2010-05-12 01:44:00 +08:00
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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 "precomp.hpp"
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2012-06-08 01:21:29 +08:00
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static CvStatus
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2010-05-12 01:44:00 +08:00
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icvJacobiEigens_32f(float *A, float *V, float *E, int n, float eps)
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{
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int i, j, k, ind;
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float *AA = A, *VV = V;
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double Amax, anorm = 0, ax;
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if( A == NULL || V == NULL || E == NULL )
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return CV_NULLPTR_ERR;
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if( n <= 0 )
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return CV_BADSIZE_ERR;
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if( eps < 1.0e-7f )
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eps = 1.0e-7f;
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/*-------- Prepare --------*/
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for( i = 0; i < n; i++, VV += n, AA += n )
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{
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for( j = 0; j < i; j++ )
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{
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double Am = AA[j];
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anorm += Am * Am;
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}
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for( j = 0; j < n; j++ )
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VV[j] = 0.f;
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VV[i] = 1.f;
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}
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anorm = sqrt( anorm + anorm );
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ax = anorm * eps / n;
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Amax = anorm;
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while( Amax > ax )
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{
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Amax /= n;
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do /* while (ind) */
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{
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int p, q;
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float *V1 = V, *A1 = A;
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ind = 0;
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for( p = 0; p < n - 1; p++, A1 += n, V1 += n )
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{
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float *A2 = A + n * (p + 1), *V2 = V + n * (p + 1);
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for( q = p + 1; q < n; q++, A2 += n, V2 += n )
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{
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double x, y, c, s, c2, s2, a;
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float *A3, Apq = A1[q], App, Aqq, Aip, Aiq, Vpi, Vqi;
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if( fabs( Apq ) < Amax )
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continue;
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ind = 1;
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/*---- Calculation of rotation angle's sine & cosine ----*/
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App = A1[p];
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Aqq = A2[q];
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y = 5.0e-1 * (App - Aqq);
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x = -Apq / sqrt( (double)Apq * Apq + (double)y * y );
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if( y < 0.0 )
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x = -x;
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s = x / sqrt( 2.0 * (1.0 + sqrt( 1.0 - (double)x * x )));
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s2 = s * s;
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c = sqrt( 1.0 - s2 );
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c2 = c * c;
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a = 2.0 * Apq * c * s;
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/*---- Apq annulation ----*/
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A3 = A;
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for( i = 0; i < p; i++, A3 += n )
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{
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Aip = A3[p];
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Aiq = A3[q];
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Vpi = V1[i];
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Vqi = V2[i];
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A3[p] = (float) (Aip * c - Aiq * s);
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A3[q] = (float) (Aiq * c + Aip * s);
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V1[i] = (float) (Vpi * c - Vqi * s);
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V2[i] = (float) (Vqi * c + Vpi * s);
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}
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for( ; i < q; i++, A3 += n )
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{
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Aip = A1[i];
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Aiq = A3[q];
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Vpi = V1[i];
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Vqi = V2[i];
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A1[i] = (float) (Aip * c - Aiq * s);
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A3[q] = (float) (Aiq * c + Aip * s);
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V1[i] = (float) (Vpi * c - Vqi * s);
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V2[i] = (float) (Vqi * c + Vpi * s);
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}
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for( ; i < n; i++ )
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{
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Aip = A1[i];
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Aiq = A2[i];
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Vpi = V1[i];
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Vqi = V2[i];
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A1[i] = (float) (Aip * c - Aiq * s);
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A2[i] = (float) (Aiq * c + Aip * s);
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V1[i] = (float) (Vpi * c - Vqi * s);
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V2[i] = (float) (Vqi * c + Vpi * s);
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}
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A1[p] = (float) (App * c2 + Aqq * s2 - a);
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A2[q] = (float) (App * s2 + Aqq * c2 + a);
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A1[q] = A2[p] = 0.0f;
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} /*q */
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} /*p */
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}
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while( ind );
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Amax /= n;
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} /* while ( Amax > ax ) */
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for( i = 0, k = 0; i < n; i++, k += n + 1 )
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E[i] = A[k];
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/*printf(" M = %d\n", M); */
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/* -------- ordering -------- */
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for( i = 0; i < n; i++ )
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{
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int m = i;
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float Em = (float) fabs( E[i] );
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for( j = i + 1; j < n; j++ )
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{
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float Ej = (float) fabs( E[j] );
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m = (Em < Ej) ? j : m;
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Em = (Em < Ej) ? Ej : Em;
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}
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if( m != i )
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{
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int l;
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float b = E[i];
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E[i] = E[m];
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E[m] = b;
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for( j = 0, k = i * n, l = m * n; j < n; j++, k++, l++ )
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{
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b = V[k];
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V[k] = V[l];
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V[l] = b;
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}
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}
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}
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return CV_NO_ERR;
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}
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/*F///////////////////////////////////////////////////////////////////////////////////////
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// Name: icvCalcCovarMatrixEx_8u32fR
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// Purpose: The function calculates a covariance matrix for a group of input objects
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// (images, vectors, etc.). ROI supported.
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// Context:
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// Parameters: nObjects - number of source objects
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// objects - array of pointers to ROIs of the source objects
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// imgStep - full width of each source object row in bytes
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// avg - pointer to averaged object
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// avgStep - full width of averaged object row in bytes
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// size - ROI size of each source and averaged objects
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// covarMatrix - covariance matrix (output parameter; must be allocated
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// before call)
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//
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// Returns: CV_NO_ERR or error code
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//
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// Notes:
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//F*/
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static CvStatus CV_STDCALL
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icvCalcCovarMatrixEx_8u32fR( int nObjects, void *input, int objStep1,
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int ioFlags, int ioBufSize, uchar* buffer,
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void *userData, float *avg, int avgStep,
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CvSize size, float *covarMatrix )
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{
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int objStep = objStep1;
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/* ---- TEST OF PARAMETERS ---- */
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if( nObjects < 2 )
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return CV_BADFACTOR_ERR;
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if( ioFlags < 0 || ioFlags > 3 )
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return CV_BADFACTOR_ERR;
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if( ioFlags && ioBufSize < 1024 )
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return CV_BADFACTOR_ERR;
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if( ioFlags && buffer == NULL )
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return CV_NULLPTR_ERR;
