generated from freudenreichan/info2Praktikum-NeuronalesNetz
Compare commits
9
Commits
| Author | SHA1 | Date | |
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2b388ab748 | ||
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e0ded7b738 | ||
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880514b55f | ||
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419296af9e | ||
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4d1908ed27 | ||
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ce371e4228 | ||
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98aa5f354a | ||
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5ce0982e17 | ||
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cfac9ae60e |
+133
-2
@@ -6,17 +6,148 @@
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#define BUFFER_SIZE 100
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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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/// @brief Reads a value in little-endian format from file
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/// @param openedFile stream FILE, from which to read
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/// @param bytes how many bytes to read
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static unsigned int readLittleEndian(FILE* openedFile, int bytes) {
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unsigned int value = 0;
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if (openedFile == NULL) return 0;
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for (int i = 0; i < bytes; i++) {
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int tmp = fgetc(openedFile);
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if (tmp == EOF) return 0;
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value |= ((unsigned int)tmp) << (i * 8);
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}
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return value;
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}
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// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
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GrayScaleImageSeries *readImages(const char *path)
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{
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GrayScaleImageSeries *series = NULL;
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FILE* openFile = fopen(path, "rb");
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// file Could not be opened/does not exist
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if (openFile == NULL) {
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return NULL;
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}
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char actualFileTag[strlen(FILE_HEADER_STRING) + 1];
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size_t tagLength = strlen(FILE_HEADER_STRING);
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if (fread(actualFileTag, 1, tagLength, openFile) != tagLength) {
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fclose(openFile);
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return NULL;
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}
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actualFileTag[tagLength] = '\0';
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// checks if the files are equal
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if (strcmp(actualFileTag, FILE_HEADER_STRING) != 0) {
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fclose(openFile);
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return NULL;
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}
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unsigned int numberOfImages = readLittleEndian(openFile, 2);
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// no Images in series -> No image-series
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if (numberOfImages == 0) {
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fclose(openFile);
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return NULL;
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}
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unsigned int width = readLittleEndian(openFile, 2);
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unsigned int height = readLittleEndian(openFile, 2);
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// no height/width --> impossible file
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if(height == 0 || width == 0) {
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fclose(openFile);
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return NULL;
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}
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//all the starting parameters are set --> the images can be read and stored
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GrayScaleImageSeries* series = malloc(sizeof(GrayScaleImageSeries));
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if (series == NULL) {
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fclose(openFile);
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return NULL;
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}
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GrayScaleImage* images = malloc(numberOfImages * sizeof(GrayScaleImage));
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unsigned char* labels = malloc(numberOfImages * sizeof(unsigned char));
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if (images == NULL || labels == NULL) {
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free(images);
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free(labels);
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free(series);
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fclose(openFile);
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return NULL;
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}
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series->count = 0;
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series->images = images;
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series->labels = labels;
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for (unsigned int i = 0; i < numberOfImages; i++) {
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// allocating the actual matrix image for each image
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images[i].buffer = malloc(width * height);
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if (images[i].buffer == NULL) {
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for (unsigned int k = 0; k < i; k++) {
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free(images[k].buffer);
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}
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free(images);
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free(labels);
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free(series);
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fclose(openFile);
