Fixed trailing whitespace
Update to initInverseRectificationMap documentation for clarity
Added test case for initInverseRectificationMap()
Updated documentation.
Fixed whitespace error in docs
Small update to test function
Now passes success_error_level
final update to inverseRectification documentation
- Added missing documentation for the CALIB_FIX_FOCAL_LENGTH flag
- Removed erroneous information about the number of distortion coefficients
returned
- Added some missing @ref tags
This commit passes the parameter maxIters that represent
the maximum number of iterations, that can be passed to findFundamentalMat
to the method LMeDS.
This parameter were added to the function findFundamentalMat and
were passed just for the RANSAC method, but should be passed to
both methods to be consistent.
Init params (StereoBMParams) in StereoBMImpl constructor initialization list
* Init StereoBMImpl in initialization list
To improve preformence it is better to init the params (StereoBMImpl) in the
initialization list.
* coding style
* drop useless copy/move ctor
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
* Update polynom_solver.cpp
This pull request is in the response to Issue #19526. I have fixed the problem with the cube root calculation of 2*R. The Issue was in the usage of pow function with negative values of R, but if it is calculated for only positive values of R then changing x0 according to the parity of R, the Issue is resolved. Kindly consider it, Thanks!
* add cv::cubeRoot(double)
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
* Added CALIB_FIX_FOCAL_LENGTH to fisheye calibration #13450
Sometimes you want to calibrate just the principal point of a camera, or just the distortion coefficients. In this case, you can pass the CALIB_FIX_FOCAL_LENGTH flag to keep Fx and Fy
* Added test for CALIB_FIX_FOCAL_LENGTH option in fisheye callinration.
calib3d(usac): do not crash on empty models
* calib3d(test): regression test for issue 19639
* calib3d(usac): do not crash in setModelParameters()
* calib3d(usac): handle empty models in isModelGood()
Fisheye test has been updated to use new enum cv::fisheye::CALIB_ZERO_DISPARITY and included CV_StaticAssert(...) to ensure cv::CALIB_ZERO_DISPARITY == cv::fisheye::CALIB_ZERO_DISPARITY.
- detect case with infinite loop and raise NoConv exception
- handle such exception
- add support for case with missing `blobDetector` (image contains Point2f array of candidates)
- add regression test
- undone rectification for "failed" detections too
- drop redirectError() usage
Added SQPnP algorithm to SolvePnP
* Added sqpnp
* Fixed test case
* Added fix for duplicate point checking and inverse func reuse
* Changes for 3x speedup
Changed norm method (significant speed increase), changed nearest rotation computation to FOAM
* Added symmetric 3x3 inverse and unrolled loops
* Fixed error with SVD
* Fixed error from with indices
Indices were initialized negative. When nullspace is large, points coplanar, and rotation near 0, indices not changed.
* add findEssentialMat for two different cameras
* added smoke test for the newly added variant of findEssentialMatrix
Co-authored-by: tompollok <tom.pollok@gmail.com>
fix instable fisheye undistortPoints
* remove artefacts when (un)distorting fisheye images with large distortion coefficient values
* fix fisheye undistortion when theta is close to zero
* add fisheye image undistort and distort test
* Fixed type conversion warnings
* fixed trailing whitespace
Objc binding
* Initial work on Objective-C wrapper
* Objective-C generator script; update manually generated wrappers
* Add Mat tests
* Core Tests
* Imgproc wrapper generation and tests
* Fixes for Imgcodecs wrapper
* Miscellaneous fixes. Swift build support
* Objective-C wrapper build/install
* Add Swift wrappers for videoio/objdetect/feature2d
* Framework build;iOS support
* Fix toArray functions;Use enum types whenever possible
* Use enum types where possible;prepare test build
* Update test
* Add test runner scripts for iOS and macOS
* Add test scripts and samples
* Build fixes
* Fix build (cmake 3.17.x compatibility)
* Fix warnings
* Fix enum name conflicting handling
* Add support for document generation with Jazzy
* Swift/Native fast accessor functions
* Add Objective-C wrapper for calib3d, dnn, ml, photo and video modules
* Remove IntOut/FloatOut/DoubleOut classes
* Fix iOS default test platform value
* Fix samples
* Revert default framework name to opencv2
* Add converter util functions
* Fix failing test
* Fix whitespace
* Add handling for deprecated methods;fix warnings;define __OPENCV_BUILD
* Suppress cmake warnings
* Reduce severity of "jazzy not found" log message
* Fix incorrect #include of compatibility header in ios.h
* Use explicit returns in subscript/get implementation
* Reduce minimum required cmake version to 3.15 for Objective-C/Swift binding
* Fixed indexing in prefilter
* Initialised prefilter
* Initialised prefilter with value initialisation
* Added TC to trigger different Mem Allocs in BufferBM
* Optimize cases with only needed conditions
added estimateTranslation3D to calib3d/ptsetreg
* added estimateTranslation3D; follows API and implementation structure for estimateAffine3D, but only allows for translation
* void variables in null function to suppress compiler warnings
* added test for estimateTranslation3D
* changed to Matx13d datatype for translation vector in ptsetreg and test; used short license in test
* removed iostream include
* calib3d: code cleanup
Image sharpness, as well as brightness, are a critical parameter for
accuracte camera calibration. For accessing these parameters for
filtering out problematic calibraiton images, this method calculates
edge profiles by traveling from black to white chessboard cell centers.
Based on this, the number of pixels is calculated required to transit
from black to white. This width of the transition area is a good
indication of how sharp the chessboard is imaged and should be below
~3.0 pixels.
Based on this also motion blur can be detectd by comparing sharpness in
vertical and horizontal direction. All unsharp images should be excluded
from calibration as they will corrupt the calibration result. The same
is true for overexposued images due to a none-linear sensor response.
This can be detected by looking at the average cell brightness of the
detected chessboard.
Lets the user choose the maximum number of iterations the robust
estimator runs for, similary to findHomography. This can significantly
improve performance (at a computational cost).