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if( input == NULL || avg == NULL || covarMatrix == NULL )
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return CV_NULLPTR_ERR;
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if( size.width > objStep || 4 * size.width > avgStep || size.height < 1 )
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return CV_BADSIZE_ERR;
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avgStep /= 4;
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if( ioFlags & CV_EIGOBJ_INPUT_CALLBACK ) /* ==== USE INPUT CALLBACK ==== */
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{
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int nio, ngr, igr, n = size.width * size.height, mm = 0;
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CvCallback read_callback = ((CvInput *) & input)->callback;
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uchar *buffer2;
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objStep = n;
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nio = ioBufSize / n; /* number of objects in buffer */
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ngr = nObjects / nio; /* number of io groups */
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if( nObjects % nio )
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mm = 1;
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ngr += mm;
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buffer2 = (uchar *)cvAlloc( sizeof( uchar ) * n );
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if( buffer2 == NULL )
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return CV_OUTOFMEM_ERR;
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for( igr = 0; igr < ngr; igr++ )
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{
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int k, l;
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int io, jo, imin = igr * nio, imax = imin + nio;
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uchar *bu1 = buffer, *bu2;
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if( imax > nObjects )
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imax = nObjects;
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/* read igr group */
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for( io = imin; io < imax; io++, bu1 += n )
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{
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CvStatus r;
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r = (CvStatus)read_callback( io, (void *) bu1, userData );
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if( r )
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return r;
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}
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/* diagonal square calc */
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bu1 = buffer;
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for( io = imin; io < imax; io++, bu1 += n )
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{
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bu2 = bu1;
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for( jo = io; jo < imax; jo++, bu2 += n )
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{
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float w = 0.f;
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float *fu = avg;
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int ij = 0;
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for( k = 0; k < size.height; k++, fu += avgStep )
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for( l = 0; l < size.width; l++, ij++ )
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{
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float f = fu[l], u1 = bu1[ij], u2 = bu2[ij];
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w += (u1 - f) * (u2 - f);
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}
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covarMatrix[io * nObjects + jo] = covarMatrix[jo * nObjects + io] = w;
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}
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}
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/* non-diagonal elements calc */
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for( jo = imax; jo < nObjects; jo++ )
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{
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CvStatus r;
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bu1 = buffer;
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bu2 = buffer2;
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/* read jo object */
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r = (CvStatus)read_callback( jo, (void *) bu2, userData );
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if( r )
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return r;
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for( io = imin; io < imax; io++, bu1 += n )
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{
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float w = 0.f;
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float *fu = avg;
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int ij = 0;
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for( k = 0; k < size.height; k++, fu += avgStep )
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{
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for( l = 0; l < size.width - 3; l += 4, ij += 4 )
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{
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float f = fu[l];
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uchar u1 = bu1[ij];
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uchar u2 = bu2[ij];
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w += (u1 - f) * (u2 - f);
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f = fu[l + 1];
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u1 = bu1[ij + 1];
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u2 = bu2[ij + 1];
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w += (u1 - f) * (u2 - f);
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f = fu[l + 2];
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u1 = bu1[ij + 2];
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u2 = bu2[ij + 2];
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w += (u1 - f) * (u2 - f);
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f = fu[l + 3];
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u1 = bu1[ij + 3];
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u2 = bu2[ij + 3];
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w += (u1 - f) * (u2 - f);
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}
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for( ; l < size.width; l++, ij++ )
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{
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float f = fu[l], u1 = bu1[ij], u2 = bu2[ij];
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w += (u1 - f) * (u2 - f);
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}
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}
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covarMatrix[io * nObjects + jo] = covarMatrix[jo * nObjects + io] = w;
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}
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}
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} /* igr */
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cvFree( &buffer2 );
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} /* if() */
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else
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/* ==== NOT USE INPUT CALLBACK ==== */
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{
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int i, j;
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uchar **objects = (uchar **) (((CvInput *) & input)->data);
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for( i = 0; i < nObjects; i++ )
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{
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uchar *bu = objects[i];
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for( j = i; j < nObjects; j++ )
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{
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int k, l;
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float w = 0.f;
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float *a = avg;
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uchar *bu1 = bu;
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uchar *bu2 = objects[j];
|
|
|
|
|
|
|
|
for( k = 0; k < size.height;
|
|
|
|
k++, bu1 += objStep, bu2 += objStep, a += avgStep )
|
|
|
|
{
|
|
|
|
for( l = 0; l < size.width - 3; l += 4 )
|
|
|
|
{
|
|
|
|
float f = a[l];
|
|
|
|
uchar u1 = bu1[l];
|
|
|
|
uchar u2 = bu2[l];
|
|
|
|
|
|
|
|
w += (u1 - f) * (u2 - f);
|
|
|
|
f = a[l + 1];
|
|
|
|
u1 = bu1[l + 1];
|
|
|
|
u2 = bu2[l + 1];
|
|
|
|
w += (u1 - f) * (u2 - f);
|
|
|
|
f = a[l + 2];
|
|
|
|
u1 = bu1[l + 2];
|
|
|
|
u2 = bu2[l + 2];
|
|
|
|
w += (u1 - f) * (u2 - f);
|
|
|
|
f = a[l + 3];
|
|
|
|
u1 = bu1[l + 3];
|
|
|
|
u2 = bu2[l + 3];
|
|
|
|
w += (u1 - f) * (u2 - f);
|
|
|
|
}
|
|
|
|
for( ; l < size.width; l++ )
|
|
|
|
{
|
|
|
|
float f = a[l];
|
|
|
|
uchar u1 = bu1[l];
|
|
|
|
uchar u2 = bu2[l];
|
|
|
|
|
|
|
|
w += (u1 - f) * (u2 - f);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
covarMatrix[i * nObjects + j] = covarMatrix[j * nObjects + i] = w;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
} /* else */
|
|
|
|
|
|
|
|
return CV_NO_ERR;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*======================== end of icvCalcCovarMatrixEx_8u32fR ===========================*/
|
|
|
|
|
|
|
|
|
|
|
|
static int
|
|
|
|
icvDefaultBufferSize( void )
|
|
|
|
{
|
|
|
|
return 10 * 1024 * 1024;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Name: icvCalcEigenObjects_8u32fR
|
|
|
|
// Purpose: The function calculates an orthonormal eigen basis and a mean (averaged)
|
|
|
|
// object for a group of input objects (images, vectors, etc.). ROI supported.
|
|
|
|
// Context:
|
|
|
|
// Parameters: nObjects - number of source objects
|
|
|
|
// input - pointer either to array of pointers to input objects
|
|
|
|
// or to read callback function (depending on ioFlags)
|
|
|
|
// imgStep - full width of each source object row in bytes
|
|
|
|
// output - pointer either to array of pointers to output eigen objects
|
|
|
|
// or to write callback function (depending on ioFlags)
|
|
|
|
// eigStep - full width of each eigenobject row in bytes
|
|
|
|
// size - ROI size of each source object
|
|
|
|
// ioFlags - input/output flags (see Notes)
|
|
|
|
// ioBufSize - input/output buffer size
|
|
|
|
// userData - pointer to the structure which contains all necessary
|
|
|
|
// data for the callback functions
|
|
|
|
// calcLimit - determines the calculation finish conditions
|
|
|
|
// avg - pointer to averaged object (has the same size as ROI)
|
|
|
|
// avgStep - full width of averaged object row in bytes
|
|
|
|
// eigVals - pointer to corresponding eigenvalues (array of <nObjects>
|
|
|
|
// elements in descending order)
|
|
|
|
//
|
|
|
|
// Returns: CV_NO_ERR or error code
|
|
|
|
//
|
|
|
|
// Notes: 1. input/output data (that is, input objects and eigen ones) may either
|
|
|
|
// be allocated in the RAM or be read from/written to the HDD (or any
|
|
|
|
// other device) by read/write callback functions. It depends on the
|
|
|
|
// value of ioFlags paramater, which may be the following:
|
|
|
|
// CV_EIGOBJ_NO_CALLBACK, or 0;
|
|
|
|
// CV_EIGOBJ_INPUT_CALLBACK;
|
|
|
|
// CV_EIGOBJ_OUTPUT_CALLBACK;
|
|
|
|
// CV_EIGOBJ_BOTH_CALLBACK, or
|
|
|
|
// CV_EIGOBJ_INPUT_CALLBACK | CV_EIGOBJ_OUTPUT_CALLBACK.
|
|
|
|
// The callback functions as well as the user data structure must be
|
|
|
|
// developed by the user.
|
|
|
|
//
|
|
|
|
// 2. If ioBufSize = 0, or it's too large, the function dermines buffer size
|
|
|
|
// itself.
|
|
|
|
//
|
|
|
|
// 3. Depending on calcLimit parameter, calculations are finished either if
|
|
|
|
// eigenfaces number comes up to certain value or the relation of the
|
|
|
|
// current eigenvalue and the largest one comes down to certain value
|
|
|
|
// (or any of the above conditions takes place). The calcLimit->type value
|
|
|
|
// must be CV_TERMCRIT_NUMB, CV_TERMCRIT_EPS or
|
|
|
|
// CV_TERMCRIT_NUMB | CV_TERMCRIT_EPS. The function returns the real
|
|
|
|
// values calcLimit->max_iter and calcLimit->epsilon.
|
|
|
|
//
|
|
|
|
// 4. eigVals may be equal to NULL (if you don't need eigen values in further).
