mac上用opencv计算视差图

#include <opencv2/opencv.hpp> #include <opencv2/features2d/features2d.hpp> #include <opencv2/nonfree/nonfree.hpp> #include <opencv2/legacy/legacy.hpp> #include <vector> #include <stdio.h> #include <stdlib.h> #include <vector> #include <string> #include <algorithm> #include <stdio.h> #include <ctype.h> #include "cxcore.h" #include "highgui.h" #include "cv.h" #include "cvaux.h" #include "cxmisc.h" #include "math.h" using namespace std; using namespace cv; int main() { initModule_nonfree();//initialize module for sift and surf Ptr<FeatureDetector> detector = FeatureDetector::create( "SIFT" );//creat SIFT feature detector Ptr<DescriptorExtractor> descriptor_extractor = DescriptorExtractor::create( "SIFT" );//creat feature vector generator Ptr<DescriptorMatcher> descriptor_matcher = DescriptorMatcher::create( "BruteForce" );//creat feature matcher if( detector.empty() || descriptor_extractor.empty() ) cout<<"fail to create detector!"; //load image Mat disp, disp8; Mat img1 = imread("/Users/henry/Desktop/2.png"); Mat img2 = imread("/Users/henry/Desktop/3.png"); IplImage* img3 =cvLoadImage("/Users/henry/Desktop/2.png",0); IplImage* img4 =cvLoadImage("/Users/henry/Desktop/3.png",0); imshow("image1 before", img1); imshow("image2 before",img2); //keypoint detection SiftFeatureDetector siftdtc; //double t = getTickCount();//current time vector<KeyPoint> keypoints1,keypoints2; siftdtc.detect(img1,keypoints1);//detect the keypoints in img1 siftdtc.detect(img2,keypoints2); cout<<"img1keypointsnumber:"<<keypoints1.size()<<endl; cout<<"img2keypointsnumber:"<<keypoints2.size()<<endl; //calculate the feature descriptor matrix Mat descriptors1,descriptors2; descriptor_extractor->compute( img1, keypoints1, descriptors1 ); descriptor_extractor->compute( img2, keypoints2, descriptors2 ); //t = ((double)getTickCount() - t)/getTickFrequency(); //cout<<"SURFrunning time："<<t<<"sec"<<endl; cout<<"img1 feature descriptor matrix size："<<descriptors1.size() <<"，feature vector number："<<descriptors1.rows<<"，dimension："<<descriptors1.cols<<endl; cout<<"img2 feature descriptor matrix size："<<descriptors2.size() <<"，feature vector number："<<descriptors2.rows<<"，dimension："<<descriptors2.cols<<endl; //draw keypoints Mat img_keypoints1,img_keypoints2; drawKeypoints(img1,keypoints1,img_keypoints1,CV_RGB(0,255,0),2); drawKeypoints(img2,keypoints2,img_keypoints2,CV_RGB(0,255,0),2); imshow("left",img_keypoints1); imshow("right",img_keypoints2); //feature matching vector<DMatch> matches;//matching result descriptor_matcher->match( descriptors1, descriptors2, matches );//match the feature matrix cout<<"Match number："<<matches.size()<<endl;//total matching number //calculate the longest and shorest distance double max_dist = 0; double min_dist = 100; //double min2_dist=100; for(int i=0; i<matches.size(); i++) { double dist = matches[i].distance; if(dist < min_dist) min_dist = dist; if(dist > max_dist) max_dist = dist; } cout<<"longest distance："<<max_dist<<endl; cout<<"shortest distance："<<min_dist<<endl; /*for( int i=0; i<matches.size(); i++) { double dist2= matches[i].distance; if(min_dist< dist2 < min2_dist) min2_dist = dist2; } cout<<"second shortest dist:"<<min2_dist<<endl; //double ratio = min_dist/min2_dist;*/ //filtering to get good matches vector<DMatch> goodMatches; for(int i=0; i<matches.size(); i++) { //if(ratio<0.6) if(matches[i].distance < 0.38 * max_dist) { goodMatches.push_back(matches[i]); } } cout<<"goodMatch