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940 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Suleyman TURKMEN
|
d9c0ee234f |
Merge pull request #27679 from sturkmen72:libtiff-4.7.0
libtiff upgrade to version 4.7.0 #27679 ### 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 |
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 Aakash Preetam
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8366a2e506 |
Merge pull request #27525 from CodeLinaro:apreetam_7thPost
Update FastCV lib hash for Linux and Android Updated libs PR [opencv/opencv_3rdparty#101](https://github.com/opencv/opencv_3rdparty/pull/101) ### 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 |
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 Alexander Alekhin
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83309580f4 | ffmpeg/4.x: update FFmpeg wrapper 2025.06 | ||
 eplankin
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287dad8102 |
Merge pull request #27354 from eplankin:ipp_update22.1
Update IPP integration #27354 Please merge together with https://github.com/opencv/opencv_3rdparty/pull/96 Supported IPP version was updated to IPP 2022.1.0 for Linux and Windows. Bugs in norm() function which caused failure of sanity check in performance tests were fixed, IPP calls were enabled. Previous update: https://github.com/opencv/opencv/pull/26463 |
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Aakash Preetam
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d97e926f70 |
Merge pull request #27403 from CodeLinaro:apreetam_6thPost
FastCV latest libs hash update #27403 Update hash for the fastcv libs for Linux Updated libs PR: https://github.com/opencv/opencv_3rdparty/pull/97 ### 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 |
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 Alexander Smorkalov
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987548d041 | Use older version of IPP for Android x86 32bit to resolve linkage issues. | ||
 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 |
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 Alexander Smorkalov
|
4530206445 |
Merge pull request #27340 from asmorkalov:apreetam_5thPost
Update hash for the fastcv libs for both Linux and Android #27340 Replaces https://github.com/opencv/opencv/pull/27290 Updated libs PR: https://github.com/opencv/opencv_3rdparty/pull/95 ### 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 |
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Alexander Smorkalov
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a39db41390 | Cherry-pick OpenJPEG deconding status fix. | ||
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Alexander Smorkalov
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19c4d97638 |
Merge pull request #27252 from asmorkalov:as/extract_hal
Extract all HALs from 3rdparty to dedicated folder. #27252 ### 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 |
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 adsha-quic
|
edccfa7961 |
Merge pull request #27184 from CodeLinaro:gemm_fastcv_hal
FastCV gemm hal #27184 FastCV hal for gemm 32f ### 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 |
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|
Yuantao Feng
|
325e59bd4c |
Merge pull request #27229 from fengyuentau:4x/hal_rvv/transpose
HAL: implemented cv_hal_transpose in hal_rvv #27229 Checklists: - [x] transpose2d_8u - [x] transpose2d_16u - [ ] ~transpose2d_8uC3~ - [x] transpose2d_32s - [ ] ~transpose2d_16uC3~ - [x] transpose2d_32sC2 - [ ] ~transpose_32sC3~ - [ ] ~transpose_32sC4~ - [ ] ~transpose_32sC6~ - [ ] ~transpose_32sC8~ - [ ] ~inplace transpose~ ### 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 |
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Alexander Smorkalov
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cd5a636459 |
