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8190837dd4fcdfc218945e21362daab183cbfdff
opencv/tests/cxcore/src/aarithm.cpp
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Vadim Pisarevsky 127d6649a1 "atomic bomb" commit. Reorganized OpenCV directory structure
2010-05-11 17:44:00 +00:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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// 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.
//
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
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// or tort (including negligence or otherwise) arising in any way out of
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//M*/
//////////////////////////////////////////////////////////////////////////////////////////
////////////////// tests for arithmetic, logic and statistical functions /////////////////
//////////////////////////////////////////////////////////////////////////////////////////
#include "cxcoretest.h"
#include <float.h>
static const CvSize arithm_sizes[] = {{10,10}, {100,100}, {720,480}, {-1,-1}};
static const CvSize arithm_whole_sizes[] = {{10,10}, {720,480}, {720,480}, {-1,-1}};
static const int arithm_depths[] = { CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F, -1 };
static const int arithm_channels[] = { 1, 2, 3, 4, -1 };
static const char* arithm_mask_param_names[] = { "size", "channels", "depth", "use_mask", 0 };
static const char* arithm_param_names[] = { "size", "channels", "depth", 0 };
static const char* minmax_param_names[] = { "size", "depth", 0 };
class CxCore_ArithmTestImpl : public CvArrTest
{
public:
CxCore_ArithmTestImpl( const char* test_name, const char* test_funcs,
int _generate_scalars=0, bool _allow_mask=true, bool _calc_abs=false );
protected:
void prepare_to_validation( int test_case_idx );
void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
void get_timing_test_array_types_and_sizes( int /*test_case_idx*/,
CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images );
void generate_scalars( int depth );
void finalize_scalar( CvScalar& s );
CvScalar alpha, beta, gamma;
int gen_scalars;
bool calc_abs;
bool test_nd;
};
CxCore_ArithmTestImpl::CxCore_ArithmTestImpl( const char* test_name, const char* test_funcs,
int _generate_scalars, bool _allow_mask, bool _calc_abs )
: CvArrTest( test_name, test_funcs, "" ),
gen_scalars(_generate_scalars), calc_abs(_calc_abs)
{
test_array[INPUT].push(NULL);
test_array[INPUT].push(NULL);
optional_mask = _allow_mask;
if( optional_mask )
{
test_array[INPUT_OUTPUT].push(NULL);
test_array[REF_INPUT_OUTPUT].push(NULL);
test_array[TEMP].push(NULL);
test_array[MASK].push(NULL);
}
else
{
test_array[OUTPUT].push(NULL);
test_array[REF_OUTPUT].push(NULL);
}
alpha = beta = gamma = cvScalarAll(0);
size_list = arithm_sizes;
whole_size_list = arithm_whole_sizes;
depth_list = arithm_depths;
cn_list = arithm_channels;
test_nd = false;
}
void CxCore_ArithmTestImpl::generate_scalars( int depth )
{
bool is_timing = ts->get_testing_mode() == CvTS::TIMING_MODE;
double ab_min_val = -1.;
double ab_max_val = 1.;
double gamma_min_val = depth == CV_8U ? -100 : depth < CV_32F ? -10000 : -1e6;
double gamma_max_val = depth == CV_8U ? 100 : depth < CV_32F ? 10000 : 1e6;
if( gen_scalars )
{
CvRNG* rng = ts->get_rng();
int i;
double m = 3.;
for( i = 0; i < 4; i++ )
{
if( gen_scalars & 1 )
{
alpha.val[i] = exp((cvTsRandReal(rng)-0.5)*m*2*CV_LOG2);
alpha.val[i] *= (cvTsRandInt(rng) & 1) ? 1 : -1;
if( is_timing )
{
alpha.val[i] = MAX( alpha.val[i], ab_min_val );
alpha.val[i] = MIN( alpha.val[i], ab_max_val );
}
}
if( gen_scalars & 2 )
{
beta.val[i] = exp((cvTsRandReal(rng)-0.5)*m*2*CV_LOG2);
beta.val[i] *= (cvTsRandInt(rng) & 1) ? 1 : -1;
if( is_timing )
{
beta.val[i] = MAX( beta.val[i], ab_min_val );
beta.val[i] = MIN( beta.val[i], ab_max_val );
}
}
if( gen_scalars & 4 )
{
gamma.val[i] = exp((cvTsRandReal(rng)-0.5)*m*2*CV_LOG2);
gamma.val[i] *= (cvTsRandInt(rng) & 1) ? 1 : -1;
if( is_timing )
{
gamma.val[i] = MAX( gamma.val[i], gamma_min_val );
gamma.val[i] = MIN( gamma.val[i], gamma_max_val );
}
}
}
}
if( depth == CV_32F )
{
CvMat fl = cvMat( 1, 4, CV_32F, buf );
CvMat db = cvMat( 1, 4, CV_64F, 0 );
db.data.db = alpha.val;
cvTsConvert( &db, &fl );
cvTsConvert( &fl, &db );
db.data.db = beta.val;
cvTsConvert( &db, &fl );
cvTsConvert( &fl, &db );
db.data.db = gamma.val;
cvTsConvert( &db, &fl );
cvTsConvert( &fl, &db );
}
}
void CxCore_ArithmTestImpl::finalize_scalar( CvScalar& s )
{
int depth = CV_MAT_DEPTH(test_mat[INPUT][0].type);
if( depth < CV_32F )
s = cvScalar(cvRound(s.val[0]), cvRound(s.val[1]), cvRound(s.val[2]), cvRound(s.val[3]));
}
void CxCore_ArithmTestImpl::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
CvRNG* rng = ts->get_rng();
int depth = cvTsRandInt(rng)%(CV_64F+1);
int cn = cvTsRandInt(rng) % 4 + 1;
int i, j;
depth += depth == CV_8S;
CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
generate_scalars( depth );
for( i = 0; i < max_arr; i++ )
{
int count = test_array[i].size();
int type = i != MASK ? CV_MAKETYPE(depth, cn) : CV_8UC1;
for( j = 0; j < count; j++ )
{
types[i][j] = type;
}
}
test_nd = cvTsRandInt(rng)%3 == 0;
}
void CxCore_ArithmTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
{
CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
whole_sizes, are_images );
generate_scalars( types[INPUT][0] );
test_nd = false;
}
void CxCore_ArithmTestImpl::prepare_to_validation( int /*test_case_idx*/ )
{
const CvMat* mask = test_array[MASK].size() > 0 && test_array[MASK][0] ? &test_mat[MASK][0] : 0;
CvMat* output = test_array[REF_INPUT_OUTPUT].size() > 0 ?
&test_mat[REF_INPUT_OUTPUT][0] : &test_mat[REF_OUTPUT][0];
CvMat* temp_dst = mask ? &test_mat[TEMP][0] : output;
cvTsAdd( &test_mat[INPUT][0], alpha,
test_array[INPUT].size() > 1 ? &test_mat[INPUT][1] : 0, beta,
gamma, temp_dst, calc_abs );
if( mask )
cvTsCopy( temp_dst, output, mask );
}
CxCore_ArithmTestImpl arithm( "arithm", "", 0, false );
class CxCore_ArithmTest : public CxCore_ArithmTestImpl
{
public:
CxCore_ArithmTest( const char* test_name, const char* test_funcs,
int _generate_scalars=0, bool _allow_mask=true, bool _calc_abs=false );
};
CxCore_ArithmTest::CxCore_ArithmTest( const char* test_name, const char* test_funcs,
int _generate_scalars, bool _allow_mask, bool _calc_abs ) :
CxCore_ArithmTestImpl( test_name, test_funcs, _generate_scalars, _allow_mask, _calc_abs )
{
default_timing_param_names = optional_mask ? arithm_mask_param_names : arithm_param_names;
// inherit the default parameters from arithmetical test
size_list = 0;
whole_size_list = 0;
depth_list = 0;
cn_list = 0;
}
////////////////////////////// add /////////////////////////////
class CxCore_AddTest : public CxCore_ArithmTest
{
public:
CxCore_AddTest();
protected:
void run_func();
};
CxCore_AddTest::CxCore_AddTest()
: CxCore_ArithmTest( "arithm-add", "cvAdd", 0, true )
{
alpha = beta = cvScalarAll(1.);
}
void CxCore_AddTest::run_func()
{
if(!test_nd)
{
cvAdd( test_array[INPUT][0], test_array[INPUT][1],
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
cv::MatND b = cv::cvarrToMatND(test_array[INPUT][1]);
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
if( !test_array[MASK][0] )
cv::add(a, b, c);
else
cv::add(a, b, c, cv::cvarrToMatND(test_array[MASK][0]));
}
}
CxCore_AddTest add_test;
////////////////////////////// sub /////////////////////////////
class CxCore_SubTest : public CxCore_ArithmTest
{
public:
CxCore_SubTest();
protected:
void run_func();
};
CxCore_SubTest::CxCore_SubTest()
: CxCore_ArithmTest( "arithm-sub", "cvSub", 0, true )
{
alpha = cvScalarAll(1.);
beta = cvScalarAll(-1.);
}
void CxCore_SubTest::run_func()
{
if(!test_nd)
{
cvSub( test_array[INPUT][0], test_array[INPUT][1],
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
cv::MatND b = cv::cvarrToMatND(test_array[INPUT][1]);
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
if( !test_array[MASK][0] )
cv::subtract(a, b, c);
else
cv::subtract(a, b, c, cv::cvarrToMatND(test_array[MASK][0]));
}
}
CxCore_SubTest sub_test;
////////////////////////////// adds /////////////////////////////
class CxCore_AddSTest : public CxCore_ArithmTest
{
public:
CxCore_AddSTest();
protected:
void run_func();
};
CxCore_AddSTest::CxCore_AddSTest()
: CxCore_ArithmTest( "arithm-adds", "cvAddS", 4, true )
{
test_array[INPUT].pop();
alpha = cvScalarAll(1.);
}
void CxCore_AddSTest::run_func()
{
finalize_scalar(gamma);
if(!test_nd)
{
if( test_mat[INPUT][0].cols % 2 == 0 )
cvAddS( test_array[INPUT][0], gamma,
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
else
{
cv::Mat a = cv::cvarrToMat(test_array[INPUT][0]),
c = cv::cvarrToMat(test_array[INPUT_OUTPUT][0]);
cv::subtract(a, -cv::Scalar(gamma), c, test_array[MASK][0] ?
cv::cvarrToMat(test_array[MASK][0]) : cv::Mat());
}
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
cv::add( cv::cvarrToMatND(test_array[INPUT][0]),
gamma, c, test_array[MASK][0] ?
cv::cvarrToMatND(test_array[MASK][0]) : cv::MatND());
}
}
CxCore_AddSTest adds_test;
////////////////////////////// subrs /////////////////////////////
class CxCore_SubRSTest : public CxCore_ArithmTest
{
public:
CxCore_SubRSTest();
protected:
void run_func();
};
CxCore_SubRSTest::CxCore_SubRSTest()
: CxCore_ArithmTest( "arithm-subrs", "cvSubRS", 4, true )
{
test_array[INPUT].pop();
alpha = cvScalarAll(-1.);
}
void CxCore_SubRSTest::run_func()
{
finalize_scalar(gamma);
if(!test_nd)
{
cvSubRS( test_array[INPUT][0], gamma,
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
cv::subtract( gamma,
cv::cvarrToMatND(test_array[INPUT][0]),
c, test_array[MASK][0] ?
