diff --git a/modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst b/modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst index 55cea58d5..ad5c22cbb 100644 --- a/modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst +++ b/modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst @@ -118,6 +118,48 @@ These values are proved to be invariants to the image scale, rotation, and refle .. seealso:: :ocv:func:`matchShapes` +connectedComponents +----------- +computes the connected components labeled image of boolean image I with 4 or 8 way connectivity - returns N, the total +number of labels [0, N-1] where 0 represents the background label. L's value type determines the label type, an important +consideration based on the total number of labels or alternatively the total number of pixels. + +.. ocv:function:: uint64 connectedComponents(Mat &L, const Mat &I, int connectivity = 8) + +.. ocv:function:: uint64 connectedComponentsWithStats(Mat &L, const Mat &I, std::vector &statsv, int connectivity = 8) + + :param L: destitination Labeled image + + :param I: the image to be labeled + + :param connectivity: 8 or 4 for 8-way or 4-way connectivity respectively + + :param statsv: statistics for each label, including the background label + +Statistics information such as bounding box, area, and centroid is exported via the ``ConnectComponentStats`` structure defined as: :: + + class CV_EXPORTS ConnectedComponentStats + { + public: + //! lower left corner column + int lower_x; + //! lower left corner row + int lower_y; + //! upper right corner column + int upper_x; + //! upper right corner row + int upper_y; + //! centroid column + double centroid_x; + //! centroid row + double centroid_y; + //! sum of all columns where the image was non-zero + uint64 integral_x; + //! sum of all rows where the image was non-zero + uint64 integral_y; + //! count of all non-zero pixels + unsigned int area; + }; findContours ---------------- diff --git a/modules/imgproc/include/opencv2/imgproc/imgproc.hpp b/modules/imgproc/include/opencv2/imgproc/imgproc.hpp index c0c51f57a..6be7ef6d1 100644 --- a/modules/imgproc/include/opencv2/imgproc/imgproc.hpp +++ b/modules/imgproc/include/opencv2/imgproc/imgproc.hpp @@ -1102,6 +1102,15 @@ enum { TM_SQDIFF=0, TM_SQDIFF_NORMED=1, TM_CCORR=2, TM_CCORR_NORMED=3, TM_CCOEFF CV_EXPORTS_W void matchTemplate( InputArray image, InputArray templ, OutputArray result, int method ); +enum { CC_STAT_LEFT=0, CC_STAT_TOP=1, CC_STAT_WIDTH=2, CC_STAT_HEIGHT=3, CC_STAT_AREA=4, CC_STAT_MAX = 5}; + +//! computes the connected components labeled image of boolean image I with 4 or 8 way connectivity - returns N, the total +//number of labels [0, N-1] where 0 represents the background label. L's value type determines the label type, an important +//consideration based on the total number of labels or alternatively the total number of pixels. +CV_EXPORTS_W int connectedComponents(InputArray image, OutputArray labels, int connectivity = 8, int ltype=CV_32S); +CV_EXPORTS_W int connectedComponentsWithStats(InputArray image, OutputArray labels, OutputArray stats, OutputArray centroids, int connectivity = 8, int ltype=CV_32S); + + //! mode of the contour retrieval algorithm enum { diff --git a/modules/imgproc/src/connectedcomponents.cpp b/modules/imgproc/src/connectedcomponents.cpp new file mode 100644 index 000000000..97da8824d --- /dev/null +++ b/modules/imgproc/src/connectedcomponents.cpp @@ -0,0 +1,437 @@ +/*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 +//M*/ +// +#include "precomp.hpp" +#include + +#if defined _MSC_VER +#pragma warning(disable: 4127) +#endif + +namespace cv{ + namespace connectedcomponents{ + + template + 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 + struct CCStatsOp{ + OutputArray _mstatsv; + cv::Mat statsv; + OutputArray _mcentroidsv; + cv::Mat centroidsv; + std::vector 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::type); + statsv = _mstatsv.getMat(); + _mcentroidsv.create(cv::Size(nlabels, 