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Open Source Computer Vision Library
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691 lines
21 KiB
691 lines
21 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// Intel License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000, Intel Corporation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of Intel Corporation may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "_cxts.h" |
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static const int default_test_case_count = 500; |
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static const int default_max_log_array_size = 9; |
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CvArrTest::CvArrTest( const char* _test_name, const char* _test_funcs, const char* _test_descr ) : |
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CvTest( _test_name, _test_funcs, _test_descr ) |
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{ |
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test_case_count = default_test_case_count; |
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iplimage_allowed = true; |
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cvmat_allowed = true; |
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optional_mask = false; |
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min_log_array_size = 0; |
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max_log_array_size = default_max_log_array_size; |
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element_wise_relative_error = true; |
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size_list = 0; |
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whole_size_list = 0; |
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depth_list = 0; |
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cn_list = 0; |
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max_arr = MAX_ARR; |
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test_array = new CvTestPtrVec[max_arr]; |
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max_hdr = 0; |
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hdr = 0; |
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support_testing_modes = CvTS::CORRECTNESS_CHECK_MODE + CvTS::TIMING_MODE; |
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} |
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CvArrTest::~CvArrTest() |
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{ |
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clear(); |
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delete[] test_array; |
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test_array = 0; |
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} |
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int CvArrTest::write_default_params( CvFileStorage* fs ) |
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{ |
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int code = CvTest::write_default_params( fs ); |
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if( code < 0 ) |
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return code; |
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if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE ) |
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{ |
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write_param( fs, "test_case_count", test_case_count ); |
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write_param( fs, "min_log_array_size", min_log_array_size ); |
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write_param( fs, "max_log_array_size", max_log_array_size ); |
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} |
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else if( ts->get_testing_mode() == CvTS::TIMING_MODE ) |
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{ |
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int i; |
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start_write_param( fs ); // make sure we have written the entry header containing the test name |
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if( size_list ) |
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{ |
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cvStartWriteStruct( fs, "size", CV_NODE_SEQ+CV_NODE_FLOW ); |
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for( i = 0; size_list[i].width >= 0; i++ ) |
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{ |
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cvStartWriteStruct( fs, 0, CV_NODE_SEQ+CV_NODE_FLOW ); |
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cvWriteInt( fs, 0, size_list[i].width ); |
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cvWriteInt( fs, 0, size_list[i].height ); |
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if( whole_size_list && |
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(whole_size_list[i].width > size_list[i].width || |
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whole_size_list[i].height > size_list[i].height) ) |
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{ |
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cvWriteInt( fs, 0, whole_size_list[i].width ); |
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cvWriteInt( fs, 0, whole_size_list[i].height ); |
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} |
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cvEndWriteStruct( fs ); |
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} |
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cvEndWriteStruct(fs); |
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} |
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if( depth_list ) |
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{ |
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cvStartWriteStruct( fs, "depth", CV_NODE_SEQ+CV_NODE_FLOW ); |
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for( i = 0; depth_list[i] >= 0; i++ ) |
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cvWriteString( fs, 0, cvTsGetTypeName(depth_list[i]) ); |
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cvEndWriteStruct(fs); |
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} |
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write_int_list( fs, "channels", cn_list, -1, -1 ); |
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if( optional_mask ) |
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{ |
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static const int use_mask[] = { 0, 1 }; |
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write_int_list( fs, "use_mask", use_mask, 2 ); |
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} |
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} |
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return 0; |
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} |
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void CvArrTest::clear() |
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{ |
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if( test_array ) |
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{ |
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int i, j, n; |
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for( i = 0; i < max_arr; i++ ) |
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{ |
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n = test_array[i].size(); |
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for( j = 0; j < n; j++ ) |
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cvRelease( &test_array[i][j] ); |
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} |
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} |
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delete[] hdr; |
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hdr = 0; |
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max_hdr = 0; |
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CvTest::clear(); |
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} |
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int CvArrTest::read_params( CvFileStorage* fs ) |
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{ |
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int code = CvTest::read_params( fs ); |
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if( code < 0 ) |
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return code; |
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if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE ) |
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{ |
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min_log_array_size = cvReadInt( find_param( fs, "min_log_array_size" ), min_log_array_size ); |
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max_log_array_size = cvReadInt( find_param( fs, "max_log_array_size" ), max_log_array_size ); |
