mirror of
https://github.com/modelec/detection_pot.git
synced 2026-01-19 00:57:28 +01:00
277 lines
9.7 KiB
C++
277 lines
9.7 KiB
C++
#include "ArucoDetector.h"
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ArucoDetector::ArucoDetector(const std::string& calibrationPath, const Team team, const bool headless) : headless(headless), team(team)
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{
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// opencv 4.8
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// this->detector = cv::aruco::ArucoDetector(getPredefinedDictionary(cv::aruco::DICT_4X4_50), cv::aruco::DetectorParameters());
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// this->dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_4X4_50);
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// this->parameters = cv::aruco::DetectorParameters();
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// 4.6
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this->dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_4X4_50);
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this->parameters = cv::aruco::DetectorParameters::create();
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// TODO
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// Adjusting parameters based on specific needs
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/*parameters->adaptiveThreshConstant = true;
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parameters->minMarkerPerimeterRate = 0.02;
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parameters->maxMarkerPerimeterRate = 4.0;
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parameters->perspectiveRemoveIgnoredMarginPerCell = 0.13;
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parameters->polygonalApproxAccuracyRate = 0.03;*/
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this->readCameraParameters(calibrationPath);
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this->cam = new lccv::PiCamera;
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cam->options->video_width=1920;
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cam->options->video_height=1080;
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cam->options->framerate=5;
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cam->options->verbose=true;
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started = true;
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if (!headless)
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{
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cv::namedWindow("ArUco Detection", cv::WINDOW_NORMAL);
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}
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// auto whiteFlower = ArucoTag(36, "White flower", 20, FLOWER);
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// whiteFlower.setFlowerObjectRepresentation();
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// this->addArucoTag(whiteFlower);
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// auto purpleFlower = ArucoTag(13, "Purple flower", 20, FLOWER);
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// purpleFlower.setFlowerObjectRepresentation();
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// this->addArucoTag(purpleFlower);
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// this->addArucoTag(ArucoTag(47, "Solar panel", 50, SOLAR_PANEL));
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cam->startVideo();
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}
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ArucoDetector::~ArucoDetector()
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{
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cam->stopVideo();
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cv::destroyAllWindows();
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delete cam;
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}
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void ArucoDetector::readCameraParameters(const std::string& path)
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{
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cv::FileStorage fs(path, cv::FileStorage::READ);
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if (fs.isOpened()) {
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fs["cameraMatrix"] >> this->cameraMatrix;
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fs["distCoeffs"] >> this->distCoeffs;
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fs.release();
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} else {
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std::cerr << "Error reading calibration file." << std::endl;
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}
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}
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void ArucoDetector::addArucoTag(const ArucoTag& tag)
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{
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this->arucoTags.push_back(tag);
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}
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std::pair<int, std::vector<std::pair<ArucoTag, std::pair<cv::Mat, cv::Mat>>>> ArucoDetector::detectArucoTags(std::vector<ArucoTag> tags)
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{
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/*if (!started)
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{
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std::pair<int, std::vector<std::pair<ArucoTag, std::pair<cv::Mat, cv::Mat>>>> result;
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result.first = -2;
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return result;
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}*/
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if (tags.empty())
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{
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tags = this->arucoTags;
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}
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cv::Mat frame;
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cv::Mat frameNotRotated;
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cv::Mat frameDistored;
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cam->getVideoFrame(frameNotRotated, 1000);
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cv::flip(frameNotRotated, frameDistored, -1);
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cv::undistort(frameDistored, frame, cameraMatrix, distCoeffs);
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std::pair<int, std::vector<std::pair<ArucoTag, std::pair<cv::Mat, cv::Mat>>>> result;
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if (frame.empty()) {
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result.first = -2;
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return result;
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}
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// Convert frame to grayscale
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cv::Mat gray;
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cv::cvtColor(frame, gray, cv::COLOR_BGR2GRAY);
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std::vector<int> markerIds;
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std::vector<std::vector<cv::Point2f>> markerCorners;
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// Preprocess with adaptive thresholding to handle varying lighting
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/*cv::Mat adaptiveThresh;
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cv::adaptiveThreshold(gray, adaptiveThresh, 255, cv::ADAPTIVE_THRESH_MEAN_C, cv::THRESH_BINARY, 11, 2);
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// Find contours in the thresholded image
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std::vector<std::vector<cv::Point>> contours;
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std::vector<cv::Vec4i> hierarchy;
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cv::findContours(adaptiveThresh, contours, hierarchy, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE);
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// Approximate contours to polygons
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std::vector<std::vector<cv::Point>> approxContours(contours.size());
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for (size_t i = 0; i < contours.size(); i++) {
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cv::approxPolyDP(cv::Mat(contours[i]), approxContours[i], 3, true); // Adjust epsilon as needed
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}
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// Use approximated contours to define regions of interest (ROIs)
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std::vector<cv::Rect> ROIs;
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for (const auto& contour : approxContours) {
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cv::Rect boundingRect = cv::boundingRect(contour);
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// Optionally, apply filtering based on ROI size or aspect ratio
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// For example:
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// if (boundingRect.area() > minArea && boundingRect.width / static_cast<double>(boundingRect.height) > minAspectRatio) {
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ROIs.push_back(boundingRect);
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}
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// Detect ArUco markers within defined ROIs
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for (const auto& roi : ROIs) {
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cv::Rect roiRect = roi & cv::Rect(0, 0, frame.cols, frame.rows); // Ensure the ROI is within the image boundaries
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cv::Mat roiFrame = frame(roiRect).clone(); // Extract ROI
