forked from freudenreichan/info2Praktikum-NeuronalesNetz
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2
Commits
| Author | SHA1 | Date | |
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51f176e892 | ||
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fbd456f6a0 |
No files matched your search
+1
-89
@@ -8,103 +8,15 @@
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// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
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// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
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/* Liest den Datei-Header sowie Anzahl und Abmessungen der Bilder. */
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static int readFileHeader(FILE *file, unsigned short *count, unsigned short *width, unsigned short *height)
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{
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char tag[sizeof(FILE_HEADER_STRING) - 1];
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return fread(tag, sizeof(tag), 1, file) == 1 &&
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memcmp(tag, FILE_HEADER_STRING, sizeof(tag)) == 0 && /* vergleicht File-Header mit dem erwarteten Wert */
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fread(count, sizeof(*count), 1, file) == 1 &&
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fread(width, sizeof(*width), 1, file) == 1 &&
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fread(height, sizeof(*height), 1, file) == 1 &&
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*count > 0 && *width > 0 && *height > 0;
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}
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/* Liest die Pixel und das unmittelbar folgende Label eines Bildes. */
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static int readImage(FILE *file, GrayScaleImage *image, unsigned char *label, size_t pixelCount)
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{
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image->buffer = (GrayScalePixelType *)malloc(pixelCount);
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if (image->buffer == NULL || fread(image->buffer, sizeof(*image->buffer), pixelCount, file) != pixelCount || fread(label, sizeof(*label), 1, file) != 1) /*Prüft ob Speicher korrekt reserviert wurde */
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{
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free(image->buffer);
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image->buffer = NULL;
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return 0;
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}
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return 1;
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}
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/* Gibt auch bereits teilweise geladene Serien und deren Pixelpuffer frei. */
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static void freeImages(GrayScaleImageSeries *series)
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{
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if (series == NULL) /*Prüft ob Serie übergeben Wurde*/
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return;
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if (series->images != NULL)
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{
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for (unsigned int i = 0; i < series->count; ++i) /* Prüft jedes bIld der Serie*/
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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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// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
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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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GrayScaleImageSeries *readImages(const char *path)
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{
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{
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GrayScaleImageSeries *series = NULL;
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GrayScaleImageSeries *series = NULL;
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unsigned short count, width, height;
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size_t pixelCount;
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FILE *file;
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if (path == NULL || (file = fopen(path, "rb")) == NULL) /*prüft ob sich Pfad öffnen lässt*/
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return 0;
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/* Zuerst den Header prüfen, bevor Speicher reserviert wird */
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if (!readFileHeader(file, &count, &width, &height))
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{
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fclose(file);
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freeImages(series);
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return 0;
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}
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pixelCount = (size_t)width * height;
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series = (GrayScaleImageSeries *)calloc(1, sizeof(*series)); /*Speicher für Serie reservieren*/
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if (series == NULL)
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{
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fclose(file);
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freeImages(series);
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return 0;
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}
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series->count = count; /*speicher die anzahl der Bilder*/
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series->images = (GrayScaleImage *)calloc(count, sizeof(*series->images));
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series->labels = (unsigned char *)malloc(count * sizeof(*series->labels));
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if (series->images == NULL || series->labels == NULL)
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{
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fclose(file);
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freeImages(series);
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return 0;
