bool ImageTransformation::findHomography( const Keypoints& source, const Keypoints& result, const Matches& input, Matches& inliers, cv::Mat& homography)
{
if (input.size() < 8)
return false;
std::vector<cv::Point2f> srcPoints, dstPoints;
const int pointsCount = input.size();
for (int i=0; i<pointsCount; i++)
{
srcPoints.push_back(source[input[i].trainIdx].pt);
dstPoints.push_back(result[input[i].queryIdx].pt);
}
std::vector<unsigned char> status;
cv::findHomography(srcPoints, dstPoints, CV_FM_RANSAC, 3, status);
inliers.clear();
for (int i=0; i<pointsCount; i++)
{
if (status[i])
{
inliers.push_back(input[i]);
}
}
return true;
}
MatchPersistence MatchPersistenceFromJSON(const Value &value) {
auto executableName = value["executableName"].GetString();
auto matcherName = value["matcherName"].GetString();
auto executableArchitecture = value["executableArchitecture"].GetString();
auto realTime = value["realTime"].GetDouble();
auto cpuTime = value["cpuTime"].GetDouble();
Matches matches;
auto &matchesValue = value["matches"];
for (rapidjson::SizeType i = 0; i < matchesValue.Size(); ++i) {
auto match = MatchFromJSON(matchesValue[i]);
if (match) {
matches.push_back(match);
}
}
return MatchPersistence(executableName,matcherName,executableArchitecture,realTime,cpuTime,matches);
}
void ratioTest(const std::vector<Matches>& knMatches, float maxRatio, Matches& goodMatches)
{
goodMatches.clear();
for (size_t i=0; i< knMatches.size(); i++)
{
const cv::DMatch& best = knMatches[i][0];
const cv::DMatch& good = knMatches[i][1];
assert(best.distance <= good.distance);
float ratio = (best.distance / good.distance);
if (ratio <= maxRatio)
{
goodMatches.push_back(best);
}
}
}
/*
* Function: initRouteMatrix()
* Comments: Initializes global route matrix for this Solution
*/
void Solution::initRouteMatrix()
{
if(matrixInitType == FLUSH || myInternalMatrix.use_count() == 0)
{
Matches matches;
Riders riders;
for(MatchesMap::iterator it = myMatches.begin();
it != myMatches.end();
it++)
{
matches.push_back(it->second);
for(Riders::iterator rider = it->second.confirmedRiders.begin();
rider != it->second.confirmedRiders.end();
rider++){
riders.push_back(*rider);
}
}
for(RidersMap::iterator it = myRiders.begin();
it != myRiders.end();
it++)
{
riders.push_back(it->second);
}
Drivers emptyDrivers;
if(useLocalMatrix){
myInternalMatrix.reset(new RouteMatrixLocal(emptyDrivers,riders,matches));
}else{
myInternalMatrix.reset(new RouteMatrix<>(emptyDrivers,riders,matches));
}
}
else
{
//std::cout << "Using old route Matrix" <<std::endl;
}
routeMatrix = myInternalMatrix;
}
bool ImageTransformation::findHomography( const Keypoints& source, const Keypoints& result, const Matches& input, Matches& inliers, cv::Mat& homography)
{
if (input.size() < 4)
return false;
const int pointsCount = input.size();
const float reprojectionThreshold = 2;
//Prepare src and dst points
std::vector<cv::Point2f> srcPoints, dstPoints;
for (int i = 0; i < pointsCount; i++)
{
srcPoints.push_back(source[input[i].trainIdx].pt);
dstPoints.push_back(result[input[i].queryIdx].pt);
}
// Find homography using RANSAC algorithm
std::vector<unsigned char> status;
homography = cv::findHomography(srcPoints, dstPoints, cv::RANSAC, reprojectionThreshold, status);
// Warp dstPoints to srcPoints domain using inverted homography transformation
std::vector<cv::Point2f> srcReprojected;
cv::perspectiveTransform(dstPoints, srcReprojected, homography.inv());
// Pass only matches with low reprojection error (less than reprojectionThreshold value in pixels)
inliers.clear();
for (int i = 0; i < pointsCount; i++)
{
cv::Point2f actual = srcPoints[i];
cv::Point2f expect = srcReprojected[i];
cv::Point2f v = actual - expect;
float distanceSquared = v.dot(v);
if (/*status[i] && */distanceSquared <= reprojectionThreshold * reprojectionThreshold)
{
inliers.push_back(input[i]);
}
}
// Test for bad case
if (inliers.size() < 4)
return false;
// Now use only good points to find refined homography:
std::vector<cv::Point2f> refinedSrc, refinedDst;
for (int i = 0; i < inliers.size(); i++)
{
refinedSrc.push_back(source[inliers[i].trainIdx].pt);
refinedDst.push_back(result[inliers[i].queryIdx].pt);
}
// Use least squares method to find precise homography
cv::Mat homography2 = cv::findHomography(refinedSrc, refinedDst, 0, reprojectionThreshold);
// Reproject again:
cv::perspectiveTransform(dstPoints, srcReprojected, homography2.inv());
inliers.clear();
for (int i = 0; i < pointsCount; i++)
{
cv::Point2f actual = srcPoints[i];
cv::Point2f expect = srcReprojected[i];
cv::Point2f v = actual - expect;
float distanceSquared = v.dot(v);
if (distanceSquared <= reprojectionThreshold * reprojectionThreshold)
{
inliers.push_back(input[i]);
}
}
homography = homography2;
return inliers.size() >= 4;
}
