Optimize cv::applyColorMap() for simple case
* Optimize cv::applyColorMap() for simple case
PR for 21640
For regular cv::Mat CV_8UC1 src, applying the colormap is simpler than calling the cv::LUT() mechanism.
* add support for src as CV_8UC3
src as CV_8UC3 is handled with a BGR2GRAY conversion, the same optimized code being used afterwards
* code style
rely on cv::Mat.ptr() to index data
* Move new implementation to ColorMap::operator()
Changes as suggested by reviewer
* style
improvements suggsted by reviewer
* typo
* tune parallel work
* better usage of parallel_for_
use nstripes parameter of parallel_for_
assume _lut is continuous to bring faster pixel indexing
optimize src/dst access by contiguous rows of pixels
do not locally copy the LUT any more, it is no more relevant with the new optimizations
* Added NEON support in builds for Windows on ARM
* Fixed `HAVE_CPU_NEON_SUPPORT` display broken during compiler test
* Fixed a build error prior to Visual Studio 2022
4.x: submodule or a class scope for exported classes
* feature: submodule or a class scope for exported classes
All classes are registered in the scope that corresponds to C++
namespace or exported class.
Example:
`cv::ml::Boost` is exported as `cv.ml.Boost`
`cv::SimpleBlobDetector::Params` is exported as
`cv.SimpleBlobDetector.Params`
For backward compatibility all classes are registered in the global
module with their mangling name containing scope information.
Example:
`cv::ml::Boost` has `cv.ml_Boost` alias to `cv.ml.Boost` type
* refactor: remove redundant GAPI aliases
* fix: use explicit string literals in CVPY_TYPE macro
* fix: add handling for class aliases
Use YuNet of fixed input shape to fix not-supported-dynamic-zero-shape for FaceDetectorYN
* use yunet with input of fixed shape
* update yunet used in face recognition regression
Thread Sanitizer identified an incorrect implementation of double checked locking.
Replaced it with a static, which therefore can only be created once.
Default FFMPEG VideoCapture backend to rtsp_flags=prefer_tcp
* Make the VideoCapture ffmpeg backends default rtsp connection type prefer_tcp.
* Ensure that the ffmpeg version of avformat is checked.
Per intel docs for libva, when vaDeriveImage fails vaCreateImage +
vaPutImage should be tried. This is important as mesa with AMD HW
will always fail because the image is interlaced so a indirect
method must be used to get the surface to/from and image
Fixes https://github.com/opencv/opencv/issues/21536
* Fix wrong MSAN errors.
Because Fortran is called in Lapack, MSAN does not think the memory
has been written even though it is the case.
MSAN does no support well cross-language memory analysis.
* Make a dedicated check.
Pierre Chatelier
Tatsuro Shibamura
Vadim Levin
Sergey Ivanov
Aleksei Trutnev
Yuantao Feng
KaurkerDevourer
Artem Saratovtsev
Yuriy Chernyshov
Anna Khakimova
Sean McBride
Alexander Alekhin
Maksim Shabunin
Yusuke Kameda
Suleyman TURKMEN
Pavel Rojtberg
cudawarped
Vincent Rabaud
Greg Fiumara
Anatoliy Talamanov
Dmitry Budnikov
lamm45
Maksim Shabunin
Ed Martin
Harvey