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1147 lines
46 KiB
C++
1147 lines
46 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#include "test_precomp.hpp"
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#include "opencv2/objdetect/aruco_detector.hpp"
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#include "opencv2/calib3d.hpp"
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namespace cv {
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namespace aruco {
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bool operator==(const Dictionary& d1, const Dictionary& d2);
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bool operator==(const Dictionary& d1, const Dictionary& d2) {
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return d1.markerSize == d2.markerSize
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&& std::equal(d1.bytesList.begin<Vec<uint8_t, 4>>(), d1.bytesList.end<Vec<uint8_t, 4>>(), d2.bytesList.begin<Vec<uint8_t, 4>>())
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&& std::equal(d2.bytesList.begin<Vec<uint8_t, 4>>(), d2.bytesList.end<Vec<uint8_t, 4>>(), d1.bytesList.begin<Vec<uint8_t, 4>>())
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&& d1.maxCorrectionBits == d2.maxCorrectionBits;
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};
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}
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}
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namespace opencv_test { namespace {
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/**
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* @brief Draw 2D synthetic markers and detect them
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*/
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class CV_ArucoDetectionSimple : public cvtest::BaseTest {
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public:
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CV_ArucoDetectionSimple();
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protected:
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void run(int);
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};
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CV_ArucoDetectionSimple::CV_ArucoDetectionSimple() {}
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void CV_ArucoDetectionSimple::run(int) {
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aruco::ArucoDetector detector(aruco::getPredefinedDictionary(aruco::DICT_6X6_250));
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// 20 images
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for(int i = 0; i < 20; i++) {
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const int markerSidePixels = 100;
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int imageSize = markerSidePixels * 2 + 3 * (markerSidePixels / 2);
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// draw synthetic image and store marker corners and ids
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vector<vector<Point2f> > groundTruthCorners;
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vector<int> groundTruthIds;
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Mat img = Mat(imageSize, imageSize, CV_8UC1, Scalar::all(255));
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for(int y = 0; y < 2; y++) {
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for(int x = 0; x < 2; x++) {
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Mat marker;
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int id = i * 4 + y * 2 + x;
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aruco::generateImageMarker(detector.getDictionary(), id, markerSidePixels, marker);
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Point2f firstCorner =
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Point2f(markerSidePixels / 2.f + x * (1.5f * markerSidePixels),
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markerSidePixels / 2.f + y * (1.5f * markerSidePixels));
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Mat aux = img.colRange((int)firstCorner.x, (int)firstCorner.x + markerSidePixels)
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.rowRange((int)firstCorner.y, (int)firstCorner.y + markerSidePixels);
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marker.copyTo(aux);
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groundTruthIds.push_back(id);
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groundTruthCorners.push_back(vector<Point2f>());
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groundTruthCorners.back().push_back(firstCorner);
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groundTruthCorners.back().push_back(firstCorner + Point2f(markerSidePixels - 1, 0));
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groundTruthCorners.back().push_back(
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firstCorner + Point2f(markerSidePixels - 1, markerSidePixels - 1));
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groundTruthCorners.back().push_back(firstCorner + Point2f(0, markerSidePixels - 1));
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}
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}
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if(i % 2 == 1) img.convertTo(img, CV_8UC3);
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// detect markers
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vector<vector<Point2f> > corners;
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vector<int> ids;
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detector.detectMarkers(img, corners, ids);
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// check detection results
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for(unsigned int m = 0; m < groundTruthIds.size(); m++) {
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int idx = -1;
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for(unsigned int k = 0; k < ids.size(); k++) {
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if(groundTruthIds[m] == ids[k]) {
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idx = (int)k;
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break;
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}
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}
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if(idx == -1) {
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ts->printf(cvtest::TS::LOG, "Marker not detected");
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
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return;
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}
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for(int c = 0; c < 4; c++) {
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double dist = cv::norm(groundTruthCorners[m][c] - corners[idx][c]); // TODO cvtest
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if(dist > 0.001) {
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ts->printf(cvtest::TS::LOG, "Incorrect marker corners position");
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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return;
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}
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}
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}
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}
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}
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static double deg2rad(double deg) { return deg * CV_PI / 180.; }
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/**
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* @brief Get rvec and tvec from yaw, pitch and distance
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*/
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static void getSyntheticRT(double yaw, double pitch, double distance, Mat &rvec, Mat &tvec) {
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rvec = Mat(3, 1, CV_64FC1);
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tvec = Mat(3, 1, CV_64FC1);
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// Rvec
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// first put the Z axis aiming to -X (like the camera axis system)
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Mat rotZ(3, 1, CV_64FC1);
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rotZ.ptr<double>(0)[0] = 0;
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rotZ.ptr<double>(0)[1] = 0;
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rotZ.ptr<double>(0)[2] = -0.5 * CV_PI;
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Mat rotX(3, 1, CV_64FC1);
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rotX.ptr<double>(0)[0] = 0.5 * CV_PI;
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rotX.ptr<double>(0)[1] = 0;
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rotX.ptr<double>(0)[2] = 0;
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Mat camRvec, camTvec;
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composeRT(rotZ, Mat(3, 1, CV_64FC1, Scalar::all(0)), rotX, Mat(3, 1, CV_64FC1, Scalar::all(0)),
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camRvec, camTvec);
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// now pitch and yaw angles
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Mat rotPitch(3, 1, CV_64FC1);
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rotPitch.ptr<double>(0)[0] = 0;
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rotPitch.ptr<double>(0)[1] = pitch;
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rotPitch.ptr<double>(0)[2] = 0;
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Mat rotYaw(3, 1, CV_64FC1);
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rotYaw.ptr<double>(0)[0] = yaw;
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rotYaw.ptr<double>(0)[1] = 0;
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rotYaw.ptr<double>(0)[2] = 0;
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composeRT(rotPitch, Mat(3, 1, CV_64FC1, Scalar::all(0)), rotYaw,
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Mat(3, 1, CV_64FC1, Scalar::all(0)), rvec, tvec);
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// compose both rotations
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composeRT(camRvec, Mat(3, 1, CV_64FC1, Scalar::all(0)), rvec,
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Mat(3, 1, CV_64FC1, Scalar::all(0)), rvec, tvec);
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// Tvec, just move in z (camera) direction the specific distance
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tvec.ptr<double>(0)[0] = 0.;
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tvec.ptr<double>(0)[1] = 0.;
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tvec.ptr<double>(0)[2] = distance;
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}
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/**
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* @brief Create a synthetic image of a marker with perspective
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*/
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static Mat projectMarker(const aruco::Dictionary &dictionary, int id, Mat cameraMatrix, double yaw,
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double pitch, double distance, Size imageSize, int markerBorder,
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vector<Point2f> &corners, int encloseMarker=0) {
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// canonical image
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Mat marker, markerImg;
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const int markerSizePixels = 100;
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aruco::generateImageMarker(dictionary, id, markerSizePixels, marker, markerBorder);
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marker.copyTo(markerImg);
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if(encloseMarker){ //to enclose the marker
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int enclose = int(marker.rows/4);
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markerImg = Mat::zeros(marker.rows+(2*enclose), marker.cols+(enclose*2), CV_8UC1);
