C++实现卷积和池化

不念不忘少年蓝@ 2023-07-18 09:21 19阅读 0赞

1、生成高斯核

Mat Gass_Kernel(float sigmma)
    {
    	Mat Kernel = Mat(Size(3, 3), CV_32FC1);
    	float val_sum = 0.f;
    	for (int i=0;i<3;i++)
    		for (int j = 0; j < 3; j++)
    		{
    			float val = exp(-((i - 3/2)*(i - 3/2) + (j - 3/2)*(j - 3/2)) / (2 * sigmma*sigmma));
    			Kernel.at<float>(i, j) = val;
    			val_sum += val;
    		}
    	cout << Kernel << endl;
    	cout << val_sum << endl;
    
    	for (int i = 0; i<3; i++)
    		for (int j = 0; j < 3; j++)
    		{
    			Kernel.at<float>(i, j) = Kernel.at<float>(i, j)/ val_sum;
    		}
    	return Kernel;
    
    }

2、卷积

Mat Conv(Mat &map, Mat & kernel)
    {
    	int new_h =int((map.rows - kernel.rows)/1)+1;
    	int new_w= int((map.cols - kernel.cols) /1) + 1;
    	Mat new_mat = Mat(Size(new_h, new_w), map.depth());
    	for (int i = 1; i < map.rows-1; i++)
    	{
    		for (int j = 1; j < map.cols - 1; j++)
    		{
    
              //卷积计算
    			float value = 0.f;
    			for (int k_i=-1 ;k_i<=1 ;k_i++)
    				for (int k_j = -1; k_j <= 1; k_j++)
    				{
    					value += kernel.at<uchar>(k_i + 1, k_j + 1)*map.at<uchar>(i + k_i, j + k_j);
    				}
    			new_mat.at<uchar>(i, j) = uchar(value);
    		}
    	}
    
    	return new_mat;
    }

3、池化

float getMax(Mat matrix, int kernel_size, int x, int y) {
    	float max_value = matrix.at<uchar>(x,y);
    	for (int i = 0; i < kernel_size; i++) {
    		for (int j = 0; j < kernel_size; j++) {
    			if (max_value < matrix.at<uchar>(x+i,y+j))
    			{
    				max_value = matrix.at<uchar>(x + i, y + j);
    			}
    		}
    	}
    	return max_value;
    }
    
    Mat Pool(Mat feat_mat,int kernel_size=3,int strides=2)
    {
    	int src_img_h = feat_mat.rows;
    	int src_img_w= feat_mat.cols;
    	int new_h = int((feat_mat.rows- kernel_size)/ strides+1);
    	int new_w = int((feat_mat.cols - kernel_size) / strides + 1);
    	printf("%d %d", new_h, new_w);
    	Mat new_mat = Mat(Size(new_h, new_w), feat_mat.depth());
    	for (int i = 0; i < new_mat.rows ; i++)
    	{
    		for (int j = 0; j < new_mat.cols; j++)
    		{
    
    			float gray_value = getMax(feat_mat, 3, i*strides, j*strides);
    			new_mat.at<uchar>(i, j) = gray_value;
    
    		}
    	}
    
    	return new_mat;
    
    
    }

4、所有代码合起来

#define _CRT_SECURE_NO_WARNINGS
    #include <iostream>
    #include <fstream>
    #include <opencv2/core/core.hpp>
    #include <opencv2/highgui/highgui.hpp>
    #include <opencv2/imgproc/imgproc.hpp>
    #include <opencv2/objdetect/objdetect.hpp>
    #include <opencv2/ml/ml.hpp>
    #include <stdlib.h>
    #include<ctime>  //时间
    #include <map>
    #include <cassert>
    #include <direct.h>
    #include <io.h>
    
    using namespace std;
    using namespace cv;
    
    Mat Conv(Mat &map, Mat & kernel)
    {
    	int new_h =int((map.rows - kernel.rows)/1)+1;
    	int new_w= int((map.cols - kernel.cols) /1) + 1;
    	Mat new_mat = Mat(Size(new_h, new_w), map.depth());
    	for (int i = 1; i < map.rows-1; i++)
    	{
    		for (int j = 1; j < map.cols - 1; j++)
    		{
    
