generated from freudenreichan/info2Praktikum-NeuronalesNetz
Compare commits
31
Commits
| Author | SHA1 | Date | |
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fb8672e5a1 |
+112
-33
@@ -6,48 +6,127 @@
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|||||||
#define BUFFER_SIZE 100
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#define BUFFER_SIZE 100
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#define FILE_HEADER_STRING "__info2_image_file_format__"
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#define FILE_HEADER_STRING "__info2_image_file_format__"
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// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
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int checkString (FILE *file){ //Checks if String at the start of File equals expected Format (0 for wrong 1 for right)
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void setParameters(const char buffer[], unsigned int* imageCount, int* width, int* height);
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if (file == NULL){ //returns 0 for empty file
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void allocateMemory(GrayScaleImageSeries *s, const int imageCount, const int width, const int height);
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return 0;
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// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
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}
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char expectedString[] = FILE_HEADER_STRING;
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char actualString[BUFFER_SIZE];
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rewind(file);
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size_t bytesRead = fread(actualString, 1,27 , file); //Stores Bytes of start of File to actualString
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if (bytesRead != 27){
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return 0;
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} //Returns 0 if File is to short
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actualString[27] = '\0';
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if (strcmp(actualString, expectedString) != 0){
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return 0;
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}
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else{
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return 1;
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}
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}
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static void setParameters(FILE* file, unsigned int* imageCount, unsigned int* width, unsigned int* height);
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static int allocateMemory(GrayScaleImageSeries *series, const int imageCount, const int width, const int height);
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GrayScaleImageSeries *readImages(const char *path)
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GrayScaleImageSeries *readImages(const char *path)
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{
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{
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GrayScaleImageSeries *series = NULL;
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FILE* file = fopen(path, "rb");
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if(!(checkString(file))){
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fclose(file);
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return NULL;
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}
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// hier Niko Stuff
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unsigned int width, height; //uninitialised Variables, will be set by setparamters
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// create char array buffer with bytes containing initialization information
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// TODO some kind of logic to get correct address in binary file
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char initBuffer[3];
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/*
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int readBytes = fread(initBuffer, 1, 3, //file);
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*/
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unsigned int* imageCount = &(series->count); // sets a pointer for int variable count in struct
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setParameters(initBuffer, imageCount, series->images->width, series->images->height);
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allocateMemory(*imageCount, series->images->width, series->images->height);
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GrayScaleImageSeries *series = malloc(sizeof(GrayScaleImageSeries)); //Reserving memory for series
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setParameters(file, &(series->count), &width, &height); //setting parameters taken from image file
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if(!allocateMemory(series, series->count, width, height)){
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clearSeries(series); //If Memory couldnt be correctly allocated a clearing is necessary
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fclose(file);
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return NULL;
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}
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//Getting image data
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for(unsigned int i = 0; i < series->count ; i++){ //Iterating for every image
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for(unsigned int j = 0; j < width * height; j++){ //Iterating for every pixel
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fread(&(series->images[i].buffer[j]), sizeof(GrayScalePixelType), 1, file);
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}
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fread(&(series->labels[i]), sizeof(unsigned char), 1, file); // TODO Added writing in labels array
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}
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fclose(file);
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return series;
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return series;
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}
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}
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void setParameters(const char buffer[], unsigned int* imageCount, int* width, int* height) { // sets the parameters
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*imageCount = (int) buffer[0];
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*width = (int) buffer[1];
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*height = (int) buffer[2];
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}
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void allocateMemory(GrayScaleImageSeries s, const int imageCount, const int width, const int height) {
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for (int i = 0; i < imageCount; i++) {
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s->images[i].buffer = (unsigned char *) malloc(width * height * sizeof(unsigned char)); // allocates memory for every image in the series
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}
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}
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// TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt
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void clearSeries(GrayScaleImageSeries *series)
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void clearSeries(GrayScaleImageSeries *series)
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{
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{
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for(size_t i = GrayScaleImageSeries.count - 1; i >= 0; i--)
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if (!series)
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return;
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//Freeing Pixelbuffer for every image
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for(unsigned int i = 0; i < series->count; i++)
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{
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{
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free(GrayScaleImageSeries.images+GrayScaleImageSeries.count*sizeof(GrayScaleImage)*i);
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free(series->images[i].buffer);
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free(GrayScaleImageSeries.labels+GrayScaleImageSeries.count*sizeof(unsigned char)*i);
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}
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}
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GrayScaleImageSeries.images = NULL;
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free(series->images); //Freeing Images array
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GrayScaleImageSeries.labels = NULL;
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free(series->labels); //Freeing Labels
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free(series); //Freeing Main Structure
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}
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static void setParameters(FILE* file, unsigned int* imageCount, unsigned int* width, unsigned int* height) { // sets the parameters
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unsigned short buffer[3];
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fseek(file, 27, SEEK_SET);
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if(fread(buffer, sizeof(unsigned short), 3, file) != 3){ // TODO changed some stuff here, used UNSIGNED SHORT instead of UNSIGNED CHAR!!