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test_case_count = cvReadInt( find_param( fs, "test_case_count" ), test_case_count ); |
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test_case_count = cvRound( test_case_count*ts->get_test_case_count_scale() ); |
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min_log_array_size = cvTsClipInt( min_log_array_size, 0, 20 ); |
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max_log_array_size = cvTsClipInt( max_log_array_size, min_log_array_size, 20 ); |
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test_case_count = cvTsClipInt( test_case_count, 0, 100000 ); |
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} |
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return code; |
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} |
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void CvArrTest::get_test_array_types_and_sizes( int /*test_case_idx*/, CvSize** sizes, int** types ) |
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{ |
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CvRNG* rng = ts->get_rng(); |
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CvSize size; |
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double val; |
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int i, j; |
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val = cvRandReal(rng) * (max_log_array_size - min_log_array_size) + min_log_array_size; |
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size.width = cvRound( exp(val*CV_LOG2) ); |
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val = cvRandReal(rng) * (max_log_array_size - min_log_array_size) + min_log_array_size; |
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size.height = cvRound( exp(val*CV_LOG2) ); |
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for( i = 0; i < max_arr; i++ ) |
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{ |
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int count = test_array[i].size(); |
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for( j = 0; j < count; j++ ) |
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{ |
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sizes[i][j] = size; |
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types[i][j] = CV_8UC1; |
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} |
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} |
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} |
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void CvArrTest::get_timing_test_array_types_and_sizes( int /*test_case_idx*/, CvSize** sizes, int** types, |
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CvSize** whole_sizes, bool *are_images ) |
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{ |
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const CvFileNode* size_node = find_timing_param( "size" ); |
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const CvFileNode* depth_node = find_timing_param( "depth" ); |
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const CvFileNode* channels_node = find_timing_param( "channels" ); |
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int i, j; |
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int depth = 0, channels = 1; |
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CvSize size = {1,1}, whole_size = size; |
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if( size_node && CV_NODE_IS_SEQ(size_node->tag) ) |
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{ |
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CvSeq* seq = size_node->data.seq; |
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size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,0), 1); |
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size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,1), 1); |
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whole_size = size; |
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if( seq->total > 2 ) |
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{ |
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whole_size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,2), 1); |
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whole_size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(seq,3), 1); |
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whole_size.width = MAX( whole_size.width, size.width ); |
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whole_size.height = MAX( whole_size.height, size.height ); |
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} |
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} |
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if( depth_node && CV_NODE_IS_STRING(depth_node->tag) ) |
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{ |
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depth = cvTsTypeByName( depth_node->data.str.ptr ); |
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if( depth < 0 || depth > CV_64F ) |
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depth = 0; |
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} |
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if( channels_node && CV_NODE_IS_INT(channels_node->tag) ) |
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{ |
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channels = cvReadInt( channels_node, 1 ); |
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if( channels < 0 || channels > CV_CN_MAX ) |
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channels = 1; |
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} |
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for( i = 0; i < max_arr; i++ ) |
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{ |
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int count = test_array[i].size(); |
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for( j = 0; j < count; j++ ) |
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{ |
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sizes[i][j] = size; |
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whole_sizes[i][j] = whole_size; |
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if( i != MASK ) |
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types[i][j] = CV_MAKETYPE(depth,channels); |
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else |
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types[i][j] = CV_8UC1; |
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if( i == REF_OUTPUT || i == REF_INPUT_OUTPUT ) |
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sizes[i][j] = cvSize(0,0); |
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} |
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} |
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if( are_images ) |
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*are_images = false; // by default CvMat is used in performance tests |
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} |
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void CvArrTest::print_timing_params( int /*test_case_idx*/, char* ptr, int params_left ) |
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{ |
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int i; |
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for( i = 0; i < params_left; i++ ) |
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{ |
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sprintf( ptr, "-," ); |
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ptr += 2; |
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} |
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} |
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void CvArrTest::print_time( int test_case_idx, double time_clocks, double time_cpu_clocks ) |
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{ |
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int in_type = -1, out_type = -1; |
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CvSize size = { -1, -1 }; |
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const CvFileNode* size_node = find_timing_param( "size" ); |
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char str[1024], *ptr = str; |
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int len; |
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bool have_mask; |
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double cpe; |
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if( size_node ) |
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{ |
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if( !CV_NODE_IS_SEQ(size_node->tag) ) |
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{ |
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size.width = cvReadInt(size_node,-1); |
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size.height = 1; |
