643 lines
21 KiB
C++
643 lines
21 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "cvtest.h"
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static const int motempl_silh_ratio[] = { 10, 50 };
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static const int motempl_duration[] = { 200, 2000 };
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static const int motempl_gradient_aperture[] = { 3, 5 };
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static const char* motempl_update_param_names[] = { "silh_ratio", "duration", "size", 0 };
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static const char* motempl_gradient_param_names[] = { "silh_ratio", "duration", "aperture", "size", 0 };
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static const char* motempl_global_param_names[] = { "silh_ratio", "duration", "size", 0 };
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static const CvSize motempl_sizes[] = {{320, 240}, {720,480}, {-1,-1}};
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///////////////////// base MHI class ///////////////////////
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class CV_MHIBaseTest : public CvArrTest
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{
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public:
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CV_MHIBaseTest( const char* test_name, const char* test_funcs );
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protected:
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int write_default_params(CvFileStorage* fs);
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void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
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void 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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void print_timing_params( int test_case_idx, char* ptr, int params_left );
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void get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
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int prepare_test_case( int test_case_idx );
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double timestamp, duration, max_log_duration;
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int mhi_i, mhi_ref_i;
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double silh_ratio;
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};
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CV_MHIBaseTest::CV_MHIBaseTest( const char* test_name, const char* test_funcs )
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: CvArrTest( test_name, test_funcs )
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{
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timestamp = duration = 0;
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max_log_duration = 9;
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mhi_i = mhi_ref_i = -1;
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size_list = whole_size_list = strcmp( test_funcs, "" ) == 0 ? motempl_sizes : 0;
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depth_list = 0;
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cn_list = 0;
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default_timing_param_names = 0;
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silh_ratio = 0.25;
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}
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int CV_MHIBaseTest::write_default_params( CvFileStorage* fs )
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{
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int code = CvArrTest::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::TIMING_MODE && strcmp(tested_functions, "") == 0 )
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{
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start_write_param( fs );
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write_int_list( fs, "silh_ratio", motempl_silh_ratio, CV_DIM(motempl_silh_ratio) );
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write_int_list( fs, "duration", motempl_duration, CV_DIM(motempl_duration) );
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}
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return code;
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}
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void CV_MHIBaseTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
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{
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CvArrTest::get_minmax_bounds( i, j, type, low, high );
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if( i == INPUT && CV_MAT_DEPTH(type) == CV_8U )
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{
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*low = cvScalarAll(cvRound(-1./silh_ratio)+2.);
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*high = cvScalarAll(2);
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}
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else if( i == mhi_i || i == mhi_ref_i )
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{
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*low = cvScalarAll(-exp(max_log_duration));
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*high = cvScalarAll(0.);
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}
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}
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void CV_MHIBaseTest::get_test_array_types_and_sizes( int test_case_idx,
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CvSize** sizes, int** types )
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{
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CvRNG* rng = ts->get_rng();
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CvArrTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
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types[INPUT][0] = CV_8UC1;
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types[mhi_i][0] = types[mhi_ref_i][0] = CV_32FC1;
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duration = exp(cvTsRandReal(rng)*max_log_duration);
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timestamp = duration + cvTsRandReal(rng)*30.-10.;
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}
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void CV_MHIBaseTest::get_timing_test_array_types_and_sizes( int test_case_idx,
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CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
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{
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CvArrTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