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*imageCount = 0;
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*width = 0;
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*height = 0;
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return;
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} //Stops if file is too short and clean up
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*imageCount = (unsigned int) buffer[0];
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*width = (unsigned int) buffer[1];
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*height = (unsigned int) buffer[2];
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}
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static int allocateMemory(GrayScaleImageSeries *series, const int imageCount, const int width, const int height) {
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series->count = imageCount; //counts number of images in series
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series->images = malloc (sizeof(GrayScaleImage) * imageCount); //Reserving Memory for Images Array
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if (series->images == NULL)
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return 0;
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series->labels = malloc (series->count * sizeof(unsigned char)); //One Label for every Image
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if (series->labels == NULL){
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return 0;}
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for (int i = 0; i < imageCount; i++) { //Reserving Memory for every Images Pixelbuffer and setting width and height
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series->images[i].width = width;
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series->images[i].height = height;
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series->images[i].buffer = malloc(width * height * sizeof(unsigned char)); // allocates memory for every image in the series
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if (series->images[i].buffer == NULL){
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for (int j = 0; j < i; j++){
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free(series->images[j].buffer);
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}
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free(series->images);
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free(series->labels);
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return 0;
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}
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}
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return 1;
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}
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}
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@@ -39,12 +39,16 @@ static void prepareImageFile(const char *path, unsigned short int width, unsigne
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void test_readImagesReturnsCorrectNumberOfImages(void)
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void test_readImagesReturnsCorrectNumberOfImages(void)
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{
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{
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GrayScaleImageSeries *series = NULL;
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GrayScaleImageSeries *series = NULL;
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const unsigned short expectedNumberOfImages = 2;
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const unsigned short expectedNumberOfImages = 2;
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const char *path = "testFile.info2";
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const char *path = "testFile.info2";
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prepareImageFile(path, 8, 8, expectedNumberOfImages, 1);
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prepareImageFile(path, 8, 8, expectedNumberOfImages, 1);
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series = readImages(path);
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series = readImages(path);
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TEST_ASSERT_NOT_NULL(series);
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TEST_ASSERT_NOT_NULL(series);
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TEST_ASSERT_EQUAL_UINT16(expectedNumberOfImages, series->count);
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TEST_ASSERT_EQUAL_UINT16(expectedNumberOfImages, series->count);
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clearSeries(series);
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clearSeries(series);
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remove(path);
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remove(path);
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}
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}
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@@ -5,26 +5,29 @@
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// TODO Matrix-Funktionen implementieren
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// TODO Matrix-Funktionen implementieren
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typedef struct Matrix {
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unsigned int rows;
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|
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unsigned int cols;
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MatrixType* buffer;
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} Matrix;
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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{
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{
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Matrix newMatrix;
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Matrix newMatrix;
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if (rows == 0 || cols == 0) {