Merge pull request #27249 from fengyuentau:4x/hal_rvv/bugfix-norm2-int
HAL: aligned behavior of normDiff 32s kernels in hal_rvv in 4.x |
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fengyuentau
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a7749c3813 | aligned behavior in normDiff in hal_rvv for 4.x | ||
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fengyuentau
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8eb9d27a31 | implemented cv_hal_cmp* in hal_rvv | ||
 YooLc
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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 |
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Yuantao Feng
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11e46cda86 |
Merge pull request #27201 from fengyuentau:4x/hal_rvv/dotprod
HAL: implemented cv_hal_dotProduct in hal_rvv #27201 ### 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 |
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 quic-xuezha
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b5d38ea4cb |
Merge pull request #27217 from CodeLinaro:gaussianBlur_hal_fix
Optimize gaussian blur performance in FastCV HAL #27217 ### 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 |
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adsha-quic
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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 |
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Alexander Smorkalov
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3962803e7a |
Merge pull request #27216 from CodeLinaro:xuezha_3rdPost
Add SVD into FastCV HAL |
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Alexander Smorkalov
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250ea3d7c6 | Fixed Android build with FastCV. | ||
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adsha-quic
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ba6eb8d952 |
Merge pull request #27214 from CodeLinaro:fastcv_lib_hash_update
Adding latest FastCV static libs updated libs PR: [opencv/opencv_3rdparty/pull/94](https://github.com/opencv/opencv_3rdparty/pull/94) ### 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 |
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Alexander Smorkalov
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050dfab749 |
Merge pull request #27218 from gfrankliu:tbb-lib-upgrade
upgrade tbb to version 2022.1.0 |
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 Frank Liu
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70ab545b90 |
upgrade tbb to version 2022.1.0
upgrade tbb from version 2021.11.0 to 2022.1.0 to fix https://github.com/opencv/opencv/issues/25187 |
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Alexander Smorkalov
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fa7a0c1e12 | Migrated IPP impl for flip and transpose to HAL. | ||
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Xue Zhang
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0d092c7b1e | Add SVD into HAL | ||
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Alexander Smorkalov
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78662ac085 | Transfer IPP polarToCart to HAL. | ||
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Yuantao Feng
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81859255ca |
Merge pull request #27175 from fengyuentau:4x/hal_rvv/div_recip
HAL: implemented cv_hal_div* and cv_hal_recip* in hal_rvv #27175 ### 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 |
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Yuantao Feng
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ec1cbe294a |
Merge pull request #27162 from fengyuentau:4x/hal_rvv/copyMask
HAL: added copyToMask and implemented in hal_rvv #27162 ### 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 |