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// Detect ArUco markers within the ROI
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std::vector<int> ids;
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std::vector<std::vector<cv::Point2f>> corners;
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cv::aruco::detectMarkers(roiFrame, this->dictionary, corners, ids, this->parameters);
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// Adjust marker corners to global coordinates
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for (auto& corner : corners) {
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for (auto& pt : corner) {
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pt.x += roiRect.x;
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pt.y += roiRect.y;
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}
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}
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// Merge results
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markerIds.insert(markerIds.end(), ids.begin(), ids.end());
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markerCorners.insert(markerCorners.end(), corners.begin(), corners.end());
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}*/
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// opencv 4.8
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// detector.detectMarkers(frame, markerCorners, markerIds);
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// 4.6
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cv::aruco::detectMarkers(frame, this->dictionary, markerCorners, markerIds, this->parameters);
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if (!markerIds.empty())
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{
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if (!headless)
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{
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cv::aruco::drawDetectedMarkers(frame, markerCorners, markerIds);
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}
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for (size_t i = 0; i < markerCorners.size(); i++)
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{
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int id = markerIds[i];
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if (std::find_if(tags.begin(), tags.end(), [id](const ArucoTag& tag) { return tag.id == id; }) == tags.end())
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{
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continue;
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}
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ArucoTag tag = *std::find_if(tags.begin(), tags.end(), [id](const ArucoTag& tag) { return tag.id == id; });
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cv::Mat rvec, tvec;
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try {
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solvePnP(tag.objectRepresenation, markerCorners.at(i), cameraMatrix, distCoeffs, rvec, tvec, false, cv::SOLVEPNP_IPPE_SQUARE);
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} catch (const cv::Exception& e) {
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std::cerr << "Error: " << e.what() << std::endl;
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continue;
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}
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if (!headless)
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{
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drawFrameAxes(frame, cameraMatrix, distCoeffs, rvec, tvec, tag.length/2.f);
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// draw::drawCenterPoints(frame, markerCorners, 100);
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}
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// Convert rotation vector to rotation matrix
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cv::Mat rotationMatrix;
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cv::Rodrigues(rvec, rotationMatrix);
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// std::cout << rvec << std::endl;
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// std::cout << rotationMatrix << std::endl;
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// Extract Euler angles from the rotation matrix
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double roll, pitch, yaw;
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pitch = asin(rotationMatrix.at<double>(2, 0));
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roll = atan2(-rotationMatrix.at<double>(2, 1), rotationMatrix.at<double>(2, 2));
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yaw = atan2(-rotationMatrix.at<double>(1, 0), rotationMatrix.at<double>(0, 0));
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// Angles can be used to calculate the distance to the center of the flower.
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// std::cout << roll << " " << pitch << " " << yaw << std::endl << std::endl;
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cv::Mat rotaEuler = (cv::Mat_<double>(3, 1) << roll, pitch, yaw);
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// Apply the homogeneous transformation to tvec
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result.second.emplace_back(tag, std::make_pair(tvec, rotaEuler));
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}
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}
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std::sort(result.second.begin(), result.second.end(), [this](const std::pair<ArucoTag, std::pair<cv::Mat, cv::Mat>>& a, const std::pair<ArucoTag, std::pair<cv::Mat, cv::Mat>>& b)
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{
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return distanceBetweenRobotAndTagOnXY(a.second.first) < distanceBetweenRobotAndTagOnXY(b.second.first);
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});
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if (!headless)
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{
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cv::imshow("ArUco Detection", frame);
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if (cv::waitKey(10) == 27)
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{
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// Press 'Esc' to exit
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result.first = 1;
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return result;
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}
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}
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result.first = 0;
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return result;
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}
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/*void ArucoDetector::flowerDetector(const ArucoTag& tag, const cv::Mat& translationMatrix, const cv::Mat& rotationMatrix, Type::RobotPose* robotPose)
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{
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constexpr double distanceToPot = 21;
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const double distanceXFlower = translationMatrix.at<double>(0, 0);// + (distanceToPot * sin(rotationMatrix.at<double>(1, 0)));
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const double distanceZFlower = translationMatrix.at<double>(2, 0);// + (distanceToPot * cos(rotationMatrix.at<double>(1, 0)));
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const double distanceFlower = distanceBetweenRobotAndTag(robotPose, translationMatrix);
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//std::cout << tag.name << " Pos : x: " << distanceXFlower << " z: " << distanceZFlower << " " << "distance: " << distanceFlower << std::endl;
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}
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void ArucoDetector::solarPanelDetector(const ArucoTag& tag, cv::Mat translationMatrix, const cv::Mat& rotationMatrix, Type::RobotPose* robotPose)
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{
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std::cout << tag.name << " Pos : x: " << translationMatrix.at<double>(0, 0) << " z: " << translationMatrix.at<double>(2, 0) << " " << std::endl;
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const auto yaw = rotationMatrix.at<double>(2, 0);
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const auto rotationBaseTable = (-yaw) + robotPose->theta;
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std::cout << " Rotation: " << rotationBaseTable * (180 / CV_PI) << std::endl;
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if (rotationBaseTable > 70 && rotationBaseTable <= 110)
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{
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std::cout << "Mid" << std::endl;
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}
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else if (rotationBaseTable > 30 && rotationBaseTable <= 70)
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{
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std::cout << "Blue side" << std::endl;
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}
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else if (rotationBaseTable > 110 && rotationBaseTable <= 150)
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{
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std::cout << "Yellow side" << std::endl;
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}
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else
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{
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std::cout << "Mid" << std::endl;
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}
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// BLUE => 90, YELLOW => -90
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}
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*/ |