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439 lines
20 KiB
439 lines
20 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "precomp.hpp" |
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using namespace cv; |
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using namespace cv::gpu; |
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using namespace std; |
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#if !defined (HAVE_CUDA) |
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void cv::gpu::matchTemplate(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); } |
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#else |
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namespace cv { namespace gpu { namespace device |
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{ |
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namespace match_template |
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{ |
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void matchTemplateNaive_CCORR_8U(const DevMem2Db image, const DevMem2Db templ, DevMem2Df result, int cn, cudaStream_t stream); |
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void matchTemplateNaive_CCORR_32F(const DevMem2Db image, const DevMem2Db templ, DevMem2Df result, int cn, cudaStream_t stream); |
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void matchTemplateNaive_SQDIFF_8U(const DevMem2Db image, const DevMem2Db templ, DevMem2Df result, int cn, cudaStream_t stream); |
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void matchTemplateNaive_SQDIFF_32F(const DevMem2Db image, const DevMem2Db templ, DevMem2Df result, int cn, cudaStream_t stream); |
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void matchTemplatePrepared_SQDIFF_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum, unsigned long long templ_sqsum, DevMem2Df result, |
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int cn, cudaStream_t stream); |
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void matchTemplatePrepared_SQDIFF_NORMED_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum, unsigned long long templ_sqsum, DevMem2Df result, |
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int cn, cudaStream_t stream); |
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void matchTemplatePrepared_CCOFF_8U(int w, int h, const DevMem2D_<unsigned int> image_sum, unsigned int templ_sum, DevMem2Df result, cudaStream_t stream); |
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void matchTemplatePrepared_CCOFF_8UC2( |
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int w, int h, |
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const DevMem2D_<unsigned int> image_sum_r, |
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const DevMem2D_<unsigned int> image_sum_g, |
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unsigned int templ_sum_r, |
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unsigned int templ_sum_g, |
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DevMem2Df result, cudaStream_t stream); |
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void matchTemplatePrepared_CCOFF_8UC3( |
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int w, int h, |
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const DevMem2D_<unsigned int> image_sum_r, |
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const DevMem2D_<unsigned int> image_sum_g, |
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const DevMem2D_<unsigned int> image_sum_b, |
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unsigned int templ_sum_r, |
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unsigned int templ_sum_g, |
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unsigned int templ_sum_b, |
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DevMem2Df result, cudaStream_t stream); |
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void matchTemplatePrepared_CCOFF_8UC4( |
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int w, int h, |
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const DevMem2D_<unsigned int> image_sum_r, |
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const DevMem2D_<unsigned int> image_sum_g, |
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const DevMem2D_<unsigned int> image_sum_b, |
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const DevMem2D_<unsigned int> image_sum_a, |
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unsigned int templ_sum_r, |
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unsigned int templ_sum_g, |
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unsigned int templ_sum_b, |
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unsigned int templ_sum_a, |
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DevMem2Df result, cudaStream_t stream); |
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void matchTemplatePrepared_CCOFF_NORMED_8U( |
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int w, int h, const DevMem2D_<unsigned int> image_sum, |
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const DevMem2D_<unsigned long long> image_sqsum, |
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unsigned int templ_sum, unsigned long long templ_sqsum, |
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DevMem2Df result, cudaStream_t stream); |
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void matchTemplatePrepared_CCOFF_NORMED_8UC2( |
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int w, int h, |
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const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r, |
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const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g, |
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unsigned int templ_sum_r, unsigned long long templ_sqsum_r, |
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unsigned int templ_sum_g, unsigned long long templ_sqsum_g, |
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DevMem2Df result, cudaStream_t stream); |
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void matchTemplatePrepared_CCOFF_NORMED_8UC3( |
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int w, int h, |
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const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r, |
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const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g, |
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const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b, |
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unsigned int templ_sum_r, unsigned long long templ_sqsum_r, |
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unsigned int templ_sum_g, unsigned long long templ_sqsum_g, |
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unsigned int templ_sum_b, unsigned long long templ_sqsum_b, |
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DevMem2Df result, cudaStream_t stream); |
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void matchTemplatePrepared_CCOFF_NORMED_8UC4( |
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int w, int h, |
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const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r, |
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const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g, |
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const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b, |
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const DevMem2D_<unsigned int> image_sum_a, const DevMem2D_<unsigned long long> image_sqsum_a, |
