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Author SHA1 Message Date
s-trinh e258f2595e Merge pull request #26299 from s-trinh:feat/getClosestEllipsePoints_2
Add getClosestEllipsePoints() function to get the closest point on an ellipse #26299

Following https://github.com/opencv/opencv/issues/26078, I was thinking that a function to get for a considered 2d point the corresponding closest point (or maybe directly the distance?) on an ellipse could be useful.
This would allow computing the fitting error with `fitEllipse()` for instance.

Code is based from:
- https://stackoverflow.com/questions/22959698/distance-from-given-point-to-given-ellipse/46007540#46007540
- https://blog.chatfield.io/simple-method-for-distance-to-ellipse/
- https://github.com/0xfaded/ellipse_demo

---

Demo code:

<details>
  <summary>code</summary>
 
```cpp
#include <iostream>
#include <opencv2/opencv.hpp>

namespace
{
void scaleApplyColormap(const cv::Mat &img_float, cv::Mat &img)
{
  cv::Mat img_scale = cv::Mat::zeros(img_float.size(), CV_8UC3);

  double min_val = 0, max_val = 0;
  cv::minMaxLoc(img_float, &min_val, &max_val);
  std::cout << "min_val=" << min_val << " ; max_val=" << max_val << std::endl;

  if (max_val - min_val > 1e-2) {
    float a = 255 / (max_val - min_val);
    float b = -a * min_val;

    cv::convertScaleAbs(img_float, img_scale, a, b);
    cv::applyColorMap(img_scale, img, cv::COLORMAP_TURBO);
  }
  else {
    std::cerr << "max_val - min_val <= 1e-2" << std::endl;
  }
}

cv::Mat drawEllipseDistanceMap(const cv::RotatedRect &ellipse_params)
{
  float bb_rect_w = ellipse_params.center.x + ellipse_params.size.width;
  float bb_rect_h = ellipse_params.center.y + ellipse_params.size.height;

  std::vector<cv::Point2f> points_list;
  points_list.resize(1);
  cv::Mat pointsf;
  cv::Mat closest_pts;
  cv::Mat dist_map = cv::Mat::zeros(bb_rect_h*1.5, bb_rect_w*1.5, CV_32F);
  for (int i = 0; i < dist_map.rows; i++) {
    for (int j = 0; j < dist_map.cols; j++) {
      points_list[0].x = j;
      points_list[0].y = i;
      cv::Mat(points_list).convertTo(pointsf, CV_32F);
      cv::getClosestEllipsePoints(ellipse_params, pointsf, closest_pts);
      dist_map.at<float>(i, j) = std::hypot(closest_pts.at<cv::Point2f>(0).x-j, closest_pts.at<cv::Point2f>(0).y-i);
    }
  }

  cv::Mat dist_map_8u;
  scaleApplyColormap(dist_map, dist_map_8u);
  return dist_map_8u;
}
}

int main()
{
  std::vector<cv::Point2f> points_list;

  // [1434, 308], [1434, 309], [1433, 310], [1427, 310], [1427, 312], [1426, 313], [1422, 313], [1422, 314],
  points_list.push_back(cv::Point2f(1434, 308));
  points_list.push_back(cv::Point2f(1434, 309));
  points_list.push_back(cv::Point2f(1433, 310));
  points_list.push_back(cv::Point2f(1427, 310));
  points_list.push_back(cv::Point2f(1427, 312));
  points_list.push_back(cv::Point2f(1426, 313));
  points_list.push_back(cv::Point2f(1422, 313));
  points_list.push_back(cv::Point2f(1422, 314));

  // [1421, 315], [1415, 315], [1415, 316], [1414, 317], [1408, 317], [1408, 319], [1407, 320], [1403, 320],
  points_list.push_back(cv::Point2f(1421, 315));
  points_list.push_back(cv::Point2f(1415, 315));
  points_list.push_back(cv::Point2f(1415, 316));
  points_list.push_back(cv::Point2f(1414, 317));
  points_list.push_back(cv::Point2f(1408, 317));
