root/modules/cudaimgproc/src/mssegmentation.cpp

/* [<][>][^][v][top][bottom][index][help] */

DEFINITIONS

This source file includes following definitions.
  1. meanShiftSegmentation
  2. val
  3. size
  4. find
  5. merge
  6. edges
  7. addEdge
  8. pix
  9. sqr
  10. dist2
  11. dist2
  12. meanShiftSegmentation

/*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.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"

#if !defined HAVE_CUDA || defined(CUDA_DISABLER)

void cv::cuda::meanShiftSegmentation(InputArray, OutputArray, int, int, int, TermCriteria, Stream&) { throw_no_cuda(); }

#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;
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;

    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)
{
    GpuMat src = _src.getGpuMat();

    CV_Assert( src.type() == CV_8UC4 );

    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();

    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;
    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());

    // 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));
    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();

    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;
        }
    }
}

#endif // #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)

/* [<][>][^][v][top][bottom][index][help] */