[HAL RVV] impl sqrt and invSqrt opencv#27015

Implement through the existing interfaces `cv_hal_sqrt32f`, `cv_hal_sqrt64f`, `cv_hal_invSqrt32f`, `cv_hal_invSqrt64f`.

Perf test done on MUSE-PI and CanMV K230. Because the performance of scalar is much worse than universal intrinsic, only ui and hal rvv is compared.

In RVV's UI, `invSqrt` is computed using `1 / sqrt()`. This patch first uses `frsqrt` and then applies the Newton-Raphson method to achieve higher precision. For the initial value, I tried using the famous [fast inverse square root algorithm](https://en.wikipedia.org/wiki/Fast_inverse_square_root), which involves one bit shift and one subtraction. However, on both MUSE-PI and CanMV K230, the performance was slightly lower (about 3%), so I chose to use `frsqrt` for the initial value instead. 

BTW, I think this patch can directly replace RVV's UI.

**UPDATE**: Due to strange vector registers allocation strategy in clang, for `invSqrt`, clang use LMUL m4 while gcc use LMUL m8, which leads to some performance loss in clang. So the test for clang is appended.

```sh
$ opencv_test_core --gtest_filter="Core_HAL/mathfuncs.*"
$ opencv_perf_core --gtest_filter="SqrtFixture.*" --perf_min_samples=300 --perf_force_samples=300
```

CanMV K230:
```
              Name of Test                 ui    rvv      rvv    
                                                           vs    
                                                           ui    
                                                       (x-factor)
Sqrt::SqrtFixture::(127x61, 5, false)    0.052  0.027     1.96   
Sqrt::SqrtFixture::(127x61, 5, true)     0.101  0.026     3.80   
Sqrt::SqrtFixture::(127x61, 6, false)    0.106  0.059     1.79   
Sqrt::SqrtFixture::(127x61, 6, true)     0.207  0.058     3.55   
Sqrt::SqrtFixture::(640x480, 5, false)   1.988  0.956     2.08   
Sqrt::SqrtFixture::(640x480, 5, true)    3.920  0.948     4.13   
Sqrt::SqrtFixture::(640x480, 6, false)   4.179  2.342     1.78   
Sqrt::SqrtFixture::(640x480, 6, true)    8.220  2.290     3.59   
Sqrt::SqrtFixture::(1280x720, 5, false)  5.969  2.881     2.07   
Sqrt::SqrtFixture::(1280x720, 5, true)   11.731 2.857     4.11   
Sqrt::SqrtFixture::(1280x720, 6, false)  12.533 7.031     1.78   
Sqrt::SqrtFixture::(1280x720, 6, true)   24.643 6.917     3.56   
Sqrt::SqrtFixture::(1920x1080, 5, false) 13.423 6.483     2.07   
Sqrt::SqrtFixture::(1920x1080, 5, true)  26.379 6.436     4.10   
Sqrt::SqrtFixture::(1920x1080, 6, false) 28.200 15.833    1.78   
Sqrt::SqrtFixture::(1920x1080, 6, true)  55.434 15.565    3.56   
```

MUSE-PI:
```
                                                 GCC              |        clang            
              Name of Test                 ui    rvv      rvv     |   ui    rvv      rvv    
                                                           vs     |                   vs    
                                                           ui     |                   ui    
                                                       (x-factor) |               (x-factor)
Sqrt::SqrtFixture::(127x61, 5, false)    0.027  0.018     1.46    | 0.027  0.016     1.65   
Sqrt::SqrtFixture::(127x61, 5, true)     0.050  0.017     2.98    | 0.050  0.017     2.99   
Sqrt::SqrtFixture::(127x61, 6, false)    0.053  0.031     1.72    | 0.052  0.032     1.64   
Sqrt::SqrtFixture::(127x61, 6, true)     0.100  0.030     3.31    | 0.101  0.035     2.86   
Sqrt::SqrtFixture::(640x480, 5, false)   0.955  0.483     1.98    | 0.959  0.499     1.92   
Sqrt::SqrtFixture::(640x480, 5, true)    1.873  0.489     3.83    | 1.873  0.520     3.60   
Sqrt::SqrtFixture::(640x480, 6, false)   2.027  1.163     1.74    | 2.037  1.218     1.67   
Sqrt::SqrtFixture::(640x480, 6, true)    3.961  1.153     3.44    | 3.961  1.341     2.95   
Sqrt::SqrtFixture::(1280x720, 5, false)  2.916  1.538     1.90    | 2.912  1.598     1.82   
Sqrt::SqrtFixture::(1280x720, 5, true)   5.735  1.534     3.74    | 5.726  1.661     3.45   
Sqrt::SqrtFixture::(1280x720, 6, false)  6.121  3.585     1.71    | 6.109  3.725     1.64   
Sqrt::SqrtFixture::(1280x720, 6, true)   12.059 3.501     3.44    | 12.053 4.080     2.95   
Sqrt::SqrtFixture::(1920x1080, 5, false) 6.540  3.535     1.85    | 6.540  3.643     1.80   
Sqrt::SqrtFixture::(1920x1080, 5, true)  12.943 3.445     3.76    | 12.908 3.706     3.48   
Sqrt::SqrtFixture::(1920x1080, 6, false) 13.714 8.062     1.70    | 13.711 8.376     1.64   
Sqrt::SqrtFixture::(1920x1080, 6, true)  27.011 7.989     3.38    | 27.115 9.245     2.93   
```