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whole_sizes, are_images );
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types[INPUT][0] = CV_8UC1;
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types[mhi_i][0] = CV_32FC1;
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duration = cvReadInt( find_timing_param( "duration" ), 500 );
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silh_ratio = cvReadInt( find_timing_param( "silh_ratio" ), 25 )*0.01;
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timestamp = duration;
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}
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void CV_MHIBaseTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
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{
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sprintf( ptr, "ratio=%d%%,duration=%dms,", cvRound(silh_ratio*100), cvRound(duration) );
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ptr += strlen(ptr);
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params_left -= 2;
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CvArrTest::print_timing_params( test_case_idx, ptr, params_left );
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}
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int CV_MHIBaseTest::prepare_test_case( int test_case_idx )
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{
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int code = CvArrTest::prepare_test_case( test_case_idx );
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if( code > 0 )
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{
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CvMat* mat = &test_mat[mhi_i][0];
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cvTsAdd( mat, cvScalarAll(1.), 0, cvScalarAll(0.), cvScalarAll(duration), mat, 0 );
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cvTsMinMaxS( mat, 0, mat, CV_TS_MAX );
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if( ts->get_testing_mode() == CvTS::CORRECTNESS_CHECK_MODE && mhi_i != mhi_ref_i )
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{
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CvMat* mat0 = &test_mat[mhi_ref_i][0];
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cvTsCopy( mat, mat0 );
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}
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}
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return code;
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}
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CV_MHIBaseTest mhi_base_test( "mhi", "" );
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///////////////////// update motion history ////////////////////////////
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static void cvTsUpdateMHI( const CvMat* silh, CvMat* mhi, double timestamp, double duration )
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{
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int i, j;
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float delbound = (float)(timestamp - duration);
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for( i = 0; i < mhi->rows; i++ )
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{
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const uchar* silh_row = silh->data.ptr + i*silh->step;
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float* mhi_row = (float*)(mhi->data.ptr + i*mhi->step);
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for( j = 0; j < mhi->cols; j++ )
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{
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if( silh_row[j] )
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mhi_row[j] = (float)timestamp;
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else if( mhi_row[j] < delbound )
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mhi_row[j] = 0.f;
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}
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}
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}
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class CV_UpdateMHITest : public CV_MHIBaseTest
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{
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public:
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CV_UpdateMHITest();
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protected:
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double get_success_error_level( int test_case_idx, int i, int j );
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void run_func();
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void prepare_to_validation( int );
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};
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CV_UpdateMHITest::CV_UpdateMHITest()
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: CV_MHIBaseTest( "mhi-update", "cvUpdateMotionHistory" )
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{
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test_array[INPUT].push(NULL);
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test_array[INPUT_OUTPUT].push(NULL);
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test_array[REF_INPUT_OUTPUT].push(NULL);
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mhi_i = INPUT_OUTPUT; mhi_ref_i = REF_INPUT_OUTPUT;
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default_timing_param_names = motempl_update_param_names;
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}
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double CV_UpdateMHITest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
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{
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return 0;
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}
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void CV_UpdateMHITest::run_func()
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{
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cvUpdateMotionHistory( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], timestamp, duration );
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}
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void CV_UpdateMHITest::prepare_to_validation( int /*test_case_idx*/ )
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{
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cvTsUpdateMHI( &test_mat[INPUT][0], &test_mat[REF_INPUT_OUTPUT][0], timestamp, duration );
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}
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CV_UpdateMHITest mhi_update_test;