2), cv::DataType::type); + centroidsv = _mcentroidsv.getMat(); + + for(int l = 0; l < (int) nlabels; ++l){ + unsigned int *row = (unsigned int *) &statsv.at(l, 0); + row[CC_STAT_LEFT] = std::numeric_limits::max(); + row[CC_STAT_TOP] = std::numeric_limits::max(); + row[CC_STAT_WIDTH] = std::numeric_limits::min(); + row[CC_STAT_HEIGHT] = std::numeric_limits::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(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(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(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 + 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 + 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 + 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 + 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 + 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, 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 +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()(I, L, sop); + }else{ + return (int) LabelingImpl()(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()(I, L, sop); + }else{ + return (int) LabelingImpl()(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 typechecks in debug mode + if(iDepth == CV_8U || iDepth == CV_8S){ + if(connectivity == 4){ + return (int) LabelingImpl()(I, L, sop); + }else{ + return (int) LabelingImpl()(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 sop; return connectedComponents_sub1(I, L, connectivity, sop); + }else if(ltype == CV_32S){ + connectedcomponents::NoOp 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 sop(statsv, centroids); return connectedComponents_sub1(I, L, connectivity, sop); + }else if(ltype == CV_32S){ + connectedcomponents::CCStatsOp sop(statsv, centroids); return connectedComponents_sub1(I, L, connectivity, sop); + }else{ + CV_Assert(false); + return 0; + } +} + +} diff --git a/modules/imgproc/test/test_connectedcomponents.cpp b/modules/imgproc/test/test_connectedcomponents.cpp new file mode 100644 index 000000000..c428cc074 --- /dev/null +++ b/modules/imgproc/test/test_connectedcomponents.cpp @@ -0,0 +1,108 @@ +/*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 + +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(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(); } + diff --git a/modules/python/src2/cv2.cpp b/modules/python/src2/cv2.cpp index 28cf00eac..bc52f308c 100644 --- a/modules/python/src2/cv2.cpp +++ b/modules/python/src2/cv2.cpp @@ -410,7 +410,7 @@ static bool pyopencv_to(PyObject* obj, bool& value, const char* name = " threshval); - - vector > contours; - vector hierarchy; - - findContours( bw, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE ); - - Mat dst = Mat::zeros(img.size(), CV_8UC3); - - if( !contours.empty() && !hierarchy.empty() ) - { - // iterate through all the top-level contours, - // draw each connected component with its own random color - int idx = 0; - for( ; idx >= 0; idx = hierarchy[idx][0] ) - { - Scalar color( (rand()&255), (rand()&255), (rand()&255) ); - drawContours( dst, contours, idx, color, CV_FILLED, 8, hierarchy ); - } + Mat labelImage(img.size(), CV_32S); + int nLabels = connectedComponents(bw, labelImage, 8); + std::vector colors(nLabels); + colors[0] = Vec3b(0, 0, 0);//background + for(int label = 1; label < nLabels; ++label){ + colors[label] = Vec3b( (rand()&255), (rand()&255), (rand()&255) ); } + Mat dst(img.size(), CV_8UC3); + for(int r = 0; r < dst.rows; ++r){ + for(int c = 0; c < dst.cols; ++c){ + int label = labelImage.at(r, c); + Vec3b &pixel = dst.at(r, c); + pixel = colors[label]; + } + } imshow( "Connected Components", dst ); } @@ -45,14 +41,14 @@ static void help() const char* keys = { - "{@image |stuff.jpg|image for converting to a grayscale}" + "{@image|stuff.jpg|image for converting to a grayscale}" }; int main( int argc, const char** argv ) { help(); CommandLineParser parser(argc, argv, keys); - string inputImage = parser.get(1); + string inputImage = parser.get("@image"); img = imread(inputImage.c_str(), 0); if(img.empty())