/*!
Find and return markers
*/
void MarkerDetector::findMarkers( cv::Mat& src, std::vector<Marker>& markers)
{
// convert image to a grayscale image.
cv::cvtColor(src, _grayscale, CV_BGRA2GRAY);
// Make it binary
performThreshold(_grayscale, _threshold_image);
_contours.clear();
// Detect contours
findContours(_threshold_image, _contours, _grayscale.cols / 5);
// Find closed contours that can be approximated with 4 points
findCandidates(_contours, detectedMarkers);
// Find is them are markers
recognizeMarkers(_grayscale, detectedMarkers);
// Calculate their poses
estimatePosition(detectedMarkers);
//sort by id
std::sort(detectedMarkers.begin(), detectedMarkers.end());
markers = detectedMarkers;
}
bool MarkerDetector::findMarkers(const BGRAVideoFrame& frame, std::vector<Marker>& detectedMarkers)
{
cv::Mat bgraMat(frame.height, frame.width, CV_8UC3, frame.data, frame.stride);
// Convert the image to grayscale
prepareImage(bgraMat, m_grayscaleImage);
// Make it binary
performThreshold(m_grayscaleImage, m_thresholdImg);
// Detect contours
findContours(m_thresholdImg, m_contours, m_grayscaleImage.cols / 20);
// Find closed contours that can be approximated with 4 points
findMarkerCandidates(m_contours, detectedMarkers);
// Find is them are markers
detectMarkers(m_grayscaleImage, detectedMarkers);
// Calcualte their poses
estimatePosition(detectedMarkers);
//sort by id
std::sort(detectedMarkers.begin(), detectedMarkers.end());
return false;
}
bool MarkerDetector::findMarkers(const cv::Mat& grayscale, std::vector<Marker>& detectedMarkers)
{
if (grayscale.type()!=CV_8UC1)
throw cv::Exception(9000,"input.type()!=CV_8UC1","MarkerDetector::findMarkers",__FILE__,__LINE__);
// Prepare the image for processing
//prepareImage(frame, m_grayscaleImage);
// Make it binary
performThreshold(grayscale, m_thresholdImg);
//cv::imshow("threshold", m_thresholdImg);
//cv::waitKey(1);
//cv::imshow("resul2", m_thresholdImg);
//cv::waitKey(1);
// Detect contours
findCandidates(m_thresholdImg, detectedMarkers, m_thresholdImg.cols*0.16,m_thresholdImg.cols*2);
/*
for (size_t i=0; i<m_contours.size(); i++)
{
drawContours( frame, m_contours, i, cv::Scalar(0,0,255), CV_FILLED, 8);
}
cv::imshow("resul2", frame);
cv::waitKey(0);*/
// Find closed contours that can be approximated with 4 points
// Find is them are markers
recognizeMarkers(grayscale, detectedMarkers);
// Calculate their poses
//estimatePosition(detectedMarkers);
//sort by id
//std::sort(detectedMarkers.begin(), detectedMarkers.end());
return false;
}
bool MarkerDetector::findMarkers(const cv::Mat& frame, std::vector<Marker>& detectedMarkers)
{
// Convert the image to grayscale
prepareImage(frame, m_grayscaleImage);
// Make it binary
performThreshold(m_grayscaleImage, m_thresholdImg);
// Detect contours
findContours(m_thresholdImg, m_contours, m_grayscaleImage.cols / 5);
// Find closed contours that can be approximated with 4 points
findCandidates(m_contours, detectedMarkers);
// Find is them are markers
recognizeMarkers(m_grayscaleImage, detectedMarkers);
// Calculate their poses
estimatePosition(detectedMarkers);
//sort by id
std::sort(detectedMarkers.begin(), detectedMarkers.end());
return false;
}