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newMatrix.rows = 0;
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newMatrix.cols = 0;
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newMatrix.buffer = NULL;
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return newMatrix;
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}
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newMatrix.rows = rows;
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newMatrix.rows = rows;
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newMatrix.cols = cols;
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newMatrix.cols = cols;
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newMatrix.buffer = calloc(rows*cols, sizeof(MatrixType));
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newMatrix.buffer = calloc(rows*cols, sizeof(MatrixType));
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return newMatrix;
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return newMatrix;
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}
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}
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void clearMatrix(Matrix *matrix)
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void clearMatrix(Matrix *matrix)
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{
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{
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free(matrix.buffer);
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free(matrix->buffer);
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matrix.buffer = NULL;
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matrix->buffer = NULL;
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matrix->rows = 0;
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matrix->cols = 0;
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}
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}
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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@@ -52,15 +55,10 @@ MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int co
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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Matrix add(const Matrix matrix1, const Matrix matrix2)
|
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{
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{
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Matrix MatrixErgebnis = createMatrix(matrix1.rows, matrix1.cols); //Creating Result Matrix
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|
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if(matrix1.cols != matrix2.cols || matrix1.rows != matrix2.rows){
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printf("Matrix dimensions do not match\n"); //Error Message if dimensions of Input Matrixes are not identical
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clearMatrix(MatrixErgebnis);
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MatrixErgebnis = NULL;
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|
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return MatrixErgebnis;
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|
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}
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else{
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|
||||||
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|
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//If rows and cols of both Matrixes are the same the normal addition starts
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if (matrix1.rows == matrix2.rows && matrix1.cols == matrix2.cols){
|
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Matrix MatrixErgebnis = createMatrix(matrix1.rows, matrix1.cols);
|
||||||
for (unsigned int i = 0; i < matrix1.rows; i++){
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for (unsigned int i = 0; i < matrix1.rows; i++){
|
||||||
for (unsigned int j = 0; j < matrix1.cols; j++){
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for (unsigned int j = 0; j < matrix1.cols; j++){
|
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//Adding Matrix Elements of same row and col index together and store in new Matrix
|
//Adding Matrix Elements of same row and col index together and store in new Matrix
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@@ -68,20 +66,59 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
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|
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}
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}
|
||||||
}
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}
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return MatrixErgebnis;
|
||||||
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}
|
||||||
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|
||||||
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//if matrix1 is a Vektor it adds elements to first col of matrix2
|
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else if (matrix1.cols == 1 && matrix1.rows == matrix2.rows){
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Matrix MatrixErgebnis = createMatrix(matrix2.rows, matrix2.cols);
|
||||||
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for (unsigned int i = 0; i < matrix2.rows; i++) {
|
||||||
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for (unsigned int j = 0; j < matrix2.cols; j++) {
|
||||||
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//Copy Matrix2 to ErgebnisMatrix
|
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MatrixErgebnis.buffer[i * matrix2.cols + j] = getMatrixAt(matrix2, i, j);
|
||||||
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//Adding Elements of first col of Matrix 1 (Vector) to all Elements of MatrixErgebnis
|
||||||
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MatrixErgebnis.buffer[i * matrix2.cols + j] += matrix1.buffer[i];
|
||||||
|
}
|
||||||
}
|
}
|
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return MatrixErgebnis;
