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#include <iostream>
// ViSP includes
#include <visp3/core/vpConfig.h>
#include <visp3/core/vpException.h>
#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageConvert.h>
#include <visp3/core/vpImageDraw.h>
#include <visp3/core/vpIoTools.h>
#include <visp3/core/vpTime.h>
#include <visp3/imgproc/vpCircleHoughTransform.h>
#include <visp3/imgproc/vpImgproc.h>
#include <visp3/io/vpImageIo.h>
#include <visp3/io/vpVideoReader.h>
#if (VISP_CXX_STANDARD >= VISP_CXX_STANDARD_11)
#include "drawingHelpers.h"
//! [Enum input]
typedef enum TypeInputImage
{
FULL_DISKS = 0,
HALF_DISKS = 1,
QUARTER_DISKS = 2,
USER_IMG = 3
}TypeInputImage;
std::string typeInputImageToString(const TypeInputImage &type)
{
std::string name;
switch (type) {
case FULL_DISKS:
name = "full_disks";
break;
case HALF_DISKS:
name = "half_disks";
break;
case QUARTER_DISKS:
name = "quarter_disks";
break;
case USER_IMG:
name = "path/to/your/image";
}
return name;
}
//! [Enum input]
TypeInputImage typeInputImageFromString(const std::string &name)
{
TypeInputImage type(USER_IMG);
bool hasFound(false);
for (unsigned int id = 0; id < USER_IMG && !hasFound; id++) {
TypeInputImage candidate = (TypeInputImage)id;
if (name == typeInputImageToString(candidate)) {
type = candidate;
hasFound = true;
}
}
return type;
}
std::string getAvailableTypeInputImage(const std::string &prefix = "<", const std::string &sep = " , ", const std::string &suffix = ">")
{
std::string list(prefix);
for (unsigned int id = 0; id < USER_IMG; id++) {
list += typeInputImageToString((TypeInputImage)id) + sep;
}
list += typeInputImageToString(USER_IMG) + suffix;
return list;
}
//! [Draw disks]
void
drawDisk(vpImage<unsigned char> &I, const vpImagePoint ¢er, const unsigned int &radius,
const unsigned int &borderColor, const unsigned int &fillingColor, const unsigned int &thickness, const unsigned int &bckg)
//! [Draw disks]
{
vpImageDraw::drawCircle(I, center, radius, borderColor, thickness);
vp::floodFill(I,
center,
bckg,
fillingColor,
vpImageMorphology::CONNEXITY_4
);
}
//! [Draw synthetic]
vpImage<unsigned char>
generateImage(const TypeInputImage &inputType)
//! [Draw synthetic]
{
// // Image dimensions and background
const unsigned int width = 640;
const unsigned int height = 480;
const unsigned int bckg = 0;
// // Disks parameters
const unsigned int circleColor = 128;
const unsigned int circleRadius = 50;
const unsigned int circleThickness = 1;
// // Disks position when full circles
const double topFull = height / 4;
const double bottomFull = 3 * height / 4;
const double leftFull = width / 4;
const double rightFull = 3 * width / 4;
// // Disks position when Half of circles
const double topHalf = 1; // m_centerThresh(25) , m_radiusBinSize(10) , m_radiusRatioThresh(50) , m_mergingDistanceThresh(15) , m_mergingRadiusDiffThresh(1.5 * (double) m_radiusBinSize)
const double bottomHalf = height - 1;
const double leftHalf = width / 4;
const double rightHalf = 3 * width / 4;
// // Disks position when Quarter of circles
const double topQuarter = 1; // m_centerThresh(15) , m_radiusBinSize(10) , m_radiusRatioThresh(50) , m_mergingDistanceThresh(15) , m_mergingRadiusDiffThresh(1.5 * (double) m_radiusBinSize)
const double bottomQuarter = height - 1;
const double leftQuarter = 1;
const double rightQuarter = width - 1;
vpImage<unsigned char> I_src(height, width, bckg);
// // Selecting position of the disks depending on their visibility
double top, left, bottom, right;
switch (inputType) {
case FULL_DISKS:
top = topFull;
left = leftFull;
bottom = bottomFull;
right = rightFull;
break;
case HALF_DISKS:
top = topHalf;
left = leftHalf;
bottom = bottomHalf;
right = rightHalf;
