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image_pthreads.c
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172 lines (150 loc) · 6.69 KB
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#include <stdio.h>
#include <stdint.h>
#include <time.h>
#include <string.h>
#include <pthread.h>
#include <stdlib.h>
#include "image.h"
#define STB_IMAGE_IMPLEMENTATION
#include "stb_image.h"
#define STB_IMAGE_WRITE_IMPLEMENTATION
#include "stb_image_write.h"
#define NUM_THREADS 4
//An array of kernel matrices to be used for image convolution.
//The indexes of these match the enumeration from the header file. ie. algorithms[BLUR] returns the kernel corresponding to a box blur.
Matrix algorithms[]={
{{0,-1,0},{-1,4,-1},{0,-1,0}},
{{0,-1,0},{-1,5,-1},{0,-1,0}},
{{1/9.0,1/9.0,1/9.0},{1/9.0,1/9.0,1/9.0},{1/9.0,1/9.0,1/9.0}},
{{1.0/16,1.0/8,1.0/16},{1.0/8,1.0/4,1.0/8},{1.0/16,1.0/8,1.0/16}},
{{-2,-1,0},{-1,1,1},{0,1,2}},
{{0,0,0},{0,1,0},{0,0,0}}
};
// Structure to pass data to each thread
typedef struct {
Image* srcImage;
Image* destImage;
Matrix algorithm;
int start_row;
int end_row;
} ThreadData;
//getPixelValue - Computes the value of a specific pixel on a specific channel using the selected convolution kernel
//Parameters: srcImage: An Image struct populated with the image being convoluted
// x: The x coordinate of the pixel
// y: The y coordinate of the pixel
// bit: The color channel being manipulated
// algorithm: The 3x3 kernel matrix to use for the convolution
//Returns: The new value for this x,y pixel and bit channel
uint8_t getPixelValue(Image* srcImage,int x,int y,int bit,Matrix algorithm){
int px,mx,py,my,i,span;
span=srcImage->width*srcImage->bpp;
// for the edge pixels, just reuse the edge pixel
px=x+1; py=y+1; mx=x-1; my=y-1;
if (mx<0) mx=0;
if (my<0) my=0;
if (px>=srcImage->width) px=srcImage->width-1;
if (py>=srcImage->height) py=srcImage->height-1;
uint8_t result=
algorithm[0][0]*srcImage->data[Index(mx,my,srcImage->width,bit,srcImage->bpp)]+
algorithm[0][1]*srcImage->data[Index(x,my,srcImage->width,bit,srcImage->bpp)]+
algorithm[0][2]*srcImage->data[Index(px,my,srcImage->width,bit,srcImage->bpp)]+
algorithm[1][0]*srcImage->data[Index(mx,y,srcImage->width,bit,srcImage->bpp)]+
algorithm[1][1]*srcImage->data[Index(x,y,srcImage->width,bit,srcImage->bpp)]+
algorithm[1][2]*srcImage->data[Index(px,y,srcImage->width,bit,srcImage->bpp)]+
algorithm[2][0]*srcImage->data[Index(mx,py,srcImage->width,bit,srcImage->bpp)]+
algorithm[2][1]*srcImage->data[Index(x,py,srcImage->width,bit,srcImage->bpp)]+
algorithm[2][2]*srcImage->data[Index(px,py,srcImage->width,bit,srcImage->bpp)];
return result;
}
// Thread function: processes a range of rows
void* convolute_thread(void* arg){
ThreadData* data = (ThreadData*)arg;
int row, pix, bit;
// Process assigned rows
for (row = data->start_row; row < data->end_row; row++){
for (pix = 0; pix < data->srcImage->width; pix++){
for (bit = 0; bit < data->srcImage->bpp; bit++){
data->destImage->data[Index(pix,row,data->srcImage->width,bit,data->srcImage->bpp)] =
getPixelValue(data->srcImage, pix, row, bit, data->algorithm);
}
}
}
return NULL;
}
//convolute: Applies a kernel matrix to an image using pthreads
//Parameters: srcImage: The image being convoluted
// destImage: A pointer to a pre-allocated structure to receive the convoluted image
// algorithm: The kernel matrix to use for the convolution
//Returns: Nothing
void convolute(Image* srcImage, Image* destImage, Matrix algorithm){
pthread_t threads[NUM_THREADS];
ThreadData thread_data[NUM_THREADS];
int rows_per_thread = srcImage->height / NUM_THREADS;
int i;
// Create threads
for (i = 0; i < NUM_THREADS; i++){
thread_data[i].srcImage = srcImage;
thread_data[i].destImage = destImage;
memcpy(thread_data[i].algorithm, algorithm, sizeof(Matrix));
thread_data[i].start_row = i * rows_per_thread;
// Last thread handles any remaining rows
if (i == NUM_THREADS - 1){
thread_data[i].end_row = srcImage->height;
} else {
thread_data[i].end_row = (i + 1) * rows_per_thread;
}
pthread_create(&threads[i], NULL, convolute_thread, &thread_data[i]);
}
// Wait for all threads to complete
for (i = 0; i < NUM_THREADS; i++){
pthread_join(threads[i], NULL);
}
}
//Usage: Prints usage information for the program
//Returns: -1
int Usage(){
printf("Usage: image <filename> <type>\n\twhere type is one of (edge,sharpen,blur,gauss,emboss,identity)\n");
return -1;
}
//GetKernelType: Converts the string name of a convolution into a value from the KernelTypes enumeration
//Parameters: type: A string representation of the type
//Returns: an appropriate entry from the KernelTypes enumeration, defaults to IDENTITY
enum KernelTypes GetKernelType(char* type){
if (!strcmp(type,"edge")) return EDGE;
else if (!strcmp(type,"sharpen")) return SHARPEN;
else if (!strcmp(type,"blur")) return BLUR;
else if (!strcmp(type,"gauss")) return GAUSE_BLUR;
else if (!strcmp(type,"emboss")) return EMBOSS;
else return IDENTITY;
}
//main:
//argv is expected to take 2 arguments. First is the source file name (can be jpg, png, bmp, tga). Second is the lower case name of the algorithm.
int main(int argc,char** argv){
long t1,t2;
t1=time(NULL);
stbi_set_flip_vertically_on_load(0);
if (argc!=3) return Usage();
char* fileName=argv[1];
if (!strcmp(argv[1],"pic4.jpg")&&!strcmp(argv[2],"gauss")){
printf("You have applied a gaussian filter to Gauss which has caused a tear in the time-space continuum.\n");
}
enum KernelTypes type=GetKernelType(argv[2]);
Image srcImage,destImage;
srcImage.data=stbi_load(fileName,&srcImage.width,&srcImage.height,&srcImage.bpp,0);
if (!srcImage.data){
printf("Error loading file %s.\n",fileName);
return -1;
}
destImage.bpp=srcImage.bpp;
destImage.height=srcImage.height;
destImage.width=srcImage.width;
destImage.data=malloc(sizeof(uint8_t)*destImage.width*destImage.bpp*destImage.height);
printf("Using %d threads (pthreads version)\n", NUM_THREADS);
convolute(&srcImage,&destImage,algorithms[type]);
stbi_write_png("output.png",destImage.width,destImage.height,destImage.bpp,destImage.data,destImage.bpp*destImage.width);
stbi_image_free(srcImage.data);
free(destImage.data);
t2=time(NULL);
printf("Took %ld seconds\n",t2-t1);
return 0;
}