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removing old code
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@kalwalt
kalwalt committed Jun 5, 2024
1 parent 47e1984 commit 1e98161
Showing 1 changed file with 2 additions and 260 deletions.
262 changes: 2 additions & 260 deletions WebARKit/WebARKitTrackers/WebARKitOpticalTracking/WebARKitTracker.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -139,8 +139,7 @@ class WebARKitTracker::WebARKitTrackerImpl {
if (enableBlur) {
cv::blur(grayFrame, grayFrame, blurSize);
}
// buildImagePyramid(grayFrame);
processFrame2(grayFrame);
processFrame(grayFrame);
grayFrame.release();
};

Expand All @@ -157,170 +156,6 @@ class WebARKitTracker::WebARKitTrackerImpl {
bool isValid() { return _valid; };

protected:
bool resetTracking(cv::Mat& currIm) {
if (!initialized) {
WEBARKIT_LOGe("Reference image not found. AR is unintialized!\n");
return NULL;
}

WEBARKIT_LOGi("Reset Tracking!\n");

clear_output();

_isDetected = false;

cv::Mat frameDescr;
std::vector<cv::KeyPoint> frameKeyPts;
bool valid;

cv::Mat featureMask = createFeatureMask(currIm);

if (!extractFeatures(currIm, featureMask, frameKeyPts, frameDescr)) {
WEBARKIT_LOGe("No features detected in resetTracking!\n");
return false;
};

if (!_isDetected) {
std::vector<cv::Point2f> refPts;

getMatches(frameDescr, frameKeyPts, refPts, framePts);
numMatches = framePts.size();

WEBARKIT_LOG("Num Matches: %d\n", numMatches);

if (numMatches >= minNumMatches) {
// m_H = cv::findHomography(refPts, framePts, cv::RANSAC);
webarkit::homography::WebARKitHomographyInfo homographyInfo = getHomographyInliers(refPts, framePts);
valid = homographyInfo.validHomography;

// if ((valid = homographyValid(m_H))) {
if (valid) {
m_H = homographyInfo.homography;
_isDetected = true;
perspectiveTransform(_bBox, _bBoxTransformed, homographyInfo.homography);
}
}
}

return valid;
};

bool track() {
if (!initialized) {
WEBARKIT_LOGe("Reference image not found. AR is unintialized!\n");
return NULL;
}

WEBARKIT_LOGi("Start tracking!\n");
clear_output();

// use optical flow to track keypoints
std::vector<float> err;
// std::vector<uchar> status;
std::vector<uchar> statusFirstPass, statusSecondPass;
std::vector<cv::Point2f> currPts, goodPtsCurr, goodPtsPrev;
bool valid;
calcOpticalFlowPyrLK(_prevPyramid, _pyramid, framePts, currPts, statusFirstPass, err, winSize, maxLevel,
termcrit, 0, 0.001);
calcOpticalFlowPyrLK(_pyramid, _prevPyramid, currPts, framePts, statusSecondPass, err, winSize, maxLevel,
termcrit, 0, 0.001);
// calculate average variance
double mean, avg_variance = 0.0;
double sum = 0.0;
double diff;
std::vector<double> diffs;
int killed1 = 0;

for (auto j = 0; j != currPts.size(); ++j) {
if (!statusFirstPass[j] || !statusSecondPass[j]) {
statusFirstPass[j] = (uchar)0;
killed1++;
continue;
}

goodPtsCurr.push_back(currPts[j]);
goodPtsPrev.push_back(framePts[j]);

diff = sqrt(pow(currPts[j].x - framePts[j].x, 2.0) + pow(currPts[j].y - framePts[j].y, 2.0));
sum += diff;
diffs.push_back(diff);
}

mean = sum / diffs.size();
for (int i = 0; i < goodPtsCurr.size(); ++i) {
avg_variance += pow(diffs[i] - mean, 2);
}
avg_variance /= diffs.size();

if ((goodPtsCurr.size() > numMatches / 2) && (1.75 > avg_variance)) {
cv::Mat transform = estimateAffine2D(goodPtsPrev, goodPtsCurr);

// add row of {0,0,1} to transform to make it 3x3
cv::Mat row = cv::Mat::zeros(1, 3, CV_64F);
row.at<double>(0, 2) = 1.0;
transform.push_back(row);

// update homography matrix
if (!m_H.empty()) {
m_H = transform * m_H;
}
// m_H = transform * m_H;