cv::cvarrToMatND(test_array[MASK][0]) : cv::MatND());
}
}
CxCore_SubRSTest subrs_test;
////////////////////////////// addweighted /////////////////////////////
class CxCore_AddWeightedTest : public CxCore_ArithmTest
{
public:
CxCore_AddWeightedTest();
protected:
void get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types );
double get_success_error_level( int test_case_idx, int i, int j );
void run_func();
};
CxCore_AddWeightedTest::CxCore_AddWeightedTest()
: CxCore_ArithmTest( "arithm-addweighted", "cvAddWeighted", 7, false )
{
}
void CxCore_AddWeightedTest::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
CxCore_ArithmTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
alpha = cvScalarAll(alpha.val[0]);
beta = cvScalarAll(beta.val[0]);
gamma = cvScalarAll(gamma.val[0]);
}
double CxCore_AddWeightedTest::get_success_error_level( int test_case_idx, int i, int j )
{
int type = cvGetElemType(test_array[i][j]), depth = CV_MAT_DEPTH(type);
if( depth <= CV_32S )
return 2;
if( depth == CV_32F )
{
CvScalar low=cvScalarAll(0), high=low;
get_minmax_bounds(i,j,type, &low, &high);
double a = (fabs(alpha.val[0])+fabs(beta.val[0]))*(fabs(low.val[0])+fabs(high.val[0]));
double b = fabs(gamma.val[0]);
return (a+b)*500*FLT_EPSILON;
}
return CvArrTest::get_success_error_level( test_case_idx, i, j );
}
void CxCore_AddWeightedTest::run_func()
{
if(!test_nd)
{
cvAddWeighted( test_array[INPUT][0], alpha.val[0],
test_array[INPUT][1], beta.val[0],
gamma.val[0], test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::addWeighted(cv::cvarrToMatND(test_array[INPUT][0]),
alpha.val[0],
cv::cvarrToMatND(test_array[INPUT][1]),
beta.val[0], gamma.val[0], c);
}
}
CxCore_AddWeightedTest addweighted_test;
////////////////////////////// absdiff /////////////////////////////
class CxCore_AbsDiffTest : public CxCore_ArithmTest
{
public:
CxCore_AbsDiffTest();
protected:
void run_func();
};
CxCore_AbsDiffTest::CxCore_AbsDiffTest()
: CxCore_ArithmTest( "arithm-absdiff", "cvAbsDiff", 0, false, true )
{
alpha = cvScalarAll(1.);
beta = cvScalarAll(-1.);
}
void CxCore_AbsDiffTest::run_func()
{
if(!test_nd)
{
cvAbsDiff( test_array[INPUT][0], test_array[INPUT][1], test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::absdiff(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]),
c );
}
}
CxCore_AbsDiffTest absdiff_test;
////////////////////////////// absdiffs /////////////////////////////
class CxCore_AbsDiffSTest : public CxCore_ArithmTest
{
public:
CxCore_AbsDiffSTest();
protected:
void run_func();
};
CxCore_AbsDiffSTest::CxCore_AbsDiffSTest()
: CxCore_ArithmTest( "arithm-absdiffs", "cvAbsDiffS", 4, false, true )
{
alpha = cvScalarAll(-1.);
test_array[INPUT].pop();
}
void CxCore_AbsDiffSTest::run_func()
{
finalize_scalar(gamma);
if(!test_nd)
{
cvAbsDiffS( test_array[INPUT][0], test_array[OUTPUT][0], gamma );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::absdiff(cv::cvarrToMatND(test_array[INPUT][0]),
gamma, c);
}
}
CxCore_AbsDiffSTest absdiffs_test;
////////////////////////////// mul /////////////////////////////
static const char* mul_param_names[] = { "size", "scale", "channels", "depth", 0 };
static const char* mul_scale_flags[] = { "scale==1", "scale!=1", 0 };
class CxCore_MulTest : public CxCore_ArithmTest
{
public:
CxCore_MulTest();
protected:
void run_func();
void get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images );
double get_success_error_level( int test_case_idx, int i, int j );
void print_timing_params( int test_case_idx, char* ptr, int params_left );
void prepare_to_validation( int test_case_idx );
int write_default_params( CvFileStorage* fs );
};
CxCore_MulTest::CxCore_MulTest()
: CxCore_ArithmTest( "arithm-mul", "cvMul", 4, false, false )
{
default_timing_param_names = mul_param_names;
}
int CxCore_MulTest::write_default_params( CvFileStorage* fs )
{
int code = CxCore_ArithmTest::write_default_params(fs);
if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
return code;
write_string_list( fs, "scale", mul_scale_flags );
return code;
}
void CxCore_MulTest::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images )
{
CxCore_ArithmTest::get_timing_test_array_types_and_sizes( test_case_idx,
sizes, types, whole_sizes, are_images );
const char* scale_flag_str = cvReadString( find_timing_param( "scale" ), "scale==1" );
if( strstr( scale_flag_str, "==1" ) )
alpha.val[0] = 1.;
else
{
double val = alpha.val[0];
int depth = CV_MAT_DEPTH(types[INPUT][0]);
if( val == 1. )
val = 1./CV_PI;
if( depth == CV_16U || depth == CV_16S || depth == CV_32S )
{
double minmax = 1./cvTsMaxVal(depth);
if( val < -minmax )
val = -minmax;
else if( val > minmax )
val = minmax;
if( depth == CV_16U && val < 0 )
val = -val;
}
alpha.val[0] = val;
ts->printf( CvTS::LOG, "alpha = %g\n", alpha.val[0] );
}
}
void CxCore_MulTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
sprintf( ptr, "%s,", alpha.val[0] == 1. ? "scale==1" : "scale!=1" );
ptr += strlen(ptr);
params_left--;
CxCore_ArithmTest::print_timing_params( test_case_idx, ptr, params_left );
}
double CxCore_MulTest::get_success_error_level( int test_case_idx, int i, int j )
{
if( CV_MAT_DEPTH(cvGetElemType(test_array[i][j])) <= CV_32S )
{
return gamma.val[0] != cvRound(gamma.val[0]);
}
else
return CvArrTest::get_success_error_level( test_case_idx, i, j );
}
void CxCore_MulTest::run_func()
{
if(!test_nd)
{
cvMul( test_array[INPUT][0], test_array[INPUT][1],
test_array[OUTPUT][0], alpha.val[0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::multiply(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]),
c, alpha.val[0]);
}
}
void CxCore_MulTest::prepare_to_validation( int /*test_case_idx*/ )
{
cvTsMul( &test_mat[INPUT][0], &test_mat[INPUT][1],
cvScalarAll(alpha.val[0]),
&test_mat[REF_OUTPUT][0] );
}
CxCore_MulTest mul_test;
////////////////////////////// div /////////////////////////////
class CxCore_DivTest : public CxCore_ArithmTest
{
public:
CxCore_DivTest();
protected:
void run_func();
void print_timing_params( int test_case_idx, char* ptr, int params_left );
void prepare_to_validation( int /*test_case_idx*/ );
};
CxCore_DivTest::CxCore_DivTest()
: CxCore_ArithmTest( "arithm-div", "cvDiv", 4, false, false )
{
}
void CxCore_DivTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
sprintf( ptr, "s*A(i)/B(i)," );
ptr += strlen(ptr);
params_left--;
CxCore_ArithmTest::print_timing_params( test_case_idx, ptr, params_left );
}
void CxCore_DivTest::run_func()
{
if(!test_nd)
{
cvDiv( test_array[INPUT][0], test_array[INPUT][1],
test_array[OUTPUT][0], alpha.val[0] );
}
else
{
cv::MatND b = cv::cvarrToMatND(test_array[INPUT][1]);
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::divide(cv::cvarrToMatND(test_array[INPUT][0]),
b, c, alpha.val[0]);
}
}
void CxCore_DivTest::prepare_to_validation( int /*test_case_idx*/ )
{
cvTsDiv( &test_mat[INPUT][0], &test_mat[INPUT][1],
cvScalarAll(alpha.val[0]),
&test_mat[REF_OUTPUT][0] );
}
CxCore_DivTest div_test;
////////////////////////////// recip /////////////////////////////
class CxCore_RecipTest : public CxCore_ArithmTest
{
public:
CxCore_RecipTest();
protected:
void run_func();
void print_timing_params( int test_case_idx, char* ptr, int params_left );
void prepare_to_validation( int /*test_case_idx*/ );
};
CxCore_RecipTest::CxCore_RecipTest()
: CxCore_ArithmTest( "arithm-recip", "cvDiv", 4, false, false )
{
test_array[INPUT].pop();
}
void CxCore_RecipTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
sprintf( ptr, "s/B(i)," );
ptr += strlen(ptr);
params_left--;
CxCore_ArithmTest::print_timing_params( test_case_idx, ptr, params_left );
}
void CxCore_RecipTest::run_func()
{
if(!test_nd)
{
cvDiv( 0, test_array[INPUT][0],
test_array[OUTPUT][0], gamma.val[0] );
}
else
{
cv::MatND b = cv::cvarrToMatND(test_array[INPUT][0]);
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::divide(gamma.val[0], b, c);
}
}
void CxCore_RecipTest::prepare_to_validation( int /*test_case_idx*/ )
{
cvTsDiv( 0, &test_mat[INPUT][0],
cvScalarAll(gamma.val[0]),
&test_mat[REF_OUTPUT][0] );
}
CxCore_RecipTest recip_test;
///////////////// matrix copy/initializing/permutations /////////////////////
class CxCore_MemTestImpl : public CxCore_ArithmTestImpl
{
public:
CxCore_MemTestImpl( const char* test_name, const char* test_funcs,
int _generate_scalars=0, bool _allow_mask=true );
protected:
double get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ );
};
CxCore_MemTestImpl::CxCore_MemTestImpl( const char* test_name, const char* test_funcs,
int _generate_scalars, bool _allow_mask ) :
CxCore_ArithmTestImpl( test_name, test_funcs, _generate_scalars, _allow_mask, false )
{
}
double CxCore_MemTestImpl::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
return 0;
}
CxCore_MemTestImpl mem_test( "mem", "", 0, false );
class CxCore_MemTest : public CxCore_MemTestImpl
{
public:
CxCore_MemTest( const char* test_name, const char* test_funcs,
int _generate_scalars=0, bool _allow_mask=true );
};
CxCore_MemTest::CxCore_MemTest( const char* test_name, const char* test_funcs,
int _generate_scalars, bool _allow_mask ) :
CxCore_MemTestImpl( test_name, test_funcs, _generate_scalars, _allow_mask )
{
default_timing_param_names = optional_mask ? arithm_mask_param_names : arithm_param_names;
// inherit the default parameters from arithmerical test
size_list = 0;
whole_size_list = 0;
depth_list = 0;
cn_list = 0;
}
///////////////// setidentity /////////////////////
class CxCore_SetIdentityTest : public CxCore_MemTest
{
public:
CxCore_SetIdentityTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
};
CxCore_SetIdentityTest::CxCore_SetIdentityTest() :
CxCore_MemTest( "mem-setidentity", "cvSetIdentity", 4, false )
{
test_array[INPUT].clear();
}
void CxCore_SetIdentityTest::run_func()
{
if(!test_nd)
cvSetIdentity(test_array[OUTPUT][0], gamma);
else
{
cv::Mat a = cv::cvarrToMat(test_array[OUTPUT][0]);
cv::setIdentity(a, gamma);
}
}
void CxCore_SetIdentityTest::prepare_to_validation( int )
{
cvTsSetIdentity( &test_mat[REF_OUTPUT][0], gamma );
}
CxCore_SetIdentityTest setidentity_test;
///////////////// SetZero /////////////////////
class CxCore_SetZeroTest : public CxCore_MemTest
{
public:
CxCore_SetZeroTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
};
CxCore_SetZeroTest::CxCore_SetZeroTest() :
CxCore_MemTest( "mem-setzero", "cvSetZero", 0, false )
{
test_array[INPUT].clear();
}
void CxCore_SetZeroTest::run_func()
{
if(!test_nd)
cvSetZero(test_array[OUTPUT][0]);
else
{
