#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <eigen3/Eigen/Core>
#include <eigen3/Eigen/Dense>
Eigen::MatrixXf extractPixel(cv::Mat img,int k,int num)
{
int rows=img.rows;
int cols=img.cols;
Eigen::MatrixXf res(num,3);
int c=0;
for (int i=0;i<rows;i++) {
for (int j=0;j<cols;j++) {
int m=img.at<int>(i,j);
if(m==uchar(k))
{
res(c,0)=i;res(c,1)=j;res(c,2)=0;c++;
}
}
}
res.resize(c,3);
return res;
}
Eigen::RowVectorXf featurenormalize(Eigen::MatrixXf &X)
{
//计算每一维度均值
Eigen::MatrixXf meanval = X.colwise().mean();//每一列的矩阵，列降维
Eigen::RowVectorXf meanvecRow = meanval;
//样本均值化为0
X.rowwise() -= meanvecRow;
return meanvecRow;
}
void computeCov(Eigen::MatrixXf &X, Eigen::MatrixXf &C)
{
//计算协方差矩阵C = XTX / n-1;
C = X.adjoint()*X ;
C = C.array() / X.rows() - 1;
}
void computeEig(Eigen::MatrixXf &C, Eigen::MatrixXf &vec, Eigen::MatrixXf &val)
{
//计算特征值和特征向量，使用selfadjont按照对阵矩阵的算法去计算，可以让产生的vec和val按照有序排列
Eigen::SelfAdjointEigenSolver<Eigen::MatrixXf> eig(C);
vec = eig.eigenvectors();
val = eig.eigenvalues();
}
cv::Mat ColinearMat(cv::Mat input,int label)
{
cv::Mat pcaMat=cv::Mat::zeros(300,500,CV_8UC1);
cv::Mat labels, stats, centroids;
int nccomps = connectedComponentsWithStats(input, labels, stats, centroids); //可以得到连通域的个数
for (int comp = 1; comp < nccomps; ++comp)
{
//erase small block
if(stats.at<int>(comp, 4)<50)
continue;
//extract compenet pixel
Eigen::MatrixXf obj = extractPixel(labels,comp,stats.at<int>(comp, 4));
//zero-mean
Eigen::MatrixXf obj_mean=obj;
Eigen::RowVectorXf meanvecRow=featurenormalize(obj_mean);
//coveriance
Eigen::MatrixXf cov(3,3);
computeCov(obj_mean, cov);
//calculate feature vec & val
Eigen::MatrixXf featureVec,featureVal;
computeEig(cov, featureVec, featureVal);
//projectPCA
Eigen::Vector3f direction=featureVec.col(2).transpose();
direction.normalize();
Eigen::MatrixXf point_proj=obj_mean*(direction*direction.transpose());
point_proj.rowwise() += meanvecRow;
//draw mat
for (int i=0;i<point_proj.rows();i++)
{
int x=int(point_proj(i,0));
int y=int(point_proj(i,1));
pcaMat.at<uchar>(x,y)=label;
}
}
return pcaMat;
}
int main()
{
cv::Mat srcImg=cv::imread("/home/freja/component2.png",0);
int label=2;
cv::Mat pcaMat = ColinearMat(srcImg,label);
cv::imshow("img", srcImg);
cv::imshow("pcaMat", pcaMat);
cv::waitKey(0);
// */
std::cout << "Hello World!" << std::endl;
return 0;
}
