1 #include <stdio.h>
2 #include <iostream>
3 #include <opencv2/imgproc/imgproc.hpp>
4 #include <opencv2/highgui/highgui.hpp>
5 #include <opencv2/core/utility.hpp>
6
7 using namespace cv; // all the new API is put into "cv" namespace. Export its content
8 using namespace std;
9
help()10 static void help()
11 {
12 cout <<
13 "\nThis program shows how to use cv::Mat and IplImages converting back and forth.\n"
14 "It shows reading of images, converting to planes and merging back, color conversion\n"
15 "and also iterating through pixels.\n"
16 "Call:\n"
17 "./image [image-name Default: ../data/lena.jpg]\n" << endl;
18 }
19
20 // enable/disable use of mixed API in the code below.
21 #define DEMO_MIXED_API_USE 1
22
23 #ifdef DEMO_MIXED_API_USE
24 # include <opencv2/highgui/highgui_c.h>
25 # include <opencv2/imgcodecs/imgcodecs_c.h>
26 #endif
27
main(int argc,char ** argv)28 int main( int argc, char** argv )
29 {
30 help();
31 const char* imagename = argc > 1 ? argv[1] : "../data/lena.jpg";
32 #if DEMO_MIXED_API_USE
33 //! [iplimage]
34 Ptr<IplImage> iplimg(cvLoadImage(imagename)); // Ptr<T> is safe ref-counting pointer class
35 if(!iplimg)
36 {
37 fprintf(stderr, "Can not load image %s\n", imagename);
38 return -1;
39 }
40 Mat img = cv::cvarrToMat(iplimg); // cv::Mat replaces the CvMat and IplImage, but it's easy to convert
41 // between the old and the new data structures (by default, only the header
42 // is converted, while the data is shared)
43 //! [iplimage]
44 #else
45 Mat img = imread(imagename); // the newer cvLoadImage alternative, MATLAB-style function
46 if(img.empty())
47 {
48 fprintf(stderr, "Can not load image %s\n", imagename);
49 return -1;
50 }
51 #endif
52
53 if( img.empty() ) // check if the image has been loaded properly
54 return -1;
55
56 Mat img_yuv;
57 cvtColor(img, img_yuv, COLOR_BGR2YCrCb); // convert image to YUV color space. The output image will be created automatically
58
59 vector<Mat> planes; // Vector is template vector class, similar to STL's vector. It can store matrices too.
60 split(img_yuv, planes); // split the image into separate color planes
61
62 #if 1
63 // method 1. process Y plane using an iterator
64 MatIterator_<uchar> it = planes[0].begin<uchar>(), it_end = planes[0].end<uchar>();
65 for(; it != it_end; ++it)
66 {
67 double v = *it*1.7 + rand()%21-10;
68 *it = saturate_cast<uchar>(v*v/255.);
69 }
70
71 // method 2. process the first chroma plane using pre-stored row pointer.
72 // method 3. process the second chroma plane using individual element access
73 for( int y = 0; y < img_yuv.rows; y++ )
74 {
75 uchar* Uptr = planes[1].ptr<uchar>(y);
76 for( int x = 0; x < img_yuv.cols; x++ )
77 {
78 Uptr[x] = saturate_cast<uchar>((Uptr[x]-128)/2 + 128);
79 uchar& Vxy = planes[2].at<uchar>(y, x);
80 Vxy = saturate_cast<uchar>((Vxy-128)/2 + 128);
81 }
82 }
83
84 #else
85 Mat noise(img.size(), CV_8U); // another Mat constructor; allocates a matrix of the specified size and type
86 randn(noise, Scalar::all(128), Scalar::all(20)); // fills the matrix with normally distributed random values;
87 // there is also randu() for uniformly distributed random number generation
88 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
89
90 const double brightness_gain = 0;
91 const double contrast_gain = 1.7;
92 #if DEMO_MIXED_API_USE
93 // it's easy to pass the new matrices to the functions that only work with IplImage or CvMat:
94 // step 1) - convert the headers, data will not be copied
95 IplImage cv_planes_0 = planes[0], cv_noise = noise;
96 // step 2) call the function; do not forget unary "&" to form pointers
97 cvAddWeighted(&cv_planes_0, contrast_gain, &cv_noise, 1, -128 + brightness_gain, &cv_planes_0);
98 #else
99 addWeighted(planes[0], contrast_gain, noise, 1, -128 + brightness_gain, planes[0]);
100 #endif
101 const double color_scale = 0.5;
102 // Mat::convertTo() replaces cvConvertScale. One must explicitly specify the output matrix type (we keep it intact - planes[1].type())
103 planes[1].convertTo(planes[1], planes[1].type(), color_scale, 128*(1-color_scale));
104 // alternative form of cv::convertScale if we know the datatype at compile time ("uchar" here).
105 // This expression will not create any temporary arrays and should be almost as fast as the above variant
106 planes[2] = Mat_<uchar>(planes[2]*color_scale + 128*(1-color_scale));
107
108 // Mat::mul replaces cvMul(). Again, no temporary arrays are created in case of simple expressions.
109 planes[0] = planes[0].mul(planes[0], 1./255);
110 #endif
111
112 // now merge the results back
113 merge(planes, img_yuv);
114 // and produce the output RGB image
115 cvtColor(img_yuv, img, COLOR_YCrCb2BGR);
116
117 // this is counterpart for cvNamedWindow
118 namedWindow("image with grain", WINDOW_AUTOSIZE);
119 #if DEMO_MIXED_API_USE
120 // this is to demonstrate that img and iplimg really share the data - the result of the above
121 // processing is stored in img and thus in iplimg too.
122 cvShowImage("image with grain", iplimg);
123 #else
124 imshow("image with grain", img);
125 #endif
126 waitKey();
127
128 return 0;
129 // all the memory will automatically be released by Vector<>, Mat and Ptr<> destructors.
130 }
131