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Mat field= markerImg.rowRange(int(enclose), int(markerImg.rows-enclose))
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.colRange(int(0), int(markerImg.cols));
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field.setTo(255);
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field= markerImg.rowRange(int(0), int(markerImg.rows))
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.colRange(int(enclose), int(markerImg.cols-enclose));
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field.setTo(255);
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field = markerImg(Rect(enclose,enclose,marker.rows,marker.cols));
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marker.copyTo(field);
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}
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// get rvec and tvec for the perspective
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Mat rvec, tvec;
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getSyntheticRT(yaw, pitch, distance, rvec, tvec);
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const float markerLength = 0.05f;
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vector<Point3f> markerObjPoints;
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markerObjPoints.push_back(Point3f(-markerLength / 2.f, +markerLength / 2.f, 0));
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markerObjPoints.push_back(markerObjPoints[0] + Point3f(markerLength, 0, 0));
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markerObjPoints.push_back(markerObjPoints[0] + Point3f(markerLength, -markerLength, 0));
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markerObjPoints.push_back(markerObjPoints[0] + Point3f(0, -markerLength, 0));
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// project markers and draw them
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Mat distCoeffs(5, 1, CV_64FC1, Scalar::all(0));
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projectPoints(markerObjPoints, rvec, tvec, cameraMatrix, distCoeffs, corners);
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vector<Point2f> originalCorners;
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originalCorners.push_back(Point2f(0+float(encloseMarker*markerSizePixels/4), 0+float(encloseMarker*markerSizePixels/4)));
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originalCorners.push_back(originalCorners[0]+Point2f((float)markerSizePixels, 0));
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originalCorners.push_back(originalCorners[0]+Point2f((float)markerSizePixels, (float)markerSizePixels));
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originalCorners.push_back(originalCorners[0]+Point2f(0, (float)markerSizePixels));
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Mat transformation = getPerspectiveTransform(originalCorners, corners);
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Mat img(imageSize, CV_8UC1, Scalar::all(255));
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Mat aux;
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const char borderValue = 127;
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warpPerspective(markerImg, aux, transformation, imageSize, INTER_NEAREST, BORDER_CONSTANT,
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Scalar::all(borderValue));
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// copy only not-border pixels
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for(int y = 0; y < aux.rows; y++) {
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for(int x = 0; x < aux.cols; x++) {
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if(aux.at<unsigned char>(y, x) == borderValue) continue;
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img.at<unsigned char>(y, x) = aux.at<unsigned char>(y, x);
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}
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}
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return img;
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}
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enum class ArucoAlgParams
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{
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USE_DEFAULT = 0,
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USE_APRILTAG=1, /// Detect marker candidates :: using AprilTag
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DETECT_INVERTED_MARKER, /// Check if there is a white marker
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USE_ARUCO3 /// Check if aruco3 should be used
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};
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/**
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* @brief Draws markers in perspective and detect them
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*/
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class CV_ArucoDetectionPerspective : public cvtest::BaseTest {
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public:
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CV_ArucoDetectionPerspective(ArucoAlgParams arucoAlgParam) : arucoAlgParams(arucoAlgParam) {}
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protected:
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void run(int);
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ArucoAlgParams arucoAlgParams;
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};
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void CV_ArucoDetectionPerspective::run(int) {
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int iter = 0;
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int szEnclosed = 0;
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Mat cameraMatrix = Mat::eye(3, 3, CV_64FC1);
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Size imgSize(500, 500);
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cameraMatrix.at<double>(0, 0) = cameraMatrix.at<double>(1, 1) = 650;
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cameraMatrix.at<double>(0, 2) = imgSize.width / 2;
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cameraMatrix.at<double>(1, 2) = imgSize.height / 2;
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aruco::DetectorParameters params;
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params.minDistanceToBorder = 1;
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aruco::ArucoDetector detector(aruco::getPredefinedDictionary(aruco::DICT_6X6_250), params);
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// detect from different positions
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for(double distance : {0.1, 0.3, 0.5, 0.7}) {
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for(int pitch = 0; pitch < 360; pitch += (distance == 0.1? 60:180)) {
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for(int yaw = 70; yaw <= 120; yaw += 40){
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int currentId = iter % 250;
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int markerBorder = iter % 2 + 1;
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iter++;
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vector<Point2f> groundTruthCorners;
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aruco::DetectorParameters detectorParameters = params;
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detectorParameters.markerBorderBits = markerBorder;
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/// create synthetic image
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Mat img=
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projectMarker(detector.getDictionary(), currentId, cameraMatrix, deg2rad(yaw), deg2rad(pitch),
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distance, imgSize, markerBorder, groundTruthCorners, szEnclosed);
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// marker :: Inverted
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if(ArucoAlgParams::DETECT_INVERTED_MARKER == arucoAlgParams){
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img = ~img;
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detectorParameters.detectInvertedMarker = true;
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}
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if(ArucoAlgParams::USE_APRILTAG == arucoAlgParams){
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detectorParameters.cornerRefinementMethod = (int)aruco::CORNER_REFINE_APRILTAG;
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}
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if (ArucoAlgParams::USE_ARUCO3 == arucoAlgParams) {
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detectorParameters.useAruco3Detection = true;
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detectorParameters.cornerRefinementMethod = (int)aruco::CORNER_REFINE_SUBPIX;
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}
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detector.setDetectorParameters(detectorParameters);
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// detect markers
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vector<vector<Point2f> > corners;
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vector<int> ids;
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detector.detectMarkers(img, corners, ids);
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// check results
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if(ids.size() != 1 || (ids.size() == 1 && ids[0] != currentId)) {
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if(ids.size() != 1)
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ts->printf(cvtest::TS::LOG, "Incorrect number of detected markers");
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else
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ts->printf(cvtest::TS::LOG, "Incorrect marker id");
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
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return;
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}
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for(int c = 0; c < 4; c++) {
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double dist = cv::norm(groundTruthCorners[c] - corners[0][c]); // TODO cvtest
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if(dist > 5) {
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ts->printf(cvtest::TS::LOG, "Incorrect marker corners position");
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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return;
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}
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}
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}
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}
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// change the state :: to detect an enclosed inverted marker
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if(ArucoAlgParams::DETECT_INVERTED_MARKER == arucoAlgParams && distance == 0.1){
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distance -= 0.1;
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szEnclosed++;
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}
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}
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}
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// Helper struc and functions for CV_ArucoDetectionUnc
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struct ArucoUncTestConfig {
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// Number of bits (per dimension) for each cell of the marker when removing the perspective (default 4).
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int perspectiveRemovePixelPerCell;
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// Width of the margin of pixels on each cell not considered for the determination of the cell bit.
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// This parameter is relative to the total size of the cell.
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// For instance if the cell size is 40 pixels and the value of this parameter is 0.1, a margin of 40*0.1=4 pixels is ignored in the cells.
