Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
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// If you do not agree to this license, do not download, install,
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//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
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//
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//M*/
#include "_cxts.h"
static const int default_test_case_count = 500;
static const int default_max_log_array_size = 9;
CvArrTest::CvArrTest( const char* _test_name, const char* _test_funcs, const char* _test_descr ) :
CvTest( _test_name, _test_funcs, _test_descr )
{
test_case_count = default_test_case_count;
iplimage_allowed = true;
cvmat_allowed = true;
optional_mask = false;
min_log_array_size = 0;
max_log_array_size = default_max_log_array_size;
element_wise_relative_error = true;
size_list = 0;
whole_size_list = 0;
depth_list = 0;
cn_list = 0;
max_arr = MAX_ARR;
test_array = new CvTestPtrVec[max_arr];
max_hdr = 0;
hdr = 0;
support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE + CvTS::TIMING_MODE;
}
CvArrTest::~CvArrTest()
{
clear();
delete[] test_array;
test_array = 0;
}
int CvArrTest::write_default_params( CvFileStorage* fs )
{
int code = CvTest::write_default_params( fs );
if( code < 0 )
return code;
if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
{
write_param( fs, "test_case_count", test_case_count );
write_param( fs, "min_log_array_size", min_log_array_size );
write_param( fs, "max_log_array_size", max_log_array_size );
}
else if( ts->get_testing_mode() == CvTS::TIMING_MODE )
{
int i;
start_write_param( fs ); // make sure we have written the entry header containing the test name
if( size_list )
{
cvStartWriteStruct( fs, "size", CV_NODE_SEQ+CV_NODE_FLOW );
for( i = 0; size_list[i].width >= 0; i++ )
{
cvStartWriteStruct( fs, 0, CV_NODE_SEQ+CV_NODE_FLOW );
cvWriteInt( fs, 0, size_list[i].width );
cvWriteInt( fs, 0, size_list[i].height );
if( whole_size_list &&
(whole_size_list[i].width > size_list[i].width ||
whole_size_list[i].height > size_list[i].height) )
{
cvWriteInt( fs, 0, whole_size_list[i].width );
cvWriteInt( fs, 0, whole_size_list[i].height );
}
cvEndWriteStruct( fs );
}
cvEndWriteStruct(fs);
}
if( depth_list )
{
cvStartWriteStruct( fs, "depth", CV_NODE_SEQ+CV_NODE_FLOW );
for( i = 0; depth_list[i] >= 0; i++ )
cvWriteString( fs, 0, cvTsGetTypeName(depth_list[i]) );
cvEndWriteStruct(fs);
}
write_int_list( fs, "channels", cn_list, -1, -1 );
if( optional_mask )
{
static const int use_mask[] = { 0, 1 };
write_int_list( fs, "use_mask", use_mask, 2 );
}
}
return 0;
}
void CvArrTest::clear()
{
if( test_array )
{
int i, j, n;
for( i = 0; i < max_arr; i++ )
{
n = test_array[i].size();
for( j = 0; j < n; j++ )
cvRelease( &test_array[i][j] );
}
}
delete[] hdr;
hdr = 0;
max_hdr = 0;
CvTest::clear();
}
int CvArrTest::read_params( CvFileStorage* fs )
{
int code = CvTest::read_params( fs );
if( code < 0 )
return code;
if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE )
{
min_log_array_size = cvReadInt( find_param( fs, "min_log_array_size" ), min_log_array_size );
max_log_array_size = cvReadInt( find_param( fs, "max_log_array_size" ), max_log_array_size );
test_case_count = cvReadInt( find_param( fs, "test_case_count" ), test_case_count );
test_case_count = cvRound( test_case_count*ts->get_test_case_count_scale() );
min_log_array_size = cvTsClipInt( min_log_array_size, 0, 20 );
max_log_array_size = cvTsClipInt( max_log_array_size, min_log_array_size, 20 );
test_case_count = cvTsClipInt( test_case_count, 0, 100000 );
}
return code;
}
void CvArrTest::get_test_array_types_and_sizes( int /*test_case_idx*/, CvSize** sizes, int** types )
