Optionale Aufgabe Eigene Ziffern malen

neuralNetworkTests.c
check

imageInput.c

@@ -9,14 +9,172 @@
 // TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
 
 // TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
+
+
+static int checkFileHeader(FILE *file)
+{
+    char buffer[BUFFER_SIZE];
+    int length = strlen(FILE_HEADER_STRING);
+
+    // Prüfen ob fread erfolgreich war
+    if (fread(buffer, sizeof(char), length, file) != length) {
+        return 0;  // Lesefehler
+    }
+
+    buffer[length] = '\0';
+
+    if (strcmp(buffer, FILE_HEADER_STRING) == 0) {
+        return 1;
+    } else {
+        return 0;
+    }
+}
+
+static int readDimensions(FILE *file, unsigned short * count, unsigned short *width, unsigned short *height)
+{
+    // Anzahl lesen
+    if (fread(count, sizeof(unsigned short), 1, file) != 1) {
+    return 0;
+    }
+    // Breite lesen
+    if (fread(width, sizeof(unsigned short), 1, file) != 1) {
+    return 0;
+    }
+    // Höhe lesen
+    if (fread(height, sizeof(unsigned short), 1, file) != 1) {
+    return 0;
+    }
+
+return 1; // Alles ok
+}
+
+static int readSingleImage(FILE *file, GrayScaleImage *image, unsigned char *label, unsigned short width, unsigned short height)
+{
+    // Schritt 1: Gesamtzahl Pixel berechnen
+    int totalPixels = width * height;
+
+    // Schritt 2: Speicher allokieren
+    image->buffer = (unsigned char *)malloc(totalPixels * sizeof(unsigned char));
+    if (image->buffer == NULL) {
+        return 0;  // Fehler: kein Speicher verfügbar
+    }
+
+    // Schritt 3: Breite und Höhe setzen
+    image->width = width;
+    image->height = height;
+
+    // Schritt 4: Pixel lesen
+    if (fread(image->buffer, sizeof(unsigned char), totalPixels, file) != totalPixels) {
+        free(image->buffer);  // Aufräumen!
+        return 0;  // Fehler beim Lesen
+    }
+
+    // Schritt 5: Label lesen
+    if (fread(label, sizeof(unsigned char), 1, file) != 1) {
+        free(image->buffer);  // Aufräumen!
+        return 0;  // Fehler beim Lesen
+    }
+
+    return 1;  // Erfolg!
+}
+
 GrayScaleImageSeries *readImages(const char *path)
 {
-    GrayScaleImageSeries *series = NULL;
-    
+    // Schritt 1: Datei öffnen
+    FILE *file = fopen(path, "rb");
+    if (file == NULL) {
+        return NULL;
+    }
+
+    // Schritt 2: Header prüfen
+    if (!checkFileHeader(file)) {
+        fclose(file);
+        return NULL;
+    }
+
+    // Schritt 3: Dimensionen lesen
+    unsigned short count, width, height;
+    if (!readDimensions(file, &count, &width, &height)) {
+        fclose(file);
+        return NULL;
+    }
+
+    // Schritt 4: Speicher für die Serie allokieren
+    GrayScaleImageSeries *series = (GrayScaleImageSeries *)malloc(sizeof(GrayScaleImageSeries));
+    if (series == NULL) {
+        fclose(file);
+        return NULL;
+    }
+
+    // Schritt 5: Speicher für das images-Array allokieren
+    series->images = (GrayScaleImage *)malloc(count * sizeof(GrayScaleImage));
+    if (series->images == NULL) {
+        free(series);
+        fclose(file);
+        return NULL;
+    }
+
+    // Schritt 6: Speicher für das labels-Array allokieren
+    series->labels = (unsigned char *)malloc(count * sizeof(unsigned char));
+    if (series->labels == NULL) {
+        free(series->images);
+        free(series);
+        fclose(file);
+        return NULL;
+    }
+
+    // Schritt 7: count setzen
+    series->count = count;
+
+    // Schritt 8: Alle Bilder in einer Schleife einlesen
+    for (int i = 0; i < count; i++) {
+        if (!readSingleImage(file, &series->images[i], &series->labels[i], width, height)) {
+            // Bei Fehler: Aufräumen!
+            for (int j = 0; j < i; j++) {
+                free(series->images[j].buffer);
+            }
+            free(series->images);
+            free(series->labels);
+            free(series);
+            fclose(file);
+            return NULL;
+        }
+    }
+
+    // Schritt 9: Datei schließen
+    fclose(file);
+
+    // Schritt 10: Fertige Serie zurückgeben
     return series;
 }
 
 // TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt
 void clearSeries(GrayScaleImageSeries *series)
 {
-}
+    // Schritt 0: Prüfen ob series überhaupt existiert
+    if (series == NULL) {
+        return;  // Nichts zu tun
+    }
+
+    // Schritt 1: Alle Pixel-Buffer freigeben (für jedes Bild)
+    if (series->images != NULL) {
+        for (int i = 0; i < series->count; i++) {
+            if (series->images[i].buffer != NULL) {
+                free(series->images[i].buffer);  // ← Buffer von Bild i freigeben
+            }
+        }
+    }
+
+    // Schritt 2: Das images-Array freigeben
+    if (series->images != NULL) {
+        free(series->images);
+    }
+
+    // Schritt 3: Das labels-Array freigeben
+    if (series->labels != NULL) {
+        free(series->labels);
+    }
+
+    // Schritt 4: Die Serie-Struktur selbst freigeben
+    free(series);
+}

imageInput.h

@@ -5,17 +5,17 @@ typedef unsigned char GrayScalePixelType;
 
 typedef struct
 {
-    GrayScalePixelType *buffer;
-    unsigned int width;
-    unsigned int height;
-} GrayScaleImage;
+    GrayScalePixelType *buffer; // Breite in Pixeln
+    unsigned int width;         // Höhe in Pixeln
+    unsigned int height;        // Die Pixelwerte (0-255)
+} GrayScaleImage;           // EIN Bild
 
 typedef struct
 {
-    GrayScaleImage *images;
-    unsigned char *labels;
-    unsigned int count;
-} GrayScaleImageSeries;
+    GrayScaleImage *images;    // Array von Bildern
+    unsigned char *labels;     // Array von Labels (welche Ziffer?)
+    unsigned int count;        // Wie viele Bilder ?
+} GrayScaleImageSeries;    // Sammlung der Bilder
 
 GrayScaleImageSeries *readImages(const char *path);
 void clearSeries(GrayScaleImageSeries *series);

matrix.c

@@ -1,35 +1,173 @@
 #include <stdlib.h>
 #include <string.h>
+#include <stdio.h>
 #include "matrix.h"
 
 // TODO Matrix-Funktionen implementieren
 
 Matrix createMatrix(unsigned int rows, unsigned int cols)
 {
-    
+    Matrix m;
+    m.rows = rows;
+    m.cols = cols;
+
+    m.buffer = (MatrixType*)malloc(sizeof(MatrixType) * rows * cols);
+    // Prüfe auf ungültige Dimensionen
+    if (rows == 0 || cols == 0) {
+        m.rows = 0;
+        m.cols = 0;
+        m.buffer = NULL;
+        return m;
+    }
+    if (m.buffer == NULL){
+    fprintf(stderr, "Error: Memory allocation failed in createMatrix!.\n");
+    m.rows = 0;
+    m.cols = 0;
+    return m;
+    }
+for (unsigned int i = 0; i < rows * cols; i++){
+    m.buffer[i] = 0.0f;
+    }
+return m;
 }
 
+
 void clearMatrix(Matrix *matrix)
 {
-    
+
+        if (matrix == NULL) {
+            return;
+        }
+
+        // Speicher freigeben falls vorhanden
+        if (matrix->buffer != NULL) {
+            free(matrix->buffer);
+            matrix->buffer = NULL;
+        }
+
+        // Dimensionen zurücksetzen
+        matrix->rows = 0;
+        matrix->cols = 0;
+
 }
 
 void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
 {
-    
+    if (rowIdx >= matrix.rows || colIdx >= matrix.cols) {
+        fprintf(stderr, "Error: setMatrixAt index out of bounds.\n");
+        return;
+    }
+
+    matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
 }
 
 MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
 {
-    
+    if (rowIdx >= matrix.rows || colIdx >= matrix.cols) {
+        fprintf(stderr, "Error: getMatrixAt index out of bounds.\n");
+        return UNDEFINED_MATRIX_VALUE;
+    }
+
+    return matrix.buffer[rowIdx * matrix.cols + colIdx];
 }
 