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float perspectiveRemoveIgnoredMarginPerCell;
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// Number of bits of the marker border, i.e. marker border width (default 1).
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int markerBorderBits;
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// Fraction of tempered (inverted) pixels per cell (area ratio, e.g. 0.02 for 2%)
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float invertPixelPercent;
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// Percentage of offset used for perspective distortion, bigger means more distorted
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float distortionRatio;
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};
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struct MarkerCreationConfig {
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int id; // Unique marker ID (will be offset per test run)
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int markerSidePixels; // Marker size (in pixels)
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int rotation; // Rotation of the marker in degrees (0, 90, 180, 270)
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};
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/**
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* @brief Create a synthetic image of a marker
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* Applies an optional rotation and an optional perspective warp to simulate a distorted marker.
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* Inverts a square region within each cell (including borders) to simulate uncertainty in detection.
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* Computes the ground-truth uncertainty as the ratio of inverted area to the total marker area.
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*/
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Mat generateMarkerImage(const MarkerCreationConfig &markerConfig, const ArucoUncTestConfig &detectorConfig,
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const aruco::Dictionary &dictionary, double &groundTruthUnc)
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{
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Mat marker;
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// Generate the synthetic marker image
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aruco::generateImageMarker(dictionary, markerConfig.id, markerConfig.markerSidePixels,
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marker, detectorConfig.markerBorderBits);
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// Rotate the marker if needed.
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if (markerConfig.rotation == 90) {
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cv::transpose(marker, marker);
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cv::flip(marker, marker, 0);
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} else if (markerConfig.rotation == 180) {
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cv::flip(marker, marker, -1);
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} else if (markerConfig.rotation == 270) {
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cv::transpose(marker, marker);
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cv::flip(marker, marker, 1);
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}
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// Compute the number of cells in one dimension.
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const int markerSizeWithBorders = dictionary.markerSize + 2 * detectorConfig.markerBorderBits;
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const int cellSidePixelsSize = markerConfig.markerSidePixels / markerSizeWithBorders;
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// We want the inverted square area to have an area ratio equal to invertPixelPercent.
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// That is: (cellSidePixelsInvert/cellSidePixelsSize)^2 = invertPixelPercent.
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int cellSidePixelsInvert = int(cellSidePixelsSize * std::sqrt(detectorConfig.invertPixelPercent));
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int cellMarginPixels = (cellSidePixelsSize - cellSidePixelsInvert) / 2;
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int numCellsInverted = 0;
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// Loop over each cell in the marker grid.
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if (cellSidePixelsInvert > 0) {
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for (int row = 0; row < markerSizeWithBorders; row++) {
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for (int col = 0; col < markerSizeWithBorders; col++) {
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int xStart = col * cellSidePixelsSize + cellMarginPixels;
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int yStart = row * cellSidePixelsSize + cellMarginPixels;
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Rect cellRect(xStart, yStart, cellSidePixelsInvert, cellSidePixelsInvert);
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Mat cellROI = marker(cellRect);
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bitwise_not(cellROI, cellROI);
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numCellsInverted++;
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}
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}
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}
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// Compute ground-truth uncertainty as (inverted area)/(total marker area).
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groundTruthUnc = (numCellsInverted * cellSidePixelsInvert * cellSidePixelsInvert) /
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static_cast<double>(markerConfig.markerSidePixels * markerConfig.markerSidePixels);
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// Optionally apply a distortion (a perspective warp) to simulate a non-ideal capture.
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if (detectorConfig.distortionRatio > 0.f) {
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vector<Point2f> src = { {0, 0},
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{static_cast<float>(marker.cols), 0},
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{static_cast<float>(marker.cols), static_cast<float>(marker.rows)},
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{0, static_cast<float>(marker.rows)} };
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float offset = marker.cols * detectorConfig.distortionRatio; // distortionRatio % offset for distortion
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vector<Point2f> dst = { {offset, offset},
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{marker.cols - offset, 0},
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{marker.cols - offset, marker.rows - offset},
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{0, marker.rows - offset} };
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Mat M = getPerspectiveTransform(src, dst);
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warpPerspective(marker, marker, M, marker.size(), INTER_LINEAR, BORDER_CONSTANT, Scalar(255));
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}
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return marker;
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}
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/**
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* @brief Copies a marker image into a larger image at the given top-left position.
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*/
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void placeMarker(Mat &img, const Mat &marker, const Point2f &topLeft)
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{
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Rect roi(Point(static_cast<int>(topLeft.x), static_cast<int>(topLeft.y)), marker.size());
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marker.copyTo(img(roi));
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}
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/**
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* @brief Test the marker uncertainty computations.
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* Loops over a set of detector configurations (expected uncertainty, distortion, DetectorParameters such as markerBorderBits)
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* For each configuration, it creates a synthetic image containing four markers arranged in a 2x2 grid.
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* Each marker is generated with its own configuration (id, size, rotation).
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* Finally, it runs the detector and checks that each marker is detected and
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* that its computed uncertainty is close to the ground truth value.
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*/
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|
class CV_ArucoDetectionUnc : public cvtest::BaseTest {
|
|
public:
|
|
// The parameter arucoAlgParam allows switching between detecting normal and inverted markers.
|
|
CV_ArucoDetectionUnc(ArucoAlgParams algParam) : arucoAlgParam(algParam) {}
|
|
|
|
protected:
|
|
void run(int);
|
|
ArucoAlgParams arucoAlgParam;
|
|
};
|
|
|
|
|
|
void CV_ArucoDetectionUnc::run(int) {
|
|
|
|
aruco::DetectorParameters params;
|
|
aruco::ArucoDetector detector(aruco::getPredefinedDictionary(aruco::DICT_6X6_250), params);
|
|
|
|
const bool detectInvertedMarker = (arucoAlgParam == ArucoAlgParams::DETECT_INVERTED_MARKER);
|
|
|
|
// Define several detector configurations to test different settings.
|
|
// perspectiveRemovePixelPerCell, perspectiveRemoveIgnoredMarginPerCell, markerBorderBits, invertPixelPercent, distortionRatio
|
|
vector<ArucoUncTestConfig> detectorConfigs = {
|
|
// No margins, No distortion
|
|
{8, 0.0f, 1, 0.0f, 0.f},
|
|
{8, 0.0f, 1, 0.01f, 0.f},
|
|
{8, 0.0f, 2, 0.05f, 0.f},
|
|
{8, 0.0f, 1, 0.1f, 0.f},
|
|
// Margins, No distortion
|
|
{8, 0.05f, 1, 0.0f, 0.f},
|
|
{8, 0.05f, 2, 0.01f, 0.f},
|
|
{8, 0.1f, 3, 0.05f, 0.f},
|
|
{8, 0.15f, 1, 0.1f, 0.f},
|
|
// No margins, distortion
|
|
{8, 0.0f, 1, 0.0f, 0.01f},
|
|
{8, 0.0f, 1, 0.01f, 0.02f},
|
|
{8, 0.0f, 2, 0.05f, 0.05f},
|
|
{8, 0.0f, 1, 0.1f, 0.1f},
|
|
{8, 0.0f, 2, 0.1f, 0.2f},
|
|
// Margins, distortion
|
|
{8, 0.05f, 2, 0.0f, 0.01f},
|
|
{8, 0.05f, 1, 0.01f, 0.02f},
|
|
{8, 0.1f, 2, 0.05f, 0.05f},
|
|
{8, 0.15f, 1, 0.1f, 0.1f},
|
|
{8, 0.0f, 1, 0.1f, 0.2f},
|
|
};
|
|
|
|
// Define marker configurations for the 4 markers.