{
CvRNG* rng = ts->get_rng();
CvSize size;
double val;
int i, j;
val = cvRandReal(rng) * (max_log_array_size - min_log_array_size) + min_log_array_size;
size.width = cvRound( exp(val*CV_LOG2) );
val = cvRandReal(rng) * (max_log_array_size - min_log_array_size) + min_log_array_size;
size.height = cvRound( exp(val*CV_LOG2) );
for( i = 0; i < max_arr; i++ )
{
int count = test_array[i].size();
for( j = 0; j < count; j++ )
{
sizes[i][j] = size;
types[i][j] = CV_8UC1;
}
}
}
void CvArrTest::get_timing_test_array_types_and_sizes( int /*test_case_idx*/, CvSize** sizes, int** types,
CvSize** whole_sizes, bool *are_images )
{
const CvFileNode* size_node = find_timing_param( "size" );
const CvFileNode* depth_node = find_timing_param( "depth" );
const CvFileNode* channels_node = find_timing_param( "channels" );
int i, j;
int depth = 0, channels = 1;
CvSize size = {1,1}, whole_size = size;
if( size_node && CV_NODE_IS_SEQ(size_node->tag) )
{
CvSeq* seq = size_node->data.seq;
size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,0), 1);
size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,1), 1);
whole_size = size;
if( seq->total > 2 )
{
whole_size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,2), 1);
whole_size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,3), 1);
whole_size.width = MAX( whole_size.width, size.width );
whole_size.height = MAX( whole_size.height, size.height );
}
}
if( depth_node && CV_NODE_IS_STRING(depth_node->tag) )
{
depth = cvTsTypeByName( depth_node->data.str.ptr );
if( depth < 0 || depth > CV_64F )
depth = 0;
}
if( channels_node && CV_NODE_IS_INT(channels_node->tag) )
{
channels = cvReadInt( channels_node, 1 );
if( channels < 0 || channels > CV_CN_MAX )
channels = 1;
}
for( i = 0; i < max_arr; i++ )
{
int count = test_array[i].size();
for( j = 0; j < count; j++ )
{
sizes[i][j] = size;
whole_sizes[i][j] = whole_size;
if( i != MASK )
types[i][j] = CV_MAKETYPE(depth,channels);
else
types[i][j] = CV_8UC1;
if( i == REF_OUTPUT || i == REF_INPUT_OUTPUT )
sizes[i][j] = cvSize(0,0);
}
}
if( are_images )
*are_images = false; // by default CvMat is used in performance tests
}
void CvArrTest::print_timing_params( int /*test_case_idx*/, char* ptr, int params_left )
{
int i;
for( i = 0; i < params_left; i++ )
{
sprintf( ptr, "-," );
ptr += 2;
}
}
void CvArrTest::print_time( int test_case_idx, double time_clocks, double time_cpu_clocks )
{
int in_type = -1, out_type = -1;
CvSize size = { -1, -1 };
const CvFileNode* size_node = find_timing_param( "size" );
char str[1024], *ptr = str;
int len;
bool have_mask;
double cpe;
if( size_node )
{
if( !CV_NODE_IS_SEQ(size_node->tag) )
{
size.width = cvReadInt(size_node,-1);
size.height = 1;
}
else
{
size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(size_node->data.seq,0),-1);
size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(size_node->data.seq,1),-1);
}
}
if( test_array[INPUT].size() )
{
in_type = CV_MAT_TYPE(test_mat[INPUT][0].type);
if( size.width == -1 )
size = cvGetMatSize(&test_mat[INPUT][0]);
}
if( test_array[OUTPUT].size() )
{
out_type = CV_MAT_TYPE(test_mat[OUTPUT][0].type);
if( in_type < 0 )
in_type = out_type;
if( size.width == -1 )
size = cvGetMatSize(&test_mat[OUTPUT][0]);
}
if( out_type < 0 && test_array[INPUT_OUTPUT].size() )
{
out_type = CV_MAT_TYPE(test_mat[INPUT_OUTPUT][0].type);
if( in_type < 0 )
in_type = out_type;
if( size.width == -1 )
size = cvGetMatSize(&test_mat[INPUT_OUTPUT][0]);
}
have_mask = test_array[MASK].size() > 0 && test_array[MASK][0] != 0;
if( in_type < 0 && out_type < 0 )
return;
if( out_type < 0 )
out_type = in_type;
ptr = strchr( (char*)tested_functions, ',' );
