C++ (Cpp) Mat::Release Examples

Programming Language: C++ (Cpp)

Class/Type: Mat

Method/Function: Release

Examples at hotexamples.com: 3

The C++ Mat release function is a member function of the OpenCV library that deallocates the Mat object's memory, releasing all the data. This function is useful when dealing with a large number of Mat objects, as it frees up memory space and prevents memory leaks.

Here are some examples of using the Mat release function:

Example 1: Release a Mat object

#include 
#include 

int main()
{
    cv::Mat img = cv::imread("image.jpg");
    // use img for processing
    img.release(); // release memory
    return 0;
}

In this example, we load an image file into a Mat object named "img". We then use the image for some processing and release the memory using the release function.

This code uses the OpenCV library.

Example 2: Release an array of Mat objects

#include 
#include 

int main()
{
    cv::Mat imgs[3];
    for(int i=0; i<3; i++)
    {
        imgs[i] = cv::imread("image"+i+".jpg");
        // use imgs[i] for processing
    }
    cv::Mat::release(&imgs, 3); // release memory for all 3 images
    return 0;
}

In this example, we create an array of 3 Mat objects and load 3 different image files into them. We then use the images for some processing and release the memory for all 3 images using the Mat::release function. This code also uses the OpenCV library. Based on the use of the OpenCV library, it can be concluded that the package/library for these examples is OpenCV.

C++ (Cpp) Mat::Release - 3 examples found. These are the top rated real world C++ (Cpp) examples of Mat::Release from package ACM extracted from open source projects. You can rate examples to help us improve the quality of examples.

Frequently Used Methods

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mul(30)

Rows(30)

at(30)

channels(30)

checkVector(30)

clone(30)

col(30)

colRange(30)

colptr(30)

cols(30)

convertTo(30)

copyTo(30)

create(30)

depth(30)

dot(30)

elemSize(30)

empty(30)

inv(30)

isContinuous(30)

memptr(30)

Cols(27)

copy_size(23)

elemSize1(16)

is_empty(14)

is_vec(14)

cross(12)

get(12)

get_CoeffRing(10)

locateROI(10)

SetDims(10)

ATD(10)

diag(9)

channel(9)

getUMat(9)

fl(9)

eye(9)

clear(8)

NumCols(7)

in_range(7)

adjustROI(7)

NumRows(6)

init(6)

is_square(5)

fset(5)

Create(5)

get_m(5)

MaxNorm(4)

baseInterface(4)

begin(4)

isSubmatrix(4)

Example #1

Show file

File: ColorSpace.cpp Project: ArchieGoodwin/OnTimeMed

void ColorSpace::GraytoRGB (const Mat& gray, Mat& color)
{
	if (gray.Channels()==3)
	{
		color.Create (gray, TRUE);
		return;
	}
	if (gray.SizeObject() != color.SizeObject() || color.Channels()==3)
	{
		color.Release();
		color.Create (gray.SizeObject(), (TYPE)CVLIB_MAKETYPE(gray.Type(), 3));
	}
	int nH = color.Rows(), nW = color.Cols();
	int elemsize=CVLIB_ELEM_SIZE(gray.Type());
	for (int i = 0; i < nH; i ++)
	{
		uchar* pcolor=color.data.ptr[i];
		uchar* pgray=gray.data.ptr[i];
		for (int k=0; k<nW; k++)
		{
			memcpy (&pcolor[3*k*elemsize], &pgray[k*elemsize], elemsize);
			memcpy (&pcolor[(3*k+1)*elemsize], &pgray[k*elemsize], elemsize);
			memcpy (&pcolor[(3*k+2)*elemsize], &pgray[k*elemsize], elemsize);
		}
	}
}

Example #2

Show file

File: ColorSpace.cpp Project: ArchieGoodwin/OnTimeMed

void ColorSpace::RGBtoGray (const Mat& colorImg, Mat& mgray)
{
	if (colorImg.Channels()==1)
	{
		mgray.Create (colorImg, TRUE);
		return;
	}
	if (mgray.SizeObject() != colorImg.SizeObject() || mgray.Channels()==3)
	{
		mgray.Release();
		mgray.Create (colorImg.SizeObject(), colorImg.Type());
	}
	int nH = colorImg.Rows(), nW = colorImg.Cols();
	for (int i = 0; i < nH; i ++)
	{
		uchar* pcolor=colorImg.data.ptr[i];
		uchar* pgray=mgray.data.ptr[i];
		for (int j = 0, k=0; k<nW; j+=3, k++)
			pgray[k] = (uchar)((299 * pcolor[j] + 587 * pcolor[j+1] + 114 * pcolor[j+2]) / 1000);
	}
}

Example #3

Show file

File: blur.cpp Project: yikouniao/point-features-based-tracking

void GaussianBlur(const Mat& src, Mat& dst, int kwidth, int kheight,
                  double sigmax, double sigmay) {
  if (!(kwidth % 2) || !(kheight % 2) || kwidth < 0 || kheight < 0 ||
      (kwidth == 1 && kheight == 1) || sigmax <= 0 || sigmay <= 0) {
    dst = src;
    return;
  }

  Mat dst_(src.rows, src.cols);
  dst_.Allocate();

  // Get kernels
  vector<float> kernelx, kernely;
  GetGaussianKernel(kernelx, kwidth, sigmax);
  GetGaussianKernel(kernely, kheight, sigmay);

  // Blur
  GaussianBlurImpl(src, dst_, kernelx, kernely);

  dst.Release();
  dst = dst_;
}