--- /dev/null
+/*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.
+//
+//
+// Intel License Agreement
+// For Open Source Computer Vision Library
+//
+// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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.
+//
+// 2011 Jason Newton <nevion@gmail.com>
+//M*/
+//
+#include "precomp.hpp"
+#include <vector>
+
+#if defined _MSC_VER
+#pragma warning(disable: 4127)
+#endif
+
+namespace cv{
+ namespace connectedcomponents{
+
+ template<typename LabelT>
+ struct NoOp{
+ NoOp(){
+ }
+ void init(const LabelT labels){
+ (void) labels;
+ }
+ inline
+ void operator()(int r, int c, LabelT l){
+ (void) r;
+ (void) c;
+ (void) l;
+ }
+ void finish(){}
+ };
+ struct Point2ui64{
+ uint64 x, y;
+ Point2ui64(uint64 _x, uint64 _y):x(_x), y(_y){}
+ };
+ template<typename LabelT>
+ struct CCStatsOp{
+ OutputArray _mstatsv;
+ cv::Mat statsv;
+ OutputArray _mcentroidsv;
+ cv::Mat centroidsv;
+ std::vector<Point2ui64> integrals;
+
+ CCStatsOp(OutputArray _statsv, OutputArray _centroidsv): _mstatsv(_statsv), _mcentroidsv(_centroidsv){
+ }
+ inline
+ void init(const LabelT nlabels){
+ _mstatsv.create(cv::Size(nlabels, CC_STAT_MAX), cv::DataType<int>::type);
+ statsv = _mstatsv.getMat();
+ _mcentroidsv.create(cv::Size(nlabels, 2), cv::DataType<double>::type);
+ centroidsv = _mcentroidsv.getMat();
+
+ for(int l = 0; l < (int) nlabels; ++l){
+ unsigned int *row = (unsigned int *) &statsv.at<int>(l, 0);
+ row[CC_STAT_LEFT] = std::numeric_limits<LabelT>::max();
+ row[CC_STAT_TOP] = std::numeric_limits<LabelT>::max();
+ row[CC_STAT_WIDTH] = std::numeric_limits<LabelT>::min();
+ row[CC_STAT_HEIGHT] = std::numeric_limits<LabelT>::min();
+ //row[CC_STAT_CX] = 0;
+ //row[CC_STAT_CY] = 0;
+ row[CC_STAT_AREA] = 0;
+ }
+ integrals.resize(nlabels, Point2ui64(0, 0));
+ }
+ void operator()(int r, int c, LabelT l){
+ int *row = &statsv.at<int>(l, 0);
+ unsigned int *urow = (unsigned int *) row;
+ if(c > row[CC_STAT_WIDTH]){
+ row[CC_STAT_WIDTH] = c;
+ }else{
+ if(c < row[CC_STAT_LEFT]){
+ row[CC_STAT_LEFT] = c;
+ }
+ }
+ if(r > row[CC_STAT_HEIGHT]){
+ row[CC_STAT_HEIGHT] = r;
+ }else{
+ if(r < row[CC_STAT_TOP]){
+ row[CC_STAT_TOP] = r;
+ }
+ }
+ urow[CC_STAT_AREA]++;
+ Point2ui64 &integral = integrals[l];
+ integral.x += c;
+ integral.y += r;
+ }
+ void finish(){
+ for(int l = 0; l < statsv.rows; ++l){
+ unsigned int *row = (unsigned int *) &statsv.at<int>(l, 0);
+ row[CC_STAT_LEFT] = std::min(row[CC_STAT_LEFT], row[CC_STAT_WIDTH]);
+ row[CC_STAT_WIDTH] = row[CC_STAT_WIDTH] - row[CC_STAT_LEFT] + 1;
+ row[CC_STAT_TOP] = std::min(row[CC_STAT_TOP], row[CC_STAT_HEIGHT]);
+ row[CC_STAT_HEIGHT] = row[CC_STAT_HEIGHT] - row[CC_STAT_TOP] + 1;
+
+ Point2ui64 &integral = integrals[l];
+ double *centroid = ¢roidsv.at<double>(l, 0);
+ centroid[0] = double(integral.x) / row[CC_STAT_AREA];
+ centroid[1] = double(integral.y) / row[CC_STAT_AREA];
+ }
+ }
+ };
+
+ //Find the root of the tree of node i
+ template<typename LabelT>
+ inline static
+ LabelT findRoot(const LabelT *P, LabelT i){
+ LabelT root = i;