|
|
|
|
//
|
|
|
|
//F*/
|
|
|
|
static CvStatus CV_STDCALL
|
|
|
|
icvCalcEigenObjects_8u32fR( int nObjects, void* input, int objStep,
|
|
|
|
void* output, int eigStep, CvSize size,
|
|
|
|
int ioFlags, int ioBufSize, void* userData,
|
|
|
|
CvTermCriteria* calcLimit, float* avg,
|
|
|
|
int avgStep, float *eigVals )
|
|
|
|
{
|
|
|
|
int i, j, n, iev = 0, m1 = nObjects - 1, objStep1 = objStep, eigStep1 = eigStep / 4;
|
|
|
|
CvSize objSize, eigSize, avgSize;
|
|
|
|
float *c = 0;
|
|
|
|
float *ev = 0;
|
|
|
|
float *bf = 0;
|
|
|
|
uchar *buf = 0;
|
|
|
|
void *buffer = 0;
|
|
|
|
float m = 1.0f / (float) nObjects;
|
|
|
|
CvStatus r;
|
|
|
|
|
|
|
|
if( m1 > calcLimit->max_iter && calcLimit->type != CV_TERMCRIT_EPS )
|
|
|
|
m1 = calcLimit->max_iter;
|
|
|
|
|
|
|
|
/* ---- TEST OF PARAMETERS ---- */
|
|
|
|
|
|
|
|
if( nObjects < 2 )
|
|
|
|
return CV_BADFACTOR_ERR;
|
|
|
|
if( ioFlags < 0 || ioFlags > 3 )
|
|
|
|
return CV_BADFACTOR_ERR;
|
|
|
|
if( input == NULL || output == NULL || avg == NULL )
|
|
|
|
return CV_NULLPTR_ERR;
|
|
|
|
if( size.width > objStep || 4 * size.width > eigStep ||
|
|
|
|
4 * size.width > avgStep || size.height < 1 )
|
|
|
|
return CV_BADSIZE_ERR;
|
|
|
|
if( !(ioFlags & CV_EIGOBJ_INPUT_CALLBACK) )
|
|
|
|
for( i = 0; i < nObjects; i++ )
|
|
|
|
if( ((uchar **) input)[i] == NULL )
|
|
|
|
return CV_NULLPTR_ERR;
|
|
|
|
if( !(ioFlags & CV_EIGOBJ_OUTPUT_CALLBACK) )
|
|
|
|
for( i = 0; i < m1; i++ )
|
|
|
|
if( ((float **) output)[i] == NULL )
|
|
|
|
return CV_NULLPTR_ERR;
|
|
|
|
|
|
|
|
avgStep /= 4;
|
|
|
|
eigStep /= 4;
|
|
|
|
|
|
|
|
if( objStep == size.width && eigStep == size.width && avgStep == size.width )
|
|
|
|
{
|
|
|
|
size.width *= size.height;
|
|
|
|
size.height = 1;
|
|
|
|
objStep = objStep1 = eigStep = eigStep1 = avgStep = size.width;
|
|
|
|
}
|
|
|
|
objSize = eigSize = avgSize = size;
|
|
|
|
|
|
|
|
if( ioFlags & CV_EIGOBJ_INPUT_CALLBACK )
|
|
|
|
{
|
|
|
|
objSize.width *= objSize.height;
|
|
|
|
objSize.height = 1;
|
|
|
|
objStep = objSize.width;
|
|
|
|
objStep1 = size.width;
|
|
|
|
}
|
|
|
|
|
|
|
|
if( ioFlags & CV_EIGOBJ_OUTPUT_CALLBACK )
|
|
|
|
{
|
|
|
|
eigSize.width *= eigSize.height;
|
|
|
|
eigSize.height = 1;
|
|
|
|
eigStep = eigSize.width;
|
|
|
|
eigStep1 = size.width;
|
|
|
|
}
|
|
|
|
|
|
|
|
n = objSize.height * objSize.width * (ioFlags & CV_EIGOBJ_INPUT_CALLBACK) +
|
|
|
|
2 * eigSize.height * eigSize.width * (ioFlags & CV_EIGOBJ_OUTPUT_CALLBACK);
|
|
|
|
|
|
|
|
/* Buffer size determination */
|
|
|
|
if( ioFlags )
|
|
|
|
{
|
|
|
|
int size = icvDefaultBufferSize();
|
|
|
|
ioBufSize = MIN( size, n );
|
|
|
|
}
|
|
|
|
|
|
|
|
/* memory allocation (if necesseay) */
|
|
|
|
|
|
|
|
if( ioFlags & CV_EIGOBJ_INPUT_CALLBACK )
|
|
|
|
{
|
|
|
|
buf = (uchar *) cvAlloc( sizeof( uchar ) * objSize.width );
|
|
|
|
if( buf == NULL )
|
|
|
|
return CV_OUTOFMEM_ERR;
|
|
|
|
}
|
|
|
|
|
|
|
|
if( ioFlags )
|
|
|
|
{
|
|
|
|
buffer = (void *) cvAlloc( ioBufSize );
|
|
|
|
if( buffer == NULL )
|
|
|
|
{
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return CV_OUTOFMEM_ERR;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
/* Calculation of averaged object */
|
|
|
|
bf = avg;
|
|
|
|
for( i = 0; i < avgSize.height; i++, bf += avgStep )
|
|
|
|
for( j = 0; j < avgSize.width; j++ )
|
|
|
|
bf[j] = 0.f;
|
|
|
|
|
|
|
|
for( i = 0; i < nObjects; i++ )
|
|
|
|
{
|
|
|
|
int k, l;
|
|
|
|
uchar *bu = (ioFlags & CV_EIGOBJ_INPUT_CALLBACK) ? buf : ((uchar **) input)[i];
|
|
|
|
|
|
|
|
if( ioFlags & CV_EIGOBJ_INPUT_CALLBACK )
|
|
|
|
{
|
|
|
|
CvCallback read_callback = ((CvInput *) & input)->callback;
|
|
|
|
|
|
|
|
r = (CvStatus)read_callback( i, (void *) buf, userData );
|
|
|
|
if( r )
|
|
|
|
{
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return r;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
bf = avg;
|
|
|
|
for( k = 0; k < avgSize.height; k++, bf += avgStep, bu += objStep1 )
|
|
|
|
for( l = 0; l < avgSize.width; l++ )
|
|
|
|
bf[l] += bu[l];
|
|
|
|
}
|
|
|
|
|
|
|
|
bf = avg;
|
|
|
|
for( i = 0; i < avgSize.height; i++, bf += avgStep )
|
|
|
|
for( j = 0; j < avgSize.width; j++ )
|
|
|
|
bf[j] *= m;
|
|
|
|
|
|
|
|
/* Calculation of covariance matrix */
|
|
|
|
c = (float *) cvAlloc( sizeof( float ) * nObjects * nObjects );
|
|
|
|
|
|
|
|
if( c == NULL )
|
|
|
|
{
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return CV_OUTOFMEM_ERR;
|
|
|
|
}
|
|
|
|
|
|
|
|
r = icvCalcCovarMatrixEx_8u32fR( nObjects, input, objStep1, ioFlags, ioBufSize,
|
|
|
|
(uchar *) buffer, userData, avg, 4 * avgStep, size, c );
|
|
|
|
if( r )
|
|
|
|
{
|
|
|
|
cvFree( &c );
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return r;
|
|
|
|
}
|
|
|
|
|
|
|
|
/* Calculation of eigenvalues & eigenvectors */
|
|
|
|
ev = (float *) cvAlloc( sizeof( float ) * nObjects * nObjects );
|
|
|
|
|
|
|
|
if( ev == NULL )
|
|
|
|
{
|
|
|
|
cvFree( &c );
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return CV_OUTOFMEM_ERR;
|
|
|
|
}
|
|
|
|
|
|
|
|
if( eigVals == NULL )
|
|
|
|
{
|
|
|
|
eigVals = (float *) cvAlloc( sizeof( float ) * nObjects );
|
|
|
|
|
|
|
|
if( eigVals == NULL )
|
|
|
|
{
|
|
|
|
cvFree( &c );
|
|
|
|
cvFree( &ev );
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return CV_OUTOFMEM_ERR;
|
|
|
|
}
|
|
|
|
iev = 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
r = icvJacobiEigens_32f( c, ev, eigVals, nObjects, 0.0f );
|
|
|
|
cvFree( &c );
|
|
|
|
if( r )
|
|
|
|
{
|
|
|
|
cvFree( &ev );
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
if( iev )
|
|
|
|
cvFree( &eigVals );
|
|
|
|
return r;
|
|
|
|
}
|
|
|
|
|
|
|
|
/* Eigen objects number determination */
|
|
|
|
if( calcLimit->type != CV_TERMCRIT_NUMBER )
|
|
|
|
{
|
|
|
|
for( i = 0; i < m1; i++ )
|
|
|
|
if( fabs( eigVals[i] / eigVals[0] ) < calcLimit->epsilon )
|
|
|
|
break;
|
|
|
|
m1 = calcLimit->max_iter = i;
|
|
|
|
}
|
|
|
|
else
|
|
|
|
m1 = calcLimit->max_iter;
|
|
|
|
calcLimit->epsilon = (float) fabs( eigVals[m1 - 1] / eigVals[0] );
|
|
|
|
|
|
|
|
for( i = 0; i < m1; i++ )
|
|
|
|
eigVals[i] = (float) (1.0 / sqrt( (double)eigVals[i] ));
|
|
|
|
|
|
|
|
/* ----------------- Calculation of eigenobjects ----------------------- */
|
|
|
|
if( ioFlags & CV_EIGOBJ_OUTPUT_CALLBACK )
|
|
|
|
{
|
|
|
|
int nio, ngr, igr;
|
|
|
|
|
|
|
|
nio = ioBufSize / (4 * eigSize.width); /* number of eigen objects in buffer */
|
|
|
|
ngr = m1 / nio; /* number of io groups */
|
|
|
|
if( nObjects % nio )
|
|
|
|
ngr += 1;
|
|
|
|
|
|
|
|
for( igr = 0; igr < ngr; igr++ )
|
|
|
|
{
|
|
|
|
int i, io, ie, imin = igr * nio, imax = imin + nio;
|
|
|
|
|
|
|
|
if( imax > m1 )
|
|
|
|
imax = m1;
|
|
|
|
|
|
|
|
for( i = 0; i < eigSize.width * (imax - imin); i++ )
|
|
|
|
((float *) buffer)[i] = 0.f;
|
|
|
|
|
|
|
|
for( io = 0; io < nObjects; io++ )