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} |
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else |
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{ |
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size.width = cvReadInt((const CvFileNode*)cvGetSeqElem(size_node->data.seq,0),-1); |
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size.height = cvReadInt((const CvFileNode*)cvGetSeqElem(size_node->data.seq,1),-1); |
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} |
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} |
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if( test_array[INPUT].size() ) |
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{ |
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in_type = CV_MAT_TYPE(test_mat[INPUT][0].type); |
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if( size.width == -1 ) |
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size = cvGetMatSize(&test_mat[INPUT][0]); |
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} |
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if( test_array[OUTPUT].size() ) |
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{ |
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out_type = CV_MAT_TYPE(test_mat[OUTPUT][0].type); |
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if( in_type < 0 ) |
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in_type = out_type; |
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if( size.width == -1 ) |
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size = cvGetMatSize(&test_mat[OUTPUT][0]); |
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} |
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if( out_type < 0 && test_array[INPUT_OUTPUT].size() ) |
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{ |
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out_type = CV_MAT_TYPE(test_mat[INPUT_OUTPUT][0].type); |
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if( in_type < 0 ) |
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in_type = out_type; |
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if( size.width == -1 ) |
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size = cvGetMatSize(&test_mat[INPUT_OUTPUT][0]); |
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} |
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have_mask = test_array[MASK].size() > 0 && test_array[MASK][0] != 0; |
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if( in_type < 0 && out_type < 0 ) |
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return; |
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if( out_type < 0 ) |
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out_type = in_type; |
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ptr = strchr( (char*)tested_functions, ',' ); |
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if( ptr ) |
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{ |
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len = (int)(ptr - tested_functions); |
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strncpy( str, tested_functions, len ); |
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} |
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else |
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{ |
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len = (int)strlen( tested_functions ); |
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strcpy( str, tested_functions ); |
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} |
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ptr = str + len; |
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*ptr = '\0'; |
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if( have_mask ) |
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{ |
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sprintf( ptr, "(Mask)" ); |
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ptr += strlen(ptr); |
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} |
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*ptr++ = ','; |
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sprintf( ptr, "%s", cvTsGetTypeName(in_type) ); |
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ptr += strlen(ptr); |
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if( CV_MAT_DEPTH(out_type) != CV_MAT_DEPTH(in_type) ) |
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{ |
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sprintf( ptr, "%s", cvTsGetTypeName(out_type) ); |
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ptr += strlen(ptr); |
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} |
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*ptr++ = ','; |
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sprintf( ptr, "C%d", CV_MAT_CN(in_type) ); |
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ptr += strlen(ptr); |
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if( CV_MAT_CN(out_type) != CV_MAT_CN(in_type) ) |
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{ |
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sprintf( ptr, "C%d", CV_MAT_CN(out_type) ); |
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ptr += strlen(ptr); |
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} |
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*ptr++ = ','; |
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sprintf( ptr, "%dx%d,", size.width, size.height ); |
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ptr += strlen(ptr); |
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print_timing_params( test_case_idx, ptr ); |
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ptr += strlen(ptr); |
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cpe = time_cpu_clocks / ((double)size.width * size.height); |
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if( cpe >= 100 ) |
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sprintf( ptr, "%.0f,", cpe ); |
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else |
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sprintf( ptr, "%.1f,", cpe ); |
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ptr += strlen(ptr); |
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sprintf( ptr, "%g", time_clocks*1e6/cv::getTickFrequency() ); |
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ts->printf( CvTS::CSV, "%s\n", str ); |
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} |
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static const int icvTsTypeToDepth[] = |
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{ |
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IPL_DEPTH_8U, IPL_DEPTH_8S, IPL_DEPTH_16U, IPL_DEPTH_16S, |
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IPL_DEPTH_32S, IPL_DEPTH_32F, IPL_DEPTH_64F |
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}; |
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int CvArrTest::prepare_test_case( int test_case_idx ) |
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{ |
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int code = 1; |
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CvSize** sizes = (CvSize**)malloc( max_arr*sizeof(sizes[0]) ); |
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CvSize** whole_sizes = (CvSize**)malloc( max_arr*sizeof(whole_sizes[0]) ); |
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int** types = (int**)malloc( max_arr*sizeof(types[0]) ); |
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int i, j, total = 0; |
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CvRNG* rng = ts->get_rng(); |
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bool is_image = false; |
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bool is_timing_test = false; |
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CV_FUNCNAME( "CvArrTest::prepare_test_case" ); |
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__BEGIN__; |
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is_timing_test = ts->get_testing_mode() == CvTS::TIMING_MODE; |
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if( is_timing_test ) |
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{ |
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if( !get_next_timing_param_tuple() ) |
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{ |
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code = -1; |
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EXIT; |
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} |
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} |
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for( i = 0; i < max_arr; i++ ) |
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{ |
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int count = test_array[i].size(); |
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count = MAX(count, 1); |
