Compare commits
15
Commits
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fa26fbfb39 | ||
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66a9212093 | ||
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d096780389 | ||
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ae761afb00 | ||
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4486fbd82e | ||
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2f30c2d030 |
Vendored
+5
@@ -0,0 +1,5 @@
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{
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"files.associations": {
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"unity.h": "c"
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}
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}
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+1
-1
@@ -12,7 +12,7 @@ typedef struct
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typedef struct
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typedef struct
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{
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{
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GrayScaleImage *images; //in sich verschachtelte Struktur
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GrayScaleImage *images;
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unsigned char *labels;
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unsigned char *labels;
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unsigned int count;
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unsigned int count;
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} GrayScaleImageSeries;
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} GrayScaleImageSeries;
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@@ -2,20 +2,22 @@
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#include <string.h>
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#include <string.h>
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#include "matrix.h"
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#include "matrix.h"
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// TODO Matrix-Funktionen implementieren
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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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Matrix m = {NULL, 0, 0};
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Matrix matrix = {NULL, 0, 0};
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if (rows == 0 || cols == 0)
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if (rows == 0 || cols == 0)
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return m;
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return matrix; //gibt leere Matrix zurück
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m.buffer = (MatrixType *)calloc(rows * cols, sizeof(MatrixType));
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matrix.buffer = (MatrixType *)calloc(rows * cols, sizeof(MatrixType));
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if (m.buffer == NULL)
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if (matrix.buffer == NULL) //auf verfügbaren Speicherplatz prüfen
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return m;
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return matrix;
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m.rows = rows;
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matrix.rows = rows;
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m.cols = cols;
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matrix.cols = cols;
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return m;
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return matrix; //Matrix zurückgeben
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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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@@ -23,18 +25,18 @@ void clearMatrix(Matrix *matrix)
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if (matrix != NULL)
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if (matrix != NULL)
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{
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{
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free(matrix->buffer);
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free(matrix->buffer); //Speicherplatz bereinigen
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matrix->buffer = NULL;
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matrix->buffer = NULL; //Werte auf 0 setzen
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matrix->rows = 0;
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matrix->rows = 0;
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matrix->cols = 0;
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matrix->cols = 0;
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}
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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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// Matrix matrix zu Matrix *matrix, empfehlung
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{
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{
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if (rowIdx < matrix.rows && colIdx < matrix.cols && matrix.buffer != NULL)
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if (rowIdx < matrix.rows && colIdx < matrix.cols && matrix.buffer != NULL) //Prüft ob Zugriff möglich
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matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
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matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
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//schreibt 2D element in 1D Liste: Element_Reihe*Matrix_Spalten + Element_Spalte
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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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@@ -45,11 +47,10 @@ MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int co
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}
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}
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// TODO: Funktionen implementieren
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// TODO: Funktionen implementieren
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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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// check, equal rows
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// immer Probe, gleiche Zeilen der Matrizen
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// "Elementweise Addition": test, if two matrix has exact size
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// "Elementweise Addition": Probe, ob matrix gleiche größe hat
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if (matrix1.rows == matrix2.rows && matrix1.cols == matrix2.cols)
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if (matrix1.rows == matrix2.rows && matrix1.cols == matrix2.cols)
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{
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{
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Matrix result_add = createMatrix(matrix1.rows, matrix1.cols);
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Matrix result_add = createMatrix(matrix1.rows, matrix1.cols);
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@@ -64,7 +65,7 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
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}
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}
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return result_add;
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return result_add;
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}
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}
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// "Broadcasting": matrix1 has 1 collum
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// "Broadcasting": matrix1 hat 1 Spalte
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if (matrix1.rows == matrix2.rows && matrix1.cols == 1)
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if (matrix1.rows == matrix2.rows && matrix1.cols == 1)
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{
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{
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Matrix result_add = createMatrix(matrix1.rows, matrix2.cols);
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Matrix result_add = createMatrix(matrix1.rows, matrix2.cols);
