From abe51f21d65b8bb7f9307cea3ed249ceae055d62 Mon Sep 17 00:00:00 2001
From: jw <jannik.wild@siemens.com>
Date: Sat, 22 Nov 2025 16:09:38 +0100
Subject: [PATCH] fertiges Programm

---
 imageInput.c         | 91 ++++++++++++++++++++++++++++++++++++++++----
 neuralNetworkTests.c | 40 ++++++++++++++++++-
 2 files changed, 122 insertions(+), 9 deletions(-)

diff --git a/imageInput.c b/imageInput.c
index bb30de1..000d1a7 100644
--- a/imageInput.c
+++ b/imageInput.c
@@ -1,3 +1,4 @@
+
 #include <stdio.h>
 #include <stdlib.h>
 #include <string.h>
@@ -6,17 +7,93 @@
 #define BUFFER_SIZE 100
 #define FILE_HEADER_STRING "__info2_image_file_format__"
 
-// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
-
-// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
 GrayScaleImageSeries *readImages(const char *path)
 {
-    GrayScaleImageSeries *series = NULL;
-    
+    if (path == NULL) return NULL;
+
+    FILE *file = fopen(path, "rb");
+    if (!file) return NULL;
+
+    // Header prüfen
+    size_t tagLen = strlen(FILE_HEADER_STRING);
+    if (tagLen >= BUFFER_SIZE) { fclose(file); return NULL; }
+
+    char tagBuf[BUFFER_SIZE];
+    if (fread(tagBuf, 1, tagLen, file) != tagLen || memcmp(tagBuf, FILE_HEADER_STRING, tagLen) != 0) {
+        fclose(file);
+        return NULL;
+    }
+
+ 
+
+    // Anzahl, Breite, Höhe lesen
+    unsigned short numberOfImages = 0, width = 0, height = 0;
+    if (fread(&numberOfImages, sizeof(numberOfImages), 1, file) != 1 ||
+        fread(&width, sizeof(width), 1, file) != 1 ||
+        fread(&height, sizeof(height), 1, file) != 1) {
+        fclose(file);
+        return NULL;
+    }
+
+    if (numberOfImages == 0 || width == 0 || height == 0) {
+        fclose(file);
+        return NULL;
+    }
+
+    // Serie allokieren
+    GrayScaleImageSeries *series = malloc(sizeof(GrayScaleImageSeries));
+    if (!series) { fclose(file); return NULL; }
+
+    series->count = numberOfImages;
+    series->images = calloc(series->count, sizeof(GrayScaleImage));
+    series->labels = calloc(series->count, sizeof(unsigned char));
+    if (!series->images || !series->labels) {
+        free(series->images);
+        free(series->labels);
+        free(series);
+        fclose(file);
+        return NULL;
+    }
+
+    size_t pixelsPerImage = (size_t)width * height;
+    for (unsigned int i = 0; i < series->count; i++) {
+        series->images[i].width = width;
+        series->images[i].height = height;
+        series->images[i].buffer = malloc(pixelsPerImage * sizeof(GrayScalePixelType));
+        if (!series->images[i].buffer) {
+            for (unsigned int j = 0; j < i; j++) free(series->images[j].buffer);
+            free(series->images);
+            free(series->labels);
+            free(series);
+            fclose(file);
+            return NULL;
+        }
+
+        if (fread(series->images[i].buffer, sizeof(GrayScalePixelType), pixelsPerImage, file) != pixelsPerImage ||
+            fread(&series->labels[i], sizeof(unsigned char), 1, file) != 1) {
+            for (unsigned int j = 0; j <= i; j++) free(series->images[j].buffer);
+            free(series->images);
+            free(series->labels);
+            free(series);
+            fclose(file);
+            return NULL;
+        }
+    }
+
+    fclose(file);
     return series;
 }
 
-// TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt
 void clearSeries(GrayScaleImageSeries *series)
 {
-}
\ No newline at end of file
+    if (!series) return;
+    if (series->images) {
+        for (unsigned int i = 0; i < series->count; i++) {
+            free(series->images[i].buffer);
+        }
+        free(series->images);
+    }
+    free(series->labels);
+    free(series);
+}
+
diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c
index 21ab370..46d175c 100644
--- a/neuralNetworkTests.c
+++ b/neuralNetworkTests.c
@@ -7,8 +7,44 @@
 
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
-{
-    // TODO
+{ 
+    
+
+    FILE *file = fopen(path, "wb");
+    if (!file) return;
+
+    const char *header = "__info2_neural_network_file_format__";
+    fwrite(header, sizeof(char), strlen(header), file);
+
+    if (nn.numberOfLayers > 0) {
+        // Erste Schicht: inputDim und outputDim
+        unsigned int inputDim = nn.layers[0].weights.cols;
+        unsigned int outputDim = nn.layers[0].weights.rows;
+        fwrite(&inputDim, sizeof(unsigned int), 1, file);
+        fwrite(&outputDim, sizeof(unsigned int), 1, file);
+
+        // Erste Schicht schreiben
+        fwrite(nn.layers[0].weights.buffer, sizeof(MatrixType), inputDim * outputDim, file);
+        fwrite(nn.layers[0].biases.buffer, sizeof(MatrixType), outputDim, file);
+
+        // Weitere Schichten: nur outputDim + Matrizen
+        for (unsigned int i = 1; i < nn.numberOfLayers; i++) {
+            outputDim = nn.layers[i].weights.rows;
+            fwrite(&outputDim, sizeof(unsigned int), 1, file);
+            fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType),
+                   nn.layers[i].weights.rows * nn.layers[i].weights.cols, file);
+            fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType),
+                   nn.layers[i].biases.rows, file);
+        }
+    }
+
+    // Endmarker
+    unsigned int zero = 0;
+    fwrite(&zero, sizeof(unsigned int), 1, file);
+
+    fclose(file);
+
+
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)