|
|
const int markerSidePixels = 480;
|
|
// id, markerSidePixels, rotation
|
|
vector<MarkerCreationConfig> markerCreationConfig = {
|
|
{0, markerSidePixels, 90, },
|
|
{1, markerSidePixels, 270,},
|
|
{2, markerSidePixels, 0, },
|
|
{3, markerSidePixels, 180,}
|
|
};
|
|
|
|
// Loop over each detector configuration.
|
|
for (size_t cfgIdx = 0; cfgIdx < detectorConfigs.size(); cfgIdx++) {
|
|
ArucoUncTestConfig detCfg = detectorConfigs[cfgIdx];
|
|
|
|
// Update detector parameters.
|
|
params.perspectiveRemovePixelPerCell = detCfg.perspectiveRemovePixelPerCell;
|
|
params.perspectiveRemoveIgnoredMarginPerCell = detCfg.perspectiveRemoveIgnoredMarginPerCell;
|
|
params.markerBorderBits = detCfg.markerBorderBits;
|
|
params.detectInvertedMarker = detectInvertedMarker;
|
|
detector.setDetectorParameters(params);
|
|
|
|
// Create a blank image large enough to hold 4 markers in a 2x2 grid.
|
|
const int margin = markerSidePixels / 2;
|
|
const int imageSize = (markerSidePixels * 2) + margin * 3;
|
|
Mat img(imageSize, imageSize, CV_8UC1, Scalar(255));
|
|
|
|
vector<double> groundTruthUncs;
|
|
vector<int> groundTruthIds;
|
|
const aruco::Dictionary &dictionary = detector.getDictionary();
|
|
|
|
// Place each marker into the image.
|
|
for (int row = 0; row < 2; row++) {
|
|
for (int col = 0; col < 2; col++) {
|
|
int index = row * 2 + col;
|
|
MarkerCreationConfig markerCfg = markerCreationConfig[index];
|
|
// Adjust marker id to be unique for each detector configuration.
|
|
markerCfg.id += static_cast<int>(cfgIdx * markerCreationConfig.size());
|
|
groundTruthIds.push_back(markerCfg.id);
|
|
|
|
double gtUnc = 0.0;
|
|
Mat markerImg = generateMarkerImage(markerCfg, detCfg, dictionary, gtUnc);
|
|
groundTruthUncs.push_back(gtUnc);
|
|
|
|
// Place marker in the image.
|
|
Point2f topLeft(margin + col * (markerSidePixels + margin),
|
|
margin + row * (markerSidePixels + margin));
|
|
placeMarker(img, markerImg, topLeft);
|
|
}
|
|
}
|
|
|
|
// If testing inverted markers globally, invert the whole image.
|
|
if (detectInvertedMarker) {
|
|
bitwise_not(img, img);
|
|
}
|
|
|
|
// Run detection.
|
|
vector<vector<Point2f>> corners, rejected;
|
|
vector<int> ids;
|
|
vector<float> markerUnc;
|
|
detector.detectMarkersWithUnc(img, corners, ids, rejected, markerUnc);
|
|
|
|
// Verify that every marker is detected and its uncertainty is within tolerance.
|
|
for (size_t m = 0; m < groundTruthIds.size(); m++) {
|
|
int detectedIdx = -1;
|
|
for (size_t k = 0; k < ids.size(); k++) {
|
|
if (groundTruthIds[m] == ids[k]) {
|
|
detectedIdx = static_cast<int>(k);
|
|
break;
|
|
}
|
|
}
|
|
if (detectedIdx == -1) {
|
|
ts->printf(cvtest::TS::LOG, "Marker id %d: not detected (detector config %zu)\n",
|
|
groundTruthIds[m], cfgIdx);
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
|
|
return;
|
|
}
|
|
double diff = fabs(groundTruthUncs[m] - markerUnc[detectedIdx]);
|
|
if (diff > 0.05) {
|
|
ts->printf(cvtest::TS::LOG,
|
|
"Marker id %d: computed uncertainty %.2f differs from ground truth %.2f (diff=%.2f) (detector config %zu)\n",
|
|
groundTruthIds[m], markerUnc[detectedIdx], groundTruthUncs[m], diff, cfgIdx);
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/**
|
|
* @brief Check max and min size in marker detection parameters
|
|
*/
|
|
class CV_ArucoDetectionMarkerSize : public cvtest::BaseTest {
|
|
public:
|
|
CV_ArucoDetectionMarkerSize();
|
|
|
|
protected:
|
|
void run(int);
|
|
};
|
|
|
|
|
|
CV_ArucoDetectionMarkerSize::CV_ArucoDetectionMarkerSize() {}
|
|
|
|
|
|
void CV_ArucoDetectionMarkerSize::run(int) {
|
|
aruco::DetectorParameters params;
|
|
aruco::ArucoDetector detector(aruco::getPredefinedDictionary(aruco::DICT_6X6_250), params);
|
|
int markerSide = 20;
|
|
int imageSize = 200;
|
|
|
|
// 10 cases
|
|
for(int i = 0; i < 10; i++) {
|
|
Mat marker;
|
|
int id = 10 + i * 20;
|
|
|
|
// create synthetic image
|
|
Mat img = Mat(imageSize, imageSize, CV_8UC1, Scalar::all(255));
|
|
aruco::generateImageMarker(detector.getDictionary(), id, markerSide, marker);
|
|
Mat aux = img.colRange(30, 30 + markerSide).rowRange(50, 50 + markerSide);
|
|
marker.copyTo(aux);
|
|
|
|
vector<vector<Point2f> > corners;
|
|
vector<int> ids;
|
|
|
|
// set a invalid minMarkerPerimeterRate
|
|
aruco::DetectorParameters detectorParameters = params;
|
|
detectorParameters.minMarkerPerimeterRate = min(4., (4. * markerSide) / float(imageSize) + 0.1);
|
|
detector.setDetectorParameters(detectorParameters);
|
|
detector.detectMarkers(img, corners, ids);
|
|
if(corners.size() != 0) {
|
|
ts->printf(cvtest::TS::LOG, "Error in DetectorParameters::minMarkerPerimeterRate");
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
|
return;
|
|
}
|
|
|
|
// set an valid minMarkerPerimeterRate
|
|
detectorParameters = params;
|
|
detectorParameters.minMarkerPerimeterRate = max(0., (4. * markerSide) / float(imageSize) - 0.1);
|
|
detector.setDetectorParameters(detectorParameters);
|
|
detector.detectMarkers(img, corners, ids);