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///////////////////// calc motion gradient ////////////////////////////
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static void cvTsMHIGradient( const CvMat* mhi, CvMat* mask, CvMat* orientation,
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double delta1, double delta2, int aperture_size )
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{
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CvPoint anchor = { aperture_size/2, aperture_size/2 };
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CvMat* src = cvCreateMat( mhi->rows + aperture_size - 1, mhi->cols + aperture_size - 1, CV_32FC1 );
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CvMat* kernel = cvCreateMat( aperture_size, aperture_size, CV_32FC1 );
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CvMat* dx = cvCreateMat( mhi->rows, mhi->cols, CV_32FC1 );
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CvMat* dy = cvCreateMat( mhi->rows, mhi->cols, CV_32FC1 );
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CvMat* min_mhi = cvCreateMat( mhi->rows, mhi->cols, CV_32FC1 );
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CvMat* max_mhi = cvCreateMat( mhi->rows, mhi->cols, CV_32FC1 );
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IplConvKernel* element = cvCreateStructuringElementEx( aperture_size, aperture_size,
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aperture_size/2, aperture_size/2, CV_SHAPE_RECT );
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int i, j;
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double limit = 1e-4*aperture_size*aperture_size;
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cvTsPrepareToFilter( mhi, src, anchor );
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cvTsCalcSobelKernel2D( 1, 0, aperture_size, 0, kernel );
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cvTsConvolve2D( src, dx, kernel, anchor );
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cvTsCalcSobelKernel2D( 0, 1, aperture_size, 0, kernel );
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cvTsConvolve2D( src, dy, kernel, anchor );
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cvReleaseMat( &kernel );
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cvTsMinMaxFilter( src, min_mhi, element, CV_TS_MIN );
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cvTsMinMaxFilter( src, max_mhi, element, CV_TS_MAX );
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cvReleaseMat( &src );
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cvReleaseStructuringElement( &element );
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if( delta1 > delta2 )
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{
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double t;
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CV_SWAP( delta1, delta2, t );
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}
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for( i = 0; i < mhi->rows; i++ )
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{
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uchar* mask_row = mask->data.ptr + i*mask->step;
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float* orient_row = (float*)(orientation->data.ptr + i*orientation->step);
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const float* dx_row = (float*)(dx->data.ptr + i*dx->step);
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const float* dy_row = (float*)(dy->data.ptr + i*dy->step);
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const float* min_row = (float*)(min_mhi->data.ptr + i*min_mhi->step);
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const float* max_row = (float*)(max_mhi->data.ptr + i*max_mhi->step);
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for( j = 0; j < mhi->cols; j++ )
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{
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double delta = max_row[j] - min_row[j];
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double _dx = dx_row[j], _dy = dy_row[j];
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if( delta1 <= delta && delta <= delta2 &&
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(fabs(_dx) > limit || fabs(_dy) > limit) )
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{
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mask_row[j] = 1;
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double angle = atan2( _dy, _dx ) * (180/CV_PI);
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if( angle < 0 )
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angle += 360.;
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orient_row[j] = (float)angle;
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}
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else
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{
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mask_row[j] = 0;
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orient_row[j] = 0.f;
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}
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}
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}
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cvReleaseMat( &dx );
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cvReleaseMat( &dy );
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cvReleaseMat( &min_mhi );
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cvReleaseMat( &max_mhi );
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}
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class CV_MHIGradientTest : public CV_MHIBaseTest
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{
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public:
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CV_MHIGradientTest();
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protected:
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void get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types );
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void 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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void print_timing_params( int test_case_idx, char* ptr, int params_left );
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double get_success_error_level( int test_case_idx, int i, int j );
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void run_func();
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void prepare_to_validation( int );
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int write_default_params(CvFileStorage* fs);
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double delta1, delta2, delta_range_log;