|
return MatrixErgebnis;
|
||||||
}
|
}
|
||||||
|
//if matrix2 is a Vektor it adds elements to first col of matrix1
|
||||||
|
else if (matrix2.cols == 1 && matrix1.rows == matrix2.rows){
|
||||||
|
Matrix MatrixErgebnis = createMatrix(matrix1.rows, matrix1.cols);
|
||||||
|
for (unsigned int i = 0; i < matrix1.rows; i++) {
|
||||||
|
for (unsigned int j = 0; j < matrix1.cols; j++) {
|
||||||
|
//Copy Matrix1 to ErgebnisMatrix
|
||||||
|
MatrixErgebnis.buffer[i * matrix1.cols + j] = getMatrixAt(matrix1, i, j);
|
||||||
|
//Adding Elements of first col of Matrix 2 (Vector) to first col of MatrixErgebnis
|
||||||
|
MatrixErgebnis.buffer[i * matrix1.cols + j] += matrix2.buffer[i];
|
||||||
|
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return MatrixErgebnis;
|
||||||
|
}
|
||||||
|
else{
|
||||||
|
printf("Matrix dimensions do not match\n"); //Error Message if dimensions of Input Matrixes are not identical
|
||||||
|
Matrix MatrixErgebnis = createMatrix(0, 0);
|
||||||
|
clearMatrix(&MatrixErgebnis);
|
||||||
|
return MatrixErgebnis;
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
Matrix multiply(const Matrix matrix1, const Matrix matrix2)
|
Matrix multiply(const Matrix matrix1, const Matrix matrix2)
|
||||||
{
|
{
|
||||||
|
|
||||||
Matrix result;
|
Matrix result;
|
||||||
|
result.rows = 0;
|
||||||
|
result.cols = 0;
|
||||||
|
result.buffer = NULL;
|
||||||
|
|
||||||
|
if (matrix1.cols != matrix2.rows) {
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
result.rows = matrix1.rows;
|
result.rows = matrix1.rows;
|
||||||
result.cols = matrix2.cols;
|
result.cols = matrix2.cols;
|
||||||
|
|
||||||
if (matrix1.rows == matrix2.cols) {
|
|
||||||
|
|
||||||
result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
|
result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
|
||||||
|
|
||||||
for(int i = 0; i < result.rows; i++) {
|
for(int i = 0; i < result.rows; i++) {
|
||||||
@@ -90,11 +127,8 @@ Matrix multiply(const Matrix matrix1, const Matrix matrix2)
|
|||||||
for(int k = 0; k < matrix1.cols; k++) {
|
for(int k = 0; k < matrix1.cols; k++) {
|
||||||
value += matrix1.buffer[i * matrix1.cols + k] * matrix2.buffer[k * matrix2.cols + j];
|
value += matrix1.buffer[i * matrix1.cols + k] * matrix2.buffer[k * matrix2.cols + j];
|
||||||
}
|
}
|
||||||
result.buffer[i * matrix1.cols + j] = value;
|
result.buffer[i * result.cols + j] = value;
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
return result;
|
return result;
|
||||||
}
|
}
|
||||||
printf("Die angegebenen Matrizen haben keine passenden Dimensionen für die Multiplikation");
|
|
||||||
return result;
|
|
||||||
}
|
|
||||||
@@ -7,7 +7,11 @@ typedef float MatrixType;
|
|||||||
|
|
||||||
// TODO Matrixtyp definieren
|
// TODO Matrixtyp definieren
|
||||||
|
|
||||||
typedef struct Matrix Matrix;
|
typedef struct Matrix{
|
||||||
|
unsigned int rows;
|
||||||
|
unsigned int cols;
|
||||||
|
MatrixType* buffer;
|
||||||
|
}Matrix;
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|||||||
+1
-2
@@ -155,7 +155,6 @@ NeuralNetwork loadModel(const char *path)
|
|||||||
|
|
||||||
model.layers[model.numberOfLayers] = layer;
|
model.layers[model.numberOfLayers] = layer;
|
||||||
model.numberOfLayers++;
|
model.numberOfLayers++;
|
||||||
|
|
||||||
inputDimension = outputDimension;
|
inputDimension = outputDimension;
|
||||||
outputDimension = readDimension(file);
|
outputDimension = readDimension(file);
|
||||||
}
|
}
|
||||||
@@ -170,7 +169,7 @@ NeuralNetwork loadModel(const char *path)
|
|||||||
|
|
||||||
static Matrix imageBatchToMatrixOfImageVectors(const GrayScaleImage images[], unsigned int count)
|
static Matrix imageBatchToMatrixOfImageVectors(const GrayScaleImage images[], unsigned int count)
|
||||||
{
|
{
|
||||||
Matrix matrix = {NULL, 0, 0};
|
Matrix matrix = {0, 0, NULL}; // TODO changed this line to fit our functionality
|
||||||
|
|
||||||
if(count > 0 && images != NULL)
|
if(count > 0 && images != NULL)
|
||||||
{
|
{
|
||||||
|
|||||||
@@ -9,6 +9,29 @@
|
|||||||
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
|
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
|
||||||
{
|
{
|
||||||
// TODO
|
// TODO
|
||||||
|
FILE* file = fopen(path, "wb");
|
||||||
|
if(file == NULL) {
|
||||||
|
printf("Failed to open file");
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
printf("\nLayers in pNNF: %d\n", nn.numberOfLayers);
|
||||||
|
const char* header = "__info2_neural_network_file_format__";
|
||||||
|
fwrite(header, sizeof(const char), strlen(header), file);
|
||||||
|
|
||||||
|
for (int i = 0; i < nn.numberOfLayers; i++) {
|
||||||
|
|
||||||
|
fwrite(&(nn.layers[i].weights.cols), sizeof(unsigned int), 1, file);
|
||||||
|
fwrite(&(nn.layers[i].weights.rows), sizeof(unsigned int), 1, file);
|
||||||
|
}
|
||||||
|
|
||||||
|
for(int i = 0; i < nn.numberOfLayers; i++) {
|
||||||
|
//write everything to do with weights
|
||||||
|
fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), nn.layers[i].weights.rows * nn.layers[i].weights.cols, file);
|
||||||
|
|
||||||
|
//write everything to do with biases
|
||||||
|
fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType), nn.layers[i].biases.rows * nn.layers[i].biases.cols, file);
|
||||||
|
}
|
||||||
|
fclose(file);
|
||||||
}
|
}
|
||||||
|
|
||||||
void test_loadModelReturnsCorrectNumberOfLayers(void)
|
void test_loadModelReturnsCorrectNumberOfLayers(void)
|
||||||
@@ -25,6 +48,7 @@ void test_loadModelReturnsCorrectNumberOfLayers(void)
|
|||||||
Layer layers[] = {{.weights=weights1, .biases=biases1}, {.weights=weights2, .biases=biases2}};
|
Layer layers[] = {{.weights=weights1, .biases=biases1}, {.weights=weights2, .biases=biases2}};
|
||||||
|
|
||||||
NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=2};
|
NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=2};
|
||||||
|
printf("\nexpectedNetLayers: %d", expectedNet.numberOfLayers);
|
||||||
NeuralNetwork netUnderTest;
|
NeuralNetwork netUnderTest;
|
||||||
|
|
||||||
prepareNeuralNetworkFile(path, expectedNet);
|
prepareNeuralNetworkFile(path, expectedNet);
|
||||||
|
|||||||
Reference in New Issue
Block a user