Support C++20 standard #26590
Close https://github.com/opencv/opencv/issues/26589
Related https://github.com/opencv/opencv_contrib/pull/3842
Related: https://github.com/opencv/opencv/issues/20269
- do not arithmetic enums and ( different enums or floating numeric)
- remove unused variable
### 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.
- [x] The feature is well documented and sample code can be built with the project CMake
* Replaced most remaining sprintf with snprintf
* Deprecated encodeFormat and introduced new method that takes the buffer length
* Also increased buffer size at call sites to be a little bigger, in case int is 64 bit
* imgproc: templmatch: Add support for mask for all methods
Add support for masked template matching. Fix/scrub old implementation
for masked matching, as it did partly not even really do a meaningful
masking, and only supported limited template matching methods.
Add documentation including formulas for masked matching.
* imgproc: test: Add tests for masked template matching
Test accuracy by comparing to naive implementation for one point.
Test compatibility/correctness by comparing results without mask and
with all ones mask.
All tests are done for all methods, all supported depths, and for 1 and
3 channels.
* imgproc: test: templmatch: Add test for crossCorr
Add a test for the crossCorr function in templmatch.cpp. crossCorr() had
to be added to exported functions to be testable.
This test can maybe help to identify the problem with template matching
on MacOSX.
* fix: Fixed wrong evaluations of the MatExpr on Clang
* fix: removed crossCorr from public interface.
If it should be exported, it should be done as separate PR.
Co-authored-by: Vadim Levin <vadim.levin@xperience.ai>
Crosscorr cleanup (#14936)
* Simplify code for convolution destination type/size
For the 2d filter code, destination size equals source size, and the
crossCorr function even (re-)creates the output matrix with the given size.
The number of channels also have to match. The destination type() is the
one used to create the output matrix, so we can use its type() here.
This is a preparatory patch.
Signed-off-by: Stefan Brüns <stefan.bruens@rwth-aachen.de>
* Remove redundant destination size and type parameters from crossCorr
All calling sites of crossCorr already use (...,
mat, mat.size(), mat.type(), ...), so the parameters are redundant.
Signed-off-by: Stefan Brüns <stefan.bruens@rwth-aachen.de>
* another round of dnn optimization:
* increased malloc alignment across OpenCV from 16 to 64 bytes to make it AVX2 and even AVX-512 friendly
* improved SIMD optimization of pooling layer, optimized average pooling
* cleaned up convolution layer implementation
* made activation layer "attacheable" to all other layers, including fully connected and addition layer.
* fixed bug in the fusion algorithm: "LayerData::consumers" should not be cleared, because it desctibes the topology.
* greatly optimized permutation layer, which improved SSD performance
* parallelized element-wise binary/ternary/... ops (sum, prod, max)
* also, added missing copyrights to many of the layer implementation files
* temporarily disabled (again) the check for intermediate blobs consistency; fixed warnings from various builders
Removed IPP port for tiny arithm.cpp functions
Additional warnings fix on various platforms.
Build without OPENCL and GCC warnings fixed
Fixed warnings, trailing spaces and removed unused secure_cpy.
IPP code refactored.
IPP code path implemented as separate static functions to simplify future work with IPP code and make it more readable.
IPP can be switched on and off on runtime;
Optional implementation collector was added (switched off by default in CMake). Gathers data of implementation used in functions and report this info through performance TS;
TS modifications for implementations control;
MaximSmolskiy
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Alexander Smorkalov
Dmitry Kurtaev
captain-n3m0
Sean McBride
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Alexander Alekhin
danielenricocahall
jumostedu
StefanBruens
lqy123000
Alexander Alekhin
Hamdi Sahloul
Vadim Pisarevsky
Pavel Vlasov
Maksim Shabunin
Dmitry Budnikov
Vladislav Vinogradov
Yan Wang
Adil Ibragimov
Elena Gvozdeva
Alexander Alekhin
Ilya Lavrenov