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int aperture_size;
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};
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CV_MHIGradientTest::CV_MHIGradientTest()
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: CV_MHIBaseTest( "mhi-gradient", "cvCalcMotionGradient" )
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{
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mhi_i = mhi_ref_i = INPUT;
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test_array[INPUT].push(NULL);
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test_array[OUTPUT].push(NULL);
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test_array[OUTPUT].push(NULL);
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test_array[REF_OUTPUT].push(NULL);
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test_array[REF_OUTPUT].push(NULL);
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delta1 = delta2 = 0;
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aperture_size = 0;
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delta_range_log = 4;
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default_timing_param_names = motempl_gradient_param_names;
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}
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int CV_MHIGradientTest::write_default_params( CvFileStorage* fs )
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{
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int code = CvArrTest::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::TIMING_MODE )
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{
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start_write_param( fs );
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write_int_list( fs, "aperture", motempl_gradient_aperture, CV_DIM(motempl_gradient_aperture) );
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}
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return code;
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}
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void CV_MHIGradientTest::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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CV_MHIBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
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types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8UC1;
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types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_32FC1;
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delta1 = exp(cvTsRandReal(rng)*delta_range_log + 1.);
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delta2 = exp(cvTsRandReal(rng)*delta_range_log + 1.);
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aperture_size = (cvTsRandInt(rng)%3)*2+3;
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//duration = exp(cvTsRandReal(rng)*max_log_duration);
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//timestamp = duration + cvTsRandReal(rng)*30.-10.;
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}
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void CV_MHIGradientTest::get_timing_test_array_types_and_sizes( int test_case_idx,
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CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
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{
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CV_MHIBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
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whole_sizes, are_images );
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types[OUTPUT][0] = CV_8UC1;
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types[OUTPUT][1] = CV_32FC1;
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aperture_size = cvReadInt( find_timing_param( "aperture" ), 3 );
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delta1 = duration*0.02;
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delta2 = duration*0.2;
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}
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void CV_MHIGradientTest::print_timing_params( int test_case_idx, char* ptr, int params_left )
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{
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sprintf( ptr, "aperture=%d,", aperture_size );
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ptr += strlen(ptr);
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params_left--;
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CV_MHIBaseTest::print_timing_params( test_case_idx, ptr, params_left );
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}
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double CV_MHIGradientTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int j )
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{
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return j == 0 ? 0 : 2e-1;
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}
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void CV_MHIGradientTest::run_func()
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{
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cvCalcMotionGradient( test_array[INPUT][0], test_array[OUTPUT][0],
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test_array[OUTPUT][1], delta1, delta2, aperture_size );
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}
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void CV_MHIGradientTest::prepare_to_validation( int /*test_case_idx*/ )
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{
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cvTsMHIGradient( &test_mat[INPUT][0], &test_mat[REF_OUTPUT][0],
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&test_mat[REF_OUTPUT][1], delta1, delta2, aperture_size );
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cvTsAdd( &test_mat[REF_OUTPUT][1], cvScalarAll(1.), 0, cvScalarAll(0.),
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cvScalarAll(1.), &test_mat[REF_OUTPUT][1], 0 );
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cvTsAdd( &test_mat[OUTPUT][1], cvScalarAll(1.), 0, cvScalarAll(0.),
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cvScalarAll(1.), &test_mat[OUTPUT][1], 0 );
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}
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CV_MHIGradientTest mhi_gradient_test;
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////////////////////// calc global orientation /////////////////////////
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static double
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cvTsCalcGlobalOrientation( const CvMat* orient, const CvMat* mask, const CvMat* mhi,