// set old points to new points
framePts = goodPtsCurr;
std::vector<cv::Point2f> warpedCorners;

if ((valid = homographyValid(m_H))) {
fill_output(m_H);

warpedCorners = getSelectedFeaturesWarped(m_H);

_patternTrackingInfo.computePose(_pattern.points3d, warpedCorners, m_camMatrix, m_distortionCoeff);

_patternTrackingInfo.computeGLviewMatrix();

_isDetected = true;
} else {
_isDetected = false;
}
}

return valid;
};

bool track2() {
if (!initialized) {
WEBARKIT_LOGe("Reference image not found. AR is unintialized!\n");
return NULL;
}
int i = 0;

WEBARKIT_LOGi("Start tracking!\n");
clear_output();

// std::cout << _prevPyramid.size() << std::endl;

if (_prevPyramid.size() > 0) {
// std::cout << "Starting Optical Flow" << std::endl;
std::vector<cv::Point2f> warpedPoints;
// perspectiveTransform(framePts, warpedPoints, m_H);
warpedPoints = getSelectedFeaturesWarped(m_H);
// if (!runOpticalFlow(i, trackablePoints, trackablePointsWarped)) {
if (!runOpticalFlow(i, framePts, warpedPoints)) {
std::cout << "Optical flow failed." << std::endl;
return true;
} else {
// if (_trackVizActive) _trackViz.opticalFlowOK = true;
// Refine optical flow with template match.
/*if (!RunTemplateMatching(frame, i)) {
//std::cout << "Template matching failed." << std::endl;
}*/
// std::cout << "Optical flow ok." << std::endl;
return false;
}
}
}

bool RunTemplateMatching(cv::Mat frame, int trackableId) {
// std::cout << "Starting template match" << std::endl;
std::vector<cv::Point2f> finalTemplatePoints, finalTemplateMatchPoints;
Expand Down Expand Up @@ -445,17 +280,6 @@ class WebARKitTracker::WebARKitTrackerImpl {
}

void processFrame(cv::Mat& frame) {
if (!this->_valid) {
this->_valid = resetTracking(frame);
} else {
if (!track2()) {
};
}
WEBARKIT_LOG("Marker detected : %s\n", _isDetected ? "true" : "false");
swapImagePyramid();
};

void processFrame2(cv::Mat& frame) {
buildImagePyramid(frame);

if (!initialized) {
Expand Down Expand Up @@ -502,27 +326,6 @@ class WebARKitTracker::WebARKitTrackerImpl {
WEBARKIT_LOGd("frameKeyPts.size() = %d\n", frameKeyPts.size());
if (static_cast<int>(frameKeyPts.size()) > minRequiredDetectedFeatures) {
MatchFeatures(frameKeyPts, frameDescr);
/*std::vector<cv::Point2f> refPts;
getMatches(frameDescr, frameKeyPts, refPts, framePts);
numMatches = framePts.size();
WEBARKIT_LOG("Num Matches: %d\n", numMatches);
if (numMatches >= minNumMatches) {
// m_H = cv::findHomography(refPts, framePts, cv::RANSAC);
webarkit::homography::WebARKitHomographyInfo homographyInfo = getHomographyInliers(refPts,
framePts); valid = homographyInfo.validHomography;
// if ((valid = homographyValid(m_H))) {
if (valid) {
m_H = homographyInfo.homography;
_isDetected = true;
_trackSelection.ResetSelection();
_trackSelection.SetHomography(homographyInfo.homography);
perspectiveTransform(_bBox, _bBoxTransformed, homographyInfo.homography);
}
}*/
}
//} ref -> if (_currentlyTrackedMarkers < _maxNumberOfMarkersToTrack) {
int i = 0;
Expand All @@ -531,76 +334,37 @@ class WebARKitTracker::WebARKitTrackerImpl {
if (_frameCount > 0 && _prevPyramid.size() > 0) {
// if (_prevPyramid.size() > 0) {
// std::cout << "Starting Optical Flow" << std::endl;
// std::vector<cv::Point2f> warpedPoints;
// perspectiveTransform(framePts, warpedPoints, m_H);
// warpedPoints = getSelectedFeaturesWarped(m_H);
std::vector<cv::Point2f> trackablePoints = _trackSelection.GetInitialFeatures();
std::vector<cv::Point2f> trackablePointsWarped = _trackSelection.GetTrackedFeaturesWarped();
if (!runOpticalFlow(i, trackablePoints, trackablePointsWarped)) {
// if (!runOpticalFlow(i, framePts, warpedPoints)) {
WEBARKIT_LOGd("Optical flow failed.\n");
// return true;
} else {
if (_trackVizActive) { _trackViz.opticalFlowOK = true;}
// Refine optical flow with template match.
if (!RunTemplateMatching(frame, i)) {
WEBARKIT_LOGd("Template matching failed.");
}
// std::cout << "Optical flow ok." << std::endl;
// return false;
}
}
}

