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			191 lines
		
	
	
		
			5.7 KiB
		
	
	
	
		
			C++
		
	
			
		
		
	
	
			191 lines
		
	
	
		
			5.7 KiB
		
	
	
	
		
			C++
		
	
/***********************************************************************
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 * Software License Agreement (BSD License)
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 *
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 * Copyright 2008-2009  Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
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 * Copyright 2008-2009  David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
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 *
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 * THE BSD LICENSE
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 *
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 * Redistribution and use in source and binary forms, with or without
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 * modification, are permitted provided that the following conditions
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 * are met:
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 *
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 * 1. Redistributions of source code must retain the above copyright
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 *    notice, this list of conditions and the following disclaimer.
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 * 2. Redistributions in binary form must reproduce the above copyright
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 *    notice, this list of conditions and the following disclaimer in the
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 *    documentation and/or other materials provided with the distribution.
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 *
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 * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
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 * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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 * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
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 * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
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 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
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 * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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 * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
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 * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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 *************************************************************************/
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#ifndef OPENCV_FLANN_SIMPLEX_DOWNHILL_H_
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#define OPENCV_FLANN_SIMPLEX_DOWNHILL_H_
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//! @cond IGNORED
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namespace cvflann
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{
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/**
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    Adds val to array vals (and point to array points) and keeping the arrays sorted by vals.
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 */
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template <typename T>
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void addValue(int pos, float val, float* vals, T* point, T* points, int n)
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{
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    vals[pos] = val;
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    for (int i=0; i<n; ++i) {
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        points[pos*n+i] = point[i];
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    }
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    // bubble down
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    int j=pos;
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    while (j>0 && vals[j]<vals[j-1]) {
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        swap(vals[j],vals[j-1]);
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        for (int i=0; i<n; ++i) {
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            swap(points[j*n+i],points[(j-1)*n+i]);
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        }
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        --j;
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    }
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}
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/**
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    Simplex downhill optimization function.
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    Preconditions: points is a 2D mattrix of size (n+1) x n
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                    func is the cost function taking n an array of n params and returning float
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                    vals is the cost function in the n+1 simplex points, if NULL it will be computed
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    Postcondition: returns optimum value and points[0..n] are the optimum parameters
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 */
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template <typename T, typename F>
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float optimizeSimplexDownhill(T* points, int n, F func, float* vals = NULL )
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{
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    const int MAX_ITERATIONS = 10;
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    CV_DbgAssert(n>0);
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    T* p_o = new T[n];
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    T* p_r = new T[n];
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    T* p_e = new T[n];
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    int alpha = 1;
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    int iterations = 0;
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    bool ownVals = false;
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    if (vals == NULL) {
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        ownVals = true;
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        vals = new float[n+1];
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        for (int i=0; i<n+1; ++i) {
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            float val = func(points+i*n);
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            addValue(i, val, vals, points+i*n, points, n);
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        }
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    }
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    int nn = n*n;
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    while (true) {
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        if (iterations++ > MAX_ITERATIONS) break;
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        // compute average of simplex points (except the highest point)
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        for (int j=0; j<n; ++j) {
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            p_o[j] = 0;
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            for (int i=0; i<n; ++i) {
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                p_o[i] += points[j*n+i];
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            }
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        }
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        for (int i=0; i<n; ++i) {
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            p_o[i] /= n;
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        }
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        bool converged = true;
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        for (int i=0; i<n; ++i) {
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            if (p_o[i] != points[nn+i]) {
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                converged = false;
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            }
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        }
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        if (converged) break;
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        // trying a reflection
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        for (int i=0; i<n; ++i) {
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            p_r[i] = p_o[i] + alpha*(p_o[i]-points[nn+i]);
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        }
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        float val_r = func(p_r);
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        if ((val_r>=vals[0])&&(val_r<vals[n])) {
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            // reflection between second highest and lowest
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            // add it to the simplex
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            Logger::info("Choosing reflection\n");
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            addValue(n, val_r,vals, p_r, points, n);
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            continue;
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        }
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        if (val_r<vals[0]) {
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            // value is smaller than smallest in simplex
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            // expand some more to see if it drops further
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            for (int i=0; i<n; ++i) {
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                p_e[i] = 2*p_r[i]-p_o[i];
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            }
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            float val_e = func(p_e);
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            if (val_e<val_r) {
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                Logger::info("Choosing reflection and expansion\n");
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                addValue(n, val_e,vals,p_e,points,n);
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            }
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            else {
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                Logger::info("Choosing reflection\n");
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                addValue(n, val_r,vals,p_r,points,n);
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            }
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            continue;
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        }
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        if (val_r>=vals[n]) {
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            for (int i=0; i<n; ++i) {
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                p_e[i] = (p_o[i]+points[nn+i])/2;
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            }
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            float val_e = func(p_e);
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            if (val_e<vals[n]) {
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                Logger::info("Choosing contraction\n");
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                addValue(n,val_e,vals,p_e,points,n);
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                continue;
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            }
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        }
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        {
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            Logger::info("Full contraction\n");
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            for (int j=1; j<=n; ++j) {
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                for (int i=0; i<n; ++i) {
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                    points[j*n+i] = (points[j*n+i]+points[i])/2;
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                }
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                float val = func(points+j*n);
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                addValue(j,val,vals,points+j*n,points,n);
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            }
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        }
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    }
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    float bestVal = vals[0];
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    delete[] p_r;
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    delete[] p_o;
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    delete[] p_e;
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    if (ownVals) delete[] vals;
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    return bestVal;
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}
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}
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//! @endcond
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#endif //OPENCV_FLANN_SIMPLEX_DOWNHILL_H_
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