break;
case QUARTER_DISKS:
top = topQuarter;
left = leftQuarter;
bottom = bottomQuarter;
right = rightQuarter;
break;
default:
throw(vpException(vpException::badValue, "Using other type of input than the one that has been implemented to generate disks."));
break;
}
drawDisk(I_src, vpImagePoint(top, left), circleRadius, circleColor, circleColor, circleThickness, bckg);
drawDisk(I_src, vpImagePoint(top, left), circleRadius / 2, circleColor / 2, circleColor / 2, circleThickness, circleColor);
drawDisk(I_src, vpImagePoint(bottom, left), circleRadius, circleColor, circleColor, circleThickness, bckg);
drawDisk(I_src, vpImagePoint(bottom, left), circleRadius / 2, circleColor / 2, circleColor / 2, circleThickness, circleColor);
drawDisk(I_src, vpImagePoint(top, right), circleRadius, circleColor, circleColor, circleThickness, bckg);
drawDisk(I_src, vpImagePoint(top, right), circleRadius / 2, circleColor / 2, circleColor / 2, circleThickness, circleColor);
drawDisk(I_src, vpImagePoint(bottom, right), circleRadius, circleColor, circleColor, circleThickness, bckg);
drawDisk(I_src, vpImagePoint(bottom, right), circleRadius / 2, circleColor / 2, circleColor / 2, circleThickness, circleColor);
std::cout << "Done drawing" << std::endl << std::flush;
return I_src;
}
bool test_detection(const vpImage<unsigned char> &I_src, vpCircleHoughTransform &detector, const int &nbCirclesToDetect, const bool &blockingMode, const bool &displayCanny)
{
double t0 = vpTime::measureTimeMicros();
//! [Run detection]
std::vector<vpImageCircle> detectedCircles = detector.detect(I_src, nbCirclesToDetect);
//! [Run detection]
double tF = vpTime::measureTimeMicros();
std::cout << "Process time = " << (tF - t0) * 0.001 << "ms" << std::endl << std::flush;
vpImage<vpRGBa> I_disp;
vpImageConvert::convert(I_src, I_disp);
unsigned int id = 0;
std::vector<vpColor> v_colors = { vpColor::red, vpColor::purple, vpColor::orange, vpColor::yellow, vpColor::blue };
unsigned int idColor = 0;
//! [Iterate detections]
for (auto circleCandidate : detectedCircles) {
vpImageDraw::drawCircle(I_disp, circleCandidate, v_colors[idColor], 2);
std::cout << "Circle #" << id << ":" << std::endl;
std::cout << "\tCenter: (" << circleCandidate.getCenter() << ")" << std::endl;
std::cout << "\tRadius: (" << circleCandidate.getRadius() << ")" << std::endl;
id++;
idColor = (idColor + 1) % v_colors.size();
}
//! [Iterate detections]
if (displayCanny) {
vpImage<unsigned char> edgeMap = detector.getEdgeMap();
drawingHelpers::display(edgeMap, "Edge map", true);
}
return drawingHelpers::display(I_disp, "Detection results", blockingMode);
}
int main(int argc, char **argv)
{
const std::string def_input(typeInputImageToString(FULL_DISKS));
const std::string def_jsonFilePath = std::string("");
const int def_nbCirclesToDetect = -1;
const int def_gaussianKernelSize = 5;
const float def_gaussianSigma = 1.f;
const int def_sobelKernelSize = 3;
#ifdef HAVE_OPENCV_IMGPROC
const float def_lowerCannyThresh = 50.f;
const float def_upperCannyThresh = 150.f;
#else
const float def_lowerCannyThresh = 8.f;
const float def_upperCannyThresh = 25.f;
#endif
const int def_nbEdgeFilteringIter = 2;
const std::pair<int, int> def_centerXlimits = std::pair<int, int>(0, 640);
const std::pair<int, int> def_centerYlimits = std::pair<int, int>(0, 480);
const unsigned int def_minRadius = 0;
const unsigned int def_maxRadius = 1000;
const int def_dilatationRepet = 1;
const float def_centerThresh = -1.f;
const float def_radiusThreshRatio = -1.f;
const float def_circlePerfectness = 0.85f;
const float def_centerDistanceThresh = 15.f;
const float def_radiusDifferenceThresh = 15.f;
std::string opt_input(def_input);
std::string opt_jsonFilePath = def_jsonFilePath;