if (_isDetected || _isTracking) {
// std::vector<cv::Point2f> warpedCorners = _trackSelection.GetTrackedFeaturesWarped();
cv::Mat _pose;
std::vector<cv::Point2f> imgPoints = _trackSelection.GetTrackedFeaturesWarped();
std::vector<cv::Point3f> objPoints = _trackSelection.GetTrackedFeatures3d();
_patternTrackingInfo.cameraPoseFromPoints(_pose, objPoints, imgPoints, m_camMatrix, m_distortionCoeff);
// _patternTrackingInfo.computePose(_pattern.points3d, warpedCorners, m_camMatrix, m_distortionCoeff);
_patternTrackingInfo.getTrackablePose(_pose);
fill_output2(m_H);
fill_output(m_H);
WEBARKIT_LOGi("Marker tracked ! Num. matches : %d\n", numMatches);
}

swapImagePyramid();
_frameCount++;
}

bool homographyValid(cv::Mat& H) {
if (H.empty()) {
return false;
}
const double det = H.at<double>(0, 0) * H.at<double>(1, 1) - H.at<double>(1, 0) * H.at<double>(0, 1);
return 1 / N < fabs(det) && fabs(det) < N;
};

void fill_output(cv::Mat& H) {
std::vector<cv::Point2f> warped(4);
cv::perspectiveTransform(corners, warped, H);

output[0] = H.at<double>(0, 0);
output[1] = H.at<double>(0, 1);
output[2] = H.at<double>(0, 2);
output[3] = H.at<double>(1, 0);
output[4] = H.at<double>(1, 1);
output[5] = H.at<double>(1, 2);
output[6] = H.at<double>(2, 0);
output[7] = H.at<double>(2, 1);
output[8] = H.at<double>(2, 2);

output[9] = warped[0].x;
output[10] = warped[0].y;
output[11] = warped[1].x;
output[12] = warped[1].y;
output[13] = warped[2].x;
output[14] = warped[2].y;
output[15] = warped[3].x;
output[16] = warped[3].y;
};

void fill_output2(cv::Mat& H) {
output[0] = H.at<double>(0, 0);
output[1] = H.at<double>(0, 1);
output[2] = H.at<double>(0, 2);
Expand Down Expand Up @@ -850,22 +614,6 @@ class WebARKitTracker::WebARKitTrackerImpl {
return testVertexPoints;
}

void getMatches(const cv::Mat& frameDescr, std::vector<cv::KeyPoint>& frameKeyPts,
std::vector<cv::Point2f>& refPoints, std::vector<cv::Point2f>& framePoints) {
std::vector<std::vector<cv::DMatch>> knnMatches;
_matcher->knnMatch(frameDescr, refDescr, knnMatches, 2);

framePoints.clear();

// find the best matches
for (size_t i = 0; i < knnMatches.size(); ++i) {
if (knnMatches[i][0].distance < _nn_match_ratio * knnMatches[i][1].distance) {
framePoints.push_back(frameKeyPts[knnMatches[i][0].queryIdx].pt);
refPoints.push_back(refKeyPts[knnMatches[i][0].trainIdx].pt);
}
}
}

std::vector<std::vector<cv::DMatch>> getMatches(const cv::Mat& frameDescr) {
std::vector<std::vector<cv::DMatch>> knnMatches;
_matcher->knnMatch(frameDescr, refDescr, knnMatches, 2);
Expand Down Expand Up @@ -902,12 +650,6 @@ class WebARKitTracker::WebARKitTrackerImpl {
return featureMask;
}

std::vector<cv::Point2f> getSelectedFeaturesWarped(cv::Mat& H) {
std::vector<cv::Point2f> warpedPoints;
perspectiveTransform(_pattern.points2d, warpedPoints, H);
return warpedPoints;
}

cv::Mat _image;

int _currentlyTrackedMarkers;
Expand Down

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