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sizes[i] = (CvSize*)malloc( count*sizeof(sizes[i][0]) ); |
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types[i] = (int*)malloc( count*sizeof(types[i][0]) ); |
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whole_sizes[i] = (CvSize*)malloc( count*sizeof(whole_sizes[i][0]) ); |
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} |
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if( !is_timing_test ) |
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get_test_array_types_and_sizes( test_case_idx, sizes, types ); |
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else |
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{ |
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get_timing_test_array_types_and_sizes( test_case_idx, sizes, types, |
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whole_sizes, &is_image ); |
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} |
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for( i = 0; i < max_arr; i++ ) |
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{ |
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int count = test_array[i].size(); |
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total += count; |
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for( j = 0; j < count; j++ ) |
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{ |
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unsigned t = cvRandInt(rng); |
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bool create_mask = true, use_roi = false; |
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CvSize size = sizes[i][j], whole_size = size; |
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CvRect roi = {0,0,0,0}; |
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if( !is_timing_test ) |
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{ |
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is_image = !cvmat_allowed ? true : iplimage_allowed ? (t & 1) != 0 : false; |
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create_mask = (t & 6) == 0; // ~ each of 3 tests will use mask |
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use_roi = (t & 8) != 0; |
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if( use_roi ) |
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{ |
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whole_size.width += cvRandInt(rng) % 10; |
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whole_size.height += cvRandInt(rng) % 10; |
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} |
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} |
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else |
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{ |
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whole_size = whole_sizes[i][j]; |
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use_roi = whole_size.width != size.width || whole_size.height != size.height; |
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create_mask = cvReadInt(find_timing_param( "use_mask" ),0) != 0; |
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} |
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cvRelease( &test_array[i][j] ); |
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if( size.width > 0 && size.height > 0 && |
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types[i][j] >= 0 && (i != MASK || create_mask) ) |
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{ |
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if( use_roi ) |
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{ |
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roi.width = size.width; |
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roi.height = size.height; |
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if( whole_size.width > size.width ) |
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{ |
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if( !is_timing_test ) |
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roi.x = cvRandInt(rng) % (whole_size.width - size.width); |
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else |
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roi.x = 1; |
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} |
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if( whole_size.height > size.height ) |
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{ |
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if( !is_timing_test ) |
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roi.y = cvRandInt(rng) % (whole_size.height - size.height); |
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else |
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roi.y = 1; |
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} |
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} |
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if( is_image ) |
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{ |
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CV_CALL( test_array[i][j] = cvCreateImage( whole_size, |
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icvTsTypeToDepth[CV_MAT_DEPTH(types[i][j])], |
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CV_MAT_CN(types[i][j]) )); |
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if( use_roi ) |
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cvSetImageROI( (IplImage*)test_array[i][j], roi ); |
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} |
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else |
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{ |
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CV_CALL( test_array[i][j] = cvCreateMat( whole_size.height, |
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whole_size.width, types[i][j] )); |
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if( use_roi ) |
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{ |
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CvMat submat, *mat = (CvMat*)test_array[i][j]; |
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cvGetSubRect( test_array[i][j], &submat, roi ); |
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submat.refcount = mat->refcount; |
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*mat = submat; |
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} |
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} |
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} |
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} |
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} |
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if( total > max_hdr ) |
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{ |
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delete hdr; |
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max_hdr = total; |
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hdr = new CvMat[max_hdr]; |
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} |
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total = 0; |
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for( i = 0; i < max_arr; i++ ) |
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{ |
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int count = test_array[i].size(); |
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test_mat[i] = count > 0 ? hdr + total : 0; |
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for( j = 0; j < count; j++ ) |
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{ |
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CvArr* arr = test_array[i][j]; |
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CvMat* mat = &test_mat[i][j]; |
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if( !arr ) |
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memset( mat, 0, sizeof(*mat) ); |
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else if( CV_IS_MAT( arr )) |
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{ |
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*mat = *(CvMat*)arr; |
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mat->refcount = 0; |
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} |
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else |
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cvGetMat( arr, mat, 0, 0 ); |
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if( mat->data.ptr ) |
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fill_array( test_case_idx, i, j, mat ); |
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} |
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total += count; |
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} |
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__END__; |
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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. */
|
|
|