int opt_nbCirclesToDetect = def_nbCirclesToDetect;
int opt_gaussianKernelSize = def_gaussianKernelSize;
float opt_gaussianSigma = def_gaussianSigma;
int opt_sobelKernelSize = def_sobelKernelSize;
float opt_lowerCannyThresh = def_lowerCannyThresh;
float opt_upperCannyThresh = def_upperCannyThresh;
int opt_nbEdgeFilteringIter = def_nbEdgeFilteringIter;
std::pair<int, int> opt_centerXlimits = def_centerXlimits;
std::pair<int, int> opt_centerYlimits = def_centerYlimits;
unsigned int opt_minRadius = def_minRadius;
unsigned int opt_maxRadius = def_maxRadius;
int opt_dilatationRepet = def_dilatationRepet;
float opt_centerThresh = def_centerThresh;
float opt_radiusThreshRatio = def_radiusThreshRatio;
float opt_circlePerfectness = def_circlePerfectness;
float opt_centerDistanceThresh = def_centerDistanceThresh;
float opt_radiusDifferenceThresh = def_radiusDifferenceThresh;
bool opt_displayCanny = false;
for (int i = 1; i < argc; i++) {
std::string argName(argv[i]);
if (argName == "--input" && i + 1 < argc) {
opt_input = std::string(argv[i + 1]);
i++;
}
#ifdef VISP_HAVE_NLOHMANN_JSON
else if (argName == "--config" && i + 1 < argc) {
opt_jsonFilePath = std::string(argv[i + 1]);
i++;
}
#endif
else if (argName == "--nb-circles" && i + 1 < argc) {
opt_nbCirclesToDetect = atoi(argv[i + 1]);
i++;
}
else if (argName == "--gaussian-kernel" && i + 1 < argc) {
opt_gaussianKernelSize = atoi(argv[i + 1]);
i++;
}
else if (argName == "--gaussian-sigma" && i + 1 < argc) {
opt_gaussianSigma = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (argName == "--sobel-kernel" && i + 1 < argc) {
opt_sobelKernelSize = atoi(argv[i + 1]);
i++;
}
else if (argName == "--canny-thresh" && i + 2 < argc) {
opt_lowerCannyThresh = static_cast<float>(atof(argv[i + 1]));
opt_upperCannyThresh = static_cast<float>(atof(argv[i + 2]));
i += 2;
}
else if (argName == "--edge-filter" && i + 1 < argc) {
opt_nbEdgeFilteringIter = atoi(argv[i + 1]);
i++;
}
else if (argName == "--dilatation-repet" && i + 1 < argc) {
opt_dilatationRepet = atoi(argv[i + 1]);
i++;
}
else if (argName == "--radius-limits" && i + 2 < argc) {
opt_minRadius = atoi(argv[i + 1]);
opt_maxRadius = atoi(argv[i + 2]);
i += 2;
}
else if (argName == "--center-thresh" && i + 1 < argc) {
opt_centerThresh = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (argName == "--center-xlim" && i + 2 < argc) {
opt_centerXlimits = std::pair<int, int>(atoi(argv[i + 1]), atoi(argv[i + 2]));
i += 2;
}
else if (argName == "--center-ylim" && i + 2 < argc) {
opt_centerYlimits = std::pair<int, int>(atoi(argv[i + 1]), atoi(argv[i + 2]));
i += 2;
}
else if (argName == "--radius-thresh" && i + 1 < argc) {
opt_radiusThreshRatio = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (argName == "--circle-perfectness" && i + 1 < argc) {
opt_circlePerfectness = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (argName == "--merging-thresh" && i + 2 < argc) {
opt_centerDistanceThresh = static_cast<float>(atof(argv[i + 1]));
opt_radiusDifferenceThresh = static_cast<float>(atof(argv[i + 2]));
i += 2;
}
else if (argName == "--display-edge-map") {
opt_displayCanny = true;
}
else if (argName == "--help" || argName == "-h") {
std::cout << "NAME" << std::endl;
std::cout << "\t" << argv[0] << " Test program for the home-made Hough Circle Detection algorithm" << std::endl
<< std::endl;
std::cout << "SYNOPSIS" << std::endl;
std::cout << "\t" << argv[0]
<< "\t [--input " << getAvailableTypeInputImage() << "]" << std::endl
#ifdef VISP_HAVE_NLOHMANN_JSON
<< "\t [--config <path/to/json/file>] (default: " << (def_jsonFilePath.empty() ? "unused" : def_jsonFilePath) << ")" << std::endl
#endif
