245 lines
8.0 KiB
C++
245 lines
8.0 KiB
C++
/*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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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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