Bonjour,
je suis nouveau dans la programmation en C. J'ai un programme Matlab qui marche bien, et je souhaiterais l'implémenter en C. Le pgm compile bien, mais me sort un "segmentation fault" à l'exécution. Le pgm doit prendre une image en RAW data en entrée, lui appliquer un algo de tri, puis en ressortir une image modifiée, toujours en RAW.
Il doit y avoir un pb de pointeurs...mais où? Si vous pouviez m'aider, ca serait vraiment inespéré!
Merci par avance.
Psysta
@mailPS: le pgm a l'air long, mais en grande partie à cause des déclarations et initialisations.
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#include <stdio.h>
#include <math.h>
#include <stdlib.h>
#define INT_TYPE unsigned int
#define IMAGE_TYPE unsigned char
#define DOUBLE_TYPE double
void fatal(s)
char *s;
{
printf("\n%s\n",s);
exit(-1);
}
FILE *fichier, *ouput;
IMAGE_TYPE **image, **newImage;
DOUBLE_TYPE *sumClustCol;
INT_TYPE *averageRowDist, *averageColDist, *averageCol, *colCent, *rowCent, *columnCent,
*whichColCent, **whichCent, **rowDistance, **columnDistance, *sumRowDistance,
*sumColDistance, *pixelsInClust, *colorOfCent;
int numClustCent=10, NBC=256, NBL=256;
int i, j, A, Q, O, P, I, J, k, K, N, M, R, S, X, Z, m1, m2, H, p=1,
whichColor,
currentRow,
currentColumn,
rowDist,
columnDist,
clustCent,
colCentOrder,
centerBelong;
double whichDistCent, totalDist;
long int taille;
main()
{ /* Entry variables */
averageRowDist = (unsigned int*)calloc(numClustCent, sizeof(unsigned int));
averageColDist = (unsigned int*)calloc(numClustCent, sizeof(unsigned int));
averageCol = (unsigned int*)calloc(numClustCent,sizeof(unsigned int));
for(i=0;i<numClustCent;i++)
{averageRowDist[i]=0;}
for(i=0;i<numClustCent;i++)
{averageColDist[i]=0;}
for(i=0;i<numClustCent;i++)
{averageCol[i]=0;}
colorOfCent = (unsigned int*)calloc(numClustCent,sizeof(unsigned int));
colCent = (unsigned int*)calloc(numClustCent, sizeof(unsigned int));
rowCent = (unsigned int*)calloc(numClustCent, sizeof(unsigned int));
columnCent = (unsigned int*)calloc(numClustCent, sizeof(unsigned int));
whichColCent = (unsigned int*)calloc(numClustCent, sizeof(unsigned int));
whichCent = (unsigned int**)calloc(NBC, sizeof(unsigned int));
for (i=0;i<NBL;i++)
{ whichCent[i] = (unsigned int*)calloc(NBC,sizeof(unsigned int));}
rowDistance = (unsigned int**)calloc(NBC, sizeof(unsigned int));
for (i=0;i<NBL;i++)
{ rowDistance[i] = (unsigned int*)calloc(NBC,sizeof(unsigned int));}
columnDistance = (unsigned int**)calloc(NBC, sizeof(unsigned int));
for (i=0;i<NBL;i++)
{ columnDistance[i] = (unsigned int*)calloc(NBC,sizeof(unsigned int));}
/* Reading of the image file */
if((fichier=fopen("lenna.dat","rb"))==NULL)
{fatal("Can't open input file");}
fseek(fichier,0,SEEK_END);
taille = ftell(fichier);
fseek(fichier,0,SEEK_SET);
image = (unsigned char**)calloc(NBC,sizeof(unsigned char));
for (i=0;i<NBL;i++)
{ image[i] = (unsigned char*)calloc(NBC,sizeof(unsigned char));}
fread(image[i][j],1,taille,fichier);
fclose(fichier);
newImage = (unsigned char**)calloc(NBC,sizeof(unsigned char));
for (i=0;i<NBL;i++)
{ newImage[i] = (unsigned char*)calloc(NBC,sizeof(unsigned char));}
/* start of Kmean algorithm */
m1 = floor((double)NBL/numClustCent);
m2 = floor((double)NBC/numClustCent);
/* see where to put cluster centers initially */
for(H=0;H<numClustCent;H++)
{ rowCent[H]= floor(((double)H-1.0)*m1+m1/2.0);