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…ncorrect-detection-near-image-edge

Fix Aruco marker incorrect detection near image edge opencv#26968

### Pull Request Readiness Checklist

Fix opencv#26922 

As I understood the algorithm, at the first stage we search for the contours of the marker several times (adaptive threshold with different windows sizes). Therefore, for the same marker, we get several contours (inner and outer with different sizes due to the different windows sizes). In the second stage, we group the contours for the same marker into one group, from which we take the largest contour as the best candidate (which should best match the border of the marker).

The problem is that using the `minDistanceToBorder` parameter, we discard contours at the first stage. Thus, we discard the best candidates most appropriate to the marker border, and inner contours may remain, representing a significantly smaller marker border (which we observe in the issue).

But if we use the `minDistanceToBorder` parameter to discard the best candidate of the group at the second stage, then there will be no such problems and we will completely discard markers located too close to the border of the image.

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.
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core: vectorize normDiff with universal intrinsics opencv#27042

Merge with opencv/opencv_extra#1242.

Performance results on Desktop Intel i7-12700K, Apple M2, Jetson Orin and SpaceMIT K1:

[perf-normDiff.zip](https://github.com/user-attachments/files/19178689/perf-normDiff.zip)


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RISC-V: Fix opencv#27003.

Added optional mask to cv::threshold opencv#26842
 
Proposal for opencv#26777

To avoid code duplication, and keep performance when no mask is used, inner implementation always propagate the const cv::Mat& mask, but they use a template<bool useMask> parameter that let the compiler optimize out unnecessary tests when the mask is not to be used.

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

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Find contours speedup opencv#26834

It is an attempt, as suggested by opencv#26775, to restore lost speed when migrating `findContours()` implementation from C to C++

The patch adds an "Arena" (a pool) of pre-allocated memory so that contours points (and TreeNodes) can be picked from the Arena.
The code of `findContours()` is mostly unchanged, the arena usage being implicit through a utility class Arena::Item that provides C++ overloaded operators and construct/destruct logic.

As mentioned in opencv#26775, the contour points are allocated and released in order, and can be represented by ranges of indices in their arena. No range subset will be released and drill a hole, that's why the internal representation as a range of indices makes sense.

The TreeNodes use another Arena class that does not comply to that range logic.

Currently, there is a significant improvement of the run-time on the test mentioned in opencv#26775, but it is still far from the `findContours_legacy()` performance.


- [x] I agree to contribute to the project under Apache 2 License.
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Local decolor pipeline optimization

Test for in-memory animation encoding and decoding opencv#27013
 
Tests for opencv#26964

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Make sure there are enough channels to check for opacity opencv#27040

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[HAL RVV] impl magnitude | add perf test opencv#27002

Implement through the existing `cv_hal_magnitude32f` and `cv_hal_magnitude64f` interfaces.

**UPDATE**: UI is enabled. The only difference between UI and HAL now is HAL use a approximate `sqrt`.

Perf test done on MUSE-PI.

```sh
$ opencv_test_core --gtest_filter="*Magnitude*"
$ opencv_perf_core --gtest_filter="*Magnitude*" --perf_min_samples=300 --perf_force_samples=300
```