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return NULL;
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}
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images[i].height = height;
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images[i].width = width;
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if (fread(images[i].buffer, 1, width * height, openFile) != width * height) {
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for (unsigned int k = 0; k <= i; k++) {
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free(images[k].buffer);
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}
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free(images);
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free(labels);
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free(series);
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fclose(openFile);
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return NULL;
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}
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//rest of the values that only affect the image itself
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int label = fgetc(openFile);
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if (label == EOF) {
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for (unsigned int k = 0; k <= i; k++) {
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free(images[k].buffer);
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}
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free(images);
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free(labels);
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free(series);
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fclose(openFile);
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return NULL;
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}
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series->labels[i] = (unsigned char)label;
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series->count++;
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}
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fclose(openFile);
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return series;
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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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{
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if (series == NULL) return;
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for (int i = 0; i < series->count; i++) {
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free(series->images[i].buffer);
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}
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free(series->images);
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free(series->labels);
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free(series);
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}
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@@ -0,0 +1,115 @@
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include "imageInput.h"
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#define BUFFER_SIZE 100
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#define FILE_HEADER_STRING "__info2_image_file_format__"
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/// @brief Gets the next char value from specified and opened file
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/// @param openedFile stream FILE, from which to read
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/// @param iterations how many chars are being taken from (1 char equals 2 Hexdecimals equals 8bit)
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static int getCharValueFromFile(FILE* openedFile, int iterations) {
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int addToFile = 0;
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if (openedFile == NULL) return 0;
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for (int i = 0; i < iterations; i++) {
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int tmp = fgetc(openedFile);
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//If the File ends, the method returns a '0'
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if (openedFile == EOF) return addToFile;
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addToFile += tmp;
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}
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return addToFile;
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}
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// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
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GrayScaleImageSeries *readImages(const char *path)
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{
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GrayScaleImageSeries *series = NULL;
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FILE* openFile;
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openFile = fopen(path, "rb");
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// file Could not be opened/does not exist
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if (openFile != NULL) {
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char* actualFileTag = malloc(strlen(FILE_HEADER_STRING) * sizeof(char));
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int numberOfImages = 0;
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int width = 0;
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int height = 0;
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for (int i = 0; i < strlen(FILE_HEADER_STRING); i++) {
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actualFileTag += fgetc(openFile);
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}
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// checks if the files are equal: strcmp should return '0' --> convert it to '1' for 'true'
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int fileTagEqual = !strcmp(actualFileTag, FILE_HEADER_STRING);
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//we only need the fileTag to verify its an image for our series.
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free(actualFileTag);
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actualFileTag = NULL;
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if (fileTagEqual) {
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numberOfImages = getCharValueFromFile(openFile, 2);
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// no Images in series -> No image-series
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if (numberOfImages == 0) {
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fclose(openFile);
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return series;
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}
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width = getCharValueFromFile(openFile, 2);
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height = getCharValueFromFile(openFile, 2);
