HYPEREGO's profile - activity

The error is very explanatory, it say that you should recompile the entire library with the nonfree module. In opencv 3

The error is very explanatory, it say that you should recompile the entire library with the nonfree module. In opencv 3

how to resolve org.opencv.imgproc.Imgproc.blur_2(Native Method) Hello everyone, I am creating a system for object recogn

The pinhole in photography is used but the problem here is the autofocus from my perspective, i Think. And yeah, moreove

features2D is already on OpenCV, you should have it installed. Without any other information is difficult give an help.

@cudawarped sorry for tagging but your website is a reference for me THANK YOU A LOT and I hope that you can give to me

I finally solved this problem using the code from findFundamentalMat as suggested by @eduardo in his question and answer

The = operator in OpenCV is a soft-copy (just the mat header) while a copyTo is an hard-copy. Hard copy means that the e

That's strange, are you sure that you get the correct calibration matrices? It look like it is shifted, have you tried a

warpAffine and use the memory allocated on CUDA devices Hi folks, I' trying to to the following pipeline in C++ using Op

warpAffine and use the memory allocated on CUDA devices Hi folks, I' trying to to the following pipeline in C++ using Op

It can be an idea, I'll see if I've time. It is something that I should figure it out when everything is working, it sho

It can be an idea, I'll see if I've time, but is something that I should figure it out when everything is working, it sh

warpAffine and use the memory allocated on CUDA devices Hi folks, I' trying to to the following pipeline in C++ using Op

is it possibele to use 2 darknets one one machine with two Gpu ,s I want to use 2 seperate instances of darknet running

How warpAffine works? when i use warpAffine(InputArray src, OutputArray dst, InputArray M, Size dsize); imshow("dst",d

You can directly pass the array of GpuMats to kernels, but use them as an array of PtrStepSz in the kernel. You don't ha

Can you provide to me a little bit of more code? The input points should be a std::vector<cv::Point2f> or a cv::Ma

Can you provide to me a little bit of more code? The input points should be a std::vector<cv::point2f> or a cv::Ma

Ok, I got it but there are some tricky part. You need to apply an homography to make the two image as have been acquired

If you don't mind please mark my reply as correct answer to help who's looking at the same thing. Thank you!

What you're doing is completely fine. You just need to answer to this: which distance you would like to use? There are t

What you're doing is completely fine. You just need to answer to this: which distance you would like to use? There are t

Have you compiled it with the RELEASE flag instead of the DEBUG flag?

Hi guys,

as in the previous topics I made I'm still working on self calibration stuff. I'm generating the data for the evaluation but I end out with some strange error computing the residual error as defined here slide 31. But maybe I'm using the wrong function to compute the norm. The resulting residual error is absurd, while the epipolar equation x'Fx=0 give to me a residual of 0.25 so I suppose is almost perfect.

I've points correspondences for image L and R and the fundamental matrix. Actually I'm doing in this way, I don't care that it isn't efficient since is not important, is just for data generation.

 for(int i=0; i<maskInliers.rows; i++)
 {
    if((uchar)maskInliers.at<uchar>(i) == 1)
    {   
        inliersL.push_back(featuresL.at(i));
        inliersR.push_back(featuresR.at(i));

        cv::Mat temp_point_1 = cv::Mat(3,1,CV_64F);
        temp_point_1.at<double>(0,0) = featuresL.at(i).x;
        temp_point_1.at<double>(1,0) = featuresL.at(i).y;
        temp_point_1.at<double>(2,0) = 1;

        cv::Mat temp_point_2 = cv::Mat(3,1,CV_64F);
        temp_point_2.at<double>(0,0) = featuresR.at(i).x;
        temp_point_2.at<double>(1,0) = featuresR.at(i).y;
        temp_point_2.at<double>(2,0) = 1;

        /*******************************
        * COMPUTING THE F RESIDUALS
        *******************************/
        //Epipolar equation x'Fx=0
        cv::Mat tempResF = temp_point_2.t()*fundamentalMat*temp_point_1;
        residualF += fabs(tempResF.at<double>(0,0));

        //Residual error
        double resError = cv::norm(temp_point_2-(fundamentalMat*temp_point_1)) + 
                     cv::norm(temp_point_1-(fundamentalMat.t()*temp_point_2));
        residualF_error += resError;
     }
 }

I would like to find the residual error, is there any built in function to do that? I've looked on the documentation but I've not find it.

