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opencv has nice row(i) col(i) functions, you can use those to build a new Mat from another one:

// this is only used for the easy initialization in this demo,
// usually you will have a plain Mat A:
Mat_<float> A(3,6);
A << 1,2,3,4,5,6,
     1,2,3,4,5,6,
     1,2,3,4,5,6;
// now we can start collecting the even cols of A,
// unfortunately opencv insists on pushing into *rows* here, 
// so we will need to transpose the result later..
Mat B;
for (int i=0; i<A.cols; i+=2)
{
    B.push_back(A.col(i));
}
// now we got 1 large 1d flat array with all the collected elements,
// let's make a 3x3 Mat of it again:
B = B.reshape(1,3); // 1 elem per channel, 3 rows.
B = B.t();          // transpose it
cerr << B << endl;
[1, 3, 5;
  1, 3, 5;
  1, 3, 5]

// here's the same thing for rows(no transpose needed):    
Mat_<float> A2(6,3);
A2 << 1,1,1,
     2,2,2,
     3,3,3,
     4,4,4,
     5,5,5,
     6,6,6;

Mat B2;
for (int i=0; i<A2.rows; i+=2)
{
    B2.push_back(A2.row(i));
}
cerr << B2.reshape(1,3) << endl;  
[1, 1, 1;
  3, 3, 3;
  5, 5, 5]

opencv has nice row(i) col(i) functions, you can use those to build a new Mat from another one:

// this is only used for the easy initialization in this demo,
// usually you will have a plain Mat A:
Mat_<float> A(3,6);
A << 1,2,3,4,5,6,
     1,2,3,4,5,6,
     1,2,3,4,5,6;
// now we can start collecting the even cols of A,
// unfortunately opencv insists on pushing into *rows* here, 
// so we will need to transpose the result later..
Mat B;
for (int i=0; i<A.cols; i+=2)
{
    B.push_back(A.col(i));
}
// now we got 1 large 1d flat (column) array with all the collected elements,
// let's make a 3x3 Mat of it again:
B = B.reshape(1,3); // 1 elem per channel, 3 rows.
B = B.t();          // transpose it
cerr << B << endl;
[1, 3, 5;
  1, 3, 5;
  1, 3, 5]

// here's the same thing for rows(no transpose needed):    
Mat_<float> A2(6,3);
A2 << 1,1,1,
     2,2,2,
     3,3,3,
     4,4,4,
     5,5,5,
     6,6,6;

Mat B2;
for (int i=0; i<A2.rows; i+=2)
{
    B2.push_back(A2.row(i));
}
// also, since we were pushing row vectors already, we can skip the reshape:
cerr << B2.reshape(1,3) << B2<< endl;  
[1, 1, 1;
  3, 3, 3;
  5, 5, 5]

opencv has nice row(i) col(i) functions, you can use those to build a new Mat from another one:

// this is only used for the easy initialization in this demo,
// usually you will have a plain Mat A:
Mat_<float> A(3,6);
A << 1,2,3,4,5,6,
     1,2,3,4,5,6,
     1,2,3,4,5,6;
// now we can start collecting the even cols of A,
// unfortunately opencv insists on pushing into *rows* here, 
// so we will need to transpose the result later..
Mat B;
for (int i=0; i<A.cols; i+=2)
{
    B.push_back(A.col(i));
}
// now we got 1 large 1d flat (column) array with all the collected elements,
// let's make a 3x3 Mat of it again:
B = B.reshape(1,3); // 1 elem per channel, B.reshape(-1,3); // keep channel count, but rearrange to 3 rows.
B = B.t();           // transpose it
cerr << B << endl;
[1, 3, 5;
  1, 3, 5;
  1, 3, 5]

// here's the same thing for rows(no transpose needed):    
Mat_<float> A2(6,3);
A2 << 1,1,1,
     2,2,2,
     3,3,3,
     4,4,4,
     5,5,5,
     6,6,6;

Mat B2;
for (int i=0; i<A2.rows; i+=2)
{
    B2.push_back(A2.row(i));
}
// also, since we were pushing row vectors already, we can skip the reshape:
cerr << B2<< endl;  
[1, 1, 1;
  3, 3, 3;
  5, 5, 5]

opencv has nice row(i) col(i) functions, you can use those to build a new Mat from another one:

// this is only used for the easy initialization in this demo,
// usually you will have a plain Mat A:
Mat_<float> A(3,6);
A << 1,2,3,4,5,6,
     1,2,3,4,5,6,
     1,2,3,4,5,6;
// now we can start collecting the even cols of A,
// unfortunately opencv insists on pushing into *rows* here, 
// so we will need to transpose the result later..
Mat B;
for (int i=0; i<A.cols; i+=2)
{
    B.push_back(A.col(i));
}
// now we got 1 large 1d flat (column) array with all the collected elements,
// let's make a 3x3 Mat of it again:
B = B.reshape(-1,3); B.reshape(0,3); // keep channel count, but rearrange to 3 rows.
B = B.t();           // transpose it
cerr << B << endl;
[1, 3, 5;
  1, 3, 5;
  1, 3, 5]

// here's the same thing for rows(no transpose needed):    
Mat_<float> A2(6,3);
A2 << 1,1,1,
     2,2,2,
     3,3,3,
     4,4,4,
     5,5,5,
     6,6,6;

Mat B2;
for (int i=0; i<A2.rows; i+=2)
{
    B2.push_back(A2.row(i));
}
// also, since we were pushing row vectors already, we can skip the reshape:
cerr << B2<< endl;  
[1, 1, 1;
  3, 3, 3;
  5, 5, 5]

opencv has nice row(i) col(i) functions, you can use those to build a new Mat from another one:

// this is only used for the easy initialization in this demo,
// usually you will have a plain Mat A:
Mat_<float> A(3,6);
A << 1,2,3,4,5,6,
     1,2,3,4,5,6,
     1,2,3,4,5,6;
// now we can start collecting the even cols of A,
// unfortunately opencv insists on pushing into *rows* here, 
// so we will need to transpose the result later..
Mat B;
for (int i=0; i<A.cols; i+=2)
{
    B.push_back(A.col(i));
}
// now we got 1 large 1d flat (column) array with all the collected elements,
// let's make a 3x3 Mat of it again:
B = B.reshape(0,3); B.reshape(0,A.cols/2); // keep channel count, but rearrange to 3 rows.
half the cols we had before.
B = B.t();           // transpose it
cerr << B << endl;
[1, 3, 5;
  1, 3, 5;
  1, 3, 5]

// here's the same thing for rows(no transpose needed):    
Mat_<float> A2(6,3);
A2 << 1,1,1,
     2,2,2,
     3,3,3,
     4,4,4,
     5,5,5,
     6,6,6;

Mat B2;
for (int i=0; i<A2.rows; i+=2)
{
    B2.push_back(A2.row(i));
}
// also, since we were pushing row vectors already, we can skip the reshape:
cerr << B2<< endl;  
[1, 1, 1;
  3, 3, 3;
  5, 5, 5]