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}
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/*Parameter jedes Bildes einlesen*/
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for (unsigned int i = 0; i < count; ++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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if (!readImage(file, &series->images[i], &series->labels[i], pixelCount))
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{
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fclose(file);
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freeImages(series);
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return 0;
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}
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}
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fclose(file);
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return series;
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return series;
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}
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}
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// TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt
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void clearSeries(GrayScaleImageSeries *series)
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void clearSeries(GrayScaleImageSeries *series)
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{
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{
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freeImages(series);
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}
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}
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@@ -119,17 +119,6 @@ void test_readImagesFailsOnWrongFileTag(void)
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remove(path);
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remove(path);
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}
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}
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void test_readImagesFailsOnZeroWidth(void)
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{
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const char *path = "testFile.info2";
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prepareImageFile(path, 0, 8, 1, 1);
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TEST_ASSERT_NULL(readImages(path));
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remove(path);
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}
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void setUp(void) {
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void setUp(void) {
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// Falls notwendig, kann hier Vorbereitungsarbeit gemacht werden
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// Falls notwendig, kann hier Vorbereitungsarbeit gemacht werden
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}
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}
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@@ -149,7 +138,6 @@ int main()
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RUN_TEST(test_readImagesReturnsCorrectLabels);
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RUN_TEST(test_readImagesReturnsCorrectLabels);
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RUN_TEST(test_readImagesReturnsNullOnNotExistingPath);
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RUN_TEST(test_readImagesReturnsNullOnNotExistingPath);
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RUN_TEST(test_readImagesFailsOnWrongFileTag);
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RUN_TEST(test_readImagesFailsOnWrongFileTag);
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RUN_TEST(test_readImagesFailsOnZeroWidth);
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return UNITY_END();
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return UNITY_END();
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}
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}
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@@ -6,158 +6,30 @@
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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{
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{
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if (rows == 0 || cols == 0) {
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return (Matrix){0}; // Setzt rows, cols und den Puffer auf 0/NULL
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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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// Speicher reservieren und mit 0 initialisieren
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m.buffer = (MatrixType *)calloc((size_t)rows * cols, sizeof(MatrixType));
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// Falls Arbeitsspeicher voll ist
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if (m.buffer == NULL) {
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m.rows = 0;
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m.cols = 0;
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}
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return m;
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}
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}
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void clearMatrix(Matrix *matrix)
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void clearMatrix(Matrix *matrix)
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{
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{
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//prüfen ob pointer exisitert und ob es einen buffer gibt
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if (matrix != NULL && matrix->buffer != NULL)
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{
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// Speicher freigeben
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free(matrix->buffer);
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// Werte zurücksetzen
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matrix->buffer = NULL;
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matrix->rows = 0;
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matrix->cols = 0;
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}
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}
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}