 Matrix add(const Matrix matrix1, const Matrix matrix2)
 {
-    
+    Matrix result;
+
+    // Fall 1: Normale elementweise Addition (gleiche Dimensionen)
+    if (matrix1.rows == matrix2.rows && matrix1.cols == matrix2.cols) {
+        result = createMatrix(matrix1.rows, matrix1.cols);
+        if (result.buffer == NULL) {
+            return result;
+        }
+
+        for (unsigned int i = 0; i < matrix1.rows; i++) {
+            for (unsigned int j = 0; j < matrix1.cols; j++) {
+                setMatrixAt(
+                    getMatrixAt(matrix1, i, j) + getMatrixAt(matrix2, i, j),
+                    result,
+                    i, j
+                );
+            }
+        }
+        return result;
+    }
+
+    // Fall 2: Broadcasting - matrix2 ist Spaltenvektor (cols=1)
+    else if (matrix1.rows == matrix2.rows && matrix2.cols == 1) {
+        result = createMatrix(matrix1.rows, matrix1.cols);
+        if (result.buffer == NULL) {
+            return result;
+        }
+
+        for (unsigned int i = 0; i < matrix1.rows; i++) {
+            for (unsigned int j = 0; j < matrix1.cols; j++) {
+                // matrix2 hat nur 1 Spalte (Index 0), wird über alle Spalten verteilt
+                setMatrixAt(
+                    getMatrixAt(matrix1, i, j) + getMatrixAt(matrix2, i, 0),
+                    result,
+                    i, j
+                );
+            }
+        }
+        return result;
+    }
+
+    // Fall 3: Broadcasting - matrix1 ist Spaltenvektor (cols=1)
+    else if (matrix2.rows == matrix1.rows && matrix1.cols == 1) {
+        result = createMatrix(matrix2.rows, matrix2.cols);
+        if (result.buffer == NULL) {
+            return result;
+        }
+
+        for (unsigned int i = 0; i < matrix2.rows; i++) {
+            for (unsigned int j = 0; j < matrix2.cols; j++) {
+                // matrix1 hat nur 1 Spalte (Index 0), wird über alle Spalten verteilt
+                setMatrixAt(
+                    getMatrixAt(matrix1, i, 0) + getMatrixAt(matrix2, i, j),
+                    result,
+                    i, j
+                );
+            }
+        }
+        return result;
+    }
+
+    // Fall 4: Ungültige Dimensionen
+    else {
+        fprintf(stderr, "Error: Matrix dimensions do not match for addition.\n");
+        Matrix empty = {0, 0, NULL};
+        return empty;
+    }
 }
 
+
+
 Matrix multiply(const Matrix matrix1, const Matrix matrix2)
 {
-    
+  if (matrix1.cols != matrix2.rows) {
+        fprintf(stderr, "Error: Invalid matrix dimensions for multiplication.\n");
+        Matrix empty = {0, 0, NULL};
+        return empty;
+    }
+
+    Matrix result = createMatrix(matrix1.rows, matrix2.cols);
+    if (result.buffer == NULL) {
+        return result;
+    }
+
+    for (unsigned int i = 0; i < matrix1.rows; i++) {
+        for (unsigned int j = 0; j < matrix2.cols; j++) {
+            MatrixType sum = 0.0f;
+
+            for (unsigned int k = 0; k < matrix1.cols; k++) {
+                sum += getMatrixAt(matrix1, i, k) * getMatrixAt(matrix2, k, j);
+            }
+
+            setMatrixAt(sum, result, i, j);
+        }
+    }
+
+    return result;
 }

matrix.h

@@ -6,7 +6,12 @@
 typedef float MatrixType;
 
 // TODO Matrixtyp definieren
+typedef struct{
+	unsigned int rows;
+	unsigned int cols;
+	MatrixType* buffer;
 
+}	Matrix;
 
 Matrix createMatrix(unsigned int rows, unsigned int cols);
 void clearMatrix(Matrix *matrix);

mnistVisualization.c

@@ -2,10 +2,22 @@
 #include <stdio.h>
 #include <string.h>
 #include "mnistVisualization.h"
+#include "imageInput.h"
+#include "neuralNetwork.h"
+
+// Matrix-Namenskonflikt mit Raylib lösen: Raylib's Matrix umbenennen
+#define Matrix RaylibMatrix
 #include "raylib.h"
+#undef Matrix
 
 #define MAX_TEXT_LEN 100
 
+// Enum für die verschiedenen Modi
+typedef enum {
+    MODE_BROWSE,
+    MODE_DRAW
+} AppMode;
+
 typedef struct
 {
     Vector2 position;
@@ -13,6 +25,10 @@ typedef struct
     const unsigned char *predictions;
     unsigned int currentIdx;
     Vector2 pixelSize;
+    AppMode mode;
+    GrayScaleImage drawingCanvas;
+    unsigned char canvasPrediction;
+    const NeuralNetwork *model;
 } MnistVisualization;
 
 typedef struct
@@ -45,20 +61,86 @@ static TextLabel *createTextLabel(const char *text, unsigned int fontSize, Color
     return label;
 }
 
