image.c

#include <stdio.h>
#include <stdint.h>
#include <time.h>
#include <string.h>
#include <pthread.h>
#include "pthread.h"

#define STB_IMAGE_IMPLEMENTATION
#include "stb_image.h"

#define STB_IMAGE_WRITE_IMPLEMENTATION
#include "stb_image_write.h"


#define NUM_THREADS 64

//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}}
};

// This is the lock that is used for modifying the image's data
pthread_mutex_t image_lock;

// The original image that will be modified
Image srcImage;

// The image that is going to be written
Image destImage;

// The algorithm that will be used for image modification
Matrix algorithm;



//getPixelValue - Computes the value of a specific pixel on a specific channel using the selected convolution kernel
//Paramters: 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){
    int px,mx,py,my,i,span;
    // for the edge pixes, 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;
}


//convolute:  Applies a kernel matrix to an image
//Parameters: srcImage: The image being convoluted
//            destImage: A pointer to a  pre-allocated (including space for the pixel array) structure to receive the convoluted image. It should be the same size as srcImage
//            algorithm: The kernel matrix to use for the convolution
//Returns: Nothing
void *convolute(void *rank){
    int row; 
    int end_row; 
    int pix; 
    int bit; 
    int span;
    int ind;
    uint8_t pvalue;
    long my_rank = (long) rank;

    int inc = srcImage.height / NUM_THREADS;
    row = my_rank * inc;
    end_row = row + inc - 1;

    for (; row <= end_row; row++){
        for (pix=0;pix<srcImage.width;pix++){
            for (bit=0;bit<srcImage.bpp;bit++){
                ind = Index(pix,row,srcImage.width,bit,srcImage.bpp);
                pvalue = getPixelValue(&srcImage,pix,row,bit);
                destImage.data[ind] = pvalue;
            }
        }
    }
    
    return 0;
}

/*
    Function: threadedConvolute that creates threads to apply a kernel matrix to an image in parallel
    Parameters: srcImage: The image being convoluted
                destImage: A pointer to a pre-allocated (including space for the pixel array) structure to receive the convoluted image. It should be the same size as srcImage
                algorithm: The kernel matrix to use for the convolution
                numThreads: The number of threads to spawn for the work
*/
void threadedConvolute() {
    int row, pix, bit, span;
    long i;
    uint8_t pvalue;
    pthread_t threads[NUM_THREADS];
    pthread_mutex_init(&image_lock, NULL);

    for (i = 0; i < NUM_THREADS; i++) {
        //create the new thread 
        //thread id, attributes for the thread, pointer to convolute function to be executed, pointer to a void value that can be used to pass arguments to the function being executed
        pthread_create(&threads[i], NULL, &convolute, (void *)i);
    }

    for (i = 0; i < NUM_THREADS; i++) {
        //waits for the threads created above to finish executing before continuing
        pthread_join(threads[i], NULL);
    }
    //destroy the mutex object &image_lock
    pthread_mutex_destroy(&image_lock);
}

//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, which does nothing but copy the image.
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 continum.\n");
    }
    enum KernelTypes type=GetKernelType(argv[2]);

    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);
    memcpy(algorithm, algorithms[type], sizeof(Matrix));
    threadedConvolute();
    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;
}