|
|
if(corners.size() != 1 || (corners.size() == 1 && ids[0] != id)) {
|
|
ts->printf(cvtest::TS::LOG, "Error in DetectorParameters::minMarkerPerimeterRate");
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
|
return;
|
|
}
|
|
|
|
// set a invalid maxMarkerPerimeterRate
|
|
detectorParameters = params;
|
|
detectorParameters.maxMarkerPerimeterRate = min(4., (4. * markerSide) / float(imageSize) - 0.1);
|
|
detector.setDetectorParameters(detectorParameters);
|
|
detector.detectMarkers(img, corners, ids);
|
|
if(corners.size() != 0) {
|
|
ts->printf(cvtest::TS::LOG, "Error in DetectorParameters::maxMarkerPerimeterRate");
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
|
return;
|
|
}
|
|
|
|
// set an valid maxMarkerPerimeterRate
|
|
detectorParameters = params;
|
|
detectorParameters.maxMarkerPerimeterRate = max(0., (4. * markerSide) / float(imageSize) + 0.1);
|
|
detector.setDetectorParameters(detectorParameters);
|
|
detector.detectMarkers(img, corners, ids);
|
|
if(corners.size() != 1 || (corners.size() == 1 && ids[0] != id)) {
|
|
ts->printf(cvtest::TS::LOG, "Error in DetectorParameters::maxMarkerPerimeterRate");
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
/**
|
|
* @brief Check error correction in marker bits
|
|
*/
|
|
class CV_ArucoBitCorrection : public cvtest::BaseTest {
|
|
public:
|
|
CV_ArucoBitCorrection();
|
|
|
|
protected:
|
|
void run(int);
|
|
};
|
|
|
|
|
|
CV_ArucoBitCorrection::CV_ArucoBitCorrection() {}
|
|
|
|
|
|
void CV_ArucoBitCorrection::run(int) {
|
|
|
|
aruco::Dictionary dictionary1 = aruco::getPredefinedDictionary(aruco::DICT_6X6_250);
|
|
aruco::Dictionary dictionary2 = aruco::getPredefinedDictionary(aruco::DICT_6X6_250);
|
|
aruco::DetectorParameters params;
|
|
aruco::ArucoDetector detector1(dictionary1, params);
|
|
int markerSide = 50;
|
|
int imageSize = 150;
|
|
|
|
// 10 markers
|
|
for(int l = 0; l < 10; l++) {
|
|
Mat marker;
|
|
int id = 10 + l * 20;
|
|
|
|
Mat currentCodeBytes = dictionary1.bytesList.rowRange(id, id + 1);
|
|
aruco::DetectorParameters detectorParameters = detector1.getDetectorParameters();
|
|
// 5 valid cases
|
|
for(int i = 0; i < 5; i++) {
|
|
// how many bit errors (the error is low enough so it can be corrected)
|
|
detectorParameters.errorCorrectionRate = 0.2 + i * 0.1;
|
|
detector1.setDetectorParameters(detectorParameters);
|
|
int errors =
|
|
(int)std::floor(dictionary1.maxCorrectionBits * detector1.getDetectorParameters().errorCorrectionRate - 1.);
|
|
|
|
// create erroneous marker in currentCodeBits
|
|
Mat currentCodeBits =
|
|
aruco::Dictionary::getBitsFromByteList(currentCodeBytes, dictionary1.markerSize);
|
|
for(int e = 0; e < errors; e++) {
|
|
currentCodeBits.ptr<unsigned char>()[2 * e] =
|
|
!currentCodeBits.ptr<unsigned char>()[2 * e];
|
|
}
|
|
|
|
// add erroneous marker to dictionary2 in order to create the erroneous marker image
|
|
Mat currentCodeBytesError = aruco::Dictionary::getByteListFromBits(currentCodeBits);
|
|
currentCodeBytesError.copyTo(dictionary2.bytesList.rowRange(id, id + 1));
|
|
Mat img = Mat(imageSize, imageSize, CV_8UC1, Scalar::all(255));
|
|
dictionary2.generateImageMarker(id, markerSide, marker);
|
|
Mat aux = img.colRange(30, 30 + markerSide).rowRange(50, 50 + markerSide);
|
|
marker.copyTo(aux);
|
|
|
|
// try to detect using original dictionary
|
|
vector<vector<Point2f> > corners;
|
|
vector<int> ids;
|
|
detector1.detectMarkers(img, corners, ids);
|
|
if(corners.size() != 1 || (corners.size() == 1 && ids[0] != id)) {
|
|
ts->printf(cvtest::TS::LOG, "Error in bit correction");
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
|
return;
|
|
}
|
|
}
|
|
|
|
// 5 invalid cases
|
|
for(int i = 0; i < 5; i++) {
|
|
// how many bit errors (the error is too high to be corrected)
|
|
detectorParameters.errorCorrectionRate = 0.2 + i * 0.1;
|
|
detector1.setDetectorParameters(detectorParameters);
|
|
int errors =
|
|
(int)std::floor(dictionary1.maxCorrectionBits * detector1.getDetectorParameters().errorCorrectionRate + 1.);
|
|
|
|
// create erroneous marker in currentCodeBits
|
|
Mat currentCodeBits =
|
|
aruco::Dictionary::getBitsFromByteList(currentCodeBytes, dictionary1.markerSize);
|
|
for(int e = 0; e < errors; e++) {
|
|
currentCodeBits.ptr<unsigned char>()[2 * e] =
|
|
!currentCodeBits.ptr<unsigned char>()[2 * e];
|
|
}
|
|
|
|
// dictionary3 is only composed by the modified marker (in its original form)
|
|
aruco::Dictionary _dictionary3 = aruco::Dictionary(
|
|
dictionary2.bytesList.rowRange(id, id + 1).clone(),
|
|
dictionary1.markerSize,
|
|
dictionary1.maxCorrectionBits);
|
|
aruco::ArucoDetector detector3(_dictionary3, detector1.getDetectorParameters());
|
|
// add erroneous marker to dictionary2 in order to create the erroneous marker image
|
|
Mat currentCodeBytesError = aruco::Dictionary::getByteListFromBits(currentCodeBits);
|
|
currentCodeBytesError.copyTo(dictionary2.bytesList.rowRange(id, id + 1));
|
|
Mat img = Mat(imageSize, imageSize, CV_8UC1, Scalar::all(255));