-static MnistVisualization *createVisualizationContainer(const GrayScaleImageSeries *series, const unsigned char predictions[], Vector2 size)
+static GrayScaleImage createCanvas(unsigned int width, unsigned int height)
+{
+    GrayScaleImage canvas;
+    canvas.width = width;
+    canvas.height = height;
+    canvas.buffer = (GrayScalePixelType *)calloc(width * height, sizeof(GrayScalePixelType));
+    return canvas;
+}
+
+static void clearCanvas(GrayScaleImage *canvas)
+{
+    if(canvas != NULL && canvas->buffer != NULL)
+    {
+        memset(canvas->buffer, 0, canvas->width * canvas->height * sizeof(GrayScalePixelType));
+    }
+}
+
+static GrayScaleImage downsampleCanvas(const GrayScaleImage *largeCanvas, unsigned int targetWidth, unsigned int targetHeight)
+{
+    GrayScaleImage smallImage = createCanvas(targetWidth, targetHeight);
+
+    if(smallImage.buffer != NULL && largeCanvas != NULL && largeCanvas->buffer != NULL)
+    {
+        unsigned int scaleX = largeCanvas->width / targetWidth;
+        unsigned int scaleY = largeCanvas->height / targetHeight;
+
+        for(unsigned int y = 0; y < targetHeight; y++)
+        {
+            for(unsigned int x = 0; x < targetWidth; x++)
+            {
+                // Durchschnitt über den entsprechenden Bereich berechnen
+                unsigned int sum = 0;
+                unsigned int count = 0;
+
+                for(unsigned int sy = 0; sy < scaleY; sy++)
+                {
+                    for(unsigned int sx = 0; sx < scaleX; sx++)
+                    {
+                        unsigned int srcX = x * scaleX + sx;
+                        unsigned int srcY = y * scaleY + sy;
+
+                        if(srcX < largeCanvas->width && srcY < largeCanvas->height)
+                        {
+                            sum += largeCanvas->buffer[srcY * largeCanvas->width + srcX];
+                            count++;
+                        }
+                    }
+                }
+
+                smallImage.buffer[y * targetWidth + x] = (unsigned char)(sum / count);
+            }
+        }
+    }
+
+    return smallImage;
+}
+
+static MnistVisualization *createVisualizationContainer(const GrayScaleImageSeries *series, const unsigned char predictions[], Vector2 size, const NeuralNetwork *model)
 {
     MnistVisualization *container = NULL;
-    
+
     if(size.x > 0 && size.y > 0 && series != NULL && series->images != NULL && series->count > 0 && predictions != NULL)
     {
         container = (MnistVisualization *)calloc(1, sizeof(MnistVisualization));
 
         if(container != NULL)
         {
-            Vector2 pixelSize = {(int)(size.x / series->images[0].width), (int)(size.y / series->images[0].height)};
+            // Canvas ist 4x größer (112x112), also pixelSize anpassen
+            Vector2 pixelSize = {(int)(size.x / (series->images[0].width * 4)),
+                                (int)(size.y / (series->images[0].height * 4))};
             container->pixelSize = pixelSize;
             container->series = series;
             container->predictions = predictions;
+            container->mode = MODE_BROWSE;
+            container->model = model;
+
+            // Canvas erstellen (4x größer als MNIST für feineres Zeichnen: 112x112 statt 28x28)
+            unsigned int canvasSize = series->images[0].width * 4;
+            container->drawingCanvas = createCanvas(canvasSize, canvasSize);
+            container->canvasPrediction = 0;
         }
     }
 
@@ -94,15 +176,28 @@ static void drawDigit(const GrayScaleImage image, Vector2 position, Vector2 pixe
     }
 }
 
-static void drawAll(const MnistVisualization *container, const TextLabel *navigationLabel, const TextLabel *predictionLabel)
+static void drawAll(const MnistVisualization *container, const TextLabel *navigationLabel, const TextLabel *predictionLabel, const TextLabel *modeLabel)
 {
     BeginDrawing();
     ClearBackground(BLACK);
-    
-    drawDigit(container->series->images[container->currentIdx], container->position, container->pixelSize);
+
+    if(container->mode == MODE_BROWSE)
+    {
+        // Im Browse-Modus: MNIST Bilder sind 28x28, aber pixelSize ist für 112x112
+        // Also pixelSize * 4 verwenden
+        Vector2 browsePixelSize = {container->pixelSize.x * 4, container->pixelSize.y * 4};
+        drawDigit(container->series->images[container->currentIdx], container->position, browsePixelSize);
+    }
+    else // MODE_DRAW
+    {
+        // Im Draw-Modus: Canvas ist 112x112, pixelSize passt
+        drawDigit(container->drawingCanvas, container->position, container->pixelSize);
+    }
+
     drawTextLabel(navigationLabel);
     drawTextLabel(predictionLabel);
-        
+    drawTextLabel(modeLabel);
+
     EndDrawing();
 }
 