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 天音あめ
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14e1f6ce96 |
Merge pull request #27160 from amane-ame:resize_hal_rvv
Add RISC-V HAL implementation for cv::resize #27160 This patch implements `cv_hal_resize` using native intrinsics, optimizing the performance of `cv::resize` for `CV_INTER_NEAREST/CV_INTER_NEAREST_EXACT/CV_INTER_LINEAR/CV_INTER_LINEAR_EXACT/CV_INTER_AREA` modes. Tested on MUSE-PI (Spacemit X60) for both gcc 14.2 and clang 20.1. ``` $ ./opencv_test_imgproc --gtest_filter="*Resize*:*resize*" $ ./opencv_perf_imgproc --gtest_filter="*Resize*:*resize*" --perf_min_samples=300 --perf_force_samples=300 ``` View the full perf table here: [hal_rvv_resize.pdf](https://github.com/user-attachments/files/19480756/hal_rvv_resize.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 |
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天音あめ
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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 |
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Yuantao Feng
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a2a2f37ebb |
Merge pull request #27115 from fengyuentau:4x/hal_rvv/normDiff
core: refactored normDiff in hal_rvv and extended with support of more data types #27115 Merge wtih https://github.com/opencv/opencv_extra/pull/1246. ### 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 |
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 Alexander Smorkalov
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a77623a32b | Move IPP minMaxIdx to HAL. | ||
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Alexander Smorkalov
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0944f7ad26 |
Merge pull request #27128 from asmorkalov:as/ipp_norm
Move IPP norm and normDiff to HAL #27128 Continues https://github.com/opencv/opencv/pull/26880 ### 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 |
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Alexander Smorkalov
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01ef38dcad |
Merge pull request #26880 from asmorkalov:as/ipp_hal
Initial version of IPP-based HAL for x86 and x86_64 platforms #26880 ### 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 |
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天音あめ
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46bd22abad |
Fix RISC-V HAL solve:SVD and BGRtoLab (#27046)
Fix RISC-V HAL solve/SVD and BGRtoLab #27046 Closes #27044. Also suppressed some warnings in other HAL. ### 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 |
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天音あめ
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ec5f7bb9f1 |
Merge pull request #27097 from amane-ame:blur_hal_rvv
Add RISC-V HAL implementation for cv::blur series #27097 This patch implements `cv_hal_gaussianBlurBinomial`, `cv_hal_medianBlur`, `cv_hal_boxFilter` and `cv_hal_bilateralFilter` using native intrinsics, optimizing the performance of `cv::GaussianBlur/cv::medianBlur/cv::boxFilter/cv::bilateralFilter` for `3x3/5x5` kernels. Tested on MUSE-PI (Spacemit X60) for both gcc 14.2 and clang 20.0. ``` $ ./opencv_test_imgproc --gtest_filter="*Filter*:*Blur*" $ ./opencv_perf_imgproc --gtest_filter="*gauss*:*box*:*Bilateral*:*median*" --perf_min_samples=2000 --perf_force_samples=2000 ``` View the full perf table here: [hal_rvv_blur.pdf](https://github.com/user-attachments/files/19335582/hal_rvv_blur.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 |
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Alexander Smorkalov
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50072f8d4f |
Merge pull request #27089 from amane-ame:hist_hal_rvv
Add RISC-V HAL implementation for cv::equalizeHist |