if( ptr )
{
len = (int)(ptr - tested_functions);
strncpy( str, tested_functions, len );
}
else
{
len = (int)strlen( tested_functions );
strcpy( str, tested_functions );
}
ptr = str + len;
*ptr = '\0';
if( have_mask )
{
sprintf( ptr, "(Mask)" );
ptr += strlen(ptr);
}
*ptr++ = ',';
sprintf( ptr, "%s", cvTsGetTypeName(in_type) );
ptr += strlen(ptr);
if( CV_MAT_DEPTH(out_type) != CV_MAT_DEPTH(in_type) )
{
sprintf( ptr, "%s", cvTsGetTypeName(out_type) );
ptr += strlen(ptr);
}
*ptr++ = ',';
sprintf( ptr, "C%d", CV_MAT_CN(in_type) );
ptr += strlen(ptr);
if( CV_MAT_CN(out_type) != CV_MAT_CN(in_type) )
{
sprintf( ptr, "C%d", CV_MAT_CN(out_type) );
ptr += strlen(ptr);
}
*ptr++ = ',';
sprintf( ptr, "%dx%d,", size.width, size.height );
ptr += strlen(ptr);
print_timing_params( test_case_idx, ptr );
ptr += strlen(ptr);
cpe = time_cpu_clocks / ((double)size.width * size.height);
if( cpe >= 100 )
sprintf( ptr, "%.0f,", cpe );
else
sprintf( ptr, "%.1f,", cpe );
ptr += strlen(ptr);
sprintf( ptr, "%g", time_clocks*1e6/cv::getTickFrequency() );
ts->printf( CvTS::CSV, "%s\n", str );
}
static const int icvTsTypeToDepth[] =
{
IPL_DEPTH_8U, IPL_DEPTH_8S, IPL_DEPTH_16U, IPL_DEPTH_16S,
IPL_DEPTH_32S, IPL_DEPTH_32F, IPL_DEPTH_64F
};
int CvArrTest::prepare_test_case( int test_case_idx )
{
int code = 1;
CvSize** sizes = (CvSize**)malloc( max_arr*sizeof(sizes[0]) );
CvSize** whole_sizes = (CvSize**)malloc( max_arr*sizeof(whole_sizes[0]) );
int** types = (int**)malloc( max_arr*sizeof(types[0]) );
int i, j, total = 0;
CvRNG* rng = ts->get_rng();
bool is_image = false;
bool is_timing_test = false;
CV_FUNCNAME( "CvArrTest::prepare_test_case" );
__BEGIN__;
is_timing_test = ts->get_testing_mode() == CvTS::TIMING_MODE;
if( is_timing_test )
{
if( !get_next_timing_param_tuple() )
{
code = -1;
EXIT;
}
}
for( i = 0; i < max_arr; i++ )
{
int count = test_array[i].size();
count = MAX(count, 1);
sizes[i] = (CvSize*)malloc( count*sizeof(sizes[i][0]) );
types[i] = (int*)malloc( count*sizeof(types[i][0]) );
whole_sizes[i] = (CvSize*)malloc( count*sizeof(whole_sizes[i][0]) );
}
if( !is_timing_test )
get_test_array_types_and_sizes( test_case_idx, sizes, types );
else
{
get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
whole_sizes, &is_image );
}
for( i = 0; i < max_arr; i++ )
{
int count = test_array[i].size();
total += count;
for( j = 0; j < count; j++ )
{
unsigned t = cvRandInt(rng);
bool create_mask = true, use_roi = false;
CvSize size = sizes[i][j], whole_size = size;
CvRect roi = {0,0,0,0};
if( !is_timing_test )
{
is_image = !cvmat_allowed ? true : iplimage_allowed ? (t & 1) != 0 : false;
create_mask = (t & 6) == 0; // ~ each of 3 tests will use mask
use_roi = (t & 8) != 0;
if( use_roi )
{
whole_size.width += cvRandInt(rng) % 10;
whole_size.height += cvRandInt(rng) % 10;
}
}
else
{
whole_size = whole_sizes[i][j];
use_roi = whole_size.width != size.width || whole_size.height != size.height;
create_mask = cvReadInt(find_timing_param( "use_mask" ),0) != 0;
}
cvRelease( &test_array[i][j] );
if( size.width > 0 && size.height > 0 &&
types[i][j] >= 0 && (i != MASK || create_mask) )
{
if( use_roi )
{
roi.width = size.width;
roi.height = size.height;
if( whole_size.width > size.width )
{
if( !is_timing_test )
roi.x = cvRandInt(rng) % (whole_size.width - size.width);
else
roi.x = 1;
}
if( whole_size.height > size.height )
{
if( !is_timing_test )
roi.y = cvRandInt(rng) % (whole_size.height - size.height);
else
roi.y = 1;
}
}
if( is_image )
{
CV_CALL( test_array[i][j] = cvCreateImage( whole_size,
icvTsTypeToDepth[CV_MAT_DEPTH(types[i][j])],
CV_MAT_CN(types[i][j]) ));
if( use_roi )
cvSetImageROI( (IplImage*)test_array[i][j], roi );