+ while(P[root] < root){
+ root = P[root];
+ }
+ return root;
+ }
+
+ //Make all nodes in the path of node i point to root
+ template<typename LabelT>
+ inline static
+ void setRoot(LabelT *P, LabelT i, LabelT root){
+ while(P[i] < i){
+ LabelT j = P[i];
+ P[i] = root;
+ i = j;
+ }
+ P[i] = root;
+ }
+
+ //Find the root of the tree of the node i and compress the path in the process
+ template<typename LabelT>
+ inline static
+ LabelT find(LabelT *P, LabelT i){
+ LabelT root = findRoot(P, i);
+ setRoot(P, i, root);
+ return root;
+ }
+
+ //unite the two trees containing nodes i and j and return the new root
+ template<typename LabelT>
+ inline static
+ LabelT set_union(LabelT *P, LabelT i, LabelT j){
+ LabelT root = findRoot(P, i);
+ if(i != j){
+ LabelT rootj = findRoot(P, j);
+ if(root > rootj){
+ root = rootj;
+ }
+ setRoot(P, j, root);
+ }
+ setRoot(P, i, root);
+ return root;
+ }
+
+ //Flatten the Union Find tree and relabel the components
+ template<typename LabelT>
+ inline static
+ LabelT flattenL(LabelT *P, LabelT length){
+ LabelT k = 1;
+ for(LabelT i = 1; i < length; ++i){
+ if(P[i] < i){
+ P[i] = P[P[i]];
+ }else{
+ P[i] = k; k = k + 1;
+ }
+ }
+ return k;
+ }
+
+ //Based on "Two Strategies to Speed up Connected Components Algorithms", the SAUF (Scan array union find) variant
+ //using decision trees
+ //Kesheng Wu, et al
+ //Note: rows are encoded as position in the "rows" array to save lookup times
+ //reference for 4-way: {{-1, 0}, {0, -1}};//b, d neighborhoods
+ const int G4[2][2] = {{1, 0}, {0, -1}};//b, d neighborhoods
+ //reference for 8-way: {{-1, -1}, {-1, 0}, {-1, 1}, {0, -1}};//a, b, c, d neighborhoods
+ const int G8[4][2] = {{1, -1}, {1, 0}, {1, 1}, {0, -1}};//a, b, c, d neighborhoods
+ template<typename LabelT, typename PixelT, typename StatsOp = NoOp<LabelT>, int connectivity = 8>
+ struct LabelingImpl{
+ LabelT operator()(const cv::Mat &I, cv::Mat &L, StatsOp &sop){
+ CV_Assert(L.rows == I.rows);
+ CV_Assert(L.cols == I.cols);
+ const int rows = L.rows;
+ const int cols = L.cols;
+ size_t Plength = (size_t(rows + 3 - 1)/3) * (size_t(cols + 3 - 1)/3);
+ if(connectivity == 4){
+ Plength = 4 * Plength;//a quick and dirty upper bound, an exact answer exists if you want to find it
+ //the 4 comes from the fact that a 3x3 block can never have more than 4 unique labels
+ }
+ LabelT *P = (LabelT *) fastMalloc(sizeof(LabelT) * Plength);
+ P[0] = 0;
+ LabelT lunique = 1;
+ //scanning phase
+ for(int r_i = 0; r_i < rows; ++r_i){
+ LabelT *Lrow = (LabelT *)(L.data + L.step.p[0] * r_i);
+ LabelT *Lrow_prev = (LabelT *)(((char *)Lrow) - L.step.p[0]);
+ const PixelT *Irow = (PixelT *)(I.data + I.step.p[0] * r_i);
+ const PixelT *Irow_prev = (const PixelT *)(((char *)Irow) - I.step.p[0]);
+ LabelT *Lrows[2] = {
+ Lrow,
+ Lrow_prev
+ };
+ const PixelT *Irows[2] = {
+ Irow,
+ Irow_prev
+ };
+ if(connectivity == 8){
+ const int a = 0;
+ const int b = 1;
+ const int c = 2;
+ const int d = 3;
+ const bool T_a_r = (r_i - G8[a][0]) >= 0;
+ const bool T_b_r = (r_i - G8[b][0]) >= 0;
+ const bool T_c_r = (r_i - G8[c][0]) >= 0;
