opencv/modules/cudaimgproc/src/mssegmentation.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
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// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
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// and on any theory of liability, whether in contract, strict liability,
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#include "precomp.hpp"
#if !defined HAVE_CUDA || defined(CUDA_DISABLER)
void cv::cuda::meanShiftSegmentation(InputArray, OutputArray, int, int, int, TermCriteria, Stream&) { throw_no_cuda(); }
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#else
// Auxiliray stuff
namespace
{
//
// Declarations
//
class DjSets
{
public:
DjSets(int n);
int find(int elem);
int merge(int set1, int set2);
std::vector<int> parent;
std::vector<int> rank;
std::vector<int> size;
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private:
DjSets(const DjSets&);
void operator =(const DjSets&);
};
template <typename T>
struct GraphEdge
{
GraphEdge() {}
GraphEdge(int to_, int next_, const T& val_) : to(to_), next(next_), val(val_) {}
int to;
int next;
T val;
};
template <typename T>
class Graph
{
public:
typedef GraphEdge<T> Edge;
Graph(int numv, int nume_max);
void addEdge(int from, int to, const T& val=T());
std::vector<int> start;
std::vector<Edge> edges;
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int numv;
int nume_max;
int nume;
private:
Graph(const Graph&);
void operator =(const Graph&);
};
struct SegmLinkVal
{
SegmLinkVal() {}
SegmLinkVal(int dr_, int dsp_) : dr(dr_), dsp(dsp_) {}
bool operator <(const SegmLinkVal& other) const
{
return dr + dsp < other.dr + other.dsp;
}
int dr;
int dsp;
};
struct SegmLink
{
SegmLink() {}
SegmLink(int from_, int to_, const SegmLinkVal& val_)
: from(from_), to(to_), val(val_) {}
bool operator <(const SegmLink& other) const
{
return val < other.val;
}
int from;
int to;
SegmLinkVal val;
};
//
// Implementation
//
DjSets::DjSets(int n) : parent(n), rank(n, 0), size(n, 1)
{
for (int i = 0; i < n; ++i)
parent[i] = i;
}
inline int DjSets::find(int elem)
{
int set = elem;
while (set != parent[set])
set = parent[set];
while (elem != parent[elem])
{
int next = parent[elem];
parent[elem] = set;
elem = next;
}
return set;
}
inline int DjSets::merge(int set1, int set2)
{
if (rank[set1] < rank[set2])
{
parent[set1] = set2;
size[set2] += size[set1];
return set2;
}
if (rank[set2] < rank[set1])
{
parent[set2] = set1;
size[set1] += size[set2];
return set1;
}
parent[set1] = set2;
rank[set2]++;
size[set2] += size[set1];
return set2;
}
template <typename T>
Graph<T>::Graph(int numv_, int nume_max_) : start(numv_, -1), edges(nume_max_)
{
this->numv = numv_;
this->nume_max = nume_max_;
nume = 0;
}
template <typename T>
inline void Graph<T>::addEdge(int from, int to, const T& val)
{
edges[nume] = Edge(to, start[from], val);
start[from] = nume;
nume++;
}
inline int pix(int y, int x, int ncols)
{
return y * ncols + x;
}
inline int sqr(int x)
{
return x * x;
}
inline int dist2(const cv::Vec4b& lhs, const cv::Vec4b& rhs)
{
return sqr(lhs[0] - rhs[0]) + sqr(lhs[1] - rhs[1]) + sqr(lhs[2] - rhs[2]);
}
inline int dist2(const cv::Vec2s& lhs, const cv::Vec2s& rhs)
{
return sqr(lhs[0] - rhs[0]) + sqr(lhs[1] - rhs[1]);
}
} // anonymous namespace
void cv::cuda::meanShiftSegmentation(InputArray _src, OutputArray _dst, int sp, int sr, int minsize, TermCriteria criteria, Stream& stream)
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{
GpuMat src = _src.getGpuMat();
CV_Assert( src.type() == CV_8UC4 );
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const int nrows = src.rows;
const int ncols = src.cols;
const int hr = sr;
const int hsp = sp;
// Perform mean shift procedure and obtain region and spatial maps
GpuMat d_rmap, d_spmap;
cuda::meanShiftProc(src, d_rmap, d_spmap, sp, sr, criteria, stream);
stream.waitForCompletion();
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Mat rmap(d_rmap);
Mat spmap(d_spmap);
Graph<SegmLinkVal> g(nrows * ncols, 4 * (nrows - 1) * (ncols - 1)
+ (nrows - 1) + (ncols - 1));
// Make region adjacent graph from image