Test result between enabled UI and HAL:
```
                 Name of Test                     ui    rvv      rvv    
                                                                  vs    
                                                                  ui    
                                                              (x-factor)
Magnitude::MagnitudeFixture::(127x61, 32FC1)    0.029  0.016     1.75   
Magnitude::MagnitudeFixture::(127x61, 64FC1)    0.057  0.036     1.57   
Magnitude::MagnitudeFixture::(640x480, 32FC1)   1.063  0.648     1.64   
Magnitude::MagnitudeFixture::(640x480, 64FC1)   2.261  1.530     1.48   
Magnitude::MagnitudeFixture::(1280x720, 32FC1)  3.261  2.118     1.54   
Magnitude::MagnitudeFixture::(1280x720, 64FC1)  6.802  4.682     1.45   
Magnitude::MagnitudeFixture::(1920x1080, 32FC1) 7.287  4.738     1.54   
Magnitude::MagnitudeFixture::(1920x1080, 64FC1) 15.226 10.334    1.47   
```

Test result before and after enabling UI:
```
                 Name of Test                    orig    pr       pr    
                                                                  vs    
                                                                 orig   
                                                              (x-factor)
Magnitude::MagnitudeFixture::(127x61, 32FC1)    0.032  0.029     1.11   
Magnitude::MagnitudeFixture::(127x61, 64FC1)    0.067  0.057     1.17   
Magnitude::MagnitudeFixture::(640x480, 32FC1)   1.228  1.063     1.16   
Magnitude::MagnitudeFixture::(640x480, 64FC1)   2.786  2.261     1.23   
Magnitude::MagnitudeFixture::(1280x720, 32FC1)  3.762  3.261     1.15   
Magnitude::MagnitudeFixture::(1280x720, 64FC1)  8.549  6.802     1.26   
Magnitude::MagnitudeFixture::(1920x1080, 32FC1) 8.408  7.287     1.15   
Magnitude::MagnitudeFixture::(1920x1080, 64FC1) 18.884 15.226    1.24   
```

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Fix some vectorized loop conditions.

[HAL RVV] reuse atan | impl cart_to_polar | add perf test opencv#27000

Implement through the existing `cv_hal_cartToPolar32f` and `cv_hal_cartToPolar64f` interfaces.

Add `cartToPolar` performance tests.

cv_hal_rvv::fast_atan is modified to make it more reusable because it's needed in cartToPolar.

**UPDATE**: UI enabled. Since the vec type of RVV can't be stored in struct. UI implementation of `v_atan_f32` is modified. Both `fastAtan` and `cartToPolar` are affected so the test result for `atan` is also appended. I have tested the modified UI on RVV and AVX2 and no regressions appears.

Perf test done on MUSE-PI. AVX2 test done on Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz.

```sh
$ opencv_test_core --gtest_filter="*CartToPolar*:*Core_CartPolar_reverse*:*Phase*" 
$ opencv_perf_core --gtest_filter="*CartToPolar*:*phase*" --perf_min_samples=300 --perf_force_samples=300
```

Test result between enabled UI and HAL:
```
                   Name of Test                       ui    rvv      rvv    
                                                                      vs    
                                                                      ui    
                                                                  (x-factor)
CartToPolar::CartToPolarFixture::(127x61, 32FC1)    0.106  0.059     1.80   
CartToPolar::CartToPolarFixture::(127x61, 64FC1)    0.155  0.070     2.20   
CartToPolar::CartToPolarFixture::(640x480, 32FC1)   4.188  2.317     1.81   
CartToPolar::CartToPolarFixture::(640x480, 64FC1)   6.593  2.889     2.28   
CartToPolar::CartToPolarFixture::(1280x720, 32FC1)  12.600 7.057     1.79   
CartToPolar::CartToPolarFixture::(1280x720, 64FC1)  19.860 8.797     2.26   
CartToPolar::CartToPolarFixture::(1920x1080, 32FC1) 28.295 15.809    1.79   
CartToPolar::CartToPolarFixture::(1920x1080, 64FC1) 44.573 19.398    2.30   
phase32f::VectorLength::128                         0.002  0.002     1.20   
phase32f::VectorLength::1000                        0.008  0.006     1.32   
phase32f::VectorLength::131072                      1.061  0.731     1.45   
phase32f::VectorLength::524288                      3.997  2.976     1.34   
phase32f::VectorLength::1048576                     8.001  5.959     1.34   
phase64f::VectorLength::128                         0.002  0.002     1.33   
phase64f::VectorLength::1000                        0.012  0.008     1.58   
phase64f::VectorLength::131072                      1.648  0.931     1.77   
phase64f::VectorLength::524288                      6.836  3.837     1.78   
phase64f::VectorLength::1048576                     14.060 7.540     1.86   
```

