Improves support for Unix non-Linux systems, including QNX
* Fixes#20395. Improves support for Unix non-Linux systems. Focus on QNX Neutrino.
Signed-off-by: promero <promero@mathworks.com>
* Update system.cpp
There can be an int overflow.
cv::norm( InputArray _src, int normType, InputArray _mask ) is fine,
not cv::norm( InputArray _src1, InputArray _src2, int normType, InputArray _mask ).
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>
This commit adds the feature of selecting the thickness
of the matches drawn by the drawMatches function.
In larger images, the default thickness of 1 pixel creates images
that are hard to visualize.
Improve performance on Arm64
* Improve performance on Apple silicon
This patch will
- Enable dot product intrinsics for macOS arm64 builds
- Enable for macOS arm64 builds
- Improve HAL primitives
- reduction (sum, min, max, sad)
- signmask
- mul_expand
- check_any / check_all
Results on a M1 Macbook Pro
* Updates to #20011 based on feedback
- Removes Apple Silicon specific workarounds
- Makes #ifdef sections smaller for v_mul_expand cases
- Moves dot product optimization to compiler optimization check
- Adds 4x4 matrix transpose optimization
* Remove dotprod and fix v_transpose
Based on the latest, we've removed dotprod entirely and will revisit in a future PR.
Added explicit cats with v_transpose4x4()
This should resolve all opens with this PR
* Remove commented out lines
Remove two extraneous comments
* 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>
- 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
Fix unsigned int bug in computeECC
* address issue with unsigned ints in computeEcc
* remove additional logic checking firstOctave
* use swap instead of same src/dst
* simplify the unsigned check logic
fix a build warning:
```
C:\Slave\workspace\precommit\windows10\opencv\modules\photo\src\contrast_preserve.hpp(289): warning C4244: '=': conversion from 'double' to '_Tp', possible loss of data
with
[
_Tp=float
]
C:\Slave\workspace\precommit\windows10\opencv\modules\photo\src\contrast_preserve.hpp(361): warning C4244: '=': conversion from 'double' to '_Tp', possible loss of data
with
[
_Tp=float
]
```
(from https://build.opencv.org.cn/job/precommit/job/windows10/1633/console)
Currently, the LOADER_DIR is set as os.path.dirname(os.path.abspath(__file__)). This does not point to the true library path if the cv2 folder is symlinked into the Python package directory such that importing cv2 under Python fails. The proposed change only resolves symbolic links correctly by calling os.path.realpath(__file__) first and does not change anything if __file__ contains no symbolic link.
Fix bug with predictions in RTrees/Boost
* address bug where predict functions with invalid feature count in rtrees/boost models
* compact matrix rep in tests
* check 1..n-1 and n+1 in feature size validation test
Fix Single ThresholdBug in Simple Blob Detector
* address bug with using min dist between blobs in blob detector
cast type in comparison and remove docs
address bug with using min dist between blobs in blob detector
use scalar instead of int
address bug with using min dist between blobs in blob detector
* fix namespace and formatting
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
