I have a matrix of 630 values (values range from 0-35)...
I want to find the most frequently occurring value in this matrix. So how do I write a histogram for this? Also is there any other way that I can find the most frequently occurring value (I don't want to use counters as i will need 36 counters and My code would become very inefficient)
..Thanks!
You can use calcHist with a Mat of size 1xN, where N is 630 in your case.
I don't understand your argument against counters. To build the histogram, you must use counters anyway. There are ways to make counting very efficient.
OR
Assuming your image is a cv::Mat variable im with size 1x630 and type CV_8UC1, try:
std::vector<int> counts(36, 0);
for (int c = 0; c < 630; c++)
counts.at(im.at<unsigned char>(1, c)) += 1;
std::cout << "Most frequently occuring value: " << std::max_element(counts);
This uses counting, but will not take more than 0.1ms on an average PC.
Why not do it manually?
Mat myimage(cvSize(1,638), CV_8U);
randn(myimage, Scalar::all(128), Scalar::all(20)); //Random fill
vector<int> histogram(256);
for (int i=0;i<638;i++)
histogram[(int)myimage.at<uchar>(i,0)]++;
Related
I want to make an Identity matrix and then subtract some different floats from its diagonal elements. Here is what I have done:
cv::Mat R = cv::Mat::eye(trainingMat.rows,trainingMat.rows, CV_32F);
(trainingMat is an other matrix)And here is the strange thing. When I write:
std::cerr<<R.at<double>(0,0)<<std::endl;
I get an strange number(but it should be 1.0f right?). And when I do this:
for(unsigned int i = 0; i < trainingMat.rows; i++){
std::cerr<<R.at<double>(i,i)<<std::endl;
}
again I get some strange numbers. What am I doing wrong?
I met this kind of situation several times which turn out to be the problem of Wrong Type of the Mat.
Here are some pairs that you may keep in mind.
CV_8U <-> uchar
CV_32S <-> int
CV_32F <-> float
CV_64F <-> double
TYPE float takes up 4 bytes, and double takes up 8 bytes in the memory.
You try to using double to take one element, but in fact, you take two elements, and use these two to represent one. so you got the unexpected number.
I want to create a 1-D array of exactly 100 values and at each index store the index of another array. If I am to use std::vector<int16_t> someVector, how do I ensure that someVector has only 100 values and maybe add the first value at location 48 like someVector[48] = 29322, and so on.
As an alternative I tried creating a 1-D mat of Mat someArray(1,100,CV_16UC1,Scalar(9999)). Now when I try to retrieve the value at index 48, by using int retrievedValue = someArray.row(0).col(48), it says cannot convert from Mat to int.
I realize I'm doing something crazy for something very simple, but please help.
When you initialize vector you can set its size:
std::vector<int16_t> someVector(100);
This way it will be created with as array of 100 elements. But don't forget that size of vector may be changed later.
As for Mat, operators like row() or col() give you sub-matrix of initial matrix. So the code you created will return you a 1x1 matrix, not a short. If you want to access an element in matrix it should be:
int retrievedValue = someArray.at<ushort>(0,48);
can any one help me about how to get the absolute value of a complex matrix.the matrix contains real value in one channel and imaginary value in another one channel.please help me
if s possible means give me some example.
Thanks in advance
Arangarajan
Let's assume you have 2 components: X and Y, two matrices of the same size and type. In your case it can be real/im values.
// n rows, m cols, type float; we assume the following matrices are filled
cv::Mat X(n,m,CV_32F);
cv::Mat Y(n,m,CV_32F);
You can compute the absolute value of each complex number like this:
// create a new matrix for storage
cv::Mat A(n,m,CV_32F,cv::Scalar(0.0));
for(int i=0;i<n;i++){
// pointer to row(i) values
const float* rowi_x = X.ptr<float>(i);
const float* rowi_y = Y.ptr<float>(i);
float* rowi_a = A.ptr<float>(i);
for(int j=0;j<=m;j++){
rowi_a[j] = sqrt(rowi_x[j]*rowi_x[j]+rowi_y[j]*rowi_y[j]);
}
}
If you look in the OpenCV phasecorr.cpp module, there's a function called magSpectrums that does this already and will handle conjugate symmetry-packed DFT results too. I don't think it's exposed by the header file, but it's easy enough to copy it. If you care about speed, make sure you compile with any available SIMD options turned on too because they can make a big difference with this calculation.