cv::MatND a = cv::cvarrToMatND(test_array[OUTPUT][0]);
a.setTo(cv::Scalar());
}
}
void CxCore_SetZeroTest::prepare_to_validation( int )
{
cvTsZero( &test_mat[REF_OUTPUT][0] );
}
CxCore_SetZeroTest setzero_test;
///////////////// Set /////////////////////
class CxCore_FillTest : public CxCore_MemTest
{
public:
CxCore_FillTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
};
CxCore_FillTest::CxCore_FillTest() :
CxCore_MemTest( "mem-fill", "cvSet", 4, true )
{
test_array[INPUT].clear();
}
void CxCore_FillTest::run_func()
{
const CvArr* mask = test_array[MASK][0];
if(!test_nd)
cvSet(test_array[INPUT_OUTPUT][0], gamma, mask);
else
{
cv::MatND a = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
a.setTo(gamma, mask ? cv::cvarrToMatND(mask) : cv::MatND());
}
}
void CxCore_FillTest::prepare_to_validation( int )
{
if( test_array[MASK][0] )
{
cvTsAdd( 0, cvScalarAll(0.), 0, cvScalarAll(0.), gamma, &test_mat[TEMP][0], 0 );
cvTsCopy( &test_mat[TEMP][0], &test_mat[REF_INPUT_OUTPUT][0], &test_mat[MASK][0] );
}
else
{
cvTsAdd( 0, cvScalarAll(0.), 0, cvScalarAll(0.), gamma, &test_mat[REF_INPUT_OUTPUT][0], 0 );
}
}
CxCore_FillTest fill_test;
///////////////// Copy /////////////////////
class CxCore_CopyTest : public CxCore_MemTest
{
public:
CxCore_CopyTest();
protected:
double get_success_error_level( int test_case_idx, int i, int j );
void run_func();
void prepare_to_validation( int test_case_idx );
};
CxCore_CopyTest::CxCore_CopyTest() :
CxCore_MemTest( "mem-copy", "cvCopy", 0, true )
{
test_array[INPUT].pop();
}
double CxCore_CopyTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
return 0;
}
void CxCore_CopyTest::run_func()
{
const CvArr* mask = test_array[MASK][0];
if(!test_nd)
cvCopy(test_array[INPUT][0], test_array[INPUT_OUTPUT][0], mask);
else
{
cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
if(!mask)
a.copyTo(c);
else
a.copyTo(c, cv::cvarrToMatND(mask));
}
}
void CxCore_CopyTest::prepare_to_validation( int )
{
cvTsCopy( &test_mat[INPUT][0], &test_mat[REF_INPUT_OUTPUT][0],
test_array[MASK].size() > 0 && test_array[MASK][0] ? &test_mat[MASK][0] : 0 );
}
CxCore_CopyTest copy_test;
///////////////// Transpose /////////////////////
class CxCore_TransposeTest : public CxCore_MemTest
{
public:
CxCore_TransposeTest();
protected:
void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
void get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images );
int prepare_test_case( int test_case_idx );
void run_func();
void prepare_to_validation( int test_case_idx );
bool inplace;
};
CxCore_TransposeTest::CxCore_TransposeTest() :
CxCore_MemTest( "mem-transpose", "cvTranspose", 0, false ), inplace(false)
{
test_array[INPUT].pop();
}
void CxCore_TransposeTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
{
int bits = cvTsRandInt(ts->get_rng());
CxCore_MemTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
inplace = false;
if( bits & 1 )
{
sizes[INPUT][0].height = sizes[INPUT][0].width;
inplace = (bits & 2) != 0;
}
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(sizes[INPUT][0].height, sizes[INPUT][0].width );
}
void CxCore_TransposeTest::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
{
CxCore_MemTest::get_timing_test_array_types_and_sizes( test_case_idx,
sizes, types, whole_sizes, are_images );
CvSize size = sizes[INPUT][0];
if( size.width != size.height )
{
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] =
whole_sizes[OUTPUT][0] = whole_sizes[REF_OUTPUT][0] = cvSize(size.height,size.width);
}
}
int CxCore_TransposeTest::prepare_test_case( int test_case_idx )
{
int code = CxCore_MemTest::prepare_test_case( test_case_idx );
if( inplace && code > 0 )
cvTsCopy( &test_mat[INPUT][0], &test_mat[OUTPUT][0] );
return code;
}
void CxCore_TransposeTest::run_func()
{
cvTranspose( inplace ? test_array[OUTPUT][0] : test_array[INPUT][0], test_array[OUTPUT][0]);
}
void CxCore_TransposeTest::prepare_to_validation( int )
{
cvTsTranspose( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0] );
}
CxCore_TransposeTest transpose_test;
///////////////// Flip /////////////////////
static const int flip_codes[] = { 0, 1, -1, INT_MIN };
static const char* flip_strings[] = { "center", "vert", "horiz", 0 };
static const char* flip_param_names[] = { "size", "flip_op", "channels", "depth", 0 };
class CxCore_FlipTest : public CxCore_MemTest
{
public:
CxCore_FlipTest();
protected:
void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
void get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images );
int prepare_test_case( int test_case_idx );
void print_timing_params( int test_case_idx, char* ptr, int params_left );
void run_func();
void prepare_to_validation( int test_case_idx );
int write_default_params( CvFileStorage* fs );
int flip_type;
bool inplace;
};
CxCore_FlipTest::CxCore_FlipTest() :
CxCore_MemTest( "mem-flip", "cvFlip", 0, false ), flip_type(0), inplace(false)
{
test_array[INPUT].pop();
default_timing_param_names = flip_param_names;
}
int CxCore_FlipTest::write_default_params( CvFileStorage* fs )
{
int i, code = CxCore_MemTest::write_default_params(fs);
if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
return code;
start_write_param( fs );
cvStartWriteStruct( fs, "flip_op", CV_NODE_SEQ + CV_NODE_FLOW );
for( i = 0; flip_codes[i] != INT_MIN; i++ )
cvWriteString( fs, 0, flip_strings[flip_codes[i]+1] );
cvEndWriteStruct(fs);
return code;
}
void CxCore_FlipTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
{
int bits = cvTsRandInt(ts->get_rng());
CxCore_MemTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
flip_type = (bits & 3) - 2;
flip_type += flip_type == -2;
inplace = (bits & 4) != 0;
}
void CxCore_FlipTest::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images )
{
CxCore_MemTest::get_timing_test_array_types_and_sizes( test_case_idx,
sizes, types, whole_sizes, are_images );
const char* flip_op_str = cvReadString( find_timing_param( "flip_op" ), "center" );
if( strcmp( flip_op_str, "vert" ) == 0 )
flip_type = 0;
else if( strcmp( flip_op_str, "horiz" ) == 0 )
flip_type = 1;
else
flip_type = -1;
}
void CxCore_FlipTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
sprintf( ptr, "%s,", flip_type > 0 ? "horiz" : flip_type < 0 ? "center" : "vert" );
ptr += strlen(ptr);
params_left--;
CxCore_MemTest::print_timing_params( test_case_idx, ptr, params_left );
}
int CxCore_FlipTest::prepare_test_case( int test_case_idx )
{
int code = CxCore_MemTest::prepare_test_case( test_case_idx );
if( inplace && code > 0 )
cvTsCopy( &test_mat[INPUT][0], &test_mat[OUTPUT][0] );
return code;
}
void CxCore_FlipTest::run_func()
{
cvFlip(inplace ? test_array[OUTPUT][0] : test_array[INPUT][0], test_array[OUTPUT][0], flip_type);
}
void CxCore_FlipTest::prepare_to_validation( int )
{
cvTsFlip( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0], flip_type );
}
CxCore_FlipTest flip_test;
///////////////// Split/Merge /////////////////////
static const char* split_merge_types[] = { "all", "single", 0 };
static int split_merge_channels[] = { 2, 3, 4, -1 };
static const char* split_merge_param_names[] = { "size", "planes", "channels", "depth", 0 };
class CxCore_SplitMergeBaseTest : public CxCore_MemTest
{
public:
CxCore_SplitMergeBaseTest( const char* test_name, const char* test_funcs, int _is_split );
protected:
void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
void get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images );
int prepare_test_case( int test_case_idx );
void print_timing_params( int test_case_idx, char* ptr, int params_left );
void prepare_to_validation( int test_case_idx );
int write_default_params( CvFileStorage* fs );
bool are_images;
int is_split, coi;
void* hdrs[4];
};
CxCore_SplitMergeBaseTest::CxCore_SplitMergeBaseTest( const char* test_name,
const char* test_funcs, int _is_split )
: CxCore_MemTest( test_name, test_funcs, 0, false ), are_images(false), is_split(_is_split), coi(0)
{
test_array[INPUT].pop();
if( is_split )
;
else
{
test_array[OUTPUT].clear();
test_array[REF_OUTPUT].clear();
test_array[INPUT_OUTPUT].push(NULL);
test_array[REF_INPUT_OUTPUT].push(NULL);
}
memset( hdrs, 0, sizeof(hdrs) );
default_timing_param_names = split_merge_param_names;
cn_list = split_merge_channels;
}
int CxCore_SplitMergeBaseTest::write_default_params( CvFileStorage* fs )
{
int code = CxCore_MemTest::write_default_params(fs);
if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
return code;
write_string_list( fs, "planes", split_merge_types );
return code;
}
void CxCore_SplitMergeBaseTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
{
int cn, depth;
CvRNG* rng = ts->get_rng();
CxCore_MemTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
cn = cvTsRandInt(rng)%3 + 2;
depth = CV_MAT_DEPTH(types[INPUT][0]);
if( is_split )
{
types[INPUT][0] = CV_MAKETYPE(depth, cn);
types[OUTPUT][0] = types[REF_OUTPUT][0] = depth;
}
else
{
types[INPUT][0] = depth;
types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(depth, cn);
}
if( (cvTsRandInt(rng) & 3) != 0 )
{
coi = cvTsRandInt(rng) % cn;
}
else
{
CvSize size = sizes[INPUT][0];
size.height *= cn;
if( is_split )
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = size;
else
sizes[INPUT][0] = size;
coi = -1;
}
are_images = cvTsRandInt(rng)%2 != 0;
}
void CxCore_SplitMergeBaseTest::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types, CvSize** whole_sizes, bool* _are_images )
{
CxCore_MemTest::get_timing_test_array_types_and_sizes( test_case_idx,
sizes, types, whole_sizes, _are_images );
const char* split_merge_type = cvReadString( find_timing_param( "planes" ), "all" );
int type0 = types[INPUT][0];
int depth = CV_MAT_DEPTH(type0);
int cn = CV_MAT_CN(type0);
CvSize size = sizes[INPUT][0];
if( strcmp( split_merge_type, "single" ) == 0 )
coi = cvTsRandInt(ts->get_rng()) % cn;
else
{
coi = -1;
size.height *= cn;
}
if( is_split )
{
types[OUTPUT][0] = types[REF_OUTPUT][0] = depth;
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = size;
// planes are put into separate arrays, not ROI's
whole_sizes[OUTPUT][0] = whole_sizes[REF_OUTPUT][0] = size;
}
else
{
types[INPUT][0] = depth;
sizes[INPUT][0] = size;
// planes are put into separate arrays, not ROI's
whole_sizes[INPUT][0] = size;
}
are_images = false;
}
void CxCore_SplitMergeBaseTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
int i;
sprintf( ptr, "%s,", coi >= 0 ? "single" : "all" );
ptr += strlen(ptr);
params_left--;
// at once, delete the headers, though is not very good from structural point of view ...
