C++实现卷积和池化

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");
	}
}