When computing:
t1 = (bayer[1] + bayer[bayer_step] + bayer[bayer_step+2] + bayer[bayer_step*2+1])*G2Y;
there is a T (unsigned short or char) multiplied by an int which can overflow.
Then again, it is stored to t1 which is unsigned so the overflow disappears.
Keeping all unsigned is safer.
* Fix integer overflow in cv::Luv2RGBinteger::process.
For LL=49, uu=205, vv=23, we end up with x=7373056 and y=458
which overflows y*x.
* imgproc(test): adjust test parameters to cover SIMD code
In case of very small negative h (e.g. -1e-40), with the current implementation,
you will go through the first condition and end up with h = 6.f, and will miss
the second condition.
* Add RowVec_8u32f
* Fix build errors in Linux x64 Debug and armeabi-v7a
* Reformat code to make it more clean and conventional
* Optimise with vx_load_expand_q()
different paddings in cvtColorTwoPlane() for biplane YUV420
* Different paddings support in cvtColorTwoPlane() for biplane YUV420
* Build fix for dispatch case.
* Resoted old behaviour for y.step==uv.step to exclude perf regressions.
Co-authored-by: amir.tulegenov <amir.tulegenov@xperience.ai>
Co-authored-by: Alexander Smorkalov <alexander.smorkalov@xperience.ai>
Update rotatedRectangleIntersection function to calculate near to origin
* Change type used in points function from RotatedRect
In the function that sets the points of a RotatedRect, the types
should be double in order to keep the precision when dealing with
RotatedRects that are defined far from the origin.
This commit solves the problem in some assertions from
rotatedRectangleIntersection when dealing with rectangles far from
origin.
* added proper type casts
* Update rotatedRectangleIntersection function to calculate near to origin
This commit changes the rotatedRectangleIntersection function in order
to calculate the intersection of two rectangles considering that they
are shifted near the coordinates origin (0, 0).
This commit solves the problem in some assertions from
rotatedRectangleIntersection when dealing with rectangles far from
origin.
* Revert type changes in types.cpp and adequate code to c++98
* Revert unnecessary casts on types.cpp
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
* Add Neon optimised RGB2Lab conversion
* Fix compile errors, change lambda to macro
* Change NEON optimised RGB2Lab to just use HAL
* Change [] to v_extract_n in RGB2Lab
* RGB2LAB Code quality, change to nlane agnostic
* Change RGB2Lab to use function rather than macro
* Remove whitespace
Co-authored-by: Francesco Petrogalli <25690309+fpetrogalli@users.noreply.github.com>
Also bring perf_imgproc CornerMinEigenVal accuracy requirements in line with
the test_imgproc accuracy requirements on that test and fix indentation on
the latter.
Partially addresses issue #9821
The MinEigenVal path through the corner.cl kernel makes use of native_sqrt,
a math builtin function which has implementation defined accuracy.
Partially addresses issue #9821
* goodFeaturesToTrack returns also corner value
(cherry picked from commit 4a8f06755c)
* Added response to GFTT Detector keypoints
(cherry picked from commit b88fb40c6e)
* Moved corner values to another optional variable to preserve backward compatibility
(cherry picked from commit 6137383d32)
* Removed corners valus from perf tests and better unit tests for corners values
(cherry picked from commit f3d0ef21a7)
* Fixed detector gftt call
(cherry picked from commit be2975553b)
* Restored test_cornerEigenValsVecs
(cherry picked from commit ea3e11811f)
* scaling fixed;
mineigen calculation rolled back;
gftt function overload added (with quality parameter);
perf tests were added for the new api function;
external bindings were added for the function (with different alias);
fixed issues with composition of the output array of the new function (e.g. as requested in comments) ;
added sanity checks in the perf tests;
removed C API changes.
* minor change to GFTTDetector::detect
* substitute ts->printf with EXPECT_LE
* avoid re-allocations
Co-authored-by: Anas <anas.el.amraoui@live.com>
Co-authored-by: amir.tulegenov <amir.tulegenov@xperience.ai>
Return accumulator value in HoughLines algorithm
* try to solve #17050
use cv_wrap_as
add python test
parameters
* review
* move wrapper to imgproc/bindings.hpp