for( i = 0; i < 4; i++ )
cvRelease( &hdrs[i] );
CxCore_MemTest::print_timing_params( test_case_idx, ptr, params_left );
}
int CxCore_SplitMergeBaseTest::prepare_test_case( int test_case_idx )
{
int code = CxCore_MemTest::prepare_test_case( test_case_idx );
if( code > 0 )
{
CvMat* input = &test_mat[INPUT][0];
CvMat* output = &test_mat[is_split ? OUTPUT : INPUT_OUTPUT][0];
CvMat* merged = is_split ? input : output;
CvMat* planes = is_split ? output : input;
int depth = CV_MAT_DEPTH(merged->type);
int i, cn = CV_MAT_CN(merged->type), y = 0;
CvSize sz = cvGetMatSize(merged);
for( i = 0; i < cn; i++ )
{
if( coi < 0 || coi == i )
{
if( are_images )
hdrs[i] = cvCreateImageHeader( sz, cvIplDepth(depth), 1 );
else
hdrs[i] = cvCreateMatHeader( sz.height, sz.width, depth );
cvSetData( hdrs[i], planes->data.ptr + planes->step*y, planes->step );
y += sz.height;
}
}
}
return code;
}
void CxCore_SplitMergeBaseTest::prepare_to_validation( int )
{
CvMat* input = &test_mat[INPUT][0];
CvMat* output = &test_mat[is_split ? REF_OUTPUT : REF_INPUT_OUTPUT][0];
CvMat* merged = is_split ? input : output;
CvMat* planes = is_split ? output : input;
int i, cn = CV_MAT_CN(merged->type), y = 0;
CvSize sz = cvGetSize(merged);
for( i = 0; i < cn; i++ )
{
if( coi < 0 || coi == i )
{
CvMat stub, *h;
cvSetData( hdrs[i], planes->data.ptr + planes->step*y, planes->step );
h = cvGetMat( hdrs[i], &stub );
if( is_split )
cvTsExtract( input, h, i );
else
cvTsInsert( h, output, i );
cvSetData( hdrs[i], 0, 0 );
cvRelease( &hdrs[i] );
y += sz.height;
}
}
}
class CxCore_SplitTest : public CxCore_SplitMergeBaseTest
{
public:
CxCore_SplitTest();
protected:
void run_func();
};
CxCore_SplitTest::CxCore_SplitTest() :
CxCore_SplitMergeBaseTest( "mem-split", "cvSplit", 1 )
{
}
void CxCore_SplitTest::run_func()
{
int i, nz = (hdrs[0] != 0) + (hdrs[1] != 0) + (hdrs[2] != 0) + (hdrs[3] != 0);
if(!test_nd || nz != CV_MAT_CN(test_mat[INPUT][0].type))
cvSplit( test_array[INPUT][0], hdrs[0], hdrs[1], hdrs[2], hdrs[3] );
else
{
cv::MatND _hdrs[4];
for( i = 0; i < nz; i++ )
_hdrs[i] = cv::cvarrToMatND(hdrs[i]);
cv::split(cv::cvarrToMatND(test_array[INPUT][0]), _hdrs);
}
}
CxCore_SplitTest split_test;
class CxCore_MergeTest : public CxCore_SplitMergeBaseTest
{
public:
CxCore_MergeTest();
protected:
void run_func();
};
CxCore_MergeTest::CxCore_MergeTest() :
CxCore_SplitMergeBaseTest( "mem-merge", "cvMerge", 0 )
{
}
void CxCore_MergeTest::run_func()
{
int i, nz = (hdrs[0] != 0) + (hdrs[1] != 0) + (hdrs[2] != 0) + (hdrs[3] != 0);
if(!test_nd || nz != CV_MAT_CN(test_mat[INPUT_OUTPUT][0].type))
cvMerge( hdrs[0], hdrs[1], hdrs[2], hdrs[3], test_array[INPUT_OUTPUT][0] );
else
{
cv::MatND _hdrs[4], dst = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
for( i = 0; i < nz; i++ )
_hdrs[i] = cv::cvarrToMatND(hdrs[i]);
cv::merge(_hdrs, nz, dst);
}
}
CxCore_MergeTest merge_test;
///////////////// CompleteSymm /////////////////////
class CxCore_CompleteSymm : public CvArrTest
{
public:
CxCore_CompleteSymm();
protected:
void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
int prepare_test_case( int test_case_idx );
void run_func();
void prepare_to_validation( int test_case_idx );
int LtoR; //flags
};
CxCore_CompleteSymm::CxCore_CompleteSymm() :
CvArrTest("matrix-symm", "cvCompleteSymm", "Test of cvCompleteSymm function")
{
/*Generates 1 input and 1 outputs (by default we have 2 inputs and 1 output)*/
test_array[INPUT].clear();
test_array[INPUT].push(NULL);
test_array[OUTPUT].clear();
test_array[OUTPUT].push(NULL);
test_array[REF_OUTPUT].clear();
test_array[REF_OUTPUT].push(NULL);
}
void CxCore_CompleteSymm::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
{
CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
sizes[INPUT][0] =sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(sizes[INPUT][0].height, sizes[INPUT][0].height );
/*Making input and output matrixes one-channel*/
int type;
switch (test_case_idx % 3)
{
case 0:
type = CV_32FC1;
break;
case 1:
type = CV_32SC1;
break;
default:
type = CV_64FC1;
}
types[OUTPUT][0] = types[INPUT][0] = types[REF_OUTPUT][0] = type;
}
int CxCore_CompleteSymm::prepare_test_case( int test_case_idx )
{
int code = CvArrTest::prepare_test_case( test_case_idx );
if (code)
{
CvRNG* rng = ts->get_rng();
unsigned val = cvRandInt(rng);
LtoR = val % 2;
cvConvert(&test_mat[INPUT][0], &test_mat[OUTPUT][0]);
}
return code;
}
void CxCore_CompleteSymm::run_func()
{
cvCompleteSymm(&test_mat[OUTPUT][0],LtoR);
}
void CxCore_CompleteSymm::prepare_to_validation( int )
{
CvMat* ref_output = cvCreateMat(test_mat[OUTPUT][0].rows, test_mat[OUTPUT][0].cols, CV_64F);
CvMat* input = cvCreateMat(test_mat[INPUT][0].rows, test_mat[INPUT][0].cols, CV_64F);
cvConvert(&test_mat[INPUT][0], input);
for (int i=0;i<input->rows;i++)
{
ref_output->data.db[i*input->cols+i]=input->data.db[i*input->cols+i];
if (LtoR)
{
for (int j=0;j<i;j++)
{
ref_output->data.db[j*input->cols+i] = ref_output->data.db[i*input->cols+j]=input->data.db[i*input->cols+j];
}
}
else
{
for (int j=0;j<i;j++)
{
ref_output->data.db[j*input->cols+i] = ref_output->data.db[i*input->cols+j]=input->data.db[j*input->cols+i];
}
}
}
cvConvert(ref_output, &test_mat[REF_OUTPUT][0]);
cvReleaseMat(&input);
cvReleaseMat(&ref_output);
}
CxCore_CompleteSymm complete_symm;
////////////////////////////// Sort /////////////////////////////////
class CxCore_SortTest : public CxCore_MemTest
{
public:
CxCore_SortTest();
protected:
void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
int prepare_test_case( int test_case_idx );
void run_func();
void prepare_to_validation( int test_case_idx );
int flags; //flags for sorting
private:
static int compareIndexes (const void * a, const void * b); // comparing two elements of the matrix with pointers sorting
static int compare(const void * a, const void * b); // comparing two elements of the matrix with pointers sorting
bool useIndexMatrix;
bool useInPlaceSort;
CvMat* input;
};
CxCore_SortTest::CxCore_SortTest() :
CxCore_MemTest( "matrix-sort", "cvSort", 0, false )
{
/*Generates 1 input and 2 outputs (by default we have 2 inputs and 1 output)*/
test_array[INPUT].clear();
test_array[INPUT].push(NULL);
test_array[OUTPUT].push(NULL);
test_array[REF_OUTPUT].push(NULL);
}
void CxCore_SortTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
{
CxCore_MemTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = cvSize(sizes[INPUT][0].height, sizes[INPUT][0].width );
types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_32SC1;
/*Making input and output matrixes one-channel*/
types[OUTPUT][0] = types[INPUT][0] = CV_MAKETYPE(CV_MAT_DEPTH(types[INPUT][0]), 1);
types[REF_OUTPUT][0] = CV_MAKETYPE(CV_MAT_DEPTH(types[REF_OUTPUT][0]), 1);
}
int CxCore_SortTest::prepare_test_case( int test_case_idx )
{
if (test_case_idx==0)
{
useIndexMatrix=true;
useInPlaceSort=false;
}
int code = CxCore_MemTest::prepare_test_case( test_case_idx );
if( code > 0 )
{
//Copying input data
input = cvCreateMat(test_mat[INPUT][0].rows, test_mat[INPUT][0].cols, CV_64F);
cvConvert(&test_mat[INPUT][0], input);
CvRNG* rng = ts->get_rng();
unsigned val = cvRandInt(rng);
// Setting up flags
switch (val%4)
{
case 0:
flags = CV_SORT_EVERY_ROW + CV_SORT_DESCENDING;
break;
case 1:
flags = CV_SORT_EVERY_ROW + CV_SORT_ASCENDING;
break;
case 2:
flags = CV_SORT_EVERY_COLUMN + CV_SORT_DESCENDING;
break;
case 3:
flags = CV_SORT_EVERY_COLUMN + CV_SORT_ASCENDING;
break;
}
if (val%3)
useIndexMatrix = !useIndexMatrix;
if (val%5)
useInPlaceSort = !useInPlaceSort;
}
return code;
}
void CxCore_SortTest::run_func()
{
//test_mat[OUTPUT][0] is sorted matrix
//test_mat[OUTPUT][1] is index matrix
if (useInPlaceSort)
{
cvConvert(&test_mat[INPUT][0], &test_mat[OUTPUT][0]);
if (useIndexMatrix)
cvSort(&(test_mat[OUTPUT][0]),&(test_mat[OUTPUT][0]),&(test_mat[OUTPUT][1]),flags);
else
{
cvSort(&(test_mat[OUTPUT][0]),&(test_mat[OUTPUT][0]),0,flags);
}
}
else
{
if (useIndexMatrix)
cvSort(&(test_mat[INPUT][0]),&(test_mat[OUTPUT][0]),&(test_mat[OUTPUT][1]),flags);
else
{
cvSort(&(test_mat[INPUT][0]),&(test_mat[OUTPUT][0]),0,flags);
}
}
}
int CxCore_SortTest::compareIndexes (const void * a, const void * b)
{
double zero = 1e-30;
double res=(**((double**)a)-**((double**)b));
return res<-zero?-1:(res>zero?1:0);
}
int CxCore_SortTest::compare (const void * a, const void * b)
{
return *((int*)a)-*((int*)b);
}
void CxCore_SortTest::prepare_to_validation(int)
{
/*Creating matrixes copies to work with*/
CvMat* ref_indexes = cvCreateMat(test_mat[REF_OUTPUT][1].rows, test_mat[REF_OUTPUT][1].cols, CV_32SC1);
CvMat* indexes = cvCreateMat(test_mat[OUTPUT][1].rows, test_mat[OUTPUT][1].cols, CV_32SC1);
CvMat* ref_output = cvCreateMat(test_mat[OUTPUT][0].rows, test_mat[OUTPUT][0].cols,CV_64F);
/*Copying data*/
cvConvert(&test_mat[REF_OUTPUT][1], ref_indexes);
cvConvert(&test_mat[OUTPUT][1], indexes);
/*Following block generates REF_OUTPUT indexes matrix*/
if ((flags == (CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)) ||(flags == (CV_SORT_EVERY_ROW+CV_SORT_DESCENDING)))
for (int i=0;i<test_mat[REF_OUTPUT][1].rows;i++)
for (int j=0;j<test_mat[REF_OUTPUT][1].cols;j++)
ref_indexes->data.i[ref_indexes->cols*i + j]=j;
else
for (int i=0;i<test_mat[REF_OUTPUT][1].rows;i++)
for (int j=0;j<test_mat[REF_OUTPUT][1].cols;j++)
ref_indexes->data.i[ref_indexes->cols*i + j]=i;
cvConvert(ref_indexes, &test_mat[REF_OUTPUT][1]);
/*End of block*/
/* Matrix User's Sorting Algorithm */
int order = -1; // order of sorting (ASCENDING or DESCENDING)
//// Following to variables are for sorting rows or cols in one block without any conditions (if statements)
short rowsSort=0;
short colsSort=0;
if ((flags == CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)||(flags == CV_SORT_EVERY_COLUMN+CV_SORT_ASCENDING)) order=1;
if ((flags == CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)||(flags == CV_SORT_EVERY_ROW+CV_SORT_DESCENDING)) rowsSort=1;
else colsSort=1;
int i,j;
// For accessing [i,j] element using index matrix we can use following formula
// input->data.db[(input->cols*i+ref_indexes->cols*i+j)*rowsSort+(cols*(ref_indexes->cols*i+j)+j)*colsSort];
if ((flags == CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)||(flags == CV_SORT_EVERY_ROW+CV_SORT_DESCENDING))
{
double** row = new double*[input->cols];
for (i=0;i<input->rows; i++)
{
for (int j=0;j<input->cols;j++)
row[j]=&(input->data.db[(input->cols*i+j)]);
qsort(row,input->cols,sizeof(row[0]),&CxCore_SortTest::compareIndexes);
for (int j=0;j<ref_indexes->cols;j++)
{
if (order==1)
ref_indexes->data.i[ref_indexes->cols*i+j]=(int)(row[j]-&(input->data.db[input->cols*i]));
else
ref_indexes->data.i[ref_indexes->cols*(i+1)-1-j]=(int)(row[j]-&(input->data.db[input->cols*i]));
}
}
delete[] row;
}
else
{
double** col = new double*[input->rows];
for (j=0;j<input->cols; j++)
{
for (int i=0;i<input->rows;i++)
col[i]=&(input->data.db[(input->cols*i+j)]);
qsort(col,input->rows,sizeof(col[0]),&CxCore_SortTest::compareIndexes);
for (int i=0;i<ref_indexes->rows;i++)
{
if (order==1)
ref_indexes->data.i[ref_indexes->cols*i+j]=(int)((col[i]-&(input->data.db[j]))/(ref_output->cols));
else
ref_indexes->data.i[ref_indexes->cols*(ref_indexes->rows-1-i)+j]=(int)(col[i]-&(input->data.db[j]))/(ref_output->cols);
