forked from freudenreichan/info2Praktikum-NeuronalesNetz
Merge branch 'main' of https://git.efi.th-nuernberg.de/gitea/kachelto100370/info2Praktikum-NeuronalesNetz into RMax
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5fcc3cd042
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@ -7,16 +7,23 @@
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#define FILE_HEADER_STRING "__info2_image_file_format__"
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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 Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
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GrayScaleImage readImage()
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{
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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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FILE *file = fopen("mnist_test.info2","rb");
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char headOfFile;
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series = malloc();
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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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// 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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}
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}
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6
matrix.h
6
matrix.h
@ -6,12 +6,14 @@
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typedef float MatrixType;
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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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{
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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 *data; //Zeiger auf Speicher (Reihen*Spalten)
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MatrixType *data;
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} Matrix;
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} Matrix;
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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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void clearMatrix(Matrix *matrix);
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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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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
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@ -71,6 +71,32 @@ void test_addFailsOnDifferentInputDimensions(void)
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TEST_ASSERT_EQUAL_UINT32(0, result.cols);
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TEST_ASSERT_EQUAL_UINT32(0, result.cols);
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}
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}
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void test_addSupportsBroadcasting(void)
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{
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MatrixType buffer1[] = {1, 2, 3, 4, 5, 6};
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MatrixType buffer2[] = {7, 8};
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Matrix matrix1 = {.rows=2, .cols=3, .buffer=buffer1};
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Matrix matrix2 = {.rows=2, .cols=1, .buffer=buffer2};
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Matrix result1 = add(matrix1, matrix2);
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Matrix result2 = add(matrix2, matrix1);
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float expectedResults[] = {8, 9, 10, 12, 13, 14};
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TEST_ASSERT_EQUAL_UINT32(matrix1.rows, result1.rows);
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TEST_ASSERT_EQUAL_UINT32(matrix1.cols, result1.cols);
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TEST_ASSERT_EQUAL_UINT32(matrix1.rows, result2.rows);
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TEST_ASSERT_EQUAL_UINT32(matrix1.cols, result2.cols);
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TEST_ASSERT_EQUAL_INT(sizeof(expectedResults)/sizeof(expectedResults[0]), result1.rows * result1.cols);
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TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, result1.buffer, result1.cols * result1.rows);
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TEST_ASSERT_EQUAL_INT(sizeof(expectedResults)/sizeof(expectedResults[0]), result2.rows * result2.cols);
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TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, result2.buffer, result2.cols * result2.rows);
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free(result1.buffer);
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free(result2.buffer);
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}
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void test_multiplyReturnsCorrectResults(void)
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void test_multiplyReturnsCorrectResults(void)
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{
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{
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MatrixType buffer1[] = {1, 2, 3, 4, 5, 6};
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MatrixType buffer1[] = {1, 2, 3, 4, 5, 6};
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@ -138,7 +164,7 @@ void test_setMatrixAtFailsOnIndicesOutOfRange(void)
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Matrix matrixToTest = {.rows=2, .cols=3, .buffer=buffer};
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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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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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}
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void setUp(void) {
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void setUp(void) {
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@ -159,6 +185,7 @@ int main()
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RUN_TEST(test_clearMatrixSetsMembersToNull);
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RUN_TEST(test_clearMatrixSetsMembersToNull);
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RUN_TEST(test_addReturnsCorrectResult);
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RUN_TEST(test_addReturnsCorrectResult);
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RUN_TEST(test_addFailsOnDifferentInputDimensions);
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RUN_TEST(test_addFailsOnDifferentInputDimensions);
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RUN_TEST(test_addSupportsBroadcasting);
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RUN_TEST(test_multiplyReturnsCorrectResults);
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RUN_TEST(test_multiplyReturnsCorrectResults);
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RUN_TEST(test_multiplyFailsOnWrongInputDimensions);
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RUN_TEST(test_multiplyFailsOnWrongInputDimensions);
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RUN_TEST(test_getMatrixAtReturnsCorrectResult);
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RUN_TEST(test_getMatrixAtReturnsCorrectResult);
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29
neuralN_readFiles
Normal file
29
neuralN_readFiles
Normal file
@ -0,0 +1,29 @@
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Inhalte: Dynamische Speicherverwaltung, Strukturen, Dateien lesen.
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Ziel: Die Bilder aus mnist_test.info 2 auslesen
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Struktur für einlesen des Strings am Anfang der Datei:
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int AnzahlBilder
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int breiteBilder
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int LaengeBilder
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Struktur für Bilder:
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unsinged int array Breite * Höhe
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unsigned int Klasse (Label 0 - 9)
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Speicher für Bilder dynamisch allokieren
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GrayScaleImageSeries:
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datei einlesen
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header String aus der Datei lesen
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mit header String den benötigten Speicher freigeben
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in den Speicher die Datei einschreiben (mit Hilfsfunktion)
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Hilfsfunktion (saveFile)
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gehe zum Anfang des Strings
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speicher alles der Reihe nach ein
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clearSeries:
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pointer der be malloc kommt nehemen
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free()
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