在OpenCV中将Mat转换为Array / Vector

I am novice in OpenCV. Recently, I have troubles finding OpenCV functions to convert from Mat to Array. I researched with .ptr and .at methods available in OpenCV APIs, but I could not get proper data. I would like to have direct conversion from Mat to Array(if available, if not to Vector). I need OpenCV functions because the code has to be undergo high level synthesis in Vivado HLS. Please help.

我是OpenCV的新手。最近，我发现OpenCV函数从Mat转换为Array很麻烦。我使用OpenCV API中提供的.ptr和.at方法进行了研究，但是我无法获得正确的数据。我希望从Mat到Array直接转换（如果可用，如果没有，则转换为Vector）。我需要OpenCV函数，因为代码必须在Vivado HLS中进行高级综合。请帮忙。

6 个解决方案

#1

If the memory of the Mat mat is continuous (all its data is continuous), you can directly get its data to a 1D array:

如果Mat mat的内存是连续的（其所有数据都是连续的），您可以直接将其数据转换为1D数组：

std::vector<uchar> array(mat.rows*mat.cols);
if (mat.isContinuous())
    array = mat.data;

Otherwise, you have to get its data row by row, e.g. to a 2D array:

否则，您必须逐行获取其数据，例如到2D数组：

uchar **array = new uchar*[mat.rows];
for (int i=0; i<mat.rows; ++i)
    array[i] = new uchar[mat.cols];

for (int i=0; i<mat.rows; ++i)
    array[i] = mat.ptr<uchar>(i);

---

UPDATE: It will be easier if you're using std::vector, where you can do like this:

更新：如果你使用std :: vector会更容易，你可以这样做：

std::vector<uchar> array;
if (mat.isContinuous()) {
  array.assign(mat.datastart, mat.dataend);
} else {
  for (int i = 0; i < mat.rows; ++i) {
    array.insert(array.end(), mat.ptr<uchar>(i), mat.ptr<uchar>(i)+mat.cols);
  }
}

p.s.: For cv::Mats of other types, like CV_32F, you should do like this:

p.s。：对于其他类型的cv :: Mats，比如CV_32F，你应该这样做：

std::vector<float> array;
if (mat.isContinuous()) {
  array.assign((float*)mat.datastart, (float*)mat.dataend);
} else {
  for (int i = 0; i < mat.rows; ++i) {
    array.insert(array.end(), mat.ptr<float>(i), mat.ptr<float>(i)+mat.cols);
  }
}

#2

Here is another possible solution assuming matrix have one column( you can reshape original Mat to one column Mat via reshape):

这是另一种可能的解决方案，假设矩阵有一列（您可以通过重塑将原始Mat重新整形为一列Mat）：

Mat matrix= Mat::zeros(20, 1, CV_32FC1);
vector<float> vec;
matrix.col(0).copyTo(vec);

#3

Instead of getting image row by row, you can put it directly to an array. For CV_8U type image, you can use byte array, for other types check here.

您可以将其直接放入数组，而不是逐行获取图像。对于CV_8U类型的图像，可以使用字节数组，其他类型请在此处查看。

Mat img; // Should be CV_8U for using byte[]
int size = (int)img.total() * img.channels();
byte[] data = new byte[size];
img.get(0, 0, data); // Gets all pixels

#4

None of the provided examples here work for the generic case, which are N dimensional matrices. Anything using "rows" assumes theres columns and rows only, a 4 dimensional matrix might have more.

这里提供的示例都不适用于通用情况，即N维矩阵。任何使用“行”的东西都只假设列和行，4维矩阵可能有更多。

Here is some example code copying a non-continuous N-dimensional matrix into a continuous memory stream - then converts it back into a Cv::Mat

下面是一些将非连续N维矩阵复制到连续内存流中的示例代码 - 然后将其转换回Cv :: Mat

#include <iostream>
#include <cstdint>
#include <cstring>
#include <opencv2/opencv.hpp>

int main(int argc, char**argv)
{
    if ( argc != 2 )
    {
        std::cerr << "Usage: " << argv[0] << " <Image_Path>\n";
        return -1;
    }
    cv::Mat origSource = cv::imread(argv[1],1);

    if (!origSource.data) {
        std::cerr << "Can't read image";
        return -1;
    }