  points_list.push_back(cv::Point2f(1408, 319));
  points_list.push_back(cv::Point2f(1407, 320));
  points_list.push_back(cv::Point2f(1403, 320));

  // [1403, 321], [1402, 322], [1396, 322], [1396, 323], [1395, 324], [1389, 324], [1389, 326], [1388, 327],
  points_list.push_back(cv::Point2f(1403, 321));
  points_list.push_back(cv::Point2f(1402, 322));
  points_list.push_back(cv::Point2f(1396, 322));
  points_list.push_back(cv::Point2f(1396, 323));
  points_list.push_back(cv::Point2f(1395, 324));
  points_list.push_back(cv::Point2f(1389, 324));
  points_list.push_back(cv::Point2f(1389, 326));
  points_list.push_back(cv::Point2f(1388, 327));

  // [1382, 327], [1382, 328], [1381, 329], [1376, 329], [1376, 330], [1375, 331], [1369, 331], [1369, 333],
  points_list.push_back(cv::Point2f(1382, 327));
  points_list.push_back(cv::Point2f(1382, 328));
  points_list.push_back(cv::Point2f(1381, 329));
  points_list.push_back(cv::Point2f(1376, 329));
  points_list.push_back(cv::Point2f(1376, 330));
  points_list.push_back(cv::Point2f(1375, 331));
  points_list.push_back(cv::Point2f(1369, 331));
  points_list.push_back(cv::Point2f(1369, 333));

  // [1368, 334], [1362, 334], [1362, 335], [1361, 336], [1359, 336], [1359, 1016], [1365, 1016], [1366, 1017],
  points_list.push_back(cv::Point2f(1368, 334));
  points_list.push_back(cv::Point2f(1362, 334));
  points_list.push_back(cv::Point2f(1362, 335));
  points_list.push_back(cv::Point2f(1361, 336));
  points_list.push_back(cv::Point2f(1359, 336));
  points_list.push_back(cv::Point2f(1359, 1016));
  points_list.push_back(cv::Point2f(1365, 1016));
  points_list.push_back(cv::Point2f(1366, 1017));

  // [1366, 1019], [1430, 1019], [1430, 1017], [1431, 1016], [1440, 1016], [1440, 308]
  points_list.push_back(cv::Point2f(1366, 1019));
  points_list.push_back(cv::Point2f(1430, 1019));
  points_list.push_back(cv::Point2f(1430, 1017));
  points_list.push_back(cv::Point2f(1431, 1016));
  points_list.push_back(cv::Point2f(1440, 1016));
  points_list.push_back(cv::Point2f(1440, 308));

  cv::Mat pointsf;
  cv::Mat(points_list).convertTo(pointsf, CV_32F);

  cv::RotatedRect ellipse_params = cv::fitEllipseAMS(pointsf);
  std::cout << "ellipse_params, center=" << ellipse_params.center << " ; size=" << ellipse_params.size
    << " ; angle=" << ellipse_params.angle << std::endl;

  cv::TickMeter tm;
  tm.start();
  cv::Mat dist_map_8u = drawEllipseDistanceMap(ellipse_params);
  tm.stop();
  std::cout << "Elapsed time: " << tm.getAvgTimeSec() << " sec" << std::endl;

  cv::Point center(ellipse_params.center.x, ellipse_params.center.y);
  cv::Point axis(ellipse_params.size.width/2, ellipse_params.size.height/2);
  std::vector<cv::Point> ellipse_pts_list;
  cv::ellipse2Poly(center, axis, ellipse_params.angle, 0, 360, 1, ellipse_pts_list);
  cv::polylines(dist_map_8u, ellipse_pts_list, false, cv::Scalar(0, 0, 0), 3);

  // Points to be fitted
  cv::Mat closest_pts;
  cv::getClosestEllipsePoints(ellipse_params, pointsf, closest_pts);
  for (int i = 0; i < closest_pts.rows; i++) {
    cv::Point pt;
    pt.x = closest_pts.at<cv::Point2f>(i).x;
    pt.y = closest_pts.at<cv::Point2f>(i).y;
    cv::circle(dist_map_8u, pt, 8, cv::Scalar(0, 0, 255), 2);
  }

  cv::imwrite("dist_map_8u.png", dist_map_8u);

  return EXIT_SUCCESS;
}
```
</details>