@@ -114,10 +209,232 @@ static int checkUserInput()
         inputResult = -1;
     else if(IsKeyReleased(KEY_RIGHT))
         inputResult = 1;
-    
+
     return inputResult;
 }
 
+static void handleDrawing(MnistVisualization *container)
+{
+    static Vector2 lastMousePos = {-1, -1};
+
+    if(IsMouseButtonDown(MOUSE_LEFT_BUTTON))
+    {
+        Vector2 mousePos = GetMousePosition();
+
+        // Berechne welches Pixel geklickt wurde (pixelSize ist bereits für 112x112)
+        int pixelX = (int)((mousePos.x - container->position.x) / container->pixelSize.x);
+        int pixelY = (int)((mousePos.y - container->position.y) / container->pixelSize.y);
+
+        // Wenn wir eine vorherige Position haben, zeichne eine Linie
+        if(lastMousePos.x >= 0 && lastMousePos.y >= 0)
+        {
+            int lastPixelX = (int)((lastMousePos.x - container->position.x) / container->pixelSize.x);
+            int lastPixelY = (int)((lastMousePos.y - container->position.y) / container->pixelSize.y);
+
+            // Bresenham Linien-Algorithmus (vereinfacht)
+            int dx = abs(pixelX - lastPixelX);
+            int dy = abs(pixelY - lastPixelY);
+            int sx = (lastPixelX < pixelX) ? 1 : -1;
+            int sy = (lastPixelY < pixelY) ? 1 : -1;
+            int err = dx - dy;
+
+            int currentX = lastPixelX;
+            int currentY = lastPixelY;
+
+            while(1)
+            {
+                // Zeichne dünnen Pinsel für 112x112 Canvas
+                if(currentX >= 0 && currentX < container->drawingCanvas.width &&
+                   currentY >= 0 && currentY < container->drawingCanvas.height)
+                {
+                    // Zentrum: 2x2 Pixel weiß (entspricht 0.5x0.5 auf 28x28)
+                    for(int dy = 0; dy <= 1; dy++)
+                    {
+                        for(int dx = 0; dx <= 1; dx++)
+                        {
+                            int nx = currentX + dx;
+                            int ny = currentY + dy;
+                            if(nx >= 0 && nx < container->drawingCanvas.width &&
+                               ny >= 0 && ny < container->drawingCanvas.height)
+                            {
+                                int nidx = ny * container->drawingCanvas.width + nx;
+                                container->drawingCanvas.buffer[nidx] = 255;
+                            }
+                        }
+                    }
+
+                    // Ring 1: Direkte Nachbarn (sehr hell)
+                    int ring1[][2] = {{-1,0}, {-1,1}, {0,-1}, {2,0}, {2,1}, {0,2}, {1,2}, {1,-1}};
+                    for(int i = 0; i < 8; i++)
+                    {
+                        int nx = currentX + ring1[i][0];
+                        int ny = currentY + ring1[i][1];
+                        if(nx >= 0 && nx < container->drawingCanvas.width &&
+                           ny >= 0 && ny < container->drawingCanvas.height)
+                        {
+                            int nidx = ny * container->drawingCanvas.width + nx;
+                            if(container->drawingCanvas.buffer[nidx] < 200) {
+                                container->drawingCanvas.buffer[nidx] = 200;
+                            }
+                        }
+                    }
+
+                    // Ring 2: Weitere Nachbarn (mittel)
+                    int ring2[][2] = {{-2,0}, {-2,1}, {-1,-1}, {-1,2}, {0,-2}, {0,3},
+                                      {1,-2}, {1,3}, {2,-1}, {2,2}, {3,0}, {3,1}};
+                    for(int i = 0; i < 12; i++)
+                    {
+                        int nx = currentX + ring2[i][0];
+                        int ny = currentY + ring2[i][1];
+                        if(nx >= 0 && nx < container->drawingCanvas.width &&
+                           ny >= 0 && ny < container->drawingCanvas.height)
+                        {
+                            int nidx = ny * container->drawingCanvas.width + nx;
+                            if(container->drawingCanvas.buffer[nidx] < 140) {
+                                container->drawingCanvas.buffer[nidx] = 140;
+                            }
+                        }
+                    }
+
+                    // Ring 3: Äußere Nachbarn (dunkel)
+                    int ring3[][2] = {{-3,0}, {-3,1}, {-2,-1}, {-2,2}, {-1,-2}, {-1,3},
+                                      {0,-3}, {0,4}, {1,-3}, {1,4}, {2,-2}, {2,3},
+                                      {3,-1}, {3,2}, {4,0}, {4,1}};
+                    for(int i = 0; i < 16; i++)
+                    {
+                        int nx = currentX + ring3[i][0];
+                        int ny = currentY + ring3[i][1];
+                        if(nx >= 0 && nx < container->drawingCanvas.width &&
+                           ny >= 0 && ny < container->drawingCanvas.height)
+                        {
+                            int nidx = ny * container->drawingCanvas.width + nx;
+                            if(container->drawingCanvas.buffer[nidx] < 80) {
+                                container->drawingCanvas.buffer[nidx] = 80;
+                            }
