1 #include "cv.h" // include standard OpenCV headers, same as before
4 using namespace cv; // all the new API is put into "cv" namespace. Export its content
6 // enable/disable use of mixed API in the code below.
7 #define DEMO_MIXED_API_USE 1
9 int main( int argc, char** argv )
11 const char* imagename = argc > 1 ? argv[1] : "lena.jpg";
12 #if DEMO_MIXED_API_USE
13 Ptr<IplImage> iplimg = cvLoadImage(imagename); // Ptr<T> is safe ref-conting pointer class
16 fprintf(stderr, "Can not load image %s\n", imagename);
19 Mat img(iplimg); // cv::Mat replaces the CvMat and IplImage, but it's easy to convert
20 // between the old and the new data structures (by default, only the header
21 // is converted, while the data is shared)
23 Mat img = imread(imagename); // the newer cvLoadImage alternative, MATLAB-style function
26 fprintf(stderr, "Can not load image %s\n", imagename);
31 if( !img.data ) // check if the image has been loaded properly
35 cvtColor(img, img_yuv, CV_BGR2YCrCb); // convert image to YUV color space. The output image will be created automatically
37 vector<Mat> planes; // Vector is template vector class, similar to STL's vector. It can store matrices too.
38 split(img_yuv, planes); // split the image into separate color planes
41 // method 1. process Y plane using an iterator
42 MatIterator_<uchar> it = planes[0].begin<uchar>(), it_end = planes[0].end<uchar>();
43 for(; it != it_end; ++it)
45 double v = *it*1.7 + rand()%21-10;
46 *it = saturate_cast<uchar>(v*v/255.);
49 // method 2. process the first chroma plane using pre-stored row pointer.
50 // method 3. process the second chroma plane using individual element access
51 for( int y = 0; y < img_yuv.rows; y++ )
53 uchar* Uptr = planes[1].ptr<uchar>(y);
54 for( int x = 0; x < img_yuv.cols; x++ )
56 Uptr[x] = saturate_cast<uchar>((Uptr[x]-128)/2 + 128);
57 uchar& Vxy = planes[2].at<uchar>(y, x);
58 Vxy = saturate_cast<uchar>((Vxy-128)/2 + 128);
63 Mat noise(img.size(), CV_8U); // another Mat constructor; allocates a matrix of the specified size and type
64 randn(noise, Scalar::all(128), Scalar::all(20)); // fills the matrix with normally distributed random values;
65 // there is also randu() for uniformly distributed random number generation
66 GaussianBlur(noise, noise, Size(3, 3), 0.5, 0.5); // blur the noise a bit, kernel size is 3x3 and both sigma's are set to 0.5
68 const double brightness_gain = 0;
69 const double contrast_gain = 1.7;
70 #if DEMO_MIXED_API_USE
71 // it's easy to pass the new matrices to the functions that only work with IplImage or CvMat:
72 // step 1) - convert the headers, data will not be copied
73 IplImage cv_planes_0 = planes[0], cv_noise = noise;
74 // step 2) call the function; do not forget unary "&" to form pointers
75 cvAddWeighted(&cv_planes_0, contrast_gain, &cv_noise, 1, -128 + brightness_gain, &cv_planes_0);
77 addWeighted(planes[0], constrast_gain, noise, 1, -128 + brightness_gain, planes[0]);
79 const double color_scale = 0.5;
80 // Mat::convertTo() replaces cvConvertScale. One must explicitly specify the output matrix type (we keep it intact - planes[1].type())
81 planes[1].convertTo(planes[1], planes[1].type(), color_scale, 128*(1-color_scale));
82 // alternative form of cv::convertScale if we know the datatype at compile time ("uchar" here).
83 // This expression will not create any temporary arrays and should be almost as fast as the above variant
84 planes[2] = Mat_<uchar>(planes[2]*color_scale + 128*(1-color_scale));
86 // Mat::mul replaces cvMul(). Again, no temporary arrays are created in case of simple expressions.
87 planes[0] = planes[0].mul(planes[0], 1./255);
90 // now merge the results back
91 merge(planes, img_yuv);
92 // and produce the output RGB image
93 cvtColor(img_yuv, img, CV_YCrCb2BGR);
95 // this is counterpart for cvNamedWindow
96 namedWindow("image with grain", CV_WINDOW_AUTOSIZE);
97 #if DEMO_MIXED_API_USE
98 // this is to demonstrate that img and iplimg really share the data - the result of the above
99 // processing is stored in img and thus in iplimg too.
100 cvShowImage("image with grain", iplimg);
102 imshow("image with grain", img);
107 // all the memory will automatically be released by Vector<>, Mat and Ptr<> destructors.