opoints_inliers.resize(npoints1);
ipoints_inliers.resize(npoints1);
- result = solvePnP(opoints_inliers, ipoints_inliers, cameraMatrix,
- distCoeffs, rvec, tvec, useExtrinsicGuess,
- (flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P) ? SOLVEPNP_EPNP : flags) ? 1 : -1;
+ try
+ {
+ result = solvePnP(opoints_inliers, ipoints_inliers, cameraMatrix,
+ distCoeffs, rvec, tvec, useExtrinsicGuess,
+ (flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P) ? SOLVEPNP_EPNP : flags) ? 1 : -1;
+ }
+ catch (const cv::Exception& e)
+ {
+ if (flags == SOLVEPNP_ITERATIVE &&
+ npoints1 == 5 &&
+ e.what() &&
+ std::string(e.what()).find("DLT algorithm needs at least 6 points") != std::string::npos
+ )
+ {
+ CV_LOG_INFO(NULL, "solvePnPRansac(): solvePnP stage to compute the final pose using points "
+ "in the consensus set raised DLT 6 points exception, use result from MSS (Minimal Sample Sets) stage instead.");
+ rvec = _local_model.col(0); // output rotation vector
+ tvec = _local_model.col(1); // output translation vector
+ result = 1;
+ }
+ else
+ {
+ // raise other exceptions
+ throw;
+ }
+ }
- if( result <= 0 )
+ if (result <= 0)
{
_rvec.assign(_local_model.col(0)); // output rotation vector
_tvec.assign(_local_model.col(1)); // output translation vector
- if( _inliers.needed() )
+ if (_inliers.needed())
_inliers.release();
+ CV_LOG_DEBUG(NULL, "solvePnPRansac(): solvePnP stage to compute the final pose using points in the consensus set failed. Return false");
return false;
}
else
EXPECT_LE(cvtest::norm(t, Mat_<double>(tF), NORM_INF), 1e-3);
}
+TEST(Calib3d_SolvePnPRansac, bad_input_points_19253)
+{
+ // with this specific data
+ // when computing the final pose using points in the consensus set with SOLVEPNP_ITERATIVE and solvePnP()
+ // an exception is thrown from solvePnP because there are 5 non-coplanar 3D points and the DLT algorithm needs at least 6 non-coplanar 3D points
+ // with PR #19253 we choose to return true, with the pose estimated from the MSS stage instead of throwing the exception
+
+ float pts2d_[] = {
+ -5.38358629e-01f, -5.09638414e-02f,
+ -5.07192254e-01f, -2.20743284e-01f,
+ -5.43107152e-01f, -4.90474701e-02f,
+ -5.54325163e-01f, -1.86715424e-01f,
+ -5.59334219e-01f, -4.01909500e-02f,
+ -5.43504596e-01f, -4.61776406e-02f
+ };
+ Mat pts2d(6, 2, CV_32FC1, pts2d_);
+
+ float pts3d_[] = {
+ -3.01153604e-02f, -1.55665115e-01f, 4.50000018e-01f,
+ 4.27827090e-01f, 4.28645730e-01f, 1.08600008e+00f,
+ -3.14165242e-02f, -1.52656138e-01f, 4.50000018e-01f,
+ -1.46217480e-01f, 5.57961613e-02f, 7.17000008e-01f,
+ -4.89348806e-02f, -1.38795510e-01f, 4.47000027e-01f,
+ -3.13065052e-02f, -1.52636901e-01f, 4.51000035e-01f
+ };
+ Mat pts3d(6, 3, CV_32FC1, pts3d_);
+
+ Mat camera_mat = Mat::eye(3, 3, CV_64FC1);
+ Mat rvec, tvec;
+ vector<int> inliers;
+
+ // solvePnPRansac will return true with 5 inliers, which means the result is from MSS stage.
+ bool result = solvePnPRansac(pts3d, pts2d, camera_mat, noArray(), rvec, tvec, false, 100, 4.f / 460.f, 0.99, inliers);
+ EXPECT_EQ(inliers.size(), size_t(5));
+ EXPECT_TRUE(result);
+}
+
TEST(Calib3d_SolvePnP, input_type)
{
Matx33d intrinsics(5.4794130238156129e+002, 0., 2.9835545700043139e+002, 0.,