![image](https://github.com/user-attachments/assets/3345cc86-ba83-44f9-ac78-74058a33a7dc)

---

### 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
2025-06-03 17:12:16 +03:00
Liane Lin 8a0ea789e7 Merge pull request #27149 from liane-lin:4.x
Fix #25696: Solved the problem in Subdiv2D, empty delaunay triangulation #27149

Detailed description

Expected behaviour:
Given 4 points, where no three points are collinear, the Delaunay Triangulation Algorithm should return 2 triangles.

Actual:
The algorithm returns zero triangles in this particular case.

Fix:
The radius of the circumcircle tends to infinity when the points are closer to form collinear points, so the problem occurs because the super-triangles are not large enough,
which then results in certain edges are not swapped. The proposed solution just increases the super triangle, duplicating the value of constant for example.

### 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
- [ ] 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
2025-05-30 15:20:01 +03:00
Yuantao Feng c37f54aeed Merge pull request #27343 from fengyuentau:4x/build/fix_more_warnings
build: fix more warnings from recent gcc versions after #27337 #27343

More fixings after https://github.com/opencv/opencv/pull/27337

### 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
2025-05-21 16:12:09 +03:00
Yuantao Feng 166f76d224 Merge pull request #27337 from fengyuentau:4x/build/riscv/fix_warnings
build: fix warnings from recent gcc versions #27337

This PR addresses the following found warnings:
- [x] -Wmaybe-uninitialized
- [x] -Wunused-variable
- [x] -Wsign-compare

Tested building with GCC 14.2 (RISC-V 64).

### 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
2025-05-21 09:28:29 +03:00
Alexander Smorkalov 79a5e5276a Merge pull request #27334 from fengyuentau:4x/imgproc/compareHist_chisqr_simd
imgproc: vectorize mode CHISQR and CHISQR_ALT in compareHist
2025-05-21 07:07:57 +03:00
Yuantao Feng 9b08167769 hal/imgproc: add hal for calcHist and implement in hal:riscv-rvv (#27332)
hal/imgproc: add hal for calcHist and implement in hal/riscv-rvv #27332

### 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
2025-05-21 07:07:22 +03:00
Yuantao Feng 7fe8ce19d9 perf: vectorize mode CHISQR and CHISQR_ALT in compareHist 2025-05-19 17:09:33 +08:00
Madan mohan Manokar 84ea77a4be Merge pull request #27299 from amd:fast_medianblur_simd
imgproc: medianblur: Performance improvement #27299

* Bottleneck in non-vectorized path reduced.
* AVX512 dispatch added for medianblur.

### 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
2025-05-19 08:56:57 +03:00
Abhishek Gola 838babe351 Fixed bilateral filter's sigma color and sigma space issue 2025-05-14 14:22:05 +05:30
Alexander Smorkalov 306204089f Reworked HSV color conversion tables initialization for OpenCL branch. 2025-05-12 09:02:47 +03:00
Alexander Smorkalov f8de2e06e6 Merge branch 4.x 2025-05-07 13:17:42 +03:00
Kumataro 86a963cec9 Merge pull request #27226 from Kumataro:fix27225
imgproc: cvtColor: remove to copy edge pixels for COLOR_Bayer*_VNGs. #27226 

Close https://github.com/opencv/opencv/issues/27225
Close https://github.com/opencv/opencv/issues/5089
Related https://github.com/opencv/opencv_extra/pull/1249

### 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.
- [ ] The feature is well documented and sample code can be built with the project CMake
2025-04-25 11:29:22 +03:00
YooLc f20facc60a Merge pull request #27060 from YooLc:hal-rvv-integral
[hal_rvv] Add cv::integral implementation and more types of input for test #27060

This patch introduces an RVV-optimized implementation of `cv::integral()` in hal_rvv, along with performance and accuracy tests for all valid input/output type combinations specified in `modules/imgproc/src/hal_replacement.hpp`:
https://github.com/opencv/opencv/blob/2a8d4b8e43f6e499c5553edd26056caed284d5a6/modules/imgproc/src/hal_replacement.hpp#L960-L974

The vectorized prefix sum algorithm follows the approach described in [Prefix Sum with SIMD - Algorithmica](https://en.algorithmica.org/hpc/algorithms/prefix/).

I intentionally omitted support for the following cases by returning `CV_HAL_ERROR_NOT_IMPLEMENTED`, as they are harder to implement or show limited performance gains:
1. **Tilted Sum**: The data access pattern for tilted sums requires multi-row operations, making effective vectorization difficult.
2. **3-channel images (`cn == 3`)**: Current implementation requires `VLEN/SEW` (a.k.a. number of elements in a vector register) to be a multiple of channel count, which 3-channel formats typically cannot satisfy.
    - Support for 1, 2 and 4 channel images is implemented
4. **Small images (`!(width >> 8 || height >> 8)`)**: The scalar implementation demonstrates better performance for images with limited dimensions. 
    - This is the same as `3rdparty/ndsrvp/src/integral.cpp` https://github.com/opencv/opencv/blob/09c71aed141210bf2b14582974ed9d231c24edd5/3rdparty/ndsrvp/src/integral.cpp#L24-L26

Test configuration:

- Platform: SpacemiT Muse Pi (K1 @ 1.60 Ghz)
- Toolchain: GCC 14.2.0
- `integral_sqsum_full` test is disabled by default, so `--gtest_also_run_disabled_tests` is needed