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天音あめ
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46fbe1895a |
Merge pull request #27096 from amane-ame:moments_hal_rvv
Add RISC-V HAL implementation for cv::moments #27096 This patch implements `cv_hal_imageMoments` using native intrinsics, optimizing the performance of `cv::moments` for data types `CV_16U/CV_16S/CV_32F/CV_64F`. Tested on MUSE-PI (Spacemit X60) for both gcc 14.2 and clang 20.0. ``` $ ./opencv_test_imgproc --gtest_filter="*Moments*" $ ./opencv_perf_imgproc --gtest_filter="*Moments*" --perf_min_samples=1000 --perf_force_samples=1000 ```  ### 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 |
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amane-ame
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b902a8e792 |
Add equalize_hist.
Co-authored-by: Liutong HAN <liutong2020@iscas.ac.cn> |
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Yuantao Feng
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8207549638 |
Merge pull request #26991 from fengyuentau:4x/core/norm2hal_rvv
core: improve norm of hal rvv #26991 Merge with https://github.com/opencv/opencv_extra/pull/1241 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [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 |
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天音あめ
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0142231e4d |
Merge pull request #27072 from amane-ame:thresh_hal_rvv
Add RISC-V HAL implementation for cv::threshold and cv::adaptiveThreshold #27072 This patch implements `cv_hal_threshold_otsu` and `cv_hal_adaptiveThreshold` using native intrinsics, optimizing the performance of `cv::threshold(THRESH_OTSU)` and `cv::adaptiveThreshold`. Since UI is as fast as HAL `cv_hal_rvv::threshold::threshold` so `cv_hal_threshold` is not redirected, but this part of HAL is keeped because `cv_hal_threshold_otsu` depends on it. Tested on MUSE-PI (Spacemit X60) for both gcc 14.2 and clang 20.0. ``` $ ./opencv_test_imgproc --gtest_filter="*thresh*:*Thresh*" $ ./opencv_perf_imgproc --gtest_filter="*otsu*:*adaptiveThreshold*" --perf_min_samples=1000 --perf_force_samples=1000 ```  ### 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 |
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 GenshinImpactStarts
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2090407002 |
Merge pull request #26999 from GenshinImpactStarts:polar_to_cart
[HAL RVV] unify and impl polar_to_cart | add perf test #26999 ### Summary 1. Implement through the existing `cv_hal_polarToCart32f` and `cv_hal_polarToCart64f` interfaces. 2. Add `polarToCart` performance tests 3. Make `cv::polarToCart` use CALL_HAL in the same way as `cv::cartToPolar` 4. To achieve the 3rd point, the original implementation was moved, and some modifications were made. Tested through: ```sh opencv_test_core --gtest_filter="*PolarToCart*:*Core_CartPolar_reverse*" opencv_perf_core --gtest_filter="*PolarToCart*" --perf_min_samples=300 --perf_force_samples=300 ``` ### HAL performance test ***UPDATE***: Current implementation is no more depending on vlen. **NOTE**: Due to the 4th point in the summary above, the `scalar` and `ui` test is based on the modified code of this PR. The impact of this patch on `scalar` and `ui` is evaluated in the next section, `Effect of Point 4`. Vlen 256 (Muse Pi): ``` Name of Test scalar ui rvv ui rvv vs vs scalar scalar (x-factor) (x-factor) PolarToCart::PolarToCartFixture::(127x61, 32FC1) 0.315 0.110 0.034 2.85 9.34 PolarToCart::PolarToCartFixture::(127x61, 64FC1) 0.423 0.163 0.045 2.59 9.34 PolarToCart::PolarToCartFixture::(640x480, 32FC1) 13.695 4.325 1.278 3.17 10.71 PolarToCart::PolarToCartFixture::(640x480, 64FC1) 17.719 7.118 2.105 2.49 8.42 PolarToCart::PolarToCartFixture::(1280x720, 32FC1) 40.678 13.114 3.977 3.10 10.23 