c++
Mat new_image = Mat::zeros( image.size(), image.type() ); 创建一张跟原图像大小和类型一致的空白图像、像素值初始化为0
saturate_cast<uchar>(value)确保值大小范围为0~255之间
Mat.at<Vec3b>(y,x)[index]=value 给每个像素点每个通道赋值
c++
int height = src1.rows; //高度
int width = src1.cols; //宽度
double alpha = 0.8;
int beta = 30;
//生成一个空的大小和src1一样大的图
output = Mat::zeros(src1.size(), src1.type());
for (int row = 0; row < height; row++)
{
for (int col = 0; col < width; col++)
{
if (src1.channels()==3)
{
//像素点变换,换值,达到调整亮度和对比度的效果
float b = src1.at<Vec3b>(row, col)[0]; //blue
float g = src1.at<Vec3b>(row, col)[1]; //green
float r = src1.at<Vec3b>(row, col)[2]; //red
output.at<Vec3b>(row, col)[0] = saturate_cast<uchar>(alpha*b + beta);
output.at<Vec3b>(row, col)[1] = saturate_cast<uchar>(alpha*g + beta);
output.at<Vec3b>(row, col)[2] = saturate_cast<uchar>(alpha*r + beta);
}
else if(src1.channels()==1)
{
output.at<uchar>(row, col) = saturate_cast<uchar>(alpha*src1.at<uchar>(row, col)+ beta);
}
}
}
c++
Point表示2D平面上一个点x,y
Point p;
p.x = 10;
p.y = 8;
or
p = Pont(10,8);
Scalar表示四个元素的向量
Scalar(a, b, c);// a = blue, b = green, c = red表示RGB三个通道
Code
画线 cv::line (LINE_4\LINE_8\LINE_AA)
画椭圆cv::ellipse
画矩形cv::rectangle
画圆cv::circle
画填充cv::fillPoly
==示例代码==
c++
#include<opencv2\opencv.hpp>
#include<iostream>
using namespace std;
using namespace cv;
Mat bgImage;
void Myline();
void MyRectangle();
void MyEllipse();
void MyCircle();
void MyPolygon();
int main() {
bgImage = imread("C:\\Users\\Administrator\\Pictures\\girl2.jpg");
if (!bgImage.data)
{
return -1;
}
Myline();
MyRectangle();
MyEllipse();
MyCircle();
MyPolygon();
imshow("bgImage", bgImage);
waitKey(0);
return 0;
}
//画线
void Myline() {
Point p1 = Point(20, 30);
Point p2;
p2.x = 300;
p2.y = 300;
//设置颜色
Scalar color = Scalar(0, 0, 255);
line(bgImage, p1, p2, color, 1, LINE_8);
}
//画矩形
void MyRectangle() {
Rect rect = Rect(150, 500, 300, 300);
Scalar color = Scalar(255, 0, 0);
rectangle(bgImage, rect, color, 2, LINE_8);
}
//绘制椭圆
void MyEllipse() {
Scalar color = Scalar(0, 255, 0);
ellipse(bgImage,
Point(bgImage.cols / 2, bgImage.rows / 2),
Size(bgImage.cols / 4, bgImage.rows / 8),
90,0,360,color,2,LINE_8);
}
//绘制圆
void MyCircle() {
Scalar color = Scalar(0, 255, 0);
Point center = Point(bgImage.cols / 2, bgImage.rows / 2);
circle(bgImage, center, 150, color, 2, LINE_8);
}
//绘制多边形
void MyPolygon() {
Point pts[1][5];
pts[0][0] = Point(100, 100);
pts[0][1] = Point(100, 200);
pts[0][2] = Point(200, 200);
pts[0][3] = Point(200, 100);
pts[0][4] = Point(100, 100);
const Point* ppts[] = {pts[0]};
int npt[] = { 5 };
Scalar color = Scalar(255, 140, 0);
fillPoly(bgImage, ppts, npt, 1, color, LINE_8);
}
Code
生成高斯随机数gaussian (double sigma)
生成正态分布随机数uniform (int a, int b)
==随机画线代码==
c++
void RandomLineDemo() {
RNG rng(12345);
Point pt1, pt2;
Mat new_img = Mat::zeros(bgImage.size(), bgImage.type());
for (int i = 0; i < 100000;i++)
{
//随机生成的两个端点
pt1.x = rng.uniform(0, bgImage.cols);
pt2.x = rng.uniform(0, bgImage.cols);
pt1.y = rng.uniform(0, bgImage.rows);
pt2.y = rng.uniform(0, bgImage.rows);
int num = rng.uniform(0, 255);
line(new_img, pt1, pt2, CV_RGB(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)), 1, LINE_8);
//延迟50ms
if (waitKey(50)>0)
{
break;
}
imshow("随机生成图片", new_img);
}
}
c++
putText函数 中设置fontFace(cv::HersheyFonts),
putText(bgImage, "Hello World", Point(300, 300), CV_FONT_BLACK, 1.0, CV_RGB(255, 69, 0), 1, LINE_8);