Test results:

```plaintext
Geometric mean (ms)

                                     Name of Test                                       imgproc-gcc-scalar imgproc-gcc-hal  imgproc-gcc-hal  
                                                                                                                                   vs        
                                                                                                                           imgproc-gcc-scalar
                                                                                                                               (x-factor)      
integral::Size_MatType_OutMatDepth::(640x480, 8UC1, CV_32F)                                   1.973             1.415             1.39       
integral::Size_MatType_OutMatDepth::(640x480, 8UC1, CV_32S)                                   1.343             1.351             0.99       
integral::Size_MatType_OutMatDepth::(640x480, 8UC1, CV_64F)                                   2.021             2.756             0.73       
integral::Size_MatType_OutMatDepth::(640x480, 8UC2, CV_32F)                                   4.695             2.874             1.63       
integral::Size_MatType_OutMatDepth::(640x480, 8UC2, CV_32S)                                   4.028             2.801             1.44       
integral::Size_MatType_OutMatDepth::(640x480, 8UC2, CV_64F)                                   5.965             4.926             1.21       
integral::Size_MatType_OutMatDepth::(640x480, 8UC4, CV_32F)                                   9.970             4.440             2.25       
integral::Size_MatType_OutMatDepth::(640x480, 8UC4, CV_32S)                                   7.934             4.244             1.87       
integral::Size_MatType_OutMatDepth::(640x480, 8UC4, CV_64F)                                   14.696            8.431             1.74       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC1, CV_32F)                                  5.949             4.108             1.45       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC1, CV_32S)                                  4.064             4.080             1.00       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC1, CV_64F)                                  6.137             7.975             0.77       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC2, CV_32F)                                  13.896            8.721             1.59       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC2, CV_32S)                                  10.948            8.513             1.29       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC2, CV_64F)                                  18.046           15.234             1.18       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC4, CV_32F)                                  35.105           13.778             2.55       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC4, CV_32S)                                  27.135           13.417             2.02       
integral::Size_MatType_OutMatDepth::(1280x720, 8UC4, CV_64F)                                  43.477           25.616             1.70       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC1, CV_32F)                                 13.386            9.281             1.44       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC1, CV_32S)                                 9.159             9.194             1.00       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC1, CV_64F)                                 13.776           17.836             0.77       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC2, CV_32F)                                 31.943           19.435             1.64       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC2, CV_32S)                                 24.747           18.946             1.31       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC2, CV_64F)                                 35.925           33.943             1.06       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC4, CV_32F)                                 66.493           29.692             2.24       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC4, CV_32S)                                 54.737           28.250             1.94       
integral::Size_MatType_OutMatDepth::(1920x1080, 8UC4, CV_64F)                                 91.880           57.495             1.60            
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC1, CV_32F)                             4.384             4.016             1.09       
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC1, CV_32S)                             3.676             3.960             0.93       
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC1, CV_64F)                             5.620             5.224             1.08       
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC2, CV_32F)                             9.971             7.696             1.30       
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC2, CV_32S)                             8.934             7.632             1.17       
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC2, CV_64F)                             9.927             9.759             1.02       
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC4, CV_32F)                             21.556           12.288             1.75       
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC4, CV_32S)                             21.261           12.089             1.76       
integral_sqsum::Size_MatType_OutMatDepth::(640x480, 8UC4, CV_64F)                             23.989           16.278             1.47       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC1, CV_32F)                            15.232           11.752             1.30       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC1, CV_32S)                            12.976           11.721             1.11       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC1, CV_64F)                            16.450           15.627             1.05       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC2, CV_32F)                            25.932           23.243             1.12       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC2, CV_32S)                            24.750           23.019             1.08       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC2, CV_64F)                            28.228           29.605             0.95       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC4, CV_32F)                            61.665           37.477             1.65       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC4, CV_32S)                            61.536           37.126             1.66       
integral_sqsum::Size_MatType_OutMatDepth::(1280x720, 8UC4, CV_64F)                            73.989           48.994             1.51       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC1, CV_32F)                           49.640           26.529             1.87       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC1, CV_32S)                           35.869           26.417             1.36       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC1, CV_64F)                           34.378           35.056             0.98       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC2, CV_32F)                           82.138           52.661             1.56       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC2, CV_32S)                           54.644           52.089             1.05       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC2, CV_64F)                           75.073           66.670             1.13       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC4, CV_32F)                          143.283           83.943             1.71       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC4, CV_32S)                          156.851           82.378             1.90       
integral_sqsum::Size_MatType_OutMatDepth::(1920x1080, 8UC4, CV_64F)                          521.594           111.375            4.68            
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC1, DEPTH_32F_32F))          3.529             2.787             1.27       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC1, DEPTH_32F_64F))          4.396             3.998             1.10       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC1, DEPTH_32S_32F))          3.229             2.774             1.16       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC1, DEPTH_32S_32S))          2.945             2.780             1.06       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC1, DEPTH_32S_64F))          3.857             3.995             0.97       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC1, DEPTH_64F_64F))          5.872             5.228             1.12       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (16UC1, DEPTH_64F_64F))         6.075             5.277             1.15       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (16SC1, DEPTH_64F_64F))         5.680             5.296             1.07       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC1, DEPTH_32F_32F))         3.355             2.896             1.16       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC1, DEPTH_32F_64F))         4.183             4.000             1.05       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC1, DEPTH_64F_64F))         6.237             5.143             1.21       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (64FC1, DEPTH_64F_64F))         4.753             4.783             0.99       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC2, DEPTH_32F_32F))          8.021             5.793             1.38       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC2, DEPTH_32F_64F))          9.963             7.704             1.29       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC2, DEPTH_32S_32F))          7.864             5.720             1.37       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC2, DEPTH_32S_32S))          7.141             5.699             1.25       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC2, DEPTH_32S_64F))          9.228             7.646             1.21       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC2, DEPTH_64F_64F))          9.940             9.759             1.02       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (16UC2, DEPTH_64F_64F))         10.606            9.716             1.09       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (16SC2, DEPTH_64F_64F))         9.933             9.751             1.02       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC2, DEPTH_32F_32F))         7.986             5.962             1.34       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC2, DEPTH_32F_64F))         9.243             7.598             