Get CUDA code to compile with clang CUDA and without CUDA #3800
Changelist:
- there are some syntactic changes: `<< <` -> `<<<`. For some reason, I do not need to change all those in the code.
- `::min` -> `std::min` in `__host__` code
- `modules/cudaimgproc/src/moments.cpp` needs to have the CUDA code in the `#ifdef`
- The signature of `cv::cuda::swapChannels` is not exactly the same as the C++ one in `modules/cudaimgproc/src/color.cpp`
- `cv::cuda::FarnebackOpticalFlow::create` needs to be explicit about which FarnebackOpticalFlow it returns
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New dnn engine #3794
This is a companion for https://github.com/opencv/opencv/pull/26056
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slightly alter threshold for warpAffine optimization #3787
Merge with https://github.com/opencv/opencv/pull/25984
New`onfusionMatrixes[1]` is
```
[[45 0 0 0 0 0 0 0 0 0]
[ 0 57 0 0 0 0 0 0 0 0]
[ 0 0 58 2 0 0 0 0 1 0]
[ 0 0 0 43 0 0 0 1 0 0]
[ 0 0 0 0 39 0 0 0 0 1]
[ 0 0 0 1 0 49 0 0 1 0]
[ 0 0 0 0 0 0 52 0 0 0]
[ 0 0 1 0 0 0 0 54 0 0]
[ 0 0 0 0 0 0 0 0 47 0]
[ 0 1 0 1 0 0 0 0 2 44]]
```
which is about of pixel value 1 shift in each 4x or 5x pixel value.
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Fix(wechat_code): Modify isnan for compatibility with -ffast_math. #3490fix#3150
Merge with https://github.com/opencv/opencv/pull/23881
Reference: https://stackoverflow.com/questions/7263404/mingw32-stdisnan-with-ffast-math
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Correct some links in the tutorials #3771
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first proposal of cv::remap with relative displacement field
Relates to [#24621](https://github.com/opencv/opencv/pull/24621), [#24603](https://github.com/opencv/opencv/issues/24603)
CUDA implementation of the feature
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Add interleaved versions of phase/cartToPolar/polarToCart #3607
This PR is for performance only (at the cost of more template code and increased GPU code size) The additional variants can help the caller skip the creation of temporary GPU mats (where memory is more likely to be a critical resource), and can even allow in-place processing. magnitude/angles/x/y are often already interleaved when dealing with DFTs.
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supports empty kernels in cuda::SeparableLinearFilters #3731
[#25408](https://github.com/opencv/opencv/issues/25408)
When only 1D convolution is needed (row or column filter only), `cuda::LinearFilter` might be slower than `cuda::SeparableLinearFilter`
Using `cuda::SeparableLinearFilter` for 1D convolution can be done by using a `(1)` kernel for the ignored dimension.
By supporting empty kernels in `cuda::SeparableLinearFilter`, there is no need for that `(1)` kernel any more.
Additionaly, the inner `_buf ` used to store the intermediate convolution result can be saved when a single convolution is needed.
In "legacy" usage (row+col kernels), there is no regression in `cuda::SeparableLinearFilter` performance.
As soon as an empty kernel is used, the performance is largely increased.
Devil in the details : the "in-place" processing is supported and might need intermediate buf, but still no regression.
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Add conditional include for <cuda/std/tuple> to support CUDA 12.4+ #3751
Fixes https://github.com/opencv/opencv_contrib/issues/3752
Adds a preprocessor check to conditionally include <cuda/std/tuple> only for CUDA versions 12.4 and above. This ensures backward compatibility with older legacy CUDA versions.
Related to pull request #3744
### Pull Request Readiness Checklist
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Alexander Smorkalov
Alexander Smorkalov
Vincent Rabaud
cudawarped
Alexander Smorkalov
Vadim Pisarevsky
Maksim Shabunin
WU Jia
Yuantao Feng
masterAllen
Nano
Ivan Afanasyev
Kumataro
Yannis Guyon
Pierre Chatelier
Gregor Burger
Peter Rekdal Khan-Sunde