|
|
dictionary2.generateImageMarker(id, markerSide, marker);
|
|
Mat aux = img.colRange(30, 30 + markerSide).rowRange(50, 50 + markerSide);
|
|
marker.copyTo(aux);
|
|
|
|
// try to detect using dictionary3, it should fail
|
|
vector<vector<Point2f> > corners;
|
|
vector<int> ids;
|
|
detector3.detectMarkers(img, corners, ids);
|
|
if(corners.size() != 0) {
|
|
ts->printf(cvtest::TS::LOG, "Error in DetectorParameters::errorCorrectionRate");
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
typedef CV_ArucoDetectionPerspective CV_AprilTagDetectionPerspective;
|
|
typedef CV_ArucoDetectionPerspective CV_InvertedArucoDetectionPerspective;
|
|
typedef CV_ArucoDetectionPerspective CV_Aruco3DetectionPerspective;
|
|
|
|
TEST(CV_InvertedArucoDetectionPerspective, algorithmic) {
|
|
CV_InvertedArucoDetectionPerspective test(ArucoAlgParams::DETECT_INVERTED_MARKER);
|
|
test.safe_run();
|
|
}
|
|
|
|
TEST(CV_AprilTagDetectionPerspective, algorithmic) {
|
|
CV_AprilTagDetectionPerspective test(ArucoAlgParams::USE_APRILTAG);
|
|
test.safe_run();
|
|
}
|
|
|
|
TEST(CV_Aruco3DetectionPerspective, algorithmic) {
|
|
CV_Aruco3DetectionPerspective test(ArucoAlgParams::USE_ARUCO3);
|
|
test.safe_run();
|
|
}
|
|
|
|
TEST(CV_ArucoDetectionSimple, algorithmic) {
|
|
CV_ArucoDetectionSimple test;
|
|
test.safe_run();
|
|
}
|
|
|
|
TEST(CV_ArucoDetectionPerspective, algorithmic) {
|
|
CV_ArucoDetectionPerspective test(ArucoAlgParams::USE_DEFAULT);
|
|
test.safe_run();
|
|
}
|
|
|
|
TEST(CV_ArucoDetectionMarkerSize, algorithmic) {
|
|
CV_ArucoDetectionMarkerSize test;
|
|
test.safe_run();
|
|
}
|
|
|
|
TEST(CV_ArucoBitCorrection, algorithmic) {
|
|
CV_ArucoBitCorrection test;
|
|
test.safe_run();
|
|
}
|
|
|
|
typedef CV_ArucoDetectionUnc CV_InvertedArucoDetectionUnc;
|
|
|
|
TEST(CV_ArucoDetectionUnc, algorithmic) {
|
|
CV_ArucoDetectionUnc test(ArucoAlgParams::USE_DEFAULT);
|
|
test.safe_run();
|
|
}
|
|
|
|
TEST(CV_InvertedArucoDetectionUnc, algorithmic) {
|
|
CV_InvertedArucoDetectionUnc test(ArucoAlgParams::DETECT_INVERTED_MARKER);
|
|
test.safe_run();
|
|
}
|
|
|
|
TEST(CV_ArucoDetectMarkers, regression_3192)
|
|
{
|
|
aruco::ArucoDetector detector(aruco::getPredefinedDictionary(aruco::DICT_4X4_50));
|
|
vector<int> markerIds;
|
|
vector<vector<Point2f> > markerCorners;
|
|
string imgPath = cvtest::findDataFile("aruco/regression_3192.png");
|
|
Mat image = imread(imgPath);
|
|
const size_t N = 2ull;
|
|
const int goldCorners[N][8] = { {345,120, 520,120, 520,295, 345,295}, {101,114, 270,112, 276,287, 101,287} };
|
|
const int goldCornersIds[N] = { 6, 4 };
|
|
map<int, const int*> mapGoldCorners;
|
|
for (size_t i = 0; i < N; i++)
|
|
mapGoldCorners[goldCornersIds[i]] = goldCorners[i];
|
|
|
|
detector.detectMarkers(image, markerCorners, markerIds);
|
|
|
|
ASSERT_EQ(N, markerIds.size());
|
|
for (size_t i = 0; i < N; i++)
|
|
{
|
|
int arucoId = markerIds[i];
|
|
ASSERT_EQ(4ull, markerCorners[i].size());
|
|
ASSERT_TRUE(mapGoldCorners.find(arucoId) != mapGoldCorners.end());
|
|
for (int j = 0; j < 4; j++)
|
|
{
|
|
EXPECT_NEAR(static_cast<float>(mapGoldCorners[arucoId][j * 2]), markerCorners[i][j].x, 1.f);
|
|
EXPECT_NEAR(static_cast<float>(mapGoldCorners[arucoId][j * 2 + 1]), markerCorners[i][j].y, 1.f);
|
|
}
|
|
}
|
|
}
|
|
|
|
TEST(CV_ArucoDetectMarkers, regression_2492)
|
|
{
|
|
aruco::ArucoDetector detector(aruco::getPredefinedDictionary(aruco::DICT_5X5_50));
|
|
aruco::DetectorParameters detectorParameters = detector.getDetectorParameters();
|
|
detectorParameters.minMarkerDistanceRate = 0.026;
|
|
detector.setDetectorParameters(detectorParameters);
|
|
vector<int> markerIds;
|
|
vector<vector<Point2f> > markerCorners;
|
|
string imgPath = cvtest::findDataFile("aruco/regression_2492.png");
|
|
Mat image = imread(imgPath);
|
|
const size_t N = 8ull;
|
|
const int goldCorners[N][8] = { {179,139, 179,95, 223,95, 223,139}, {99,139, 99,95, 143,95, 143,139},
|
|
{19,139, 19,95, 63,95, 63,139}, {256,140, 256,93, 303,93, 303,140},
|
|
{256,62, 259,21, 300,23, 297,64}, {99,21, 143,17, 147,60, 103,64},
|
|
{69,61, 28,61, 14,21, 58,17}, {174,62, 182,13, 230,19, 223,68} };
|
|
const int goldCornersIds[N] = {13, 13, 13, 13, 1, 15, 14, 4};
|
|
map<int, vector<const int*> > mapGoldCorners;
|
|
for (size_t i = 0; i < N; i++)
|
|
mapGoldCorners[goldCornersIds[i]].push_back(goldCorners[i]);
|
|
|
|
detector.detectMarkers(image, markerCorners, markerIds);
|
|
|
|
ASSERT_EQ(N, markerIds.size());
|
|
for (size_t i = 0; i < N; i++)
|
|
{
|
|
int arucoId = markerIds[i];
|
|
ASSERT_EQ(4ull, markerCorners[i].size());
|
|
ASSERT_TRUE(mapGoldCorners.find(arucoId) != mapGoldCorners.end());
|
|
float totalDist = 8.f;
|
|
for (size_t k = 0ull; k < mapGoldCorners[arucoId].size(); k++)
|
|
{
|
|
float dist = 0.f;
|
|
for (int j = 0; j < 4; j++) // total distance up to 4 points
|
|
{
|
|
dist += abs(mapGoldCorners[arucoId][k][j * 2] - markerCorners[i][j].x);
|
|
dist += abs(mapGoldCorners[arucoId][k][j * 2 + 1] - markerCorners[i][j].y);