+ for(int c_i = 0; Irows[0] != Irow + cols; ++Irows[0], c_i++){
+ if(!*Irows[0]){
+ Lrow[c_i] = 0;
+ continue;
+ }
+ Irows[1] = Irow_prev + c_i;
+ Lrows[0] = Lrow + c_i;
+ Lrows[1] = Lrow_prev + c_i;
+ const bool T_a = T_a_r && (c_i + G8[a][1]) >= 0 && *(Irows[G8[a][0]] + G8[a][1]);
+ const bool T_b = T_b_r && *(Irows[G8[b][0]] + G8[b][1]);
+ const bool T_c = T_c_r && (c_i + G8[c][1]) < cols && *(Irows[G8[c][0]] + G8[c][1]);
+ const bool T_d = (c_i + G8[d][1]) >= 0 && *(Irows[G8[d][0]] + G8[d][1]);
+
+ //decision tree
+ if(T_b){
+ //copy(b)
+ *Lrows[0] = *(Lrows[G8[b][0]] + G8[b][1]);
+ }else{//not b
+ if(T_c){
+ if(T_a){
+ //copy(c, a)
+ *Lrows[0] = set_union(P, *(Lrows[G8[c][0]] + G8[c][1]), *(Lrows[G8[a][0]] + G8[a][1]));
+ }else{
+ if(T_d){
+ //copy(c, d)
+ *Lrows[0] = set_union(P, *(Lrows[G8[c][0]] + G8[c][1]), *(Lrows[G8[d][0]] + G8[d][1]));
+ }else{
+ //copy(c)
+ *Lrows[0] = *(Lrows[G8[c][0]] + G8[c][1]);
+ }
+ }
+ }else{//not c
+ if(T_a){
+ //copy(a)
+ *Lrows[0] = *(Lrows[G8[a][0]] + G8[a][1]);
+ }else{
+ if(T_d){
+ //copy(d)
+ *Lrows[0] = *(Lrows[G8[d][0]] + G8[d][1]);
+ }else{
+ //new label
+ *Lrows[0] = lunique;
+ P[lunique] = lunique;
+ lunique = lunique + 1;
+ }
+ }
+ }
+ }
+ }
+ }else{
+ //B & D only
+ assert(connectivity == 4);
+ const int b = 0;
+ const int d = 1;
+ const bool T_b_r = (r_i - G4[b][0]) >= 0;
+ for(int c_i = 0; Irows[0] != Irow + cols; ++Irows[0], c_i++){
+ if(!*Irows[0]){
+ Lrow[c_i] = 0;
+ continue;
+ }
+ Irows[1] = Irow_prev + c_i;
+ Lrows[0] = Lrow + c_i;
+ Lrows[1] = Lrow_prev + c_i;
+ const bool T_b = T_b_r && *(Irows[G4[b][0]] + G4[b][1]);
+ const bool T_d = (c_i + G4[d][1]) >= 0 && *(Irows[G4[d][0]] + G4[d][1]);
+ if(T_b){
+ if(T_d){
+ //copy(d, b)
+ *Lrows[0] = set_union(P, *(Lrows[G4[d][0]] + G4[d][1]), *(Lrows[G4[b][0]] + G4[b][1]));
+ }else{
+ //copy(b)
+ *Lrows[0] = *(Lrows[G4[b][0]] + G4[b][1]);
+ }
+ }else{
+ if(T_d){
+ //copy(d)
+ *Lrows[0] = *(Lrows[G4[d][0]] + G4[d][1]);
+ }else{
+ //new label
+ *Lrows[0] = lunique;
+ P[lunique] = lunique;
+ lunique = lunique + 1;
+ }
+ }
+ }
+ }
+ }
+
+ //analysis
+ LabelT nLabels = flattenL(P, lunique);
+ sop.init(nLabels);
+
+ for(int r_i = 0; r_i < rows; ++r_i){
+ LabelT *Lrow_start = (LabelT *)(L.data + L.step.p[0] * r_i);
+ LabelT *Lrow_end = Lrow_start + cols;
+ LabelT *Lrow = Lrow_start;
+ for(int c_i = 0; Lrow != Lrow_end; ++Lrow, ++c_i){
+ const LabelT l = P[*Lrow];
+ *Lrow = l;
+ sop(r_i, c_i, l);
+ }
+ }
+
+ sop.finish();
+ fastFree(P);
+
+ return nLabels;
+ }//End function LabelingImpl operator()
+
+ };//End struct LabelingImpl
+}//end namespace connectedcomponents
+
+//L's type must have an appropriate depth for the number of pixels in I
+template<typename StatsOp>
+static
+int connectedComponents_sub1(const cv::Mat &I, cv::Mat &L, int connectivity, StatsOp &sop){
+ CV_Assert(L.channels() == 1 && I.channels() == 1);
+ CV_Assert(connectivity == 8 || connectivity == 4);
+
+ int lDepth = L.depth();
+ int iDepth = I.depth();
+ using connectedcomponents::LabelingImpl;
+ //warn if L's depth is not sufficient?
