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Open Source Computer Vision Library
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244 lines
8.0 KiB
244 lines
8.0 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) 2010-2012, Multicoreware, Inc., all rights reserved. |
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// Copyright (C) 2010-2012, Advanced Micro Devices, 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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// @Authors |
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// Peng Xiao, pengxiao@outlook.com |
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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 oclMaterials 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 <map> |
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#include <functional> |
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#include "test_precomp.hpp" |
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using namespace std; |
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using namespace cvtest; |
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using namespace testing; |
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using namespace cv; |
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namespace |
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{ |
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IMPLEMENT_PARAM_CLASS(IsGreaterThan, bool) |
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IMPLEMENT_PARAM_CLASS(InputSize, int) |
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IMPLEMENT_PARAM_CLASS(SortMethod, int) |
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template<class T> |
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struct KV_CVTYPE{ static int toType() {return 0;} }; |
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template<> struct KV_CVTYPE<int> { static int toType() {return CV_32SC1;} }; |
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template<> struct KV_CVTYPE<float>{ static int toType() {return CV_32FC1;} }; |
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template<> struct KV_CVTYPE<Vec2i>{ static int toType() {return CV_32SC2;} }; |
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template<> struct KV_CVTYPE<Vec2f>{ static int toType() {return CV_32FC2;} }; |
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template<class key_type, class val_type> |
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bool kvgreater(pair<key_type, val_type> p1, pair<key_type, val_type> p2) |
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{ |
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return p1.first > p2.first; |
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} |
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template<class key_type, class val_type> |
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bool kvless(pair<key_type, val_type> p1, pair<key_type, val_type> p2) |
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{ |
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return p1.first < p2.first; |
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} |
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template<class key_type, class val_type> |
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void toKVPair( |
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MatConstIterator_<key_type> kit, |
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MatConstIterator_<val_type> vit, |
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int vecSize, |
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vector<pair<key_type, val_type> >& kvres |
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) |
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{ |
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kvres.clear(); |
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for(int i = 0; i < vecSize; i ++) |
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{ |
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kvres.push_back(make_pair(*kit, *vit)); |
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++kit; |
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++vit; |
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} |
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} |
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template<class key_type, class val_type> |
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void kvquicksort(Mat& keys, Mat& vals, bool isGreater = false) |
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{ |
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vector<pair<key_type, val_type> > kvres; |
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toKVPair(keys.begin<key_type>(), vals.begin<val_type>(), keys.cols, kvres); |
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if(isGreater) |
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{ |
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std::sort(kvres.begin(), kvres.end(), kvgreater<key_type, val_type>); |
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} |
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else |
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{ |
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std::sort(kvres.begin(), kvres.end(), kvless<key_type, val_type>); |
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} |
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key_type * kptr = keys.ptr<key_type>(); |
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val_type * vptr = vals.ptr<val_type>(); |
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for(int i = 0; i < keys.cols; i ++) |
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{ |
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kptr[i] = kvres[i].first; |
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vptr[i] = kvres[i].second; |
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} |
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} |
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class SortByKey_STL |
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{ |
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public: |
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static void sort(cv::Mat&, cv::Mat&, bool is_gt); |
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private: |
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typedef void (*quick_sorter)(cv::Mat&, cv::Mat&, bool); |
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SortByKey_STL(); |
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quick_sorter quick_sorters[CV_64FC4][CV_64FC4]; |
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static SortByKey_STL instance; |
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}; |
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SortByKey_STL SortByKey_STL::instance = SortByKey_STL(); |
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SortByKey_STL::SortByKey_STL() |
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{ |
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memset(instance.quick_sorters, 0, sizeof(quick_sorters)); |
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#define NEW_SORTER(KT, VT) \ |
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instance.quick_sorters[KV_CVTYPE<KT>::toType()][KV_CVTYPE<VT>::toType()] = kvquicksort<KT, VT>; |
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NEW_SORTER(int, int); |
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NEW_SORTER(int, Vec2i); |
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NEW_SORTER(int, float); |