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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{
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{
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// Sind Idx innerhalb der Matrix?
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if (matrix.buffer != NULL && rowIdx < matrix.rows && colIdx < matrix.cols)
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{
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// Umrechnung von 2D auf 1D
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matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
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}
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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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MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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{
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{
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// Sicherheitsprüfung wie beim setzen
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if (matrix.buffer != NULL && rowIdx < matrix.rows && colIdx < matrix.cols)
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{
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return matrix.buffer[rowIdx * matrix.cols + colIdx];
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}
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// Fehlerwert, falls außerhalb der grenzen
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return UNDEFINED_MATRIX_VALUE;
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}
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}
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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{
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{
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// Prüfen ob Zeilenanzahl gleich ist und ob buffer existieren
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if (matrix1.buffer == NULL || matrix2.buffer == NULL || matrix1.rows != matrix2.rows)
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{
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return (Matrix){0};
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}
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// Wenn beide Matrixen gleich groß sind:
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if (matrix1.cols == matrix2.cols)
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{
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Matrix result = createMatrix(matrix1.rows, matrix1.cols);
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if (result.buffer == NULL) return (Matrix){0};
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unsigned int totalElements = matrix1.rows * matrix1.cols;
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for (unsigned int i = 0; i < totalElements; i++)
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{
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result.buffer[i] = matrix1.buffer[i] + matrix2.buffer[i];
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}
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return result;
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}
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//Wenn matrix2 ein Spaltenvektor ist
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else if (matrix2.cols == 1)
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{
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Matrix result = createMatrix(matrix1.rows, matrix1.cols);
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if (result.buffer == NULL) return (Matrix){0};
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for (unsigned int r = 0; r < matrix1.rows; r++)
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{
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for (unsigned int c = 0; c < matrix1.cols; c++)
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{
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// Wert mit r und c aus m1 + Wert mit r aus m2
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result.buffer[r * matrix1.cols + c] = matrix1.buffer[r * matrix1.cols + c] + matrix2.buffer[r];
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}
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}
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return result;
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}
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//Wenn matrix1 ein Spaltenvektor ist
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else if (matrix1.cols == 1)
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{
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Matrix result = createMatrix(matrix2.rows, matrix2.cols);
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if (result.buffer == NULL) return (Matrix){0};
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for (unsigned int r = 0; r < matrix2.rows; r++)
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{
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for (unsigned int c = 0; c < matrix2.cols; c++)
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{
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//gleich wie davor nur m1 und m2 getauscht
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result.buffer[r * matrix2.cols + c] = matrix2.buffer[r * matrix2.cols + c] + matrix1.buffer[r];
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}
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}
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return result;
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}
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return (Matrix){0};
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}
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}
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Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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{
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{
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// Überprüfen, ob die Matrizen gültig sind und ob ihre Dimensionen eine Multiplikation erlauben
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if (matrix1.buffer == NULL || matrix2.buffer == NULL || matrix1.cols != matrix2.rows)
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{