1.22       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC2, DEPTH_64F_64F))         10.573            9.425             1.12       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (64FC2, DEPTH_64F_64F))         11.029            8.977             1.23       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC4, DEPTH_32F_32F))          17.236            8.881             1.94       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC4, DEPTH_32F_64F))          20.905           12.322             1.70       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC4, DEPTH_32S_32F))          16.011            8.666             1.85       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC4, DEPTH_32S_32S))          15.932            8.507             1.87       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC4, DEPTH_32S_64F))          20.713           12.115             1.71       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (8UC4, DEPTH_64F_64F))          23.953           16.284             1.47       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (16UC4, DEPTH_64F_64F))         25.127           16.341             1.54       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (16SC4, DEPTH_64F_64F))         24.950           16.441             1.52       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC4, DEPTH_32F_32F))         17.261            8.906             1.94       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC4, DEPTH_32F_64F))         21.944           12.073             1.82       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (32FC4, DEPTH_64F_64F))         25.921           15.539             1.67       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(640x480, (64FC4, DEPTH_64F_64F))         27.938           14.824             1.88       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC1, DEPTH_32F_32F))         11.156            8.260             1.35       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC1, DEPTH_32F_64F))         14.777           11.869             1.24       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC1, DEPTH_32S_32F))         9.693             8.221             1.18       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC1, DEPTH_32S_32S))         9.023             8.256             1.09       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC1, DEPTH_32S_64F))         13.276           11.821             1.12       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC1, DEPTH_64F_64F))         15.406           15.618             0.99       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (16UC1, DEPTH_64F_64F))        16.799           15.749             1.07       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (16SC1, DEPTH_64F_64F))        15.054           15.806             0.95       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC1, DEPTH_32F_32F))        10.055            7.999             1.26       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC1, DEPTH_32F_64F))        13.506           11.253             1.20       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC1, DEPTH_64F_64F))        14.952           15.021             1.00       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (64FC1, DEPTH_64F_64F))        13.761           14.002             0.98       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC2, DEPTH_32F_32F))         22.677           17.330             1.31       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC2, DEPTH_32F_64F))         26.283           23.237             1.13       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC2, DEPTH_32S_32F))         20.126           17.118             1.18       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC2, DEPTH_32S_32S))         19.337           17.041             1.13       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC2, DEPTH_32S_64F))         24.973           23.004             1.09       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC2, DEPTH_64F_64F))         29.959           29.585             1.01       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (16UC2, DEPTH_64F_64F))        33.598           29.599             1.14       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (16SC2, DEPTH_64F_64F))        46.213           29.741             1.55       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC2, DEPTH_32F_32F))        33.077           17.556             1.88       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC2, DEPTH_32F_64F))        33.960           22.991             1.48       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC2, DEPTH_64F_64F))        41.792           28.803             1.45       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (64FC2, DEPTH_64F_64F))        34.660           28.532             1.21       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC4, DEPTH_32F_32F))         52.989           27.659             1.92       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC4, DEPTH_32F_64F))         62.418           37.515             1.66       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC4, DEPTH_32S_32F))         50.902           27.310             1.86       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC4, DEPTH_32S_32S))         47.301           27.019             1.75       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC4, DEPTH_32S_64F))         61.982           37.140             1.67       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (8UC4, DEPTH_64F_64F))         79.403           49.041             1.62       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (16UC4, DEPTH_64F_64F))        86.550           49.180             1.76       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (16SC4, DEPTH_64F_64F))        85.715           49.468             1.73       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC4, DEPTH_32F_32F))        63.932           28.019             2.28       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC4, DEPTH_32F_64F))        68.180           36.858             1.85       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (32FC4, DEPTH_64F_64F))        83.063           46.483             1.79       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1280x720, (64FC4, DEPTH_64F_64F))        91.990           44.545             2.07       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC1, DEPTH_32F_32F))        25.503           18.609             1.37       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC1, DEPTH_32F_64F))        29.544           26.635             1.11       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC1, DEPTH_32S_32F))        22.581           18.514             1.22       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC1, DEPTH_32S_32S))        20.860           18.547             1.12       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC1, DEPTH_32S_64F))        26.046           26.373             0.99       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC1, DEPTH_64F_64F))        34.831           34.997             1.00       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (16UC1, DEPTH_64F_64F))       36.428           35.214             1.03       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (16SC1, DEPTH_64F_64F))       32.435           35.314             0.92       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC1, DEPTH_32F_32F))       22.548           18.845             1.20       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC1, DEPTH_32F_64F))       28.589           25.790             1.11       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC1, DEPTH_64F_64F))       32.625           33.791             0.97       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (64FC1, DEPTH_64F_64F))       30.158           31.889             0.95       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC2, DEPTH_32F_32F))        53.374           38.938             1.37       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC2, DEPTH_32F_64F))        73.892           52.747             1.40       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC2, DEPTH_32S_32F))        47.392           38.572             1.23       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC2, DEPTH_32S_32S))        45.638           38.225             1.19       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC2, DEPTH_32S_64F))        69.966           52.156             1.34       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC2, DEPTH_64F_64F))        68.560           66.963             1.02       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (16UC2, DEPTH_64F_64F))       71.487           65.420             1.09       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (16SC2, DEPTH_64F_64F))       68.127           65.718             1.04       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC2, DEPTH_32F_32F))       72.967           39.987             1.82       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC2, DEPTH_32F_64F))       63.933           51.408             1.24       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC2, DEPTH_64F_64F))       73.334           63.354             1.16       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (64FC2, DEPTH_64F_64F))       80.983           60.778             1.33       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC4, DEPTH_32F_32F))       116.981           59.908             1.95       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC4, DEPTH_32F_64F))       155.085           83.974             1.85       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC4, DEPTH_32S_32F))       109.567           58.525             1.87       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC4, DEPTH_32S_32S))       105.457           57.124             1.85       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC4, DEPTH_32S_64F))       157.325           82.485             1.91       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (8UC4, DEPTH_64F_64F))       265.776           111.577            2.38       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (16UC4, DEPTH_64F_64F))      585.218           110.583            5.29       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (16SC4, DEPTH_64F_64F))      585.418           111.302            5.26       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC4, DEPTH_32F_32F))      126.456           60.415             2.09       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC4, DEPTH_32F_64F))      169.278           81.460             2.08       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (32FC4, DEPTH_64F_64F))      281.256           104.732            2.69       
integral_sqsum_full::Size_MatType_OutMatDepthArray::(1920x1080, (64FC4, DEPTH_64F_64F))      620.885           99.953             6.21       
```

