OpenCV2.4.4+CUDA+VS2010实现图像的反转

    实现图像的反转并不难，小编在opencv篇中已经把代码贴出。本文却又旧事重提，主要为了用CUDA实现并行处理反转过程，代码难度并不大，但是却是对opencv+CUDA结合起来的一个应用，给以后一些运算量大的图像算法用CUDA并行运算实现提供一个现实参考，好了，废话不多说，先贴上代码：

/***************************************************************************************************** *    File name: cudaCppMain.cpp *    Author: source code by RamiYim *    Version: cs-hhu-cn0.0 *    Date: 2014.08.12 *    Description: 测试cuda与opencv相结合 *    Others: *    Function List: main functions and its function *    History:<rami>,<20140819>,<添加相关函数>,<desc>       <rami>,<20140812>,<创建文件>,<desc>******************************************************************************************************/#include "reverseImage.h"int main(){    reverseImage(cvLoadImage("D:/lena.jpg"));    return 0;}

/***************************************************************************************************** *    File name: reverseImage.h *    Author: source code by RamiYim *    Version: cs-hhu-cn0.0 *    Date: 2014.08.12 *    Description: 测试cuda与opencv相结合 *    Others: *    Function List: main functions and its function *    History:<rami>,<20140819>,<添加相关函数>,<desc>       <rami>,<20140812>,<创建文件>,<desc>******************************************************************************************************/#include "cv.h"#include "highgui.h"void reverseImage(IplImage *);

/***************************************************************************************************** *    File name: reverseImage.cpp *    Author: source code by RamiYim *    Version: cs-hhu-cn0.0 *    Date: 2014.08.12 *    Description: 测试cuda与opencv相结合 *    Others: *    Function List: 实现reverseImage函数 *    History:<rami>,<20140819>,<添加相关函数>,<desc>  *            <rami>,<20140812>,<创建文件>,<desc>******************************************************************************************************/#include "reverseImage.h"#include "cv.h"extern "C" int revImg(const char *, int size);void reverseImage(IplImage *sourceImage){     cvNamedWindow("sourceImage");     cvShowImage("sourceImage", sourceImage);     cvWaitKey(0);     int width, height, channels, width_step;     width = sourceImage -> width;     height = sourceImage -> height;     channels = sourceImage -> nChannels;     width_step = sourceImage -> widthStep;     const char *data = sourceImage -> imageData;    int size = width * height * channels;     revImg(data, size);     cvShowImage("reversedImage", sourceImage);    cvWaitKey(0);    cvDestroyWindow("sourceImage");     cvDestroyWindow("reversedImage");}

#include "cuda_runtime.h"#include "device_launch_parameters.h"#include <stdio.h>#include "cv.h"#include "highgui.h"cudaError_t addWithCuda(char *data, int size);__global__ void revImg(char *dev_c){    int bid = blockIdx.x * gridDim.x + blockIdx.y;   //gridDim.x为固定值400，blockIdx.x取值范围为0~399    int tid = bid * blockDim.x + threadIdx.x;        //blockDim.x为定值3，threadIdx.x取值范围为0~2    dev_c[tid] = 255 - dev_c[tid];                   //实现反转主体功能}extern "C" void revImg(char *data, int size){    cudaError_t cudaStatus = addWithCuda(data, size);    if (cudaStatus != cudaSuccess) {        fprintf(stderr, "addWithCuda failed!");    }}cudaError_t addWithCuda(char *data, int size) {    char *dev_c = 0;    cudaError_t cudaStatus;    // Choose which GPU to run on, change this on a multi-GPU system.    cudaStatus = cudaSetDevice(0);    if (cudaStatus != cudaSuccess) {        fprintf(stderr, "cudaSetDevice failed!  Do you have a CUDA-capable GPU installed?");        goto Error;    }    // Allocate GPU buffers for dev_c    cudaStatus = cudaMalloc((void**)&dev_c, size * sizeof(char));    if (cudaStatus != cudaSuccess) {        fprintf(stderr, "cudaMalloc failed!");        goto Error;    }    // Copy input vectors from host memory to GPU buffers.    cudaStatus = cudaMemcpy(dev_c, data, size * sizeof(char), cudaMemcpyHostToDevice);    if (cudaStatus != cudaSuccess) {        fprintf(stderr, "cudaMemcpy failed!");        goto Error;    }    // Launch a kernel on the GPU with one thread for each element.    dim3 dimGrid(400, 400);    dim3 dimBlock(3, 1);        //1行3列    revImg<<<dimGrid, dimBlock>>>(dev_c);        //调用内核函数    // Check for any errors launching the kernel    cudaStatus = cudaGetLastError();    if (cudaStatus != cudaSuccess) {        fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));        goto Error;    }    // cudaDeviceSynchronize waits for the kernel to finish, and returns    // any errors encountered during the launch.    cudaStatus = cudaDeviceSynchronize();    if (cudaStatus != cudaSuccess) {        fprintf(stderr, "cudaDeviceSynchronize returned error code %d after launching addKernel!\n", cudaStatus);        goto Error;    }    // Copy output vector from GPU buffer to host memory.    cudaStatus = cudaMemcpy(data, dev_c, size * sizeof(char), cudaMemcpyDeviceToHost);    if (cudaStatus != cudaSuccess) {        fprintf(stderr, "cudaMemcpy failed!");        goto Error;    }Error:    cudaFree(dev_c);    return cudaStatus;}

以上即为函数的主体功能，结果如下图：

PS:CUDA环境配置见本人博客，地址为：http://blog.csdn.net/a2112233445566/article/details/38420567

       OpenCV环境配置件本人博客，地址为：http://blog.csdn.net/a2112233445566/article/details/38540389