Test result before and after enabling UI on RVV:
```
                   Name of Test                      perf   perf     perf   
                                                      ui     ui       ui    
                                                     orig    pr       pr    
                                                                      vs    
                                                                     perf   
                                                                      ui    
                                                                     orig   
                                                                  (x-factor)
CartToPolar::CartToPolarFixture::(127x61, 32FC1)    0.141  0.106     1.33   
CartToPolar::CartToPolarFixture::(127x61, 64FC1)    0.187  0.155     1.20   
CartToPolar::CartToPolarFixture::(640x480, 32FC1)   5.990  4.188     1.43   
CartToPolar::CartToPolarFixture::(640x480, 64FC1)   8.370  6.593     1.27   
CartToPolar::CartToPolarFixture::(1280x720, 32FC1)  18.214 12.600    1.45   
CartToPolar::CartToPolarFixture::(1280x720, 64FC1)  25.365 19.860    1.28   
CartToPolar::CartToPolarFixture::(1920x1080, 32FC1) 40.437 28.295    1.43   
CartToPolar::CartToPolarFixture::(1920x1080, 64FC1) 56.699 44.573    1.27   
phase32f::VectorLength::128                         0.003  0.002     1.54   
phase32f::VectorLength::1000                        0.016  0.008     1.90   
phase32f::VectorLength::131072                      2.048  1.061     1.93   
phase32f::VectorLength::524288                      8.219  3.997     2.06   
phase32f::VectorLength::1048576                     16.426 8.001     2.05   
phase64f::VectorLength::128                         0.003  0.002     1.44   
phase64f::VectorLength::1000                        0.020  0.012     1.60   
phase64f::VectorLength::131072                      2.621  1.648     1.59   
phase64f::VectorLength::524288                      10.780 6.836     1.58   
phase64f::VectorLength::1048576                     22.723 14.060    1.62   
```

Test result before and after modifying UI on AVX2:
```
                   Name of Test                     perf  perf     perf   
                                                    avx2  avx2     avx2   
                                                    orig   pr       pr    
                                                                    vs    
                                                                   perf   
                                                                   avx2   
                                                                   orig   
                                                                (x-factor)
CartToPolar::CartToPolarFixture::(127x61, 32FC1)    0.006 0.005    1.14   
CartToPolar::CartToPolarFixture::(127x61, 64FC1)    0.010 0.009    1.08   
CartToPolar::CartToPolarFixture::(640x480, 32FC1)   0.273 0.264    1.03   
CartToPolar::CartToPolarFixture::(640x480, 64FC1)   0.511 0.487    1.05   
CartToPolar::CartToPolarFixture::(1280x720, 32FC1)  0.760 0.723    1.05   
CartToPolar::CartToPolarFixture::(1280x720, 64FC1)  2.009 1.937    1.04   
CartToPolar::CartToPolarFixture::(1920x1080, 32FC1) 1.996 1.923    1.04   
CartToPolar::CartToPolarFixture::(1920x1080, 64FC1) 5.721 5.509    1.04   
phase32f::VectorLength::128                         0.000 0.000    0.98   
phase32f::VectorLength::1000                        0.001 0.001    0.97   
phase32f::VectorLength::131072                      0.105 0.111    0.95   
phase32f::VectorLength::524288                      0.402 0.402    1.00   
phase32f::VectorLength::1048576                     0.775 0.767    1.01   
phase64f::VectorLength::128                         0.000 0.000    1.00   
phase64f::VectorLength::1000                        0.001 0.001    1.01   
phase64f::VectorLength::131072                      0.163 0.162    1.01   
phase64f::VectorLength::524288                      0.669 0.653    1.02   
phase64f::VectorLength::1048576                     1.660 1.634    1.02   
```

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Move the CV_Assert above the << operation to not trigger the fuzzer

Co-authored-by: Liutong HAN <liutong2020@iscas.ac.cn>

[RVV HAL] Add copyright and replace '#pragma once'. opencv#27056

Add copyright and in RVV HAL, since other companies or teams may join the development and add their copyright.

And the '#pragma once' are replaced.

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Optimize RISC-V HAL cv::sepFilter

…Detector-detectMarkers

Add test for ArucoDetector::detectMarkers opencv#27079

### Pull Request Readiness Checklist

Related to opencv#26968 and opencv#26922

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[HAL RVV] unify and impl polar_to_cart | add perf test opencv#26999

### Summary

1. Implement through the existing `cv_hal_polarToCart32f` and `cv_hal_polarToCart64f` interfaces.
2. Add `polarToCart` performance tests
3. Make `cv::polarToCart` use CALL_HAL in the same way as `cv::cartToPolar`
4. To achieve the 3rd point, the original implementation was moved, and some modifications were made.

