|
|
|
/*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;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
}
|