I am trying to make the dft of one single channeled image, and as cvDft is expecting complex values, I was adviced to merge the original image with another image with all 0's so this last one will be considered as imaginary part.
My problem comes when using cvmerge function,
Mat tmp = imread(filename,0);
if( tmp.empty() )
{cout << "Usage: dft <image_name>" << endl;
return -1;}
Mat Result(tmp.rows,tmp.cols,CV_64F,2);
Mat tmp1(tmp.rows,tmp.cols,CV_64F, 0);
Mat image(tmp.rows,tmp.cols,CV_64F,2);
cvMerge(tmp,tmp1,image);`
It gives me the next error: can not convert cvMAt to cvArr
Anyone could help me? thanks!
1) it seems like you're mixing up 2 different styles of opencv code
cv::Mat (- Mat) is a c++ class from the new version of opencv, cvMerge is a c function from the old version of opencv.
instead of using cvmerge use merge
2) you're trying to merge a matrix (tmp) of type CV_8U (probably) with a CV_64F
use convertTo to get tmp as CV_64F
3) why is your Result & image mats (the destination mat) are initializes to cv::Scalar(2)? i think you're misusing the constractor parameters. see here for more info.
4) you're image mat is a single channel mat and you wanted it as a 2 channel mat (as mentioned in the question), change the declaration to
Mat image(tmp.rows,tmp.cols,CV_64FC2);
Currently, I'm working on a project in medical engineering. I have a big image with several sub-images of the cell, so my first task is to divide the image.
I thought about the next thing:
Convert the image into binary
doing a projection of the brightness pixels into the x-axis so I can see where there are gaps between brightnesses values and then divide the image.
The problem comes when I try to reach the second part. My idea is using a vector as the projection and sum all the brightnesses values all along one column, so the position number 0 of the vector is the sum of all the brightnesses values that are in the first column of the image, the same until I reach the last column, so at the end I have the projection.
This is how I have tried:
void calculo(cv::Mat &result,cv::Mat &binary){ //result=the sum,binary the imag.
int i,j;
for (i=0;i<=binary.rows;i++){
for(j=0;j<=binary.cols;j++){
cv::Scalar intensity= binaria.at<uchar>(j,i);
result.at<uchar>(i,i)=result.at<uchar>(i,i)+intensity.val[0];
}
cv::Scalar intensity2= result.at<uchar>(i,i);
cout<< "content" "\n"<< intensity2.val[0] << endl;
}
}
When executing this code, I have a violation error. Another problem is that I cannot create a matrix with one unique row, so...I don't know what could I do.
Any ideas?! Thanks!
At the end, it does not work, I need to sum all the pixels in one COLUMN. I did:
cv::Mat suma(cv::Mat& matrix){
int i;
cv::Mat output(1,matrix.cols,CV_64F);
for (i=0;i<=matrix.cols;i++){
output.at<double>(0,i)=norm(matrix.col(i),1);
}
return output;
}
but It gave me a mistake:
Assertion failed (0 <= colRange.start && colRange.start <= colRange.end && colRange.end <= m.cols) in Mat, file /home/usuario/OpenCV-2.2.0/modules/core/src/matrix.cpp, line 276
I dont know, any idea would be helpful, anyway many thanks mevatron, you really left me in the way.
If you just want the sum of the binary image, you could simply take the L1-norm. Like so:
Mat binaryVectorSum(const Mat& binary)
{
Mat output(1, binary.rows, CV_64F);
for(int i = 0; i < binary.rows; i++)
{
output.at<double>(0, i) = norm(binary.row(i), NORM_L1);
}
return output;
}
I'm at work, so I can't test it out, but that should get you close.
EDIT : Got home. Tested it. It works. :) One caveat...this function works if your binary matrix is truly binary (i.e., 0's and 1's). You may need to scale the norm output with the maximum value if the binary matrix is say 0's and 255's.
EDIT : If you don't have using namespace cv; in your .cpp file, then you'll need to declare the namespace to use NORM_L1 like this cv::NORM_L1.
Have you considered transposing the matrix before you call the function? Like this:
sumCols = binaryVectorSum(binary.t());
vs.
sumRows = binaryVectorSum(binary);
EDIT : A bug with my code :)
I changed:
Mat output(1, binary.cols, CV_64F);
to
Mat output(1, binary.rows, CV_64F);
My test case was a square matrix, so that bug didn't get found...
Hope that is helpful!