|
|
|
|
{
|
|
|
|
uchar *bu = ioFlags & CV_EIGOBJ_INPUT_CALLBACK ? buf : ((uchar **) input)[io];
|
|
|
|
|
|
|
|
if( ioFlags & CV_EIGOBJ_INPUT_CALLBACK )
|
|
|
|
{
|
|
|
|
CvCallback read_callback = ((CvInput *) & input)->callback;
|
|
|
|
|
|
|
|
r = (CvStatus)read_callback( io, (void *) buf, userData );
|
|
|
|
if( r )
|
|
|
|
{
|
|
|
|
cvFree( &ev );
|
|
|
|
if( iev )
|
|
|
|
cvFree( &eigVals );
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return r;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
for( ie = imin; ie < imax; ie++ )
|
|
|
|
{
|
|
|
|
int k, l;
|
|
|
|
uchar *bv = bu;
|
|
|
|
float e = ev[ie * nObjects + io] * eigVals[ie];
|
|
|
|
float *be = ((float *) buffer) + ((ie - imin) * eigStep);
|
|
|
|
|
|
|
|
bf = avg;
|
|
|
|
for( k = 0; k < size.height; k++, bv += objStep1,
|
|
|
|
bf += avgStep, be += eigStep1 )
|
|
|
|
{
|
|
|
|
for( l = 0; l < size.width - 3; l += 4 )
|
|
|
|
{
|
|
|
|
float f = bf[l];
|
|
|
|
uchar v = bv[l];
|
|
|
|
|
|
|
|
be[l] += e * (v - f);
|
|
|
|
f = bf[l + 1];
|
|
|
|
v = bv[l + 1];
|
|
|
|
be[l + 1] += e * (v - f);
|
|
|
|
f = bf[l + 2];
|
|
|
|
v = bv[l + 2];
|
|
|
|
be[l + 2] += e * (v - f);
|
|
|
|
f = bf[l + 3];
|
|
|
|
v = bv[l + 3];
|
|
|
|
be[l + 3] += e * (v - f);
|
|
|
|
}
|
|
|
|
for( ; l < size.width; l++ )
|
|
|
|
be[l] += e * (bv[l] - bf[l]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
} /* io */
|
|
|
|
|
|
|
|
for( ie = imin; ie < imax; ie++ ) /* calculated eigen objects writting */
|
|
|
|
{
|
|
|
|
CvCallback write_callback = ((CvInput *) & output)->callback;
|
|
|
|
float *be = ((float *) buffer) + ((ie - imin) * eigStep);
|
|
|
|
|
|
|
|
r = (CvStatus)write_callback( ie, (void *) be, userData );
|
|
|
|
if( r )
|
|
|
|
{
|
|
|
|
cvFree( &ev );
|
|
|
|
if( iev )
|
|
|
|
cvFree( &eigVals );
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return r;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
} /* igr */
|
|
|
|
}
|
|
|
|
|
|
|
|
else
|
|
|
|
{
|
|
|
|
int k, p, l;
|
|
|
|
|
|
|
|
for( i = 0; i < m1; i++ ) /* e.o. annulation */
|
|
|
|
{
|
|
|
|
float *be = ((float **) output)[i];
|
|
|
|
|
|
|
|
for( p = 0; p < eigSize.height; p++, be += eigStep )
|
|
|
|
for( l = 0; l < eigSize.width; l++ )
|
|
|
|
be[l] = 0.0f;
|
|
|
|
}
|
|
|
|
|
|
|
|
for( k = 0; k < nObjects; k++ )
|
|
|
|
{
|
|
|
|
uchar *bv = (ioFlags & CV_EIGOBJ_INPUT_CALLBACK) ? buf : ((uchar **) input)[k];
|
|
|
|
|
|
|
|
if( ioFlags & CV_EIGOBJ_INPUT_CALLBACK )
|
|
|
|
{
|
|
|
|
CvCallback read_callback = ((CvInput *) & input)->callback;
|
|
|
|
|
|
|
|
r = (CvStatus)read_callback( k, (void *) buf, userData );
|
|
|
|
if( r )
|
|
|
|
{
|
|
|
|
cvFree( &ev );
|
|
|
|
if( iev )
|
|
|
|
cvFree( &eigVals );
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return r;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
for( i = 0; i < m1; i++ )
|
|
|
|
{
|
|
|
|
float v = eigVals[i] * ev[i * nObjects + k];
|
|
|
|
float *be = ((float **) output)[i];
|
|
|
|
uchar *bu = bv;
|
|
|
|
|
|
|
|
bf = avg;
|
|
|
|
|
|
|
|
for( p = 0; p < size.height; p++, bu += objStep1,
|
|
|
|
bf += avgStep, be += eigStep1 )
|
|
|
|
{
|
|
|
|
for( l = 0; l < size.width - 3; l += 4 )
|
|
|
|
{
|
|
|
|
float f = bf[l];
|
|
|
|
uchar u = bu[l];
|
|
|
|
|
|
|
|
be[l] += v * (u - f);
|
|
|
|
f = bf[l + 1];
|
|
|
|
u = bu[l + 1];
|
|
|
|
be[l + 1] += v * (u - f);
|
|
|
|
f = bf[l + 2];
|
|
|
|
u = bu[l + 2];
|
|
|
|
be[l + 2] += v * (u - f);
|
|
|
|
f = bf[l + 3];
|
|
|
|
u = bu[l + 3];
|
|
|
|
be[l + 3] += v * (u - f);
|
|
|
|
}
|
|
|
|
for( ; l < size.width; l++ )
|
|
|
|
be[l] += v * (bu[l] - bf[l]);
|
|
|
|
}
|
|
|
|
} /* i */
|
|
|
|
} /* k */
|
|
|
|
} /* else */
|
|
|
|
|
|
|
|
cvFree( &ev );
|
|
|
|
if( iev )
|
|
|
|
cvFree( &eigVals );
|
|
|
|
else
|
|
|
|
for( i = 0; i < m1; i++ )
|
|
|
|
eigVals[i] = 1.f / (eigVals[i] * eigVals[i]);
|
|
|
|
if( buffer )
|
|
|
|
cvFree( &buffer );
|
|
|
|
if( buf )
|
|
|
|
cvFree( &buf );
|
|
|
|
return CV_NO_ERR;
|
|
|
|
}
|
|
|
|
|
|
|
|
/* --- End of icvCalcEigenObjects_8u32fR --- */
|
|
|
|
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Name: icvCalcDecompCoeff_8u32fR
|
|
|
|
// Purpose: The function calculates one decomposition coefficient of input object
|
|
|
|
// using previously calculated eigen object and the mean (averaged) object
|
|
|
|
// Context:
|
|
|
|
// Parameters: obj - input object
|
|
|
|
// objStep - its step (in bytes)
|
|
|
|
// eigObj - pointer to eigen object
|
|
|
|
// eigStep - its step (in bytes)
|
|
|
|
// avg - pointer to averaged object
|
|
|
|
// avgStep - its step (in bytes)
|
|
|
|
// size - ROI size of each source object
|
|
|
|
//
|
|
|
|
// Returns: decomposition coefficient value or large negative value (if error)
|
|
|
|
//
|
|
|
|
// Notes:
|
|
|
|
//F*/
|
|
|
|
static float CV_STDCALL
|
|
|
|
icvCalcDecompCoeff_8u32fR( uchar* obj, int objStep,
|
|
|
|
float *eigObj, int eigStep,
|
|
|
|
float *avg, int avgStep, CvSize size )
|
|
|
|
{
|
|
|
|
int i, k;
|
|
|
|
float w = 0.0f;
|
|
|
|
|
|
|
|
if( size.width > objStep || 4 * size.width > eigStep
|
|
|
|
|| 4 * size.width > avgStep || size.height < 1 )
|
|
|
|
return -1.0e30f;
|
|
|
|
if( obj == NULL || eigObj == NULL || avg == NULL )
|
|
|
|
return -1.0e30f;
|
|
|
|
|
|
|
|
eigStep /= 4;
|
|
|
|
avgStep /= 4;
|
|
|
|
|
|
|
|
if( size.width == objStep && size.width == eigStep && size.width == avgStep )
|
|
|
|
{
|
|
|
|
size.width *= size.height;
|
|
|
|
size.height = 1;
|
|
|
|
objStep = eigStep = avgStep = size.width;
|
|
|
|
}
|
|
|
|
|
|
|
|
for( i = 0; i < size.height; i++, obj += objStep, eigObj += eigStep, avg += avgStep )
|
|
|
|
{
|
|
|
|
for( k = 0; k < size.width - 4; k += 4 )
|
|
|
|
{
|
|
|
|
float o = (float) obj[k];
|
|
|
|
float e = eigObj[k];
|
|
|
|
float a = avg[k];
|
|
|
|
|
|
|
|
w += e * (o - a);
|
|
|
|
o = (float) obj[k + 1];
|
|
|
|
e = eigObj[k + 1];
|
|
|
|
a = avg[k + 1];
|
|
|
|
w += e * (o - a);
|
|
|
|
o = (float) obj[k + 2];
|
|
|
|
e = eigObj[k + 2];
|
|
|
|
a = avg[k + 2];
|
|
|
|
w += e * (o - a);
|
|
|
|
o = (float) obj[k + 3];
|
|
|
|
e = eigObj[k + 3];
|
|
|
|
a = avg[k + 3];
|
|
|
|
w += e * (o - a);
|
|
|
|
}
|
|
|
|
for( ; k < size.width; k++ )
|
|
|
|
w += eigObj[k] * ((float) obj[k] - avg[k]);
|
|
|
|
}
|
|
|
|
|
|
|
|
return w;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Names: icvEigenDecomposite_8u32fR
|
|
|
|
// Purpose: The function calculates all decomposition coefficients for input object
|
|
|
|
// using previously calculated eigen objects basis and the mean (averaged)
|
|
|
|
// object
|
|
|
|
// Context:
|
|
|
|
// Parameters: obj - input object
|
|
|
|
// objStep - its step (in bytes)
|
|
|
|
// nEigObjs - number of eigen objects
|
|
|
|
// eigInput - pointer either to array of pointers to eigen objects
|
|
|
|
// or to read callback function (depending on ioFlags)
