-1 qt cuda gaussian filter npp
我尝试使用 CUDA 和 Qt 来模糊图像。我使用 NPP 库,nppiFilterGauss_8u_C1R 效果很好
void cuda_npp_gauss_filter_qt(uchar* pSourceData, uchar* pResultData, const int &ImageLineStep, const int &ImageWidth, const int &ImageHeight)
{
NppiSize oSizeROI;
oSizeROI.width = ImageWidth;
oSizeROI.height = ImageHeight;
Npp32s SourceStep = ImageLineStep;
Npp32s DestinationStep = ImageLineStep;
size_t AllocationSizeInBytes = ImageLineStep * ImageHeight;
Npp8u *pSource, *pDestination;
cudaMalloc<Npp8u>(&pSource,AllocationSizeInBytes);
cudaMalloc<Npp8u>(&pDestination,AllocationSizeInBytes);
cudaMemcpy(pSource, pSourceData, AllocationSizeInBytes, cudaMemcpyHostToDevice);
nppiFilterGauss_8u_C1R(pSource, SourceStep, pDestination, DestinationStep, oSizeROI, NPP_MASK_SIZE_15_X_15);
cudaMemcpy(pResultData, pDestination, AllocationSizeInBytes, cudaMemcpyDeviceToHost);
}
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但 nppiFilterGaussAdvanced_8u_C1R 会损坏图像
void cuda_npp_gauss_filter_qt_advanced(uchar* pSourceData, uchar* pResultData, const int &ImageLineStep, const int &ImageWidth, const int &ImageHeight, const int &Radius)
{
NppiSize oSizeROI;
oSizeROI.width = ImageWidth;
oSizeROI.height = ImageHeight;
Npp32s SourceStep = ImageLineStep;
Npp32s DestinationStep = ImageLineStep;
size_t AllocationSizeInBytes = ImageLineStep * ImageHeight;
Npp8u *pSource, *pDestination;
cudaMalloc<Npp8u>(&pSource,AllocationSizeInBytes);
cudaMalloc<Npp8u>(&pDestination,AllocationSizeInBytes);
//-------------------------------------------------------
int nFilterTaps = 2*((int)((float)ceil(Radius) + 0.5F)) + 1;
//-------------------------------------------------------
//-------------------------------------------------------
//-------------- Gaussian kernel ------------------------
double sigma = 0.3*((nFilterTaps-1)*0.5 - 1) + 0.8;
cv::Mat GaussianKernel = cv::getGaussianKernel(nFilterTaps, sigma, CV_32F);
//-------------------------------------------------------
//-------------------------------------------------------
cudaMemcpy(pSource, pSourceData, AllocationSizeInBytes, cudaMemcpyHostToDevice);
nppiFilterGaussAdvanced_8u_C1R (pSource, SourceStep, pDestination, DestinationStep, oSizeROI, nFilterTaps, (Npp32f*)GaussianKernel.data);
cudaMemcpy(pResultData, pDestination, AllocationSizeInBytes, cudaMemcpyDeviceToHost);
}
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我使用 OpenCV 创建高斯内核。
Xubuntu 16.04.1、Qt 5.7-1、CUDA 8.044、OpenCV 2.4.9。谢谢。
NPP 函数需要在设备上分配内存。OpenCV Mat(GaussianKernel
在本例中)默认分配在主机上。
所以下面这行代码就失效了。
nppiFilterGaussAdvanced_8u_C1R (pSource, SourceStep, pDestination, DestinationStep, oSizeROI, nFilterTaps, (Npp32f*)GaussianKernel.data);
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(Npp32f*)GaussianKernel.data
在传递到 NPP 功能之前,应将参数复制到设备。可以这样实现:
float* GaussianKernel_d;
size_t GaussianKernelBytes = GaussianKernel.step() * GaussianKernel.rows;
cudaMalloc<float>(&GaussianKernel_d, GaussianKernelBytes);
cudaMemcpy(GaussianKernel_d, GaussianKernel.data, GaussianKernelBytes, cudaMemcpyHostToDevice);
nppiFilterGaussAdvanced_8u_C1R (pSource, SourceStep, pDestination, DestinationStep, oSizeROI, nFilterTaps, GaussianKernel_d);
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