有没有大神帮忙看下这段代码哪里错了，我运行总是报错
#include<opencv2/opencv.hpp>
#include<math.h>
#include<iostream>
#include<opencv2/highgui/highgui_c.h>
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
char watershed_win[] = "watershed segmentation demo";
Mat src = imread("C:\\Users\\txc\\Desktop\\tupian\\扑克牌.jpg");
if (!src.data)
{
cout << "could not load image....\n" << endl;
return -1;
}
cv::namedWindow("input image", CV_WINDOW_NORMAL);
cv::imshow("input image", src);
//第一步：将白色背景变为黑色
for (int row = 0; row < src.rows; row++)
{
for (int col = 0; col < src.cols; col++)
{
if (src.at<Vec3b>(row, col) == Vec3b(255, 255, 255))
{
src.at<Vec3b>(row, col)[0] = 0;
src.at<Vec3b>(row, col)[1] = 0;
src.at<Vec3b>(row, col)[2] = 0;
}
}
}
//显示出来
cv::namedWindow("black background", CV_WINDOW_NORMAL);
cv::imshow("black background", src);
//第二步：锐化，为下一步二值化做准备
Mat kernel = (Mat_<float>(3, 3) << 1, 1, 1, 1, -8, 1, 1, 1, 1);
Mat imgLaplance;
Mat sharpenImg = src;
filter2D(src, imgLaplance, CV_32F, kernel, Point(-1, -1), 0, BORDER_DEFAULT);//通过拉普拉斯得到边缘
src.convertTo(sharpenImg, CV_32F);
Mat resultImg = sharpenImg - imgLaplance;//用原图减去这些边缘，使它们之间的差值更大，使图像得到锐化，为下一步二值化做准备
resultImg.convertTo(resultImg, CV_8UC3);
imgLaplance.convertTo(imgLaplance, CV_8UC3);//将锐化的图像转化到8UC3上
cv::namedWindow("sharpen image", CV_WINDOW_NORMAL);
cv::imshow("sharpen image", resultImg);//显示出来锐化的图像
src = resultImg;//copy back
//将锐化后的结果转换成二值图像，然后接着进行距离变换
Mat binaryImg;
cvtColor(src, resultImg, CV_BGR2GRAY);//刚刚图像变成了CV_8UC3，现在要处理一下
threshold(resultImg, binaryImg, 40, 255, THRESH_BINARY | THRESH_OTSU);//寻找自动阈值
cv::namedWindow("binaryImg image", CV_WINDOW_NORMAL);
cv::imshow("binaryImg image", binaryImg);//显示二值图像
//现在在二值图像基础上进行距离变换
Mat distImg;
distanceTransform(binaryImg, distImg, DIST_L1, 3, 5);
normalize(distImg, distImg, 0, 1, NORM_MINMAX);//对结果进行归一化
cv::namedWindow("distance result", CV_WINDOW_NORMAL);
cv::imshow("distance result", distImg);
threshold(distImg, distImg, .4, 1, THRESH_BINARY);//对距离变换的结果进行二值化
Mat k1 = Mat::ones(13, 13, CV_8UC1);
erode(distImg, distImg, k1, Point(-1, -1));//进行二值腐蚀
cv::namedWindow("distance binary image", CV_WINDOW_NORMAL);
cv::imshow("distance binary image", distImg);
//进行标记（编号处理）
Mat dist_8u;
distImg.convertTo(dist_8u, CV_8U);
vector<vector<Point>> contours;
findContours(dist_8u, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));
//创造标记
Mat markers = Mat::zeros(src.size(), CV_32SC1);
for (size_t i = 0; i < contours.size(); i++) {
drawContours(markers, contours, static_cast<int>(i), Scalar::all(static_cast<int>(i) + 1), -1);
}
circle(markers, Point(5, 5), 3, Scalar(255, 255, 255), -1);
imshow("my markers", markers * 1000);
//进行分水岭变换
watershed(src, markers);
Mat mark = Mat::zeros(markers.size(), CV_8UC1);
markers.convertTo(mark, CV_8UC1);
bitwise_not(mark, mark, Mat());
imshow("watershed image", mark);
// 随机分配颜色
vector<Vec3b> colors;
for (size_t i = 0; i < contours.size(); i++) {
int r = theRNG().uniform(0, 255);
int g = theRNG().uniform(0, 255);
int b = theRNG().uniform(0, 255);
colors.push_back(Vec3b((uchar)b, (uchar)g, (uchar)r));
}
// fill with color and display final result
Mat dst = Mat::zeros(markers.size(), CV_8UC3);
for (int row = 0; row < markers.rows; row++) {
for (int col = 0; col < markers.cols; col++) {
int index = markers.at<int>(row, col);
if (index > 0 && index <= static_cast<int>(contours.size())) {
dst.at<Vec3b>(row, col) = colors[index - 1];
}
else {
dst.at<Vec3b>(row, col) = Vec3b(0, 0, 0);
}
}
}
imshow("Final Result", dst);
waitKey(0);
return 0;
}