}
}
delete[] col;
}
/*End of Sort*/
int n;
for (i=0;i<input->rows;i++)
for (j=0;j<input->cols;j++)
{
n=(input->cols*i+ref_indexes->data.i[ref_indexes->cols*i+j])*rowsSort+
(input->cols*(ref_indexes->data.i[ref_indexes->cols*i+j])+j)*colsSort;
ref_output->data.db[ref_output->cols*i+j] = input->data.db[n];
}
if (useIndexMatrix)
{
/* Comparing indexes matrixes */
if ((flags == CV_SORT_EVERY_ROW+CV_SORT_ASCENDING)||(flags == CV_SORT_EVERY_ROW+CV_SORT_DESCENDING))
{
int begin=0,end=0;
double temp;
for (i=0;i<indexes->rows;i++)
{
for (j=0;j<indexes->cols-1;j++)
if (ref_output->data.db[ref_output->cols*i+j]==ref_output->data.db[ref_output->cols*i+j+1])
{
temp=ref_output->data.db[ref_output->cols*i+j];
begin=j++;
while ((j<ref_output->cols)&&(temp==ref_output->data.db[ref_output->cols*i+j])) j++;
end=--j;
int* row = new int[end-begin+1];
int* row1 = new int[end-begin+1];
for (int k=0;k<=end-begin;k++)
{
row[k]=ref_indexes->data.i[ref_indexes->cols*i+k+begin];
row1[k]=indexes->data.i[indexes->cols*i+k+begin];
}
qsort(row,end-begin+1,sizeof(row[0]),&CxCore_SortTest::compare);
qsort(row1,end-begin+1,sizeof(row1[0]),&CxCore_SortTest::compare);
for (int k=0;k<=end-begin;k++)
{
ref_indexes->data.i[ref_indexes->cols*i+k+begin]=row[k];
indexes->data.i[indexes->cols*i+k+begin]=row1[k];
}
delete[] row;
delete[] row1;
}
}
}
else
{
int begin=0,end=0;
double temp;
for (j=0;j<indexes->cols;j++)
{
for (i=0;i<indexes->rows-1;i++)
if (ref_output->data.db[ref_output->cols*i+j]==ref_output->data.db[ref_output->cols*(i+1)+j])
{
temp=ref_output->data.db[ref_output->cols*i+j];
begin=i++;
while ((i<ref_output->rows)&&(temp==ref_output->data.db[ref_output->cols*i+j])) i++;
end=--i;
int* col = new int[end-begin+1];
int* col1 = new int[end-begin+1];
for (int k=0;k<=end-begin;k++)
{
col[k]=ref_indexes->data.i[ref_indexes->cols*(k+begin)+j];
col1[k]=indexes->data.i[indexes->cols*(k+begin)+j];
}
qsort(col,end-begin+1,sizeof(col[0]),&CxCore_SortTest::compare);
qsort(col1,end-begin+1,sizeof(col1[0]),&CxCore_SortTest::compare);
for (int k=0;k<=end-begin;k++)
{
ref_indexes->data.i[ref_indexes->cols*(k+begin)+j]=col[k];
indexes->data.i[indexes->cols*(k+begin)+j]=col1[k];
}
delete[] col;
delete[] col1;
}
}
}
/* End of compare*/
cvConvert(ref_indexes, &test_mat[REF_OUTPUT][1]);
cvConvert(indexes, &test_mat[OUTPUT][1]);
}
else
{
cvConvert(ref_indexes, &test_mat[REF_OUTPUT][1]);
cvConvert(ref_indexes, &test_mat[OUTPUT][1]);
}
cvConvert(ref_output, &test_mat[REF_OUTPUT][0]);
/*releasing matrixes*/
cvReleaseMat(&ref_output);
cvReleaseMat(&input);
cvReleaseMat(&indexes);
cvReleaseMat(&ref_indexes);
}
CxCore_SortTest sort_test;
////////////////////////////// min/max /////////////////////////////
class CxCore_MinMaxBaseTest : public CxCore_ArithmTest
{
public:
CxCore_MinMaxBaseTest( const char* test_name, const char* test_funcs,
int _op_type, int _generate_scalars=0 );
protected:
void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
double get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ );
void prepare_to_validation( int /*test_case_idx*/ );
int op_type;
};
CxCore_MinMaxBaseTest::CxCore_MinMaxBaseTest( const char* test_name, const char* test_funcs,
int _op_type, int _generate_scalars )
: CxCore_ArithmTest( test_name, test_funcs, _generate_scalars, false, false ), op_type(_op_type)
{
if( _generate_scalars )
test_array[INPUT].pop();
default_timing_param_names = minmax_param_names;
}
double CxCore_MinMaxBaseTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
return 0;
}
void CxCore_MinMaxBaseTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
{
int i, j;
CxCore_ArithmTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
for( i = 0; i < max_arr; i++ )
{
int count = test_array[i].size();
for( j = 0; j < count; j++ )
{
types[i][j] &= ~CV_MAT_CN_MASK;
}
}
}
void CxCore_MinMaxBaseTest::prepare_to_validation( int /*test_case_idx*/ )
{
if( !gen_scalars )
cvTsMinMax( &test_mat[INPUT][0], &test_mat[INPUT][1],
&test_mat[REF_OUTPUT][0], op_type );
else
cvTsMinMaxS( &test_mat[INPUT][0], gamma.val[0],
&test_mat[REF_OUTPUT][0], op_type );
}
class CxCore_MinTest : public CxCore_MinMaxBaseTest
{
public:
CxCore_MinTest();
protected:
void run_func();
};
CxCore_MinTest::CxCore_MinTest()
: CxCore_MinMaxBaseTest( "arithm-min", "cvMin", CV_TS_MIN, 0 )
{
}
void CxCore_MinTest::run_func()
{
if(!test_nd)
{
cvMin( test_array[INPUT][0], test_array[INPUT][1], test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::min(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]), c);
}
}
CxCore_MinTest min_test;
////////////////////////////// max /////////////////////////////
class CxCore_MaxTest : public CxCore_MinMaxBaseTest
{
public:
CxCore_MaxTest();
protected:
void run_func();
};
CxCore_MaxTest::CxCore_MaxTest()
: CxCore_MinMaxBaseTest( "arithm-max", "cvMax", CV_TS_MAX, 0 )
{
}
void CxCore_MaxTest::run_func()
{
if(!test_nd)
{
cvMax( test_array[INPUT][0], test_array[INPUT][1], test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::max(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]), c);
}
}
CxCore_MaxTest max_test;
////////////////////////////// mins /////////////////////////////
class CxCore_MinSTest : public CxCore_MinMaxBaseTest
{
public:
CxCore_MinSTest();
protected:
void run_func();
};
CxCore_MinSTest::CxCore_MinSTest()
: CxCore_MinMaxBaseTest( "arithm-mins", "cvMinS", CV_TS_MIN, 4 )
{
}
void CxCore_MinSTest::run_func()
{
if(!test_nd)
{
cvMinS( test_array[INPUT][0], gamma.val[0], test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::min(cv::cvarrToMatND(test_array[INPUT][0]),
gamma.val[0], c);
}
}
CxCore_MinSTest mins_test;
////////////////////////////// maxs /////////////////////////////
class CxCore_MaxSTest : public CxCore_MinMaxBaseTest
{
public:
CxCore_MaxSTest();
protected:
void run_func();
};
CxCore_MaxSTest::CxCore_MaxSTest()
: CxCore_MinMaxBaseTest( "arithm-maxs", "cvMaxS", CV_TS_MAX, 4 )
{
}
void CxCore_MaxSTest::run_func()
{
if(!test_nd)
{
cvMaxS( test_array[INPUT][0], gamma.val[0], test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::max(cv::cvarrToMatND(test_array[INPUT][0]),
gamma.val[0], c);
}
}
CxCore_MaxSTest maxs_test;
//////////////////////////////// logic ///////////////////////////////////////
class CxCore_LogicTestImpl : public CxCore_ArithmTestImpl
{
public:
CxCore_LogicTestImpl( const char* test_name, const char* test_funcs, int _logic_op,
int _generate_scalars=0, bool _allow_mask=true );
protected:
void prepare_to_validation( int test_case_idx );
int logic_op;
};
CxCore_LogicTestImpl::CxCore_LogicTestImpl( const char* test_name, const char* test_funcs,
int _logic_op, int _generate_scalars, bool _allow_mask )
: CxCore_ArithmTestImpl( test_name, test_funcs, _generate_scalars, _allow_mask, false ),
logic_op(_logic_op)
{
if( _generate_scalars )
test_array[INPUT].pop();
}
void CxCore_LogicTestImpl::prepare_to_validation( int /*test_case_idx*/ )
{
int ref_output_idx = optional_mask ? REF_INPUT_OUTPUT : REF_OUTPUT;
int output_idx = optional_mask ? INPUT_OUTPUT : OUTPUT;
const CvMat* mask = test_array[MASK].size() > 0 && test_array[MASK][0] ? &test_mat[MASK][0] : 0;
CvMat* dst = mask ? &test_mat[TEMP][0] : &test_mat[ref_output_idx][0];
int i;
if( test_array[INPUT].size() > 1 )
{
cvTsLogic( &test_mat[INPUT][0], &test_mat[INPUT][1], dst, logic_op );
}
else
{
cvTsLogicS( &test_mat[INPUT][0], gamma, dst, logic_op );
}
if( mask )
cvTsCopy( dst, &test_mat[ref_output_idx][0], mask );
for( i = 0; i < 2; i++ )
{
dst = i == 0 ? &test_mat[ref_output_idx][0] : &test_mat[output_idx][0];
if( CV_IS_MAT(dst) )
{
CvMat* mat = (CvMat*)dst;
mat->cols *= CV_ELEM_SIZE(mat->type);
mat->type = (mat->type & ~CV_MAT_TYPE_MASK) | CV_8UC1;
}
else
{
IplImage* img = (IplImage*)dst;
int elem_size;
assert( CV_IS_IMAGE(dst) );
elem_size = ((img->depth & 255)>>3)*img->nChannels;
img->width *= elem_size;
if( img->roi )
{
img->roi->xOffset *= elem_size;
img->roi->width *= elem_size;
}
img->depth = IPL_DEPTH_8U;
img->nChannels = 1;
}
}
}
CxCore_LogicTestImpl logic_test("logic", "", -1, 0, false );
class CxCore_LogicTest : public CxCore_LogicTestImpl
{
public:
CxCore_LogicTest( const char* test_name, const char* test_funcs, int _logic_op,
int _generate_scalars=0, bool _allow_mask=true );
};
CxCore_LogicTest::CxCore_LogicTest( const char* test_name, const char* test_funcs,
int _logic_op, int _generate_scalars, bool _allow_mask )
: CxCore_LogicTestImpl( test_name, test_funcs, _logic_op, _generate_scalars, _allow_mask )
{
default_timing_param_names = optional_mask ? arithm_mask_param_names : arithm_param_names;
// inherit the default parameters from arithmerical test
size_list = 0;
whole_size_list = 0;
depth_list = 0;
cn_list = 0;
}
///////////////////////// and //////////////////////////
class CxCore_AndTest : public CxCore_LogicTest
{
public:
CxCore_AndTest();
protected:
void run_func();
};
CxCore_AndTest::CxCore_AndTest()
: CxCore_LogicTest( "logic-and", "cvAnd", CV_TS_LOGIC_AND )
{
}
void CxCore_AndTest::run_func()
{
if(!test_nd)
{
cvAnd( test_array[INPUT][0], test_array[INPUT][1],
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
cv::bitwise_and(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]),
c, cv::cvarrToMatND(test_array[MASK][0]));
}
}
CxCore_AndTest and_test;
class CxCore_AndSTest : public CxCore_LogicTest
{
public:
CxCore_AndSTest();
protected:
void run_func();
};
CxCore_AndSTest::CxCore_AndSTest()
: CxCore_LogicTest( "logic-ands", "cvAndS", CV_TS_LOGIC_AND, 4 )
{
}
void CxCore_AndSTest::run_func()
{
if(!test_nd)
{
cvAndS( test_array[INPUT][0], gamma,
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
cv::bitwise_and(cv::cvarrToMatND(test_array[INPUT][0]),
gamma, c,
cv::cvarrToMatND(test_array[MASK][0]));
}
}
CxCore_AndSTest ands_test;
///////////////////////// or /////////////////////////
class CxCore_OrTest : public CxCore_LogicTest
{
public:
CxCore_OrTest();
protected:
void run_func();
};
CxCore_OrTest::CxCore_OrTest()
: CxCore_LogicTest( "logic-or", "cvOr", CV_TS_LOGIC_OR )
{
}
void CxCore_OrTest::run_func()
{
if(!test_nd)
{
cvOr( test_array[INPUT][0], test_array[INPUT][1],
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
cv::bitwise_or(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]),
c, cv::cvarrToMatND(test_array[MASK][0]));
}
}
CxCore_OrTest or_test;
class CxCore_OrSTest : public CxCore_LogicTest
{
public:
CxCore_OrSTest();
protected:
void run_func();
};
CxCore_OrSTest::CxCore_OrSTest()
: CxCore_LogicTest( "logic-ors", "cvOrS", CV_TS_LOGIC_OR, 4 )
{
}
void CxCore_OrSTest::run_func()
{
if(!test_nd)
{
cvOrS( test_array[INPUT][0], gamma,
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
cv::bitwise_or(cv::cvarrToMatND(test_array[INPUT][0]),
gamma, c,
cv::cvarrToMatND(test_array[MASK][0]));
}
}
CxCore_OrSTest ors_test;
////////////////////////// xor ////////////////////////////
class CxCore_XorTest : public CxCore_LogicTest
{
public:
CxCore_XorTest();
protected:
void run_func();
};
CxCore_XorTest::CxCore_XorTest()
: CxCore_LogicTest( "logic-xor", "cvXor", CV_TS_LOGIC_XOR )
{
}
void CxCore_XorTest::run_func()
{
if(!test_nd)
{
cvXor( test_array[INPUT][0], test_array[INPUT][1],
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
