[人工智能]opencv代码

#include<opencv2/opencv.hpp>
#include
using namespace std;
using namespace cv;

int main()
{
//显示图像
Mat src;
src = imread(“C:\Users\siasun\Desktop\10.jpg”);
if (src.empty())
{
cout << “counld not load image…” << endl;
return -1;
}
namedWindow(“image”, CV_WINDOW_AUTOSIZE);
imshow(“image”, src);

//显示灰度图
Mat dst;
cvtColor(src, dst, CV_BGR2GRAY);
namedWindow("image", CV_WINDOW_AUTOSIZE);
imshow("image", dst);
printf("input image channels:%d\n", dst.channels());

//显示图像行列
int cols = dst.cols;
int rows = dst.rows;
printf("rows:%d cols:%d\n", rows,cols);
const uchar*firstRow = dst.ptr<uchar>(0);
printf("input image channels:%d\n", *firstRow);

//创建一张mat图像
Mat M(3, 3, CV_8UC3, Scalar(0, 0, 255));
imshow("image", M);

//创建与某图大小类型一致的空白图像
Mat m2 = Mat::zeros(dst.size(), dst.type());
imshow("image", m2);

//掩模,图像增强的两种方法
cols = src.cols * src.channels();
rows = src.rows;
int offset = src.channels();
Mat dst1 = Mat::zeros(src.size(), src.type());
/*for (int row = 1; row < rows; row++)
{
	const uchar* current = src.ptr<uchar>(row);
	const uchar* previous = src.ptr<uchar>(row - 1);
	const uchar* next = src.ptr<uchar>(row + 1);
	uchar* output = img.ptr<uchar>(row);
	for (int col = offset; col < cols; col++)

		output[col] = saturate_cast<uchar>(5 * current[col] - (current[col - offset] + current[col + offset] + previous[col] + next[col]));

}*/
Mat kernel = (Mat_<char>(3, 3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);
filter2D(src, dst1, src.depth(),kernel);
imshow("image", dst1);
imshow("image1", src);
waitKey(0);

return 0;

}