PolarToCart::PolarToCartFixture::(1280x720, 64FC1) 53.124 21.298 6.519 2.49 8.15 PolarToCart::PolarToCartFixture::(1920x1080, 32FC1) 95.158 29.465 8.894 3.23 10.70 PolarToCart::PolarToCartFixture::(1920x1080, 64FC1) 119.262 47.743 14.129 2.50 8.44 ``` ### Effect of Point 4 To make `cv::polarToCart` behave the same as `cv::cartToPolar`, the implementation detail of the former has been moved to the latter's location (from `mathfuncs.cpp` to `mathfuncs_core.simd.hpp`). #### Reason for Changes: This function works as follows: $y = \text{mag} \times \sin(\text{angle})$ and $x = \text{mag} \times \cos(\text{angle})$. The original implementation first calculates the values of $\sin$ and $\cos$, storing the results in the output buffers $x$ and $y$, and then multiplies the result by $\text{mag}$. However, when the function is used as an in-place operation (one of the output buffers is also an input buffer), the original implementation allocates an extra buffer to store the $\sin$ and $\cos$ values in case the $\text{mag}$ value gets overwritten. This extra buffer allocation prevents `cv::polarToCart` from functioning in the same way as `cv::cartToPolar`. Therefore, the multiplication is now performed immediately without storing intermediate values. Since the original implementation also had AVX2 optimizations, I have applied the same optimizations to the AVX2 version of this implementation. ***UPDATE***: UI use v_sincos from #25892 now. The original implementation has AVX2 optimizations but is slower much than current UI so it's removed, and AVX2 perf test is below. Scalar implementation isn't changed because it's faster than using UI's method. #### Test Result `scalar` and `ui` test is done on Muse PI, and AVX2 test is done on Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz. `scalar` test: ``` Name of Test orig pr pr vs orig (x-factor) PolarToCart::PolarToCartFixture::(127x61, 32FC1) 0.333 0.294 1.13 PolarToCart::PolarToCartFixture::(127x61, 64FC1) 0.385 0.403 0.96 PolarToCart::PolarToCartFixture::(640x480, 32FC1) 14.749 12.343 1.19 PolarToCart::PolarToCartFixture::(640x480, 64FC1) 19.419 16.743 1.16 PolarToCart::PolarToCartFixture::(1280x720, 32FC1) 44.155 37.822 1.17 PolarToCart::PolarToCartFixture::(1280x720, 64FC1) 62.108 50.358 1.23 PolarToCart::PolarToCartFixture::(1920x1080, 32FC1) 99.011 85.769 1.15 PolarToCart::PolarToCartFixture::(1920x1080, 64FC1) 127.740 112.874 1.13 ``` `ui` test: ``` Name of Test orig pr pr vs orig (x-factor) PolarToCart::PolarToCartFixture::(127x61, 32FC1) 0.306 0.110 2.77 PolarToCart::PolarToCartFixture::(127x61, 64FC1) 0.455 0.163 2.79 PolarToCart::PolarToCartFixture::(640x480, 32FC1) 13.381 4.325 3.09 PolarToCart::PolarToCartFixture::(640x480, 64FC1) 21.851 7.118 3.07 PolarToCart::PolarToCartFixture::(1280x720, 32FC1) 39.975 13.114 3.05 PolarToCart::PolarToCartFixture::(1280x720, 64FC1) 67.006 21.298 3.15 PolarToCart::PolarToCartFixture::(1920x1080, 32FC1) 90.362 29.465 3.07 PolarToCart::PolarToCartFixture::(1920x1080, 64FC1) 129.637 47.743 2.72 ``` AVX2 test: ``` Name of Test orig pr pr vs orig (x-factor) PolarToCart::PolarToCartFixture::(127x61, 32FC1) 0.019 0.009 2.11 PolarToCart::PolarToCartFixture::(127x61, 64FC1) 0.022 0.013 1.74 PolarToCart::PolarToCartFixture::(640x480, 32FC1) 0.788 0.355 2.22 PolarToCart::PolarToCartFixture::(640x480, 64FC1) 1.102 0.618 1.78 PolarToCart::PolarToCartFixture::(1280x720, 32FC1) 2.383 1.042 2.29 PolarToCart::PolarToCartFixture::(1280x720, 64FC1) 3.758 2.316 1.62 PolarToCart::PolarToCartFixture::(1920x1080, 32FC1) 5.577 2.559 2.18 PolarToCart::PolarToCartFixture::(1920x1080, 64FC1) 9.710 6.424 1.51 ``` A slight performance loss occurs because the check for whether $mag$ is nullptr is performed with every calculation, instead of being done once per batch. This is to reuse current `SinCos_32f` function. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [ ] 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 |
