完善目录结构
完善了目录结构，添加了以前的web段com组件调用的代码（在/测试目录下）（部署没有使用到）
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yanshui177
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/*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 "_cv.h"
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/*F///////////////////////////////////////////////////////////////////////////////////////
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// Name: cvCreateConDensation
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// Purpose: Creating CvConDensation structure and allocating memory for it
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// Context:
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// Parameters:
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// Kalman - double pointer to CvConDensation structure
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// DP - dimension of the dynamical vector
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// MP - dimension of the measurement vector
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// SamplesNum - number of samples in sample set used in algorithm
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// Returns:
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// Notes:
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//
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//F*/
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CV_IMPL CvConDensation* cvCreateConDensation( int DP, int MP, int SamplesNum )
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{
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int i;
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CvConDensation *CD = 0;
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CV_FUNCNAME( "cvCreateConDensation" );
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__BEGIN__;
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if( DP < 0 || MP < 0 || SamplesNum < 0 )
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CV_ERROR( CV_StsOutOfRange, "" );
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/* allocating memory for the structure */
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CV_CALL( CD = (CvConDensation *) cvAlloc( sizeof( CvConDensation )));
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/* setting structure params */
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CD->SamplesNum = SamplesNum;
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CD->DP = DP;
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CD->MP = MP;
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/* allocating memory for structure fields */
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CV_CALL( CD->flSamples = (float **) cvAlloc( sizeof( float * ) * SamplesNum ));
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CV_CALL( CD->flNewSamples = (float **) cvAlloc( sizeof( float * ) * SamplesNum ));
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CV_CALL( CD->flSamples[0] = (float *) cvAlloc( sizeof( float ) * SamplesNum * DP ));
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CV_CALL( CD->flNewSamples[0] = (float *) cvAlloc( sizeof( float ) * SamplesNum * DP ));
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/* setting pointers in pointer's arrays */
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for( i = 1; i < SamplesNum; i++ )
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{
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CD->flSamples[i] = CD->flSamples[i - 1] + DP;
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CD->flNewSamples[i] = CD->flNewSamples[i - 1] + DP;
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}
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CV_CALL( CD->State = (float *) cvAlloc( sizeof( float ) * DP ));
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CV_CALL( CD->DynamMatr = (float *) cvAlloc( sizeof( float ) * DP * DP ));
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CV_CALL( CD->flConfidence = (float *) cvAlloc( sizeof( float ) * SamplesNum ));
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CV_CALL( CD->flCumulative = (float *) cvAlloc( sizeof( float ) * SamplesNum ));
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CV_CALL( CD->RandS = (CvRandState *) cvAlloc( sizeof( CvRandState ) * DP ));
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CV_CALL( CD->Temp = (float *) cvAlloc( sizeof( float ) * DP ));
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CV_CALL( CD->RandomSample = (float *) cvAlloc( sizeof( float ) * DP ));
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/* Returning created structure */
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__END__;
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return CD;
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}
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/*F///////////////////////////////////////////////////////////////////////////////////////
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// Name: cvReleaseConDensation
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// Purpose: Releases CvConDensation structure and frees memory allocated for it
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// Context:
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// Parameters:
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// Kalman - double pointer to CvConDensation structure
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// DP - dimension of the dynamical vector
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// MP - dimension of the measurement vector
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// SamplesNum - number of samples in sample set used in algorithm
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// Returns:
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// Notes:
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//
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//F*/
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CV_IMPL void
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cvReleaseConDensation( CvConDensation ** ConDensation )
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{
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CV_FUNCNAME( "cvReleaseConDensation" );
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__BEGIN__;
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CvConDensation *CD = *ConDensation;
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if( !ConDensation )
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CV_ERROR( CV_StsNullPtr, "" );
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if( !CD )
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EXIT;
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/* freeing the memory */
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cvFree( &CD->State );
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cvFree( &CD->DynamMatr);
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cvFree( &CD->flConfidence );
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cvFree( &CD->flCumulative );
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cvFree( &CD->flSamples[0] );
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cvFree( &CD->flNewSamples[0] );
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cvFree( &CD->flSamples );
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cvFree( &CD->flNewSamples );
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cvFree( &CD->Temp );
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cvFree( &CD->RandS );
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cvFree( &CD->RandomSample );
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/* release structure */
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cvFree( ConDensation );
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__END__;
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}
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/*F///////////////////////////////////////////////////////////////////////////////////////
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// Name: cvConDensUpdateByTime
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// Purpose: Performing Time Update routine for ConDensation algorithm
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// Context:
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// Parameters:
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// Kalman - pointer to CvConDensation structure
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// Returns:
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// Notes:
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//
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//F*/
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CV_IMPL void
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cvConDensUpdateByTime( CvConDensation * ConDens )