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// no height/width --> impossible file
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if(height == 0 || width == 0) {
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fclose(openFile);
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return series;
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}
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//all the starting parameters are set --> the images can be read and stored
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GrayScaleImage* images = malloc(numberOfImages * sizeof(GrayScaleImage));
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unsigned char* labels = malloc(numberOfImages * sizeof(unsigned char));
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series->count = 0;
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series->images = images;
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series->labels = labels;
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for (int i = 0; i < numberOfImages; i++) {
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for (int j = 0; j < width * height; j++) {
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// allocating the actual matrix image for image
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images[i].buffer = malloc(width * height);
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images[i].height = height;
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images[i].width = width;
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images[i].buffer[j] = fgetc(openFile);
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}
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//rest of the values that only affect the image itself
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series->labels[i] = fgetc(openFile);
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series->count++;
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}
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}
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}
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fclose(openFile);
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return series;
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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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{
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for (int i = 0; i < series->count; i++) {
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free(series->images[i].buffer);
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}
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free(series->images);
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series->images = NULL;
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free(series->labels);
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series->labels = NULL;
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}
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@@ -1,47 +1,10 @@
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#include <stdlib.h>
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#include <string.h>
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#include "matrix.h"
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#include <stdbool.h>
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// TODO Matrix-Funktionen implementieren
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/*
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Alte Funktion
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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{
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Matrix m;
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m.rows = rows;
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m.cols = cols;
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m.data = NULL;
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if(rows == 0 || cols == 0){
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m.rows = m.cols = 0;
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return m;
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}
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m.data = malloc(rows * sizeof *m.data);
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if(!m.data){
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m.rows = m.cols = 0;
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return m;
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}
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for(unsigned int i = 0; i < rows; i++){
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m.data[i] = malloc(cols * sizeof *m.data[i]);
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if(!m.data[i]){
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for(unsigned int j = 0; j < i; j++){
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free(m.data[j]);
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}
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free(m.data);
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m.data = NULL;
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m.rows = m.cols = 0;
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return m;
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}
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}
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return m;
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}
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*/
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Matrix createMatrix(size_t rows, size_t cols)
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{
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Matrix m;
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@@ -109,90 +72,54 @@ MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int co
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else return 0;
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}
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/*
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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{
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//check if the matrices are able to be added (same size)
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if (matrix1.cols == matrix2.cols && matrix1.rows == matrix2.rows){
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//size of the matrices should be the same, if the addition is supposed to happen
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// Matrix outputMatrix = createMatrix(matrix1.rows, matrix1.cols);
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Matrix outputMatrix = createMatrix(matrix1.rows, matrix1.cols);
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bool doBroadcast = false;
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Matrix larger, smaller;
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|
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if(matrix1.rows == matrix2.rows && matrix1.cols == matrix2.cols){
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larger = matrix1;