}
else
{
CV_CALL( test_array[i][j] = cvCreateMat( whole_size.height,
whole_size.width, types[i][j] ));
if( use_roi )
{
CvMat submat, *mat = (CvMat*)test_array[i][j];
cvGetSubRect( test_array[i][j], &submat, roi );
submat.refcount = mat->refcount;
*mat = submat;
}
}
}
}
}
if( total > max_hdr )
{
delete hdr;
max_hdr = total;
hdr = new CvMat[max_hdr];
}
total = 0;
for( i = 0; i < max_arr; i++ )
{
int count = test_array[i].size();
test_mat[i] = count > 0 ? hdr + total : 0;
for( j = 0; j < count; j++ )
{
CvArr* arr = test_array[i][j];
CvMat* mat = &test_mat[i][j];
if( !arr )
memset( mat, 0, sizeof(*mat) );
else if( CV_IS_MAT( arr ))
{
*mat = *(CvMat*)arr;
mat->refcount = 0;
}
else
cvGetMat( arr, mat, 0, 0 );
if( mat->data.ptr )
fill_array( test_case_idx, i, j, mat );
}
total += count;
}
__END__;
for( i = 0; i < max_arr; i++ )
{
if( sizes )
free( sizes[i] );
if( whole_sizes )
free( whole_sizes[i] );
if( types )
free( types[i] );
}
free( sizes );
free( whole_sizes );
free( types );
return code;
}
void CvArrTest::get_minmax_bounds( int i, int /*j*/, int type, CvScalar* low, CvScalar* high )
{
double l, u;
if( i == MASK )
{
l = -2;
u = 2;
}
else
{
l = cvTsMinVal(type);
u = cvTsMaxVal(type);
}
*low = cvScalarAll(l);
*high = cvScalarAll(u);
}
void CvArrTest::fill_array( int /*test_case_idx*/, int i, int j, CvMat* arr )
{
if( i == REF_INPUT_OUTPUT )
cvTsCopy( &test_mat[INPUT_OUTPUT][j], arr, 0 );
else if( i == INPUT || i == INPUT_OUTPUT || i == MASK )
{
int type = cvGetElemType( arr );
CvScalar low, high;
get_minmax_bounds( i, j, type, &low, &high );
cvTsRandUni( ts->get_rng(), arr, low, high );
}
}
double CvArrTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
{
int elem_depth = CV_MAT_DEPTH(cvGetElemType(test_array[i][j]));
assert( i == OUTPUT || i == INPUT_OUTPUT );
return elem_depth < CV_32F ? 0 : elem_depth == CV_32F ? FLT_EPSILON*100: DBL_EPSILON*5000;
}
void CvArrTest::prepare_to_validation( int /*test_case_idx*/ )
{
assert(0);
}
int CvArrTest::validate_test_results( int test_case_idx )
{
static const char* arr_names[] = { "input", "input/output", "output",
"ref input/output", "ref output",
"temporary", "mask" };
int i, j;
prepare_to_validation( test_case_idx );
for( i = 0; i < 2; i++ )
{
int i0 = i == 0 ? OUTPUT : INPUT_OUTPUT;
int i1 = i == 0 ? REF_OUTPUT : REF_INPUT_OUTPUT;
int count = test_array[i0].size();
assert( count == test_array[i1].size() );
for( j = 0; j < count; j++ )
{
double err_level;
CvPoint idx = {0,0};
double max_diff = 0;
int code;
char msg[100];
if( !test_array[i1][j] )
continue;
err_level = get_success_error_level( test_case_idx, i0, j );
code = cvTsCmpEps( &test_mat[i0][j], &test_mat[i1][j], &max_diff, err_level, &idx,
element_wise_relative_error );
switch( code )
{
case -1:
sprintf( msg, "Too big difference (=%g)", max_diff );
code = CvTS::FAIL_BAD_ACCURACY;
break;
case -2:
strcpy( msg, "Invalid output" );
code = CvTS::FAIL_INVALID_OUTPUT;
break;
case -3:
strcpy( msg, "Invalid output in the reference array" );
code = CvTS::FAIL_INVALID_OUTPUT;
break;
default:
continue;
}
ts->printf( CvTS::LOG, "%s in %s array %d at (%d,%d)\n", msg,
arr_names[i0], j, idx.x, idx.y );
for( i0 = 0; i0 < max_arr; i0++ )
{
int count = test_array[i0].size();
if( i0 == REF_INPUT_OUTPUT || i0 == OUTPUT || i0 == TEMP )
continue;
for( i1 = 0; i1 < count; i1++ )
{
CvArr* arr = test_array[i0][i1];
if( arr )
{
CvSize size = cvGetSize(arr);
int type = cvGetElemType(arr);
ts->printf( CvTS::LOG, "%s array %d type=%sC%d, size=(%d,%d)\n",
arr_names[i0], i1, cvTsGetTypeName(type),
CV_MAT_CN(type), size.width, size.height );
}
}
}
ts->set_failed_test_info( code );
return code;
}
}
return 0;
}
/* End of file. */