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Merge pull request #26163 from asmorkalov:as/HAL_schaar_deriv
HAL interface for Sharr derivatives needed for Lukas-Kanade algorithm #26163 ### 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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3rdparty/carotene/hal/tegra_hal.hpp
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16
3rdparty/carotene/hal/tegra_hal.hpp
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@ -1962,4 +1962,20 @@ inline int TEGRA_LKOpticalFlowLevel(const uchar *prev_data, size_t prev_data_ste
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#define cv_hal_LKOpticalFlowLevel TEGRA_LKOpticalFlowLevel
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#define cv_hal_LKOpticalFlowLevel TEGRA_LKOpticalFlowLevel
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#endif // __ARM_ARCH=7
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#endif // __ARM_ARCH=7
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#if 0 // OpenCV provides fater parallel implementation
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inline int TEGRA_ScharrDeriv(const uchar* src_data, size_t src_step,
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short* dst_data, size_t dst_step,
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int width, int height, int cn)
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{
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if (!CAROTENE_NS::isSupportedConfiguration())
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return CV_HAL_ERROR_NOT_IMPLEMENTED;
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CAROTENE_NS::ScharrDeriv(CAROTENE_NS::Size2D(width, height), cn, src_data, src_step, dst_data, dst_step);
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return CV_HAL_ERROR_OK;
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}
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#undef cv_hal_ScharrDeriv
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#define cv_hal_ScharrDeriv TEGRA_ScharrDeriv
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#endif
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#endif
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#endif
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@ -67,6 +67,27 @@ inline int hal_ni_LKOpticalFlowLevel(const uchar *prev_data, size_t prev_data_st
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#define cv_hal_LKOpticalFlowLevel hal_ni_LKOpticalFlowLevel
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#define cv_hal_LKOpticalFlowLevel hal_ni_LKOpticalFlowLevel
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//! @endcond
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//! @endcond
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/**
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@brief Computes Schaar derivatives with inteleaved layout xyxy...
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@param src_data source image data
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@param src_step source image step
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@param dst_data destination buffer data
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@param dst_step destination buffer step
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@param width image width
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@param height image height
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@param cn source image channels
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**/
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inline int hal_ni_ScharrDeriv(const uchar* src_data, size_t src_step,
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short* dst_data, size_t dst_step,
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int width, int height, int cn)
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{
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return CV_HAL_ERROR_NOT_IMPLEMENTED;
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}
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//! @cond IGNORED
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#define cv_hal_ScharrDeriv hal_ni_ScharrDeriv
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//! @endcond
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//! @}
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//! @}
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#if defined(__clang__)
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#if defined(__clang__)
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@ -63,6 +63,9 @@ static void calcScharrDeriv(const cv::Mat& src, cv::Mat& dst)
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int rows = src.rows, cols = src.cols, cn = src.channels(), depth = src.depth();
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int rows = src.rows, cols = src.cols, cn = src.channels(), depth = src.depth();
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CV_Assert(depth == CV_8U);
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CV_Assert(depth == CV_8U);
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dst.create(rows, cols, CV_MAKETYPE(DataType<deriv_type>::depth, cn*2));
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dst.create(rows, cols, CV_MAKETYPE(DataType<deriv_type>::depth, cn*2));
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CALL_HAL(ScharrDeriv, cv_hal_ScharrDeriv, src.data, src.step, (short*)dst.data, dst.step, cols, rows, cn);
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parallel_for_(Range(0, rows), cv::detail::ScharrDerivInvoker(src, dst), cv::getNumThreads());
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parallel_for_(Range(0, rows), cv::detail::ScharrDerivInvoker(src, dst), cv::getNumThreads());
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}
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}
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