问题描述
我试图在每个像素的x方向的灰度图像上应用sobel滤镜，并显示结果。
X方向sobel过滤器为：-
I am trying to apply a sobel filter on a grayscale image in the x direction on each pixel and displaying the result.X direction sobel filter is:-
-1 0 1
-2 0 2
-1 0 1
我没有得到所需的结果。有人可以指出我的错误吗？我正在尝试使用纹理，但不确定是否正确使用了它：
I am not getting the required results. Can someone point out my mistakes? I am trying to use textures and I am not so sure as to whether I have used it correctly:
#include <cuda.h>
#include<iostream>
using namespace std;
#define CudaSafeCall( err ) __cudaSafeCall( err, __FILE__, __LINE__ )
#define CudaCheckError() __cudaCheckError( __FILE__, __LINE__ )
texture <float,2,cudaReadModeElementType> tex1;
//Kernel for x direction sobel
__global__ void implement_x_sobel(float* garbage,float* output,int width,int height,int widthStep)
{
int x=blockIdx.x*blockDim.x+threadIdx.x;
int y=blockIdx.y*blockDim.y+threadIdx.y;
float output_value=((0*tex2D(tex1,x,y))+(2*tex2D(tex1,x+1,y))+(-2*tex2D(tex1,x- 1,y))+(0*tex2D(tex1,x,y+1))+(1*tex2D(tex1,x+1,y+1))+(-1*tex2D(tex1,x-1,y+1))+ (1*tex2D(tex1,x+1,y-1))+(0*tex2D(tex1,x,y-1))+(-1*tex2D(tex1,x-1,y-1)));
output[y*widthStep+x]=output_value;
}
//Kernel for y direction sobel
//__global__ void implement_y_sobel(float* input,float* output,int width,int height,int widthStep)
//{
//}
//Host Code
inline void __cudaSafeCall( cudaError err, const char *file, const int line )
{
#ifdef CUDA_ERROR_CHECK
if ( cudaSuccess != err )
{
printf("cudaSafeCall() failed at %s:%i : %s\n",
file, line, cudaGetErrorString( err ) );
exit( -1 );
}
#endif
return;
}
inline void __cudaCheckError( const char *file, const int line )
{
#ifdef CUDA_ERROR_CHECK
cudaError err = cudaGetLastError();
if ( cudaSuccess != err )
{
printf("cudaCheckError() failed at %s:%i : %s\n",
file, line, cudaGetErrorString( err ) );
exit( -1 );
}
#endif
return;
}
void sobel(float* input,float* output,int width,int height,int widthStep)
{
cudaChannelFormatDesc channelDesc=cudaCreateChannelDesc(32,32,0,0,cudaChannelFormatKindFloat);
cudaArray * cuArray;
CudaSafeCall(cudaMallocArray(&cuArray,&channelDesc,width,height));
cudaMemcpyToArray(cuArray,0,0,input,widthStep*height,cudaMemcpyHostToDevice);
tex1.addressMode[0]=cudaAddressModeClamp;
tex1.addressMode[1]=cudaAddressModeClamp;
tex1.filterMode=cudaFilterModeLinear;
tex1.normalized=false;
cudaBindTextureToArray(tex1,cuArray,channelDesc);
float * D_output_x;
float * garbage=NULL;
CudaSafeCall(cudaMalloc(&D_output_x,widthStep*height));
dim3 blocksize(16,16);
dim3 gridsize;
gridsize.x=(width+blocksize.x-1)/blocksize.x;
gridsize.y=(height+blocksize.y-1)/blocksize.y;
//kernel call
implement_x_sobel<<<gridsize,blocksize>>>(garbage,D_output_x,width,height,widthStep/sizeof(float));
cudaThreadSynchronize();
CudaCheckError();
CudaSafeCall(cudaMemcpy(output,D_output_x,height*widthStep,cudaMemcpyDeviceToHost));
cudaFree(D_output_x);
cudaFree(garbage);
cudaFreeArray(cuArray);
}
我的主文件：-
#include<iostream>
#include <stdio.h>
#include <stdlib.h>
#include<opencv/highgui.h>
#include<opencv/cv.h>
#include"header.h"
using namespace std;
void main()
{
IplImage* img1=cvLoadImage("C://test.jpg",CV_LOAD_IMAGE_GRAYSCALE);
if( !img1) {
printf("ERROR: couldnt load file!\n");
}
IplImage* img2=cvCreateImage(cvGetSize(img1),IPL_DEPTH_32F,img1->nChannels);
IplImage* img3=cvCreateImage(cvGetSize(img1),IPL_DEPTH_32F,img1->nChannels);
unsigned char * pseudo_input=(unsigned char *)img1->imageData;
float * output=(float*)img2->imageData;
float *input=(float*)img3->imageData;
int s=img1->widthStep/sizeof(float);
for(int w=0;w<=(img1->height);w++)
for(int h=0;h<(img1->width*img1->nChannels);h++)
{
input[w*s+h]= pseudo_input[w*s+h];
}
sobel(input,output,img1->width,img1->height,img1->widthStep);
cvShowImage("Original Image",img1);
cvShowImage("Sobeled Image",img2);
cvWaitKey(0);
}}
推荐答案
很难诊断没有更多信息的问题。如果没有有意义的输出（例如，纹理读为全0），则表明纹理设置或绑定存在问题。
It is hard to diagnose the problem without more information. If you are getting no meaningful output (e.g. texture is reading all 0's), that implies a problem with your texture setup or binding.
如果您稍微偏离了一点，这可能是因为您需要将坐标偏移0.5f，并且在使用它时，在将int显式转换为float时要格外小心。如果在调用tex2D（）之前声明并分配了浮点型变量，则代码的运行不会变慢。
If you are off by a little bit, that is probably because you need to offset the coordinates by 0.5f, and while you are at it, be more careful about explicitly converting your ints to floats. The code won't run any slower if you declare and assign float-valued variables before calling tex2D().
这篇关于CUDA中x方向的Sobel滤波器的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！