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drop C-API sample code

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This commit is contained in:
Alexander Alekhin
2018-10-22 17:22:11 +00:00
committed by Alexander Alekhin
parent 9c23f2f1a6
commit 329a1fb781
11 changed files with 13 additions and 480 deletions
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samples/cpp/image.cpp
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#include <stdio.h>
#include <iostream>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/core/utility.hpp>
using namespace cv; // all the new API is put into "cv" namespace. Export its content
using namespace std;
static void help()
{
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: ../data/lena.jpg]\n" << endl;
}
// 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>
# include <opencv2/imgcodecs/imgcodecs_c.h>
#endif
int main( int argc, char** argv )
{
cv::CommandLineParser parser(argc, argv, "{help h | |}{@image|../data/lena.jpg|}");
if (parser.has("help"))
{
help();
return 0;
}
string imagename = parser.get<string>("@image");
#if DEMO_MIXED_API_USE
//! [iplimage]
Ptr<IplImage> iplimg(cvLoadImage(imagename.c_str())); // Ptr<T> is safe ref-counting pointer class
if(!iplimg)
{
fprintf(stderr, "Can not load image %s\n", imagename.c_str());
return -1;
}
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)
//! [iplimage]
#else
Mat img = imread(imagename); // the newer cvLoadImage alternative, MATLAB-style function
if(img.empty())
{
fprintf(stderr, "Can not load image %s\n", imagename.c_str());
return -1;
}
#endif
if( img.empty() ) // check if the image has been loaded properly
return -1;
Mat img_yuv;
cvtColor(img, img_yuv, COLOR_BGR2YCrCb); // convert image to YUV color space. The output image will be created automatically
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
#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.);
}
// 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);
}
}
#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
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));
// 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
// now merge the results back
merge(planes, img_yuv);
// and produce the output RGB image
cvtColor(img_yuv, img, COLOR_YCrCb2BGR);
// 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();
return 0;
// all the memory will automatically be released by Vector<>, Mat and Ptr<> destructors.
}
samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp
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//! [head]
#include <iostream>
#include <opencv2/imgproc.hpp>
#include "opencv2/imgcodecs.hpp"
#include <opencv2/highgui.hpp>
using namespace cv; // The new C++ interface API is inside this namespace. Import it.
using namespace std;
//! [head]
static 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, splitting the planes, merging back and " << endl
<< " color conversion, plus iterating through pixels. " << endl
<< "Usage:" << endl
<< progName << " [image-name Default: ../data/lena.jpg]" << endl << endl;
}
//! [start]
// comment out the define to use only the latest C++ API
#define DEMO_MIXED_API_USE
#ifdef DEMO_MIXED_API_USE
# include <opencv2/highgui/highgui_c.h>
# include <opencv2/imgcodecs/imgcodecs_c.h>
#endif
int main( int argc, char** argv )
{
help(argv[0]);
const char* imagename = argc > 1 ? argv[1] : "../data/lena.jpg";
#ifdef DEMO_MIXED_API_USE
Ptr<IplImage> IplI(cvLoadImage(imagename)); // Ptr<T> is a safe ref-counting pointer class
if(!IplI)
{
cerr << "Can not load image " << imagename << endl;
return -1;
}
Mat I = cv::cvarrToMat(IplI); // Convert to the new style container. Only header created. Image not copied.
#else
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
//! [start]
//! [new]
// convert image to YUV color space. The output image will be created automatically.
Mat I_YUV;
cvtColor(I, I_YUV, COLOR_BGR2YCrCb);
vector<Mat> planes; // Use the STL's vector structure to store multiple Mat objects
split(I_YUV, planes); // split the image into separate color planes (Y U V)
//! [new]
#if 1 // change it to 0 if you want to see a blurred and noisy version of this processing
//! [scanning]
// Mat scanning
// 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);
}
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);
}
}
//! [scanning]
#else
//! [noisy]
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);
//! [noisy]
#endif
//! [end]
merge(planes, I_YUV); // now merge the results back
cvtColor(I_YUV, I, COLOR_YCrCb2BGR); // and produce the output RGB image
namedWindow("image with grain", 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
//! [end]
waitKey();
// Tip: No memory freeing is required!
// All the memory will be automatically released by the Vector<>, Mat and Ptr<> destructor.
return 0;
}
samples/cpp/tutorial_code/core/mat_operations/mat_operations.cpp
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@@ -1,7 +1,6 @@
/* Snippet code for Operations with images tutorial (not intended to be run but should built successfully) */
#include "opencv2/core.hpp"
#include "opencv2/core/core_c.h"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
@@ -128,15 +127,6 @@ int main(int,char**)
CV_UNUSED(smallImg);
}
}
{
//! [C-API conversion]
Mat img = imread("image.jpg");
IplImage img1 = img;
CvMat m = img;
//! [C-API conversion]
CV_UNUSED(img1);
CV_UNUSED(m);
}
{
//! [BGR to Gray]
Mat img = imread("image.jpg"); // loading a 8UC3 image