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Alexander Smorkalov
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0a39f98bee |
Merge pull request #27067 from amane-ame:sepfilter_optimize
Optimize RISC-V HAL cv::sepFilter |
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 Liutong HAN
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6eaaaa410e |
Merge pull request #27056 from hanliutong:rvv-hal-copyright
[RVV HAL] Add copyright and replace '#pragma once'. #27056 Add copyright and in RVV HAL, since other companies or teams may join the development and add their copyright. And the '#pragma once' are replaced. ### 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 |
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amane-ame
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2c16f3b7d2 |
Optimize cv::sepFilter.
Co-authored-by: Liutong HAN <liutong2020@iscas.ac.cn> |
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GenshinImpactStarts
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2a8d4b8e43 |
Merge pull request #27000 from GenshinImpactStarts:cart_to_polar
[HAL RVV] reuse atan | impl cart_to_polar | add perf test #27000 Implement through the existing `cv_hal_cartToPolar32f` and `cv_hal_cartToPolar64f` interfaces. Add `cartToPolar` performance tests. cv_hal_rvv::fast_atan is modified to make it more reusable because it's needed in cartToPolar. **UPDATE**: UI enabled. Since the vec type of RVV can't be stored in struct. UI implementation of `v_atan_f32` is modified. Both `fastAtan` and `cartToPolar` are affected so the test result for `atan` is also appended. I have tested the modified UI on RVV and AVX2 and no regressions appears. Perf test done on MUSE-PI. AVX2 test done on Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz. ```sh $ opencv_test_core --gtest_filter="*CartToPolar*:*Core_CartPolar_reverse*:*Phase*" $ opencv_perf_core --gtest_filter="*CartToPolar*:*phase*" --perf_min_samples=300 --perf_force_samples=300 ``` Test result between enabled UI and HAL: ``` Name of Test ui rvv rvv vs ui (x-factor) CartToPolar::CartToPolarFixture::(127x61, 32FC1) 0.106 0.059 1.80 CartToPolar::CartToPolarFixture::(127x61, 64FC1) 0.155 0.070 2.20 CartToPolar::CartToPolarFixture::(640x480, 32FC1) 4.188 2.317 1.81 CartToPolar::CartToPolarFixture::(640x480, 64FC1) 6.593 2.889 2.28 CartToPolar::CartToPolarFixture::(1280x720, 32FC1) 12.600 7.057 1.79 CartToPolar::CartToPolarFixture::(1280x720, 64FC1) 19.860 8.797 2.26 CartToPolar::CartToPolarFixture::(1920x1080, 32FC1) 28.295 15.809 1.79 CartToPolar::CartToPolarFixture::(1920x1080, 64FC1) 44.573 19.398 2.30 phase32f::VectorLength::128 0.002 0.002 1.20 phase32f::VectorLength::1000 0.008 0.006 1.32 phase32f::VectorLength::131072 1.061 0.731 1.45 phase32f::VectorLength::524288 3.997 2.976 1.34 phase32f::VectorLength::1048576 8.001 5.959 1.34 phase64f::VectorLength::128 0.002 0.002 1.33 phase64f::VectorLength::1000 0.012 0.008 1.58 phase64f::VectorLength::131072 1.648 0.931 1.77 phase64f::VectorLength::524288 6.836 3.837 1.78 phase64f::VectorLength::1048576 14.060 7.540 1.86 ``` Test result before and after enabling UI on RVV: ``` Name of Test perf perf perf ui ui ui orig pr pr vs perf ui orig (x-factor) CartToPolar::CartToPolarFixture::(127x61, 32FC1) 0.141 0.106 1.33 CartToPolar::CartToPolarFixture::(127x61, 64FC1) 0.187 0.155 1.20 CartToPolar::CartToPolarFixture::(640x480, 32FC1) 5.990 4.188 1.43 CartToPolar::CartToPolarFixture::(640x480, 64FC1) 8.370 6.593 1.27 CartToPolar::CartToPolarFixture::(1280x720, 32FC1) 18.214 12.600 1.45 CartToPolar::CartToPolarFixture::(1280x720, 64FC1) 25.365 19.860 1.28 CartToPolar::CartToPolarFixture::(1920x1080, 32FC1) 40.437 28.295 1.43 