Vec4b r1;
Vec4b r2[4];
Vec2s sp1;
Vec2s sp2[4];
int dr[4];
int dsp[4];
for (int y = 0; y < nrows - 1; ++y)
{
Vec4b* ry = rmap.ptr<Vec4b>(y);
Vec4b* ryp = rmap.ptr<Vec4b>(y + 1);
Vec2s* spy = spmap.ptr<Vec2s>(y);
Vec2s* spyp = spmap.ptr<Vec2s>(y + 1);
for (int x = 0; x < ncols - 1; ++x)
{
r1 = ry[x];
sp1 = spy[x];
r2[0] = ry[x + 1];
r2[1] = ryp[x];
r2[2] = ryp[x + 1];
r2[3] = ryp[x];
sp2[0] = spy[x + 1];
sp2[1] = spyp[x];
sp2[2] = spyp[x + 1];
sp2[3] = spyp[x];
dr[0] = dist2(r1, r2[0]);
dr[1] = dist2(r1, r2[1]);
dr[2] = dist2(r1, r2[2]);
dsp[0] = dist2(sp1, sp2[0]);
dsp[1] = dist2(sp1, sp2[1]);
dsp[2] = dist2(sp1, sp2[2]);
r1 = ry[x + 1];
sp1 = spy[x + 1];
dr[3] = dist2(r1, r2[3]);
dsp[3] = dist2(sp1, sp2[3]);
g.addEdge(pix(y, x, ncols), pix(y, x + 1, ncols), SegmLinkVal(dr[0], dsp[0]));
g.addEdge(pix(y, x, ncols), pix(y + 1, x, ncols), SegmLinkVal(dr[1], dsp[1]));
g.addEdge(pix(y, x, ncols), pix(y + 1, x + 1, ncols), SegmLinkVal(dr[2], dsp[2]));
g.addEdge(pix(y, x + 1, ncols), pix(y + 1, x, ncols), SegmLinkVal(dr[3], dsp[3]));
}
}
for (int y = 0; y < nrows - 1; ++y)
{
r1 = rmap.at<Vec4b>(y, ncols - 1);
r2[0] = rmap.at<Vec4b>(y + 1, ncols - 1);
sp1 = spmap.at<Vec2s>(y, ncols - 1);
sp2[0] = spmap.at<Vec2s>(y + 1, ncols - 1);
dr[0] = dist2(r1, r2[0]);
dsp[0] = dist2(sp1, sp2[0]);
g.addEdge(pix(y, ncols - 1, ncols), pix(y + 1, ncols - 1, ncols), SegmLinkVal(dr[0], dsp[0]));
}
for (int x = 0; x < ncols - 1; ++x)
{
r1 = rmap.at<Vec4b>(nrows - 1, x);
r2[0] = rmap.at<Vec4b>(nrows - 1, x + 1);
sp1 = spmap.at<Vec2s>(nrows - 1, x);
sp2[0] = spmap.at<Vec2s>(nrows - 1, x + 1);
dr[0] = dist2(r1, r2[0]);
dsp[0] = dist2(sp1, sp2[0]);
g.addEdge(pix(nrows - 1, x, ncols), pix(nrows - 1, x + 1, ncols), SegmLinkVal(dr[0], dsp[0]));
}
DjSets comps(g.numv);
// Find adjacent components
for (int v = 0; v < g.numv; ++v)
{
for (int e_it = g.start[v]; e_it != -1; e_it = g.edges[e_it].next)
{
int c1 = comps.find(v);
int c2 = comps.find(g.edges[e_it].to);
if (c1 != c2 && g.edges[e_it].val.dr < hr && g.edges[e_it].val.dsp < hsp)
comps.merge(c1, c2);
}
}
std::vector<SegmLink> edges;
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edges.reserve(g.numv);
// Prepare edges connecting differnet components
for (int v = 0; v < g.numv; ++v)
{
int c1 = comps.find(v);
for (int e_it = g.start[v]; e_it != -1; e_it = g.edges[e_it].next)
{
int c2 = comps.find(g.edges[e_it].to);
if (c1 != c2)
edges.push_back(SegmLink(c1, c2, g.edges[e_it].val));
}
}
// Sort all graph's edges connecting differnet components (in asceding order)
std::sort(edges.begin(), edges.end());
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// Exclude small components (starting from the nearest couple)
for (size_t i = 0; i < edges.size(); ++i)
{
int c1 = comps.find(edges[i].from);
int c2 = comps.find(edges[i].to);
if (c1 != c2 && (comps.size[c1] < minsize || comps.size[c2] < minsize))
comps.merge(c1, c2);
}
// Compute sum of the pixel's colors which are in the same segment
Mat h_src(src);
std::vector<Vec4i> sumcols(nrows * ncols, Vec4i(0, 0, 0, 0));
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for (int y = 0; y < nrows; ++y)
{
Vec4b* h_srcy = h_src.ptr<Vec4b>(y);
for (int x = 0; x < ncols; ++x)
{
int parent = comps.find(pix(y, x, ncols));
Vec4b col = h_srcy[x];
Vec4i& sumcol = sumcols[parent];
sumcol[0] += col[0];
sumcol[1] += col[1];
sumcol[2] += col[2];
}
}
// Create final image, color of each segment is the average color of its pixels
_dst.create(src.size(), src.type());
Mat dst = _dst.getMat();
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for (int y = 0; y < nrows; ++y)
{
Vec4b* dsty = dst.ptr<Vec4b>(y);
for (int x = 0; x < ncols; ++x)
{
int parent = comps.find(pix(y, x, ncols));
const Vec4i& sumcol = sumcols[parent];
Vec4b& dstcol = dsty[x];
dstcol[0] = static_cast<uchar>(sumcol[0] / comps.size[parent]);
dstcol[1] = static_cast<uchar>(sumcol[1] / comps.size[parent]);
dstcol[2] = static_cast<uchar>(sumcol[2] / comps.size[parent]);
dstcol[3] = 255;
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}
}
}
#endif // #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)