官方提供sample:
#include <opencv2/core.hpp> #include <opencv2/imgproc.hpp> #include <opencv2/highgui.hpp> #include <opencv2/features2d.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 + "]"; } if (pAct.filterByCircularity) { 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; } if (pAct.filterByConvexity) { 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[]) { Mat img = imread("F:/1.jpg", IMREAD_COLOR); if (img.empty()) { return 1; } threshold(img, img, 150, 255, THRESH_BINARY); imshow("threshold", img); waitKey(0); SimpleBlobDetector::Params pDefaultBLOB; // This is default parameters for SimpleBlobDetector pDefaultBLOB.thresholdStep = 20; pDefaultBLOB.minThreshold = 0; pDefaultBLOB.maxThreshold = 220; pDefaultBLOB.filterByColor = false; pDefaultBLOB.filterByArea = false; pDefaultBLOB.minArea = 1; pDefaultBLOB.maxArea = 5000; pDefaultBLOB.filterByCircularity = false; pDefaultBLOB.filterByInertia = false; pDefaultBLOB.filterByConvexity = false; // 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 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 = 9999; itBLOB = pBLOB.begin(); vector<double> desMethCmp; Ptr<Feature2D> b; 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 { int s = cv::getTickCount(); // 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()) { Ptr<SimpleBlobDetector> sbd = b.dynamicCast<SimpleBlobDetector>(); 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); int e = cv::getTickCount(); std::cout << "SimpleBlobDetector cost time: " << static_cast<double>(e - s) / cv::getTickFrequency() * 1000 << "ms" << std::endl; imshow(*itDesc + label, result); imshow("Original", img); waitKey(); } catch (const Exception& e) { cout << "Feature : " << *itDesc << "\n"; cout << e.msg << endl; } } return 0; }
网上提供:
mvk-nodes/blobdetect_test.cpp at master · mangosroom/mvk-nodes (github.com)
OpenCV中drawContours用法_牧羊女说的博客-CSDN博客_drawcontours