本文主要是介绍opencv不同版本之间的互操作性,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!
下图1,为配置截图;下图2为含有#define DEMO_MIXED_API_USE的运行结果,下图3为不含有#define DEMO_MIXED_API_USE的运行结果。实现代码如下所示:
#include <stdio.h>
#include <iostream>#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>using namespace cv; // The new C++ interface API is inside this namespace. Import it.
using namespace std;void help( char* progName)
{cout << endl << progName<< " shows how to use cv::Mat and IplImages together (converting back and forth)." << endl<< "Also contains example for image read, spliting the planes, merging back and " << endl<< " color conversion, plus iterating through pixels. " << endl<< "Usage:" << endl<< progName << " [image-name Default: lena.jpg]" << endl << endl;
}// comment out the define to use only the latest C++ API
//包含C和C++应用程序接口
#define DEMO_MIXED_API_USEint main( int argc, char** argv )
{help(argv[0]);const char* imagename = argc > 1 ? argv[1] : "lena.jpg";#ifdef DEMO_MIXED_API_USE//包含C和C++应用程序接口Ptr<IplImage> IplI = cvLoadImage(imagename); // Ptr<T> is safe ref-counting pointer classif(IplI.empty()){cerr << "Can not load image " << imagename << endl;return -1;}Mat I(IplI); //转换为Mat类型,只复制指针,不复制图像
#else//纯C++应用程序接口Mat I = imread(imagename);// the newer cvLoadImage alternative, MATLAB-style functionif( I.empty() ) // same as if( !I.data ){cerr << "Can not load image " << imagename << endl;return -1;}
#endif///自动转换图像至YUV彩色空间Mat I_YUV;cvtColor(I, I_YUV, CV_BGR2YCrCb);vector<Mat> planes; //应用标准模板库矢量存储多Mat对象 split(I_YUV, planes); //把图像分割为独立的Y,U,V彩色平面#if 1 // change it to 0 if you want to see a blurred and noisy version of this processing Mat scanning// Method 1. process Y plane using an iterator递归器MatIterator_<uchar> it = planes[0].begin<uchar>(), it_end = planes[0].end<uchar>();for(; it != it_end; ++it){double v = *it * 1.7 + rand()%21 - 10;*it = saturate_cast<uchar>(v*v/255);}for( int y = 0; y < I_YUV.rows; y++ ){// Method 2. process the first chroma plane using pre-stored row pointer.uchar* Uptr = planes[1].ptr<uchar>(y);for( int x = 0; x < I_YUV.cols; x++ ){Uptr[x] = saturate_cast<uchar>((Uptr[x]-128)/2 + 128);// Method 3. process the second chroma plane using individual element accessuchar& Vxy = planes[2].at<uchar>(y, x);Vxy = saturate_cast<uchar>((Vxy-128)/2 + 128);}}#elseMat noisyI(I.size(), CV_8U); // Create a matrix of the specified size and type// Fills the matrix with normally distributed random values (around number with deviation off).// There is also randu() for uniformly distributed random number generationrandn(noisyI, Scalar::all(128), Scalar::all(20));// blur the noisyI a bit, kernel size is 3x3 and both sigma's are set to 0.5GaussianBlur(noisyI, noisyI, Size(3, 3), 0.5, 0.5);const double brightness_gain = 0;const double contrast_gain = 1.7;#ifdef DEMO_MIXED_API_USE// To pass the new matrices to the functions that only work with IplImage or CvMat do:// step 1) Convert the headers (tip: data will not be copied).// step 2) call the function (tip: to pass a pointer do not forget unary "&" to form pointers)IplImage cv_planes_0 = planes[0], cv_noise = noisyI;cvAddWeighted(&cv_planes_0, contrast_gain, &cv_noise, 1, -128 + brightness_gain, &cv_planes_0);
#elseaddWeighted(planes[0], contrast_gain, noisyI, 1, -128 + brightness_gain, planes[0]);
#endifconst double color_scale = 0.5;// Mat::convertTo() replaces cvConvertScale.// One must explicitly specify the output matrix type (we keep it intact - planes[1].type())planes[1].convertTo(planes[1], planes[1].type(), color_scale, 128*(1-color_scale));// alternative form of cv::convertScale if we know the datatype at compile time ("uchar" here).// This expression will not create any temporary arrays ( so should be almost as fast as above)planes[2] = Mat_<uchar>(planes[2]*color_scale + 128*(1-color_scale));// Mat::mul replaces cvMul(). Again, no temporary arrays are created in case of simple expressions.planes[0] = planes[0].mul(planes[0], 1./255);
#endifmerge(planes, I_YUV); // now merge the results backcvtColor(I_YUV, I, CV_YCrCb2BGR); // and produce the output RGB imagenamedWindow("image with grain", CV_WINDOW_AUTOSIZE); // use this to create images#ifdef DEMO_MIXED_API_USE// this is to demonstrate that I and IplI really share the data - the result of the above// processing is stored in I and thus in IplI too.cvShowImage("image with grain", IplI);
#elseimshow("image with grain", I); // the new MATLAB style function show
#endifwaitKey();// Tip: No memory freeing is required!// All the memory will be automatically released by the Vector<>, Mat and Ptr<> destructor.return 0;
}
图1:
图2:
图3:
这篇关于opencv不同版本之间的互操作性的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!