From c6f9776cd73f80b56746f76f54302335bd6c6f6e Mon Sep 17 00:00:00 2001 From: Benedikt Date: Tue, 25 Nov 2025 10:48:36 +0100 Subject: [PATCH] Fertisch --- imageInputTests.c | 59 +++++++++++++++----- matrix.h | 4 +- neuralNetwork.c | 2 +- neuralNetworkTests.c | 127 ++++++++++++++++++++++++++++--------------- 4 files changed, 131 insertions(+), 61 deletions(-) diff --git a/imageInputTests.c b/imageInputTests.c index 03240ab..f9922c1 100644 --- a/imageInputTests.c +++ b/imageInputTests.c @@ -1,41 +1,43 @@ - #include #include #include #include "unity.h" #include "imageInput.h" - static void prepareImageFile(const char *path, unsigned short int width, unsigned short int height, unsigned int short numberOfImages, unsigned char label) { FILE *file = fopen(path, "wb"); - if(file != NULL) + if (file != NULL) { const char *fileTag = "__info2_image_file_format__"; - GrayScalePixelType *zeroBuffer = (GrayScalePixelType *)calloc(numberOfImages * width * height, sizeof(GrayScalePixelType)); + GrayScalePixelType *buffer = (GrayScalePixelType *)calloc(numberOfImages * width * height, sizeof(GrayScalePixelType)); - if(zeroBuffer != NULL) + if (buffer != NULL) { - fwrite(fileTag, sizeof(fileTag[0]), strlen(fileTag), file); + for (int i = 0; i < width * height; i++) + { + buffer[i] = (GrayScalePixelType)i; // füllen des buffers mit Graustufen des Pixel für Test + } + + fwrite(fileTag, 1, strlen(fileTag), file); fwrite(&numberOfImages, sizeof(numberOfImages), 1, file); fwrite(&width, sizeof(width), 1, file); fwrite(&height, sizeof(height), 1, file); - for(int i = 0; i < numberOfImages; i++) + for (int i = 0; i < numberOfImages; i++) { - fwrite(zeroBuffer, sizeof(GrayScalePixelType), width * height, file); + fwrite(buffer, sizeof(GrayScalePixelType), width * height, file); fwrite(&label, sizeof(unsigned char), 1, file); } - free(zeroBuffer); + free(buffer); } fclose(file); } } - void test_readImagesReturnsCorrectNumberOfImages(void) { GrayScaleImageSeries *series = NULL; @@ -92,7 +94,8 @@ void test_readImagesReturnsCorrectLabels(void) TEST_ASSERT_NOT_NULL(series); TEST_ASSERT_NOT_NULL(series->labels); TEST_ASSERT_EQUAL_UINT16(2, series->count); - for (int i = 0; i < 2; i++) { + for (int i = 0; i < 2; i++) + { TEST_ASSERT_EQUAL_UINT8(expectedLabel, series->labels[i]); } clearSeries(series); @@ -110,7 +113,7 @@ void test_readImagesFailsOnWrongFileTag(void) { const char *path = "testFile.info2"; FILE *file = fopen(path, "w"); - if(file != NULL) + if (file != NULL) { fprintf(file, "some_tag "); fclose(file); @@ -119,18 +122,43 @@ void test_readImagesFailsOnWrongFileTag(void) remove(path); } -void setUp(void) { +// Test der Hilfsfunktionen + +void test_read_GrayScale_Pixel(void) +{ + GrayScaleImageSeries *series = NULL; + const char *path = "testFile.info2"; + + prepareImageFile(path, 8, 8, 1, 1); + series = readImages(path); + + TEST_ASSERT_NOT_NULL(series); + TEST_ASSERT_NOT_NULL(series->images); + TEST_ASSERT_EQUAL_UINT16(1, series->count); + + for (int i = 0; i < (8 * 8); i++) + { + TEST_ASSERT_EQUAL_UINT8((GrayScalePixelType)i, series->images->buffer[i]); + } + + clearSeries(series); + remove(path); +} + +void setUp(void) +{ // Falls notwendig, kann hier Vorbereitungsarbeit gemacht werden } -void tearDown(void) { +void tearDown(void) +{ // Hier kann Bereinigungsarbeit nach jedem Test durchgeführt werden } int main() { UNITY_BEGIN(); - + printf("\n============================\nImage input