    // this will select a subsection of the original source image - WITHOUT copying the data
    // (the header will point to a region of interest, adjusting data pointers and row step sizes)
    cv::Mat sourceMat = origSource(cv::Range(origSource.size[0]/4,(3*origSource.size[0])/4),cv::Range(origSource.size[1]/4,(3*origSource.size[1])/4));

    // correctly copy the contents of an N dimensional cv::Mat
    // works just as fast as copying a 2D mat, but has much more difficult to read code :)
    // see http://*.com/questions/18882242/how-do-i-get-the-size-of-a-multi-dimensional-cvmat-mat-or-matnd
    // copy this code in your own cvMat_To_Char_Array() function which really OpenCV should provide somehow...
    // keep in mind that even Mat::clone() aligns each row at a 4 byte boundary, so uneven sized images always have stepgaps
    size_t totalsize = sourceMat.step[sourceMat.dims-1];
    const size_t rowsize = sourceMat.step[sourceMat.dims-1] * sourceMat.size[sourceMat.dims-1];
    size_t coordinates[sourceMat.dims-1] = {0};
    std::cout << "Image dimensions: ";
    for (int t=0;t<sourceMat.dims;t++)
    {
        // calculate total size of multi dimensional matrix by multiplying dimensions
        totalsize*=sourceMat.size[t];
        std::cout << (t>0?" X ":"") << sourceMat.size[t];
    }
    // Allocate destination image buffer
    uint8_t * imagebuffer = new uint8_t[totalsize];
    size_t srcptr=0,dptr=0;
    std::cout << std::endl;
    std::cout << "One pixel in image has " << sourceMat.step[sourceMat.dims-1] << " bytes" <<std::endl;
    std::cout << "Copying data in blocks of " << rowsize << " bytes" << std::endl ;
    std::cout << "Total size is " << totalsize << " bytes" << std::endl;
    while (dptr<totalsize) {
        // we copy entire rows at once, so lowest iterator is always [dims-2]
        // this is legal since OpenCV does not use 1 dimensional matrices internally (a 1D matrix is a 2d matrix with only 1 row)
        std::memcpy(&imagebuffer[dptr],&(((uint8_t*)sourceMat.data)[srcptr]),rowsize);
        // destination matrix has no gaps so rows follow each other directly
        dptr += rowsize;
        // src matrix can have gaps so we need to calculate the address of the start of the next row the hard way
        // see *brief* text in opencv2/core/mat.hpp for address calculation
        coordinates[sourceMat.dims-2]++;
        srcptr = 0;
        for (int t=sourceMat.dims-2;t>=0;t--) {
            if (coordinates[t]>=sourceMat.size[t]) {
                if (t==0) break;
                coordinates[t]=0;
                coordinates[t-1]++;
            }
            srcptr += sourceMat.step[t]*coordinates[t];
        }
   }

   // this constructor assumes that imagebuffer is gap-less (if not, a complete array of step sizes must be given, too)
   cv::Mat destination=cv::Mat(sourceMat.dims, sourceMat.size, sourceMat.type(), (void*)imagebuffer);

   // and just to proof that sourceImage points to the same memory as origSource, we strike it through
   cv::line(sourceMat,cv::Point(0,0),cv::Point(sourceMat.size[1],sourceMat.size[0]),CV_RGB(255,0,0),3);

   cv::imshow("original image",origSource);
   cv::imshow("partial image",sourceMat);
   cv::imshow("copied image",destination);
   while (cv::waitKey(60)!='q');
}

#5

byte * matToBytes(Mat image)
{
   int size = image.total() * image.elemSize();
   byte * bytes = new byte[size];  //delete[] later
   std::memcpy(bytes,image.data,size * sizeof(byte));
}

#6

cv::Mat m;
m.create(10, 10, CV_32FC3);

float *array = (float *)malloc( 3*sizeof(float)*10*10 );
cv::MatConstIterator_<cv::Vec3f> it = m.begin<cv::Vec3f>();
for (unsigned i = 0; it != m.end<cv::Vec3f>(); it++ ) {
    for ( unsigned j = 0; j < 3; j++ ) {
        *(array + i ) = (*it)[j];
        i++;
    }
}

Now you have a float array. In case of 8 bit, simply change float to uchar and Vec3f to Vec3b and CV_32FC3 to CV_8UC3