Tested through:
```sh
opencv_test_core --gtest_filter="*PolarToCart*:*Core_CartPolar_reverse*" 
opencv_perf_core --gtest_filter="*PolarToCart*" --perf_min_samples=300 --perf_force_samples=300
```

### HAL performance test

***UPDATE***: Current implementation is no more depending on vlen.

**NOTE**: Due to the 4th point in the summary above, the `scalar` and `ui` test is based on the modified code of this PR. The impact of this patch on `scalar` and `ui` is evaluated in the next section, `Effect of Point 4`.

Vlen 256 (Muse Pi):
```
                   Name of Test                     scalar    ui     rvv       ui        rvv    
                                                                               vs         vs    
                                                                             scalar     scalar  
                                                                           (x-factor) (x-factor)
PolarToCart::PolarToCartFixture::(127x61, 32FC1)     0.315  0.110  0.034     2.85       9.34   
PolarToCart::PolarToCartFixture::(127x61, 64FC1)     0.423  0.163  0.045     2.59       9.34   
PolarToCart::PolarToCartFixture::(640x480, 32FC1)   13.695  4.325  1.278     3.17      10.71   
PolarToCart::PolarToCartFixture::(640x480, 64FC1)   17.719  7.118  2.105     2.49       8.42   
PolarToCart::PolarToCartFixture::(1280x720, 32FC1)  40.678  13.114 3.977     3.10      10.23   
PolarToCart::PolarToCartFixture::(1280x720, 64FC1)  53.124  21.298 6.519     2.49       8.15   
PolarToCart::PolarToCartFixture::(1920x1080, 32FC1) 95.158  29.465 8.894     3.23      10.70   
PolarToCart::PolarToCartFixture::(1920x1080, 64FC1) 119.262 47.743 14.129    2.50       8.44   
```

### Effect of Point 4

To make `cv::polarToCart` behave the same as `cv::cartToPolar`, the implementation detail of the former has been moved to the latter's location (from `mathfuncs.cpp` to `mathfuncs_core.simd.hpp`).

#### Reason for Changes:

This function works as follows:  
$y = \text{mag} \times \sin(\text{angle})$ and $x = \text{mag} \times \cos(\text{angle})$. The original implementation first calculates the values of $\sin$ and $\cos$, storing the results in the output buffers $x$ and $y$, and then multiplies the result by $\text{mag}$. 

However, when the function is used as an in-place operation (one of the output buffers is also an input buffer), the original implementation allocates an extra buffer to store the $\sin$ and $\cos$ values in case the $\text{mag}$ value gets overwritten. This extra buffer allocation prevents `cv::polarToCart` from functioning in the same way as `cv::cartToPolar`.

Therefore, the multiplication is now performed immediately without storing intermediate values. Since the original implementation also had AVX2 optimizations, I have applied the same optimizations to the AVX2 version of this implementation.

***UPDATE***: UI use v_sincos from opencv#25892 now. The original implementation has AVX2 optimizations but is slower much than current UI so it's removed, and AVX2 perf test is below. Scalar implementation isn't changed because it's faster than using UI's method.

#### Test Result

`scalar` and `ui` test is done on Muse PI, and AVX2 test is done on Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz.

`scalar` test:
```
                   Name of Test                      orig     pr        pr    
                                                                        vs    
                                                                       orig   
                                                                    (x-factor)
PolarToCart::PolarToCartFixture::(127x61, 32FC1)     0.333   0.294     1.13   
PolarToCart::PolarToCartFixture::(127x61, 64FC1)     0.385   0.403     0.96   
PolarToCart::PolarToCartFixture::(640x480, 32FC1)   14.749  12.343     1.19   
PolarToCart::PolarToCartFixture::(640x480, 64FC1)   19.419  16.743     1.16   
PolarToCart::PolarToCartFixture::(1280x720, 32FC1)  44.155  37.822     1.17   
PolarToCart::PolarToCartFixture::(1280x720, 64FC1)  62.108  50.358     1.23   
PolarToCart::PolarToCartFixture::(1920x1080, 32FC1) 99.011  85.769     1.15   
PolarToCart::PolarToCartFixture::(1920x1080, 64FC1) 127.740 112.874    1.13   
```