|
|
|
|
// eigStep - eigen objects step (in bytes)
|
|
|
|
// ioFlags - input/output flags
|
|
|
|
// iserData - pointer to the structure which contains all necessary
|
|
|
|
// data for the callback function
|
|
|
|
// avg - pointer to averaged object
|
|
|
|
// avgStep - its step (in bytes)
|
|
|
|
// size - ROI size of each source object
|
|
|
|
// coeffs - calculated coefficients (output data)
|
|
|
|
//
|
|
|
|
// Returns: icv status
|
|
|
|
//
|
|
|
|
// Notes: see notes for icvCalcEigenObjects_8u32fR function
|
|
|
|
//F*/
|
|
|
|
static CvStatus CV_STDCALL
|
|
|
|
icvEigenDecomposite_8u32fR( uchar * obj, int objStep, int nEigObjs,
|
|
|
|
void *eigInput, int eigStep, int ioFlags,
|
|
|
|
void *userData, float *avg, int avgStep,
|
|
|
|
CvSize size, float *coeffs )
|
|
|
|
{
|
|
|
|
int i;
|
|
|
|
|
|
|
|
if( nEigObjs < 2 )
|
|
|
|
return CV_BADFACTOR_ERR;
|
|
|
|
if( ioFlags < 0 || ioFlags > 1 )
|
|
|
|
return CV_BADFACTOR_ERR;
|
|
|
|
if( size.width > objStep || 4 * size.width > eigStep ||
|
|
|
|
4 * size.width > avgStep || size.height < 1 )
|
|
|
|
return CV_BADSIZE_ERR;
|
|
|
|
if( obj == NULL || eigInput == NULL || coeffs == NULL || avg == NULL )
|
|
|
|
return CV_NULLPTR_ERR;
|
|
|
|
if( !ioFlags )
|
|
|
|
for( i = 0; i < nEigObjs; i++ )
|
|
|
|
if( ((uchar **) eigInput)[i] == NULL )
|
|
|
|
return CV_NULLPTR_ERR;
|
|
|
|
|
|
|
|
if( ioFlags ) /* callback */
|
|
|
|
|
|
|
|
{
|
|
|
|
float *buffer;
|
|
|
|
CvCallback read_callback = ((CvInput *) & eigInput)->callback;
|
|
|
|
|
|
|
|
eigStep = 4 * size.width;
|
|
|
|
|
|
|
|
/* memory allocation */
|
|
|
|
buffer = (float *) cvAlloc( sizeof( float ) * size.width * size.height );
|
|
|
|
|
|
|
|
if( buffer == NULL )
|
|
|
|
return CV_OUTOFMEM_ERR;
|
|
|
|
|
|
|
|
for( i = 0; i < nEigObjs; i++ )
|
|
|
|
{
|
|
|
|
float w;
|
|
|
|
CvStatus r = (CvStatus)read_callback( i, (void *) buffer, userData );
|
|
|
|
|
|
|
|
if( r )
|
|
|
|
{
|
|
|
|
cvFree( &buffer );
|
|
|
|
return r;
|
|
|
|
}
|
|
|
|
w = icvCalcDecompCoeff_8u32fR( obj, objStep, buffer,
|
|
|
|
eigStep, avg, avgStep, size );
|
|
|
|
if( w < -1.0e29f )
|
|
|
|
{
|
|
|
|
cvFree( &buffer );
|
|
|
|
return CV_NOTDEFINED_ERR;
|
|
|
|
}
|
|
|
|
coeffs[i] = w;
|
|
|
|
}
|
|
|
|
cvFree( &buffer );
|
|
|
|
}
|
|
|
|
|
|
|
|
else
|
|
|
|
/* no callback */
|
|
|
|
for( i = 0; i < nEigObjs; i++ )
|
|
|
|
{
|
|
|
|
float w = icvCalcDecompCoeff_8u32fR( obj, objStep, ((float **) eigInput)[i],
|
|
|
|
eigStep, avg, avgStep, size );
|
|
|
|
|
|
|
|
if( w < -1.0e29f )
|
|
|
|
return CV_NOTDEFINED_ERR;
|
|
|
|
coeffs[i] = w;
|
|
|
|
}
|
|
|
|
|
|
|
|
return CV_NO_ERR;
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Names: icvEigenProjection_8u32fR
|
|
|
|
// Purpose: The function calculates object projection to the eigen sub-space (restores
|
|
|
|
// an object) using previously calculated eigen objects basis, mean (averaged)
|
|
|
|
// object and decomposition coefficients of the restored object
|
|
|
|
// Context:
|
|
|
|
// Parameters: nEigObjs - Number of eigen objects
|
|
|
|
// eigens - Array of pointers to eigen objects
|
|
|
|
// eigStep - Eigen objects step (in bytes)
|
|
|
|
// coeffs - Previously calculated decomposition coefficients
|
|
|
|
// avg - Pointer to averaged object
|
|
|
|
// avgStep - Its step (in bytes)
|
|
|
|
// rest - Pointer to restored object
|
|
|
|
// restStep - Its step (in bytes)
|
|
|
|
// size - ROI size of each object
|
|
|
|
//
|
|
|
|
// Returns: CV status
|
|
|
|
//
|
|
|
|
// Notes:
|
|
|
|
//F*/
|
|
|
|
static CvStatus CV_STDCALL
|
|
|
|
icvEigenProjection_8u32fR( int nEigObjs, void *eigInput, int eigStep,
|
|
|
|
int ioFlags, void *userData, float *coeffs,
|
|
|
|
float *avg, int avgStep, uchar * rest,
|
|
|
|
int restStep, CvSize size )
|
|
|
|
{
|
|
|
|
int i, j, k;
|
|
|
|
float *buf;
|
|
|
|
float *buffer = NULL;
|
|
|
|
float *b;
|
|
|
|
CvCallback read_callback = ((CvInput *) & eigInput)->callback;
|
|
|
|
|
|
|
|
if( size.width > avgStep || 4 * size.width > eigStep || size.height < 1 )
|
|
|
|
return CV_BADSIZE_ERR;
|
|
|
|
if( rest == NULL || eigInput == NULL || avg == NULL || coeffs == NULL )
|
|
|
|
return CV_NULLPTR_ERR;
|
|
|
|
if( ioFlags < 0 || ioFlags > 1 )
|
|
|
|
return CV_BADFACTOR_ERR;
|
|
|
|
if( !ioFlags )
|
|
|
|
for( i = 0; i < nEigObjs; i++ )
|
|
|
|
if( ((uchar **) eigInput)[i] == NULL )
|
|
|
|
return CV_NULLPTR_ERR;
|
|
|
|
eigStep /= 4;
|
|
|
|
avgStep /= 4;
|
|
|
|
|
|
|
|
if( size.width == restStep && size.width == eigStep && size.width == avgStep )
|
|
|
|
{
|
|
|
|
size.width *= size.height;
|
|
|
|
size.height = 1;
|
|
|
|
restStep = eigStep = avgStep = size.width;
|
|
|
|
}
|
|
|
|
|
|
|
|
buf = (float *) cvAlloc( sizeof( float ) * size.width * size.height );
|
|
|
|
|
|
|
|
if( buf == NULL )
|
|
|
|
return CV_OUTOFMEM_ERR;
|
|
|
|
b = buf;
|
|
|
|
for( i = 0; i < size.height; i++, avg += avgStep, b += size.width )
|
|
|
|
for( j = 0; j < size.width; j++ )
|
|
|
|
b[j] = avg[j];
|
|
|
|
|
|
|
|
if( ioFlags )
|
|
|
|
{
|
|
|
|
buffer = (float *) cvAlloc( sizeof( float ) * size.width * size.height );
|
|
|
|
|
|
|
|
if( buffer == NULL )
|
|
|
|
{
|
|
|
|
cvFree( &buf );
|
|
|
|
return CV_OUTOFMEM_ERR;
|
|
|
|
}
|
|
|
|
eigStep = size.width;
|
|
|
|
}
|
|
|
|
|
|
|
|
for( k = 0; k < nEigObjs; k++ )
|
|
|
|
{
|
|
|
|
float *e = ioFlags ? buffer : ((float **) eigInput)[k];
|
|
|
|
float c = coeffs[k];
|
|
|
|
|
|
|
|
if( ioFlags ) /* read eigen object */
|
|
|
|
{
|
|
|
|
CvStatus r = (CvStatus)read_callback( k, (void *) buffer, userData );
|
|
|
|
|
|
|
|
if( r )
|
|
|
|
{
|
|
|
|
cvFree( &buf );
|
|
|
|
cvFree( &buffer );
|
|
|
|
return r;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
b = buf;
|
|
|
|
for( i = 0; i < size.height; i++, e += eigStep, b += size.width )
|
|
|
|
{
|
|
|
|
for( j = 0; j < size.width - 3; j += 4 )
|
|
|
|
{
|
|
|
|
float b0 = c * e[j];
|
|
|
|
float b1 = c * e[j + 1];
|
|
|
|
float b2 = c * e[j + 2];
|
|
|
|
float b3 = c * e[j + 3];
|
|
|
|
|
|
|
|
b[j] += b0;
|
|
|
|
b[j + 1] += b1;
|
|
|
|
b[j + 2] += b2;
|
|
|
|
b[j + 3] += b3;
|
|
|
|
}
|
|
|
|
for( ; j < size.width; j++ )
|
|
|
|
b[j] += c * e[j];
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
b = buf;
|
|
|
|
for( i = 0; i < size.height; i++, avg += avgStep, b += size.width, rest += restStep )
|
|
|
|
for( j = 0; j < size.width; j++ )
|
|
|
|
{
|
|
|
|
int w = cvRound( b[j] );
|
|
|
|
|
|
|
|
w = !(w & ~255) ? w : w < 0 ? 0 : 255;
|
|
|
|
rest[j] = (uchar) w;
|
|
|
|
}
|
|
|
|
|
|
|
|
cvFree( &buf );
|
|
|
|
if( ioFlags )
|
|
|
|
cvFree( &buffer );
|
|
|
|
return CV_NO_ERR;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Name: cvCalcCovarMatrixEx
|
|
|
|
// Purpose: The function calculates a covariance matrix for a group of input objects
|
|
|
|
// (images, vectors, etc.).
