* add new chessboard detector
The chessboar detector is based on the paper.
Accurate Detection and Localization of Checkerboard Corners for
Calibration Alexander Duda, Udo Frese
British Machine Vision Conference, o.A., 2018.
It utilizes point symmetry of checkerboard corners in combination with a
localized Radon transform approximated by box filters to achieve high
performance even on large images. Here, tests have shown that the
ability to localize checkerboard corners is close to the theoretical
limit of 1/100 of a pixel while being considerably less sensitive
to image noise than standard methods.
* chessboard: add reference to bibtex file
* chessboard: add dependency to opencv_flann
* fix: test chesscorners. It is valid to return an empty list
In case no chessboard was detected it should be valid for the detector
to return an empty list.
For simplifcation, it should be allowed to return any number of corners
if they are flagged as not found.
* fix: opencv.bib remove empty lines
* fix: doc findChessboardCorners replace cvSize with cv::Size
* chessboard tests: factor out logic selecting detector
* chessboard: add unit test for findChessboardCorners2
This is includes a new chessboard generator which supports subpix
corners with high accuracy by wrapping an optimal chessboard using
wrapPerspective.
* fix: chessboard unit test - overwrite of default parameter flag of findCirclesGrid
* chessboard: remove trailing whitespace
* chessboard: fix debug drawing
* chessboard: fix some issues during code review
* chessboard: normalize asymmetric chessboard
* chessboard: fix float double warning
* remove trailing whitespace
* chessboards: fix compiler warnings
* chessboards: fix compiler warnings
* checkerboard: some performance improvements
* chessboard: remove NULL macros for language bindinges from internal headers
* chessboard: shorten license terms
* chessboard: remove unused internal method
* chessboard: set helper functions to static
* chessboard: fix normalizePoints1D using unshifted points
* chessboard: remove wrongly copied text
* chessboard: use CV_CheckTypeEQ macro
* chessboard: comment all NaN checks
* chessboard: use consistent color conversion
* chessboard: use CheckChannelEQ macro
* chessboard: assume gray color image for internal methods
* chessboard: use std::swap
* chessboard: use Mat.dataend
* chessboard: fix compiler warnings
* chessboard: replace some checks witch CV_CHECK macro
* chessboard: fix comparison function for partial sort
* chessboard: small cleanup
* chessboard: use short license header
* chessboard: rename findChessboard2 to findChessboardSB
* chessboard: fix type in unit test
* trying to fix the custom AVX2 builder test failures (false alarms)
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* seemingly disabled false alarm warning in surf.cpp; increased tolerance thresholds in the tests for SolvePnP and in DNN/ENet
* Add HPX backend for OpenCV implementation
Adds hpx backend for cv::parallel_for_() calls respecting the nstripes chunking parameter. C++ code for the backend is added to modules/core/parallel.cpp. Also, the necessary changes to cmake files are introduced.
Backend can operate in 2 versions (selectable by cmake build option WITH_HPX_STARTSTOP): hpx (runtime always on) and hpx_startstop (start and stop the backend for each cv::parallel_for_() call)
* WIP: Conditionally include hpx_main.hpp to tests in core module
Header hpx_main.hpp is included to both core/perf/perf_main.cpp and core/test/test_main.cpp.
The changes to cmake files for linking hpx library to above mentioned test executalbles are proposed but have issues.
* Add coditional iclusion of hpx_main.hpp to cpp cpu modules
* Remove start/stop version of hpx backend
* Add functionality to filter homography decompositions
* documentation + small refactor
* fix comparing int to size_t (compiler warning)
* fix whitespace issues
* clarification of function return values in documentation
* refactor of function parameters and change in loop nesting
* cleanup useless .h, fix size_t to int compare, small refactor
* fix documentation and whitespace
* change output from return value to outputarray parameter
* update function docs to reflect changes in parameters
* whitespace
* failing test
* fixed warnings related to extended initialisers and improper types
* initialize vectors from arrays
* initialize vectors from arrays part 2
* fix whitespace
* fix trailing whitespace
* Include <inttypes.h> in test_filter_homography_decomp.cpp, should fix 'uint8_t' : undeclared identifier error
* updated the test (made it shorter and providing better diagnostic) and significantly improved implementation (get rid of heavy repeated and/or unnecessary operations)
* fixed compile warning; removed trailing whitespace
fixes handling of empty matrices in some functions (#11634)
* a part of PR #11416 by Yuki Takehara
* moved the empty mat check in Mat::copyTo()
* fixed some test failures
* make tmpRow proper size before copyTo to avoid reallocated tmpCol
* do the transposition without creating temporary array; replace TAB with spaces.
* revert the previous commit
- removed tr1 usage (dropped in C++17)
- moved includes of vector/map/iostream/limits into ts.hpp
- require opencv_test + anonymous namespace (added compile check)
- fixed norm() usage (must be from cvtest::norm for checks) and other conflict functions
- added missing license headers
* Newton's method can be more efficient
when we get the result of function distortPoint with a point (0, 0) and then undistortPoint with the result, we get the point not (0, 0). and then we discovered that the old method is not convergence sometimes. finally we have gotten the right values by Newton's method.
* modify by advice Newton's method...#10574
* calib3d(fisheye): fix codestyle, update theta before exit EPS check
If there are no OpenCL/UMat methods calls from application.
OpenCL subsystem is initialized:
- haveOpenCL() is called from application
- useOpenCL() is called from application
- access to OpenCL allocator: UMat is created (empty UMat is ignored) or UMat <-> Mat conversions are called
Don't call OpenCL functions if OPENCV_OPENCL_RUNTIME=disabled
(independent from OpenCL linkage type)
Remove unnecessary Non-ASCII characters from source code (#9075)
* Remove unnecessary Non-ASCII characters from source code
Remove unnecessary Non-ASCII characters and replace them with ASCII
characters
* Remove dashes in the @param statement
Remove dashes and place single space in the @param statement to keep
coding style
* misc: more fixes for non-ASCII symbols
* misc: fix non-ASCII symbol in CMake file
The old error message was not giving any hint which input array (image)
led to an ill conditioned matrix. This made it near impossible to
identify poor images in a larger set.
A better approach would be to implement a checker function which gives
each image a rating before the real calibration is performed. This could
also include some image properties like sharpness, etc.
Enable p3p and ap3p in solvePnPRansac (#8585)
* add paper info
* allow p3p and ap3p being RANSAC kernel
* keep previous code
* apply catrees comment
* fix getMat
* add comment
* add solvep3p test
* test return value
* fix warnings
New p3p algorithm (accepted by CVPR 2017) (#8301)
* add p3p source code
* indent 4
* update publication info
* fix filename
* interface done
* plug in done, test needed
* debugging
* for test
* a working version
* clean p3p code
* test
* test
* fix warning, blank line
* apply patch from @catree
* add reference info
* namespace, indent 4
* static solveQuartic
* put small functions to anonymous namespace
Use identity matrix if homography finding failed. Current behavior zeros out all points.
Update circlesgrid.cpp
Addressed comments
Update circlesgrid.cpp
removed whitespace
the current camera model is only valid up to 180° FOV for larger FOV the
undistort loop does not converge.
Clip values so we still get plausible results for super fisheye images >
180°.
