wehub-resource-sync
361 lines
10 KiB
C++
361 lines
10 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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 "test_precomp.hpp"
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#include "opencv2/imgproc/imgproc_c.h"
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namespace opencv_test { namespace {
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class CV_AccumBaseTest : public cvtest::ArrayTest
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{
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public:
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CV_AccumBaseTest();
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protected:
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void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
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double get_success_error_level( int test_case_idx, int i, int j );
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double alpha;
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};
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CV_AccumBaseTest::CV_AccumBaseTest()
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{
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test_array[INPUT].push_back(NULL);
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test_array[INPUT_OUTPUT].push_back(NULL);
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test_array[REF_INPUT_OUTPUT].push_back(NULL);
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test_array[MASK].push_back(NULL);
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optional_mask = true;
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element_wise_relative_error = false;
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} // ctor
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void CV_AccumBaseTest::get_test_array_types_and_sizes( int test_case_idx,
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vector<vector<Size> >& sizes, vector<vector<int> >& types )
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{
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RNG& rng = ts->get_rng();
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int depth = cvtest::randInt(rng) % 4, cn = cvtest::randInt(rng) & 1 ? 3 : 1;
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int accdepth = (int)(cvtest::randInt(rng) % 2 + 1);
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int i, input_count = (int)test_array[INPUT].size();
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cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
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depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : depth == 2 ? CV_32F : CV_64F;
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accdepth = accdepth == 1 ? CV_32F : CV_64F;
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accdepth = MAX(accdepth, depth);
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for( i = 0; i < input_count; i++ )
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types[INPUT][i] = CV_MAKETYPE(depth,cn);
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types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(accdepth,cn);
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alpha = cvtest::randReal(rng);
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}
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double CV_AccumBaseTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
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{
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return test_mat[INPUT_OUTPUT][0].depth() < CV_64F ||
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test_mat[INPUT][0].depth() == CV_32F ? FLT_EPSILON*100 : DBL_EPSILON*1000;
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}
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/// acc
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class CV_AccTest : public CV_AccumBaseTest
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{
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public:
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CV_AccTest() { }
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protected:
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void run_func();
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void prepare_to_validation( int );
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};
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void CV_AccTest::run_func(void)
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{
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cvAcc( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
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}
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void CV_AccTest::prepare_to_validation( int )
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{
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const Mat& src = test_mat[INPUT][0];
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Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
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const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
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Mat temp;
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cvtest::add( src, 1, dst, 1, cvScalarAll(0.), temp, dst.type() );
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cvtest::copy( temp, dst, mask );
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}
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/// square acc
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class CV_SquareAccTest : public CV_AccumBaseTest
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{
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public:
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CV_SquareAccTest();
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protected:
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void run_func();
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void prepare_to_validation( int );
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};
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CV_SquareAccTest::CV_SquareAccTest()
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{
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}
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void CV_SquareAccTest::run_func()
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{
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cvSquareAcc( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
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}
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void CV_SquareAccTest::prepare_to_validation( int )
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{
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const Mat& src = test_mat[INPUT][0];
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Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
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const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
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Mat temp;
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cvtest::convert( src, temp, dst.type() );
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cvtest::multiply( temp, temp, temp, 1 );
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cvtest::add( temp, 1, dst, 1, cvScalarAll(0.), temp, dst.depth() );
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cvtest::copy( temp, dst, mask );
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}
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/// multiply acc
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class CV_MultiplyAccTest : public CV_AccumBaseTest
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{
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public:
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CV_MultiplyAccTest();
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protected:
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void run_func();
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void prepare_to_validation( int );
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};
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CV_MultiplyAccTest::CV_MultiplyAccTest()
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{
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test_array[INPUT].push_back(NULL);
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}
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void CV_MultiplyAccTest::run_func()
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{
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cvMultiplyAcc( test_array[INPUT][0], test_array[INPUT][1],
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test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
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}
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void CV_MultiplyAccTest::prepare_to_validation( int )
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{
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const Mat& src1 = test_mat[INPUT][0];
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const Mat& src2 = test_mat[INPUT][1];
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Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
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const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
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Mat temp1, temp2;
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cvtest::convert( src1, temp1, dst.type() );
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cvtest::convert( src2, temp2, dst.type() );
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cvtest::multiply( temp1, temp2, temp1, 1 );
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cvtest::add( temp1, 1, dst, 1, cvScalarAll(0.), temp1, dst.depth() );
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cvtest::copy( temp1, dst, mask );
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}