The vectorized implementation shows progressively better acceleration for larger image sizes and higher channel counts, achieving up to 6.21× speedup for 64FC4 (1920×1080) inputs with `DEPTH_64F_64F` configuration.

This is my first time proposing patch for the OpenCV Project 🥹, if there's anything that can be improved, please tell me.

### 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
- [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
2025-04-21 09:50:13 +03:00
Kumataro c1d71d5375 Merge pull request #27220 from Kumataro:fix24757
imgproc: disable SIMD for compareHist(INTERSECT) if f64 is unsupported #27220

Close https://github.com/opencv/opencv/issues/24757

### 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.
- [ ] The feature is well documented and sample code can be built with the project CMake
2025-04-10 17:24:01 +03:00
天音あめ fa58c1205b Merge pull request #27119 from amane-ame:warp_hal_rvv
Add RISC-V HAL implementation for cv::warp series #27119

This patch implements `cv_hal_remap`, `cv_hal_warpAffine` and `cv_hal_warpPerspective` using native intrinsics, optimizing the performance of `cv::remap/cv::warpAffine/cv::warpPerspective` for `CV_HAL_INTER_NEAREST/CV_HAL_INTER_LINEAR/CV_HAL_INTER_CUBIC/CV_HAL_INTER_LANCZOS4` modes.