+
+ if(lDepth == CV_8U){
+ if(iDepth == CV_8U || iDepth == CV_8S){
+ if(connectivity == 4){
+ return (int) LabelingImpl<uchar, uchar, StatsOp, 4>()(I, L, sop);
+ }else{
+ return (int) LabelingImpl<uchar, uchar, StatsOp, 8>()(I, L, sop);
+ }
+ }else{
+ CV_Assert(false);
+ }
+ }else if(lDepth == CV_16U){
+ if(iDepth == CV_8U || iDepth == CV_8S){
+ if(connectivity == 4){
+ return (int) LabelingImpl<ushort, uchar, StatsOp, 4>()(I, L, sop);
+ }else{
+ return (int) LabelingImpl<ushort, uchar, StatsOp, 8>()(I, L, sop);
+ }
+ }else{
+ CV_Assert(false);
+ }
+ }else if(lDepth == CV_32S){
+ //note that signed types don't really make sense here and not being able to use unsigned matters for scientific projects
+ //OpenCV: how should we proceed? .at<T> typechecks in debug mode
+ if(iDepth == CV_8U || iDepth == CV_8S){
+ if(connectivity == 4){
+ return (int) LabelingImpl<int, uchar, StatsOp, 4>()(I, L, sop);
+ }else{
+ return (int) LabelingImpl<int, uchar, StatsOp, 8>()(I, L, sop);
+ }
+ }else{
+ CV_Assert(false);
+ }
+ }
+
+ CV_Error(CV_StsUnsupportedFormat, "unsupported label/image type");
+ return -1;
+}
+
+int connectedComponents(InputArray _I, OutputArray _L, int connectivity, int ltype){
+ const cv::Mat I = _I.getMat();
+ _L.create(I.size(), CV_MAT_TYPE(ltype));
+ cv::Mat L = _L.getMat();
+ if(ltype == CV_16U){
+ connectedcomponents::NoOp<ushort> sop; return connectedComponents_sub1(I, L, connectivity, sop);
+ }else if(ltype == CV_32S){
+ connectedcomponents::NoOp<unsigned> sop; return connectedComponents_sub1(I, L, connectivity, sop);
+ }else{
+ CV_Assert(false);
+ return 0;
+ }
+}
+
+int connectedComponentsWithStats(InputArray _I, OutputArray _L, OutputArray statsv, OutputArray centroids, int connectivity, int ltype){
+ const cv::Mat I = _I.getMat();
+ _L.create(I.size(), CV_MAT_TYPE(ltype));
+ cv::Mat L = _L.getMat();
+ if(ltype == CV_16U){
+ connectedcomponents::CCStatsOp<ushort> sop(statsv, centroids); return connectedComponents_sub1(I, L, connectivity, sop);
+ }else if(ltype == CV_32S){
+ connectedcomponents::CCStatsOp<unsigned> sop(statsv, centroids); return connectedComponents_sub1(I, L, connectivity, sop);
+ }else{
+ CV_Assert(false);
+ return 0;
+ }
+}
+
+}
--- /dev/null
+/*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 "test_precomp.hpp"
+#include <string>
+
+using namespace cv;
+using namespace std;
+
+class CV_ConnectedComponentsTest : public cvtest::BaseTest
+{
+public:
+ CV_ConnectedComponentsTest();
+ ~CV_ConnectedComponentsTest();
+protected:
+ void run(int);
+};
+
+CV_ConnectedComponentsTest::CV_ConnectedComponentsTest() {}
+CV_ConnectedComponentsTest::~CV_ConnectedComponentsTest() {}
+
+void CV_ConnectedComponentsTest::run( int /* start_from */)
+{
+ string exp_path = string(ts->get_data_path()) + "connectedcomponents/ccomp_exp.png";
+ Mat exp = imread(exp_path, 0);
+ Mat orig = imread(string(ts->get_data_path()) + "connectedcomponents/concentric_circles.png", 0);
+
+ if (orig.empty())
+ {
+ ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
+ return;
+ }
+
+ Mat bw = orig > 128;
+ Mat labelImage;
+ int nLabels = connectedComponents(bw, labelImage, 8, CV_32S);
+
+ for(int r = 0; r < labelImage.rows; ++r){
+ for(int c = 0; c < labelImage.cols; ++c){
+ int l = labelImage.at<int>(r, c);
+ bool pass = l >= 0 && l <= nLabels;
+ if(!pass){
+ ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
+ return;
+ }
+ }
+ }
+
+ if( exp.empty() || orig.size() != exp.size() )
+ {
+ imwrite(exp_path, labelImage);
+ exp = labelImage;
+ }
+
+ if (0 != norm(labelImage > 0, exp > 0, NORM_INF))
+ {
+ ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
+ return;
+ }
+ if (nLabels != norm(labelImage, NORM_INF)+1)
+ {
+ ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
+ return;
+ }
+ ts->set_failed_test_info(cvtest::TS::OK);
+}
+
+TEST(Imgproc_ConnectedComponents, regression) { CV_ConnectedComponentsTest test; test.safe_run(); }
+
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