tests\n============================\n"); RUN_TEST(test_readImagesReturnsCorrectNumberOfImages); RUN_TEST(test_readImagesReturnsCorrectImageWidth); @@ -138,6 +166,7 @@ int main() RUN_TEST(test_readImagesReturnsCorrectLabels); RUN_TEST(test_readImagesReturnsNullOnNotExistingPath); RUN_TEST(test_readImagesFailsOnWrongFileTag); + RUN_TEST(test_read_GrayScale_Pixel); return UNITY_END(); } \ No newline at end of file diff --git a/matrix.h b/matrix.h index fb9adb1..ef1c420 100644 --- a/matrix.h +++ b/matrix.h @@ -11,8 +11,8 @@ typedef struct Matrix { unsigned int rows; unsigned int cols; - MatrixType *data; - #define buffer data + MatrixType *buffer; + } Matrix; diff --git a/neuralNetwork.c b/neuralNetwork.c index bd8f164..30e6e4f 100644 --- a/neuralNetwork.c +++ b/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}; if(count > 0 && images != NULL) { diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c index 21ab370..01c9af6 100644 --- a/neuralNetworkTests.c +++ b/neuralNetworkTests.c @@ -5,10 +5,49 @@ #include "unity.h" #include "neuralNetwork.h" - static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) { - // TODO + FILE *f = fopen(path, "wb"); + if (!f) return; + + const char *tag = "__info2_neural_network_file_format__"; + fwrite(tag, 1, strlen(tag), f); + + if (nn.numberOfLayers == 0) { + fclose(f); + return; + } // In localmodel Struktur Testdateu aufruf: + // Header --> Input Dim --> Output Dim + // i. Layer weights --> biases --> nächste Dim + + + int input = nn.layers[0].weights.cols; + int output = nn.layers[0].weights.rows; + + fwrite(&input, sizeof(int), 1, f); + fwrite(&output, sizeof(int), 1, f); + + for (int i = 0; i < nn.numberOfLayers; i++) + { + const Layer *layer = &nn.layers[i]; + int out = layer->weights.rows; + int in = layer->weights.cols; + + + fwrite(layer->weights.buffer, sizeof(MatrixType), out * in, f); + + + fwrite(layer->biases.buffer, sizeof(MatrixType), out * 1, f); + + + if (i + 1 < nn.numberOfLayers) + { + int nextOut = nn.layers[i + 1].weights.rows; + fwrite(&nextOut, sizeof(int), 1, f); + } + } + + fclose(f); } void test_loadModelReturnsCorrectNumberOfLayers(void) @@ -16,15 +55,15 @@ void test_loadModelReturnsCorrectNumberOfLayers(void) const char *path = "some__nn_test_file.info2"; MatrixType buffer1[] = {1, 2, 3, 4, 5, 6}; MatrixType buffer2[] = {1, 2, 3, 4, 5, 6}; - Matrix weights1 = {.buffer=buffer1, .rows=3, .cols=2}; - Matrix weights2 = {.buffer=buffer2, .rows=2, .cols=3}; + Matrix weights1 = {.buffer = buffer1, .rows = 3, .cols = 2}; + Matrix weights2 = {.buffer = buffer2, .rows = 2, .cols = 3}; MatrixType buffer3[] = {1, 2, 3}; MatrixType buffer4[] = {1, 2}; - Matrix biases1 = {.buffer=buffer3, .rows=3, .cols=1}; - Matrix biases2 = {.buffer=buffer4, .rows=2, .cols=1}; - Layer layers[] = {{.weights=weights1, .biases=biases1}, {.weights=weights2, .biases=biases2}}; + Matrix biases1 = {.buffer = buffer3, .rows = 3, .cols = 1}; + Matrix biases2 = {.buffer = buffer4, .rows = 2, .cols = 1}; + Layer layers[] = {{.weights = weights1, .biases = biases1}, {.weights = weights2, .biases = biases2}}; - NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=2}; + NeuralNetwork expectedNet = {.layers = layers, .numberOfLayers = 2}; NeuralNetwork netUnderTest; prepareNeuralNetworkFile(path, expectedNet); @@ -40,12 +79,12 @@ void test_loadModelReturnsCorrectWeightDimensions(void) { const char *path = "some__nn_test_file.info2"; MatrixType weightBuffer[] = {1, 2, 3, 4, 5, 6}; - Matrix