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return (Matrix){0};
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}
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// Ergebnismatrix erstellen
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Matrix result = createMatrix(matrix1.rows, matrix2.cols);
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// Überprüfen, ob die Speicherreservierung erfolgreich war
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if (result.buffer == NULL)
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{
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return (Matrix){0};
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}
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// Jede Zeile der ersten Matrix durchlaufen
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for (unsigned int i = 0; i < matrix1.rows; i++)
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{
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// Jede Spalte der zweiten Matrix durchlaufen
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for (unsigned int j = 0; j < matrix2.cols; j++)
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{
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MatrixType sum = 0;
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// Summe der Produkte berechnen
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for (unsigned int k = 0; k < matrix1.cols; k++)
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{
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sum += matrix1.buffer[i * matrix1.cols + k] *
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matrix2.buffer[k * matrix2.cols + j];
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}
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// Berechneten Wert in der Ergebnismatrix speichern
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result.buffer[i * result.cols + j] = sum;
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}
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}
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return result;
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}
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}
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+1
-1
@@ -7,9 +7,9 @@ typedef float MatrixType;
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// TODO Matrixtyp definieren
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// TODO Matrixtyp definieren
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typedef struct {
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typedef struct {
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MatrixType *buffer;
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unsigned int rows;
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unsigned int rows;
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unsigned int cols;
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unsigned int cols;
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MatrixType *buffer; // Speichert die Matrixwerte in einem Array, zeigt die Speicheradresse des ersten Matrixwerts im Array
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} Matrix;
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} Matrix;
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@@ -1,12 +1,8 @@
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#include <stdlib.h>
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#include <stdlib.h>
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#include <stdio.h>
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#include <stdio.h>
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#include <string.h>
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#include <string.h>
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#define Matrix RaylibMatrix
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#include "raylib.h"
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#undef Matrix
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#include "mnistVisualization.h"
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#include "mnistVisualization.h"
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#include "raylib.h"
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#define MAX_TEXT_LEN 100
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#define MAX_TEXT_LEN 100
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@@ -17,9 +13,6 @@ typedef struct
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const unsigned char *predictions;
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const unsigned char *predictions;
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unsigned int currentIdx;
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unsigned int currentIdx;
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Vector2 pixelSize;
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Vector2 pixelSize;
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int isDrawing;
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GrayScaleImage canvas;
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NeuralNetwork model;
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} MnistVisualization;
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} MnistVisualization;
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typedef struct
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typedef struct
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@@ -62,23 +55,16 @@ static MnistVisualization *createVisualizationContainer(const GrayScaleImageSeri
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if(container != NULL)
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if(container != NULL)
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{
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{
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container->canvas.width = series->images[0].width;
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container->canvas.height = series->images[0].height;
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container->canvas.buffer = (unsigned char *)calloc(container->canvas.width * container->canvas.height, sizeof(unsigned char));
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container->model = loadModel("mnist_model.info2");
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Vector2 pixelSize = {(int)(size.x / series->images[0].width), (int)(size.y / series->images[0].height)};