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NEW_SORTER(int, Vec2f); |
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NEW_SORTER(float, int); |
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NEW_SORTER(float, Vec2i); |
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NEW_SORTER(float, float); |
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NEW_SORTER(float, Vec2f); |
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#undef NEW_SORTER |
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} |
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void SortByKey_STL::sort(cv::Mat& keys, cv::Mat& vals, bool is_gt) |
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{ |
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instance.quick_sorters[keys.type()][vals.type()](keys, vals, is_gt); |
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} |
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bool checkUnstableSorterResult(const Mat& gkeys_, const Mat& gvals_, |
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const Mat& /*dkeys_*/, const Mat& dvals_) |
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{ |
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int cn_val = gvals_.channels(); |
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int count = gkeys_.cols; |
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//for convenience we convert depth to float and channels to 1 |
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Mat gkeys, gvals, dkeys, dvals; |
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gkeys_.reshape(1).convertTo(gkeys, CV_32F); |
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gvals_.reshape(1).convertTo(gvals, CV_32F); |
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//dkeys_.reshape(1).convertTo(dkeys, CV_32F); |
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dvals_.reshape(1).convertTo(dvals, CV_32F); |
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float * gkptr = gkeys.ptr<float>(); |
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float * gvptr = gvals.ptr<float>(); |
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//float * dkptr = dkeys.ptr<float>(); |
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float * dvptr = dvals.ptr<float>(); |
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for(int i = 0; i < count - 1; ++i) |
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{ |
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int iden_count = 0; |
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// firstly calculate the number of identical keys |
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while(gkptr[i + iden_count] == gkptr[i + 1 + iden_count]) |
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{ |
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++ iden_count; |
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} |
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// sort dv and gv |
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int num_of_val = (iden_count + 1) * cn_val; |
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std::sort(gvptr + i * cn_val, gvptr + i * cn_val + num_of_val); |
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std::sort(dvptr + i * cn_val, dvptr + i * cn_val + num_of_val); |
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// then check if [i, i + iden_count) is the same |
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for(int j = 0; j < num_of_val; ++j) |
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{ |
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if(gvptr[i + j] != dvptr[i + j]) |
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{ |
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return false; |
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} |
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} |
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i += iden_count; |
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} |
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return true; |
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} |
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} |
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#define INPUT_SIZES Values(InputSize(0x10), InputSize(0x100), InputSize(0x10000)) //2^4, 2^8, 2^16 |
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#define KEY_TYPES Values(MatType(CV_32SC1), MatType(CV_32FC1)) |
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#define VAL_TYPES Values(MatType(CV_32SC1), MatType(CV_32SC2), MatType(CV_32FC1), MatType(CV_32FC2)) |
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#define SORT_METHODS Values(SortMethod(cv::ocl::SORT_BITONIC),SortMethod(cv::ocl::SORT_MERGE),SortMethod(cv::ocl::SORT_RADIX)/*,SortMethod(cv::ocl::SORT_SELECTION)*/) |
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#define F_OR_T Values(IsGreaterThan(false), IsGreaterThan(true)) |
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PARAM_TEST_CASE(SortByKey, InputSize, MatType, MatType, SortMethod, IsGreaterThan) |
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{ |
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InputSize input_size; |
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MatType key_type, val_type; |
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SortMethod method; |
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IsGreaterThan is_gt; |
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Mat mat_key, mat_val; |
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virtual void SetUp() |
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{ |
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input_size = GET_PARAM(0); |
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key_type = GET_PARAM(1); |
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val_type = GET_PARAM(2); |
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method = GET_PARAM(3); |
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is_gt = GET_PARAM(4); |
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using namespace cv; |
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// fill key and val |
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mat_key = randomMat(Size(input_size, 1), key_type, INT_MIN, INT_MAX); |
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mat_val = randomMat(Size(input_size, 1), val_type, INT_MIN, INT_MAX); |
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} |
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}; |
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OCL_TEST_P(SortByKey, Accuracy) |
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{ |
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using namespace cv; |
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ocl::oclMat oclmat_key(mat_key); |
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ocl::oclMat oclmat_val(mat_val); |
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ocl::sortByKey(oclmat_key, oclmat_val, method, is_gt); |
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SortByKey_STL::sort(mat_key, mat_val, is_gt); |
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EXPECT_MAT_NEAR(mat_key, oclmat_key, 0.0); |
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EXPECT_TRUE(checkUnstableSorterResult(mat_key, mat_val, oclmat_key, oclmat_val)); |
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} |
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INSTANTIATE_TEST_CASE_P(OCL_SORT, SortByKey, Combine(INPUT_SIZES, KEY_TYPES, VAL_TYPES, SORT_METHODS, F_OR_T));
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