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3575 Commits

Author SHA1 Message Date
ekharkov d19dd94dee Moved IPP remap to HAL 2025-07-08 12:31:40 +02:00
eplankin c48dad1d9d Merge pull request #27324 from eplankin:warp_hal_4x
* Moved IPP impl of warpAffine to HAL
Co-authored-by: victorget <victor.getmanskiy@intel.com>
2025-07-04 12:04:31 +03:00
Martin 43112409ef Merge pull request #26974 from klosteraner:Fix-IntersectConvexConvex
Issue 26972: Proper treatment of float values in intersectConvexConvex #26974

As outlined in https://github.com/opencv/opencv/issues/26972 the function `intersectConvexConvex()` may not work as expected in the corner case, where two polygons intersect at a corner. A concrete example is given that I added as unit test. The unit test would fail without the proposed bug fix. I recommend porting the fix to all versions.

Now concerning the fix: When digging into the implementation I found, that when the line intersections are computed, openCV currently does not apply floating point comparison syntax, but pretends that line end points are exact. Instead I replaced the formulation using the eps that is already used in another component of the function in line.277: `epx=1e-5`. IMO that is solid enough, definitely better than assuming an exact floating point comparison is possible.

As a follow up I would suggest to use a scalable eps, s.t. also cases with high floating point numbers would be less error prone. However that would need to be done in all relevant sub steps, not just the line intersection code. So for me outside the scope of this fix.



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2025-06-28 22:06:42 +03:00
Alexander Smorkalov 5ee8919139 Merge pull request #27441 from KAVYANSHTYAGI:codex/find-feature-to-add-for-library
Add Support for Diamond-Shaped Structuring Element in Morphological Operations
2025-06-27 09:39:44 +03:00
Souriya Trinh ba70d1104f Check for empty vector to avoid throwing an exception in LineSegmentDetectorImpl::drawSegments() function. 2025-06-24 04:58:54 +02:00
Alexander Smorkalov 54fe519ae0 phaseCorrelate documentation imrpovement. 2025-06-23 12:28:09 +03:00
Yuantao Feng 3259863924 Merge pull request #27368 from fengyuentau:4x/imgproc/CreateHanningWindow-simd
imgproc: vectorize cv::createHanningWindow #27368

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2025-06-20 12:00:37 +03:00
Alexander Smorkalov 972e135479 Merge pull request #26703 from MaximSmolskiy:fix-matchTemplate-with-mask-crash
Fix matchTemplate with mask crash
2025-06-19 10:15:33 +03:00
Dmitry Kurtaev d750d43aa2 Merge pull request #27432 from dkurt:d.kurtaev/ipp_distTransform
Correct IPP distanceTransform results with single thread #27432

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resolves #24082

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2025-06-11 17:37:18 +03:00
Kavyansh Tyagi 452882c007 Add diamond structuring element 2025-06-11 15:54:29 +05:30
Dmitry Kurtaev d6864cdd22 Merge pull request #27418 from dkurt:fix_valgrind_warnings
Fix valgrind warnings in tests #27418

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2025-06-09 09:23:04 +03:00
Alexander Smorkalov a2c381a82b Merge pull request #27398 from asmorkalov:as/relax_remap_relative
Relax remap relative test to handle the case when HAL implements not all remap options
2025-06-04 16:29:21 +03:00
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)

---

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2025-06-03 17:12:16 +03:00
Alexander Smorkalov 0ccbd21c0a Relax remap relative test to handle the case when HAL implements not remap options. 2025-06-03 11:24:07 +03:00
Maxim Smolskiy e92cfb35f6 Merge pull request #27389 from MaximSmolskiy:add_HoughCirclesWithAccumulator_binding
Add HoughCirclesWithAccumulator binding #27389

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Fix #27377 

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2025-06-02 10:23:17 +03:00
Alexander Smorkalov a39f61b6e1 Merge pull request #27390 from MaximSmolskiy:update_HoughLinesWithAccumulator_binding
Update HoughLinesWithAccumulator binding
2025-06-02 09:41:33 +03:00
MaximSmolskiy e1f6e85c88 Update HoughLinesWithAccumulator binding 2025-06-01 19:19:21 +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.

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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

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2025-05-21 16:12:09 +03:00
omahs 0bc95d9256 Merge pull request #27338 from omahs:patch-1
Fix typos #27338

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2025-05-21 12:13:50 +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).

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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

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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.

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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
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

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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
adsha-quic 6ffc515b2a Merge pull request #27182 from CodeLinaro:boxFilter_hal_changes
Parallel_for in box Filter and support for 32f box filter in Fastcv hal #27182

Added parallel_for in box filter hal and support for 32f box filter

### 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
2025-04-16 18:33:38 +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
Gianluca Nordio 931af518d9 Merge pull request #27139 from GianlucaNordio:patch-4
Fix minAreaRect and boxPoints docs (#26799) #27139

As requested from issue #26799 the docs regarding minAreaRect and boxPoints are extended specifying the order of the corners for boxPoints and the way the angle is computed for the rotated rect returned by minAreaRect
2025-03-25 09:30:56 +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
JavaTypedScript 259ec3674d fixed typo 2025-03-19 21:38:08 +05:30
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 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
Pierre Chatelier e813326c17 Merge pull request #27039 from chacha21:threshold_otsu_doc_update
Threshold otsu doc update #27039 
 
PR for #27038

(I had already done that, but encounters git madness after branch renaming)

- [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
2025-03-10 19:40:45 +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
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

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
2025-03-04 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.
- [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
2025-03-02 12:44:39 +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
shyama7004 076bfa6431 Fix _DEBUG/NDEBUG handling across modules (#26151) 2025-02-11 22:00:44 +05:30
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