              //卷积计算
    			float value = 0.f;
    			for (int k_i=-1 ;k_i<=1 ;k_i++)
    				for (int k_j = -1; k_j <= 1; k_j++)
    				{
    					value += kernel.at<uchar>(k_i + 1, k_j + 1)*map.at<uchar>(i + k_i, j + k_j);
    				}
    			new_mat.at<uchar>(i, j) = uchar(value);
    		}
    	}
    
    	return new_mat;
    }
    
    
    
    Mat Gass_Kernel(float sigmma)
    {
    	Mat Kernel = Mat(Size(3, 3), CV_32FC1);
    	float val_sum = 0.f;
    	for (int i=0;i<3;i++)
    		for (int j = 0; j < 3; j++)
    		{
    			float val = exp(-((i - 3/2)*(i - 3/2) + (j - 3/2)*(j - 3/2)) / (2 * sigmma*sigmma));
    			Kernel.at<float>(i, j) = val;
    			val_sum += val;
    		}
    	cout << Kernel << endl;
    	cout << val_sum << endl;
    
    	for (int i = 0; i<3; i++)
    		for (int j = 0; j < 3; j++)
    		{
    			Kernel.at<float>(i, j) = Kernel.at<float>(i, j)/ val_sum;
    		}
    	return Kernel;
    
    }
    
    
    
    float getMax(Mat matrix, int kernel_size, int x, int y) {
    	float max_value = matrix.at<uchar>(x,y);
    	for (int i = 0; i < kernel_size; i++) {
    		for (int j = 0; j < kernel_size; j++) {
    			if (max_value < matrix.at<uchar>(x+i,y+j))
    			{
    				max_value = matrix.at<uchar>(x + i, y + j);
    			}
    		}
    	}
    	return max_value;
    }
    
    Mat Pool(Mat feat_mat,int kernel_size=3,int strides=2)
    {
    	int src_img_h = feat_mat.rows;
    	int src_img_w= feat_mat.cols;
    	int new_h = int((feat_mat.rows- kernel_size)/ strides+1);
    	int new_w = int((feat_mat.cols - kernel_size) / strides + 1);
    	printf("%d %d", new_h, new_w);
    	Mat new_mat = Mat(Size(new_h, new_w), feat_mat.depth());
    	for (int i = 0; i < new_mat.rows ; i++)
    	{
    		for (int j = 0; j < new_mat.cols; j++)
    		{
    
    			float gray_value = getMax(feat_mat, 3, i*strides, j*strides);
    			new_mat.at<uchar>(i, j) = gray_value;
    
    		}
    	}
    
    	return new_mat;
    
    
    }
    int main(int argc, char *argv[])
    {
    	Mat img = imread("./1/00.jpg",0);
    	Mat save_img;
    
    	Mat Feature_map=Gass_Kernel(1);
    	save_img=Conv(img, Feature_map);
    	save_img = Conv(img, Feature_map);
    	save_img = Conv(img, Feature_map);
    	save_img = Conv(img, Feature_map);
    	Mat poolmat=Pool(save_img, 3, 2);
    	cout << Feature_map << endl;
    		
    	imwrite("tesp.jpg", poolmat);
    	system("pause");
    
    	return 0;
    }
    void main_15()
    {
    	int i, j;
    	double sigma = 1;
    	const int N = 3;
    	double gussian[N][N];
    	double sum = 0.0;
    
    	for (i = 0; i<N; i++)
    	{
    		for (j = 0; j<N; j++)
    		{
    			gussian[i][j] = exp(-((i - N / 2)*(i - N / 2) + (j - N / 2)*(j - N / 2)) / (2.0*sigma*sigma));
    		
    			printf("%f  ,", gussian[i][j]);
    
    			sum += gussian[i][j];
    		}
    	}
    	
    	cout << sum << endl;
    
    	for (i = 0; i<N; i++)
    	{
    		for (j = 0; j<N; j++)
    		{
    			gussian[i][j] = gussian[i][j] / sum;
    			printf("%f  ,", gussian[i][j]);
    		}
    		printf("\n");
    	}
    }