CartToPolar::CartToPolarFixture::(1920x1080, 64FC1) 56.699 44.573 1.27 phase32f::VectorLength::128 0.003 0.002 1.54 phase32f::VectorLength::1000 0.016 0.008 1.90 phase32f::VectorLength::131072 2.048 1.061 1.93 phase32f::VectorLength::524288 8.219 3.997 2.06 phase32f::VectorLength::1048576 16.426 8.001 2.05 phase64f::VectorLength::128 0.003 0.002 1.44 phase64f::VectorLength::1000 0.020 0.012 1.60 phase64f::VectorLength::131072 2.621 1.648 1.59 phase64f::VectorLength::524288 10.780 6.836 1.58 phase64f::VectorLength::1048576 22.723 14.060 1.62 ``` Test result before and after modifying UI on AVX2: ``` Name of Test perf perf perf avx2 avx2 avx2 orig pr pr vs perf avx2 orig (x-factor) CartToPolar::CartToPolarFixture::(127x61, 32FC1) 0.006 0.005 1.14 CartToPolar::CartToPolarFixture::(127x61, 64FC1) 0.010 0.009 1.08 CartToPolar::CartToPolarFixture::(640x480, 32FC1) 0.273 0.264 1.03 CartToPolar::CartToPolarFixture::(640x480, 64FC1) 0.511 0.487 1.05 CartToPolar::CartToPolarFixture::(1280x720, 32FC1) 0.760 0.723 1.05 CartToPolar::CartToPolarFixture::(1280x720, 64FC1) 2.009 1.937 1.04 CartToPolar::CartToPolarFixture::(1920x1080, 32FC1) 1.996 1.923 1.04 CartToPolar::CartToPolarFixture::(1920x1080, 64FC1) 5.721 5.509 1.04 phase32f::VectorLength::128 0.000 0.000 0.98 phase32f::VectorLength::1000 0.001 0.001 0.97 phase32f::VectorLength::131072 0.105 0.111 0.95 phase32f::VectorLength::524288 0.402 0.402 1.00 phase32f::VectorLength::1048576 0.775 0.767 1.01 phase64f::VectorLength::128 0.000 0.000 1.00 phase64f::VectorLength::1000 0.001 0.001 1.01 phase64f::VectorLength::131072 0.163 0.162 1.01 phase64f::VectorLength::524288 0.669 0.653 1.02 phase64f::VectorLength::1048576 1.660 1.634 1.02 ``` ### 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 |
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GenshinImpactStarts
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e30697fd42 |
Merge pull request #27002 from GenshinImpactStarts:magnitude
[HAL RVV] impl magnitude | add perf test #27002 Implement through the existing `cv_hal_magnitude32f` and `cv_hal_magnitude64f` interfaces. **UPDATE**: UI is enabled. The only difference between UI and HAL now is HAL use a approximate `sqrt`. Perf test done on MUSE-PI. ```sh $ opencv_test_core --gtest_filter="*Magnitude*" $ opencv_perf_core --gtest_filter="*Magnitude*" --perf_min_samples=300 --perf_force_samples=300 ``` Test result between enabled UI and HAL: ``` Name of Test ui rvv rvv vs ui (x-factor) Magnitude::MagnitudeFixture::(127x61, 32FC1) 0.029 0.016 1.75 Magnitude::MagnitudeFixture::(127x61, 64FC1) 0.057 0.036 1.57 Magnitude::MagnitudeFixture::(640x480, 32FC1) 1.063 0.648 1.64 Magnitude::MagnitudeFixture::(640x480, 64FC1) 2.261 1.530 1.48 Magnitude::MagnitudeFixture::(1280x720, 32FC1) 3.261 2.118 1.54 Magnitude::MagnitudeFixture::(1280x720, 64FC1) 6.802 4.682 1.45 Magnitude::MagnitudeFixture::(1920x1080, 32FC1) 7.287 4.738 1.54 Magnitude::MagnitudeFixture::(1920x1080, 64FC1) 15.226 10.334 1.47 ``` Test result before and after enabling UI: ``` Name of Test orig pr pr vs orig (x-factor) Magnitude::MagnitudeFixture::(127x61, 32FC1) 0.032 0.029 1.11 Magnitude::MagnitudeFixture::(127x61, 64FC1) 0.067 0.057 1.17 Magnitude::MagnitudeFixture::(640x480, 32FC1) 1.228 1.063 1.16 Magnitude::MagnitudeFixture::(640x480, 64FC1) 2.786 2.261 1.23 Magnitude::MagnitudeFixture::(1280x720, 32FC1) 3.762 3.261 1.15 Magnitude::MagnitudeFixture::(1280x720, 64FC1) 8.549 6.802 1.26 Magnitude::MagnitudeFixture::(1920x1080, 32FC1) 8.408 7.287 1.15 Magnitude::MagnitudeFixture::(1920x1080, 64FC1) 18.884 15.226 1.24 ``` ### 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 |
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GenshinImpactStarts
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60de3ff24f |
Merge pull request #27015 from GenshinImpactStarts:sqrt