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Vector2 pixelSize = {(int)(size.x / series->images[0].width), (int)(size.y / series->images[0].height)};
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container->pixelSize = pixelSize;
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container->pixelSize = pixelSize;
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container->series = series;
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container->series = series;
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container->predictions = predictions;
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container->predictions = predictions;
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container->isDrawing = 0;
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}
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}
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||||||
}
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}
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return container;
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return container;
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||||||
}
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}
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|
||||||
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|
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static void drawTextLabel(const TextLabel *label)
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static void drawTextLabel(const TextLabel *label)
|
||||||
{
|
{
|
||||||
DrawText(label->text, label->position.x, label->position.y, label->fontSize, label->color);
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DrawText(label->text, label->position.x, label->position.y, label->fontSize, label->color);
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||||||
@@ -113,11 +99,7 @@ static void drawAll(const MnistVisualization *container, const TextLabel *naviga
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|||||||
BeginDrawing();
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BeginDrawing();
|
||||||
ClearBackground(BLACK);
|
ClearBackground(BLACK);
|
||||||
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|
||||||
if (container->isDrawing) {
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|
||||||
drawDigit(container->canvas, container->position, container->pixelSize);
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|
||||||
} else {
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|
||||||
drawDigit(container->series->images[container->currentIdx], container->position, container->pixelSize);
|
drawDigit(container->series->images[container->currentIdx], container->position, container->pixelSize);
|
||||||
}
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|
||||||
drawTextLabel(navigationLabel);
|
drawTextLabel(navigationLabel);
|
||||||
drawTextLabel(predictionLabel);
|
drawTextLabel(predictionLabel);
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||||||
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|
||||||
@@ -132,10 +114,6 @@ static int checkUserInput()
|
|||||||
inputResult = -1;
|
inputResult = -1;
|
||||||
else if(IsKeyReleased(KEY_RIGHT))
|
else if(IsKeyReleased(KEY_RIGHT))
|
||||||
inputResult = 1;
|
inputResult = 1;
|
||||||
else if(IsKeyReleased(KEY_UP))
|
|
||||||
inputResult = 2;
|
|
||||||
else if(IsKeyReleased(KEY_DOWN))
|
|
||||||
inputResult = 3;
|
|
||||||
|
|
||||||
return inputResult;
|
return inputResult;
|
||||||
}
|
}
|
||||||
@@ -158,50 +136,17 @@ static void updatePredictionLabel(TextLabel *predictionLabel, unsigned char true
|
|||||||
}
|
}
|
||||||
|
|
||||||
static void update(MnistVisualization *container, TextLabel *predictionLabel, int updateDirection)
|
static void update(MnistVisualization *container, TextLabel *predictionLabel, int updateDirection)
|
||||||
{
|
|
||||||
if (updateDirection == 2)
|
|
||||||
{
|
|
||||||
container->isDrawing = !container->isDrawing;
|
|
||||||
}
|
|
||||||
else if (updateDirection == 3)
|
|
||||||
{
|
|
||||||
memset(container->canvas.buffer, 0, container->canvas.width * container->canvas.height);
|
|
||||||
}
|
|
||||||
else if (!container->isDrawing)
|
|
||||||
{
|
{
|
||||||
updateDisplayContainer(container, updateDirection);
|
updateDisplayContainer(container, updateDirection);
|
||||||
}
|
|
||||||
|
|
||||||
if (container->isDrawing == 1 && IsMouseButtonDown(MOUSE_BUTTON_LEFT))
|
|
||||||
{
|
|
||||||
int col = GetMouseX() / (int)container->pixelSize.x;
|
|
||||||
int row = GetMouseY() / (int)container->pixelSize.y;
|
|
||||||
|
|
||||||
if (col >= 0 && col < container->canvas.width && row >= 0 && row < container->canvas.height)
|
|
||||||
{
|
|
||||||
container->canvas.buffer[row * container->canvas.width + col] = 255;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
if (container->isDrawing)
|
|
||||||
{
|
|
||||||
unsigned char *liveResult = predict(container->model, &container->canvas, 1);
|
|
||||||
unsigned char predictedDigit = liveResult[0];
|
|
||||||
free(liveResult);
|
|
||||||
updatePredictionLabel(predictionLabel, 0, predictedDigit);
|
|
||||||
}
|
|
||||||
else
|
|
||||||
{
|
|
||||||
updatePredictionLabel(predictionLabel, container->series->labels[container->currentIdx], container->predictions[container->currentIdx]);
|
updatePredictionLabel(predictionLabel, container->series->labels[container->currentIdx], container->predictions[container->currentIdx]);
|
||||||
}
|
}
|
||||||
}
|
|
||||||
|
|
||||||
void showMnist(unsigned int windowWidth, unsigned int windowHeight, const GrayScaleImageSeries *series, const unsigned char predictions[])
|
void showMnist(unsigned int windowWidth, unsigned int windowHeight, const GrayScaleImageSeries *series, const unsigned char predictions[])
|
||||||
{
|
{
|
||||||
const Vector2 windowSize = {windowWidth, windowHeight};
|
const Vector2 windowSize = {windowWidth, windowHeight};
|
||||||
|
|
||||||
MnistVisualization *container = createVisualizationContainer(series, predictions, windowSize);
|
MnistVisualization *container = createVisualizationContainer(series, predictions, windowSize);
|
||||||
TextLabel *navigationLabel = createTextLabel("Use left and right key to navigate\n Use up and down key to enable free-Drawing and reset", 20, WHITE);
|
TextLabel *navigationLabel = createTextLabel("Use left and right key to navigate ...", 20, WHITE);
|
||||||
TextLabel *predictionLabel = createTextLabel("", 20, WHITE);
|
TextLabel *predictionLabel = createTextLabel("", 20, WHITE);
|
||||||
predictionLabel->position.x = 10;
|
predictionLabel->position.x = 10;
