Fix race condition in Otsu's method #3970
I found that in some cases, Otsu's method can have two or more equal thresholds. In case of the CUDA implementation, this would create a race-condition where the last thread to write the output gets to choose which Otsu threshold to use. The resulting image from cv::cuda::threshold would be the same, but the returned threshold would vary for each run.
I solve this by first doing a poll to check if there are multiple matches with `__syncthreads_count`. If not, we can return the threshold as before. If there are more than one, the kernel does a minimum reduction to find the lowest threshold that matches the otsu score. It doesn't matter which threshold you choose as long as it is consistent, so I choose the smallest one.
I'm unsure when `__syncthreads_count` as introduced, but it is compatible with CC≥2.0. CUDA Toolkit's archive only goes back to version 8.0, but it was documented back then (https://docs.nvidia.com/cuda/archive)
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Add Otsu's method to cv::cuda::threshold #3943
I implemented Otsu's method in CUDA for a separate project and want to add it to cv::cuda::threshold
I have made an effort to use existing OpenCV functions in my code, but I had some trouble with `ThresholdTypes` and `cv::cuda::calcHist`. I couldn't figure out how to include `precomp.hpp` to get the definition of `ThresholdTypes`. For `cv::cuda::calcHist` I tried adding `opencv_cudaimgproc`, but it creates a circular dependency on `cudaarithm`. I have include a simple implementation of `calcHist` so the code runs, but I would like input on how to use `cv::cuda::calcHist` instead.
### Pull Request Readiness Checklist
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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.
### Pull Request Readiness Checklist
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- [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
- [ ] 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
