#include <iostream>
#include <vector>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include<opencv2/nonfree/nonfree.hpp>
#include<opencv2\legacy\legacy.hpp> 
#include "matcher.h"
using namespace std;
using namespace cv;
int main()
{
// Read input images讀入圖像
cv::Mat image1= cv::imread("parliament1.bmp",0);
cv::Mat image2= cv::imread("parliament2.bmp",0);
if (!image1.data || !image2.data)
return 0; 


  // Display the images顯示圖像
cv::namedWindow("Image 1");
cv::imshow("Image 1",image1);
cv::namedWindow("Image 2");
cv::imshow("Image 2",image2);


// Prepare the matcher準(zhǔn)備匹配
RobustMatcher rmatcher;
rmatcher.setConfidenceLevel(0.98);
rmatcher.setMinDistanceToEpipolar(1.0);
rmatcher.setRatio(0.65f);
cv::Ptr<cv::FeatureDetector> pfd= new cv::SurfFeatureDetector(10); 
rmatcher.setFeatureDetector(pfd);


// Match the two images
std::vector<cv::DMatch> matches;
std::vector<cv::KeyPoint> keypoints1, keypoints2;
cv::Mat fundemental= rmatcher.match(image1,image2,matches, keypoints1, keypoints2);


// draw the matches畫匹配結(jié)果
cv::Mat imageMatches;
cv::drawMatches(image1,keypoints1, // 1st image and its keypoints第一張圖像及其關(guān)鍵點
      image2,keypoints2, // 2nd image and its keypoints第二張圖像及其關(guān)鍵點
matches, // the matches匹配結(jié)果
imageMatches, // the image produced產(chǎn)生的圖像
cv::Scalar(255,255,255)); // color of the lines線的顏色
cv::namedWindow("Matches");
cv::imshow("Matches",imageMatches);

// Convert keypoints into Point2f將關(guān)鍵點轉(zhuǎn)換為Point2f
std::vector<cv::Point2f> points1, points2;
for (std::vector<cv::DMatch>::const_iterator it= matches.begin();
it!= matches.end(); ++it) {H


// Get the position of left keypoints得到左圖關(guān)鍵點位置
float x= keypoints1[it->queryIdx].pt.x;
float y= keypoints1[it->queryIdx].pt.y;
points1.push_back(cv::Point2f(x,y));
// Get the position of right keypoints得到右圖關(guān)鍵點位置
x= keypoints2[it->trainIdx].pt.x;
y= keypoints2[it->trainIdx].pt.y;
points2.push_back(cv::Point2f(x,y));
}


std::cout << points1.size() << " " << points2.size() << std::endl; 


// Find the homography between image 1 and image 2找到圖像1和圖像2之間的單應(yīng)性矩陣
std::vector<uchar> inliers(points1.size(),0);
cv::Mat homography= cv::findHomography(
cv::Mat(points1),cv::Mat(points2), // corresponding points對應(yīng)點
inliers, // outputed inliers matches 輸出內(nèi)點匹配
CV_RANSAC, // RANSAC method   RANSAC 方法
1.);  // max distance to reprojection point到對應(yīng)點的最大距離


// Draw the inlier points畫內(nèi)點
std::vector<cv::Point2f>::const_iterator itPts= points1.begin();
std::vector<uchar>::const_iterator itIn= inliers.begin();
while (itPts!=points1.end()) {


// draw a circle at each inlier location在每一個內(nèi)點畫一個圈
if (*itIn) 
 cv::circle(image1,*itPts,3,cv::Scalar(255,255,255),2);

++itPts;
++itIn;
}


itPts= points2.begin();
itIn= inliers.begin();
while (itPts!=points2.end()) {


// draw a circle at each inlier location在每一個內(nèi)點畫一個圈
if (*itIn) 
cv::circle(image2,*itPts,3,cv::Scalar(255,255,255),2);

++itPts;
++itIn;
}


  // Display the images with points顯示畫點的圖像
cv::namedWindow("Image 1 Homography Points");
cv::imshow("Image 1 Homography Points",image1);
cv::namedWindow("Image 2 Homography Points");
cv::imshow("Image 2 Homography Points",image2);


// Warp image 1 to image 2變形圖像1到圖像2
cv::Mat result;
cv::warpPerspective(image1, // input image輸入的圖像
result, // output image輸出的圖像
homography, // homography單應(yīng)性矩陣
cv::Size(2*image1.cols,image1.rows)); // size of output image輸出圖像的大小


// Copy image 1 on the first half of full image復(fù)制圖像1的上一部分
cv::Mat half(result,cv::Rect(0,0,image2.cols,image2.rows));
image2.copyTo(half);


  // Display the warp image顯示變形后圖像
cv::namedWindow("After warping");
cv::imshow("After warping",result);


cv::waitKey();
return 0;
}