Fix distransform to work with large images #22798
This attempts to fix the following bug which was caused by storing squares of large integers into 32-bit floating point variables:
https://github.com/opencv/opencv/issues/22732
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Usage of imread(): magic number 0, unchecked result
* docs: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* samples, apps: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* tests: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* doc/py_tutorials: check imread() result
In some situations the last value was missing from the discrete theta
values. Now, the last value is chosen such that it is close to the
user-provided maximum theta, while the distance to pi remains always
at least theta_step/2. This should avoid duplicate detections.
A better way would probably be to use max_theta as is and adjust the
resolution (theta_step) instead, such that the discretization would
always be uniform (in a circular sense) when full angle range is used.
Fixed out-of-bounds read in parallel version of ippGaussianBlur()
* Fixed out-of-memory read in parallel version of ippGaussianBlur()
* Fixed check
* Revert changes in CMakeLists.txt
Fixed threshold(THRESH_TOZERO) at imgproc(IPP)
* Fixed#16085: imgproc(IPP): wrong result from threshold(THRESH_TOZERO)
* 1. Added test cases with float where all bits of mantissa equal 1, min and max float as inputs
2. Used nextafterf instead of cast to hex
* Used float value in test instead of hex and casts
* Changed input value in test
* 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
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>
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
lamm45
Alexander Smorkalov
Alexander Alekhin
Alexander Alekhin
Christoph Rackwitz
inayd
Alexander Smorkalov
@lizhiyu3
heavyrain-lzy
Yulv-git
eplankin
Artem Saratovtsev
Suleyman TURKMEN
Stefano Allegretti
Vincent Rabaud
Vincent Rabaud
yuki takehara
tv3141
AleksandrPanov
Tomoaki Teshima
Amir Tulegenov
Tiago De Gaspari
Xinguang Bian
thezane
danielenricocahall
Aaron Greig
Federico Bolelli
Gil Shotan