number："<<goodMatches.size()<<endl; //draw matching map Mat img_matches,img2_matches; drawMatches(img1,keypoints1,img2,keypoints2,goodMatches,img_matches,CV_RGB(0,255,0) /*Scalar::all(-1)*//*CV_RGB(255,0,0)*/,CV_RGB(0,255,0),Mat(),2); drawMatches(img1,keypoints1,img2,keypoints2,matches,img2_matches,CV_RGB(255,0,0) /*Scalar::all(-1)*//*CV_RGB(255,0,0)*/,CV_RGB(255,0,0),Mat(),2); imshow("MatchSift",img_matches); imshow("MatchSifttotal",img2_matches); //////////////////////////////////////SAD////////////////////////////////////// CvStereoBMState *BMState = cvCreateStereoBMState(); CvMat* disparity = cvCreateMat(img3->height, img3->width, CV_32F); CvMat* norm_disparity=cvCreateMat(img3->height,img3->width,CV_8U); int SADWindowSize=15; BMState->SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 21; BMState->minDisparity = 0; BMState->numberOfDisparities = 32; BMState->textureThreshold = 10; BMState->uniquenessRatio = 15; BMState->speckleWindowSize = 100; BMState->speckleRange = 32; BMState->disp12MaxDiff = 1; cvFindStereoCorrespondenceBM( img3, img4,disparity ,BMState); cvNormalize( disparity,norm_disparity , 0, 256, CV_MINMAX ); cvNamedWindow("sbm",0); cvShowImage("sbm", norm_disparity); //////////////////////////rmse sbm/////////////////////////////////////////// IplImage* gt = cvLoadImage("/Users/henry/Desktop/t3.pgm",0); int m = norm_disparity->width; int n = norm_disparity->height; double rmse=0; double mse=0; double tmp1=0; double tmp2=0; for (int j=0; j<m; j++ ) { for (int i=0; i<n; i++) { tmp1=cvGet2D(norm_disparity,i,j).val[0]; tmp2=cvGet2D(gt,i,j).val[0]; mse=mse+(tmp1-tmp2)*(tmp1-tmp2); } } rmse=sqrt(mse/(m*n)); cout<<"rmsesbm："<<rmse<<endl; /////////////////////////////////bad pixel/////////////////////////////// int p = norm_disparity->width; int q = norm_disparity->height; double bp=0; double tmp5=0; double tmp6=0; for (int j=0; j<p; j++) { for(int i=0;i<q;i++) { tmp5=cvGet2D(norm_disparity,i,j).val[0]; tmp6=cvGet2D(gt,i,j).val[0]; if (fabs (tmp5-tmp6)>1) bp=(bp+fabs(tmp5-tmp6)); } } bp=bp/(p*q); cout<<"bpsbm:"<<bp<<endl; /////////////////////////////////////GC//////////////////////////////////// CvSize size = cvGetSize( img3 ); //the disparity map is an array h*w, with 16bit signed elements. CvStereoGCState* state = cvCreateStereoGCState( 16, 2 ); CvMat* disparity_left = cvCreateMat( size.height, size.width, CV_16S ); CvMat* disparity_right = cvCreateMat( size.height, size.width, CV_16S ); cvFindStereoCorrespondenceGC( img3,img4,disparity_left,disparity_right,state,0); cvReleaseStereoGCState( &state ); //post-progressing the result CvMat* disparity_left_visual = cvCreateMat( size.height, size.width, CV_8U ); cvConvertScale( disparity_left, disparity_left_visual, -16 ); cvNamedWindow( "gc", 1); cvShowImage("gc", disparity_left_visual ); //////////////////////////////////rmse gc////////////////////////////////// int a = disparity_left_visual->width; int b = disparity_left_visual->height; double rmsegc=0; double msegc=0; double tmp3=0; double tmp4=0; for (int j=0; j<a; j++ ) { for (int i=0; i<b; i++) { tmp3=cvGet2D(disparity_left_visual,i,j).val[0]; tmp4=cvGet2D(gt,i,j).val[0]; msegc=msegc+(tmp3-tmp4)*(tmp3-tmp4); } } rmsegc=sqrt(msegc/(a*b)); cout<<"rmsegc："<<rmsegc<<endl; ///////////////////////////////////bad pixel gc//////////////////////////////// int x = disparity_left_visual->width; int y = disparity_left_visual->height; double bpgc=0; double tm