|
|
|
|
// Context:
|
|
|
|
// Parameters: nObjects - number of source objects
|
|
|
|
// input - pointer either to array of input objects
|
|
|
|
// or to read callback function (depending on ioFlags)
|
|
|
|
// ioFlags - input/output flags (see Notes to
|
|
|
|
// cvCalcEigenObjects function)
|
|
|
|
// ioBufSize - input/output buffer size
|
|
|
|
// userData - pointer to the structure which contains all necessary
|
|
|
|
// data for the callback functions
|
|
|
|
// avg - averaged object
|
|
|
|
// covarMatrix - covariance matrix (output parameter; must be allocated
|
|
|
|
// before call)
|
|
|
|
//
|
|
|
|
// Notes: See Notes to cvCalcEigenObjects function
|
|
|
|
//F*/
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvCalcCovarMatrixEx( int nObjects, void* input, int ioFlags,
|
|
|
|
int ioBufSize, uchar* buffer, void* userData,
|
|
|
|
IplImage* avg, float* covarMatrix )
|
|
|
|
{
|
|
|
|
float *avg_data;
|
|
|
|
int avg_step = 0;
|
|
|
|
CvSize avg_size;
|
|
|
|
int i;
|
|
|
|
|
|
|
|
CV_FUNCNAME( "cvCalcCovarMatrixEx" );
|
|
|
|
|
|
|
|
__BEGIN__;
|
|
|
|
|
|
|
|
cvGetImageRawData( avg, (uchar **) & avg_data, &avg_step, &avg_size );
|
|
|
|
if( avg->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( avg->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
if( ioFlags == CV_EIGOBJ_NO_CALLBACK )
|
|
|
|
{
|
|
|
|
IplImage **images = (IplImage **) (((CvInput *) & input)->data);
|
|
|
|
uchar **objects = (uchar **) cvAlloc( sizeof( uchar * ) * nObjects );
|
|
|
|
int img_step = 0, old_step = 0;
|
|
|
|
CvSize img_size = avg_size, old_size = avg_size;
|
|
|
|
|
|
|
|
if( objects == NULL )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Insufficient memory" );
|
|
|
|
|
|
|
|
for( i = 0; i < nObjects; i++ )
|
|
|
|
{
|
|
|
|
IplImage *img = images[i];
|
|
|
|
uchar *img_data;
|
|
|
|
|
|
|
|
cvGetImageRawData( img, &img_data, &img_step, &img_size );
|
|
|
|
if( img->depth != IPL_DEPTH_8U )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( img_size != avg_size || img_size != old_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of objects" );
|
|
|
|
if( img->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
if( i > 0 && img_step != old_step )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different steps of objects" );
|
|
|
|
|
|
|
|
old_step = img_step;
|
|
|
|
old_size = img_size;
|
|
|
|
objects[i] = img_data;
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_CALL( icvCalcCovarMatrixEx_8u32fR( nObjects,
|
|
|
|
(void*) objects,
|
|
|
|
img_step,
|
|
|
|
CV_EIGOBJ_NO_CALLBACK,
|
|
|
|
0,
|
|
|
|
NULL,
|
|
|
|
NULL,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
avg_size,
|
|
|
|
covarMatrix ));
|
|
|
|
cvFree( &objects );
|
|
|
|
}
|
|
|
|
|
|
|
|
else
|
|
|
|
|
|
|
|
{
|
|
|
|
CV_CALL( icvCalcCovarMatrixEx_8u32fR( nObjects,
|
|
|
|
input,
|
|
|
|
avg_step / 4,
|
|
|
|
ioFlags,
|
|
|
|
ioBufSize,
|
|
|
|
buffer,
|
|
|
|
userData,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
avg_size,
|
|
|
|
covarMatrix ));
|
|
|
|
}
|
|
|
|
|
|
|
|
__END__;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Name: cvCalcEigenObjects
|
|
|
|
// Purpose: The function calculates an orthonormal eigen basis and a mean (averaged)
|
|
|
|
// object for a group of input objects (images, vectors, etc.).
|
|
|
|
// Context:
|
|
|
|
// Parameters: nObjects - number of source objects
|
|
|
|
// input - pointer either to array of input objects
|
|
|
|
// or to read callback function (depending on ioFlags)
|
|
|
|
// output - pointer either to output eigen objects
|
|
|
|
// or to write callback function (depending on ioFlags)
|
|
|
|
// ioFlags - input/output flags (see Notes)
|
|
|
|
// ioBufSize - input/output buffer size
|
|
|
|
// userData - pointer to the structure which contains all necessary
|
|
|
|
// data for the callback functions
|
|
|
|
// calcLimit - determines the calculation finish conditions
|
|
|
|
// avg - averaged object (has the same size as ROI)
|
|
|
|
// eigVals - pointer to corresponding eigen values (array of <nObjects>
|
|
|
|
// elements in descending order)
|
|
|
|
//
|
|
|
|
// Notes: 1. input/output data (that is, input objects and eigen ones) may either
|
|
|
|
// be allocated in the RAM or be read from/written to the HDD (or any
|
|
|
|
// other device) by read/write callback functions. It depends on the
|
|
|
|
// value of ioFlags paramater, which may be the following:
|
|
|
|
// CV_EIGOBJ_NO_CALLBACK, or 0;
|
|
|
|
// CV_EIGOBJ_INPUT_CALLBACK;
|
|
|
|
// CV_EIGOBJ_OUTPUT_CALLBACK;
|
|
|
|
// CV_EIGOBJ_BOTH_CALLBACK, or
|
|
|
|
// CV_EIGOBJ_INPUT_CALLBACK | CV_EIGOBJ_OUTPUT_CALLBACK.
|
|
|
|
// The callback functions as well as the user data structure must be
|
|
|
|
// developed by the user.
|
|
|
|
//
|
|
|
|
// 2. If ioBufSize = 0, or it's too large, the function dermines buffer size
|
|
|
|
// itself.
|
|
|
|
//
|
|
|
|
// 3. Depending on calcLimit parameter, calculations are finished either if
|
|
|
|
// eigenfaces number comes up to certain value or the relation of the
|
|
|
|
// current eigenvalue and the largest one comes down to certain value
|
|
|
|
// (or any of the above conditions takes place). The calcLimit->type value
|
|
|
|
// must be CV_TERMCRIT_NUMB, CV_TERMCRIT_EPS or
|
|
|
|
// CV_TERMCRIT_NUMB | CV_TERMCRIT_EPS. The function returns the real
|
|
|
|
// values calcLimit->max_iter and calcLimit->epsilon.
|
|
|
|
//
|
|
|
|
// 4. eigVals may be equal to NULL (if you don't need eigen values in further).
