这里做的就是使用OpenCL对图像旋转90度，也算是一个比较入门级别的程序。希望对大家有所帮助吧，看着看着这些代码就熟悉了。
图像旋转是指把定义的图像绕某一点以逆时针或顺时针方向旋转一定的角度，通常是指绕图像的中心以逆时针方向旋转。假设图像的左上角为(left, top)，右下角为(right, bottom)，则图像上任意点(x0, y0) 绕其中心(xcenter, ycenter) 逆时针旋转angle 角度后，新的坐标位置(x′, y′) 的计算公式为：
需要对图像进行处理，那么在这里介绍一个库给大家：FreeImage。
不熟悉的请看：请点这里。
使用这个库的方法：（通用方法，极有效）
属性->C/C++->常规->附加包含目录：添加.h的路径。
链接器->常规->附加库目录: 添加lib路径。
链接器->输入->附加依赖项: 添加需要的lib名称。
将dll文件放入exe路径下。
#pragma OPENCL EXTENSION cl_amd_printf : enable
__kernel void image_rotate(
__global uchar * src_data,
__global uchar * dest_data,
//Data in global memory
int W,
int H,
//Image Dimensions
float sinTheta,
float cosTheta )
//Rotation Parameters
{
//Thread gets its index within index space
const int ix = get_global_id(0);
const int iy = get_global_id(1);
int xc = W/2;
int yc = H/2;
int xpos = ( ix-xc)*cosTheta - (iy-yc)*sinTheta+xc;
int ypos = ( ix-xc)*sinTheta + (iy-yc)*cosTheta+yc;
if ((xpos>=0) && (xpos< W) && (ypos>=0) && (ypos< H)) //Bound Checking
{
dest_data[ypos*W+xpos]= src_data[iy*W+ix];
}
}我们把这个东西和CPU串行处理比较一下可以得到如下：
//CPU旋转图像：使用CPU来旋转图片
void cpu_rotate(unsigned char* inbuf, unsigned char* outbuf, int w, int h,float sinTheta, float cosTheta)
{
int i, j;
int xc = w/2;
int yc = h/2;
for(i = 0; i < h; i++)
{
for(j=0; j< w; j++)
{
int xpos = ( j-xc)*cosTheta - (i-yc)*sinTheta+xc;
int ypos = (j-xc)*sinTheta + ( i-yc)*cosTheta+yc;
if(xpos>=0&&ypos>=0&&xpos<w&&ypos<h)
outbuf[ypos*w + xpos] = inbuf[i*w+j];
}
}
}对比之后我们发现OpenCL写kernel的时候循环没有了，取而代之的就是给出global_id即可。
这里还涉及到一些图片的操作，具体请看FreeImage的使用。
#include "stdafx.h"
#include <CL/cl.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <iostream>
#include <fstream>
#include "gFreeImage.h"
using namespace std;
#define NWITEMS 4
#pragma comment (lib,"OpenCL.lib")
#pragma comment (lib,"FreeImage.lib")
//把文本文件读入一个string中,其实就是把运行程序传给从机
int convertToString(const char *filename, std::string& s)
{
size_t size;
char* str;
std::fstream f(filename, (std::fstream::in | std::fstream::binary));
if(f.is_open())
{
size_t fileSize;
f.seekg(0, std::fstream::end);
size = fileSize = (size_t)f.tellg();
f.seekg(0, std::fstream::beg);
str = new char[size+1];
if(!str)
{
f.close();
return NULL;
}
f.read(str, fileSize);
f.close();
str[size] = ‘\0‘;
s = str;
delete[] str;
return 0;
}
printf("Error: Failed to open file %s\n", filename);
return 1;
}
//CPU旋转图像：使用CPU来旋转图片
void cpu_rotate(unsigned char* inbuf, unsigned char* outbuf, int w, int h,float sinTheta, float cosTheta)
{
int i, j;
int xc = w/2;
int yc = h/2;
for(i = 0; i < h; i++)
{
for(j=0; j< w; j++)
{
int xpos = ( j-xc)*cosTheta - (i-yc)*sinTheta+xc;
int ypos = (j-xc)*sinTheta + ( i-yc)*cosTheta+yc;
if(xpos>=0&&ypos>=0&&xpos<w&&ypos<h)
outbuf[ypos*w + xpos] = inbuf[i*w+j];
}
}
}
int main(int argc, char* argv[])
{
//装入图像
unsigned char *src_image=0;
unsigned char *cpu_image=0;
int W, H;
gFreeImage img;
if(!img.LoadImageGrey("lenna.jpg"))
{
printf("装入lenna.jpg失败\n");
exit(0);
}
else
src_image = img.getImageDataGrey(W, H);
size_t mem_size = W*H;
cpu_image = (unsigned char*)malloc(mem_size);
cl_uint status;
cl_platform_id platform;
//创建平台对象
status = clGetPlatformIDs( 1, &platform, NULL );
