opencv with cuda GaussianBlur

OpenCV is an open source computer vision and machine learning software library. It provides a wide range of image and video processing functions, including Gaussian blur. In addition, OpenCV supports GPU acceleration through CUDA, which can significantly improve the performance of image and video processing algorithms.

To use Gaussian blur with CUDA acceleration in OpenCV, you need to have a CUDA-enabled GPU and install the CUDA toolkit and cuDNN library. Then, you can use the cv::cuda::GaussianBlur function to apply Gaussian blur to an image.

Here's an example code snippet:

cv::Mat image = cv::imread("image.jpg");
cv::cuda::GpuMat gpuImage(image);
cv::cuda::GpuMat gpuResult;
cv::cuda::GaussianBlur(gpuImage, gpuResult, cv::Size(5, 5), 0);
cv::Mat result;
gpuResult.download(result);
cv::imshow("Result", result);
cv::waitKey();

In this code, we first load an image using cv::imread and create a cv::cuda::GpuMat object from it. Then, we create a cv::cuda::GpuMat object to store the result of the Gaussian blur operation. We call cv::cuda::GaussianBlur to apply the Gaussian blur to the GPU image, specifying the kernel size and sigma. Finally, we download the result back to the CPU and display it using cv::imshow.