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// Copyright (C) 2011 Davis E. King (davis@dlib.net)
// License: Boost Software License See LICENSE.txt for the full license.
#ifndef DLIB_MAX_SUM_SUBMaTRIX_H__
#define DLIB_MAX_SUM_SUBMaTRIX_H__
#include "max_sum_submatrix_abstract.h"
#include "../matrix.h"
#include <vector>
#include <queue>
#include "../geometry.h"
namespace dlib
{
namespace impl
{
// ------------------------------------------------------------------------------------
template <typename T>
struct range_set
{
int top_min;
int top_max;
int bottom_min;
int bottom_max;
T weight;
bool operator<(const range_set& item) const { return weight < item.weight; }
};
// ------------------------------------------------------------------------------------
template <typename T>
bool is_terminal_set (
const range_set<T>& item
)
{
return (item.top_min >= item.top_max &&
item.bottom_min >= item.bottom_max);
}
// ------------------------------------------------------------------------------------
template <typename T>
void split (
const range_set<T>& rset,
range_set<T>& a,
range_set<T>& b
)
{
if (rset.top_max - rset.top_min > rset.bottom_max - rset.bottom_min)
{
// split top
const int middle = (rset.top_max + rset.top_min)/2;
a.top_min = rset.top_min;
a.top_max = middle;
b.top_min = middle+1;
b.top_max = rset.top_max;
a.bottom_min = rset.bottom_min;
a.bottom_max = rset.bottom_max;
b.bottom_min = rset.bottom_min;
b.bottom_max = rset.bottom_max;
}
else
{
// split bottom
const int middle = (rset.bottom_max + rset.bottom_min)/2;
a.bottom_min = rset.bottom_min;
a.bottom_max = middle;
b.bottom_min = middle+1;
b.bottom_max = rset.bottom_max;
a.top_min = rset.top_min;
a.top_max = rset.top_max;
b.top_min = rset.top_min;
b.top_max = rset.top_max;
}
}
// ------------------------------------------------------------------------------------
template <typename EXP, typename T>
void find_best_column_range (
const matrix_exp<EXP>& sum_pos,
const matrix_exp<EXP>& sum_neg,
const range_set<T>& row_range,
T& weight,
int& left,
int& right
)
{
left = 0;
right = -1;
weight = 0;
T cur_sum = 0;
int cur_pos = 0;
for (long c = 0; c < sum_pos.nc(); ++c)
{
// compute the value for the current column
T temp = sum_pos(row_range.bottom_max+1,c) - sum_pos(row_range.top_min,c);
if (row_range.top_max <= row_range.bottom_min)
temp += sum_neg(row_range.bottom_min+1,c) - sum_neg(row_range.top_max,c);
cur_sum += temp;
if (cur_sum > weight)
{
left = cur_pos;
right = c;
weight = cur_sum;
}
if (cur_sum <= 0)
{
cur_sum = 0;
cur_pos = c+1;
}
}
}
}
// ----------------------------------------------------------------------------------------
template <typename EXP>
std::vector<rectangle> max_sum_submatrix(
const matrix_exp<EXP>& mat,
unsigned long max_rects,
double thresh_ = 0
)
{
// make sure requires clause is not broken
DLIB_ASSERT(thresh_ >= 0 && mat.size() > 0,
"\t std::vector<rectangle> max_sum_submatrix()"
<< "\n\t Invalid arguments were given to this function."
<< "\n\t mat.size(): " << mat.size()
<< "\n\t thresh_: " << thresh_
);
/*
This function is basically an implementation of the efficient subwindow search (I-ESS)
algorithm presented in the following paper:
Efficient Algorithms for Subwindow Search in Object Detection and Localization
by Senjian An, Patrick Peursum, Wanquan Liu and Svetha Venkatesh
In CVPR 2009
*/
if (max_rects == 0)
return std::vector<rectangle>();
using namespace dlib::impl;
typedef typename EXP::type element_type;
typedef typename promote<element_type>::type scalar_type;
const scalar_type thresh = static_cast<scalar_type>(thresh_);
matrix<scalar_type> sum_pos;
matrix<scalar_type> sum_neg;
sum_pos.set_size(mat.nr()+1, mat.nc());
sum_neg.set_size(mat.nr()+1, mat.nc());
// integrate over the rows.
for (long c = 0; c < mat.nc(); ++c)
{
sum_pos(0,c) = 0;
sum_neg(0,c) = 0;
}
for (long r = 0; r < mat.nr(); ++r)
{
for (long c = 0; c < mat.nc(); ++c)
{
if (mat(r,c) > 0)
{
sum_pos(r+1,c) = mat(r,c) + sum_pos(r,c);
sum_neg(r+1,c) = sum_neg(r,c);
}
else
{
sum_pos(r+1,c) = sum_pos(r,c);
sum_neg(r+1,c) = mat(r,c) + sum_neg(r,c);
}
}
}
std::priority_queue<range_set<scalar_type> > q;
// the range_sets will represent ranges of columns
range_set<scalar_type> universe_set;
universe_set.bottom_min = 0;
universe_set.top_min = 0;
universe_set.bottom_max = mat.nr()-1;
universe_set.top_max = mat.nr()-1;
universe_set.weight = sum(rowm(array_to_matrix(sum_pos),mat.nr()));
q.push(universe_set);
std::vector<rectangle> results;
std::vector<scalar_type> temp_pos(mat.nc());
std::vector<scalar_type> temp_neg(mat.nc());
while (q.size() > 0)
{
if (is_terminal_set(q.top()))
{
int left, right;
scalar_type weight;
find_best_column_range(sum_pos, sum_neg, q.top(), weight, left, right);
rectangle rect(left, q.top().top_min,
right, q.top().bottom_min);
if (weight <= thresh)
break;
results.push_back(rect);
if (results.size() >= max_rects)
break;
q = std::priority_queue<range_set<scalar_type> >();
// We are going to blank out the weights we just used. So adjust the sum images appropriately.
for (long c = rect.left(); c <= rect.right(); ++c)
{
temp_pos[c] = sum_pos(rect.bottom()+1,c) - sum_pos(rect.top(),c);
temp_neg[c] = sum_neg(rect.bottom()+1,c) - sum_neg(rect.top(),c);
}
// blank out the area inside the rectangle
for (long r = rect.top(); r <= rect.bottom(); ++r)
{
for (long c = rect.left(); c <= rect.right(); ++c)
{
sum_pos(r+1,c) = sum_pos(r,c);
sum_neg(r+1,c) = sum_neg(r,c);
}
}
// account for the area below the rectangle
for (long r = rect.bottom()+2; r < sum_pos.nr(); ++r)
{
for (long c = rect.left(); c <= rect.right(); ++c)
{
sum_pos(r,c) -= temp_pos[c];
sum_neg(r,c) -= temp_neg[c];
}
}
universe_set.weight = sum(rowm(array_to_matrix(sum_pos),mat.nr()));
if (universe_set.weight <= thresh)
break;
q.push(universe_set);
continue;
}
range_set<scalar_type> a, b;
split(q.top(), a,b);
q.pop();
// these variables are not used at this point in the algorithm.
int a_left, a_right;
int b_left, b_right;
find_best_column_range(sum_pos, sum_neg, a, a.weight, a_left, a_right);
find_best_column_range(sum_pos, sum_neg, b, b.weight, b_left, b_right);
if (a.weight > thresh)
q.push(a);
if (b.weight > thresh)
q.push(b);
}
return results;
}
// ----------------------------------------------------------------------------------------
}
#endif // DLIB_MAX_SUM_SUBMaTRIX_H__
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