OpenCV2411 数据类型

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
using namespace cv;
using namespace std;

int OpenCVDataTypes()
{
////point 类
cv::Point2d p2d(0,1);
cv::Point2d p2d_2(6,7);
cv::Point3i p3i(12,25,56);
cv::Point3d p3d(p3i);
//寻址方式
cout<<"Point3d:"<<p3d.x<<" "<<p3d.y<<" "<<p3d.z<<endl;
//点积
double dot_p3d=p3i.dot(p3d);
cout<<"the dot p3d:"<<dot_p3d<<endl;

////Scalar类
cv::Scalar s(1,2,4,5);
//寻址方式
cout<<"the Scalar: "<<s[0]<<" "<<s[1]<<" "<<s[2]<<" "<<s[3]<<endl;

////Size 类
cv::Size sz(10,13);
//寻址方式
cout<<"the size, width="<<sz.width<<" , height="<<sz.height<<endl;

////矩阵Rect 类
cv::Rect re(1,2,7,8);
cv::Rect re2(p2d,sz);
//寻址方式
cout<<"the Rect, x="<<re2.x<<", y="<<re2.y<<", width="
<<re2.width<<", height="<<re2.height<<endl;

//旋转矩阵 RotateRect 类
cv::RotatedRect rre(p2d,sz,0);//(center,size,angle)
//cv::RotatedRect rre2(p2d,p2d_2);//两个corner, 有误
//寻址方式
cout<<"RotateRect:\n \tthe center: x="<<rre.center.x<<", y="<<rre.center.y
<<", \n \tthe size: width="<<rre.size.width<<", height="<<rre.size.height
<<", \n \tthe angle="<<rre.angle<<endl;

////The Fixed Matrix Classes cv::Matx 类
cv::Matx44f m44f=cv::Matx44f::randn(4,6);
//指定每个元素值
cv::Matx22d m22d(4,5,6,7);
//寻址方式
cout<<"the cv::Matx44f\n";
for(int i=0;i<4;i++)
{
cout<<"\n\t";
for(int j=0;j<4;j++)
cout<<m44f(i,j)<<" ";
cout<<endl;
}

////The Fixed Vector Classes cv::Vec<>
cv::Vec3d v3d(1,2,3);
cout<<"\nVec3d:\n"<<"\t "<<v3d[0]<<" "<<v3d(1)<<" "<<v3d[2]
<<endl;

////The Complex Number Classes cv::Complex<>
cv::Complexd cpd(8,-10);
//寻值方式
cout<<"\nComplexd, real="<<cpd.re<<", image="<<cpd.im<<endl;
//判定方式  TermCriteria( int type, int maxCount, double epsilon )
cv::TermCriteria tc(cv::TermCriteria::COUNT|cv::TermCriteria::EPS, 15,0.01);

////cv::Range 连续的整数序列
cv::Range rg(0,6);
//寻值方式
cout<<"\nthe range, size"<<rg.size()<<" Range start "<<rg.start<<" Range End "<<rg.end
<<endl;
//static Range all() 何用？

////cv::Mat 大矩阵类
//cv::Mat( int rows, int cols, int type, const Scalar& s );
cv::Mat m(3,10,CV_32FC3,cv::Scalar(1.0f,2.0f,3.0f));
//cv::Mat( cv::Size sz, int type );
cv::Mat m2(cv::Size(100,100),CV_32FC3);
//cv::Mat( const Mat& mat, const cv::Range& rows, const cv::Range& cols );
cv::Mat m3(m2,cv::Range(0,5),cv::Range(0,5));
//二维矩阵单通道寻值方式
cv::Mat m4 = cv::Mat::eye(10, 10, CV_32FC1);
printf(
"cv::Mat \n\tElement (3,3) is %f\n",
m4.at<float>(3,3) //(row, col)
);
//二维矩阵多通道寻值方式
cv::Mat m5 = cv::Mat::eye( 10, 10, CV_32FC2);
printf(
"cv::Mat \n\tElement (3,3) is (%f,%f)\n",
m5.at<cv::Vec2f>(3,3)[0],
m5.at<cv::Vec2f>(3,3)[1]
);
//类似二维矩阵多通道的取值方式
cv::Mat m6 = cv::Mat::eye( 10, 10, cv::DataType<cv::Complexf>::type );
printf(
"Element (3,3) is %f + i%f\n",
m6.at<cv::Complexf>(3,3).re,
m6.at<cv::Complexf>(3,3).im
);
//iterator遍历寻址
int sz2[3]={4,4,4};
cv::Mat m7(3,sz2,CV_32FC3);
cv::randu(m7,-1.0f,1.0f);
float max=-1000.0f;
float len2=0.0f;
cv::MatConstIterator_<cv::Vec3f> it=m7.begin<cv::Vec3f>();
while(it!=m7.end<cv::Vec3f>())
{
len2=(*it)[0]*(*it)[0]+(*it)[1]*(*it)[1]+(*it)[2]*(*it)[2];
//cout<<(*it)[0]<<" "<<(*it)[1]<<" "<<(*it)[2]<<endl;
if(max<len2)
max=len2;
it++;
}
cout<<"\nthe Max of Mat 4*4*4 32FC3: "<<max<<endl;
//randu
cv::Vec4d v4d;
cv::randu(v4d,0.0f,1.0f);
cout<<v4d[0]<<" "<<v4d[1]<<" "<<v4d[2]<<" "<<v4d[3]<<endl;

////The  N-ary Array Iterator:  NAryMatIterator
const int n_mat_size = 5;
const int n_mat_sz[] = { n_mat_size, n_mat_size, n_mat_size };
cv::Mat n_mat( 3, n_mat_sz, CV_32FC1 );

cv::RNG rng;
rng.fill( n_mat, cv::RNG::UNIFORM, 0.0f, 1.0f );

const cv::Mat* arrays[] = { &n_mat, 0 };
cv::Mat my_planes[1];
cv::NAryMatIterator nit( arrays, my_planes );
// On each iteration, it.planes[i] will be the current plane of the
// i-th array from ‘arrays’.

double SumPlanes = 0.f;                               // Total sum over all planes
int   n = 0;                                 // Total number of planes
for (unsigned int p = 0; p < nit.nplanes; p++, ++nit) {
SumPlanes += cv::sum(nit.planes[0])[0];
n++;
}
cout<<"the sum of NaryIterator: "<<SumPlanes<<endl;

return 0;
}