weights = {.buffer=weightBuffer, .rows=3, .cols=2}; + Matrix weights = {.buffer = weightBuffer, .rows = 3, .cols = 2}; MatrixType biasBuffer[] = {7, 8, 9}; - Matrix biases = {.buffer=biasBuffer, .rows=3, .cols=1}; - Layer layers[] = {{.weights=weights, .biases=biases}}; + Matrix biases = {.buffer = biasBuffer, .rows = 3, .cols = 1}; + Layer layers[] = {{.weights = weights, .biases = biases}}; - NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=1}; + NeuralNetwork expectedNet = {.layers = layers, .numberOfLayers = 1}; NeuralNetwork netUnderTest; prepareNeuralNetworkFile(path, expectedNet); @@ -63,12 +102,12 @@ void test_loadModelReturnsCorrectBiasDimensions(void) { const char *path = "some__nn_test_file.info2"; MatrixType weightBuffer[] = {1, 2, 3, 4, 5, 6}; - Matrix weights = {.buffer=weightBuffer, .rows=3, .cols=2}; + Matrix weights = {.buffer = weightBuffer, .rows = 3, .cols = 2}; MatrixType biasBuffer[] = {7, 8, 9}; - Matrix biases = {.buffer=biasBuffer, .rows=3, .cols=1}; - Layer layers[] = {{.weights=weights, .biases=biases}}; + Matrix biases = {.buffer = biasBuffer, .rows = 3, .cols = 1}; + Layer layers[] = {{.weights = weights, .biases = biases}}; - NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=1}; + NeuralNetwork expectedNet = {.layers = layers, .numberOfLayers = 1}; NeuralNetwork netUnderTest; prepareNeuralNetworkFile(path, expectedNet); @@ -86,12 +125,12 @@ void test_loadModelReturnsCorrectWeights(void) { const char *path = "some__nn_test_file.info2"; MatrixType weightBuffer[] = {1, 2, 3, 4, 5, 6}; - Matrix weights = {.buffer=weightBuffer, .rows=3, .cols=2}; + Matrix weights = {.buffer = weightBuffer, .rows = 3, .cols = 2}; MatrixType biasBuffer[] = {7, 8, 9}; - Matrix biases = {.buffer=biasBuffer, .rows=3, .cols=1}; - Layer layers[] = {{.weights=weights, .biases=biases}}; + Matrix biases = {.buffer = biasBuffer, .rows = 3, .cols = 1}; + Layer layers[] = {{.weights = weights, .biases = biases}}; - NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=1}; + NeuralNetwork expectedNet = {.layers = layers, .numberOfLayers = 1}; NeuralNetwork netUnderTest; prepareNeuralNetworkFile(path, expectedNet); @@ -111,12 +150,12 @@ void test_loadModelReturnsCorrectBiases(void) { const char *path = "some__nn_test_file.info2"; MatrixType weightBuffer[] = {1, 2, 3, 4, 5, 6}; - Matrix weights = {.buffer=weightBuffer, .rows=3, .cols=2}; + Matrix weights = {.buffer = weightBuffer, .rows = 3, .cols = 2}; MatrixType biasBuffer[] = {7, 8, 9}; - Matrix biases = {.buffer=biasBuffer, .rows=3, .cols=1}; - Layer layers[] = {{.weights=weights, .biases=biases}}; + Matrix biases = {.buffer = biasBuffer, .rows = 3, .cols = 1}; + Layer layers[] = {{.weights = weights, .biases = biases}}; - NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=1}; + NeuralNetwork expectedNet = {.layers = layers, .numberOfLayers = 1}; NeuralNetwork netUnderTest; prepareNeuralNetworkFile(path, expectedNet); @@ -138,7 +177,7 @@ void test_loadModelFailsOnWrongFileTag(void) NeuralNetwork netUnderTest; FILE *file = fopen(path, "wb"); - if(file != NULL) + if (file != NULL) { const char *fileTag = "info2_neural_network_file_format"; @@ -159,12 +198,12 @@ void test_clearModelSetsMembersToNull(void) { const char *path = "some__nn_test_file.info2"; MatrixType weightBuffer[] = {1, 2, 3, 4, 5, 6}; - Matrix weights = {.buffer=weightBuffer, .rows=3, .cols=2}; + Matrix weights = {.buffer = weightBuffer, .rows = 3, .cols = 2}; MatrixType