Repository for OpenCV's extra modules
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

330 lines
13 KiB

/*
By downloading, copying, installing or using the software you agree to this
license. If you do not agree to this license, do not download, install,
copy or use the software.
License Agreement
For Open Source Computer Vision Library
(3-clause BSD License)
Copyright (C) 2013, OpenCV Foundation, all rights reserved.
Third party copyrights are property of their respective owners.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the names of the copyright holders nor the names of the contributors
may be used to endorse or promote products derived from this software
without specific prior written permission.
This software is provided by the copyright holders and contributors "as is" and
any express or implied warranties, including, but not limited to, the implied
warranties of merchantability and fitness for a particular purpose are
disclaimed. In no event shall copyright holders or contributors be liable for
any direct, indirect, incidental, special, exemplary, or consequential damages
(including, but not limited to, procurement of substitute goods or services;
loss of use, data, or profits; or business interruption) however caused
and on any theory of liability, whether in contract, strict liability,
or tort (including negligence or otherwise) arising in any way out of
the use of this software, even if advised of the possibility of such damage.
*/
#include "test_precomp.hpp"
#include "test_aruco_utils.hpp"
namespace opencv_test { namespace {
enum class ArucoAlgParams
{
USE_DEFAULT = 0,
USE_ARUCO3 = 1
};
/**
* @brief Check pose estimation of aruco board
*/
class CV_ArucoBoardPose : public cvtest::BaseTest {
public:
CV_ArucoBoardPose(ArucoAlgParams arucoAlgParams)
{
aruco::DetectorParameters params;
Ptr<aruco::Dictionary> dictionary = aruco::getPredefinedDictionary(aruco::DICT_6X6_250);
params.minDistanceToBorder = 3;
if (arucoAlgParams == ArucoAlgParams::USE_ARUCO3) {
params.useAruco3Detection = true;
params.cornerRefinementMethod = aruco::CORNER_REFINE_SUBPIX;
params.minSideLengthCanonicalImg = 16;
params.errorCorrectionRate = 0.8;
}
detector = aruco::ArucoDetector(dictionary, params);
}
protected:
aruco::ArucoDetector detector;
void run(int);
};
void CV_ArucoBoardPose::run(int) {
int iter = 0;
Mat cameraMatrix = Mat::eye(3, 3, CV_64FC1);
Size imgSize(500, 500);
cameraMatrix.at< double >(0, 0) = cameraMatrix.at< double >(1, 1) = 650;
cameraMatrix.at< double >(0, 2) = imgSize.width / 2;
cameraMatrix.at< double >(1, 2) = imgSize.height / 2;
Mat distCoeffs(5, 1, CV_64FC1, Scalar::all(0));
const int sizeX = 3, sizeY = 3;
// for different perspectives
for(double distance = 0.2; distance <= 0.4; distance += 0.15) {
for(int yaw = -55; yaw <= 50; yaw += 25) {
for(int pitch = -55; pitch <= 50; pitch += 25) {
vector<int> tmpIds;
for(int i = 0; i < sizeX*sizeY; i++)
tmpIds.push_back((iter + int(i)) % 250);
Ptr<aruco::GridBoard> gridboard = aruco::GridBoard::create(sizeX, sizeY, 0.02f, 0.005f, detector.getDictionary(), tmpIds);
int markerBorder = iter % 2 + 1;
iter++;
// create synthetic image
Mat img = projectBoard(gridboard, cameraMatrix, deg2rad(yaw), deg2rad(pitch), distance,
imgSize, markerBorder);
vector<vector<Point2f> > corners;
vector<int> ids;
detector.getDetectorParameters().markerBorderBits = markerBorder;
detector.detectMarkers(img, corners, ids);
ASSERT_EQ(ids.size(), gridboard->getIds().size());
// estimate pose
Mat rvec, tvec;