cv::bitwise_xor(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]),
c, cv::cvarrToMatND(test_array[MASK][0]));
}
}
CxCore_XorTest xor_test;
class CxCore_XorSTest : public CxCore_LogicTest
{
public:
CxCore_XorSTest();
protected:
void run_func();
};
CxCore_XorSTest::CxCore_XorSTest()
: CxCore_LogicTest( "logic-xors", "cvXorS", CV_TS_LOGIC_XOR, 4 )
{
}
void CxCore_XorSTest::run_func()
{
if(!test_nd)
{
cvXorS( test_array[INPUT][0], gamma,
test_array[INPUT_OUTPUT][0], test_array[MASK][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[INPUT_OUTPUT][0]);
cv::bitwise_xor(cv::cvarrToMatND(test_array[INPUT][0]),
gamma, c,
cv::cvarrToMatND(test_array[MASK][0]));
}
}
CxCore_XorSTest xors_test;
////////////////////////// not ////////////////////////////
class CxCore_NotTest : public CxCore_LogicTest
{
public:
CxCore_NotTest();
protected:
void run_func();
};
CxCore_NotTest::CxCore_NotTest()
: CxCore_LogicTest( "logic-not", "cvNot", CV_TS_LOGIC_NOT, 4, false )
{
}
void CxCore_NotTest::run_func()
{
if(!test_nd)
{
cvNot( test_array[INPUT][0], test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::bitwise_not(cv::cvarrToMatND(test_array[INPUT][0]), c);
}
}
CxCore_NotTest nots_test;
///////////////////////// cmp //////////////////////////////
static int cmp_op_values[] = { CV_CMP_GE, CV_CMP_EQ, CV_CMP_NE, -1 };
class CxCore_CmpBaseTestImpl : public CxCore_ArithmTestImpl
{
public:
CxCore_CmpBaseTestImpl( const char* test_name, const char* test_funcs,
int in_range, int _generate_scalars=0 );
protected:
double get_success_error_level( int test_case_idx, int i, int j );
void get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types );
void get_timing_test_array_types_and_sizes( int test_case_idx, CvSize** sizes,
int** types, CvSize** whole_sizes, bool* are_images );
void print_timing_params( int test_case_idx, char* ptr, int params_left );
void prepare_to_validation( int test_case_idx );
int write_default_params( CvFileStorage* fs );
int in_range;
int cmp_op;
enum { CMP_OP_COUNT=6 };
const char* cmp_op_strings[CMP_OP_COUNT];
};
CxCore_CmpBaseTestImpl::CxCore_CmpBaseTestImpl( const char* test_name, const char* test_funcs,
int _in_range, int _generate_scalars )
: CxCore_ArithmTestImpl( test_name, test_funcs, _generate_scalars, 0, 0 ), in_range(_in_range)
{
static const char* cmp_param_names[] = { "size", "cmp_op", "depth", 0 };
static const char* inrange_param_names[] = { "size", "channels", "depth", 0 };
if( in_range )
{
test_array[INPUT].push(NULL);
test_array[TEMP].push(NULL);
test_array[TEMP].push(NULL);
if( !gen_scalars )
test_array[TEMP].push(NULL);
}
if( gen_scalars )
test_array[INPUT].pop();
default_timing_param_names = in_range == 1 ? inrange_param_names : cmp_param_names;
cmp_op_strings[CV_CMP_EQ] = "eq";
cmp_op_strings[CV_CMP_LT] = "lt";
cmp_op_strings[CV_CMP_LE] = "le";
cmp_op_strings[CV_CMP_GE] = "ge";
cmp_op_strings[CV_CMP_GT] = "gt";
cmp_op_strings[CV_CMP_NE] = "ne";
cmp_op = -1;
}
double CxCore_CmpBaseTestImpl::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
return 0;
}
void CxCore_CmpBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
int j, count;
CxCore_ArithmTestImpl::get_test_array_types_and_sizes( test_case_idx, sizes, types );
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8UC1;
if( in_range == 0 )
{
// for cmp tests make all the input arrays single-channel
count = test_array[INPUT].size();
for( j = 0; j < count; j++ )
types[INPUT][j] &= ~CV_MAT_CN_MASK;
cmp_op = cvTsRandInt(ts->get_rng()) % 6; // == > >= < <= !=
}
else if( in_range == 1 )
{
types[TEMP][0] = CV_8UC1;
types[TEMP][1] &= ~CV_MAT_CN_MASK;
if( !gen_scalars )
types[TEMP][2] &= ~CV_MAT_CN_MASK;
}
}
int CxCore_CmpBaseTestImpl::write_default_params( CvFileStorage* fs )
{
int code = CxCore_ArithmTestImpl::write_default_params(fs);
if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
return code;
if( in_range == 0 )
{
start_write_param( fs );
int i;
cvStartWriteStruct( fs, "cmp_op", CV_NODE_SEQ + CV_NODE_FLOW );
for( i = 0; cmp_op_values[i] >= 0; i++ )
cvWriteString( fs, 0, cmp_op_strings[cmp_op_values[i]] );
cvEndWriteStruct(fs);
}
return code;
}
void CxCore_CmpBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images )
{
CxCore_ArithmTestImpl::get_timing_test_array_types_and_sizes( test_case_idx,
sizes, types, whole_sizes, are_images );
types[OUTPUT][0] = CV_8UC1;
if( in_range == 0 )
{
const char* cmp_op_str = cvReadString( find_timing_param( "cmp_op" ), "ge" );
int i;
cmp_op = CV_CMP_GE;
for( i = 0; i < CMP_OP_COUNT; i++ )
if( strcmp( cmp_op_str, cmp_op_strings[i] ) == 0 )
{
cmp_op = i;
break;
}
}
}
void CxCore_CmpBaseTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
if( in_range == 0 )
{
sprintf( ptr, "%s,", cmp_op_strings[cmp_op] );
ptr += strlen(ptr);
params_left--;
}
CxCore_ArithmTestImpl::print_timing_params( test_case_idx, ptr, params_left );
}
void CxCore_CmpBaseTestImpl::prepare_to_validation( int /*test_case_idx*/ )
{
CvMat* dst = &test_mat[REF_OUTPUT][0];
if( !in_range )
{
if( test_array[INPUT].size() > 1 )
{
cvTsCmp( &test_mat[INPUT][0], &test_mat[INPUT][1], dst, cmp_op );
}
else
{
cvTsCmpS( &test_mat[INPUT][0], gamma.val[0], dst, cmp_op );
}
}
else
{
int el_type = CV_MAT_TYPE( test_mat[INPUT][0].type );
int i, cn = CV_MAT_CN(el_type);
CvMat* tdst = dst;
for( i = 0; i < cn*2; i++ )
{
int coi = i / 2, is_lower = (i % 2) == 0;
int cmp_op = is_lower ? CV_CMP_GE : CV_CMP_LT;
const CvMat* src = &test_mat[INPUT][0];
const CvMat* lu = gen_scalars ? 0 : &test_mat[INPUT][is_lower?1:2];
double luS = is_lower ? alpha.val[coi] : gamma.val[coi];
if( cn > 1 )
{
cvTsExtract( src, &test_mat[TEMP][1], coi );
src = &test_mat[TEMP][1];
if( !gen_scalars )
{
cvTsExtract( lu, &test_mat[TEMP][2], coi );
lu = &test_mat[TEMP][2];
}
}
if( !gen_scalars )
cvTsCmp( src, lu, tdst, cmp_op );
else
cvTsCmpS( src, luS, tdst, cmp_op );
if( i > 0 )
cvTsLogic( tdst, dst, dst, CV_TS_LOGIC_AND );
tdst = &test_mat[TEMP][0];
}
}
}
CxCore_CmpBaseTestImpl cmpbase_test( "cmp", "", -1 );
class CxCore_CmpBaseTest : public CxCore_CmpBaseTestImpl
{
public:
CxCore_CmpBaseTest( const char* test_name, const char* test_funcs,
int in_range, int _generate_scalars=0 );
};
CxCore_CmpBaseTest::CxCore_CmpBaseTest( const char* test_name, const char* test_funcs,
int _in_range, int _generate_scalars )
: CxCore_CmpBaseTestImpl( test_name, test_funcs, _in_range, _generate_scalars )
{
// inherit the default parameters from arithmerical test
size_list = 0;
depth_list = 0;
cn_list = 0;
}
class CxCore_CmpTest : public CxCore_CmpBaseTest
{
public:
CxCore_CmpTest();
protected:
void run_func();
};
CxCore_CmpTest::CxCore_CmpTest()
: CxCore_CmpBaseTest( "cmp-cmp", "cvCmp", 0, 0 )
{
}
void CxCore_CmpTest::run_func()
{
if(!test_nd)
{
cvCmp( test_array[INPUT][0], test_array[INPUT][1],
test_array[OUTPUT][0], cmp_op );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::compare(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]),
c, cmp_op);
}
}
CxCore_CmpTest cmp_test;
class CxCore_CmpSTest : public CxCore_CmpBaseTest
{
public:
CxCore_CmpSTest();
protected:
void run_func();
};
CxCore_CmpSTest::CxCore_CmpSTest()
: CxCore_CmpBaseTest( "cmp-cmps", "cvCmpS", 0, 4 )
{
}
void CxCore_CmpSTest::run_func()
{
if(!test_nd)
{
cvCmpS( test_array[INPUT][0], gamma.val[0],
test_array[OUTPUT][0], cmp_op );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::compare(cv::cvarrToMatND(test_array[INPUT][0]),
gamma.val[0], c, cmp_op);
}
}
CxCore_CmpSTest cmps_test;
class CxCore_InRangeTest : public CxCore_CmpBaseTest
{
public:
CxCore_InRangeTest();
protected:
void run_func();
};
CxCore_InRangeTest::CxCore_InRangeTest()
: CxCore_CmpBaseTest( "cmp-inrange", "cvInRange", 1, 0 )
{
}
void CxCore_InRangeTest::run_func()
{
if(!test_nd)
{
cvInRange( test_array[INPUT][0], test_array[INPUT][1],
test_array[INPUT][2], test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::inRange(cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[INPUT][1]),
cv::cvarrToMatND(test_array[INPUT][2]),
c);
}
}
CxCore_InRangeTest inrange_test;
class CxCore_InRangeSTest : public CxCore_CmpBaseTest
{
public:
CxCore_InRangeSTest();
protected:
void run_func();
};
CxCore_InRangeSTest::CxCore_InRangeSTest()
: CxCore_CmpBaseTest( "cmp-inranges", "cvInRangeS", 1, 5 )
{
}
void CxCore_InRangeSTest::run_func()
{
if(!test_nd)
{
cvInRangeS( test_array[INPUT][0], alpha, gamma, test_array[OUTPUT][0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::inRange(cv::cvarrToMatND(test_array[INPUT][0]), alpha, gamma, c);
}
}
CxCore_InRangeSTest inranges_test;
/////////////////////////// convertscale[abs] ////////////////////////////////////////
static const char* cvt_param_names[] = { "size", "scale", "dst_depth", "depth", 0 };
static const char* cvt_abs_param_names[] = { "size", "depth", 0 };
static const int cvt_scale_flags[] = { 0, 1 };
class CxCore_CvtBaseTestImpl : public CxCore_ArithmTestImpl
{
public:
CxCore_CvtBaseTestImpl( const char* test_name, const char* test_funcs, bool calc_abs );
protected:
void get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types );
void get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool *are_images );
double get_success_error_level( int test_case_idx, int i, int j );
int prepare_test_case( int test_case_idx );
void print_timing_params( int test_case_idx, char* ptr, int params_left );
int write_default_params( CvFileStorage* fs );
void prepare_to_validation( int test_case_idx );
};
CxCore_CvtBaseTestImpl::CxCore_CvtBaseTestImpl( const char* test_name,
const char* test_funcs,
bool _calc_abs )
: CxCore_ArithmTestImpl( test_name, test_funcs, 5, false, _calc_abs )
{
test_array[INPUT].pop();
default_timing_param_names = 0;
cn_list = 0;
}
// unlike many other arithmetic functions, conversion operations support 8s type,
// also, for cvCvtScale output array depth may be arbitrary and
// for cvCvtScaleAbs output depth = CV_8U
void CxCore_CvtBaseTestImpl::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
CxCore_ArithmTestImpl::get_test_array_types_and_sizes( test_case_idx, sizes, types );
CvRNG* rng = ts->get_rng();
int depth = CV_8U, rbits;
types[INPUT][0] = (types[INPUT][0] & ~CV_MAT_DEPTH_MASK)|
cvTsRandInt(rng)%(CV_64F+1);
if( !calc_abs )
depth = cvTsRandInt(rng) % (CV_64F+1);
types[OUTPUT][0] = types[REF_OUTPUT][0] = (types[INPUT][0] & ~CV_MAT_DEPTH_MASK)|depth;
rbits = cvTsRandInt(rng);
// check special cases: shift=0 and/or scale=1.
if( (rbits & 3) == 0 )
gamma.val[0] = 0;
if( (rbits & 12) == 0 )
alpha.val[0] = 1;
}
double CxCore_CvtBaseTestImpl::get_success_error_level( int, int, int )
{
if( CV_MAT_DEPTH(test_mat[OUTPUT][0].type) <= CV_32S )
return alpha.val[0] != cvRound(alpha.val[0]) ||
beta.val[0] != cvRound(beta.val[0]) ||
gamma.val[0] != cvRound(gamma.val[0]);
CvScalar l1, h1, l2, h2;
int stype = CV_MAT_TYPE(test_mat[INPUT][0].type);
int dtype = CV_MAT_TYPE(test_mat[OUTPUT][0].type);
get_minmax_bounds( INPUT, 0, stype, &l1, &h1 );
get_minmax_bounds( OUTPUT, 0, dtype, &l2, &h2 );
double maxval = 0;
for( int i = 0; i < 4; i++ )
{
maxval = MAX(maxval, fabs(l1.val[i]));
maxval = MAX(maxval, fabs(h1.val[i]));
maxval = MAX(maxval, fabs(l2.val[i]));
maxval = MAX(maxval, fabs(h2.val[i]));
}
double max_err = (CV_MAT_DEPTH(stype) == CV_64F || CV_MAT_DEPTH(dtype) == CV_64F ?