<< "\t [--nb-circles <number-circles-to-detect>] (default: " << def_nbCirclesToDetect << ")" << std::endl
<< "\t [--gaussian-kernel <kernel-size>] (default: " << def_gaussianKernelSize << ")" << std::endl
<< "\t [--gaussian-sigma <stddev>] (default: " << def_gaussianSigma << ")" << std::endl
<< "\t [--sobel-kernel <kernel-size>] (default: " << def_sobelKernelSize << ")" << std::endl
<< "\t [--canny-thresh <lower-canny-thresh upper-canny-thresh>] (default: " << def_lowerCannyThresh << " ; " << def_upperCannyThresh << ")" << std::endl
<< "\t [--edge-filter <nb-iter>] (default: " << def_nbEdgeFilteringIter << ")" << std::endl
<< "\t [--radius-limits <radius-min> <radius-max>] (default: min = " << def_minRadius << ", max = " << def_maxRadius << ")" << std::endl
<< "\t [--dilatation-repet <nb-repetitions>] (default: " << def_dilatationRepet << ")" << std::endl
<< "\t [--center-thresh <center-detection-threshold>] (default: " << (def_centerThresh < 0 ? "auto" : std::to_string(def_centerThresh)) << ")" << std::endl
<< "\t [--center-xlim <center-horizontal-min center-horizontal-max>] (default: " << def_centerXlimits.first << " , " << def_centerXlimits.second << ")" << std::endl
<< "\t [--center-ylim <center-vertical-min center-vertical-max>] (default: " << def_centerYlimits.first << " , " << def_centerYlimits.second << ")" << std::endl
<< "\t [--radius-thresh <radius-detection-threshold>] (default: " << (def_radiusThreshRatio < 0 ? "auto" : std::to_string(def_radiusThreshRatio)) << ")" << std::endl
<< "\t [--circle-perfectness <circle-perfectness-threshold>] (default: " << def_radiusThreshRatio << ")" << std::endl
<< "\t [--merging-thresh <center-distance-thresh> <radius-difference-thresh>] (default: centers distance threshold = " << def_centerDistanceThresh << ", radius difference threshold = " << def_radiusDifferenceThresh << ")" << std::endl
<< "\t [--display-edge-map]" << std::endl
<< "\t [--help, -h]" << std::endl
<< std::endl;
std::cout << "DESCRIPTION" << std::endl
<< "\t--input" << std::endl
<< "\t\tPermit to choose the type of input of the Hough Circle Algorithm" << std::endl
<< "\t\tDefault: " << def_input << std::endl
<< std::endl
#ifdef VISP_HAVE_NLOHMANN_JSON
<< "\t--config" << std::endl
<< "\t\tPermit to configure the Hough Circle Algorithm using a JSON file." << std::endl
<< "\t\tDefault: " << (def_jsonFilePath.empty() ? "unused" : def_jsonFilePath) << std::endl
<< std::endl
#endif
<< "\t--nb-circles" << std::endl
<< "\t\tPermit to choose the number of circles we want to detect in the image" << std::endl
<< "\t\tThe results will be the circles having the greatest number of votes." << std::endl
<< "\t\tDefault: " << def_nbCirclesToDetect << std::endl
<< std::endl
<< "\t--gaussian-kernel" << std::endl
<< "\t\tPermit to set the size of the Gaussian filter used to smooth the input image and compute its gradients." << std::endl
<< "\t\tMust be an odd value." << std::endl
<< "\t\tDefault: " << def_gaussianKernelSize << std::endl
<< std::endl
<< "\t--gaussian-sigma" << std::endl
<< "\t\tPermit to set the standard deviation of the Gaussian filter." << std::endl
<< "\t\tMust be a positive value." << std::endl
<< "\t\tDefault: " << def_gaussianSigma << std::endl
<< std::endl
<< "\t--canny-thresh" << std::endl
<< "\t\tPermit to set the lower and upper thresholds of the Canny edge detector." << std::endl
<< "\t\tIf a value is negative, it will be automatically computed." << std::endl
<< "\t\tDefault: " << def_upperCannyThresh << std::endl
<< std::endl
<< "\t--edge-filter" << std::endl
<< "\t\tPermit to set the number of iteration of 8-neighbor filter iterations of the result of the Canny edge detector." << std::endl
<< "\t\tIf negative, no filtering is performed." << std::endl