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/// running average
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class CV_RunningAvgTest : public CV_AccumBaseTest
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{
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public:
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CV_RunningAvgTest();
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protected:
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void run_func();
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void prepare_to_validation( int );
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};
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CV_RunningAvgTest::CV_RunningAvgTest()
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{
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}
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void CV_RunningAvgTest::run_func()
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{
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cvRunningAvg( test_array[INPUT][0], test_array[INPUT_OUTPUT][0],
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alpha, test_array[MASK][0] );
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}
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void CV_RunningAvgTest::prepare_to_validation( int )
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{
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const Mat& src = test_mat[INPUT][0];
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Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
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Mat temp;
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const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
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double a[1], b[1];
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int accdepth = test_mat[INPUT_OUTPUT][0].depth();
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CvMat A = cvMat(1,1,accdepth,a), B = cvMat(1,1,accdepth,b);
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cvSetReal1D( &A, 0, alpha);
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cvSetReal1D( &B, 0, 1 - cvGetReal1D(&A, 0));
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cvtest::convert( src, temp, dst.type() );
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cvtest::add( src, cvGetReal1D(&A, 0), dst, cvGetReal1D(&B, 0), cvScalarAll(0.), temp, temp.depth() );
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cvtest::copy( temp, dst, mask );
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}
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TEST(Video_Acc, accuracy) { CV_AccTest test; test.safe_run(); }
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TEST(Video_AccSquared, accuracy) { CV_SquareAccTest test; test.safe_run(); }
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TEST(Video_AccProduct, accuracy) { CV_MultiplyAccTest test; test.safe_run(); }
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TEST(Video_RunningAvg, accuracy) { CV_RunningAvgTest test; test.safe_run(); }
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typedef testing::TestWithParam<tuple<Size, int, int> > Video_Acc_Cn4;
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TEST_P(Video_Acc_Cn4, accuracy)
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{
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const Size size = get<0>(GetParam());
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const int pattern = get<1>(GetParam());
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const int srcType = get<2>(GetParam());
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RNG& rng = theRNG();
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Mat src(size, srcType);
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Mat dst(size, CV_32FC4);
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Mat mask(size, CV_8UC1);
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if (srcType == CV_8UC4)
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rng.fill(src, RNG::UNIFORM, Scalar::all(0), Scalar::all(256));
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else
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rng.fill(src, RNG::UNIFORM, Scalar::all(-10.0), Scalar::all(10.0));
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rng.fill(dst, RNG::UNIFORM, Scalar::all(-1000.0), Scalar::all(1000.0));
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for (int y = 0; y < mask.rows; ++y)
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{
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uchar* row = mask.ptr<uchar>(y);
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for (int x = 0; x < mask.cols; ++x)
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{
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switch (pattern)
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{
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case 0:
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row[x] = 0;
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break;
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case 1:
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row[x] = 255;
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break;
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case 2:
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row[x] = ((x + y) % 2) ? 255 : 0;
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break;
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case 3:
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row[x] = ((x * 13 + y * 7) % 5) ? 255 : 0;
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break;
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default:
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row[x] = ((x * 17 + y * 11) % 3) ? 255 : 0;
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break;
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}
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}
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}
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Mat dstRef = dst.clone();
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if (srcType == CV_32FC4)
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{
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for (int y = 0; y < src.rows; ++y)
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{
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const Vec4f* srcRow = src.ptr<Vec4f>(y);
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Vec4f* dstRefRow = dstRef.ptr<Vec4f>(y);
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const uchar* maskRow = mask.ptr<uchar>(y);
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for (int x = 0; x < src.cols; ++x)
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{
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if (maskRow[x])
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{
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for (int c = 0; c < 4; ++c)
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dstRefRow[x][c] += srcRow[x][c];
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}
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}
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}
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}
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else
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{
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CV_Assert(srcType == CV_8UC4);
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for (int y = 0; y < src.rows; ++y)
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{
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const Vec4b* srcRow = src.ptr<Vec4b>(y);
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Vec4f* dstRefRow = dstRef.ptr<Vec4f>(y);
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const uchar* maskRow = mask.ptr<uchar>(y);
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for (int x = 0; x < src.cols; ++x)
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{
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if (maskRow[x])
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{
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for (int c = 0; c < 4; ++c)
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dstRefRow[x][c] += static_cast<float>(srcRow[x][c]);
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}
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}
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}
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}
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cv::accumulate(src, dst, mask);
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const double err = cv::norm(dst, dstRef, NORM_INF);
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EXPECT_EQ(0.0, err)
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<< "size=" << size
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<< ", pattern=" << pattern
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<< ", srcType=" << srcType;
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}
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INSTANTIATE_TEST_CASE_P(Accumulate,
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Video_Acc_Cn4,
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testing::Combine(
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testing::Values(Size(1, 1),
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Size(3, 5),
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Size(17, 7),
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Size(37, 19),
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Size(128, 16),
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Size(641, 37)),
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testing::Values(0, 1, 2, 3, 4),
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testing::Values(CV_32FC4, CV_8UC4)));
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}} // namespace
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