OpenCV  5.0.0-pre
Open Source Computer Vision
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samples/cpp/snippets/detect_blob.cpp

An example using the BLOB to detect and filter region.

#include <opencv2/core.hpp>
#include <vector>
#include <map>
#include <iostream>
using namespace std;
using namespace cv;
static void help(char** argv)
{
cout << "\n This program demonstrates how to use BLOB to detect and filter region \n"
<< "Usage: \n"
<< argv[0]
<< " <image1(detect_blob.png as default)>\n"
<< "Press a key when image window is active to change descriptor";
}
static String Legende(SimpleBlobDetector::Params &pAct)
{
String s = "";
if (pAct.filterByArea)
{
String inf = static_cast<const ostringstream&>(ostringstream() << pAct.minArea).str();
String sup = static_cast<const ostringstream&>(ostringstream() << pAct.maxArea).str();
s = " Area range [" + inf + " to " + sup + "]";
}
{
String inf = static_cast<const ostringstream&>(ostringstream() << pAct.minCircularity).str();
String sup = static_cast<const ostringstream&>(ostringstream() << pAct.maxCircularity).str();
if (s.length() == 0)
s = " Circularity range [" + inf + " to " + sup + "]";
else
s += " AND Circularity range [" + inf + " to " + sup + "]";
}
if (pAct.filterByColor)
{
String inf = static_cast<const ostringstream&>(ostringstream() << (int)pAct.blobColor).str();
if (s.length() == 0)
s = " Blob color " + inf;
else
s += " AND Blob color " + inf;
}
{
String inf = static_cast<const ostringstream&>(ostringstream() << pAct.minConvexity).str();
String sup = static_cast<const ostringstream&>(ostringstream() << pAct.maxConvexity).str();
if (s.length() == 0)
s = " Convexity range[" + inf + " to " + sup + "]";
else
s += " AND Convexity range[" + inf + " to " + sup + "]";
}
if (pAct.filterByInertia)
{
String inf = static_cast<const ostringstream&>(ostringstream() << pAct.minInertiaRatio).str();
String sup = static_cast<const ostringstream&>(ostringstream() << pAct.maxInertiaRatio).str();
if (s.length() == 0)
s = " Inertia ratio range [" + inf + " to " + sup + "]";
else
s += " AND Inertia ratio range [" + inf + " to " + sup + "]";
}
return s;
}
int main(int argc, char *argv[])
{
String fileName;
cv::CommandLineParser parser(argc, argv, "{@input |detect_blob.png| }{h help | | }");
if (parser.has("h"))
{
help(argv);
return 0;
}
fileName = parser.get<string>("@input");
Mat img = imread(samples::findFile(fileName), IMREAD_COLOR);
if (img.empty())
{
cout << "Image " << fileName << " is empty or cannot be found\n";
return 1;
}
// This is default parameters for SimpleBlobDetector
pDefaultBLOB.thresholdStep = 10;
pDefaultBLOB.minThreshold = 10;
pDefaultBLOB.maxThreshold = 220;
pDefaultBLOB.minRepeatability = 2;
pDefaultBLOB.minDistBetweenBlobs = 10;
pDefaultBLOB.filterByColor = false;
pDefaultBLOB.blobColor = 0;
pDefaultBLOB.filterByArea = false;
pDefaultBLOB.minArea = 25;
pDefaultBLOB.maxArea = 5000;
pDefaultBLOB.filterByCircularity = false;
pDefaultBLOB.minCircularity = 0.9f;
pDefaultBLOB.maxCircularity = (float)1e37;
pDefaultBLOB.filterByInertia = false;
pDefaultBLOB.minInertiaRatio = 0.1f;
pDefaultBLOB.maxInertiaRatio = (float)1e37;
pDefaultBLOB.filterByConvexity = false;
pDefaultBLOB.minConvexity = 0.95f;
pDefaultBLOB.maxConvexity = (float)1e37;
// Descriptor array for BLOB
vector<String> typeDesc;
// Param array for BLOB
vector<SimpleBlobDetector::Params> pBLOB;
vector<SimpleBlobDetector::Params>::iterator itBLOB;
// Color palette
vector< Vec3b > palette;
for (int i = 0; i<65536; i++)
{
uchar c1 = (uchar)rand();
uchar c2 = (uchar)rand();
uchar c3 = (uchar)rand();
palette.push_back(Vec3b(c1, c2, c3));
}
help(argv);
// These descriptors are going to be detecting and computing BLOBS with 6 different params
// Param for first BLOB detector we want all
typeDesc.push_back("BLOB"); // see http://docs.opencv.org/5.x/d0/d7a/classcv_1_1SimpleBlobDetector.html
pBLOB.push_back(pDefaultBLOB);
pBLOB.back().filterByArea = true;
pBLOB.back().minArea = 1;
pBLOB.back().maxArea = float(img.rows*img.cols);
// Param for second BLOB detector we want area between 500 and 2900 pixels
typeDesc.push_back("BLOB");
pBLOB.push_back(pDefaultBLOB);
pBLOB.back().filterByArea = true;