biasBuffer[] = {7, 8, 9}; - Matrix biases = {.buffer=biasBuffer, .rows=3, .cols=1}; - Layer layers[] = {{.weights=weights, .biases=biases}}; + Matrix biases = {.buffer = biasBuffer, .rows = 3, .cols = 1}; + Layer layers[] = {{.weights = weights, .biases = biases}}; - NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=1}; + NeuralNetwork expectedNet = {.layers = layers, .numberOfLayers = 1}; NeuralNetwork netUnderTest; prepareNeuralNetworkFile(path, expectedNet); @@ -181,7 +220,7 @@ void test_clearModelSetsMembersToNull(void) static void someActivation(Matrix *matrix) { - for(int i = 0; i < matrix->rows * matrix->cols; i++) + for (int i = 0; i < matrix->rows * matrix->cols; i++) { matrix->buffer[i] = fabs(matrix->buffer[i]); } @@ -192,23 +231,23 @@ void test_predictReturnsCorrectLabels(void) const unsigned char expectedLabels[] = {4, 2}; GrayScalePixelType imageBuffer1[] = {10, 30, 25, 17}; GrayScalePixelType imageBuffer2[] = {20, 40, 10, 128}; - GrayScaleImage inputImages[] = {{.buffer=imageBuffer1, .width=2, .height=2}, {.buffer=imageBuffer2, .width=2, .height=2}}; + GrayScaleImage inputImages[] = {{.buffer = imageBuffer1, .width = 2, .height = 2}, {.buffer = imageBuffer2, .width = 2, .height = 2}}; MatrixType weightsBuffer1[] = {1, -2, 3, -4, 5, -6, 7, -8}; MatrixType weightsBuffer2[] = {-9, 10, 11, 12, 13, 14}; MatrixType weightsBuffer3[] = {-15, 16, 17, 18, -19, 20, 21, 22, 23, -24, 25, 26, 27, -28, -29}; - Matrix weights1 = {.buffer=weightsBuffer1, .rows=2, .cols=4}; - Matrix weights2 = {.buffer=weightsBuffer2, .rows=3, .cols=2}; - Matrix weights3 = {.buffer=weightsBuffer3, .rows=5, .cols=3}; + Matrix weights1 = {.buffer = weightsBuffer1, .rows = 2, .cols = 4}; + Matrix weights2 = {.buffer = weightsBuffer2, .rows = 3, .cols = 2}; + Matrix weights3 = {.buffer = weightsBuffer3, .rows = 5, .cols = 3}; MatrixType biasBuffer1[] = {200, 0}; MatrixType biasBuffer2[] = {0, -100, 0}; MatrixType biasBuffer3[] = {0, -1000, 0, 2000, 0}; - Matrix biases1 = {.buffer=biasBuffer1, .rows=2, .cols=1}; - Matrix biases2 = {.buffer=biasBuffer2, .rows=3, .cols=1}; - Matrix biases3 = {.buffer=biasBuffer3, .rows=5, .cols=1}; - Layer layers[] = {{.weights=weights1, .biases=biases1, .activation=someActivation}, \ - {.weights=weights2, .biases=biases2, .activation=someActivation}, \ - {.weights=weights3, .biases=biases3, .activation=someActivation}}; - NeuralNetwork netUnderTest = {.layers=layers, .numberOfLayers=3}; + Matrix biases1 = {.buffer = biasBuffer1, .rows = 2, .cols = 1}; + Matrix biases2 = {.buffer = biasBuffer2, .rows = 3, .cols = 1}; + Matrix biases3 = {.buffer = biasBuffer3, .rows = 5, .cols = 1}; + Layer layers[] = {{.weights = weights1, .biases = biases1, .activation = someActivation}, + {.weights = weights2, .biases = biases2, .activation = someActivation}, + {.weights = weights3, .biases = biases3, .activation = someActivation}}; + NeuralNetwork netUnderTest = {.layers = layers, .numberOfLayers = 3}; unsigned char *predictedLabels = predict(netUnderTest, inputImages, 2); TEST_ASSERT_NOT_NULL(predictedLabels); int n = (int)(sizeof(expectedLabels) / sizeof(expectedLabels[0])); @@ -216,11 +255,13 @@ void test_predictReturnsCorrectLabels(void) free(predictedLabels); } -void setUp(void) { +void setUp(void) +{ // Falls notwendig, kann hier Vorbereitungsarbeit gemacht werden } -void tearDown(void) { +void tearDown(void) +{ // Hier kann Bereinigungsarbeit nach jedem Test durchgeführt werden }