cl_device_id device;
//创建GPU设备
clGetDeviceIDs( platform, CL_DEVICE_TYPE_GPU,
1,
&device,
NULL);
//创建context
cl_context context = clCreateContext( NULL,
1,
&device,
NULL, NULL, NULL);
//创建命令队列
cl_command_queue queue = clCreateCommandQueue( context,
device,
CL_QUEUE_PROFILING_ENABLE, NULL );
//创建三个OpenCL内存对象，并把buf1的内容通过隐式拷贝的方式
//拷贝到clbuf1,buf2的内容通过显示拷贝的方式拷贝到clbuf2
cl_mem d_ip = clCreateBuffer(
context, CL_MEM_READ_ONLY,
mem_size,
NULL, NULL);
cl_mem d_op = clCreateBuffer(
context, CL_MEM_WRITE_ONLY,
mem_size,
NULL, NULL);
status = clEnqueueWriteBuffer (
queue , d_ip, CL_TRUE,
0, mem_size, (void *)src_image,
0, NULL, NULL);
const char * filename = "rotate.cl";
std::string sourceStr;
status = convertToString(filename, sourceStr);
const char * source = sourceStr.c_str();
size_t sourceSize[] = { strlen(source) };
//创建程序对象
cl_program program = clCreateProgramWithSource(
context,
1,
&source,
sourceSize,
NULL);
//编译程序对象
status = clBuildProgram( program, 1, &device, NULL, NULL, NULL );
if(status != 0)
{
printf("clBuild failed:%d\n", status);
char tbuf[0x10000];
clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, 0x10000, tbuf, NULL);
printf("\n%s\n", tbuf);
return -1;
}
//创建Kernel对象
//Use the “image_rotate” function as the kernel
//创建Kernel对象
cl_kernel kernel = clCreateKernel( program, "image_rotate", NULL );
//设置Kernel参数
float sintheta = 1, costheta = 0;
clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&d_ip);
clSetKernelArg(kernel, 1, sizeof(cl_mem), (void *)&d_op);
clSetKernelArg(kernel, 2, sizeof(cl_int), (void *)&W);
clSetKernelArg(kernel, 3, sizeof(cl_int), (void *)&H);
clSetKernelArg(kernel, 4, sizeof(cl_float), (void *)&sintheta);
clSetKernelArg(kernel, 5, sizeof(cl_float), (void *)&costheta);
//Set local and global workgroup sizes
size_t localws[2] = {16,16} ;
size_t globalws[2] = {W, H};//Assume divisible by 16
cl_event ev;
//执行kernel
clEnqueueNDRangeKernel(
queue ,kernel,
2, 0, globalws, localws,
0, NULL, &ev);
clFinish( queue );
//计算kerenl执行时间
cl_ulong startTime, endTime;
clGetEventProfilingInfo(ev, CL_PROFILING_COMMAND_START,
sizeof(cl_ulong), &startTime, NULL);
clGetEventProfilingInfo(ev, CL_PROFILING_COMMAND_END,
sizeof(cl_ulong), &endTime, NULL);
cl_ulong kernelExecTimeNs = endTime-startTime;
printf("kernal exec time :%8.6f ms\n ", kernelExecTimeNs*1e-6 );
//数据拷回host内存
// copy results from device back to host
unsigned char *op_data=0;
op_data = (cl_uchar *) clEnqueueMapBuffer( queue,
d_op,
CL_TRUE,
CL_MAP_READ,
0,
mem_size,
0, NULL, NULL, NULL );
int i;
cpu_rotate(src_image,cpu_image, W, H, 1, 0);
for(i = 0; i < mem_size; i++)
{
src_image[i] =cpu_image[i];
}
img.SaveImage("cpu_lenna_rotate.jpg");
for(i = 0; i < mem_size; i++)
{
src_image[i] =op_data[i];
}
img.SaveImage("lenna_rotate.jpg");
if(cpu_image)
free(cpu_image);
//删除OpenCL资源对象
clReleaseMemObject(d_ip);
clReleaseMemObject(d_op);
clReleaseProgram(program);
clReleaseCommandQueue(queue);
clReleaseContext(context);
return 0;
}最初的图片：
用OpenCL处理之后：用了灰度图。
用CPU处理之后：用了灰度图。
FreeImage下载，请点击这里。
参考代码，请点击这里。
原文地址：http://blog.csdn.net/c602273091/article/details/45418223