pBLOB.back().minArea = 500;
pBLOB.back().maxArea = 2900;
// Param for third BLOB detector we want only circular object
typeDesc.push_back("BLOB");
pBLOB.push_back(pDefaultBLOB);
pBLOB.back().filterByCircularity = true;
// Param for Fourth BLOB detector we want ratio inertia
typeDesc.push_back("BLOB");
pBLOB.push_back(pDefaultBLOB);
pBLOB.back().filterByInertia = true;
pBLOB.back().minInertiaRatio = 0;
pBLOB.back().maxInertiaRatio = (float)0.2;
// Param for fifth BLOB detector we want ratio inertia
typeDesc.push_back("BLOB");
pBLOB.push_back(pDefaultBLOB);
pBLOB.back().filterByConvexity = true;
pBLOB.back().minConvexity = 0.;
pBLOB.back().maxConvexity = (float)0.9;
// Param for six BLOB detector we want blob with gravity center color equal to 0
typeDesc.push_back("BLOB");
pBLOB.push_back(pDefaultBLOB);
pBLOB.back().filterByColor = true;
pBLOB.back().blobColor = 0;
itBLOB = pBLOB.begin();
vector<double> desMethCmp;
String label;
// Descriptor loop
vector<String>::iterator itDesc;
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); ++itDesc)
{
vector<KeyPoint> keyImg1;
if (*itDesc == "BLOB")
{
b = SimpleBlobDetector::create(*itBLOB);
label = Legende(*itBLOB);
++itBLOB;
}
try
{
// We can detect keypoint with detect method
vector<KeyPoint> keyImg;
vector<Rect> zone;
vector<vector <Point> > region;
Mat desc, result(img.rows, img.cols, CV_8UC3);
if (b.dynamicCast<SimpleBlobDetector>().get())
{
sbd->detect(img, keyImg, Mat());
drawKeypoints(img, keyImg, result);
int i = 0;
for (vector<KeyPoint>::iterator k = keyImg.begin(); k != keyImg.end(); ++k, ++i)
circle(result, k->pt, (int)k->size, palette[i % 65536]);
}
namedWindow(*itDesc + label, WINDOW_AUTOSIZE);
imshow(*itDesc + label, result);
imshow("Original", img);
}
catch (const Exception& e)
{
cout << "Feature : " << *itDesc << "\n";
cout << e.msg << endl;
}
}
return 0;
}
Designed for command line parsing.
Definition utility.hpp:890
Class passed to an error.
Definition exception.hpp:86
std::string msg
the formatted error message
Definition exception.hpp:106
virtual void detect(InputArray image, std::vector< KeyPoint > &keypoints, InputArray mask=noArray())
Detects keypoints in an image (first variant) or image set (second variant).
n-dimensional dense array class
Definition mat.hpp:950
Class for extracting blobs from an image. :
Definition features.hpp:622
Template class for short numerical vectors, a partial case of Matx.
Definition matx.hpp:379
std::string String
Definition cvstd.hpp:151
std::shared_ptr< _Tp > Ptr
Definition cvstd_wrapper.hpp:23
unsigned char uchar
Definition interface.h:51
#define CV_8UC3
Definition interface.h:101
@ circle
Definition gr_skig.hpp:62
void drawKeypoints(InputArray image, const std::vector< KeyPoint > &keypoints, InputOutputArray outImage, const Scalar &color=Scalar::all(-1), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT)
Draws keypoints.
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
int waitKey(int delay=0)
Waits for a pressed key.
void namedWindow(const String &winname, int flags=WINDOW_AUTOSIZE)
Creates a window.
CV_EXPORTS_W Mat imread(const String &filename, int flags=IMREAD_COLOR_BGR)
Loads an image from a file.
int main(int argc, char *argv[])
Definition highgui_qt.cpp:3
Definition core.hpp:107
Definition features.hpp:625
float maxCircularity
Definition features.hpp:640
uchar blobColor
Definition features.hpp:634
bool filterByCircularity
Definition features.hpp:639
float maxArea
Definition features.hpp:637
size_t minRepeatability
Definition features.hpp:630
bool filterByColor
Definition features.hpp:633
float minArea
Definition features.hpp:637
float minThreshold
Definition features.hpp:628
float minInertiaRatio
Definition features.hpp:643
float thresholdStep
Definition features.hpp:627
bool filterByArea
Definition features.hpp:636
float minConvexity
Definition features.hpp:646
float minCircularity
Definition features.hpp:640
float maxInertiaRatio
Definition features.hpp:643
float maxConvexity
Definition features.hpp:646
float maxThreshold
Definition features.hpp:629
bool filterByConvexity
Definition features.hpp:645
bool filterByInertia
Definition features.hpp:642
float minDistBetweenBlobs
Definition features.hpp:631