`ui` test:
```
                   Name of Test                      orig     pr        pr    
                                                                        vs    
                                                                       orig   
                                                                    (x-factor)
PolarToCart::PolarToCartFixture::(127x61, 32FC1)     0.306  0.110     2.77   
PolarToCart::PolarToCartFixture::(127x61, 64FC1)     0.455  0.163     2.79   
PolarToCart::PolarToCartFixture::(640x480, 32FC1)   13.381  4.325     3.09   
PolarToCart::PolarToCartFixture::(640x480, 64FC1)   21.851  7.118     3.07   
PolarToCart::PolarToCartFixture::(1280x720, 32FC1)  39.975  13.114    3.05   
PolarToCart::PolarToCartFixture::(1280x720, 64FC1)  67.006  21.298    3.15   
PolarToCart::PolarToCartFixture::(1920x1080, 32FC1) 90.362  29.465    3.07   
PolarToCart::PolarToCartFixture::(1920x1080, 64FC1) 129.637 47.743    2.72   
```

AVX2 test:
```
                   Name of Test                     orig   pr       pr    
                                                                    vs    
                                                                   orig   
                                                                (x-factor)
PolarToCart::PolarToCartFixture::(127x61, 32FC1)    0.019 0.009    2.11   
PolarToCart::PolarToCartFixture::(127x61, 64FC1)    0.022 0.013    1.74   
PolarToCart::PolarToCartFixture::(640x480, 32FC1)   0.788 0.355    2.22   
PolarToCart::PolarToCartFixture::(640x480, 64FC1)   1.102 0.618    1.78   
PolarToCart::PolarToCartFixture::(1280x720, 32FC1)  2.383 1.042    2.29   
PolarToCart::PolarToCartFixture::(1280x720, 64FC1)  3.758 2.316    1.62   
PolarToCart::PolarToCartFixture::(1920x1080, 32FC1) 5.577 2.559    2.18   
PolarToCart::PolarToCartFixture::(1920x1080, 64FC1) 9.710 6.424    1.51   
```

A slight performance loss occurs because the check for whether $mag$ is nullptr is performed with every calculation, instead of being done once per batch. This is to reuse current `SinCos_32f` function.

### 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
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      Patch to opencv_extra has the same branch name.
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displayOverlay doesn't disappear after timeout opencv#27082

Fixes opencv#26555

### Expected Behaviour
An overlay should be displayed atop an image and then disappear after `delayms` has timed out, but it doesn't. Also, `displayStatusBar` doesn't appear to set any text on the window.

### Actual Behaviour
The overlay appears but doesn't disappear unless a mouse move event happens on the image.

### Changes
- Fixed the issue with `displayOverlay` not disappearing after the timeout.

### Checklist
- [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.
- [ ] There is accuracy test, performance test, and test data in the opencv_extra repository, if applicable.
- [ ] The feature is well documented, and sample code can be built with the project CMake.

Add RISC-V HAL implementation for cv::threshold and cv::adaptiveThreshold opencv#27072

This patch implements `cv_hal_threshold_otsu` and `cv_hal_adaptiveThreshold` using native intrinsics, optimizing the performance of `cv::threshold(THRESH_OTSU)` and `cv::adaptiveThreshold`.

Since UI is as fast as HAL `cv_hal_rvv::threshold::threshold` so `cv_hal_threshold` is not redirected, but this part of HAL is keeped because `cv_hal_threshold_otsu` depends on it.

Tested on MUSE-PI (Spacemit X60) for both gcc 14.2 and clang 20.0.

```
$ ./opencv_test_imgproc --gtest_filter="*thresh*:*Thresh*"
$ ./opencv_perf_imgproc --gtest_filter="*otsu*:*adaptiveThreshold*" --perf_min_samples=1000 --perf_force_samples=1000
```

![image](https://github.com/user-attachments/assets/4bb953f8-8589-4af1-8f1c-99e2c506be3c)

### 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
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

core: improve norm of hal rvv opencv#26991

Merge with opencv/opencv_extra#1241

### 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
- [ ] There is a reference to the original bug report and related work
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      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

Co-authored-by: Liutong HAN <liutong2020@iscas.ac.cn>

imgcodecs: gif: support animated gif without loop opencv#26971

Close opencv#26970

### 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
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hal_rvv: further optimized flip opencv#27257

Checklist:
- [x] flipX
- [x] flipY
- [x] flipXY

### 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
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

Enable GIF support by default

…isteroutput

Add CV_WRAP to registerOutput for language bindings support

…-V platforms

hal/riscv_rvv: implemented flip_inplace to boost cv::rotate

…geneous_transformation

Add additional information about homogeneous transformations in the calib3d doc