|
||||||
predictionLabel->position.y = windowSize.y - 50;
|
predictionLabel->position.y = windowSize.y - 50;
|
||||||
@@ -222,11 +167,6 @@ void showMnist(unsigned int windowWidth, unsigned int windowHeight, const GraySc
|
|||||||
|
|
||||||
CloseWindow();
|
CloseWindow();
|
||||||
|
|
||||||
if(container != NULL)
|
|
||||||
{
|
|
||||||
free(container->canvas.buffer);
|
|
||||||
clearModel(&container->model);
|
|
||||||
}
|
|
||||||
free(container);
|
free(container);
|
||||||
free(navigationLabel);
|
free(navigationLabel);
|
||||||
free(predictionLabel);
|
free(predictionLabel);
|
||||||
|
|||||||
@@ -2,7 +2,6 @@
|
|||||||
#define MNISTVISUALIZATION_H
|
#define MNISTVISUALIZATION_H
|
||||||
|
|
||||||
#include "imageInput.h"
|
#include "imageInput.h"
|
||||||
#include "neuralNetwork.h"
|
|
||||||
|
|
||||||
void showMnist(unsigned int windowWidth, unsigned int windowHeight, const GrayScaleImageSeries *series, const unsigned char predictions[]);
|
void showMnist(unsigned int windowWidth, unsigned int windowHeight, const GrayScaleImageSeries *series, const unsigned char predictions[]);
|
||||||
|
|
||||||
|
|||||||
@@ -9,39 +9,6 @@
|
|||||||
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
|
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
|
||||||
{
|
{
|
||||||
// TODO
|
// TODO
|
||||||
FILE *file = fopen(path, "wb");
|
|
||||||
if (file == NULL)
|
|
||||||
{
|
|
||||||
return;
|
|
||||||
}
|
|
||||||
|
|
||||||
const char *fileTag = "__info2_neural_network_file_format__";
|
|
||||||
fwrite(fileTag, sizeof(char), strlen(fileTag), file);
|
|
||||||
|
|
||||||
if (nn.numberOfLayers > 0)
|
|
||||||
{
|
|
||||||
fwrite(&nn.layers[0].weights.cols, sizeof(int), 1, file);
|
|
||||||
fwrite(&nn.layers[0].weights.rows, sizeof(int), 1, file);
|
|
||||||
|
|
||||||
for (unsigned int i = 0; i < nn.numberOfLayers; i++)
|
|
||||||
{
|
|
||||||
if (i > 0)
|
|
||||||
{
|
|
||||||
fwrite(&nn.layers[i].weights.rows, sizeof(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 * nn.layers[i].biases.cols, file);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
int endDimension = 0;
|
|
||||||
fwrite(&endDimension, sizeof(int), 1, file);
|
|
||||||
|
|
||||||
fclose(file);
|
|
||||||
}
|
}
|
||||||
|
|
||||||
void test_loadModelReturnsCorrectNumberOfLayers(void)
|
void test_loadModelReturnsCorrectNumberOfLayers(void)
|
||||||
|
|||||||
-110
@@ -1,110 +0,0 @@
|
|||||||
#include <stdio.h>
|
|
||||||
#include <stdlib.h>
|
|
||||||
#include <string.h>
|
|
||||||
#include "imageInput.h"
|
|
||||||
|
|
||||||
#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
|
|
||||||
|
|
||||||
/* Liest den Datei-Header sowie Anzahl und Abmessungen der Bilder. */
|
|
||||||
static int readFileHeader(FILE *file, unsigned short *count, unsigned short *width, unsigned short *height)
|
|
||||||
{
|
|
||||||
char tag[sizeof(FILE_HEADER_STRING) - 1];
|
|
||||||
|
|
||||||
return fread(tag, sizeof(tag), 1, file) == 1 &&
|
|
||||||
memcmp(tag, FILE_HEADER_STRING, sizeof(tag)) == 0 && /* vergleicht File-Header mit dem erwarteten Wert */
|
|
||||||
fread(count, sizeof(*count), 1, file) == 1 &&
|
|
||||||
fread(width, sizeof(*width), 1, file) == 1 &&
|
|
||||||
fread(height, sizeof(*height), 1, file) == 1 &&
|
|
||||||
*count > 0 && *width > 0 && *height > 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
/* Liest die Pixel und das unmittelbar folgende Label eines Bildes. */
|
|
||||||
static int readImage(FILE *file, GrayScaleImage *image, unsigned char *label, size_t pixelCount)
|
|
||||||
{
|
|
||||||
image->buffer = (GrayScalePixelType *)malloc(pixelCount);
|
|
||||||
if (image->buffer == NULL || fread(image->buffer, sizeof(*image->buffer), pixelCount, file) != pixelCount || fread(label, sizeof(*label), 1, file) != 1) /*Prüft ob Speicher korrekt reserviert wurde */
|
|
||||||
{
|
|
||||||
free(image->buffer);
|
|
||||||
image->buffer = NULL;
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
return 1;
|
|
||||||
}
|
|
||||||
|
|
||||||
/* Gibt auch bereits teilweise geladene Serien und deren Pixelpuffer frei. */
|
|
||||||
static void freeImages(GrayScaleImageSeries *series)
|
|
||||||
{
|
|
||||||
if (series == NULL) /*Prüft ob Serie übergeben Wurde*/
|
|
||||||
return;
|
|
||||||
if (series->images != NULL)
|
|
||||||
{
|
|
||||||
for (unsigned int i = 0; i < series->count; ++i) /* Prüft jedes bIld der Serie*/
|
|
||||||
free(series->images[i].buffer);
|
|
||||||
}
|
|
||||||
free(series->images);
|
|
||||||
free(series->labels);
|
|
||||||
free(series);
|
|
||||||
}
|
|
||||||
// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
|
|
||||||
GrayScaleImageSeries *readImages(const char *path)
|
|
||||||
{
|
|
||||||
GrayScaleImageSeries *series = NULL;
|
|
||||||
unsigned short count, width, height;
|
|
||||||
size_t pixelCount;
|
|
||||||
FILE *file;
|
|
||||||
|
|
||||||
if (path == NULL || (file = fopen(path, "rb")) == NULL) /*prüft ob sich Pfad öffnen lässt*/
|
|
||||||
return 0;
|
|
||||||
|
|
||||||
/* Zuerst den Header prüfen, bevor Speicher reserviert wird */
|
|
||||||
if (!readFileHeader(file, &count, &width, &height))
|
|
||||||
{
|
|
||||||
fclose(file);
|
|
||||||
freeImages(series);
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
pixelCount = (size_t)width * height;
|
|
||||||
series = (GrayScaleImageSeries *)calloc(1, sizeof(*series)); /*Speicher für Serie reservieren*/
|
|
||||||
if (series == NULL)
|
|
||||||
{
|
|
||||||
|
|
||||||
fclose(file);
|
|
||||||
freeImages(series);
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
series->count = count; /*speicher die anzahl der Bilder*/
|
|
||||||
series->images = (GrayScaleImage *)calloc(count, sizeof(*series->images));
|
|
||||||
series->labels = (unsigned char *)malloc(count * sizeof(*series->labels));
|
|
||||||
if (series->images == NULL || series->labels == NULL)
|
|
||||||
{
|
|
||||||
fclose(file);
|
|
||||||
freeImages(series);
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
/*Parameter jedes Bildes einlesen*/
|
|
||||||
for (unsigned int i = 0; i < count; ++i)
|
|
||||||
{
|
|
||||||
series->images[i].width = width;
|
|
||||||
series->images[i].height = height;
|
|
||||||
if (!readImage(file, &series->images[i], &series->labels[i], pixelCount))
|
|
||||||
{
|
|
||||||
fclose(file);
|
|
||||||
freeImages(series);
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
fclose(file);
|
|
||||||
return series;
|
|
||||||
}
|
|
||||||
|
|
||||||
void clearSeries(GrayScaleImageSeries *series)
|
|
||||||
{
|
|
||||||
freeImages(series);
|
|
||||||
}
|
|
||||||
Reference in new issue
Block a user