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I just would like to inform you that according to performance criteria i would like to transfer image processing algorithms from CPU to GPU.Therefore I will be able to run it faster in high resolution image(I hope)

But unfortunately ı get some errors using filters in cuda::filter implementation.First of all I use videostream to get image continously by using normal Mat variable.Then I convert it to GpuMat using Gpumat.upload(Mat) function and i call sobel filter function using GpuMat operations.

But unfortunately there is an error indicating after using apply function for filters(I found in Debug) : sobelxfilter->apply(gray_image, sobel_variables[0].Gradx);

The error is :

OpenCV Error: Gpu API call (invalid device symbol) in filter::linearRow, file c:\users\burak.dogancay\desktop\opencv\sources\modules\cudafilters\src\cuda\row_filter.hpp, line 365

I would like to share function that includes the sobel filter operation for clear understanding.

Code :

cuda::GpuMat Morphology::Sobel_operations(cuda::GpuMat& gray_image)

vector<Sobel_variables> sobel_variables(1);
//Sobel_variables sobel_variables;
sobel_variables[0].alpha = 1;

sobel_variables[0].beta = 0.9;

//Apply sobel filter to x
Ptr<cuda::Filter> sobelxfilter=cuda::createSobelFilter(gray_image.type(), sobel_variables[0].ddepth, 1, 0, 3);
sobelxfilter->apply(gray_image, sobel_variables[0].Gradx); **//error occurs after this operation**

//Apply sobel filter to y
Ptr<cuda::Filter> sobelyfilter = cuda::createSobelFilter(gray_image.type(),sobel_variables[0].ddepth, 0, 1, 3);
sobelyfilter->apply(gray_image, sobel_variables[0].Grady);

cuda::subtract(sobel_variables[0].Gradx, sobel_variables[0].Grady, sobel_variables[0].Gradient);

//normalize(sobel_variables[0].Gradient, sobel_variables[0].Gradient, 1, 0, NORM_MINMAX);
//convertScaleAbs(sobel_variables[0].Gradient, sobel_variables[0].Gradient);


cuda::add(sobel_variables[0].Grady, sobel_variables[0].Gradx, sobel_variables[0].Gradient1);


//convertScaleAbs(sobel_variables[0].Gradient1, sobel_variables[0].Gradient1);//It can be used but not necessary

cuda::addWeighted(sobel_variables[0].Gradient, sobel_variables[0].alpha, sobel_variables[0].Gradient1, sobel_variables[0].beta, 0, sobel_variables[0].Out_Image);

//Mat cpu_sobeloutimage=Mat(sobel_variables[0].Out_Image);

imshow("Sobel_operations", sobel_variables[0].Out_Image);

//------free memory of all unnecessarry images--------------------------
sobel_variables[0].Gradx.release();
sobel_variables[0].Grady.release();
gray_image.release();
sobel_variables[0].Gradient.release();
sobel_variables[0].Gradient1.release();

return sobel_variables[0].Out_Image;

}