libeblearn
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00001 /*************************************************************************** 00002 * Copyright (C) 2011 by Pierre Sermanet * 00003 * pierre.sermanet@gmail.com * 00004 * All rights reserved. 00005 * 00006 * Redistribution and use in source and binary forms, with or without 00007 * modification, are permitted provided that the following conditions are met: 00008 * * Redistributions of source code must retain the above copyright 00009 * notice, this list of conditions and the following disclaimer. 00010 * * Redistributions in binary form must reproduce the above copyright 00011 * notice, this list of conditions and the following disclaimer in the 00012 * documentation and/or other materials provided with the distribution. 00013 * * Redistribution under a license not approved by the Open Source 00014 * Initiative (http://www.opensource.org) must display the 00015 * following acknowledgement in all advertising material: 00016 * This product includes software developed at the Courant 00017 * Institute of Mathematical Sciences (http://cims.nyu.edu). 00018 * * The names of the authors may not be used to endorse or promote products 00019 * derived from this software without specific prior written permission. 00020 * 00021 * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESS OR IMPLIED 00022 * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 00023 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 00024 * DISCLAIMED. IN NO EVENT SHALL ThE AUTHORS BE LIABLE FOR ANY 00025 * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 00026 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00027 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND 00028 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 00029 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00030 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00031 ***************************************************************************/ 00032 00033 #ifndef BBOX_HPP_ 00034 #define BBOX_HPP_ 00035 00036 namespace ebl { 00037 00038 // sorting /////////////////////////////////////////////////////////////////// 00039 00040 template <typename T> 00041 void bboxes::sort_by_difference(svector<midx<T> >& inputs) { 00042 if (inputs.size() != this->size()) 00043 eblerror("expected same number as input as bboxes but got " 00044 << inputs.size() << " and " << this->size()); 00045 // note: inputs and boxes are assumned to be sorted by confidence already 00046 double dmax, smax; 00047 for (int i = 0; i < (int) inputs.size() - 1; ++i) { 00048 int id = i; 00049 dmax = 0, smax = 0; 00050 // find most different sample below 00051 for (int j = i + 1; j < (int) inputs.size(); j++) { 00052 // compute total distance of input j with all previous samples 00053 midx<T> e1 = inputs[j]; 00054 double d = 0, s = 0; 00055 for (int k = 0; k < i + 1; k++) { 00056 midx<T> e2 = inputs[k]; 00057 if (!e1.same_dim(e2)) d += idx_l2common(e1, e2); 00058 else d += idx_l2(e1, e2); 00059 // accumulate dimensions differences 00060 for (uint l = 0; l < e1.dim(0); ++l) { 00061 idx<T> e11 = e1.get(l), e22 = e2.get(l); 00062 for (int m = 0; m < e11.order(); ++m) 00063 s += abs(e11.dim(m) - e22.dim(m)); 00064 } 00065 } 00066 if (d > dmax || s > smax) { 00067 id = j; 00068 dmax = d; 00069 smax = s; 00070 } 00071 } 00072 // swap 00073 if (id != i + 1) { 00074 // swap inputs 00075 midx<T> etmp = inputs[id]; 00076 inputs[id] = inputs[i + 1]; 00077 inputs[i + 1] = etmp; 00078 // swap boxes 00079 this->swap(id, i + 1); 00080 } 00081 } 00082 } 00083 00084 } // end namespace ebl 00085 00086 #endif /* BBOX_HPP_ */