<< "\t\tDefault: " << def_nbEdgeFilteringIter << std::endl
<< std::endl
<< "\t--radius-limits" << std::endl
<< "\t\tPermit to set the minimum and maximum radii of the circles we are looking for." << std::endl
<< "\t\tDefault: min = " << def_minRadius << ", max = " << def_maxRadius << std::endl
<< std::endl
<< "\t--dilatation-repet" << std::endl
<< "\t\tPermit to set the number of iterations of the dilatation operation used to detect the maxima of the centers votes." << std::endl
<< "\t\tMinimum tolerated value is 1." << std::endl
<< "\t\tDefault: " << def_dilatationRepet << std::endl
<< std::endl
<< "\t--center-thresh" << std::endl
<< "\t\tPermit to set the minimum number of votes a point must reach to be considered as a center candidate." << std::endl
<< "\t\tIf the input is a real image, must be a positive value." << std::endl
<< "\t\tOtherwise, if the input is a synthetic image and the value is negative, a fine-tuned value will be used." << std::endl
<< "\t\tDefault: " << (def_centerThresh < 0 ? "auto" : std::to_string(def_centerThresh)) << std::endl
<< std::endl
<< "\t--center-xlim" << std::endl
<< "\t\tPermit to set the minimum and maximum horizontal position to be considered as a center candidate." << std::endl
<< "\t\tThe search area is limited to [-maxRadius; +image.width + maxRadius]." << std::endl
<< "\t\tDefault: " << def_centerXlimits.first << " , " << def_centerXlimits.second << std::endl
<< std::endl
<< "\t--center-ylim" << std::endl
<< "\t\tPermit to set the minimum and maximum vertical position to be considered as a center candidate." << std::endl
<< "\t\tThe search area is limited to [-maxRadius; +image.height + maxRadius]." << std::endl
<< "\t\tDefault: " << def_centerYlimits.first << " , " << def_centerYlimits.second << std::endl
<< std::endl
<< "\t--radius-thresh" << std::endl
<< "\t\tPermit to to set the minimum number of votes per radian a radius must reach to be considered as a circle candidate a given pair (center candidate, radius candidate)." << std::endl
<< "\t\tDefault: " << (def_radiusThreshRatio < 0 ? "auto" : std::to_string(def_radiusThreshRatio)) << std::endl
<< std::endl
<< "\t--circle-perfectness" << std::endl
<< "\t\tPermit to set the set the circle perfectness threshold." << std::endl
<< "\t\tThis parameter is used during the radius candidates computation." << std::endl
<< "\t\tThe scalar product radius RC_ij . gradient(Ep_j) >= m_circlePerfectness * || RC_ij || * || gradient(Ep_j) || to add a vote for the radius RC_ij." << std::endl
<< "\t\tDefault: " << def_circlePerfectness << std::endl
<< std::endl
<< "\t--merging-thresh" << std::endl
<< "\t\tPermit to set the thresholds used during the merging stage of the algorithm." << std::endl
<< "\t\tThe center distance threshold indicates the maximum distance the centers can be in order to be merged." << std::endl
<< "\t\tThe radius difference threshold indicates the maximum absolute difference between the two circle candidates in order to be merged." << std::endl
<< "\t\tTwo circle candidates must met these two conditions in order to be merged together." << std::endl
<< "\t\tDefault: centers distance threshold = " << def_centerDistanceThresh << ", radius difference threshold = " << def_radiusDifferenceThresh << std::endl
<< "\t--display-edge-map" << std::endl
<< "\t\tPermit to display the edge map used to detect the circles" << std::endl
<< "\t\tDefault: off" << std::endl
<< std::endl;
return EXIT_SUCCESS;
}
}
if (opt_centerThresh < 0 && opt_jsonFilePath.empty()) {
// The user asked to use the parameter value that has been fine-tuned
TypeInputImage inputType = typeInputImageFromString(opt_input);
switch (inputType) {
case TypeInputImage::FULL_DISKS:
#ifdef HAVE_OPENCV_IMGPROC
opt_centerThresh = 100.;
#else
opt_centerThresh = 75.;
#endif
break;
case TypeInputImage::HALF_DISKS:
#ifdef HAVE_OPENCV_IMGPROC
opt_centerThresh = 50.;
#else
opt_centerThresh = 25.;
#endif
break;
case TypeInputImage::QUARTER_DISKS:
#ifdef HAVE_OPENCV_IMGPROC
opt_centerThresh = 25.;
#else
opt_centerThresh = 15.;
#endif
break;
default:
throw(vpException(vpException::badValue, "Missing center threshold value to use with actual pictures as input. See the help for more information."));
}
}
if (opt_radiusThreshRatio < 0 && opt_jsonFilePath.empty()) {
// The user asked to use the parameter value that has been fine-tuned
TypeInputImage inputType = typeInputImageFromString(opt_input);
switch (inputType) {
case TypeInputImage::FULL_DISKS:
#ifdef HAVE_OPENCV_IMGPROC
opt_radiusThreshRatio = 5.;
#else
opt_radiusThreshRatio = 1.;
#endif
break;
case TypeInputImage::HALF_DISKS:
opt_radiusThreshRatio = 2.;
break;
case TypeInputImage::QUARTER_DISKS:
opt_radiusThreshRatio = 1.;
break;
default:
throw(vpException(vpException::badValue, "Missing radius threshold value to use with actual pictures as input. See the help for more information."));
}
}
//! [Algo params]
vpCircleHoughTransform::vpCircleHoughTransformParameters
algoParams(opt_gaussianKernelSize
, opt_gaussianSigma
, opt_sobelKernelSize
, opt_lowerCannyThresh
, opt_upperCannyThresh
, opt_nbEdgeFilteringIter
, opt_centerXlimits
, opt_centerYlimits
, opt_minRadius
, opt_maxRadius
, opt_dilatationRepet
, opt_centerThresh
, opt_radiusThreshRatio
, opt_circlePerfectness
, opt_centerDistanceThresh
, opt_radiusDifferenceThresh
);
//! [Algo params]
//! [Algo init]
vpCircleHoughTransform detector;
if (opt_jsonFilePath.empty()) {
std::cout << "Initializing detector from the program arguments [...]" << std::endl;
detector.init(algoParams);
}
else {
#ifdef VISP_HAVE_NLOHMANN_JSON
std::cout << "Initializing detector from JSON file \"" << opt_jsonFilePath << "\", some of the program arguments will be ignored [...]" << std::endl;
detector.initFromJSON(opt_jsonFilePath);
#else
throw(vpException(vpException::functionNotImplementedError, "You must install nlohmann JSON library to use this feature, see https://visp-doc.inria.fr/doxygen/visp-daily/supported-third-parties.html#soft_tool_json for more information."));
#endif
}
//! [Algo init]
std::cout << detector;
vpImage<unsigned char> I_src;
TypeInputImage inputType = typeInputImageFromString(opt_input);
if (inputType == USER_IMG) {
//! [Manage video]
if (opt_input.find("%") != std::string::npos) {
// The user wants to read a sequence of images from different files
bool hasToContinue = true;
vpVideoReader g;
g.setFileName(opt_input);
g.open(I_src);
while (!g.end() && hasToContinue) {
g.acquire(I_src);
hasToContinue = test_detection(I_src, detector, opt_nbCirclesToDetect, false, opt_displayCanny);
vpTime::wait(40);
}
}
//! [Manage video]
else {
//! [Manage single image]
// Check if opt_input exists
if (!vpIoTools::checkFilename(opt_input)) {
throw(vpException(vpException::ioError, "Input file \"" + opt_input + "\" does not exist !"));
}
// Read the image and perform detection on it
vpImageIo::read(I_src, opt_input);
test_detection(I_src, detector, opt_nbCirclesToDetect, true, opt_displayCanny);
//! [Manage single image]
}
}
else {
//! [Manage synthetic image]
I_src = generateImage(inputType);
test_detection(I_src, detector, opt_nbCirclesToDetect, true, opt_displayCanny);
//! [Manage synthetic image]
}
return EXIT_SUCCESS;
}
#else
int main()
{
std::cout << "This tutorial needs to be build at least with cxx 11 standard!" << std::endl;
return EXIT_SUCCESS;
}
#endif
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