#include <opencv2/opencv.hpp>
#include <vector>
#include <iostream>
using namespace std;
using namespace cv;
static void help()
{
cout << "\n This program demonstrates how to detect compute and match ORB BRISK and AKAZE descriptors \n"
"Usage: \n"
" ./matchmethod_orb_akaze_brisk <image1(../data/basketball1.png as default)> <image2(../data/basketball2.png as default)>\n"
"Press a key when image window is active to change algorithm or descriptor";
}
int main(int argc, char *argv[])
{
vector<String> typeDesc;
vector<String> typeAlgoMatch;
vector<String> fileName;
help();
// This descriptor are going to be detect and compute
typeDesc.push_back("AKAZE-DESCRIPTOR_KAZE_UPRIGHT"); // see http://docs.opencv.org/trunk/d8/d30/classcv_1_1AKAZE.html
typeDesc.push_back("AKAZE"); // see http://docs.opencv.org/trunk/d8/d30/classcv_1_1AKAZE.html
typeDesc.push_back("ORB"); // see http://docs.opencv.org/trunk/de/dbf/classcv_1_1BRISK.html
typeDesc.push_back("BRISK"); // see http://docs.opencv.org/trunk/db/d95/classcv_1_1ORB.html
// This algorithm would be used to match descriptors see http://docs.opencv.org/trunk/db/d39/classcv_1_1DescriptorMatcher.html#ab5dc5036569ecc8d47565007fa518257
typeAlgoMatch.push_back("BruteForce");
typeAlgoMatch.push_back("BruteForce-L1");
typeAlgoMatch.push_back("BruteForce-Hamming");
typeAlgoMatch.push_back("BruteForce-Hamming(2)");
if (argc==1)
{
fileName.push_back("../data/basketball1.png");
fileName.push_back("../data/basketball2.png");
}
else if (argc==3)
{
fileName.push_back(argv[1]);
fileName.push_back(argv[2]);
}
else
{
help();
return(0);
}
Mat img1 = imread(fileName[0], IMREAD_GRAYSCALE);
Mat img2 = imread(fileName[1], IMREAD_GRAYSCALE);
if (img1.rows*img1.cols <= 0)
{
cout << "Image " << fileName[0] << " is empty or cannot be found\n";
return(0);
}
if (img2.rows*img2.cols <= 0)
{
cout << "Image " << fileName[1] << " is empty or cannot be found\n";
return(0);
}
vector<double> desMethCmp;
Ptr<Feature2D> b;
// Descriptor loop
vector<String>::iterator itDesc;
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); itDesc++)
{
Ptr<DescriptorMatcher> descriptorMatcher;
// Match between img1 and img2
vector<DMatch> matches;
// keypoint for img1 and img2
vector<KeyPoint> keyImg1, keyImg2;
// Descriptor for img1 and img2
Mat descImg1, descImg2;
vector<String>::iterator itMatcher = typeAlgoMatch.end();
if (*itDesc == "AKAZE-DESCRIPTOR_KAZE_UPRIGHT"){
b = AKAZE::create(AKAZE::DESCRIPTOR_KAZE_UPRIGHT);
}
if (*itDesc == "AKAZE"){
b = AKAZE::create();
}
if (*itDesc == "ORB"){
b = ORB::create();
}
else if (*itDesc == "BRISK"){
b = BRISK::create();
}
try
{
// We can detect keypoint with detect method
b->detect(img1, keyImg1, Mat());
// and compute their descriptors with method compute
b->compute(img1, keyImg1, descImg1);
// or detect and compute descriptors in one step
b->detectAndCompute(img2, Mat(),keyImg2, descImg2,false);
// Match method loop
for (itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); itMatcher++){
descriptorMatcher = DescriptorMatcher::create(*itMatcher);
if ((*itMatcher == "BruteForce-Hamming" || *itMatcher == "BruteForce-Hamming(2)") && (b->descriptorType() == CV_32F || b->defaultNorm() <= NORM_L2SQR))
{
cout << "**************************************************************************\n";
cout << "It's strange. You should use Hamming distance only for a binary descriptor\n";
cout << "**************************************************************************\n";
}
if ((*itMatcher == "BruteForce" || *itMatcher == "BruteForce-L1") && (b->defaultNorm() >= NORM_HAMMING))
{
cout << "**************************************************************************\n";
cout << "It's strange. You shouldn't use L1 or L2 distance for a binary descriptor\n";
cout << "**************************************************************************\n";
}
try
{
descriptorMatcher->match(descImg1, descImg2, matches, Mat());
// Keep best matches only to have a nice drawing.
// We sort distance between descriptor matches
Mat index;
int nbMatch=int(matches.size());
Mat tab(nbMatch, 1, CV_32F);
for (int i = 0; i<nbMatch; i++)
{
tab.at<float>(i, 0) = matches[i].distance;
}
sortIdx(tab, index, SORT_EVERY_COLUMN + SORT_ASCENDING);
vector<DMatch> bestMatches;
for (int i = 0; i<30; i++)
{
bestMatches.push_back(matches[index.at<int>(i, 0)]);
}
Mat result;
drawMatches(img1, keyImg1, img2, keyImg2, bestMatches, result);
namedWindow(*itDesc+": "+*itMatcher, WINDOW_AUTOSIZE);
imshow(*itDesc + ": " + *itMatcher, result);
// Saved result could be wrong due to bug 4308
FileStorage fs(*itDesc + "_" + *itMatcher + ".yml", FileStorage::WRITE);
fs<<"Matches"<<matches;
vector<DMatch>::iterator it;
cout<<"**********Match results**********\n";
cout << "Index \tIndex \tdistance\n";
cout << "in img1\tin img2\n";
// Use to compute distance between keyPoint matches and to evaluate match algorithm
double cumSumDist2=0;
for (it = bestMatches.begin(); it != bestMatches.end(); it++)
{
cout << it->queryIdx << "\t" << it->trainIdx << "\t" << it->distance << "\n";
Point2d p=keyImg1[it->queryIdx].pt-keyImg2[it->trainIdx].pt;
cumSumDist2=p.x*p.x+p.y*p.y;
}
desMethCmp.push_back(cumSumDist2);
waitKey();
}
catch (Exception& e)
{
cout << e.msg << endl;
cout << "Cumulative distance cannot be computed." << endl;
desMethCmp.push_back(-1);
}
}
}
catch (Exception& e)
{
cout << "Feature : " << *itDesc << "\n";
if (itMatcher != typeAlgoMatch.end())
{
cout << "Matcher : " << *itMatcher << "\n";
}
cout << e.msg << endl;
}
}
int i=0;
cout << "Cumulative distance between keypoint match for different algorithm and feature detector \n\t";
cout << "We cannot say which is the best but we can say results are differents! \n\t";
for (vector<String>::iterator itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); itMatcher++)
{
cout<<*itMatcher<<"\t";
}
cout << "\n";
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); itDesc++)
{
cout << *itDesc << "\t";
for (vector<String>::iterator itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); itMatcher++, i++)
{
cout << desMethCmp[i]<<"\t";
}
cout<<"\n";
}
return 0;
}