Ptr<aruco::Board> board = gridboard.staticCast<aruco::Board>();
estimatePoseBoard(corners, ids, board, cameraMatrix, distCoeffs, rvec, tvec);
// check axes
vector<Point2f> axes = getAxis(cameraMatrix, distCoeffs, rvec, tvec, gridboard->getRightBottomBorder().x);
vector<Point2f> topLeft = getMarkerById(gridboard->getIds()[0], corners, ids);
ASSERT_NEAR(topLeft[0].x, axes[0].x, 2.f);
ASSERT_NEAR(topLeft[0].y, axes[0].y, 2.f);
vector<Point2f> topRight = getMarkerById(gridboard->getIds()[2], corners, ids);
ASSERT_NEAR(topRight[1].x, axes[1].x, 2.f);
ASSERT_NEAR(topRight[1].y, axes[1].y, 2.f);
vector<Point2f> bottomLeft = getMarkerById(gridboard->getIds()[6], corners, ids);
ASSERT_NEAR(bottomLeft[3].x, axes[2].x, 2.f);
ASSERT_NEAR(bottomLeft[3].y, axes[2].y, 2.f);
// check estimate result
for(unsigned int i = 0; i < ids.size(); i++) {
int foundIdx = -1;
for(unsigned int j = 0; j < gridboard->getIds().size(); j++) {
if(gridboard->getIds()[j] == ids[i]) {
foundIdx = int(j);
break;
}
}
if(foundIdx == -1) {
ts->printf(cvtest::TS::LOG, "Marker detected with wrong ID in Board test");
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return;
}
vector< Point2f > projectedCorners;
projectPoints(gridboard->getObjPoints()[foundIdx], rvec, tvec, cameraMatrix, distCoeffs,
projectedCorners);
for(int c = 0; c < 4; c++) {
double repError = cv::norm(projectedCorners[c] - corners[i][c]); // TODO cvtest
if(repError > 5.) {
ts->printf(cvtest::TS::LOG, "Corner reprojection error too high");
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return;
}
}
}
}
}
}
}
/**
* @brief Check refine strategy
*/
class CV_ArucoRefine : public cvtest::BaseTest {
public:
CV_ArucoRefine(ArucoAlgParams arucoAlgParams)
{
Ptr<aruco::Dictionary> dictionary = aruco::getPredefinedDictionary(aruco::DICT_6X6_250);
aruco::DetectorParameters params;
params.minDistanceToBorder = 3;
params.cornerRefinementMethod = aruco::CORNER_REFINE_SUBPIX;
if (arucoAlgParams == ArucoAlgParams::USE_ARUCO3)
params.useAruco3Detection = true;
aruco::RefineParameters refineParams(10.f, 3.f, true);
detector = aruco::ArucoDetector(dictionary, params, refineParams);
}
protected:
aruco::ArucoDetector detector;
void run(int);
};
void CV_ArucoRefine::run(int) {
int iter = 0;
Mat cameraMatrix = Mat::eye(3, 3, CV_64FC1);
Size imgSize(500, 500);
Ptr<aruco::GridBoard> gridboard = aruco::GridBoard::create(3, 3, 0.02f, 0.005f, detector.getDictionary());
cameraMatrix.at< double >(0, 0) = cameraMatrix.at< double >(1, 1) = 650;
cameraMatrix.at< double >(0, 2) = imgSize.width / 2;
cameraMatrix.at< double >(1, 2) = imgSize.height / 2;
Mat distCoeffs(5, 1, CV_64FC1, Scalar::all(0));
// for different perspectives
for(double distance = 0.2; distance <= 0.4; distance += 0.2) {
for(int yaw = -60; yaw < 60; yaw += 30) {
for(int pitch = -60; pitch <= 60; pitch += 30) {
vector<int> tmpIds;
for(unsigned int i = 0; i < gridboard->getIds().size(); i++)
tmpIds.push_back(iter + int(i) % 250);
gridboard = aruco::GridBoard::create(3, 3, 0.02f, 0.005f, detector.getDictionary(), tmpIds);
int markerBorder = iter % 2 + 1;
iter++;
// create synthetic image
Mat img = projectBoard(gridboard, cameraMatrix, deg2rad(yaw), deg2rad(pitch), distance,
imgSize, markerBorder);
// detect markers
vector<vector<Point2f> > corners, rejected;
vector<int> ids;
detector.getDetectorParameters().markerBorderBits = markerBorder;
detector.detectMarkers(img, corners, ids, rejected);
// remove a marker from detection
int markersBeforeDelete = (int)ids.size();
if(markersBeforeDelete < 2) continue;
rejected.push_back(corners[0]);