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

```
$ ./opencv_test_imgproc --gtest_filter="*Remap*:*Warp*"
$ ./opencv_perf_imgproc --gtest_filter="*Remap*:*remap*:*Warp*" --perf_min_samples=200 --perf_force_samples=200
```

View the full perf table here: [hal_rvv_warp.pdf](https://github.com/user-attachments/files/19403718/hal_rvv_warp.pdf)

### 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
2025-03-25 11:57:47 +03:00
Scorpion1234567 2e9345570f Merge pull request #27108 from Scorpion1234567:Multithreading-wrapPolar
When WARP_INVERSE_MAP is used, accelerate the calculation with multi-threading #27108

### 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
2025-03-20 17:46:18 +03:00
Liutong HAN fd62bd0991 Relax the loop condition to process the final batch. 2025-03-13 07:54:41 +00:00
Pierre Chatelier d83df66ff0 Merge pull request #26834 from chacha21:findContours_speedup
Find contours speedup #26834

It is an attempt, as suggested by #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 #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 #26775, but it is still far from the `findContours_legacy()` performance.


- [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 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
2025-03-12 18:00:01 +03:00
Pierre Chatelier 0db6a496ba Merge pull request #26842 from chacha21:threshold_with_mask
Added optional mask to cv::threshold #26842
 
Proposal for #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

- [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.
- [ ] The feature is well documented and sample code can be built with the project CMake
2025-03-12 17:55:07 +03:00
Alexander Smorkalov 4919cda8b2 Merge branch 4.x 2025-03-11 17:23:06 +03:00
Alexander Smorkalov f833519506 Warning fix on Windows. 2025-03-11 11:17:20 +03:00
Alexander Smorkalov 4bb57ceb73 Merge pull request #26868 from FantasqueX/bayer2gray-simd-2
Use universal intrinsics in bayer2gray
2025-03-11 09:55:09 +03:00
Alexander Smorkalov 40843d06ab Disable CV_SIMD_SCALABLE for demosaicing as the implementation is not efficient on RISC-V RVV. 2025-03-07 16:24:20 +03:00
Alexander Smorkalov 648424eaf2 Code review fixes. 2025-03-07 15:33:54 +03:00
Alexander Smorkalov fbffaa5276 Warning fix. 2025-03-07 11:56:26 +03:00
Alexander Smorkalov db40139f16 Merge branch 4.x 2025-03-05 10:28:32 +03:00
天音あめ cbcfd772ce Merge pull request #26958 from amane-ame:pyramids_hal_rvv
Add RISC-V HAL implementation for cv::pyrDown and cv::pyrUp #26958

This patch implements `cv_hal_pyrdown/cv_hal_pyrup` function in RVV_HAL using native intrinsics, optimizing the performance for `cv::pyrDown`, `cv::pyrUp` and `cv::buildPyramids` with data types `{8U,16S,32F} x {C1,C2,C3,C4,Cn}`.

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

```
$ ./opencv_test_imgproc --gtest_filter="*pyr*:*Pyr*"
$ ./opencv_perf_imgproc --gtest_filter="*pyr*:*Pyr*" --perf_min_samples=300 --perf_force_samples=300
```

<img width="1112" alt="Untitled" src="https://github.com/user-attachments/assets/235a9fba-0d29-434e-8a10-498212bac657" />


### 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
- [ ] The PR is proposed to the proper branch
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      Patch to opencv_extra has the same branch name.
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2025-03-04 15:41:15 +03:00
Maxim Smolskiy dbd3ef9a6f Merge pull request #26926 from MaximSmolskiy:fix-getPerspectiveTransform-for-singular-case
Fix getPerspectiveTransform for singular case #26926

### Pull Request Readiness Checklist

Fix #26916 

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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- [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.
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2025-03-02 12:44:39 +03:00
Alexander Smorkalov 1483504702 Merge branch 4.x 2025-02-20 13:58:04 +03:00
Skreg 4d15b2a33f Merge pull request #26914 from shyama7004:log/linearPolar
Removal of deprecated functions in imgproc #26914
 