+                        }
+                    }
+                }
+
+                if(currentX == pixelX && currentY == pixelY) break;
+
+                int e2 = 2 * err;
+                if(e2 > -dy)
+                {
+                    err -= dy;
+                    currentX += sx;
+                }
+                if(e2 < dx)
+                {
+                    err += dx;
+                    currentY += sy;
+                }
+            }
+        }
+        else
+        {
+            // Erstes Pixel (kein Vorgänger)
+            if(pixelX >= 0 && pixelX < container->drawingCanvas.width &&
+               pixelY >= 0 && pixelY < container->drawingCanvas.height)
+            {
+                // Gleiche Logik wie oben
+                for(int dy = 0; dy <= 1; dy++)
+                {
+                    for(int dx = 0; dx <= 1; dx++)
+                    {
+                        int nx = pixelX + dx;
+                        int ny = pixelY + dy;
+                        if(nx >= 0 && nx < container->drawingCanvas.width &&
+                           ny >= 0 && ny < container->drawingCanvas.height)
+                        {
+                            int nidx = ny * container->drawingCanvas.width + nx;
+                            container->drawingCanvas.buffer[nidx] = 255;
+                        }
+                    }
+                }
+
+                int ring1[][2] = {{-1,0}, {-1,1}, {0,-1}, {2,0}, {2,1}, {0,2}, {1,2}, {1,-1}};
+                for(int i = 0; i < 8; i++)
+                {
+                    int nx = pixelX + ring1[i][0];
+                    int ny = pixelY + ring1[i][1];
+                    if(nx >= 0 && nx < container->drawingCanvas.width &&
+                       ny >= 0 && ny < container->drawingCanvas.height)
+                    {
+                        int nidx = ny * container->drawingCanvas.width + nx;
+                        if(container->drawingCanvas.buffer[nidx] < 200) {
+                            container->drawingCanvas.buffer[nidx] = 200;
+                        }
+                    }
+                }
+
+                int ring2[][2] = {{-2,0}, {-2,1}, {-1,-1}, {-1,2}, {0,-2}, {0,3},
+                                  {1,-2}, {1,3}, {2,-1}, {2,2}, {3,0}, {3,1}};
+                for(int i = 0; i < 12; i++)
+                {
+                    int nx = pixelX + ring2[i][0];
+                    int ny = pixelY + ring2[i][1];
+                    if(nx >= 0 && nx < container->drawingCanvas.width &&
+                       ny >= 0 && ny < container->drawingCanvas.height)
+                    {
+                        int nidx = ny * container->drawingCanvas.width + nx;
+                        if(container->drawingCanvas.buffer[nidx] < 140) {
+                            container->drawingCanvas.buffer[nidx] = 140;
+                        }
+                    }
+                }
+
+                int ring3[][2] = {{-3,0}, {-3,1}, {-2,-1}, {-2,2}, {-1,-2}, {-1,3},
+                                  {0,-3}, {0,4}, {1,-3}, {1,4}, {2,-2}, {2,3},
+                                  {3,-1}, {3,2}, {4,0}, {4,1}};
+                for(int i = 0; i < 16; i++)
+                {
+                    int nx = pixelX + ring3[i][0];
+                    int ny = pixelY + ring3[i][1];
+                    if(nx >= 0 && nx < container->drawingCanvas.width &&
+                       ny >= 0 && ny < container->drawingCanvas.height)
+                    {
+                        int nidx = ny * container->drawingCanvas.width + nx;
+                        if(container->drawingCanvas.buffer[nidx] < 80) {
+                            container->drawingCanvas.buffer[nidx] = 80;
+                        }
+                    }
+                }
+            }
+        }
+
+        lastMousePos = mousePos;
+    }
+    else
+    {
+        // Maustaste losgelassen - Reset der letzten Position
+        lastMousePos.x = -1;
+        lastMousePos.y = -1;
+    }
+}
+
+static void updatePredictionForCanvas(MnistVisualization *container)
+{
+    if(container->model != NULL && container->series != NULL && container->series->images != NULL)
+    {
+        // Canvas von 112x112 auf 28x28 runterskalieren
+        unsigned int targetSize = container->series->images[0].width;
+        GrayScaleImage downsampled = downsampleCanvas(&container->drawingCanvas, targetSize, targetSize);
+
+        if(downsampled.buffer != NULL)
+        {
+            unsigned char *prediction = predict(*container->model, &downsampled, 1);
+            if(prediction != NULL)
+            {
+                container->canvasPrediction = prediction[0];
+                free(prediction);
+            }
+
+            // Downsampled Image aufräumen
+            free(downsampled.buffer);
+        }
+    }
+}
+
 static void updateDisplayContainer(MnistVisualization *container, int updateDirection)
 {
     int newIndex = (int)container->currentIdx + updateDirection;
@@ -130,44 +447,124 @@ static void updateDisplayContainer(MnistVisualization *container, int updateDire
     container->currentIdx = newIndex;
 }
 