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{
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int i, j;
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float Sum = 0;
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CV_FUNCNAME( "cvConDensUpdateByTime" );
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__BEGIN__;
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if( !ConDens )
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CV_ERROR( CV_StsNullPtr, "" );
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/* Sets Temp to Zero */
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icvSetZero_32f( ConDens->Temp, ConDens->DP, 1 );
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/* Calculating the Mean */
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for( i = 0; i < ConDens->SamplesNum; i++ )
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{
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icvScaleVector_32f( ConDens->flSamples[i], ConDens->State, ConDens->DP,
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ConDens->flConfidence[i] );
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icvAddVector_32f( ConDens->Temp, ConDens->State, ConDens->Temp, ConDens->DP );
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Sum += ConDens->flConfidence[i];
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ConDens->flCumulative[i] = Sum;
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}
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/* Taking the new vector from transformation of mean by dynamics matrix */
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icvScaleVector_32f( ConDens->Temp, ConDens->Temp, ConDens->DP, 1.f / Sum );
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icvTransformVector_32f( ConDens->DynamMatr, ConDens->Temp, ConDens->State, ConDens->DP,
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ConDens->DP );
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Sum = Sum / ConDens->SamplesNum;
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/* Updating the set of random samples */
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for( i = 0; i < ConDens->SamplesNum; i++ )
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{
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j = 0;
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while( (ConDens->flCumulative[j] <= (float) i * Sum)&&(j<ConDens->SamplesNum-1))
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{
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j++;
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}
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icvCopyVector_32f( ConDens->flSamples[j], ConDens->DP, ConDens->flNewSamples[i] );
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}
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/* Adding the random-generated vector to every vector in sample set */
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for( i = 0; i < ConDens->SamplesNum; i++ )
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{
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for( j = 0; j < ConDens->DP; j++ )
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{
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cvbRand( ConDens->RandS + j, ConDens->RandomSample + j, 1 );
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}
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icvTransformVector_32f( ConDens->DynamMatr, ConDens->flNewSamples[i],
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ConDens->flSamples[i], ConDens->DP, ConDens->DP );
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icvAddVector_32f( ConDens->flSamples[i], ConDens->RandomSample, ConDens->flSamples[i],
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ConDens->DP );
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}
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__END__;
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}
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/*F///////////////////////////////////////////////////////////////////////////////////////
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// Name: cvConDensInitSamplSet
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// Purpose: Performing Time Update routine for ConDensation algorithm
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// Context:
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// Parameters:
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// conDens - pointer to CvConDensation structure
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// lowerBound - vector of lower bounds used to random update of sample set
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// lowerBound - vector of upper bounds used to random update of sample set
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// Returns:
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// Notes:
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//
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//F*/
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CV_IMPL void
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cvConDensInitSampleSet( CvConDensation * conDens, CvMat * lowerBound, CvMat * upperBound )
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{
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int i, j;
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float *LBound;
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float *UBound;
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float Prob = 1.f / conDens->SamplesNum;
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CV_FUNCNAME( "cvConDensInitSampleSet" );
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__BEGIN__;
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if( !conDens || !lowerBound || !upperBound )
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CV_ERROR( CV_StsNullPtr, "" );
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if( CV_MAT_TYPE(lowerBound->type) != CV_32FC1 ||
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!CV_ARE_TYPES_EQ(lowerBound,upperBound) )
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CV_ERROR( CV_StsBadArg, "source has not appropriate format" );
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if( (lowerBound->cols != 1) || (upperBound->cols != 1) )
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CV_ERROR( CV_StsBadArg, "source has not appropriate size" );
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if( (lowerBound->rows != conDens->DP) || (upperBound->rows != conDens->DP) )
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CV_ERROR( CV_StsBadArg, "source has not appropriate size" );
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LBound = lowerBound->data.fl;
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UBound = upperBound->data.fl;
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/* Initializing the structures to create initial Sample set */
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for( i = 0; i < conDens->DP; i++ )
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{
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cvRandInit( &(conDens->RandS[i]),
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LBound[i],
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UBound[i],
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i );
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}
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/* Generating the samples */
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for( j = 0; j < conDens->SamplesNum; j++ )
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{
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for( i = 0; i < conDens->DP; i++ )
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{
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cvbRand( conDens->RandS + i, conDens->flSamples[j] + i, 1 );
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}
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conDens->flConfidence[j] = Prob;
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}
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/* Reinitializes the structures to update samples randomly */
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for( i = 0; i < conDens->DP; i++ )
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{
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cvRandInit( &(conDens->RandS[i]),
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(LBound[i] - UBound[i]) / 5,
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(UBound[i] - LBound[i]) / 5,
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i);
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}
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__END__;
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}
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