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smaller = matrix2;
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}
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else if (matrix1.rows == matrix2.rows && matrix2.cols == 1)
|
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{
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larger = matrix1;
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smaller = matrix2;
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doBroadcast = true;
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}
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else if (matrix1.rows == matrix2.rows && matrix1.cols == 1)
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{
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larger = matrix2;
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smaller = matrix1;
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doBroadcast = true;
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}
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else{
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Matrix m = {NULL, 0, 0};
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return m;
|
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}
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|
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Matrix outputMatrix = createMatrix(larger.rows, larger.cols);
|
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if(doBroadcast){
|
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for(int i = 0; i < outputMatrix.rows; i++){
|
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MatrixType broadcastValue = smaller.buffer[i];
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for(int j = 0; j < outputMatrix.cols; j++){
|
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outputMatrix.buffer[i * outputMatrix.cols + j] = larger.buffer[i * larger.cols + j] + broadcastValue;
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}
|
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}
|
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} else{
|
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for (int i = 0; i < matrix1.rows;i++) {
|
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for (int j = 0; j < matrix1.cols; j++) {
|
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// how this should work in normal Matrix version:
|
||||
// outputmatrix.buffer[i][j] = matrix1.buffer[i][j] + matrix2.buffer[i][j];
|
||||
outputMatrix.buffer[i + outputMatrix.rows* j] = matrix1.buffer[i + matrix1.rows* j] + matrix2.buffer[i + matrix2.rows * j];
|
||||
outputMatrix.buffer[i * outputMatrix.cols + j] = matrix1.buffer[i * matrix1.cols + j] + matrix2.buffer[i * matrix2.cols + j];
|
||||
}
|
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}
|
||||
return outputMatrix;
|
||||
} else {
|
||||
//the matrix could not be added, since the matrix sizes are not set correct.
|
||||
Matrix m;
|
||||
m.rows = 0;
|
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m.cols = 0;
|
||||
m.buffer = NULL;
|
||||
return m;
|
||||
}
|
||||
|
||||
}
|
||||
*/
|
||||
|
||||
Matrix add(const Matrix matrix1, const Matrix matrix2)
|
||||
{
|
||||
//check if the matrices are able to be added (same size)
|
||||
if (matrix1.cols != matrix2.cols && matrix1.rows != matrix2.rows){
|
||||
Matrix m = {NULL, 0, 0};
|
||||
return m;
|
||||
}
|
||||
|
||||
|
||||
//size of the matrices should be the same, if the addition is supposed to happen
|
||||
Matrix outputMatrix = createMatrix(matrix1.rows, matrix1.cols);
|
||||
|
||||
if(!outputMatrix.buffer){
|
||||
Matrix m = {NULL, 0, 0};
|
||||
return m;
|
||||
}
|
||||
|
||||
for (int i = 0; i < matrix1.rows;i++) {
|
||||
for (int j = 0; j < matrix1.cols; j++) {
|
||||
// how this should work in normal Matrix version:
|
||||
// outputmatrix.buffer[i][j] = matrix1.buffer[i][j] + matrix2.buffer[i][j];
|
||||
outputMatrix.buffer[i * outputMatrix.cols + j] = matrix1.buffer[i * matrix1.cols + j] + matrix2.buffer[i * matrix2.cols + j];
|
||||
}
|
||||
}
|
||||
return outputMatrix;
|
||||
|
||||
}
|
||||
|
||||
/*
|
||||
Matrix multiply(const Matrix matrix1, const Matrix matrix2)
|
||||
{
|
||||
return outputMatrix;
|
||||
|
||||
//check, if the matrices can be multiplied
|
||||
if (matrix1.rows == matrix2.cols) {
|
||||
Matrix outputMatrix = createMatrix(matrix1.rows, matrix2.cols);
|
||||
//Matrix outputMatrix = createMatrix(matrix2.cols, matrix1.rows);
|
||||
for(int i = 0; i < matrix1.rows; i++) {
|
||||
for (int j = 0; j < matrix2.cols; j++) {
|
||||
for (int k = 0; k < matrix2.rows; k++) {
|
||||
// how this should work in normal Matrix version:
|
||||
// outputMatrix.buffer[i][j] = matrix1.buffer[i][k] * matrix2.buffer[k][j];
|
||||
outputMatrix.buffer[i + outputMatrix.rows * j] += matrix1.buffer[i + matrix1.rows * k] * matrix2.buffer[k + matrix2.rows * j];
|
||||
}
|
||||
}
|
||||
}
|
||||
return outputMatrix;
|
||||
} else {
|
||||
//the matrix could not be added, since the matrix sizes are not set correct.
|
||||
Matrix m;
|
||||
m.rows = 0;
|
||||
m.cols = 0;
|
||||
m.buffer = NULL;
|
||||
return m;
|
||||
}
|
||||
|
||||
}
|
||||
*/
|
||||
|
||||
|
||||
Matrix multiply(const Matrix matrix1, const Matrix matrix2)
|
||||
|
||||
+1
-1
@@ -164,7 +164,7 @@ NeuralNetwork loadModel(const char *path)
|
||||
|
||||
assignActivations(model);
|
||||
}
|
||||
|
||||
printf("%d\n", model.numberOfLayers);
|
||||
return model;
|
||||
}
|
||||
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
make clean && make && make neuralNetworkTests
|
||||
+34
-2
@@ -8,9 +8,41 @@
|
||||
|
||||
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
|
||||
{
|
||||
// TODO
|
||||
}
|
||||
FILE *file = fopen(path, "wb");
|
||||
|
||||
if(file != NULL){
|
||||
const char *fileTag = "__info2_neural_network_file_format__";
|
||||
|
||||
// Write file header
|
||||
fwrite(fileTag, sizeof(char), strlen(fileTag), file);
|
||||
|
||||
// Write the input dimension of the first layer
|
||||
if(nn.numberOfLayers > 0){
|
||||
fwrite(&nn.layers[0].weights.cols, sizeof(int), 1, file);
|
||||
}
|
||||
|
||||
// Write dimensions and data for each layer
|
||||
for(int i = 0; i < nn.numberOfLayers; i++){
|
||||
|
||||
// Write output dimension (rows of weights)
|
||||
fwrite(&nn.layers[i].weights.rows, sizeof(int), 1, file);
|
||||
|
||||
// Write weight matrix data
|
||||
int weightSize = nn.layers[i].weights.rows * nn.layers[i].weights.cols;
|
||||
fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), weightSize, file);
|
||||
|
||||
// Write bias matrix data
|
||||
int biasSize = nn.layers[i].biases.rows * nn.layers[i].biases.cols;
|
||||
fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType), biasSize, file);
|
||||
}
|
||||
|
||||
// Write terminating 0 to signal end of layers
|
||||
int zero = 0;
|
||||
fwrite(&zero, sizeof(int), 1, file);
|
||||
|
||||
fclose(file);
|
||||
}
|
||||
}
|
||||
void test_loadModelReturnsCorrectNumberOfLayers(void)
|
||||
{
|
||||
const char *path = "some__nn_test_file.info2";
|
||||
|
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Reference in New Issue
Block a user