void build_model() {
vector<Mat> trainDesc;
FeatureDetector *detector = new SurfFeatureDetector();
DescriptorExtractor *extractor = new SurfDescriptorExtractor();
// Generate descriptors from the image db
fs::path p = fs::system_complete(IMAGE_DATABASE);
fs::directory_iterator end_iter;
for(fs::directory_iterator dir_itr(p); dir_itr != end_iter; ++dir_itr) {
string img_name(dir_itr->path().string());
Mat img = imread(img_name, CV_LOAD_IMAGE_GRAYSCALE);
// feature extraction
vector<KeyPoint> keypoints;
detector->detect(img, keypoints);
// feature description
Mat descriptor;
extractor->compute(img, keypoints, descriptor);
trainDesc.push_back(descriptor);
imgNames.push_back(img_name);
}
// train the model
matcher->add(trainDesc);
matcher->train();
// Clean up
delete detector;
delete extractor;
}
string exec_match(Mat testDesc, int match_method) {
vector<vector<DMatch> > knnMatches;
vector<DMatch> annMatches;
vector<int> bestMatches(imgNames.size(), 0);
// apply the required matching method
switch(match_method) {
case 1: {
int knn = 1;
matcher->knnMatch(testDesc, knnMatches, knn);
// Filter results
for(vector<vector<DMatch> >::const_iterator it = knnMatches.begin(); it != knnMatches.end(); ++it) {
for(vector<DMatch>::const_iterator it2 = it->begin(); it2 != it->end(); ++it2) {
++bestMatches[(*it2).imgIdx];
}
}
}
break;
case 2: {
matcher->match(testDesc, annMatches);
for(vector<DMatch>::const_iterator iter = annMatches.begin(); iter != annMatches.end(); ++iter) {
++bestMatches[(*iter).imgIdx];
}
}
break;
}
// Filter results
/*
for(vector<vector<DMatch> >::const_iterator it = knnMatches.begin(); it != knnMatches.end(); ++it){
for(vector<DMatch>::const_iterator it2 = it->begin(); it2 != it->end(); ++it2){
++bestMatches[(*it2).imgIdx];
}
}
*/
// Find best match
int bestScore = 0;
int bestIdx = -1;
for(int i = 0; i < bestMatches.size(); ++i){
if(bestMatches[i] >= bestScore){
bestScore = bestMatches[i];
bestIdx = i;
}
}
string imgBaseName = string(fs::basename(imgNames.at(bestIdx)));
boost::replace_all(imgBaseName, "-", " ");
return imgBaseName;
}
static double match(const vector<KeyPoint>& /*kpts_train*/, const vector<KeyPoint>& /*kpts_query*/, DescriptorMatcher& matcher,
const Mat& train, const Mat& query, vector<DMatch>& matches)
{
double t = (double)getTickCount();
matcher.match(query, train, matches); //Using features2d
return ((double)getTickCount() - t) / getTickFrequency();
}
void ratioTestMatching(DescriptorMatcher& descriptorMatcher, const Mat& descriptors1, const Mat& descriptors2,
vector<DMatch>& filteredMatches12, float ratio = 0.6f)
{
const int knn = 2;
filteredMatches12.clear();
vector<vector<DMatch> > matches12;
descriptorMatcher.knnMatch(descriptors1, descriptors2, matches12, 2);
for (size_t m = 0; m < matches12.size(); m++)
{
if (matches12[m][0].distance / matches12[m][1].distance < ratio)
filteredMatches12.push_back(matches12[m][0]);
}
}