|
|
}
|
|
totalDist = min(totalDist, dist);
|
|
}
|
|
EXPECT_LT(totalDist, 8.f);
|
|
}
|
|
}
|
|
|
|
|
|
TEST(CV_ArucoDetectMarkers, regression_contour_24220)
|
|
{
|
|
aruco::ArucoDetector detector;
|
|
vector<int> markerIds;
|
|
vector<vector<Point2f> > markerCorners;
|
|
string imgPath = cvtest::findDataFile("aruco/failmask9.png");
|
|
Mat image = imread(imgPath);
|
|
|
|
const size_t N = 1ull;
|
|
const int goldCorners[8] = {392,175, 99,257, 117,109, 365,44};
|
|
const int goldCornersId = 0;
|
|
|
|
detector.detectMarkers(image, markerCorners, markerIds);
|
|
|
|
ASSERT_EQ(N, markerIds.size());
|
|
ASSERT_EQ(4ull, markerCorners[0].size());
|
|
ASSERT_EQ(goldCornersId, markerIds[0]);
|
|
for (int j = 0; j < 4; j++)
|
|
{
|
|
EXPECT_NEAR(static_cast<float>(goldCorners[j * 2]), markerCorners[0][j].x, 1.f);
|
|
EXPECT_NEAR(static_cast<float>(goldCorners[j * 2 + 1]), markerCorners[0][j].y, 1.f);
|
|
}
|
|
}
|
|
|
|
TEST(CV_ArucoMultiDict, setGetDictionaries)
|
|
{
|
|
vector<aruco::Dictionary> dictionaries = {aruco::getPredefinedDictionary(aruco::DICT_4X4_50), aruco::getPredefinedDictionary(aruco::DICT_5X5_100)};
|
|
aruco::ArucoDetector detector(dictionaries);
|
|
vector<aruco::Dictionary> dicts = detector.getDictionaries();
|
|
ASSERT_EQ(dicts.size(), 2ul);
|
|
EXPECT_EQ(dicts[0].markerSize, 4);
|
|
EXPECT_EQ(dicts[1].markerSize, 5);
|
|
dictionaries.clear();
|
|
dictionaries.push_back(aruco::getPredefinedDictionary(aruco::DICT_6X6_100));
|
|
dictionaries.push_back(aruco::getPredefinedDictionary(aruco::DICT_7X7_250));
|
|
dictionaries.push_back(aruco::getPredefinedDictionary(aruco::DICT_APRILTAG_25h9));
|
|
detector.setDictionaries(dictionaries);
|
|
dicts = detector.getDictionaries();
|
|
ASSERT_EQ(dicts.size(), 3ul);
|
|
EXPECT_EQ(dicts[0].markerSize, 6);
|
|
EXPECT_EQ(dicts[1].markerSize, 7);
|
|
EXPECT_EQ(dicts[2].markerSize, 5);
|
|
auto dict = detector.getDictionary();
|
|
EXPECT_EQ(dict.markerSize, 6);
|
|
detector.setDictionary(aruco::getPredefinedDictionary(aruco::DICT_APRILTAG_16h5));
|
|
dicts = detector.getDictionaries();
|
|
ASSERT_EQ(dicts.size(), 3ul);
|
|
EXPECT_EQ(dicts[0].markerSize, 4);
|
|
EXPECT_EQ(dicts[1].markerSize, 7);
|
|
EXPECT_EQ(dicts[2].markerSize, 5);
|
|
}
|
|
|
|
|
|
TEST(CV_ArucoMultiDict, noDict)
|
|
{
|
|
aruco::ArucoDetector detector;
|
|
EXPECT_THROW({
|
|
detector.setDictionaries({});
|
|
}, Exception);
|
|
}
|
|
|
|
|
|
TEST(CV_ArucoMultiDict, multiMarkerDetection)
|
|
{
|
|
const int markerSidePixels = 100;
|
|
const int imageSize = markerSidePixels * 2 + 3 * (markerSidePixels / 2);
|
|
vector<aruco::Dictionary> usedDictionaries;
|
|
|
|
// draw synthetic image
|
|
Mat img = Mat(imageSize, imageSize, CV_8UC1, Scalar::all(255));
|
|
for(int y = 0; y < 2; y++) {
|
|
for(int x = 0; x < 2; x++) {
|
|
Mat marker;
|
|
int id = y * 2 + x;
|
|
int dictId = x * 4 + y * 8;
|
|
auto dict = aruco::getPredefinedDictionary(dictId);
|
|
usedDictionaries.push_back(dict);
|
|
aruco::generateImageMarker(dict, id, markerSidePixels, marker);
|
|
Point2f firstCorner(markerSidePixels / 2.f + x * (1.5f * markerSidePixels),
|
|
markerSidePixels / 2.f + y * (1.5f * markerSidePixels));
|
|
Mat aux = img(Rect((int)firstCorner.x, (int)firstCorner.y, markerSidePixels, markerSidePixels));
|
|
marker.copyTo(aux);
|
|
}
|
|
}
|
|
img.convertTo(img, CV_8UC3);
|
|
|
|
aruco::ArucoDetector detector(usedDictionaries);
|
|
|
|
vector<vector<Point2f> > markerCorners;
|
|
vector<int> markerIds;
|
|
vector<vector<Point2f> > rejectedImgPts;
|
|
vector<int> dictIds;
|
|
detector.detectMarkersMultiDict(img, markerCorners, markerIds, rejectedImgPts, dictIds);
|
|
ASSERT_EQ(markerIds.size(), 4u);
|
|
ASSERT_EQ(dictIds.size(), 4u);
|
|
for (size_t i = 0; i < dictIds.size(); ++i) {
|
|
EXPECT_EQ(dictIds[i], (int)i);
|
|
}
|
|
}
|
|
|
|
|
|
TEST(CV_ArucoMultiDict, multiMarkerDoubleDetection)
|
|
{
|
|
const int markerSidePixels = 100;
|
|
const int imageWidth = 2 * markerSidePixels + 3 * (markerSidePixels / 2);
|
|
const int imageHeight = markerSidePixels + 2 * (markerSidePixels / 2);
|
|
vector<aruco::Dictionary> usedDictionaries = {
|
|
aruco::getPredefinedDictionary(aruco::DICT_5X5_50),
|
|
aruco::getPredefinedDictionary(aruco::DICT_5X5_100)
|
|
};
|
|
|
|
// draw synthetic image
|
|
Mat img = Mat(imageHeight, imageWidth, CV_8UC1, Scalar::all(255));
|
|
for(int y = 0; y < 2; y++) {
|
|
Mat marker;
|
|
int id = 49 + y;
|
|
auto dict = aruco::getPredefinedDictionary(aruco::DICT_5X5_100);
|
|
aruco::generateImageMarker(dict, id, markerSidePixels, marker);
|
|
Point2f firstCorner(markerSidePixels / 2.f + y * (1.5f * markerSidePixels),
|
|
markerSidePixels / 2.f);
|
|
Mat aux = img(Rect((int)firstCorner.x, (int)firstCorner.y, markerSidePixels, markerSidePixels));
|
|
marker.copyTo(aux);
|
|
}
|
|
img.convertTo(img, CV_8UC3);
|
|
|
|
aruco::ArucoDetector detector(usedDictionaries);
|
|
|
|
vector<vector<Point2f> > markerCorners;
|
|
vector<int> markerIds;
|
|
