【OpenCV学习】矩阵运算和操作2

#include "cv.h"
#include "highgui.h"
#include <stdio.h>
void PrintMat(CvMat *A);//显示矩阵
void GenRandn(CvMat *arr,int seed);//生成正态分布的随机矩阵
void GenRand(CvMat *arr,int seed);//生成[0,1]均匀分布的随机矩阵
static int cmp_func(const void * _a,const void * _b,void * userdata);//比较函数
void Test_Multiply();//测试矩阵乘法
void Test_cvGetRawData();//将缓存数据填入CvMat数组中
void Test_DCT();//计算DCT变换
void Test_Rand();//生成随机数
void Test_SeqSort();//二维序列排序
int main(void)
{
Test_Multiply();
Test_cvGetRawData();
Test_DCT();
Test_Rand();
Test_SeqSort();
return 0;
}
/*矩阵乘法*/
void Test_Multiply()
{
double a[]={1,2,3,4,
5,6,7,8,
9,10,11,12};
double b[]={1,5,9,
2,6,10,
3,7,11,
4,8,12};
double c[9];
CvMat Ma,Mb,Mc;
printf("/n=== Test Multiply ===/n");
cvInitMatHeader(&Ma,3,4,CV_64FC1,a,CV_AUTOSTEP);
cvInitMatHeader(&Mb,4,3,CV_64FC1,b,CV_AUTOSTEP);
cvInitMatHeader(&Mc,3,3,CV_64FC1,c,CV_AUTOSTEP);
cvMatMulAdd(&Ma,&Mb,0,&Mc);
PrintMat(&Ma);
PrintMat(&Mb);
PrintMat(&Mc);
}
void Test_cvGetRawData()
{
float *data;
int step;
float a[]={ 1,2,3,4,
-5,6,7,8,
9,-10,-11,12
};
CvMat array;
CvSize size;
int x,y;
printf("/n ===Test get raw dara! ===/n");
cvInitMatHeader(&array,3,4,CV_32FC1,a,CV_AUTOSTEP);
cvGetRawData(&array,(uchar **)&data,&step,&size);//得到矩阵的信息
step/=sizeof(data[0]);
printf("/nCvMat = ");
PrintMat(&array);
printf("/nData = ");
for (y=0;y<size.height;y++,data+=step)
{
printf("/n");
for (x=0;x<size.width;x++)
{
data[x]=(float)fabs(data[x]);
printf("%8.2f",data[x]);
}
printf("/n");
}
}
void Test_DCT()
{
float data[]={1,2,3,4,5,6,7,8};
CvMat a;
a = cvMat(2,4,CV_32FC1,data);

printf("/n === Test DCT ===");
printf("/nOriginal Matrix = ");
PrintMat(&a);
cvDCT(&a,&a,CV_DXT_FORWARD);
printf("/n2-D DCT = ");
PrintMat(&a);
cvDCT(&a,&a,CV_DXT_INVERSE);
printf("/n2-D IDCT = ");
PrintMat(&a);
}
void Test_Rand()
{
CvMat *a=cvCreateMat(10,6,CV_32F);
int i;
printf("/n === Test generating random matrix === ");
for (i=0;i<5;i++)
{
GenRandn(a,i);
PrintMat(a);
}
cvReleaseMat(&a);
}
void GenRand(CvMat *arr,int seed)
{
CvRandState rng;
rng.state =cvRNG(0xffffffff);
cvRandInit(&rng,
0,1,    /* 现在使用虚参数以后再调整 */
seed,    /* 使用一个种子  */
CV_RAND_UNI    /* 指定为均匀分布类型 */
);
cvRandArr(&rng.state,arr,CV_RAND_UNI,cvRealScalar(0),cvRealScalar(1));
}
void GenRandn(CvMat *arr,int seed)
{
CvRandState rng;
rng.state =cvRNG(0xffffffff);
cvRandInit(&rng,
0,1,    /* 现在使用虚参数以后再调整 */
seed,    /* 使用一个种子  */
CV_RAND_NORMAL    /* 指定为均匀分布类型 */
);
cvRandArr(&rng.state,arr,CV_RAND_NORMAL,cvRealScalar(0),cvRealScalar(1));
}
void PrintMat(CvMat *A)
{
int i,j;
for (i=0;i<A->rows;i++)
{
printf("/n");
switch(CV_MAT_DEPTH(A->type))
{
case CV_32F:
case CV_64F:
for (j=0;j<A->cols;j++)
printf("%9.3f",(float)cvGetReal2D(A,i,j));
break;
case CV_8U:
case CV_16U:
for (j=0;j<A->cols;j++)
printf("%6d",(int)cvGetReal2D(A,i,j));
break;
default:
break;
}
}
printf("/n");
}
void Test_SeqSort()
{
CvMemStorage *storage = cvCreateMemStorage(0);
CvSeq *seq=cvCreateSeq(CV_32SC2,sizeof(CvSeq),sizeof(CvPoint),storage);
int i;
printf("/n=== Test Sequence sorting! === ");
for (i=0;i<10;i++)
{
CvPoint pt;
pt.x= rand()%1000; // 得到1000以内的随机数
pt.y= rand()%1000;
cvSeqPush(seq,&pt);//添加元素到序列末尾
}
printf("/nOriginal point set:/n");
for (i=0;i<seq->total;i++)
{
CvPoint *pt =(CvPoint *)cvGetSeqElem(seq,i);
printf("(%d,%d)/n",pt->x,pt->y);
}
cvSeqSort(seq,cmp_func,0);
printf("/nAfter sorting: /n");
for (i=0;i<seq->total;i++)
{
CvPoint *pt =(CvPoint *)cvGetSeqElem(seq,i);
printf("(%d,%d)/n",pt->x,pt->y);
}
cvClearSeq(seq);
cvReleaseMemStorage(&storage);
}
static int cmp_func(const void * _a,const void * _b,void * userdata)
{
CvPoint *a=(CvPoint *)_a;
CvPoint *b=(CvPoint *)_b;
int y_diff=a->y-b->y;
int x_diff=a->x-b->x;
return y_diff?y_diff:x_diff;
}