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Никоноров И.Д. ЛР№2 Линейная фильтрация изображений (горизонтальное разбиение). Ядро Гаусса 3x3. OpenMP #152

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Никоноров И.Д. ЛР№2 Линейная фильтрация изображений (горизонтальное разбиение). Ядро Гаусса 3x3. OpenMP #152

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9137352
finished
Oct 13, 2019
0f4dded
Uploaded correct files
Oct 13, 2019
91915e7
f
Oct 13, 2019
00b2853
Release + Wtime + cmd-input of size
Oct 18, 2019
cd5a038
Right directory this time
Oct 19, 2019
74b918f
There's lab2 in this folder
Nov 16, 2019
f397528
Gaussian filter
Mar 20, 2020
ee4f994
Gaussian_filter + time
Mar 21, 2020
4ca59e4
OpenMP version of Gaussian filter
Apr 19, 2020
f35aec0
Очистил ветку OpenMP
May 17, 2020
8fbf4f4
Внёс коррективы в OpenMP версию в соответствие с замечаниями, добавил…
May 21, 2020
e074b4d
Добавлена функция сравнения картинок, полученных последовательным код…
May 31, 2020
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151 changes: 151 additions & 0 deletions 1706-4/nikonorov_id/Gauss_OpenMP/Gauss/Gauss.vcxproj
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176 changes: 176 additions & 0 deletions 1706-4/nikonorov_id/Gauss_OpenMP/Gauss/Source.cpp
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#include <iostream>
#include <ctime>
#include <iomanip>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <omp.h>
#include <chrono>

using namespace cv;
using namespace std;
#define M_PI 3.14159265358979323846

int Clamp(int value, int min, int max)
{
if (value < min)
return min;

if (value > max)
return max;

return value;
}

void deletekernel(double* kernel, int k) {

delete [] kernel;
}

//-------------------------------------------------------------//
//-------------------------------------------------------------//
//-------------------------------------------------------------//
//-------------------------------------------------------------//
//-------------------------------------------------------------//

double* createKernel(int rows, int cols) {
int tmp = rows * cols;
double* mas;
mas = new double[tmp];
return mas;
}
void InitKern(double* kernel, int k, double sigma)
{
int radius = (k / 2);
double sum = 0.0;
double tmp = 1 / (2 * M_PI * sigma * sigma);
int step = radius;

for (int i = -radius; i <= radius; i++)
{
for (int j = -radius; j <= radius; j++)
{
kernel[j + step] = tmp * exp(-(i * i + j * j) / (2 * sigma * sigma));
sum += kernel[j + step];
}
step += k;
}

for (int i = 0; i < k * k; i++)
{
kernel[i] /= sum;
}
}

void OpenMP_Gauss(const Mat& input, Mat& output, double* kernel, int kern_size, int thread_nums)
{
int radius = int(kern_size / 2);
#pragma omp parallel for num_threads(thread_nums)
for (int i = 1; i < input.rows; i++) {
for (int j = 1; j < input.cols; j++) {
double tmp = 0.0;
for (int l = -radius; l <= radius; l++) {
for (int w = -radius; w <= radius; w++) {
int idX = Clamp(i + l, 0, input.rows - 1);
int idY = Clamp(j + w, 0, input.cols - 1);
tmp += double(input.at<uchar>(idX, idY)) * kernel[l + w + 2 * (l + 2)];
}
}
output.at<uchar>(i, j) = int(tmp);

}
}
}

void Sequential_Gauss(const Mat& input, Mat& output, double* kernel, int kern_size)
{
int radius = int(kern_size / 2);
for (int i = 1; i < input.rows; i++) {
for (int j = 1; j < input.cols; j++) {
double tmp = 0.0;
for (int l = -radius; l <= radius; l++) {
for (int w = -radius; w <= radius; w++) {
int idX = Clamp(i + l, 0, input.rows - 1);
int idY = Clamp(j + w, 0, input.cols - 1);
tmp += double(input.at<uchar>(idX, idY)) * kernel[l + w + 2 * (l + 2)];
}
}
output.at<uchar>(i, j) = int(tmp);

}
}
}

bool check(const Mat& image1, const Mat& image2)
{
Mat res;
bitwise_xor(image1, image2, res);
if (countNonZero(res) > 0)
return false;

else
return true;

}

int main(int argc, char** argv) {
string orig_image_path;
string result_image_path;
int thread_nums;
if (argc < 4)
{
orig_image_path += "pic.jpg";
result_image_path += "result.jpg";
thread_nums = 6;
}
else
{
orig_image_path += argv[1];
result_image_path += argv[2];
}

Mat original_image;
original_image = imread(orig_image_path, IMREAD_COLOR);

if (original_image.empty())
{
cout << "No image data" << endl;
return -1;
}
Mat gray_image;
Mat seq_result;
Mat OpenMP_result;
cvtColor(original_image, gray_image, COLOR_BGR2GRAY);
cvtColor(original_image, seq_result, COLOR_BGR2GRAY);
cvtColor(original_image, OpenMP_result, COLOR_BGR2GRAY);

int k = 3;

double* kernel;
kernel = createKernel(k, k);
InitKern(kernel, k, 7);

auto begin = std::chrono::steady_clock::now();
OpenMP_Gauss(gray_image, seq_result, kernel, k, thread_nums);
auto end = std::chrono::steady_clock::now();
auto elapsed_ms = std::chrono::duration_cast<std::chrono::milliseconds>(end - begin);
cout << "The OpenMP time is: " << elapsed_ms.count() << " ms" << endl;

auto s_begin = std::chrono::steady_clock::now();
Sequential_Gauss(gray_image, OpenMP_result, kernel, k);
auto s_end = std::chrono::steady_clock::now();
auto s_elapsed_ms = std::chrono::duration_cast<std::chrono::milliseconds>(s_end - s_begin);
cout << "The sequential time is: " << s_elapsed_ms.count() << " ms" << endl;

if (check(seq_result, OpenMP_result))
{
imwrite(result_image_path, OpenMP_result);
namedWindow("my_result", WINDOW_AUTOSIZE);
namedWindow("Gray image", WINDOW_AUTOSIZE);
imshow("my_result", OpenMP_result);
imshow("Gray image", gray_image);
waitKey(0);
}
deletekernel(kernel, k);
return 0;
}