2011-02-10 04:55:11 +08:00
|
|
|
/*M///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
//
|
|
|
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
|
|
|
//
|
|
|
|
// By downloading, copying, installing or using the software you agree to this license.
|
|
|
|
// If you do not agree to this license, do not download, install,
|
|
|
|
// copy or use the software.
|
|
|
|
//
|
|
|
|
//
|
|
|
|
// Intel License Agreement
|
|
|
|
// For Open Source Computer Vision Library
|
|
|
|
//
|
|
|
|
// Copyright (C) 2000, Intel Corporation, all rights reserved.
|
|
|
|
// Third party copyrights are property of their respective owners.
|
|
|
|
//
|
|
|
|
// Redistribution and use in source and binary forms, with or without modification,
|
|
|
|
// are permitted provided that the following conditions are met:
|
|
|
|
//
|
|
|
|
// * Redistribution's of source code must retain the above copyright notice,
|
|
|
|
// this list of conditions and the following disclaimer.
|
|
|
|
//
|
|
|
|
// * Redistribution's in binary form must reproduce the above copyright notice,
|
|
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
|
|
// and/or other materials provided with the distribution.
|
|
|
|
//
|
|
|
|
// * The name of Intel Corporation may not be used to endorse or promote products
|
|
|
|
// derived from this software without specific prior written permission.
|
|
|
|
//
|
|
|
|
// This software is provided by the copyright holders and contributors "as is" and
|
|
|
|
// any express or implied warranties, including, but not limited to, the implied
|
|
|
|
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
|
|
|
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
|
|
|
// indirect, incidental, special, exemplary, or consequential damages
|
|
|
|
// (including, but not limited to, procurement of substitute goods or services;
|
|
|
|
// loss of use, data, or profits; or business interruption) however caused
|
|
|
|
// and on any theory of liability, whether in contract, strict liability,
|
|
|
|
// or tort (including negligence or otherwise) arising in any way out of
|
|
|
|
// the use of this software, even if advised of the possibility of such damage.
|
|
|
|
//
|
|
|
|
//M*/
|
|
|
|
|
|
|
|
#include "test_precomp.hpp"
|
2013-04-10 19:54:14 +08:00
|
|
|
#include "opencv2/imgproc/imgproc_c.h"
|
2011-02-10 04:55:11 +08:00
|
|
|
|
|
|
|
using namespace cv;
|
|
|
|
using namespace std;
|
|
|
|
|
|
|
|
class CV_AccumBaseTest : public cvtest::ArrayTest
|
|
|
|
{
|
|
|
|
public:
|
|
|
|
CV_AccumBaseTest();
|
|
|
|
|
|
|
|
protected:
|
|
|
|
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
|
|
|
|
double get_success_error_level( int test_case_idx, int i, int j );
|
|
|
|
double alpha;
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
CV_AccumBaseTest::CV_AccumBaseTest()
|
|
|
|
{
|
|
|
|
test_array[INPUT].push_back(NULL);
|
|
|
|
test_array[INPUT_OUTPUT].push_back(NULL);
|
|
|
|
test_array[REF_INPUT_OUTPUT].push_back(NULL);
|
|
|
|
test_array[MASK].push_back(NULL);
|
|
|
|
optional_mask = true;
|
|
|
|
element_wise_relative_error = false;
|
|
|
|
} // ctor
|
|
|
|
|
|
|
|
|
|
|
|
void CV_AccumBaseTest::get_test_array_types_and_sizes( int test_case_idx,
|
|
|
|
vector<vector<Size> >& sizes, vector<vector<int> >& types )
|
|
|
|
{
|
|
|
|
RNG& rng = ts->get_rng();
|
|
|
|
int depth = cvtest::randInt(rng) % 3, cn = cvtest::randInt(rng) & 1 ? 3 : 1;
|
|
|
|
int accdepth = std::max((int)(cvtest::randInt(rng) % 2 + 1), depth);
|
2011-07-19 20:27:07 +08:00
|
|
|
int i, input_count = (int)test_array[INPUT].size();
|
2011-02-10 04:55:11 +08:00
|
|
|
cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
|
|
|
|
depth = depth == 0 ? CV_8U : depth == 1 ? CV_32F : CV_64F;
|
|
|
|
accdepth = accdepth == 1 ? CV_32F : CV_64F;
|
|
|
|
accdepth = MAX(accdepth, depth);
|
|
|
|
|
|
|
|
for( i = 0; i < input_count; i++ )
|
|
|
|
types[INPUT][i] = CV_MAKETYPE(depth,cn);
|
|
|
|
|
|
|
|
types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(accdepth,cn);
|
|
|
|
|
|
|
|
alpha = cvtest::randReal(rng);
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
double CV_AccumBaseTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
|
|
|
|
{
|
|
|
|
return test_mat[INPUT_OUTPUT][0].depth() < CV_64F ||
|
|
|
|
test_mat[INPUT][0].depth() == CV_32F ? FLT_EPSILON*100 : DBL_EPSILON*1000;
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/// acc
|
|
|
|
class CV_AccTest : public CV_AccumBaseTest
|
|
|
|
{
|
|
|
|
public:
|
2014-01-18 05:30:29 +08:00
|
|
|
CV_AccTest() { }
|
2011-02-10 04:55:11 +08:00
|
|
|
protected:
|
|
|
|
void run_func();
|
|
|
|
void prepare_to_validation( int );