vector<vector<Point2f> > rejectedImgPts;
|
|
vector<int> dictIds;
|
|
detector.detectMarkersMultiDict(img, markerCorners, markerIds, rejectedImgPts, dictIds);
|
|
ASSERT_EQ(markerIds.size(), 3u);
|
|
ASSERT_EQ(dictIds.size(), 3u);
|
|
EXPECT_EQ(dictIds[0], 0); // 5X5_50
|
|
EXPECT_EQ(dictIds[1], 1); // 5X5_100
|
|
EXPECT_EQ(dictIds[2], 1); // 5X5_100
|
|
}
|
|
|
|
|
|
TEST(CV_ArucoMultiDict, serialization)
|
|
{
|
|
aruco::ArucoDetector detector;
|
|
{
|
|
FileStorage fs_out(".json", FileStorage::WRITE + FileStorage::MEMORY);
|
|
ASSERT_TRUE(fs_out.isOpened());
|
|
detector.write(fs_out);
|
|
std::string serialized_string = fs_out.releaseAndGetString();
|
|
FileStorage test_fs(serialized_string, FileStorage::Mode::READ + FileStorage::MEMORY);
|
|
ASSERT_TRUE(test_fs.isOpened());
|
|
aruco::ArucoDetector test_detector;
|
|
test_detector.read(test_fs.root());
|
|
// compare default constructor result
|
|
EXPECT_EQ(aruco::getPredefinedDictionary(aruco::DICT_4X4_50), test_detector.getDictionary());
|
|
}
|
|
detector.setDictionaries({aruco::getPredefinedDictionary(aruco::DICT_4X4_50), aruco::getPredefinedDictionary(aruco::DICT_5X5_100)});
|
|
{
|
|
FileStorage fs_out(".json", FileStorage::WRITE + FileStorage::MEMORY);
|
|
ASSERT_TRUE(fs_out.isOpened());
|
|
detector.write(fs_out);
|
|
std::string serialized_string = fs_out.releaseAndGetString();
|
|
FileStorage test_fs(serialized_string, FileStorage::Mode::READ + FileStorage::MEMORY);
|
|
ASSERT_TRUE(test_fs.isOpened());
|
|
aruco::ArucoDetector test_detector;
|
|
test_detector.read(test_fs.root());
|
|
// check for one additional dictionary
|
|
auto dicts = test_detector.getDictionaries();
|
|
ASSERT_EQ(2ul, dicts.size());
|
|
EXPECT_EQ(aruco::getPredefinedDictionary(aruco::DICT_4X4_50), dicts[0]);
|
|
EXPECT_EQ(aruco::getPredefinedDictionary(aruco::DICT_5X5_100), dicts[1]);
|
|
}
|
|
}
|
|
|
|
|
|
struct ArucoThreading: public testing::TestWithParam<aruco::CornerRefineMethod>
|
|
{
|
|
struct NumThreadsSetter {
|
|
NumThreadsSetter(const int num_threads)
|
|
: original_num_threads_(getNumThreads()) {
|
|
setNumThreads(num_threads);
|
|
}
|
|
|
|
~NumThreadsSetter() {
|
|
setNumThreads(original_num_threads_);
|
|
}
|
|
private:
|
|
int original_num_threads_;
|
|
};
|
|
};
|
|
|
|
TEST_P(ArucoThreading, number_of_threads_does_not_change_results)
|
|
{
|
|
// We are not testing against different dictionaries
|
|
// As we are interested mostly in small images, smaller
|
|
// markers is better -> 4x4
|
|
aruco::ArucoDetector detector(aruco::getPredefinedDictionary(aruco::DICT_4X4_50));
|
|
|
|
// Height of the test image can be chosen quite freely
|
|
// We aim to test against small images as in those the
|
|
// number of threads has most effect
|
|
const int height_img = 20;
|
|
// Just to get nice white boarder
|
|
const int shift = height_img > 10 ? 5 : 1;
|
|
const int height_marker = height_img-2*shift;
|
|
|
|
// Create a test image
|
|
Mat img_marker;
|
|
aruco::generateImageMarker(detector.getDictionary(), 23, height_marker, img_marker, 1);
|
|
|
|
// Copy to bigger image to get a white border
|
|
Mat img(height_img, height_img, CV_8UC1, Scalar(255));
|
|
img_marker.copyTo(img(Rect(shift, shift, height_marker, height_marker)));
|
|
|
|
aruco::DetectorParameters detectorParameters = detector.getDetectorParameters();
|
|
detectorParameters.cornerRefinementMethod = (int)GetParam();
|
|
detector.setDetectorParameters(detectorParameters);
|
|
|
|
vector<vector<Point2f> > original_corners;
|
|
vector<int> original_ids;
|
|
{
|
|
NumThreadsSetter thread_num_setter(1);
|
|
detector.detectMarkers(img, original_corners, original_ids);
|
|
}
|
|
|
|
ASSERT_EQ(original_ids.size(), 1ull);
|
|
ASSERT_EQ(original_corners.size(), 1ull);
|
|
|
|
int num_threads_to_test[] = { 2, 8, 16, 32, height_img-1, height_img, height_img+1};
|
|
|
|
for (size_t i_num_threads = 0; i_num_threads < sizeof(num_threads_to_test)/sizeof(int); ++i_num_threads) {
|
|
NumThreadsSetter thread_num_setter(num_threads_to_test[i_num_threads]);
|
|
|
|
vector<vector<Point2f> > corners;
|
|
vector<int> ids;
|
|
detector.detectMarkers(img, corners, ids);
|
|
|
|
// If we don't find any markers, the test is broken
|
|
ASSERT_EQ(ids.size(), 1ull);
|
|
|
|
// Make sure we got the same result as the first time
|
|
ASSERT_EQ(corners.size(), original_corners.size());
|
|
ASSERT_EQ(ids.size(), original_ids.size());
|
|
ASSERT_EQ(ids.size(), corners.size());
|
|
for (size_t i = 0; i < corners.size(); ++i) {
|
|
EXPECT_EQ(ids[i], original_ids[i]);
|
|
for (size_t j = 0; j < corners[i].size(); ++j) {
|
|
EXPECT_NEAR(corners[i][j].x, original_corners[i][j].x, 0.1f);
|
|
EXPECT_NEAR(corners[i][j].y, original_corners[i][j].y, 0.1f);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(
|
|
CV_ArucoDetectMarkers, ArucoThreading,
|
|
::testing::Values(
|
|
aruco::CORNER_REFINE_NONE,
|
|
aruco::CORNER_REFINE_SUBPIX,
|
|
aruco::CORNER_REFINE_CONTOUR,
|
|
aruco::CORNER_REFINE_APRILTAG
|
|
));
|
|
|
|
}} // namespace
|