columnCent[H] = floor(((double)H-1.0)*m2+m2/2.0);
colorOfCent[H] = (double)(image[rowCent[H]][columnCent[H]]);
}
do
{
if(p>1)
{
colorOfCent = averageCol;
rowCent = averageRowDist;
columnCent = averageColDist;
}
/* compare pixels by color and distance to determine what is cluster center for
it */
for(I=0;I<NBL;I++)
{
for(J=0;J<NBC;J++)
{
currentRow = I;
currentColumn = J;
/* compare with cluster centers */
for(K=0;K<numClustCent;K++)
{
/* compare with cluster centers for color */
clustCent = colorOfCent[K];
whichColor = abs((int)image[I][J]-clustCent);
colCent[K] = whichColor;
/* see if color centers are within treshold range */
if (whichColor>=30)
{whichColCent[K]=0;}
else {whichColCent[K]=1;}
/* list best color center */
if(K==1)
{colCentOrder=K;}
else if(colCent[K]<=colCent[colCentOrder])
{colCentOrder=K;}
}
colCentOrder=colCentOrder;
whichDistCent = sqrt(pow((double)NBL,2.0)+pow((double)NBC,2.0))+1.0;
/* compare with cluster center for distance */
for(M=0;M<numClustCent;M++)
{
/* check to see if something is within color threshold */
/* if not, then choose the closest color as cluster center */
for(k=0;k<numClustCent;k++)
{
if(whichColCent[k]!=0)
{N=1;}
else {N=0;}
}
if(N==1 || whichColCent[M]==1)
{
rowDist = abs(I-rowCent[M]);
columnDist = abs(J-columnCent[M]);
totalDist = sqrt(pow((double)rowDist,2.0)+pow((double)columnDist,2.0));
if(totalDist<=whichDistCent)
{
whichDistCent = totalDist;
whichCent[I][J] = M;
rowDistance[I][J] = rowDist;
columnDistance[I][J] = columnDist;
}
}
}
}
}
whichCent = whichCent;
/* replace cluster centers with the mean of the elements in their cluster */
/* initialization of data */
sumClustCol = (double*)calloc(numClustCent, sizeof(double));
sumRowDistance = (unsigned int*)calloc(numClustCent, sizeof(int));
sumColDistance = (unsigned int*)calloc(numClustCent, sizeof(int));
pixelsInClust = (unsigned int*)calloc(numClustCent, sizeof(int));
for(i=0;i<numClustCent;i++)
{sumClustCol[i]=0;}
for(i=0;i<numClustCent;i++)
{sumRowDistance[i]=0;}
for(i=0;i<numClustCent;i++)
{sumColDistance[i]=0;}
for(i=0;i<numClustCent;i++)
{pixelsInClust[i]=0;}
for(O=0;O<NBL;O++)
{ for(P=0;P<NBC;P++)
{ A = whichCent[O][P];
pixelsInClust[A] = pixelsInClust[A]+1;
sumClustCol[A] = sumClustCol[A]+(double)image[O][P];
sumRowDistance[A] = sumRowDistance[A]+rowDistance[O][P];
sumColDistance[A] = sumColDistance[A]+columnDistance[O][P];
}
}
for(i=0;i<numClustCent;i++)
{averageRowDist[i]=0;}
for(i=0;i<numClustCent;i++)
{averageColDist[i]=0;}
for(i=0;i<numClustCent;i++)
{averageCol[i]=0;}
for(Q=0;Q<numClustCent;Q++)
{ averageCol[Q] = (unsigned int)ceil(sumClustCol[Q]/(double)pixelsInClust[Q]);
averageColDist[Q] = (unsigned int)ceil(sumRowDistance[Q]/(double)pixelsInClust[Q]);
averageRowDist[Q] = (unsigned int)ceil(sumColDistance[Q]/(double)pixelsInClust[Q]);
}
p=p+1;
}while(rowCent!=averageRowDist && columnCent!=averageColDist &&
colorOfCent!=averageCol);
/* set all pixels that belong to a cluster to different colors */
for(R=0;R<NBL;R++)
{ for(S=0;S<NBL;S++)
{ centerBelong = whichCent[R][S];
newImage[R][S] = colorOfCent[centerBelong]*40;
}
}
/* output file generated */
ouput = fopen("sortie_kmean","wb");
if(ouput == NULL)
{ fatal("ouput file error");}
else {printf("fichier de sortie cree avec succes.");}
for(Z=0;Z<NBL;Z++)
{ for(X=0;X<NBC;X++)
{ fwrite(&newImage[Z][X],1,1,ouput);}
}
fclose(ouput);
}