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unsigned int templ_sum_r, unsigned long long templ_sqsum_r, |
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unsigned int templ_sum_g, unsigned long long templ_sqsum_g, |
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unsigned int templ_sum_b, unsigned long long templ_sqsum_b, |
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unsigned int templ_sum_a, unsigned long long templ_sqsum_a, |
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DevMem2Df result, cudaStream_t stream); |
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void normalize_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum, |
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unsigned long long templ_sqsum, DevMem2Df result, int cn, cudaStream_t stream); |
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void extractFirstChannel_32F(const DevMem2Db image, DevMem2Df result, int cn, cudaStream_t stream); |
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} |
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}}} |
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using namespace ::cv::gpu::device::match_template; |
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namespace |
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{ |
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// Evaluates optimal template's area threshold. If |
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// template's area is less than the threshold, we use naive match |
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// template version, otherwise FFT-based (if available) |
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int getTemplateThreshold(int method, int depth) |
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{ |
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switch (method) |
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{ |
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case CV_TM_CCORR: |
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if (depth == CV_32F) return 250; |
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if (depth == CV_8U) return 300; |
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break; |
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case CV_TM_SQDIFF: |
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if (depth == CV_8U) return 300; |
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break; |
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} |
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CV_Error(CV_StsBadArg, "getTemplateThreshold: unsupported match template mode"); |
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return 0; |
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} |
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void matchTemplate_CCORR_32F( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream) |
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{ |
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F); |
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if (templ.size().area() < getTemplateThreshold(CV_TM_CCORR, CV_32F)) |
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{ |
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matchTemplateNaive_CCORR_32F(image, templ, result, image.channels(), StreamAccessor::getStream(stream)); |
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return; |
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} |
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ConvolveBuf convolve_buf; |
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convolve_buf.user_block_size = buf.user_block_size; |
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if (image.channels() == 1) |
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convolve(image.reshape(1), templ.reshape(1), result, true, convolve_buf, stream); |
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else |
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{ |
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GpuMat result_; |
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convolve(image.reshape(1), templ.reshape(1), result_, true, convolve_buf, stream); |
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extractFirstChannel_32F(result_, result, image.channels(), StreamAccessor::getStream(stream)); |
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} |
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} |
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void matchTemplate_CCORR_8U( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream) |
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{ |
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if (templ.size().area() < getTemplateThreshold(CV_TM_CCORR, CV_8U)) |
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{ |
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F); |
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matchTemplateNaive_CCORR_8U(image, templ, result, image.channels(), StreamAccessor::getStream(stream)); |
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return; |
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} |
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if (stream) |
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{ |
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stream.enqueueConvert(image, buf.imagef, CV_32F); |
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stream.enqueueConvert(templ, buf.templf, CV_32F); |
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} |
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else |
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{ |
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image.convertTo(buf.imagef, CV_32F); |
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templ.convertTo(buf.templf, CV_32F); |
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} |
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matchTemplate_CCORR_32F(buf.imagef, buf.templf, result, buf, stream); |
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} |
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void matchTemplate_CCORR_NORMED_8U( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream) |
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{ |
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matchTemplate_CCORR_8U(image, templ, result, buf, stream); |
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buf.image_sqsums.resize(1); |
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sqrIntegral(image.reshape(1), buf.image_sqsums[0], stream); |
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unsigned long long templ_sqsum = (unsigned long long)sqrSum(templ.reshape(1))[0]; |
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normalize_8U(templ.cols, templ.rows, buf.image_sqsums[0], templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream)); |
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} |
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void matchTemplate_SQDIFF_32F( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream) |
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{ |
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F); |
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matchTemplateNaive_SQDIFF_32F(image, templ, result, image.channels(), StreamAccessor::getStream(stream)); |
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} |
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void matchTemplate_SQDIFF_8U( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream) |
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{ |
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if (templ.size().area() < getTemplateThreshold(CV_TM_SQDIFF, CV_8U)) |
