CUDA和OpenCV混合编程,使用CUDA的纹理内存,实现图像的二值化以及滤波功能。


#include <cuda_runtime.h> 
#include <highgui/highgui.hpp>
#include <imgproc/imgproc.hpp>

using namespace cv;

int width = 512;
int height = 512;

// 2维纹理
texture<float, 2, cudaReadModeElementType> texRef;

// 核函数
__global__ void transformKernel(uchar* output, int width, int height)
{
	// 根据tid bid计算归一化的拾取坐标
	unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;
	unsigned int y = blockIdx.y * blockDim.y + threadIdx.y;
	float u = x / (float)width;
	float v = y / (float)height;

	//从纹理存储器中拾取数据,并写入显存
	output[(y * width + x)] = tex2D(texRef, u / 4, v / 4);
}

int main()
{
	// 分配CUDA数组
	cudaChannelFormatDesc channelDesc = cudaCreateChannelDesc(32, 0, 0, 0, cudaChannelFormatKindFloat);
	cudaArray* cuArray;
	cudaMallocArray(&cuArray, &channelDesc, width, height);

	//使用OpenCV读入图像
	Mat image = imread("D:\\lena.jpg", 0);
	resize(image, image, Size(width, height));
	imshow("原始图像", image);

	cudaMemcpyToArray(cuArray, 0, 0, image.data, width*height, cudaMemcpyHostToDevice);

	// 设置纹理属性
	texRef.addressMode[0] = cudaAddressModeWrap; //循环寻址方式
	texRef.addressMode[1] = cudaAddressModeWrap;
	texRef.filterMode = cudaFilterModeLinear;   //线性滤波
	texRef.normalized = true; //归一化坐标							 

	//绑定纹理
	cudaBindTextureToArray(texRef, cuArray, channelDesc);

	Mat imageOutput = Mat(Size(width, height), CV_8UC1);
	uchar * output = imageOutput.data;

	cudaMalloc((void**)&output, width * height * sizeof(float));

	dim3 dimBlock(16, 16);
	dim3 dimGrid((width + dimBlock.x - 1) / dimBlock.x, (height + dimBlock.y - 1) / dimBlock.y);

	transformKernel << <dimGrid, dimBlock >> > (output, width, height);

	cudaMemcpy(imageOutput.data, output, height*width, cudaMemcpyDeviceToHost);

	imshow("CUDA+OpenCV滤波", imageOutput);
	waitKey();

	cudaFreeArray(cuArray);
	cudaFree(output);
}


原始lena图像:



运行效果:



posted on 2017-02-08 21:04  未雨愁眸  阅读(591)  评论(0编辑  收藏  举报