Custom Kernel GpuMat with float

Question

I'm trying to write a custom kernel using GpuMat data to find the arc cosine of an image's pixels. I can upload, download, and change values when I upload data when the GPU has CV_8UC1 data but chars cannot be used to calculate arc cosines. However, when I try to convert my GPU to CV_32FC1 type (floats) I get an illegal memory access error during the download part. Here is my code:

//.cu code 
#include <cuda_runtime.h>
#include <stdlib.h>
#include <iostream>
#include <stdio.h>
__global__ void funcKernel(const float* srcptr, float* dstptr, size_t srcstep, const     size_t dststep, int cols, int rows){
    int rowInd = blockIdx.y*blockDim.y+threadIdx.y;
    int colInd = blockIdx.x*blockDim.x+threadIdx.x;
    if(rowInd >= rows || colInd >= cols)
            return;
    const float* rowsrcptr=srcptr+rowInd*srcstep;
    float* rowdstPtr=  dstptr+rowInd*dststep;
    float val = rowsrcptr[colInd];
    if((int) val % 90 == 0)
            rowdstPtr[colInd] = -1 ;
    else{
            float acos_val = acos(val);
            rowdstPtr[colInd] = acos_val;
    }
}

int divUp(int a, int b){
    return (a+b-1)/b;
}

extern "C"
{
void func(const float* srcptr, float* dstptr, size_t srcstep, const size_t dststep, int cols, int rows){
    dim3 blDim(32,8);
    dim3 grDim(divUp(cols, blDim.x), divUp(rows,blDim.y));
    std::cout << "calling kernel from func\n";
    funcKernel<<<grDim,blDim>>>(srcptr,dstptr,srcstep,dststep,cols,rows);
    std::cout << "done with kernel call\n";
     cudaDeviceSynchronize();
}

//.cpp code
void callKernel(const GpuMat &src, GpuMat &dst){
    float* p = (float*)src.data;
    float* p2 =(float*) dst.data;
    func(p,p2,src.step,dst.step,src.cols,src.rows);
}

int main(){
    Mat input = imread("cat.jpg",0);
    Mat float_input;
    input.convertTo(float_input,CV_32FC1);
    GpuMat d_frame,d_output;
    Size size = float_input.size();
    d_frame.upload(float_input);
    d_output.create(size,CV_32FC1);
    callKernel(d_frame,d_output);
    Mat output(d_output);
    return 0;
}

When I run the program my compiler tells me this:

OpenCV Error: Gpu API call (an illegal memory access was encountered) in copy, file /home/mobile/opencv-2.4.9/modules/dynamicuda/include/opencv2/dynamicuda/dynamicuda.hpp, line 882 terminate called after throwing an instance of 'cv::Exception' what(): /home/mobile/opencv-2.4.9/modules/dynamicuda/include/opencv2/dynamicuda/dynamicuda.hpp:882: error: (-217) an illegal memory access was encountered in function copy

Answer 1

You can use cv::cuda::PtrStp<> or cv::cuda::PtrStpSz<> to write your own kernel (so you have not to use the step-Parameter for the GpuMat and it simplifies your code a little bit :D):

Kernel:

    __global__ void myKernel(const cv::cuda::PtrStepSzf input,
                             cv::cuda::PtrStepSzf output)
    {
        int x = blockIdx.x * blockDim.x + threadIdx.x;
        int y = blockIdx.y * blockDim.y + threadIdx.y;

        if (x <= input.cols - 1 && y <= input.rows - 1 && y >= 0 && x >= 0)
        {
           output(y, x) = input(y, x);
        }
    }

Notice:
cv::cuda::PtrStep<> : without size information
cv::cuda::PtrStepSz<>: with size information
cv::cuda::PtrStepSzb: for unsigned char Mats (CV_8U)
cv::cuda::PtrStepSzf: for float Mats (CV_32F)
cv::cuda::PtrStep<cv::Point2f>: example for other type

The Kernel call:

    void callKernel(cv::InputArray _input,
                    cv::OutputArray _output,
                    cv::cuda::Stream _stream)
    {
        const cv::cuda::GpuMat input = _input.getGpuMat();

        _output.create(input.size(), input.type()); 
        cv::cuda::GpuMat output = _output.getGpuMat();

        dim3 cthreads(16, 16);
        dim3 cblocks(
            static_cast<int>(std::ceil(input1.size().width /
                static_cast<double>(cthreads.x))),
            static_cast<int>(std::ceil(input1.size().height / 
                static_cast<double>(cthreads.y))));

        cudaStream_t stream = cv::cuda::StreamAccessor::getStream(_stream);
        myKernel<<<cblocks, cthreads, 0, stream>>>(input, output);

        cudaSafeCall(cudaGetLastError());
    }

You can call this function using cv::cuda::GpuMat:

   callKernel(d_frame, d_output, cv::cuda::Stream());

Answer 2

You are treating image step as if it is a float offset. It is a byte offset from one row to the next.

Try something like this instead:

const float* rowsrcptr= (const float *)(((char *)srcptr)+rowInd*srcstep);
float* rowdstPtr=  (float *) (((char *)dstptr)+rowInd*dststep);

from the documentation:

step – Number of bytes each matrix row occupies.

It's also a good idea to add proper cuda error checking to your code (e.g. to func). And you can run your code with cuda-memcheck to see the actual kernel failure generating the invalid reads/writes.