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