-static void updatePredictionLabel(TextLabel *predictionLabel, unsigned char trueLabel, unsigned char predictedLabel)
+static void updatePredictionLabel(TextLabel *predictionLabel, unsigned char trueLabel, unsigned char predictedLabel, AppMode mode)
 {
-    snprintf(predictionLabel->text, MAX_TEXT_LEN, "True label:        %u\nPredicted label:  %u", trueLabel, predictedLabel);
+    if(mode == MODE_BROWSE)
+    {
+        snprintf(predictionLabel->text, MAX_TEXT_LEN, "True label:       %u\nPredicted label:  %u", trueLabel, predictedLabel);
+    }
+    else // MODE_DRAW
+    {
+        snprintf(predictionLabel->text, MAX_TEXT_LEN, "Predicted label:  %u", predictedLabel);
+    }
 }
 
-static void update(MnistVisualization *container, TextLabel *predictionLabel, int updateDirection)
+static void updateModeLabel(TextLabel *modeLabel, AppMode mode)
 {
-    updateDisplayContainer(container, updateDirection);
-    updatePredictionLabel(predictionLabel, container->series->labels[container->currentIdx], container->predictions[container->currentIdx]);
+    if(mode == MODE_BROWSE)
+    {
+        snprintf(modeLabel->text, MAX_TEXT_LEN, "Mode: BROWSE | Press 'D' to draw");
+    }
+    else // MODE_DRAW
+    {
+        snprintf(modeLabel->text, MAX_TEXT_LEN, "Mode: DRAW | Press 'B' to browse | Press 'C' to clear");
+    }
+}
+
+static void update(MnistVisualization *container, TextLabel *predictionLabel, TextLabel *modeLabel, int updateDirection)
+{
+    // Mode-Wechsel
+    if(IsKeyPressed(KEY_D))
+    {
+        container->mode = MODE_DRAW;
+        clearCanvas(&container->drawingCanvas);
+    }
+    else if(IsKeyPressed(KEY_B))
+    {
+        container->mode = MODE_BROWSE;
+    }
+
+    // Canvas löschen im Draw-Mode
+    if(container->mode == MODE_DRAW && IsKeyPressed(KEY_C))
+    {
+        clearCanvas(&container->drawingCanvas);
+        container->canvasPrediction = 0;
+    }
+
+    if(container->mode == MODE_BROWSE)
+    {
+        updateDisplayContainer(container, updateDirection);
+        updatePredictionLabel(predictionLabel,
+                            container->series->labels[container->currentIdx],
+                            container->predictions[container->currentIdx],
+                            MODE_BROWSE);
+    }
+    else // MODE_DRAW
+    {
+        handleDrawing(container);
+
+        // Prediction alle paar Frames aktualisieren (nicht bei jedem Frame für Performance)
+        static int frameCounter = 0;
+        frameCounter++;
+        if(frameCounter % 10 == 0)
+        {
+            updatePredictionForCanvas(container);
+        }
+
+        updatePredictionLabel(predictionLabel, 0, container->canvasPrediction, MODE_DRAW);
+    }
+
+    updateModeLabel(modeLabel, container->mode);
 }
 
 void showMnist(unsigned int windowWidth, unsigned int windowHeight, const GrayScaleImageSeries *series, const unsigned char predictions[])
 {
+    // Model laden (für Draw-Modus)
+    NeuralNetwork model = loadModel("mnist_model.info2");
+
     const Vector2 windowSize = {windowWidth, windowHeight};
 