DBL_EPSILON : FLT_EPSILON)*maxval*MAX(fabs(alpha.val[0]), 1.)*100;
return max_err;
}
void CxCore_CvtBaseTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
{
CxCore_ArithmTestImpl::get_timing_test_array_types_and_sizes( test_case_idx,
sizes, types, whole_sizes, are_images );
bool scale = true;
int dst_depth = CV_8U;
int cn = CV_MAT_CN(types[INPUT][0]);
if( !calc_abs )
{
scale = cvReadInt( find_timing_param( "scale" ), 1 ) != 0;
dst_depth = cvTsTypeByName( cvReadString(find_timing_param( "dst_depth" ), "8u") );
}
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(dst_depth, cn);
if( scale )
{
alpha.val[0] = 2.1;
gamma.val[0] = -100.;
}
else
{
alpha.val[0] = 1.;
gamma.val[0] = 0.;
}
}
int CxCore_CvtBaseTestImpl::prepare_test_case( int test_case_idx )
{
int code = CxCore_ArithmTestImpl::prepare_test_case( test_case_idx );
if( code > 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
{
if( CV_ARE_TYPES_EQ( &test_mat[INPUT][0], &test_mat[OUTPUT][0] ) &&
!calc_abs && alpha.val[0] == 1 && gamma.val[0] == 0 )
code = 0; // skip the case when no any transformation is done
}
return code;
}
void CxCore_CvtBaseTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
sprintf( ptr, "%s,", alpha.val[0] == 1. && gamma.val[0] == 0. ? "no_scale" : "scale" );
ptr += strlen(ptr);
params_left--;
CxCore_ArithmTestImpl::print_timing_params( test_case_idx, ptr, params_left );
}
int CxCore_CvtBaseTestImpl::write_default_params( CvFileStorage* fs )
{
int i, code = CxCore_ArithmTestImpl::write_default_params(fs);
if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
return code;
if( !calc_abs )
{
start_write_param( fs );
cvStartWriteStruct( fs, "dst_depth", CV_NODE_SEQ + CV_NODE_FLOW );
for( i = 0; arithm_depths[i] >= 0; i++ )
cvWriteString( fs, 0, cvTsGetTypeName(arithm_depths[i]) );
cvEndWriteStruct(fs);
write_int_list( fs, "scale", cvt_scale_flags, CV_DIM(cvt_scale_flags) );
}
return code;
}
void CxCore_CvtBaseTestImpl::prepare_to_validation( int /*test_case_idx*/ )
{
cvTsAdd( &test_mat[INPUT][0], cvScalarAll(alpha.val[0]), 0, beta,
cvScalarAll(gamma.val[0]), &test_mat[REF_OUTPUT][0], calc_abs );
}
CxCore_CvtBaseTestImpl cvt_test( "cvt", "", true );
class CxCore_CvtBaseTest : public CxCore_CvtBaseTestImpl
{
public:
CxCore_CvtBaseTest( const char* test_name, const char* test_funcs, bool calc_abs );
};
CxCore_CvtBaseTest::CxCore_CvtBaseTest( const char* test_name, const char* test_funcs, bool _calc_abs )
: CxCore_CvtBaseTestImpl( test_name, test_funcs, _calc_abs )
{
// inherit the default parameters from arithmerical test
size_list = 0;
whole_size_list = 0;
depth_list = 0;
cn_list = 0;
}
class CxCore_CvtScaleTest : public CxCore_CvtBaseTest
{
public:
CxCore_CvtScaleTest();
protected:
void run_func();
};
CxCore_CvtScaleTest::CxCore_CvtScaleTest()
: CxCore_CvtBaseTest( "cvt-scale", "cvCvtScale", false )
{
default_timing_param_names = cvt_param_names;
}
void CxCore_CvtScaleTest::run_func()
{
if(!test_nd)
{
cvConvertScale( test_array[INPUT][0], test_array[OUTPUT][0],
alpha.val[0], gamma.val[0] );
}
else
{
cv::MatND c = cv::cvarrToMatND(test_array[OUTPUT][0]);
cv::cvarrToMatND(test_array[INPUT][0]).convertTo(c,c.type(),alpha.val[0], gamma.val[0]);
}
}
CxCore_CvtScaleTest cvtscale_test;
class CxCore_CvtScaleAbsTest : public CxCore_CvtBaseTest
{
public:
CxCore_CvtScaleAbsTest();
protected:
void run_func();
};
CxCore_CvtScaleAbsTest::CxCore_CvtScaleAbsTest()
: CxCore_CvtBaseTest( "cvt-scaleabs", "cvCvtScaleAbs", true )
{
default_timing_param_names = cvt_abs_param_names;
}
void CxCore_CvtScaleAbsTest::run_func()
{
if(!test_nd)
{
cvConvertScaleAbs( test_array[INPUT][0], test_array[OUTPUT][0],
alpha.val[0], gamma.val[0] );
}
else
{
cv::Mat c = cv::cvarrToMat(test_array[OUTPUT][0]);
cv::convertScaleAbs(cv::cvarrToMat(test_array[INPUT][0]),c,alpha.val[0], gamma.val[0]);
}
}
CxCore_CvtScaleAbsTest cvtscaleabs_test;
/////////////////////////////// statistics //////////////////////////////////
static const char* stat_param_names[] = { "size", "coi", "channels", "depth", 0 };
static const char* stat_mask_param_names[] = { "size", "coi", "channels", "depth", "use_mask", 0 };
static const char* stat_single_param_names[] = { "size", "channels", "depth", 0 };
static const char* stat_single_mask_param_names[] = { "size", "channels", "depth", "use_mask", 0 };
static const char* stat_coi_modes[] = { "all", "single", 0 };
class CxCore_StatTestImpl : public CvArrTest
{
public:
CxCore_StatTestImpl( const char* test_name, const char* test_funcs,
int _output_count, bool _single_channel,
bool _allow_mask=true, bool _is_binary=false );
protected:
void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
void get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images );
void print_timing_params( int test_case_idx, char* ptr, int params_left );
int write_default_params( CvFileStorage* fs );
int prepare_test_case( int test_case_idx );
double get_success_error_level( int test_case_idx, int i, int j );
int coi;
int output_count;
bool single_channel;
bool is_binary;
bool test_nd;
};
CxCore_StatTestImpl::CxCore_StatTestImpl( const char* test_name,
const char* test_funcs, int _output_count,
bool _single_channel, bool _allow_mask, bool _is_binary )
: CvArrTest( test_name, test_funcs, "" ), output_count(_output_count),
single_channel(_single_channel), is_binary(_is_binary)
{
test_array[INPUT].push(NULL);
if( is_binary )
test_array[INPUT].push(NULL);
optional_mask = _allow_mask;
if( optional_mask )
test_array[MASK].push(NULL);
test_array[OUTPUT].push(NULL);
test_array[REF_OUTPUT].push(NULL);
coi = 0;
size_list = arithm_sizes;
whole_size_list = arithm_whole_sizes;
depth_list = arithm_depths;
cn_list = arithm_channels;
test_nd = false;
}
void CxCore_StatTestImpl::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
CvRNG* rng = ts->get_rng();
int depth = cvTsRandInt(rng)%(CV_64F+1);
int cn = cvTsRandInt(rng) % 4 + 1;
int j, count = test_array[INPUT].size();
CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
depth += depth == CV_8S;
for( j = 0; j < count; j++ )
types[INPUT][j] = CV_MAKETYPE(depth, cn);
// regardless of the test case, the output is always a fixed-size tuple of numbers
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize( output_count, 1 );
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
coi = 0;
cvmat_allowed = true;
if( cn > 1 && (single_channel || (cvTsRandInt(rng) & 3) == 0) )
{
coi = cvTsRandInt(rng) % cn + 1;
cvmat_allowed = false;
}
test_nd = cvTsRandInt(rng) % 3 == 0;
}
void CxCore_StatTestImpl::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types, CvSize** whole_sizes, bool* are_images )
{
CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
whole_sizes, are_images );
const char* coi_mode_str = cvReadString(find_timing_param("coi"), single_channel ? "single" : "all");
// regardless of the test case, the output is always a fixed-size tuple of numbers
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize( output_count, 1 );
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
int cn = CV_MAT_CN(types[INPUT][0]);
coi = 0;
cvmat_allowed = true;
if( strcmp( coi_mode_str, "single" ) == 0 )
{
CvRNG* rng = ts->get_rng();
coi = cvTsRandInt(rng) % cn + 1;
cvmat_allowed = false;
*are_images = true;
}
}
int CxCore_StatTestImpl::write_default_params( CvFileStorage* fs )
{
int code = CvArrTest::write_default_params(fs);
if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
return code;
if( !single_channel )
write_string_list( fs, "coi", stat_coi_modes );
return code;
}
int CxCore_StatTestImpl::prepare_test_case( int test_case_idx )
{
int code = CvArrTest::prepare_test_case( test_case_idx );
if( coi && code > 0 )
{
int j, count = test_array[INPUT].size();
if( ts->get_testing_mode() == CvTS::TIMING_MODE && CV_MAT_CN(test_mat[INPUT][0].type) == 1 )
return 0;
for( j = 0; j < count; j++ )
{
IplImage* img = (IplImage*)test_array[INPUT][j];
if( img )
cvSetImageCOI( img, coi );
}
}
return code;
}
void CxCore_StatTestImpl::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
sprintf( ptr, "%s,", coi > 0 || CV_MAT_CN(test_mat[INPUT][0].type) == 1 ? "single" : "all" );
ptr += strlen(ptr);
params_left--;
CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
}
double CxCore_StatTestImpl::get_success_error_level( int test_case_idx, int i, int j )
{
int depth = CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0]));
if( depth == CV_32F )
return FLT_EPSILON*1000;
if( depth == CV_64F )
return DBL_EPSILON*100000;
else
return CvArrTest::get_success_error_level( test_case_idx, i, j );
}
CxCore_StatTestImpl stat_test( "stat", "", 0, true, false );
class CxCore_StatTest : public CxCore_StatTestImpl
{
public:
CxCore_StatTest( const char* test_name, const char* test_funcs,
int _output_count, bool _single_channel,
bool _allow_mask=1, bool _is_binary=0 );
};
CxCore_StatTest::CxCore_StatTest( const char* test_name, const char* test_funcs,
int _output_count, bool _single_channel,
bool _allow_mask, bool _is_binary )
: CxCore_StatTestImpl( test_name, test_funcs, _output_count, _single_channel, _allow_mask, _is_binary )
{
if( !single_channel )
default_timing_param_names = optional_mask ? stat_single_mask_param_names : stat_single_param_names;
else
default_timing_param_names = optional_mask ? stat_mask_param_names : stat_param_names;
// inherit the default parameters from arithmerical test
size_list = 0;
whole_size_list = 0;
depth_list = 0;
cn_list = 0;
}
////////////////// sum /////////////////
class CxCore_SumTest : public CxCore_StatTest
{
public:
CxCore_SumTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
double get_success_error_level( int test_case_idx, int i, int j );
};
CxCore_SumTest::CxCore_SumTest()
: CxCore_StatTest( "stat-sum", "cvSum", 4 /* CvScalar */, false, false, false )
{
}
double CxCore_SumTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
int depth = CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0]));
if( depth == CV_32F )
return FLT_EPSILON*1000;
return DBL_EPSILON*100000;
}
void CxCore_SumTest::run_func()
{
if(!test_nd || coi)
{
*(CvScalar*)(test_mat[OUTPUT][0].data.db) = cvSum(test_array[INPUT][0]);
}
else
{
*(cv::Scalar*)(test_mat[OUTPUT][0].data.db) = cv::sum(cv::cvarrToMatND(test_array[INPUT][0]));
}
}
void CxCore_SumTest::prepare_to_validation( int /*test_case_idx*/ )
{
CvScalar mean;
int nonzero = cvTsMeanStdDevNonZero( &test_mat[INPUT][0], 0, &mean, 0, coi );
*(CvScalar*)(test_mat[REF_OUTPUT][0].data.db) = mean;
mean = *(CvScalar*)(test_mat[OUTPUT][0].data.db);
mean.val[0] /= nonzero;
