forked from freudenreichan/info2Praktikum-NeuronalesNetz
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2 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 2436240736 | |||
| fde82f2d9a |
117
imageInput.c
117
imageInput.c
@ -1,97 +1,22 @@
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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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// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
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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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FILE *file = fopen(path, "rb");
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if (file == NULL)
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{
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return NULL;
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}
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// Überprüfe den Header
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char fileTag[strlen(FILE_HEADER_STRING)];
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fread(fileTag, sizeof(fileTag[0]), strlen(FILE_HEADER_STRING), file);
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if (strcmp(fileTag, FILE_HEADER_STRING) != 0)
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{
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fclose(file);
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return NULL;
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}
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// Lese die Metadaten: Anzahl der Bilder, Breite und Höhe
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unsigned short numberOfImages, width, height;
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fread(&numberOfImages, sizeof(numberOfImages), 1, file);
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fread(&width, sizeof(width), 1, file);
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fread(&height, sizeof(height), 1, file);
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GrayScaleImageSeries *series = (GrayScaleImageSeries *)malloc(sizeof(GrayScaleImageSeries));
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if (series == NULL)
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{
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fclose(file);
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return NULL;
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}
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series->count = numberOfImages;
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series->images = (GrayScaleImage *)malloc(numberOfImages * sizeof(GrayScaleImage));
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series->labels = (unsigned char *)malloc(numberOfImages * sizeof(unsigned char));
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if (series->images == NULL || series->labels == NULL)
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{
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free(series);
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fclose(file);
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return NULL;
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}
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for (int i = 0; i < numberOfImages; i++)
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{
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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 = (GrayScalePixelType *)malloc(width * height * sizeof(GrayScalePixelType));
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if (series->images[i].buffer == NULL)
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{
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// Fehlerbehandlung: Speicher freigeben, wenn malloc fehlschlägt
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for (int j = 0; j < i; j++)
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{
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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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free(series);
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fclose(file);
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return NULL;
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}
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// Lese die Pixel-Daten und das Label
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fread(series->images[i].buffer, sizeof(GrayScalePixelType), width * height, file);
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fread(&series->labels[i], sizeof(unsigned char), 1, file);
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}
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fclose(file);
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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)
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return;
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for (int i = 0; i < series->count; i++)
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{
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free(series->images[i].buffer); // Speicher für das Bild freigeben
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}
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free(series->images); // Speicher für die Bild-Array freigeben
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free(series->labels); // Speicher für die Labels freigeben
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free(series); // Speicher freigeben
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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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// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
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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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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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}
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199
matrix.c
199
matrix.c
@ -1,166 +1,35 @@
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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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// TODO Matrix-Funktionen implementieren
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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{
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Matrix m = {NULL, 0, 0};
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if (rows > 0 && cols > 0)
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{
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m.buffer = malloc(rows * cols * sizeof(int));
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m.rows = rows;
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m.cols = cols;
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}
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return m;
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}
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void clearMatrix(Matrix *matrix)
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{
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if (matrix == NULL)
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{
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return;
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}
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// Speicher freigeben, falls vorhanden
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free(matrix->buffer);
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matrix->buffer = NULL;
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// Metadaten zurücksetzen
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matrix->rows = 0;
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matrix->cols = 0;
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}
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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{
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matrix.buffer[rowIdx * matrix.cols + colIdx] = value; // setzte Matrix auf den Wert value am Punkt (row col)
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}
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MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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{
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MatrixType value = 0;
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if (rowIdx < matrix.rows && colIdx < matrix.cols)
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{
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value = matrix.buffer[rowIdx * matrix.cols + colIdx]; // hole Wert value am Punkt (row col)
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}
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return value;
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}
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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{
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Matrix result = {0};
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int broadcast_case =
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(matrix1.cols == 1 && matrix1.rows == matrix2.rows) ||
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(matrix2.cols == 1 && matrix1.rows == matrix2.rows);
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if (!broadcast_case && (matrix1.rows != matrix2.rows || matrix1.cols != matrix2.cols))
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{
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return result;
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}
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result.rows = matrix1.rows;
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result.cols = matrix1.cols;
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result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
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// wenn buffer nicht allokiert werden kann dann zurücksetzen und abbrechen
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if (result.buffer == NULL)
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{
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result.rows = result.cols = 0;
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return result;
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}
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if (matrix1.cols == 1 && matrix1.rows == matrix2.rows) // Broadcasting
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{
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result.rows = matrix2.rows;
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result.cols = matrix2.cols;
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for (unsigned int i = 0; i < matrix1.rows; i++)
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{
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for (unsigned int j = 0; j < result.cols; j++)
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{
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result.buffer[i * result.cols + j] = matrix1.buffer[i] + matrix2.buffer[i * matrix2.cols + j];
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}
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}
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}
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else if (matrix2.cols == 1 && matrix1.rows == matrix2.rows)
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{
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result.rows = matrix1.rows;
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result.cols = matrix1.cols;
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for (unsigned int i = 0; i < matrix2.rows; i++)
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{
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for (unsigned int j = 0; j < result.cols; j++)
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{