corners.erase(corners.begin(), corners.begin() + 1);
ids.erase(ids.begin(), ids.begin() + 1);
// try to refind the erased marker
Ptr<aruco::Board> board = gridboard.staticCast<aruco::Board>();
detector.refineDetectedMarkers(img, board, corners, ids, rejected, cameraMatrix,
distCoeffs, noArray());
// check result
if((int)ids.size() < markersBeforeDelete) {
ts->printf(cvtest::TS::LOG, "Error in refine detected markers");
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return;
}
}
}
}
}
TEST(CV_ArucoBoardPose, accuracy) {
CV_ArucoBoardPose test(ArucoAlgParams::USE_DEFAULT);
test.safe_run();
}
typedef CV_ArucoBoardPose CV_Aruco3BoardPose;
TEST(CV_Aruco3BoardPose, accuracy) {
CV_Aruco3BoardPose test(ArucoAlgParams::USE_ARUCO3);
test.safe_run();
}
typedef CV_ArucoRefine CV_Aruco3Refine;
TEST(CV_ArucoRefine, accuracy) {
CV_ArucoRefine test(ArucoAlgParams::USE_DEFAULT);
test.safe_run();
}
TEST(CV_Aruco3Refine, accuracy) {
CV_Aruco3Refine test(ArucoAlgParams::USE_ARUCO3);
test.safe_run();
}
TEST(CV_ArucoBoardPose, CheckNegativeZ)
{
double matrixData[9] = { -3.9062571886921410e+02, 0., 4.2350000000000000e+02,
0., 3.9062571886921410e+02, 2.3950000000000000e+02,
0., 0., 1 };
cv::Mat cameraMatrix = cv::Mat(3, 3, CV_64F, matrixData);
vector<cv::Point3f> pts3d1, pts3d2;
pts3d1.push_back(cv::Point3f(0.326198f, -0.030621f, 0.303620f));
pts3d1.push_back(cv::Point3f(0.325340f, -0.100594f, 0.301862f));
pts3d1.push_back(cv::Point3f(0.255859f, -0.099530f, 0.293416f));
pts3d1.push_back(cv::Point3f(0.256717f, -0.029557f, 0.295174f));
pts3d2.push_back(cv::Point3f(-0.033144f, -0.034819f, 0.245216f));
pts3d2.push_back(cv::Point3f(-0.035507f, -0.104705f, 0.241987f));
pts3d2.push_back(cv::Point3f(-0.105289f, -0.102120f, 0.237120f));
pts3d2.push_back(cv::Point3f(-0.102926f, -0.032235f, 0.240349f));
vector<int> tmpIds = {0, 1};
vector<vector<Point3f> > tmpObjectPoints = {pts3d1, pts3d2};
Ptr<aruco::Board> board = aruco::Board::create(tmpObjectPoints, aruco::getPredefinedDictionary(0), tmpIds);
vector<vector<Point2f> > corners;
vector<Point2f> pts2d;
pts2d.push_back(cv::Point2f(37.7f, 203.3f));
pts2d.push_back(cv::Point2f(38.5f, 120.5f));
pts2d.push_back(cv::Point2f(105.5f, 115.8f));
pts2d.push_back(cv::Point2f(104.2f, 202.7f));
corners.push_back(pts2d);
pts2d.clear();
pts2d.push_back(cv::Point2f(476.0f, 184.2f));
pts2d.push_back(cv::Point2f(479.6f, 73.8f));
pts2d.push_back(cv::Point2f(590.9f, 77.0f));
pts2d.push_back(cv::Point2f(587.5f, 188.1f));
corners.push_back(pts2d);
Vec3d rvec, tvec;
int nUsed = cv::aruco::estimatePoseBoard(corners, board->getIds(), board, cameraMatrix, Mat(), rvec, tvec);
ASSERT_EQ(nUsed, 2);
cv::Matx33d rotm; cv::Point3d out;
cv::Rodrigues(rvec, rotm);
out = cv::Point3d(tvec) + rotm*Point3d(board->getObjPoints()[0][0]);
ASSERT_GT(out.z, 0);
corners.clear(); pts2d.clear();
pts2d.push_back(cv::Point2f(38.4f, 204.5f));
pts2d.push_back(cv::Point2f(40.0f, 124.7f));
pts2d.push_back(cv::Point2f(102.0f, 119.1f));
pts2d.push_back(cv::Point2f(99.9f, 203.6f));
corners.push_back(pts2d);
pts2d.clear();
pts2d.push_back(cv::Point2f(476.0f, 184.3f));
pts2d.push_back(cv::Point2f(479.2f, 75.1f));
pts2d.push_back(cv::Point2f(588.7f, 79.2f));
pts2d.push_back(cv::Point2f(586.3f, 188.5f));
corners.push_back(pts2d);
nUsed = cv::aruco::estimatePoseBoard(corners, board->getIds(), board, cameraMatrix, Mat(), rvec, tvec, true);
ASSERT_EQ(nUsed, 2);
cv::Rodrigues(rvec, rotm);
out = cv::Point3d(tvec) + rotm*Point3d(board->getObjPoints()[0][0]);
ASSERT_GT(out.z, 0);
}
}} // namespace