EDIT: the result I'm getting are the following:

Residual of F 0.250138
Mean residual of F 0.0039084
F RESIDUAL ERROR: 65237.2

where:

• Residual of F is computed using the epipolar geometry x'Fx=0
• mean error is the previous value divided by the number of inliers used for estimating the fundamental matrix
• The last one (F RESIDUAL ERROR) is the one that is wrong and that I'm asking about

I finally solved this problem using the code from findFundamentalMat as suggested by @eduardo in his question and answer

With OpenCV you have the tools to manipulate and do whatever you want with images. You have the tools, the knowledge sho

I'll reply to myself because I've done some very stupid errors. In the second part of the code I wrote: cv::Mat U_Open

It can't open the image correctly. Check if the path is correct and the file exist. The error is very easy to be unders

Dear guys,

I'm trying to solve SVD using the Eigen library, since I'm trying to solve one of the biggest error I've got so far in retrieving the fundamental matrix (here the link)

I'm using OpenCV 3.x and I can't compile OpenCV from sources with Eigen and/or LAPACK support, so I downloaded the Eigen library and putted under usr/local/include. No problem so far, I can see Eigen function and variables, so the linker and compiler are ok with that, I suppose. So, since I'm interesting in SVD and since I mostly use OpenCV for my stuff, I would like to write a function that directly compute the SVD for me. I've seen that there are a lot of possibilities to make cv::Mat working as Eigen::Matrix and vice-versa. What I would like is a function that do that:

int runEigenSVD(cv::InputArray _mat,
    cv::OutputArray _U, cv::OutputArray _S, cv::OutputArray _V,
    unsigned int QRPreconditioner,
    unsigned int computationOptions)

I'm not even able to compile since using different approaches I always get different errors. I obtain the input matrix with cv::Mat inputMat = _mat.getMat();, so suppose mat as my input matrix, always.

First try:

//OpenCV-> Eigen: it works!
 Eigen::Map<Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>
            mat_Eigen(inputMat.ptr<double>(), mat.rows, mat.cols);

//Executing Eigen stuff, here SVD
 Eigen::JacobiSVD<Eigen::MatrixXd, Eigen::FullPivHouseholderQRPreconditioner> 
            svd(mat_Eigen, Eigen::ComputeThinU | Eigen::ComputeThinV);

//Eigen -> OpenCV
 int U_row = svd.matrixU().rows();
 int U_cols = svd.matrixU().cols();
 cv::Mat U_OpenCV(U_row, U_cols, CV_64FC1, svd.matrixU().data());

The errors I got are in the last line:

invalid conversion from ‘const void’ to ‘void’ [-fpermissive]

no matching function for call to ‘cv::Mat::Mat(int&, int&, int, const Scalar*)’

Using eigen2cv and cv2eigen

I got always error, using both function, even with simple code like this one:

cv::Mat_<float> a = Mat_<float>::ones(2,2);
Eigen::Matrix<float,Eigen::Dynamic,Eigen::Dynamic> b;
cv::cv2eigen(a,b);

The error I get is:

Invalid arguments ' Candidates are:

void eigen2cv(const ? &, cv::Mat &)

void eigen2cv(const ? &, cv::Matx<#0,int3 #1 0,int3 #2 0> &)'

Any suggestion? The documentation regarding it is like... nothing and it's incredible that nobody else have done it so far!!

EDIT ## I'm able to map from Mat to Eigen, but still find no way to map it back without the use of for-loop

I'll reply to myself because I've done some very stupid errors. In the second part of the code I wrote: cv::Mat U_Open

You should define what is aligned from the algorithm point of view. For us, aligned means that the writing of the coins

The feature detection and matching are very common tasks, there are a LOT of tutorials. You just need to understand basi

This task is addressed as a augmented reality. There are several tutorial and articles on the web, I suggest you to star

Ciao, bel libro! (for english reader is just "hello, nice book!) Can you provide an example of the result that you expe

You need to take care about it. From the documentation of Sobel function you can see that the third argument is ddepth t

You should define what is aligned from the algorithm point of view. For us, aligned means that the writing of the coins

You should define what is aligned from the algorithm point of view. For us, aligned means that the writing of the coins