Fixes : #26410

### Pull Request Readiness Checklist

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2025-02-18 14:03:45 +03:00
Alexander Smorkalov acc9084044 Move OpenVX integrations to imgproc to OpenVX HAL
Covered functions:
- medianBlur
- Sobel
- Canny
- pyrDown
- BoxFilter
- equalizeHist
- GaussianBlur
- remap
- threshold
2025-02-15 09:55:37 +03:00
Alexander Smorkalov 55a2ca58f0 Merge branch 4.x 2025-02-05 09:28:27 +03:00
Letu Ren 0fa61de22a Fix bayer2RGB_EA macro 2025-02-03 14:19:52 +08:00
Letu Ren d6dc22d03c Fix build on RISC-V 2025-02-03 00:09:36 +08:00
shyama7004 0cfc2e8fd8 minor change 2025-01-31 21:12:36 +05:30
Skreg e62ab4ff71 Merge pull request #26850 from shyama7004:update-headers
Update includes in filter.hpp #26850

Fixes :
```
identifier "Mat" is undefinedC/C++(20)
namespace "std" has no member "vector"C/C++(135)
```

### Pull Request Readiness Checklist

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2025-01-28 07:26:40 +03:00
Vincent Rabaud c5f6ed6fef Fix overlow pointers.
`step` and `maskStep` are used to increase/decrease `pImage`.
But it's done on unsigned type, relying on overflow, which is UB.
(step is size_t but seed.y is int and can be negative, the result
is therefore unsigned which can overflow)
2025-01-27 11:55:10 +01:00
Pierre Chatelier 3cbb4acd2d Merge pull request #26836 from chacha21:thresholding_compute_threshold_only
Add cv::THRESH_DRYRUN flag to get adaptive threshold values without thresholding #26836

A first proposal for #26777

Adds a `cv::THRESH_DRYRUN` flag to let cv::threshold() compute the threshold (useful for OTSU/TRIANGLE), but without actually running the thresholding. This flags is a proposal instead of a new function cv::computeThreshold()

- [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.
- [ ] The feature is well documented and sample code can be built with the project CMake
2025-01-24 14:25:21 +03:00
Maxim Smolskiy 8ab0ad6e1b Merge pull request #26810 from MaximSmolskiy:improve-robustness-for-fitEllipseAMS
Improve robustness for fitEllipseAMS #26810

### Pull Request Readiness Checklist

Related to #26694 

Added functionality to add noise to points in degenerate cases and try again for `fitEllipseAMS`. `fitEllipseNoDirect` and `fitEllipseDirect` already have this

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.
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2025-01-22 12:49:12 +03:00
Skreg fe9405e8c0 Merge pull request #26806 from shyama7004:fix-typo
* fix a small typo

* removal of unused variable
2025-01-20 17:14:27 +03:00
Maxim Smolskiy a2a3f5e86c Merge pull request #26773 from MaximSmolskiy:improve-robustness-for-ellipse-fitting
Improve robustness for ellipse fitting #26773

### Pull Request Readiness Checklist

Related to #26694 

Current noise addition is not very good because for example it turns degenerate case of one horizontal line into degenerate case of two parallel horizontal lines

Improving noise addition leads to improved robustness of algorithms

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
2025-01-20 14:25:40 +03:00
Vincent Rabaud e76924ef0d Don't overflow pointer addition
In both cases we add negative value (as unsigned type), so
pointer addition wraps, which is undefined behavior.
2025-01-15 11:07:43 +01:00
Yannis Guyon b62ab874d1 Avoid adding value to nullptr
This UB can be avoided by postponing calculation until needed.
2025-01-14 10:50:53 +01:00
Diego1V 052b2c43c3 Update types inside HoughLinesProbabilistic in order to handle great images. 2025-01-13 09:36:44 +03:00
FantasqueX 162179748a Merge pull request #26651 from FantasqueX:remove-msvs-2013
Remove MSVS 2013 related #26651

OpenCV 5.x requires MSVC >= 2017 15.7 and MSVS 2013 is EOF currently.

### 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
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
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2025-01-11 19:14:34 +03:00
FantasqueX d229ac9c76 Merge pull request #26676 from FantasqueX:clean-up-sse-utils-1
Clean up sse_utils.hpp #26676

Remove unused functions in sse_utils.hpp. If they are still needed, I believe universal intrinsics should be more appropriate.

Related: https://github.com/opencv/opencv/issues/25002

### 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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2025-01-10 14:35:42 +03:00
Masahiro Ogawa fc994a6ae8 Merge pull request #21407 from sensyn-robotics:feature/weighted_hough
Feature: weighted Hough Transform #21407

### Pull Request Readiness Checklist

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2025-01-06 15:35:35 +03:00
MaximSmolskiy ab0a818c84 Fix matchTemplate with mask crash 2025-01-02 22:14:08 +03:00
MaximSmolskiy f15fa21c6b Speed up and reduce memory consumption for findContours 2024-12-31 02:49:15 +03:00
Alexander Alekhin 09892c9d17 fix FFmpeg wrapper build 2024-12-26 12:15:46 +00:00