|
|
|
|
//
|
|
|
|
//F*/
|
|
|
|
CV_IMPL void
|
|
|
|
cvCalcEigenObjects( int nObjects,
|
|
|
|
void* input,
|
|
|
|
void* output,
|
|
|
|
int ioFlags,
|
|
|
|
int ioBufSize,
|
|
|
|
void* userData,
|
|
|
|
CvTermCriteria* calcLimit,
|
|
|
|
IplImage* avg,
|
|
|
|
float* eigVals )
|
|
|
|
{
|
|
|
|
float *avg_data;
|
|
|
|
int avg_step = 0;
|
|
|
|
CvSize avg_size;
|
|
|
|
int i;
|
|
|
|
int nEigens = nObjects - 1;
|
|
|
|
|
|
|
|
CV_FUNCNAME( "cvCalcEigenObjects" );
|
|
|
|
|
|
|
|
__BEGIN__;
|
|
|
|
|
|
|
|
cvGetImageRawData( avg, (uchar **) & avg_data, &avg_step, &avg_size );
|
|
|
|
if( avg->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( avg->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
if( nEigens > calcLimit->max_iter && calcLimit->type != CV_TERMCRIT_EPS )
|
|
|
|
nEigens = calcLimit->max_iter;
|
|
|
|
|
|
|
|
switch (ioFlags)
|
|
|
|
{
|
|
|
|
case CV_EIGOBJ_NO_CALLBACK:
|
|
|
|
{
|
|
|
|
IplImage **objects = (IplImage **) (((CvInput *) & input)->data);
|
|
|
|
IplImage **eigens = (IplImage **) (((CvInput *) & output)->data);
|
|
|
|
uchar **objs = (uchar **) cvAlloc( sizeof( uchar * ) * nObjects );
|
|
|
|
float **eigs = (float **) cvAlloc( sizeof( float * ) * nEigens );
|
|
|
|
int obj_step = 0, old_step = 0;
|
|
|
|
int eig_step = 0, oldeig_step = 0;
|
|
|
|
CvSize obj_size = avg_size, old_size = avg_size,
|
|
|
|
|
|
|
|
eig_size = avg_size, oldeig_size = avg_size;
|
|
|
|
|
|
|
|
if( objects == NULL || eigens == NULL )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Insufficient memory" );
|
|
|
|
|
|
|
|
for( i = 0; i < nObjects; i++ )
|
|
|
|
{
|
|
|
|
IplImage *img = objects[i];
|
|
|
|
uchar *obj_data;
|
|
|
|
|
|
|
|
cvGetImageRawData( img, &obj_data, &obj_step, &obj_size );
|
|
|
|
if( img->depth != IPL_DEPTH_8U )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( obj_size != avg_size || obj_size != old_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of objects" );
|
|
|
|
if( img->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
if( i > 0 && obj_step != old_step )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different steps of objects" );
|
|
|
|
|
|
|
|
old_step = obj_step;
|
|
|
|
old_size = obj_size;
|
|
|
|
objs[i] = obj_data;
|
|
|
|
}
|
|
|
|
for( i = 0; i < nEigens; i++ )
|
|
|
|
{
|
|
|
|
IplImage *eig = eigens[i];
|
|
|
|
float *eig_data;
|
|
|
|
|
|
|
|
cvGetImageRawData( eig, (uchar **) & eig_data, &eig_step, &eig_size );
|
|
|
|
if( eig->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( eig_size != avg_size || eig_size != oldeig_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of objects" );
|
|
|
|
if( eig->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
if( i > 0 && eig_step != oldeig_step )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different steps of objects" );
|
|
|
|
|
|
|
|
oldeig_step = eig_step;
|
|
|
|
oldeig_size = eig_size;
|
|
|
|
eigs[i] = eig_data;
|
|
|
|
}
|
|
|
|
CV_CALL( icvCalcEigenObjects_8u32fR( nObjects, (void*) objs, obj_step,
|
|
|
|
(void*) eigs, eig_step, obj_size,
|
|
|
|
ioFlags, ioBufSize, userData,
|
|
|
|
calcLimit, avg_data, avg_step, eigVals ));
|
|
|
|
cvFree( &objs );
|
|
|
|
cvFree( &eigs );
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
|
|
|
case CV_EIGOBJ_OUTPUT_CALLBACK:
|
|
|
|
{
|
|
|
|
IplImage **objects = (IplImage **) (((CvInput *) & input)->data);
|
|
|
|
uchar **objs = (uchar **) cvAlloc( sizeof( uchar * ) * nObjects );
|
|
|
|
int obj_step = 0, old_step = 0;
|
|
|
|
CvSize obj_size = avg_size, old_size = avg_size;
|
|
|
|
|
|
|
|
if( objects == NULL )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Insufficient memory" );
|
|
|
|
|
|
|
|
for( i = 0; i < nObjects; i++ )
|
|
|
|
{
|
|
|
|
IplImage *img = objects[i];
|
|
|
|
uchar *obj_data;
|
|
|
|
|
|
|
|
cvGetImageRawData( img, &obj_data, &obj_step, &obj_size );
|
|
|
|
if( img->depth != IPL_DEPTH_8U )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( obj_size != avg_size || obj_size != old_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of objects" );
|
|
|
|
if( img->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
if( i > 0 && obj_step != old_step )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different steps of objects" );
|
|
|
|
|
|
|
|
old_step = obj_step;
|
|
|
|
old_size = obj_size;
|
|
|
|
objs[i] = obj_data;
|
|
|
|
}
|
|
|
|
CV_CALL( icvCalcEigenObjects_8u32fR( nObjects,
|
|
|
|
(void*) objs,
|
|
|
|
obj_step,
|
|
|
|
output,
|
|
|
|
avg_step,
|
|
|
|
obj_size,
|
|
|
|
ioFlags,
|
|
|
|
ioBufSize,
|
|
|
|
userData,
|
|
|
|
calcLimit,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
eigVals ));
|
|
|
|
cvFree( &objs );
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
|
|
|
case CV_EIGOBJ_INPUT_CALLBACK:
|
|
|
|
{
|
|
|
|
IplImage **eigens = (IplImage **) (((CvInput *) & output)->data);
|
|
|
|
float **eigs = (float**) cvAlloc( sizeof( float* ) * nEigens );
|
|
|
|
int eig_step = 0, oldeig_step = 0;
|
|
|
|
CvSize eig_size = avg_size, oldeig_size = avg_size;
|
|
|
|
|
|
|
|
if( eigens == NULL )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Insufficient memory" );
|
|
|
|
|
|
|
|
for( i = 0; i < nEigens; i++ )
|
|
|
|
{
|
|
|
|
IplImage *eig = eigens[i];
|
|
|
|
float *eig_data;
|
|
|
|
|
|
|
|
cvGetImageRawData( eig, (uchar **) & eig_data, &eig_step, &eig_size );
|
|
|
|
if( eig->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( eig_size != avg_size || eig_size != oldeig_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of objects" );
|
|
|
|
if( eig->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
if( i > 0 && eig_step != oldeig_step )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different steps of objects" );
|
|
|
|
|
|
|
|
oldeig_step = eig_step;
|
|
|
|
oldeig_size = eig_size;
|
|
|
|
eigs[i] = eig_data;
|
|
|
|
}
|
|
|
|
CV_CALL( icvCalcEigenObjects_8u32fR( nObjects,
|
|
|
|
input,
|
|
|
|
avg_step / 4,
|
|
|
|
(void*) eigs,
|
|
|
|
eig_step,
|
|
|
|
eig_size,
|
|
|
|
ioFlags,
|
|
|
|
ioBufSize,
|
|
|
|
userData,
|
|
|
|
calcLimit,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
eigVals ));
|
|
|
|
cvFree( &eigs );
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
case CV_EIGOBJ_INPUT_CALLBACK | CV_EIGOBJ_OUTPUT_CALLBACK:
|
|
|
|
|
|
|
|
CV_CALL( icvCalcEigenObjects_8u32fR( nObjects,
|
|
|
|
input,
|
|
|
|
avg_step / 4,
|
|
|
|
output,
|
|
|
|
avg_step,
|
|
|
|
avg_size,
|
|
|
|
ioFlags,
|
|
|
|
ioBufSize,
|
|
|
|
userData,
|
|
|
|
calcLimit,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
eigVals ));
|
|
|
|
break;
|
|
|
|
|
|
|
|
default:
|
|
|
|
CV_ERROR( CV_StsBadArg, "Unsupported i/o flag" );
|
|
|
|
}
|
|
|
|
|
|
|
|
__END__;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*--------------------------------------------------------------------------------------*/
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Name: cvCalcDecompCoeff
|
|
|
|
// Purpose: The function calculates one decomposition coefficient of input object
|
|
|
|
// using previously calculated eigen object and the mean (averaged) object
|
|
|
|
// Context:
|
|
|
|
// Parameters: obj - input object
|
|
|
|
// eigObj - eigen object
|
|
|
|
// avg - averaged object
|
|
|
|
//
|
|
|
|
// Returns: decomposition coefficient value or large negative value (if error)
|
|
|
|
//
|
|
|
|
// Notes:
|
|
|
|
//F*/
|
|
|
|
|
|
|
|
CV_IMPL double
|
|
|
|
cvCalcDecompCoeff( IplImage * obj, IplImage * eigObj, IplImage * avg )
|
|
|
|
{
|
|
|
|
double coeff = DBL_MAX;
|
|
|
|
|
|
|
|
uchar *obj_data;
|
|
|
|
float *eig_data;
|
|
|
|
float *avg_data;
|
|
|
|
int obj_step = 0, eig_step = 0, avg_step = 0;
|
|
|
|
CvSize obj_size, eig_size, avg_size;
|
|
|
|
|
|
|
|
CV_FUNCNAME( "cvCalcDecompCoeff" );
|
|
|
|
|
|
|
|
__BEGIN__;
|
|
|
|
|
|
|
|
cvGetImageRawData( obj, &obj_data, &obj_step, &obj_size );
|
|
|
|
if( obj->depth != IPL_DEPTH_8U )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( obj->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
cvGetImageRawData( eigObj, (uchar **) & eig_data, &eig_step, &eig_size );
|
|
|
|
if( eigObj->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( eigObj->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