[HAL RVV] impl sqrt and invSqrt #27015 Implement through the existing interfaces `cv_hal_sqrt32f`, `cv_hal_sqrt64f`, `cv_hal_invSqrt32f`, `cv_hal_invSqrt64f`. Perf test done on MUSE-PI and CanMV K230. Because the performance of scalar is much worse than universal intrinsic, only ui and hal rvv is compared. In RVV's UI, `invSqrt` is computed using `1 / sqrt()`. This patch first uses `frsqrt` and then applies the Newton-Raphson method to achieve higher precision. For the initial value, I tried using the famous [fast inverse square root algorithm](https://en.wikipedia.org/wiki/Fast_inverse_square_root), which involves one bit shift and one subtraction. However, on both MUSE-PI and CanMV K230, the performance was slightly lower (about 3%), so I chose to use `frsqrt` for the initial value instead. BTW, I think this patch can directly replace RVV's UI. **UPDATE**: Due to strange vector registers allocation strategy in clang, for `invSqrt`, clang use LMUL m4 while gcc use LMUL m8, which leads to some performance loss in clang. So the test for clang is appended. ```sh $ opencv_test_core --gtest_filter="Core_HAL/mathfuncs.*" $ opencv_perf_core --gtest_filter="SqrtFixture.*" --perf_min_samples=300 --perf_force_samples=300 ``` CanMV K230: ``` Name of Test ui rvv rvv vs ui (x-factor) Sqrt::SqrtFixture::(127x61, 5, false) 0.052 0.027 1.96 Sqrt::SqrtFixture::(127x61, 5, true) 0.101 0.026 3.80 Sqrt::SqrtFixture::(127x61, 6, false) 0.106 0.059 1.79 Sqrt::SqrtFixture::(127x61, 6, true) 0.207 0.058 3.55 Sqrt::SqrtFixture::(640x480, 5, false) 1.988 0.956 2.08 Sqrt::SqrtFixture::(640x480, 5, true) 3.920 0.948 4.13 Sqrt::SqrtFixture::(640x480, 6, false) 4.179 2.342 1.78 Sqrt::SqrtFixture::(640x480, 6, true) 8.220 2.290 3.59 Sqrt::SqrtFixture::(1280x720, 5, false) 5.969 2.881 2.07 Sqrt::SqrtFixture::(1280x720, 5, true) 11.731 2.857 4.11 Sqrt::SqrtFixture::(1280x720, 6, false) 12.533 7.031 1.78 Sqrt::SqrtFixture::(1280x720, 6, true) 24.643 6.917 3.56 Sqrt::SqrtFixture::(1920x1080, 5, false) 13.423 6.483 2.07 Sqrt::SqrtFixture::(1920x1080, 5, true) 26.379 6.436 4.10 Sqrt::SqrtFixture::(1920x1080, 6, false) 28.200 15.833 1.78 Sqrt::SqrtFixture::(1920x1080, 6, true) 55.434 15.565 3.56 ``` MUSE-PI: ``` GCC | clang Name of Test ui rvv rvv | ui rvv rvv vs | vs ui | ui (x-factor) | (x-factor) Sqrt::SqrtFixture::(127x61, 5, false) 0.027 0.018 1.46 | 0.027 0.016 1.65 Sqrt::SqrtFixture::(127x61, 5, true) 0.050 0.017 2.98 | 0.050 0.017 2.99 Sqrt::SqrtFixture::(127x61, 6, false) 0.053 0.031 1.72 | 0.052 0.032 1.64 Sqrt::SqrtFixture::(127x61, 6, true) 0.100 0.030 3.31 | 0.101 0.035 2.86 Sqrt::SqrtFixture::(640x480, 5, false) 0.955 0.483 1.98 | 0.959 0.499 1.92 Sqrt::SqrtFixture::(640x480, 5, true) 1.873 0.489 3.83 | 1.873 0.520 3.60 Sqrt::SqrtFixture::(640x480, 6, false) 2.027 1.163 1.74 | 2.037 1.218 1.67 Sqrt::SqrtFixture::(640x480, 6, true) 3.961 1.153 3.44 | 3.961 1.341 2.95 Sqrt::SqrtFixture::(1280x720, 5, false) 2.916 1.538 1.90 | 2.912 1.598 1.82 Sqrt::SqrtFixture::(1280x720, 5, true) 5.735 1.534 3.74 | 5.726 1.661 3.45 Sqrt::SqrtFixture::(1280x720, 6, false) 6.121 3.585 1.71 | 6.109 3.725 1.64 Sqrt::SqrtFixture::(1280x720, 6, true) 12.059 3.501 3.44 | 12.053 4.080 2.95 Sqrt::SqrtFixture::(1920x1080, 5, false) 6.540 3.535 1.85 | 6.540 3.643 1.80 Sqrt::SqrtFixture::(1920x1080, 5, true) 12.943 3.445 3.76 | 12.908 3.706 3.48 Sqrt::SqrtFixture::(1920x1080, 6, false) 13.714 8.062 1.70 | 13.711 8.376 1.64 Sqrt::SqrtFixture::(1920x1080, 6, true) 27.011 7.989 3.38 | 27.115 9.245 2.93 ``` ### 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 |
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Alexander Smorkalov
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a48e78cdfc |
Merge pull request #27026 from amane-ame/filter_hal_rvv
Add RISC-V HAL implementation for cv::filter series |