mean.val[1] /= nonzero;
mean.val[2] /= nonzero;
mean.val[3] /= nonzero;
*(CvScalar*)(test_mat[OUTPUT][0].data.db) = mean;
}
CxCore_SumTest sum_test;
////////////////// nonzero /////////////////
class CxCore_NonZeroTest : public CxCore_StatTest
{
public:
CxCore_NonZeroTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
void get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types );
};
CxCore_NonZeroTest::CxCore_NonZeroTest()
: CxCore_StatTest( "stat-nonzero", "cvCountNonZero", 1 /* int */, true, false, false )
{
test_array[TEMP].push(NULL);
test_array[TEMP].push(NULL);
}
void CxCore_NonZeroTest::run_func()
{
if(!test_nd || coi)
{
test_mat[OUTPUT][0].data.db[0] = cvCountNonZero(test_array[INPUT][0]);
}
else
{
test_mat[OUTPUT][0].data.db[0] = cv::countNonZero(cv::cvarrToMatND(test_array[INPUT][0]));
}
}
void CxCore_NonZeroTest::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
CxCore_StatTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
types[TEMP][0] = CV_8UC1;
if( CV_MAT_CN(types[INPUT][0]) > 1 )
types[TEMP][1] = types[INPUT][0] & ~CV_MAT_CN_MASK;
else
sizes[TEMP][1] = cvSize(0,0);
}
void CxCore_NonZeroTest::prepare_to_validation( int /*test_case_idx*/ )
{
CvMat* plane = &test_mat[INPUT][0];
if( CV_MAT_CN(plane->type) > 1 )
{
plane = &test_mat[TEMP][1];
assert( coi > 0 );
cvTsExtract( &test_mat[INPUT][0], plane, coi-1 );
}
cvTsCmpS( plane, 0, &test_mat[TEMP][0], CV_CMP_NE );
int nonzero = cvTsMeanStdDevNonZero( &test_mat[INPUT][0], &test_mat[TEMP][0], 0, 0, coi );
test_mat[REF_OUTPUT][0].data.db[0] = nonzero;
}
CxCore_NonZeroTest nonzero_test;
/////////////////// mean //////////////////////
class CxCore_MeanTest : public CxCore_StatTest
{
public:
CxCore_MeanTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
};
CxCore_MeanTest::CxCore_MeanTest()
: CxCore_StatTest( "stat-mean", "cvAvg", 4 /* CvScalar */, false, true, false )
{
}
void CxCore_MeanTest::run_func()
{
if(!test_nd || coi)
{
*(CvScalar*)(test_mat[OUTPUT][0].data.db) =
cvAvg(test_array[INPUT][0], test_array[MASK][0]);
}
else
{
*(cv::Scalar*)(test_mat[OUTPUT][0].data.db) = cv::mean(
cv::cvarrToMatND(test_array[INPUT][0]),
cv::cvarrToMatND(test_array[MASK][0]));
}
}
void CxCore_MeanTest::prepare_to_validation( int /*test_case_idx*/ )
{
CvScalar mean;
cvTsMeanStdDevNonZero( &test_mat[INPUT][0],
test_array[MASK][0] ? &test_mat[MASK][0] : 0,
&mean, 0, coi );
*(CvScalar*)(test_mat[REF_OUTPUT][0].data.db) = mean;
}
CxCore_MeanTest mean_test;
/////////////////// mean_stddev //////////////////////
class CxCore_MeanStdDevTest : public CxCore_StatTest
{
public:
CxCore_MeanStdDevTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
double get_success_error_level( int test_case_idx, int i, int j );
};
CxCore_MeanStdDevTest::CxCore_MeanStdDevTest()
: CxCore_StatTest( "stat-mean_stddev", "cvAvgSdv", 8 /* CvScalar x 2 */, false, true, false )
{
}
void CxCore_MeanStdDevTest::run_func()
{
if(!test_nd || coi)
{
cvAvgSdv( test_array[INPUT][0],
&((CvScalar*)(test_mat[OUTPUT][0].data.db))[0],
&((CvScalar*)(test_mat[OUTPUT][0].data.db))[1],
test_array[MASK][0] );
}
else
{
cv::meanStdDev(cv::cvarrToMatND(test_array[INPUT][0]),
((cv::Scalar*)(test_mat[OUTPUT][0].data.db))[0],
((cv::Scalar*)(test_mat[OUTPUT][0].data.db))[1],
cv::cvarrToMatND(test_array[MASK][0]) );
}
}
double CxCore_MeanStdDevTest::get_success_error_level( int test_case_idx, int i, int j )
{
int depth = CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0]));
if( depth < CV_64F && depth != CV_32S )
return CxCore_StatTest::get_success_error_level( test_case_idx, i, j );
return DBL_EPSILON*1e6;
}
void CxCore_MeanStdDevTest::prepare_to_validation( int /*test_case_idx*/ )
{
CvScalar mean, stddev;
int i;
CvMat* output = &test_mat[OUTPUT][0];
CvMat* ref_output = &test_mat[REF_OUTPUT][0];
cvTsMeanStdDevNonZero( &test_mat[INPUT][0],
test_array[MASK][0] ? &test_mat[MASK][0] : 0,
&mean, &stddev, coi );
((CvScalar*)(ref_output->data.db))[0] = mean;
((CvScalar*)(ref_output->data.db))[1] = stddev;
for( i = 0; i < 4; i++ )
{
output->data.db[i] *= output->data.db[i];
output->data.db[i+4] = output->data.db[i+4]*output->data.db[i+4] + 1000;
ref_output->data.db[i] *= ref_output->data.db[i];
ref_output->data.db[i+4] = ref_output->data.db[i+4]*ref_output->data.db[i+4] + 1000;
}
}
CxCore_MeanStdDevTest mean_stddev_test;
/////////////////// minmaxloc //////////////////////
class CxCore_MinMaxLocTest : public CxCore_StatTest
{
public:
CxCore_MinMaxLocTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
};
CxCore_MinMaxLocTest::CxCore_MinMaxLocTest()
: CxCore_StatTest( "stat-minmaxloc", "cvMinMaxLoc", 6 /* double x 2 + CvPoint x 2 */, true, true, false )
{
}
void CxCore_MinMaxLocTest::run_func()
{
CvPoint minloc = {0,0}, maxloc = {0,0};
double* output = test_mat[OUTPUT][0].data.db;
cvMinMaxLoc( test_array[INPUT][0],
output, output+1, &minloc, &maxloc,
test_array[MASK][0] );
output[2] = minloc.x;
output[3] = minloc.y;
output[4] = maxloc.x;
output[5] = maxloc.y;
}
void CxCore_MinMaxLocTest::prepare_to_validation( int /*test_case_idx*/ )
{
double minval = 0, maxval = 0;
CvPoint minloc = {0,0}, maxloc = {0,0};
double* ref_output = test_mat[REF_OUTPUT][0].data.db;
cvTsMinMaxLoc( &test_mat[INPUT][0], test_array[MASK][0] ?
&test_mat[MASK][0] : 0, &minval, &maxval, &minloc, &maxloc, coi );
ref_output[0] = minval;
ref_output[1] = maxval;
ref_output[2] = minloc.x;
ref_output[3] = minloc.y;
ref_output[4] = maxloc.x;
ref_output[5] = maxloc.y;
}
CxCore_MinMaxLocTest minmaxloc_test;
/////////////////// norm //////////////////////
static const char* stat_norm_param_names[] = { "size", "coi", "norm_type", "channels", "depth", "use_mask", 0 };
static const char* stat_norm_type_names[] = { "Inf", "L1", "L2", "diff_Inf", "diff_L1", "diff_L2", 0 };
class CxCore_NormTest : public CxCore_StatTest
{
public:
CxCore_NormTest();
protected:
void run_func();
void prepare_to_validation( int test_case_idx );
void get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types );
void get_timing_test_array_types_and_sizes( int /*test_case_idx*/,
CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images );
int prepare_test_case( int test_case_idx );
void print_timing_params( int test_case_idx, char* ptr, int params_left );
int write_default_params( CvFileStorage* fs );
double get_success_error_level( int test_case_idx, int i, int j );
int norm_type;
};
CxCore_NormTest::CxCore_NormTest()
: CxCore_StatTest( "stat-norm", "cvNorm", 1 /* double */, false, true, true )
{
test_array[TEMP].push(NULL);
default_timing_param_names = stat_norm_param_names;
}
double CxCore_NormTest::get_success_error_level( int test_case_idx, int i, int j )
{
int depth = CV_MAT_DEPTH(cvGetElemType(test_array[INPUT][0]));
if( (depth == CV_16U || depth == CV_16S) /*&& (norm_type&3) != CV_C*/ )
return 1e-4;
else
return CxCore_StatTest::get_success_error_level( test_case_idx, i, j );
}
void CxCore_NormTest::get_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types )
{
int intype;
int norm_kind;
CxCore_StatTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
norm_type = cvTsRandInt(ts->get_rng()) % 3; // CV_C, CV_L1 or CV_L2
norm_kind = cvTsRandInt(ts->get_rng()) % 3; // simple, difference or relative difference
if( norm_kind == 0 )
sizes[INPUT][1] = cvSize(0,0);
norm_type = (1 << norm_type) | (norm_kind*8);
intype = types[INPUT][0];
if( CV_MAT_CN(intype) > 1 && coi == 0 )
sizes[MASK][0] = cvSize(0,0);
sizes[TEMP][0] = cvSize(0,0);
if( (norm_type & (CV_DIFF|CV_RELATIVE)) && CV_MAT_DEPTH(intype) <= CV_32F )
{
sizes[TEMP][0] = sizes[INPUT][0];
types[TEMP][0] = (intype & ~CV_MAT_DEPTH_MASK)|
(CV_MAT_DEPTH(intype) < CV_32F ? CV_32S : CV_64F);
}
}
void CxCore_NormTest::get_timing_test_array_types_and_sizes( int test_case_idx,
CvSize** sizes, int** types,
CvSize** whole_sizes, bool* are_images )
{
CxCore_StatTest::get_timing_test_array_types_and_sizes( test_case_idx,
sizes, types, whole_sizes, are_images );
const char* norm_type_str = cvReadString( find_timing_param( "norm_type" ), "L2" );
bool diff = false;
if( strncmp( norm_type_str, "diff_", 5 ) == 0 )
{
diff = true;
norm_type_str += 5;
}
if( strcmp( norm_type_str, "L1" ) == 0 )
norm_type = CV_L1;
else if( strcmp( norm_type_str, "L2" ) == 0 )
norm_type = CV_L2;
else
norm_type = CV_C;
if( diff )
norm_type += CV_DIFF;
else
sizes[INPUT][1] = cvSize(0,0);
}
int CxCore_NormTest::prepare_test_case( int test_case_idx )
{
int code = CxCore_StatTest::prepare_test_case( test_case_idx );
if( code > 0 && ts->get_testing_mode() == CvTS::TIMING_MODE )
{
// currently it is not supported
if( test_array[MASK][0] && CV_MAT_CN(test_mat[INPUT][0].type) > 1 && coi == 0 )
return 0;
}
return code;
}
int CxCore_NormTest::write_default_params( CvFileStorage* fs )
{
int code = CxCore_StatTest::write_default_params(fs);
if( code < 0 || ts->get_testing_mode() != CvTS::TIMING_MODE )
return code;
write_string_list( fs, "norm_type", stat_norm_type_names );
return code;
}
void CxCore_NormTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
{
int nt = norm_type & CV_NORM_MASK;
sprintf( ptr, "%s%s,", norm_type & CV_DIFF ? "diff_" : "",
nt == CV_C ? "Inf" : nt == CV_L1 ? "L1" : "L2" );
ptr += strlen(ptr);
params_left--;
CxCore_StatTest::print_timing_params( test_case_idx, ptr, params_left );
}
void CxCore_NormTest::run_func()
{
if(!test_nd || coi)
{
test_mat[OUTPUT][0].data.db[0] = cvNorm( test_array[INPUT][0],
test_array[INPUT][1], norm_type, test_array[MASK][0] );
}
else
{
cv::MatND a = cv::cvarrToMatND(test_array[INPUT][0]);
cv::MatND b = cv::cvarrToMatND(test_array[INPUT][1]);
cv::MatND mask = cv::cvarrToMatND(test_array[MASK][0]);
test_mat[OUTPUT][0].data.db[0] = b.data ?
cv::norm( a, b, norm_type, mask ) :
cv::norm( a, norm_type, mask );
}
}
void CxCore_NormTest::prepare_to_validation( int /*test_case_idx*/ )
{
double a_norm = 0, b_norm = 0;
CvMat* a = &test_mat[INPUT][0];
CvMat* b = &test_mat[INPUT][1];
CvMat* mask = test_array[MASK][0] ? &test_mat[MASK][0] : 0;
CvMat* diff = a;
if( norm_type & (CV_DIFF|CV_RELATIVE) )
{
diff = test_array[TEMP][0] ? &test_mat[TEMP][0] : a;
cvTsAdd( a, cvScalarAll(1.), b, cvScalarAll(-1.),
cvScalarAll(0.), diff, 0 );
}
a_norm = cvTsNorm( diff, mask, norm_type & CV_NORM_MASK, coi );
if( norm_type & CV_RELATIVE )
{
b_norm = cvTsNorm( b, mask, norm_type & CV_NORM_MASK, coi );
a_norm /= (b_norm + DBL_EPSILON );
}
test_mat[REF_OUTPUT][0].data.db[0] = a_norm;
}
CxCore_NormTest norm_test;
// TODO: repeat(?), reshape(?), lut
/* End of file. */
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