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feat(ceres_intrinsic_camera_calibrator): ceres-based intrinsic calibrator #141
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Numerical results seem to be the same as opencv but it is way faster when using a large number of calibration images Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
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## tier4/universe #141 +/- ##
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- Coverage 0.95% 0.00% -0.96%
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Files 269 4 -265
Lines 20908 338 -20570
Branches 387 0 -387
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- Hits 200 0 -200
+ Misses 20551 338 -20213
+ Partials 157 0 -157
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Signed-off-by: amadeuszsz <[email protected]>
Signed-off-by: amadeuszsz <[email protected]>
Signed-off-by: amadeuszsz <[email protected]>
… data conditions Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
…(was lost in an experimental branch) Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: amadeuszsz <[email protected]>
Signed-off-by: amadeuszsz <[email protected]>
Signed-off-by: amadeuszsz <[email protected]>
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LGTM
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
@@ -47,11 +47,13 @@ calibrate( | |||
const Eigen::MatrixXd & initial_dist_coeffs_eigen, int num_radial_coeffs, int num_rational_coeffs, | |||
bool use_tangential_distortion, bool verbose) | |||
{ | |||
int num_dist_coeffs = initial_dist_coeffs_eigen.rows() * initial_dist_coeffs_eigen.cols(); |
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nit: narrowing conversion, std::size_t might be applied in both lines
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Implemented a ceres-based camera intrinsics calibrator.
Numerical results seem to be the same as opencv but it is way faster when using a large number of calibration images
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