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{ |
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F); |
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matchTemplateNaive_SQDIFF_8U(image, templ, result, image.channels(), StreamAccessor::getStream(stream)); |
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return; |
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} |
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buf.image_sqsums.resize(1); |
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sqrIntegral(image.reshape(1), buf.image_sqsums[0], stream); |
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unsigned long long templ_sqsum = (unsigned long long)sqrSum(templ.reshape(1))[0]; |
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matchTemplate_CCORR_8U(image, templ, result, buf, stream); |
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matchTemplatePrepared_SQDIFF_8U(templ.cols, templ.rows, buf.image_sqsums[0], templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream)); |
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} |
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void matchTemplate_SQDIFF_NORMED_8U( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream) |
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{ |
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buf.image_sqsums.resize(1); |
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sqrIntegral(image.reshape(1), buf.image_sqsums[0], stream); |
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unsigned long long templ_sqsum = (unsigned long long)sqrSum(templ.reshape(1))[0]; |
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matchTemplate_CCORR_8U(image, templ, result, buf, stream); |
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matchTemplatePrepared_SQDIFF_NORMED_8U(templ.cols, templ.rows, buf.image_sqsums[0], templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream)); |
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} |
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void matchTemplate_CCOFF_8U( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream) |
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{ |
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matchTemplate_CCORR_8U(image, templ, result, buf, stream); |
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if (image.channels() == 1) |
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{ |
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buf.image_sums.resize(1); |
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integral(image, buf.image_sums[0], stream); |
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unsigned int templ_sum = (unsigned int)sum(templ)[0]; |
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matchTemplatePrepared_CCOFF_8U(templ.cols, templ.rows, buf.image_sums[0], templ_sum, result, StreamAccessor::getStream(stream)); |
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} |
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else |
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{ |
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split(image, buf.images); |
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buf.image_sums.resize(buf.images.size()); |
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for (int i = 0; i < image.channels(); ++i) |
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integral(buf.images[i], buf.image_sums[i], stream); |
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Scalar templ_sum = sum(templ); |
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switch (image.channels()) |
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{ |
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case 2: |
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matchTemplatePrepared_CCOFF_8UC2( |
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templ.cols, templ.rows, buf.image_sums[0], buf.image_sums[1], |
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(unsigned int)templ_sum[0], (unsigned int)templ_sum[1], |
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result, StreamAccessor::getStream(stream)); |
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break; |
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case 3: |
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matchTemplatePrepared_CCOFF_8UC3( |
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templ.cols, templ.rows, buf.image_sums[0], buf.image_sums[1], buf.image_sums[2], |
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(unsigned int)templ_sum[0], (unsigned int)templ_sum[1], (unsigned int)templ_sum[2], |
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result, StreamAccessor::getStream(stream)); |
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break; |
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case 4: |
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matchTemplatePrepared_CCOFF_8UC4( |
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templ.cols, templ.rows, buf.image_sums[0], buf.image_sums[1], buf.image_sums[2], buf.image_sums[3], |
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(unsigned int)templ_sum[0], (unsigned int)templ_sum[1], (unsigned int)templ_sum[2], |
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(unsigned int)templ_sum[3], result, StreamAccessor::getStream(stream)); |
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break; |
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default: |
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CV_Error(CV_StsBadArg, "matchTemplate: unsupported number of channels"); |
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} |
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} |
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} |
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void matchTemplate_CCOFF_NORMED_8U( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream) |
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{ |
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if (stream) |
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{ |
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stream.enqueueConvert(image, buf.imagef, CV_32F); |
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stream.enqueueConvert(templ, buf.templf, CV_32F); |
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} |
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else |
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{ |
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image.convertTo(buf.imagef, CV_32F); |
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templ.convertTo(buf.templf, CV_32F); |
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} |
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matchTemplate_CCORR_32F(buf.imagef, buf.templf, result, buf, stream); |
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if (image.channels() == 1) |
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{ |
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buf.image_sums.resize(1); |
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integral(image, buf.image_sums[0], stream); |
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buf.image_sqsums.resize(1); |
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sqrIntegral(image, buf.image_sqsums[0], stream); |
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unsigned int templ_sum = (unsigned int)sum(templ)[0]; |
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unsigned long long templ_sqsum = (unsigned long long)sqrSum(templ)[0]; |
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matchTemplatePrepared_CCOFF_NORMED_8U( |
