opencv/samples/cpp/image.cpp

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#include <stdio.h>
#include <iostream>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/flann/miniflann.hpp>
#include <opencv2/core/utility.hpp>
using namespace cv; // all the new API is put into "cv" namespace. Export its content
using namespace std;
using namespace cv::flann;
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static void help()
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{
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cout <<
"\nThis program shows how to use cv::Mat and IplImages converting back and forth.\n"
"It shows reading of images, converting to planes and merging back, color conversion\n"
"and also iterating through pixels.\n"
"Call:\n"
"./image [image-name Default: lena.jpg]\n" << endl;
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}
// enable/disable use of mixed API in the code below.
#define DEMO_MIXED_API_USE 1
#ifdef DEMO_MIXED_API_USE
# include <opencv2/highgui/highgui_c.h>
#endif
int main( int argc, char** argv )
{
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help();
const char* imagename = argc > 1 ? argv[1] : "lena.jpg";
#if DEMO_MIXED_API_USE
Ptr<IplImage> iplimg = cvLoadImage(imagename); // Ptr<T> is safe ref-conting pointer class
if(iplimg.empty())
{
fprintf(stderr, "Can not load image %s\n", imagename);
return -1;
}
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Mat img = cv::cvarrToMat(iplimg); // cv::Mat replaces the CvMat and IplImage, but it's easy to convert
// between the old and the new data structures (by default, only the header
// is converted, while the data is shared)
#else
Mat img = imread(imagename); // the newer cvLoadImage alternative, MATLAB-style function
if(img.empty())
{
fprintf(stderr, "Can not load image %s\n", imagename);
return -1;
}
#endif
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if( !img.data ) // check if the image has been loaded properly
return -1;
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Mat img_yuv;
cvtColor(img, img_yuv, COLOR_BGR2YCrCb); // convert image to YUV color space. The output image will be created automatically
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vector<Mat> planes; // Vector is template vector class, similar to STL's vector. It can store matrices too.
split(img_yuv, planes); // split the image into separate color planes
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#if 1
// method 1. process Y plane using an iterator
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.);
}
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// method 2. process the first chroma plane using pre-stored row pointer.
// method 3. process the second chroma plane using individual element access
for( int y = 0; y < img_yuv.rows; y++ )
{
uchar* Uptr = planes[1].ptr<uchar>(y);
for( int x = 0; x < img_yuv.cols; x++ )
{
Uptr[x] = saturate_cast<uchar>((Uptr[x]-128)/2 + 128);
uchar& Vxy = planes[2].at<uchar>(y, x);
Vxy = saturate_cast<uchar>((Vxy-128)/2 + 128);
}
}
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#else
Mat noise(img.size(), CV_8U); // another Mat constructor; allocates a matrix of the specified size and type
randn(noise, Scalar::all(128), Scalar::all(20)); // fills the matrix with normally distributed random values;
// there is also randu() for uniformly distributed random number generation
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
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const double brightness_gain = 0;
const double contrast_gain = 1.7;
#if DEMO_MIXED_API_USE
// it's easy to pass the new matrices to the functions that only work with IplImage or CvMat:
// step 1) - convert the headers, data will not be copied
IplImage cv_planes_0 = planes[0], cv_noise = noise;
// step 2) call the function; do not forget unary "&" to form pointers
cvAddWeighted(&cv_planes_0, contrast_gain, &cv_noise, 1, -128 + brightness_gain, &cv_planes_0);
#else
addWeighted(planes[0], contrast_gain, noise, 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 and should be almost as fast as the above variant
planes[2] = Mat_<uchar>(planes[2]*color_scale + 128*(1-color_scale));
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// 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
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// now merge the results back
merge(planes, img_yuv);
// and produce the output RGB image
cvtColor(img_yuv, img, COLOR_YCrCb2BGR);
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// this is counterpart for cvNamedWindow
namedWindow("image with grain", WINDOW_AUTOSIZE);
#if DEMO_MIXED_API_USE
// this is to demonstrate that img and iplimg really share the data - the result of the above
// processing is stored in img and thus in iplimg too.
cvShowImage("image with grain", iplimg);
#else
imshow("image with grain", img);
#endif
waitKey();
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return 0;
// all the memory will automatically be released by Vector<>, Mat and Ptr<> destructors.
}