-    MnistVisualization *container = createVisualizationContainer(series, predictions, windowSize);
+    MnistVisualization *container = createVisualizationContainer(series, predictions, windowSize, &model);
     TextLabel *navigationLabel = createTextLabel("Use left and right key to navigate ...", 20, WHITE);
     TextLabel *predictionLabel = createTextLabel("", 20, WHITE);
+    TextLabel *modeLabel = createTextLabel("", 20, WHITE);
+
+    navigationLabel->position.x = windowSize.x - 400; // Rechts (mit Abstand)
+    navigationLabel->position.y = windowSize.y - 30;  // Ganz unten
+
     predictionLabel->position.x = 10;
     predictionLabel->position.y = windowSize.y - 50;
 
-    if(container != NULL && navigationLabel != NULL && predictionLabel != NULL)
+    modeLabel->position.x = 10;
+    modeLabel->position.y = 10;
+
+    if(container != NULL && navigationLabel != NULL && predictionLabel != NULL && modeLabel != NULL)
     {
-        InitWindow(windowSize.x, windowSize.y, "MNIST Browser");
+        InitWindow(windowSize.x, windowSize.y, "MNIST Browser & Drawer");
 
         SetTargetFPS(60);
 
         while (!WindowShouldClose())
         {
             int updateDirection = checkUserInput();
-            update(container, predictionLabel, updateDirection);
-            drawAll(container, navigationLabel, predictionLabel);
+            update(container, predictionLabel, modeLabel, updateDirection);
+            drawAll(container, navigationLabel, predictionLabel, modeLabel);
         }
     }
 
     CloseWindow();
 
-    free(container);
+    // Cleanup
+    if(container != NULL)
+    {
+        if(container->drawingCanvas.buffer != NULL)
+        {
+            free(container->drawingCanvas.buffer);
+        }
+        free(container);
+    }
     free(navigationLabel);
     free(predictionLabel);
+    free(modeLabel);
+    clearModel(&model);
 }

neuralNetwork.c

@@ -170,7 +170,7 @@ NeuralNetwork loadModel(const char *path)
 
 static Matrix imageBatchToMatrixOfImageVectors(const GrayScaleImage images[], unsigned int count)
 {
-    Matrix matrix = {NULL, 0, 0};
+    Matrix matrix = {0, 0, NULL}; //hier evtl Null auf int casten?
 
     if(count > 0 && images != NULL)
     {

neuralNetworkTests.c

@@ -8,7 +8,42 @@
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    FILE *file = fopen(path, "wb");
+
+    if (file == NULL) {
+        return;
+    }
+
+    // 1. Header schreiben
+    const char *fileTag = "__info2_neural_network_file_format__";
+    fwrite(fileTag, sizeof(char), strlen(fileTag), file);
+
+    // 2. Alle Schichten schreiben
+    for (unsigned int i = 0; i < nn.numberOfLayers; i++) {
+        // NUR bei der ERSTEN Schicht: Input-Dimension schreiben
+        if (i == 0) {
+            int inputDim = nn.layers[i].weights.cols;
+            fwrite(&inputDim, sizeof(int), 1, file);
+        }
+
+        // Output-Dimension (= Anzahl Zeilen der Gewichtsmatrix)
+        int outputDim = nn.layers[i].weights.rows;
+        fwrite(&outputDim, sizeof(int), 1, file);
+
+        // Gewichtsmatrix schreiben (alle Werte)
+        int weightCount = nn.layers[i].weights.rows * nn.layers[i].weights.cols;
+        fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), weightCount, file);
+
+        // Bias-Matrix schreiben (alle Werte)
+        int biasCount = nn.layers[i].biases.rows * nn.layers[i].biases.cols;
+        fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType), biasCount, file);
+    }
+
+    // 3. Terminator schreiben (outputDimension = 0 zum Stoppen)
+    int terminator = 0;
+    fwrite(&terminator, sizeof(int), 1, file);
+
+    fclose(file);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)