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templ.cols, templ.rows, buf.image_sums[0], buf.image_sqsums[0], |
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templ_sum, templ_sqsum, result, StreamAccessor::getStream(stream)); |
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} |
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else |
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{ |
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split(image, buf.images); |
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buf.image_sums.resize(buf.images.size()); |
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buf.image_sqsums.resize(buf.images.size()); |
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for (int i = 0; i < image.channels(); ++i) |
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{ |
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integral(buf.images[i], buf.image_sums[i], stream); |
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sqrIntegral(buf.images[i], buf.image_sqsums[i], stream); |
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} |
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Scalar templ_sum = sum(templ); |
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Scalar templ_sqsum = sqrSum(templ); |
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switch (image.channels()) |
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{ |
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case 2: |
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matchTemplatePrepared_CCOFF_NORMED_8UC2( |
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templ.cols, templ.rows, |
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buf.image_sums[0], buf.image_sqsums[0], |
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buf.image_sums[1], buf.image_sqsums[1], |
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(unsigned int)templ_sum[0], (unsigned long long)templ_sqsum[0], |
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(unsigned int)templ_sum[1], (unsigned long long)templ_sqsum[1], |
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result, StreamAccessor::getStream(stream)); |
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break; |
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case 3: |
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matchTemplatePrepared_CCOFF_NORMED_8UC3( |
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templ.cols, templ.rows, |
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buf.image_sums[0], buf.image_sqsums[0], |
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buf.image_sums[1], buf.image_sqsums[1], |
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buf.image_sums[2], buf.image_sqsums[2], |
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(unsigned int)templ_sum[0], (unsigned long long)templ_sqsum[0], |
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(unsigned int)templ_sum[1], (unsigned long long)templ_sqsum[1], |
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(unsigned int)templ_sum[2], (unsigned long long)templ_sqsum[2], |
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result, StreamAccessor::getStream(stream)); |
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break; |
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case 4: |
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matchTemplatePrepared_CCOFF_NORMED_8UC4( |
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templ.cols, templ.rows, |
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buf.image_sums[0], buf.image_sqsums[0], |
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buf.image_sums[1], buf.image_sqsums[1], |
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buf.image_sums[2], buf.image_sqsums[2], |
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buf.image_sums[3], buf.image_sqsums[3], |
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(unsigned int)templ_sum[0], (unsigned long long)templ_sqsum[0], |
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(unsigned int)templ_sum[1], (unsigned long long)templ_sqsum[1], |
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(unsigned int)templ_sum[2], (unsigned long long)templ_sqsum[2], |
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(unsigned int)templ_sum[3], (unsigned long long)templ_sqsum[3], |
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result, StreamAccessor::getStream(stream)); |
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break; |
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default: |
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CV_Error(CV_StsBadArg, "matchTemplate: unsupported number of channels"); |
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} |
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} |
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} |
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} |
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void cv::gpu::matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, Stream& stream) |
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{ |
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MatchTemplateBuf buf; |
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matchTemplate(image, templ, result, method, buf, stream); |
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} |
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void cv::gpu::matchTemplate( |
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const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, |
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MatchTemplateBuf &buf, Stream& stream) |
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{ |
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CV_Assert(image.type() == templ.type()); |
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CV_Assert(image.cols >= templ.cols && image.rows >= templ.rows); |
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typedef void (*Caller)(const GpuMat&, const GpuMat&, GpuMat&, MatchTemplateBuf&, Stream& stream); |
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static const Caller callers8U[] = { ::matchTemplate_SQDIFF_8U, ::matchTemplate_SQDIFF_NORMED_8U, |
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::matchTemplate_CCORR_8U, ::matchTemplate_CCORR_NORMED_8U, |
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::matchTemplate_CCOFF_8U, ::matchTemplate_CCOFF_NORMED_8U }; |
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static const Caller callers32F[] = { ::matchTemplate_SQDIFF_32F, 0, |
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::matchTemplate_CCORR_32F, 0, 0, 0 }; |
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const Caller* callers = 0; |
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switch (image.depth()) |
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{ |
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case CV_8U: callers = callers8U; break; |
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case CV_32F: callers = callers32F; break; |
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default: CV_Error(CV_StsBadArg, "matchTemplate: unsupported data type"); |
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} |
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Caller caller = callers[method]; |
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CV_Assert(caller); |
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caller(image, templ, result, buf, stream); |
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} |
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#endif
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