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result.buffer[i * result.cols + j] = matrix1.buffer[i * matrix1.cols + j] + matrix2.buffer[i];
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}
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}
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}
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else
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{
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// Elementweise Addition
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for (unsigned int i = 0; i < result.rows; i++)
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{
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for (unsigned int j = 0; j < result.cols; j++)
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{
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result.buffer[i * result.cols + j] = matrix1.buffer[i * matrix1.cols + j] + matrix2.buffer[i * matrix2.cols + j];
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}
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}
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}
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return result;
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}
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Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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{
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Matrix result = {0};
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if (matrix1.cols != matrix2.rows)
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{
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return result;
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}
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result.rows = matrix1.rows;
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result.cols = matrix2.cols;
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result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
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// wenn buffer nicht allokiert werden kann dann zurücksetzen und abbrechen
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if (result.buffer == NULL)
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{
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result.rows = result.cols = 0;
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return result;
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}
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// Matritzenmultiplikation
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for (int r = 0; r < result.rows; r++) // Zeile in Ergebnis
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{
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for (int m = 0; m < result.cols; m++) // Spalte in Ergebnis
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{
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MatrixType sum = 0;
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for (int n = 0; n < matrix1.cols; n++)
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{
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sum += matrix1.buffer[r * matrix1.cols + n] *
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matrix2.buffer[n * matrix2.cols + m];
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}
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result.buffer[r * result.cols + m] = sum;
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}
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}
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return result;
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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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// TODO Matrix-Funktionen implementieren
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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{
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}
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void clearMatrix(Matrix *matrix)
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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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{
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}
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MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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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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}
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Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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{
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}
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45
matrix.h
45
matrix.h
@ -1,26 +1,19 @@
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#ifndef MATRIX_H
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#define MATRIX_H
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#define UNDEFINED_MATRIX_VALUE 0
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typedef float MatrixType;
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// TODO Matrixtyp definieren
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typedef struct
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{
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MatrixType *buffer; // Zeiger auf die Matrixdaten
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unsigned int rows; // Anzahl der Zeilen
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unsigned int cols; // Anzahl der Spalten
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} Matrix;
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Matrix createMatrix(unsigned int rows, unsigned int cols);
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void clearMatrix(Matrix *matrix);
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
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MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
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Matrix add(const Matrix matrix1, const Matrix matrix2);
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Matrix multiply(const Matrix matrix1, const Matrix matrix2);
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#endif
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#ifndef MATRIX_H
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#define MATRIX_H
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#define UNDEFINED_MATRIX_VALUE 0
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typedef float MatrixType;
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// TODO Matrixtyp definieren
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Matrix createMatrix(unsigned int rows, unsigned int cols);
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void clearMatrix(Matrix *matrix);
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
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MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
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Matrix add(const Matrix matrix1, const Matrix matrix2);
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Matrix multiply(const Matrix matrix1, const Matrix matrix2);
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#endif
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@ -164,7 +164,7 @@ void test_setMatrixAtFailsOnIndicesOutOfRange(void)
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Matrix matrixToTest = {.rows=2, .cols=3, .buffer=buffer};
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setMatrixAt(-1, matrixToTest, 2, 3);
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TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, matrixToTest.buffer, matrixToTest.cols * matrixToTest.rows);
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TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, matrixToTest.buffer, sizeof(buffer)/sizeof(MatrixType));
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}
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void setUp(void) {
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@ -8,62 +8,7 @@
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static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
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{
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FILE *file = fopen(path, "wb");
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if (!file) {
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perror("Fehler beim Erstellen der Testdatei");
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exit(EXIT_FAILURE);
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}
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// File header
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const char *fileTag = "__info2_neural_network_file_format__";
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fwrite(fileTag, strlen(fileTag), 1, file);
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if (nn.numberOfLayers == 0)
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{
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unsigned int zero = 0;
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fwrite(&zero, sizeof(unsigned int), 1, file);
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fclose(file);
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return;
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}
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// first layer dimension
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unsigned int in = nn.layers[0].weights.cols;
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unsigned int out = nn.layers[0].weights.rows;
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fwrite(&in, sizeof(unsigned int), 1, file);
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fwrite(&out, sizeof(unsigned int), 1, file);
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// do all layers
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for (unsigned int i = 0; i < nn.numberOfLayers; i++)
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{
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const Layer *L = &nn.layers[i];
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// Write weights matrix
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fwrite(L->weights.buffer,
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sizeof(MatrixType),
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L->weights.rows * L->weights.cols,
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file);
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// Write biases matrix
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fwrite(L->biases.buffer,
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sizeof(MatrixType),
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L->biases.rows * L->biases.cols,
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file);
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// After layer i, write dimension of next layer
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if (i + 1 < nn.numberOfLayers)
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{
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unsigned int nextOut = nn.layers[i+1].weights.rows;
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fwrite(&nextOut, sizeof(unsigned int), 1, file);
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}
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}
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// --- 5. Write terminating zero ---
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unsigned int zero = 0;
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fwrite(&zero, sizeof(unsigned int), 1, file);
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fclose(file);
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// TODO
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}
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void test_loadModelReturnsCorrectNumberOfLayers(void)
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Block a user