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double timestamp, double duration )
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{
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const int HIST_SIZE = 12;
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int y, x;
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int histogram[HIST_SIZE];
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int max_bin = 0;
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double base_orientation = 0, delta_orientation = 0, weight = 0;
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double low_time, global_orientation;
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memset( histogram, 0, sizeof( histogram ));
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timestamp = 0;
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for( y = 0; y < orient->rows; y++ )
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{
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const float* orient_data = (const float*)(orient->data.ptr + y*orient->step);
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const uchar* mask_data = mask->data.ptr + y*mask->step;
|
|
const float* mhi_data = (const float*)(mhi->data.ptr + y*mhi->step);
|
|
for( x = 0; x < orient->cols; x++ )
|
|
if( mask_data[x] )
|
|
{
|
|
int bin = cvFloor( (orient_data[x]*HIST_SIZE)/360 );
|
|
histogram[bin < 0 ? 0 : bin >= HIST_SIZE ? HIST_SIZE-1 : bin]++;
|
|
if( mhi_data[x] > timestamp )
|
|
timestamp = mhi_data[x];
|
|
}
|
|
}
|
|
|
|
low_time = timestamp - duration;
|
|
|
|
for( x = 1; x < HIST_SIZE; x++ )
|
|
{
|
|
if( histogram[x] > histogram[max_bin] )
|
|
max_bin = x;
|
|
}
|
|
|
|
base_orientation = ((double)max_bin*360)/HIST_SIZE;
|
|
|
|
for( y = 0; y < orient->rows; y++ )
|
|
{
|
|
const float* orient_data = (const float*)(orient->data.ptr + y*orient->step);
|
|
const float* mhi_data = (const float*)(mhi->data.ptr + y*mhi->step);
|
|
const uchar* mask_data = mask->data.ptr + y*mask->step;
|
|
|
|
for( x = 0; x < orient->cols; x++ )
|
|
{
|
|
if( mask_data[x] && mhi_data[x] > low_time )
|
|
{
|
|
double diff = orient_data[x] - base_orientation;
|
|
double delta_weight = (((mhi_data[x] - low_time)/duration)*254 + 1)/255;
|
|
|
|
if( diff < -180 ) diff += 360;
|
|
if( diff > 180 ) diff -= 360;
|
|
|
|
if( delta_weight > 0 && fabs(diff) < 45 )
|
|
{
|
|
delta_orientation += diff*delta_weight;
|
|
weight += delta_weight;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
if( weight == 0 )
|
|
global_orientation = base_orientation;
|
|
else
|
|
{
|
|
global_orientation = base_orientation + delta_orientation/weight;
|
|
if( global_orientation < 0 ) global_orientation += 360;
|
|
if( global_orientation > 360 ) global_orientation -= 360;
|
|
}
|
|
|
|
return global_orientation;
|
|
}
|
|
|
|
|
|
class CV_MHIGlobalOrientTest : public CV_MHIBaseTest
|
|
{
|
|
public:
|
|
CV_MHIGlobalOrientTest();
|
|
|
|
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 get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high );
|
|
double get_success_error_level( int test_case_idx, int i, int j );
|
|
int validate_test_results( int test_case_idx );
|
|
void run_func();
|
|
double angle, min_angle, max_angle;
|
|
};
|
|
|
|
|
|
CV_MHIGlobalOrientTest::CV_MHIGlobalOrientTest()
|
|
: CV_MHIBaseTest( "mhi-global", "cvCalcGlobalOrientation" )
|
|
{
|
|
mhi_i = mhi_ref_i = INPUT;
|
|
test_array[INPUT].push(NULL);
|
|
test_array[INPUT].push(NULL);
|
|
test_array[INPUT].push(NULL);
|
|
min_angle = max_angle = 0;
|
|
|
|
default_timing_param_names = motempl_global_param_names;
|
|
}
|
|
|
|
|
|
void CV_MHIGlobalOrientTest::get_test_array_types_and_sizes( int test_case_idx, CvSize** sizes, int** types )
|
|
{
|
|
CvRNG* rng = ts->get_rng();
|
|
CV_MHIBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
|
|
CvSize size = sizes[INPUT][0];
|
|
|
|
size.width = MAX( size.width, 16 );
|
|
size.height = MAX( size.height, 16 );
|
|
sizes[INPUT][0] = sizes[INPUT][1] = sizes[INPUT][2] = size;
|
|
|
|
types[INPUT][1] = CV_8UC1; // mask
|
|
types[INPUT][2] = CV_32FC1; // orientation
|
|
|
|
min_angle = cvTsRandReal(rng)*359.9;
|
|
max_angle = cvTsRandReal(rng)*359.9;
|
|
if( min_angle >= max_angle )
|
|
{
|
|
double t;
|
|
CV_SWAP( min_angle, max_angle, t );
|
|
}
|
|
max_angle += 0.1;
|
|
duration = exp(cvTsRandReal(rng)*max_log_duration);
|
|
timestamp = duration + cvTsRandReal(rng)*30.-10.;
|
|
}
|
|
|
|
|
|
void CV_MHIGlobalOrientTest::get_timing_test_array_types_and_sizes( int test_case_idx,
|
|
CvSize** sizes, int** types, CvSize** whole_sizes, bool *are_images )
|
|
{
|
|
CV_MHIBaseTest::get_timing_test_array_types_and_sizes( test_case_idx, sizes, types,
|
|
whole_sizes, are_images );
|
|
types[INPUT][1] = CV_8UC1;
|
|
types[INPUT][2] = CV_32FC1;
|
|
}
|
|
|
|
|
|
void CV_MHIGlobalOrientTest::get_minmax_bounds( int i, int j, int type, CvScalar* low, CvScalar* high )
|
|
{
|
|
CV_MHIBaseTest::get_minmax_bounds( i, j, type, low, high );
|
|
if( i == INPUT && j == 2 )
|
|
{
|
|
*low = cvScalarAll(min_angle);
|
|
*high = cvScalarAll(max_angle);
|
|
}
|
|
}
|
|
|
|
|
|
double CV_MHIGlobalOrientTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
|
|
{
|
|
return 15;
|
|
}
|
|
|
|
|
|
void CV_MHIGlobalOrientTest::run_func()
|
|
{
|
|
angle = cvCalcGlobalOrientation( test_array[INPUT][2], test_array[INPUT][1],
|
|
test_array[INPUT][0], timestamp, duration );
|
|
}
|
|
|
|
|
|
int CV_MHIGlobalOrientTest::validate_test_results( int test_case_idx )
|
|
{
|
|
//printf("%d. rows=%d, cols=%d, nzmask=%d\n", test_case_idx, test_mat[INPUT][1].rows, test_mat[INPUT][1].cols,
|
|
// cvCountNonZero(test_array[INPUT][1]));
|
|
|
|
double ref_angle = cvTsCalcGlobalOrientation( &test_mat[INPUT][2], &test_mat[INPUT][1],
|
|
&test_mat[INPUT][0], timestamp, duration );
|
|
double err_level = get_success_error_level( test_case_idx, 0, 0 );
|
|
int code = CvTS::OK;
|
|
int nz = cvCountNonZero( test_array[INPUT][1] );
|
|
|
|
if( nz > 32 && !(min_angle - err_level <= angle &&
|
|
max_angle + err_level >= angle) &&
|
|
!(min_angle - err_level <= angle+360 &&
|
|
max_angle + err_level >= angle+360) )
|
|
{
|
|
ts->printf( CvTS::LOG, "The angle=%g is outside (%g,%g) range\n",
|
|
angle, min_angle - err_level, max_angle + err_level );
|
|
code = CvTS::FAIL_BAD_ACCURACY;
|
|
}
|
|
else if( fabs(angle - ref_angle) > err_level &&
|
|
fabs(360 - fabs(angle - ref_angle)) > err_level )
|
|
{
|
|
ts->printf( CvTS::LOG, "The angle=%g differs too much from reference value=%g\n",
|
|
angle, ref_angle );
|
|
code = CvTS::FAIL_BAD_ACCURACY;
|
|
}
|
|
|
|
if( code < 0 )
|
|
ts->set_failed_test_info( code );
|
|
return code;
|
|
}
|
|
|
|
|
|
CV_MHIGlobalOrientTest mhi_global_orient_test;
|
|
|