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_USE int 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 class if(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 function if( 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 access uchar& Vxy = planes[2].at<uchar>(y, x); Vxy = saturate_cast<uchar>((Vxy-128)/2 + 128); } } #else Mat 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 generation randn(noisyI, Scalar::all(128), Scalar::all(20)); // blur the noisyI a bit, kernel size is 3x3 and both sigma's are set to 0.5 GaussianBlur(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); #else addWeighted(planes[0], contrast_gain, noisyI, 1, -128 + brightness_gain, planes[0]); #endif const 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); #endif merge(planes, I_YUV); // now merge the results back cvtColor(I_YUV, I, CV_YCrCb2BGR); // and produce the output RGB image namedWindow("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); #else imshow("image with grain", I); // the new MATLAB style function show #endif waitKey(); // Tip: No memory freeing is required! // All the memory will be automatically released by the Vector<>, Mat and Ptr<> destructor. return 0; }
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