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@@ -78,7 +79,7 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
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}
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}
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return result_add;
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return result_add;
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}
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}
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// "Broadcasting": matrix2 has 1 collum
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// "Broadcasting": matrix2 hat 1 Spalte
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if (matrix1.rows == matrix2.rows && matrix2.cols == 1)
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if (matrix1.rows == matrix2.rows && matrix2.cols == 1)
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{
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{
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Matrix result_add = createMatrix(matrix1.rows, matrix1.cols);
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Matrix result_add = createMatrix(matrix1.rows, matrix1.cols);
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@@ -98,13 +99,14 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
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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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// Needed: rows/Zeilen, collums/Spalten
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MatrixType buffer_add;
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MatrixType buffer_add;
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// Probe ob Spalten1 = Zeilen2
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if (matrix1.cols != matrix2.rows)
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if (!matrix1.buffer || !matrix2.buffer) // Probe ob leere Matrize vorliegt
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return createMatrix(0, 0);
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if (matrix1.cols != matrix2.rows) // Probe ob Spalten1 = Zeilen2
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return createMatrix(0, 0);
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return createMatrix(0, 0);
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Matrix result_mul = createMatrix(matrix1.rows, matrix2.cols); // ""
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Matrix result_mul = createMatrix(matrix1.rows, matrix2.cols);
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for (unsigned int index = 0; index < matrix1.rows; index++)
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for (unsigned int index = 0; index < matrix1.rows; index++)
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{
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{
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@@ -113,12 +115,10 @@ Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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buffer_add = 0;
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buffer_add = 0;
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for (unsigned int skalar = 0; skalar < matrix1.cols; skalar++)
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for (unsigned int skalar = 0; skalar < matrix1.cols; skalar++)
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{
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{
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// buffer_add += matrix1[index][skalar]*matrix2[skalar][shift];
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buffer_add += getMatrixAt(matrix1, index, skalar) * getMatrixAt(matrix2, skalar, shift);
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buffer_add += getMatrixAt(matrix1, index, skalar) * getMatrixAt(matrix2, skalar, shift);
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}
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}
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// matrix_mul[index][shift] = buffer_add;
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setMatrixAt(buffer_add, result_mul, index, shift);
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setMatrixAt(buffer_add, result_mul, index, shift); // result als Pointer, also mit &result
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}
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}
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}
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}
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return result_mul;
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return result_mul;
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}
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}
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@@ -7,10 +7,10 @@ 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 *matrix;
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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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}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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+46
-1
@@ -8,7 +8,52 @@
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static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
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static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
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{
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{
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// TODO
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FILE *file = fopen(path, "wb");
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if (!file)
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{
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return;
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}
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// Schreibe den Datei-Tag
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const char *tag = "info2_neural_network_file_format";
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fwrite(tag, 1, strlen(tag), file);
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// Überprüfe, ob es Layer gibt
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if (nn.numberOfLayers == 0)
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{
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fclose(file);
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return;
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}
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// Schreibe die Eingabe- und Ausgabegrößen des Netzwerks
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int input = nn.layers[0].weights.cols;
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int output = nn.layers[0].weights.rows;
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fwrite(&input, sizeof(int), 1, file);
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fwrite(&output, sizeof(int), 1, file);
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// Schreibe die Layer-Daten
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for (int i = 0; i < nn.numberOfLayers; i++)
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{
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const Layer *layer = &nn.layers[i];
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int out = layer->weights.rows;
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int in = layer->weights.cols;
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fwrite(layer->weights.buffer, sizeof(MatrixType), out * in, file);
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fwrite(layer->biases.buffer, sizeof(MatrixType), out * 1, file);
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if (i + 1 < nn.numberOfLayers)
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{
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int nextOut = nn.layers[i + 1].weights.rows;
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fwrite(&nextOut, sizeof(int), 1, file);
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}
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}
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fclose(file);
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}
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}
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void test_loadModelReturnsCorrectNumberOfLayers(void)
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void test_loadModelReturnsCorrectNumberOfLayers(void)
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Reference in New Issue
Block a user