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
void CV_AccTest::run_func(void)
|
|
|
|
{
|
|
|
|
cvAcc( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void CV_AccTest::prepare_to_validation( int )
|
|
|
|
{
|
|
|
|
const Mat& src = test_mat[INPUT][0];
|
|
|
|
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
|
|
|
|
const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
|
|
|
|
Mat temp;
|
|
|
|
cvtest::add( src, 1, dst, 1, cvScalarAll(0.), temp, dst.type() );
|
|
|
|
cvtest::copy( temp, dst, mask );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/// square acc
|
|
|
|
class CV_SquareAccTest : public CV_AccumBaseTest
|
|
|
|
{
|
|
|
|
public:
|
|
|
|
CV_SquareAccTest();
|
|
|
|
protected:
|
|
|
|
void run_func();
|
|
|
|
void prepare_to_validation( int );
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
CV_SquareAccTest::CV_SquareAccTest()
|
|
|
|
{
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void CV_SquareAccTest::run_func()
|
|
|
|
{
|
|
|
|
cvSquareAcc( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void CV_SquareAccTest::prepare_to_validation( int )
|
|
|
|
{
|
|
|
|
const Mat& src = test_mat[INPUT][0];
|
|
|
|
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
|
|
|
|
const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
|
|
|
|
Mat temp;
|
2012-10-17 15:12:04 +08:00
|
|
|
|
|
|
|
cvtest::convert( src, temp, dst.type() );
|
2011-02-10 04:55:11 +08:00
|
|
|
cvtest::multiply( temp, temp, temp, 1 );
|
|
|
|
cvtest::add( temp, 1, dst, 1, cvScalarAll(0.), temp, dst.depth() );
|
|
|
|
cvtest::copy( temp, dst, mask );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/// multiply acc
|
|
|
|
class CV_MultiplyAccTest : public CV_AccumBaseTest
|
|
|
|
{
|
|
|
|
public:
|
|
|
|
CV_MultiplyAccTest();
|
|
|
|
protected:
|
|
|
|
void run_func();
|
|
|
|
void prepare_to_validation( int );
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
CV_MultiplyAccTest::CV_MultiplyAccTest()
|
|
|
|
{
|
|
|
|
test_array[INPUT].push_back(NULL);
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void CV_MultiplyAccTest::run_func()
|
|
|
|
{
|
|
|
|
cvMultiplyAcc( test_array[INPUT][0], test_array[INPUT][1],
|
|
|
|
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void CV_MultiplyAccTest::prepare_to_validation( int )
|
|
|
|
{
|
|
|
|
const Mat& src1 = test_mat[INPUT][0];
|
|
|
|
const Mat& src2 = test_mat[INPUT][1];
|
|
|
|
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
|
|
|
|
const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
|
|
|
|
Mat temp1, temp2;
|
2012-10-17 15:12:04 +08:00
|
|
|
|
2011-02-10 04:55:11 +08:00
|
|
|
cvtest::convert( src1, temp1, dst.type() );
|
|
|
|
cvtest::convert( src2, temp2, dst.type() );
|
2012-10-17 15:12:04 +08:00
|
|
|
|
2011-02-10 04:55:11 +08:00
|
|
|
cvtest::multiply( temp1, temp2, temp1, 1 );
|
|
|
|
cvtest::add( temp1, 1, dst, 1, cvScalarAll(0.), temp1, dst.depth() );
|
|
|
|
cvtest::copy( temp1, dst, mask );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/// running average
|
|
|
|
class CV_RunningAvgTest : public CV_AccumBaseTest
|
|
|
|
{
|
|
|
|
public:
|
|
|
|
CV_RunningAvgTest();
|
|
|
|
protected:
|
|
|
|
void run_func();
|
|
|
|
void prepare_to_validation( int );
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
CV_RunningAvgTest::CV_RunningAvgTest()
|
|
|
|
{
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void CV_RunningAvgTest::run_func()
|
|
|
|
{
|
|
|
|
cvRunningAvg( test_array[INPUT][0], test_array[INPUT_OUTPUT][0],
|
|
|
|
alpha, test_array[MASK][0] );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void CV_RunningAvgTest::prepare_to_validation( int )
|
|
|
|
{
|
|
|
|
const Mat& src = test_mat[INPUT][0];
|
|
|
|
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
|
|
|
|
Mat temp;
|
|
|
|
const Mat& mask = test_array[MASK][0] ? test_mat[MASK][0] : Mat();
|
|
|
|
double a[1], b[1];
|
|
|
|
int accdepth = test_mat[INPUT_OUTPUT][0].depth();
|
|
|
|
CvMat A = cvMat(1,1,accdepth,a), B = cvMat(1,1,accdepth,b);
|
|
|
|
cvSetReal1D( &A, 0, alpha);
|
|
|
|
cvSetReal1D( &B, 0, 1 - cvGetReal1D(&A, 0));
|
|
|
|
|
|
|
|
cvtest::convert( src, temp, dst.type() );
|
|
|
|
cvtest::add( src, cvGetReal1D(&A, 0), dst, cvGetReal1D(&B, 0), cvScalarAll(0.), temp, temp.depth() );
|
|
|
|
cvtest::copy( temp, dst, mask );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
TEST(Video_Acc, accuracy) { CV_AccTest test; test.safe_run(); }
|
|
|
|
TEST(Video_AccSquared, accuracy) { CV_SquareAccTest test; test.safe_run(); }
|
|
|
|
TEST(Video_AccProduct, accuracy) { CV_MultiplyAccTest test; test.safe_run(); }
|
|
|
|
TEST(Video_RunningAvg, accuracy) { CV_RunningAvgTest test; test.safe_run(); }
|