cvGetImageRawData( avg, (uchar **) & avg_data, &avg_step, &avg_size );
|
|
|
|
if( avg->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( avg->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
if( obj_size != eig_size || obj_size != avg_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "different sizes of images" );
|
|
|
|
|
|
|
|
coeff = icvCalcDecompCoeff_8u32fR( obj_data, obj_step,
|
|
|
|
eig_data, eig_step,
|
|
|
|
avg_data, avg_step, obj_size );
|
|
|
|
|
|
|
|
__END__;
|
|
|
|
|
|
|
|
return coeff;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*--------------------------------------------------------------------------------------*/
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Names: cvEigenDecomposite
|
|
|
|
// Purpose: The function calculates all decomposition coefficients for input object
|
|
|
|
// using previously calculated eigen objects basis and the mean (averaged)
|
|
|
|
// object
|
|
|
|
//
|
|
|
|
// Parameters: obj - input object
|
|
|
|
// nEigObjs - number of eigen objects
|
|
|
|
// eigInput - pointer either to array of pointers to eigen objects
|
|
|
|
// or to read callback function (depending on ioFlags)
|
|
|
|
// ioFlags - input/output flags
|
|
|
|
// userData - pointer to the structure which contains all necessary
|
|
|
|
// data for the callback function
|
|
|
|
// avg - averaged object
|
|
|
|
// coeffs - calculated coefficients (output data)
|
|
|
|
//
|
|
|
|
// Notes: see notes for cvCalcEigenObjects function
|
|
|
|
//F*/
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvEigenDecomposite( IplImage* obj,
|
|
|
|
int nEigObjs,
|
|
|
|
void* eigInput,
|
|
|
|
int ioFlags,
|
|
|
|
void* userData,
|
|
|
|
IplImage* avg,
|
|
|
|
float* coeffs )
|
|
|
|
{
|
|
|
|
float *avg_data;
|
|
|
|
uchar *obj_data;
|
|
|
|
int avg_step = 0, obj_step = 0;
|
|
|
|
CvSize avg_size, obj_size;
|
|
|
|
int i;
|
|
|
|
|
|
|
|
CV_FUNCNAME( "cvEigenDecomposite" );
|
|
|
|
|
|
|
|
__BEGIN__;
|
|
|
|
|
|
|
|
cvGetImageRawData( avg, (uchar **) & avg_data, &avg_step, &avg_size );
|
|
|
|
if( avg->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( avg->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
cvGetImageRawData( obj, &obj_data, &obj_step, &obj_size );
|
|
|
|
if( obj->depth != IPL_DEPTH_8U )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( obj->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
if( obj_size != avg_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of objects" );
|
|
|
|
|
|
|
|
if( ioFlags == CV_EIGOBJ_NO_CALLBACK )
|
|
|
|
{
|
|
|
|
IplImage **eigens = (IplImage **) (((CvInput *) & eigInput)->data);
|
|
|
|
float **eigs = (float **) cvAlloc( sizeof( float * ) * nEigObjs );
|
|
|
|
int eig_step = 0, old_step = 0;
|
|
|
|
CvSize eig_size = avg_size, old_size = avg_size;
|
|
|
|
|
|
|
|
if( eigs == NULL )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Insufficient memory" );
|
|
|
|
|
|
|
|
for( i = 0; i < nEigObjs; i++ )
|
|
|
|
{
|
|
|
|
IplImage *eig = eigens[i];
|
|
|
|
float *eig_data;
|
|
|
|
|
|
|
|
cvGetImageRawData( eig, (uchar **) & eig_data, &eig_step, &eig_size );
|
|
|
|
if( eig->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( eig_size != avg_size || eig_size != old_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of objects" );
|
|
|
|
if( eig->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
if( i > 0 && eig_step != old_step )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different steps of objects" );
|
|
|
|
|
|
|
|
old_step = eig_step;
|
|
|
|
old_size = eig_size;
|
|
|
|
eigs[i] = eig_data;
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_CALL( icvEigenDecomposite_8u32fR( obj_data,
|
|
|
|
obj_step,
|
|
|
|
nEigObjs,
|
|
|
|
(void*) eigs,
|
|
|
|
eig_step,
|
|
|
|
ioFlags,
|
|
|
|
userData,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
obj_size,
|
|
|
|
coeffs ));
|
|
|
|
cvFree( &eigs );
|
|
|
|
}
|
|
|
|
|
|
|
|
else
|
|
|
|
|
|
|
|
{
|
|
|
|
CV_CALL( icvEigenDecomposite_8u32fR( obj_data,
|
|
|
|
obj_step,
|
|
|
|
nEigObjs,
|
|
|
|
eigInput,
|
|
|
|
avg_step,
|
|
|
|
ioFlags,
|
|
|
|
userData,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
obj_size,
|
|
|
|
coeffs ));
|
|
|
|
}
|
|
|
|
|
|
|
|
__END__;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*--------------------------------------------------------------------------------------*/
|
|
|
|
/*F///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Name: cvEigenProjection
|
|
|
|
// Purpose: The function calculates object projection to the eigen sub-space (restores
|
|
|
|
// an object) using previously calculated eigen objects basis, mean (averaged)
|
|
|
|
// object and decomposition coefficients of the restored object
|
|
|
|
// Context:
|
|
|
|
// Parameters: nEigObjs - number of eigen objects
|
|
|
|
// eigInput - pointer either to array of pointers to eigen objects
|
|
|
|
// or to read callback function (depending on ioFlags)
|
|
|
|
// ioFlags - input/output flags
|
|
|
|
// userData - pointer to the structure which contains all necessary
|
|
|
|
// data for the callback function
|
|
|
|
// coeffs - array of decomposition coefficients
|
|
|
|
// avg - averaged object
|
|
|
|
// proj - object projection (output data)
|
|
|
|
//
|
|
|
|
// Notes: see notes for cvCalcEigenObjects function
|
|
|
|
//F*/
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvEigenProjection( void* eigInput,
|
|
|
|
int nEigObjs,
|
|
|
|
int ioFlags,
|
|
|
|
void* userData,
|
|
|
|
float* coeffs,
|
|
|
|
IplImage* avg,
|
|
|
|
IplImage* proj )
|
|
|
|
{
|
|
|
|
float *avg_data;
|
|
|
|
uchar *proj_data;
|
|
|
|
int avg_step = 0, proj_step = 0;
|
|
|
|
CvSize avg_size, proj_size;
|
|
|
|
int i;
|
|
|
|
|
|
|
|
CV_FUNCNAME( "cvEigenProjection" );
|
|
|
|
|
|
|
|
__BEGIN__;
|
|
|
|
|
|
|
|
cvGetImageRawData( avg, (uchar **) & avg_data, &avg_step, &avg_size );
|
|
|
|
if( avg->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( avg->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
cvGetImageRawData( proj, &proj_data, &proj_step, &proj_size );
|
|
|
|
if( proj->depth != IPL_DEPTH_8U )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( proj->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
|
|
|
|
if( proj_size != avg_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of projects" );
|
|
|
|
|
|
|
|
if( ioFlags == CV_EIGOBJ_NO_CALLBACK )
|
|
|
|
{
|
|
|
|
IplImage **eigens = (IplImage**) (((CvInput *) & eigInput)->data);
|
|
|
|
float **eigs = (float**) cvAlloc( sizeof( float * ) * nEigObjs );
|
|
|
|
int eig_step = 0, old_step = 0;
|
|
|
|
CvSize eig_size = avg_size, old_size = avg_size;
|
|
|
|
|
|
|
|
if( eigs == NULL )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Insufficient memory" );
|
|
|
|
|
|
|
|
for( i = 0; i < nEigObjs; i++ )
|
|
|
|
{
|
|
|
|
IplImage *eig = eigens[i];
|
|
|
|
float *eig_data;
|
|
|
|
|
|
|
|
cvGetImageRawData( eig, (uchar **) & eig_data, &eig_step, &eig_size );
|
|
|
|
if( eig->depth != IPL_DEPTH_32F )
|
|
|
|
CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
|
|
|
|
if( eig_size != avg_size || eig_size != old_size )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different sizes of objects" );
|
|
|
|
if( eig->nChannels != 1 )
|
|
|
|
CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
|
|
|
|
if( i > 0 && eig_step != old_step )
|
|
|
|
CV_ERROR( CV_StsBadArg, "Different steps of objects" );
|
|
|
|
|
|
|
|
old_step = eig_step;
|
|
|
|
old_size = eig_size;
|
|
|
|
eigs[i] = eig_data;
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_CALL( icvEigenProjection_8u32fR( nEigObjs,
|
|
|
|
(void*) eigs,
|
|
|
|
eig_step,
|
|
|
|
ioFlags,
|
|
|
|
userData,
|
|
|
|
coeffs,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
proj_data,
|
|
|
|
proj_step,
|
|
|
|
avg_size ));
|
|
|
|
cvFree( &eigs );
|
|
|
|
}
|
|
|
|
|
|
|
|
else
|
|
|
|
|
|
|
|
{
|
|
|
|
CV_CALL( icvEigenProjection_8u32fR( nEigObjs,
|
|
|
|
eigInput,
|
|
|
|
avg_step,
|
|
|
|
ioFlags,
|
|
|
|
userData,
|
|
|
|
coeffs,
|
|
|
|
avg_data,
|
|
|
|
avg_step,
|
|
|
|
proj_data,
|
|
|
|
proj_step,
|
|
|
|
avg_size ));
|
|
|
|
}
|
|
|
|
|
|
|
|
__END__;
|
|
|
|
}
|
|
|
|
|
|
|
|
/* End of file. */
|